From 762c32be76814aa2d2257f0bea402fd186de59c3 Mon Sep 17 00:00:00 2001
From: mmarchegiani <matmarcheg@gmail.com>
Date: Thu, 16 Mar 2023 17:27:58 +0100
Subject: [PATCH 01/24] Building DataMC class

---
 pocket_coffea/utils/plot_utils.py | 949 +++---------------------------
 1 file changed, 67 insertions(+), 882 deletions(-)

diff --git a/pocket_coffea/utils/plot_utils.py b/pocket_coffea/utils/plot_utils.py
index 09d688ae..434035c2 100644
--- a/pocket_coffea/utils/plot_utils.py
+++ b/pocket_coffea/utils/plot_utils.py
@@ -14,887 +14,72 @@ import mplhep as hep
 
 from ..parameters.lumi import lumi, femtobarn
 
-fontsize = 22
-fontsize_legend_ratio = 12
-plt.style.use([hep.style.ROOT, {'font.size': fontsize}])
-plt.rcParams.update({'font.size': fontsize})
-
-opts_figure = {
-    "total" : {
-        'figsize' : (12,12),
-        'gridspec_kw' : {"height_ratios": (3, 1)},
-        'sharex' : True,
-    },
-    "partial" : {
-        'figsize' : (12,15),
-        'gridspec_kw' : {"height_ratios": (3, 1)},
-        'sharex' : True,
-    },
-}
-
-opts_data = {
-    'linestyle': 'solid',
-    'linewidth': 0,
-    'marker': '.',
-    'markersize': 5.0,
-    'color': 'black',
-    'elinewidth': 1,
-    'label': 'Data',
-}
-
-hatch_density = 4
-opts_unc = {
-    "total" : {
-        "step": "post",
-        "color": (0, 0, 0, 0.4),
-        "facecolor": (0, 0, 0, 0.0),
-        "linewidth": 0,
-        "hatch": '/' * hatch_density,
-        "zorder": 2,
-    },
-    'Up': {
-        'linestyle': 'dashed',
-        'linewidth': 1,
-        'marker': '.',
-        'markersize': 1.0,
-        #'color': 'red',
-        'elinewidth': 1,
-    },
-    'Down': {
-        'linestyle': 'dotted',
-        'linewidth': 1,
-        'marker': '.',
-        'markersize': 1.0,
-        #'color': 'red',
-        'elinewidth': 1,
-    },
-}
-
-opts_unc_total = {
-    'Up': {
-        'linestyle': 'dashed',
-        'linewidth': 1,
-        'marker': '.',
-        'markersize': 1.0,
-        'color': 'gray',
-        'elinewidth': 2,
-    },
-    'Down': {
-        'linestyle': 'dotted',
-        'linewidth': 1,
-        'marker': '.',
-        'markersize': 1.0,
-        'color': 'gray',
-        'elinewidth': 2,
-    },
-}
-
-opts_sf = {
-    'nominal': {
-        'linestyle': 'solid',
-        'linewidth': 1,
-        'marker': '.',
-        'markersize': 1.0,
-        'color': 'red',
-        'elinewidth': 1,
-    },
-    'Up': {
-        'linestyle': 'dashed',
-        'linewidth': 1,
-        'marker': '.',
-        'markersize': 1.0,
-        'color': 'red',
-        'elinewidth': 1,
-    },
-    'Down': {
-        'linestyle': 'dotted',
-        'linewidth': 1,
-        'marker': '.',
-        'markersize': 1.0,
-        'color': 'red',
-        'elinewidth': 1,
-    },
-}
-
-opts_errorbar = {
-    'nominal': {'linestyle': 'solid'},
-    'Up': {'linestyle': 'dashed'},
-    'Down': {'linestyle': 'dotted'},
-}
-
-# Flavor ordering by stats, dependent on plot scale
-flavors_order = {
-    'linear': ['l', 'bb', 'cc', 'b', 'c'],
-    'log': ['c', 'b', 'cc', 'bb', 'l'],
-}
-# Color scheme for l, c+cc, b+bb
-colors_bb = ['blue', 'magenta', 'cyan']
-colors_cc = ['blue', 'cyan', 'magenta']
-colors_5f = {
-    'l': (0.51, 0.79, 1.0),  # blue
-    'c': (1.0, 0.4, 0.4),  # red
-    'b': (1.0, 0.71, 0.24),  # orange
-    'cc': (0.96, 0.88, 0.40),  # yellow
-    'bb': (0.51, 0.91, 0.51),  # green
-}
-
-colors_tthbb = {
-    'ttHTobb': 'pink',
-    'TTTo2L2Nu': (0.51, 0.79, 1.0),  # blue
-    'TTToSemiLeptonic': (1.0, 0.71, 0.24),  # orange
-    'SingleTop' : (1.0, 0.4, 0.4), #red
-    'ST' : (1.0, 0.4, 0.4), #red
-    'WJetsToLNu_HT' : '#cc99ff', #violet
-}
-
-
-def slice_accumulator(accumulator, entrystart, entrystop):
-    '''Returns an accumulator containing only a reduced set of histograms, i.e. those between the positions `entrystart` and `entrystop`.'''
-    _accumulator = dict([(key, value) for key, value in accumulator.items()])
-    _accumulator['variables'] = dict(
-        [(key, value) for key, value in accumulator['variables'].items()][
-            entrystart:entrystop
-        ]
-    )
-    return _accumulator
-
-
-def dense_dim(h):
-    '''Returns the number of dense axes of a histogram.'''
-    dense_dim = 0
-    if type(h) == dict:
-        h = h[list(h.keys())[0]]
-    for ax in h.axes:
-        if not type(ax) in [hist.axis.StrCategory, hist.axis.IntCategory]:
-            dense_dim += 1
-    return dense_dim
-
-
-def dense_axes(h):
-    '''Returns the list of dense axes of a histogram.'''
-    dense_axes = []
-    if type(h) == dict:
-        h = h[list(h.keys())[0]]
-    for ax in h.axes:
-        if not type(ax) in [hist.axis.StrCategory, hist.axis.IntCategory]:
-            dense_axes.append(ax)
-    return dense_axes
-
-
-def stack_sum(stack):
-    '''Returns the sum histogram of a stack (`hist.stack.Stack`) of histograms.'''
-    if len(stack) == 1:
-        return stack[0]
-    else:
-        htot = stack[0]
-        for h in stack[1:]:
-            htot = htot + h
-        return htot
-
-
-def get_axis_items(h, axis_name):
-    axis = h.axes[axis_name]
-    return list(axis.value(range(axis.size)))
-
-
-def get_index(h, edges):
-    indices = []
-
-    for edge in edges:
-        indices.append(np.where(np.isclose(h.axes[-1].edges, edge, atol=0.01))[0][0])
-    return indices
-
-
-def rebin_histogram(h, index):
-    values = [
-        np.sum(h.values()[start:stop]) for start, stop in zip(index[:-1], index[1:])
-    ]
-    variances = [
-        np.sum(h.variances()[start:stop]) for start, stop in zip(index[:-1], index[1:])
-    ]
-    edges = [h.axes[-1].edges[i] for i in index]
-    nh = hist.new.Var(edges, name=h.axes[-1].name, label=h.axes[-1].label).Weight()
-    nh[...] = np.stack([values, variances], axis=-1)
-
-    return nh
-
-
-def rebin_stack(stack, index):
-    histos_rebinned = {}
-    for i, h in enumerate(stack):
-        # print(type(rebin(h, index)))
-        histos_rebinned[h.name] = rebin_histogram(h, index)
-
-    return hist.Stack.from_dict(histos_rebinned)
-
-
-def rebin(h, edges):
-    index = get_index(h, edges)
-    if type(h) == hist.stack.Stack:
-        return rebin_stack(h, index)
-    elif type(h) == hist.hist.Hist:
-        return rebin_histogram(h, index)
-
-
-def get_data_mc_ratio(h1, h2):
-    if type(h1) == hist.Stack:
-        h1 = stack_sum(h1)
-    if type(h2) == hist.Stack:
-        h2 = stack_sum(h2)
-    num = h1.values()
-    den = h2.values()
-    ratio = num / den
-    #ratio[ratio == 0] = np.nan
-    #ratio[np.isinf(ratio)] = np.nan
-    unc = np.sqrt(num) / den
-    unc[np.isnan(unc)] = np.inf
-
-    return ratio, unc
-
-
-def get_systematic_uncertainty(
-    stack_mc, variations, mcstat=True, stat_only=False, edges=None
-):
-    '''This function computes the total systematic uncertainty on the MC stack, by summing in quadrature the systematic uncertainties of the single MC samples.
-    For each MC sample, the systematic uncertainty is computed by summing in quadrature all the systematic uncertainties.
-    The asymmetric error band is constructed by summing in quadrature uncertainties that are moving the nominal value in the same direction, i.e. the total "up" uncertainty is obtained by summing in quadrature all the systematic effects that are pulling the nominal value up.'''
-    if stack_mc[0].ndim != 2:
-        raise Exception(
-            "Only histograms with a dense axis and the variation axis are allowed as input."
-        )
-    if type(variations) == str:
-        variations = [variations]
-
-    systematics = [s.split("Up")[0] for s in variations if 'Up' in s]
-
-    nom_template = stack_mc[0][{'variation': 'nominal'}]
-    if edges:
-        nom_template = rebin(nom_template, edges)
-
-    syst_err2_up_dict = {}
-    syst_err2_down_dict = {}
-    if not stat_only:
-        syst_err2_up_dict = {syst : 0.0 for syst in systematics}
-        syst_err2_down_dict = {syst : 0.0 for syst in systematics}
-        #syst_err2_tot_up = np.zeros_like(nom_template.values())
-        #syst_err2_tot_down = np.zeros_like(nom_template.values())
-    if mcstat:
-        syst_err2_up_dict.update({"mcstat" : 0.0})
-        syst_err2_down_dict.update({"mcstat" : 0.0})
-    for h in stack_mc:
-        sample = h.name
-        nom = h[{'variation': 'nominal'}]
-        if edges:
-            nom = rebin(nom, edges)
-        syst_err2_up = np.zeros_like(nom.values())
-        syst_err2_down = np.zeros_like(nom.values())
-        if not stat_only:
-            for syst in systematics:
-                systUp = f"{syst}Up"
-                systDown = f"{syst}Down"
-
-                # Compute the uncertainties corresponding to the up/down variations
-                varUp = h[{'variation': systUp}]
-                varDown = h[{'variation': systDown}]
-                if edges:
-                    varUp = rebin(varUp, edges)
-                    varDown = rebin(varDown, edges)
-                errUp = varUp.values() - nom.values()
-                errDown = varDown.values() - nom.values()
-
-                # Compute the flags to check which of the two variations (up and down) are pushing the nominal value up and down
-                up_is_up = errUp > 0
-                down_is_down = errDown < 0
-                # Compute the flag to check if the uncertainty is one-sided, i.e. when both variations are up or down
-                is_onesided = (up_is_up ^ down_is_down)
-
-                # Sum in quadrature of the systematic uncertainties
-                # N.B.: valid only for double sided uncertainties
-                syst_err2_up_twosided = np.where(up_is_up, errUp**2, errDown**2)
-                syst_err2_down_twosided = np.where(up_is_up, errDown**2, errUp**2)
-                syst_err2_max = np.maximum(syst_err2_up_twosided, syst_err2_down_twosided)
-                syst_err2_up_onesided = np.where(is_onesided & up_is_up, syst_err2_max, 0)
-                syst_err2_down_onesided = np.where(is_onesided & down_is_down, syst_err2_max, 0)
-                syst_err2_up_combined = np.where(is_onesided, syst_err2_up_onesided, syst_err2_up_twosided)
-                syst_err2_down_combined = np.where(is_onesided, syst_err2_down_onesided, syst_err2_down_twosided)
-
-                syst_err2_up_dict[syst] += syst_err2_up_combined
-                syst_err2_down_dict[syst] += syst_err2_down_combined
-
-        # Add in quadrature the MC statistical uncertainty
-        if mcstat:
-            mcstat_err2 = nom.variances()
-            #syst_err2_up += mcstat_err2
-            #syst_err2_down += mcstat_err2
-            syst_err2_up_dict["mcstat"] += mcstat_err2
-            syst_err2_down_dict["mcstat"] += mcstat_err2
-
-        # Sum in quadrature of the systematic uncertainties for each MC sample
-        #syst_err2_tot_up += syst_err2_up
-        #syst_err2_tot_down += syst_err2_down
-
-    #return np.sqrt(syst_err2_tot_up), np.sqrt(syst_err2_tot_down)
-    return syst_err2_up_dict,  syst_err2_down_dict
-
-
-def plot_uncertainty_band(h_mc_sum, syst_err2_up, syst_err2_down, ax, ratio=False):
-    '''This function computes and plots the uncertainty band as a hashed gray area.
-    To plot the systematic uncertainty in a ratio plot, `ratio` has to be set to True and the uncertainty band will be plotted around 1 in the ratio plot.'''
-    nom = h_mc_sum.values()
-    # Sum in quadrature of the systematic uncertainties for each variation
-    up = nom + np.sqrt(sum(syst_err2_up.values()))
-    down = nom - np.sqrt(sum(syst_err2_down.values()))
-
-    if ratio:
-        # In order to get a consistent uncertainty band, the up/down variations of the ratio are set to 1 where the nominal value is 0
-        up = np.where(nom != 0, up / nom, 1)
-        down = np.where(nom!=0, down / nom, 1)
-
-    unc_band = np.array([down, up])
-
-    ax.fill_between(
-        h_mc_sum.axes[0].edges,
-        np.r_[unc_band[0], unc_band[0, -1]],
-        np.r_[unc_band[1], unc_band[1, -1]],
-        **opts_unc['total'],
-        label="syst. unc.",
-    )
-    if ratio:
-        ax.hlines(1.0, *ak.Array(h_mc_sum.axes[0].edges)[[0,-1]], colors='gray', linestyles='dashed')
-
-def plot_systematic_uncertainty(
-    stack_mc_nominal, syst_err2_up, syst_err2_down, ax, ratio=False, split_systematics=False, only_syst=[], partial_unc_band=False,
-):
-    '''This function plots the asymmetric systematic uncertainty band on top of the MC stack, if `ratio` is set to False.
-    To plot the systematic uncertainty in a ratio plot, `ratio` has to be set to True and the uncertainty band will be plotted around 1 in the ratio plot.'''
-    if (not type(syst_err2_up) == dict) or (not type(syst_err2_down) == dict):
-        raise Exception("`syst_err2_up` and `syst_err2_down` must be dictionaries")
-
-    h_mc_sum = stack_sum(stack_mc_nominal)
-    nom = h_mc_sum.values()
-
-    if only_syst:
-        syst_err2_up_filtered = { syst : unc for syst, unc in syst_err2_up.items() if any(key in syst for key in only_syst)}
-        syst_err2_down_filtered = { syst : unc for syst, unc in syst_err2_down.items() if any(key in syst for key in only_syst)}
-    else:
-        syst_err2_up_filtered = syst_err2_up
-        syst_err2_down_filtered = syst_err2_down
-
-    if not split_systematics:
-        plot_uncertainty_band(h_mc_sum, syst_err2_up_filtered, syst_err2_down_filtered, ax, ratio)
-    else:
-        if syst_err2_up_filtered.keys() != syst_err2_down_filtered.keys():
-            raise Exception("The up and down uncertainties comes from different systematics. `syst_err2_up_filtered` and `syst_err2_down_filtered` must have the same keys.")
-
-        axis_x = h_mc_sum.axes[0]
-        edges_x = axis_x.edges
-        binwidth_x = np.ediff1d(edges_x)
-        x = edges_x[:-1] + 0.5 * binwidth_x
-        xerr = 0.5 * binwidth_x
-
-        if partial_unc_band:
-            # Sum in quadrature of the systematic uncertainties for each variation
-            up_tot = nom + np.sqrt(sum(syst_err2_up_filtered.values()))
-            down_tot = nom - np.sqrt(sum(syst_err2_down_filtered.values()))
-            label = "partial"
-        else:
-            # Sum in quadrature of the systematic uncertainties for each variation
-            up_tot = nom + np.sqrt(sum(syst_err2_up.values()))
-            down_tot = nom - np.sqrt(sum(syst_err2_down.values()))
-            label = "total"
-        if ratio:
-            up_tot = up_tot / nom
-            down_tot = down_tot / nom
-        linesUp_tot = ax.errorbar(x, up_tot, yerr=0, xerr=xerr, label=f"{label}Up", **opts_unc_total['Up'], fmt='none')
-        linesDown_tot = ax.errorbar(x, down_tot, yerr=0, xerr=xerr, label=f"{label}Down", **opts_unc_total['Down'], fmt='none')
-        for lines, var in zip([linesDown_tot, linesUp_tot], ['Down', 'Up']):
-            errorbar_x = lines[-1][0]
-            errorbar_y = lines[-1][1]
-            errorbar_x.set_linestyle(opts_errorbar[var]['linestyle'])
-            errorbar_y.set_linewidth(0)
-
-        color = iter(cm.gist_rainbow(np.linspace(0, 1, len(syst_err2_up_filtered.keys()))))
-        for i, syst in enumerate(syst_err2_up_filtered.keys()):
-            up = nom + np.sqrt(syst_err2_up_filtered[syst])
-            down = nom - np.sqrt(syst_err2_down_filtered[syst])
-            if ratio:
-                up = up / nom
-                down = down / nom
-            c = next(color)
-            linesUp = ax.errorbar(x, up, yerr=0, xerr=xerr, label=f"{syst}Up", **opts_unc['Up'], fmt='none', color=c)
-            linesDown = ax.errorbar(x, down, yerr=0, xerr=xerr, label=f"{syst}Down", **opts_unc['Down'], fmt='none', color=c)
-
-            for lines, var in zip([linesDown, linesUp], ['Down', 'Up']):
-                errorbar_x = lines[-1][0]
-                errorbar_y = lines[-1][1]
-                errorbar_x.set_linestyle(opts_errorbar[var]['linestyle'])
-                errorbar_y.set_linewidth(0)
-        if ratio:
-            ax.hlines(1.0, *ak.Array(edges_x)[[0,-1]], colors='gray', linestyles='dashed')
-            ax.legend(fontsize=fontsize_legend_ratio, ncols=2)
+class DataMC:
+    '''This class handles the plotting of 1D data/MC histograms.'''
+    def __init__(self, h_dict, name, data_key="DATA"):
+        self.h_dict = h_dict
+        self.name = name
+        self.data_key = data_key
+        assert type(h_dict) == dict, "The DataMC object receives a dictionary of hist.Hist objects as argument."
+        self.define_samples()
+        assert self.dense_dim == 1, f"Histograms with dense dimension {self.dense_dim} cannot be plotted. Only 1D histograms are supported."
+        self.load_attributes()
+
+    @property
+    def dense_axes(self):
+        '''Returns the list of dense axes of a histogram.'''
+        dense_axes_dict = {s : [] for s in self.h_dict.keys()}
+
+        for s, h in self.h_dict.items():
+            for ax in h.axes:
+                if not type(ax) in [hist.axis.StrCategory, hist.axis.IntCategory]:
+                    dense_axes_dict[s].append(ax)
+        dense_axes = list(dense_axes_dict.values())
+        assert all(v == dense_axes[0] for v in dense_axes), "Not all the histograms in the dictionary have the same dense dimension."
+        dense_axes = dense_axes[0]
+
+        return dense_axes
+    
+    @property
+    def categorical_axes(self, mc=True):
+        '''Returns the list of categorical axes of a histogram.'''
+        # Since MC and data have different categorical axes, the argument mc needs to specified
+        if mc:
+            d = {s : v for s, v in self.h_dict.items() if s in self.samples_mc}
         else:
-            ax.legend(fontsize=fontsize, ncols=2)
-
-
-def plot_data_mc_hist1D(
-    h,
-    histname,
-    config=None,
-    plot_dir=None,
-    save=True,
-    only_cat=None,
-    mcstat=True,
-    stat_only=False,
-    reweighting_function=None,
-    flavorsplit=None,
-    split_systematics=False,
-    only_syst=False,
-    partial_unc_band=False,
-    log=False,
-):
-    '''This function plots 1D histograms in all the categories contained in the `cat` axis, for each data-taking year in the `year` axis.
-    The data/MC ratio is also shown in the bottom subplot
-    The MC systematic uncertainty is plotted on top of the MC stack in the histogram plot and around 1 in the ratio plot.
-    The uncertainty on data corresponds to the statistical uncertainty only.
-    The plots are saved in `plot_dir` if no config argument is passed. If `save` is False, the plots are not saved but just shown.
-    The argument `only_cat` can be a string or a list of strings to plot only a subset of categories.
-    To reweight the histograms, one can additionally pass the `reweighting_function` argument which is a 1D function of the variable on the x-axis that modifies the histogram weights.'''
-    for sample in h.keys():
-        if dense_dim(h[sample]) != 1:
-            print(
-                f"Histograms with dense dimension {dense_dim(h[sample])} cannot be plotted. Only 1D histograms are supported."
-            )
-            return
-    samples = h.keys()
-    samples_data = list(filter(lambda d: 'DATA' in d, samples))
-    samples_mc = list(filter(lambda d: 'DATA' not in d, samples))
-
-    h_mc = h[samples_mc[0]]
-
-    years = get_axis_items(h_mc, 'year')
-    categories = get_axis_items(h_mc, 'cat')
-    variations = get_axis_items(h_mc, 'variation')
-
-    axis_x = dense_axes(h_mc)[0]
-    edges_x = axis_x.edges
-    binwidth_x = np.ediff1d(edges_x)
-
-    if len(samples_data) == 0:
-        is_mc_only = True
-    else:
-        is_mc_only = False
-
-    for year in years:
-
-        for cat in categories:
-            if only_cat:
-                if isinstance(only_cat, list):
-                    if not cat in only_cat:
-                        continue
-                elif isinstance(only_cat, str):
-                    if cat != only_cat:
-                        continue
-                else:
-                    raise NotImplementedError
-            slicing_mc = {'year': year, 'cat': cat}
-            slicing_mc_nominal = {'year': year, 'cat': cat, 'variation': 'nominal'}
-            if flavorsplit == '3f':
-                flavors = flavors_order['linear']
-                dict_mc = {
-                    f: stack_sum(
-                        hist.Stack.from_iter(
-                            [
-                                h[d][slicing_mc]
-                                for d in samples_mc
-                                if d.endswith(f'_{f}')
-                            ]
-                        )
-                    )
-                    for f in flavors
-                }
-                dict_mc_nominal = {
-                    f: stack_sum(
-                        hist.Stack.from_iter(
-                            [
-                                h[d][slicing_mc_nominal]
-                                for d in samples_mc
-                                if d.endswith(f'_{f}')
-                            ]
-                        )
-                    )
-                    for f in flavors
-                }
-                dict_mc = {
-                    'l': dict_mc['l'],
-                    'c+cc': dict_mc['c'] + dict_mc['cc'],
-                    'b+bb': dict_mc['b'] + dict_mc['bb'],
-                }
-                dict_mc_nominal = {
-                    'l': dict_mc_nominal['l'],
-                    'c+cc': dict_mc_nominal['c'] + dict_mc_nominal['cc'],
-                    'b+bb': dict_mc_nominal['b'] + dict_mc_nominal['bb'],
-                }
-                if any(
-                    cc in histname
-                    for cc in [
-                        'btagDDCvLV2',
-                        'particleNetMD_Xcc_QCD',
-                        'deepTagMD_ZHccvsQCD',
-                    ]
-                ):
-                    dict_mc = {
-                        'l': dict_mc['l'],
-                        'b+bb': dict_mc['b+bb'],
-                        'c+cc': dict_mc['c+cc'],
-                    }
-                    colors = colors_cc
-                else:
-                    colors = colors_bb
-            elif flavorsplit == '5f':
-                flavors = flavors_order['linear']
-                if config:
-                    if hasattr(config, "plot_options"):
-                        if histname in config.plot_options["variables"].keys():
-                            cfg_plot = config.plot_options["variables"][histname]
-                            if 'scale' in cfg_plot.keys():
-                                flavors = flavors_order[
-                                    cfg_plot['scale']
-                                ]
-                dict_mc = {
-                    f: stack_sum(
-                        hist.Stack.from_iter(
-                            [
-                                h[d][slicing_mc]
-                                for d in samples_mc
-                                if d.endswith(f'_{f}')
-                            ]
-                        )
-                    )
-                    for f in flavors
-                }
-                dict_mc_nominal = {
-                    f: stack_sum(
-                        hist.Stack.from_iter(
-                            [
-                                h[d][slicing_mc_nominal]
-                                for d in samples_mc
-                                if d.endswith(f'_{f}')
-                            ]
-                        )
-                    )
-                    for f in flavors
-                }
-                colors = [colors_5f[f] for f in flavors]
-                nevents = {
-                    f: round(sum(dict_mc_nominal[f].values()), 1) for f in flavors
-                }
-            else:
-                dict_mc = {d: h[d][slicing_mc] for d in samples_mc}
-                dict_mc_nominal = {d: h[d][slicing_mc_nominal] for d in samples_mc}
-                nevents = {
-                    d: round(sum(dict_mc_nominal[d].values()), 1) for d in samples_mc
-                }
-                reverse=True
-                if ("variables" in config.plot_options) & (histname in config.plot_options["variables"].keys()):
-                    cfg_plot = config.plot_options["variables"][histname]
-                    if 'scale' in cfg_plot.keys():
-                        reverse = False
-                if log:
-                    reverse = False
-                nevents = dict( sorted(nevents.items(), key=lambda x:x[1], reverse=reverse) )
-                dict_mc = {d: dict_mc[d] for d in nevents.keys()}
-                dict_mc_nominal = {d: dict_mc_nominal[d] for d in nevents.keys()}
-                colors = [colors_tthbb[d] for d in nevents.keys()]
-            if reweighting_function:
-                for sample, val in dict_mc_nominal.items():
-                    histo_reweighted = hist.Hist(dict_mc_nominal[sample].axes[0])
-                    histo_reweighted.fill(
-                        dict_mc_nominal[sample].axes[0].centers,
-                        weight=dict_mc_nominal[sample].values()
-                        * reweighting_function(dict_mc_nominal[sample].axes[0].centers),
-                    )
-                    dict_mc_nominal[sample] = histo_reweighted
-            stack_mc = hist.Stack.from_dict(dict_mc)
-            stack_mc_nominal = hist.Stack.from_dict(dict_mc_nominal)
-
-            if not is_mc_only:
-                # Sum over eras if era axis exists in data histogram
-                if 'era' in h[samples_data[0]].axes.name:
-                    slicing_data = {'year': year, 'cat': cat, 'era': sum}
-                else:
-                    slicing_data = {'year': year, 'cat': cat}
-                dict_data = {d: h[d][slicing_data] for d in samples_data}
-                stack_data = hist.Stack.from_dict(dict_data)
-
-            rebinning = False
-            if config:
-                if hasattr(config, "plot_options"):
-                    if histname in config.plot_options["variables"].keys():
-                        cfg_plot = config.plot_options["variables"][histname]
-                        if 'binning' in cfg_plot.keys():
-                            rebinning = True
-                            stack_data = rebin(
-                                stack_data, cfg_plot['binning']
-                            )
-                            stack_mc_nominal = rebin(
-                                stack_mc_nominal,
-                                cfg_plot['binning'],
-                            )
-
-            if not is_mc_only:
-                h_data = stack_sum(stack_data)
-                if flavorsplit == '5f':
-                    nevents['Data'] = round(sum(h_data.values()))
-
-            totalLumi = femtobarn(lumi[year]['tot'], digits=1)
-            if partial_unc_band:
-                opts_fig = opts_figure['partial']
-            else:
-                opts_fig = opts_figure['total']
-            fig, (ax, rax) = plt.subplots(2, 1, **opts_fig)
-            fig.subplots_adjust(hspace=0.06)
-            hep.cms.text("Preliminary", fontsize=fontsize, loc=0, ax=ax)
-            hep.cms.lumitext(
-                text=f'{totalLumi}' + r' fb$^{-1}$, 13 TeV,' + f' {year}',
-                fontsize=fontsize,
-                ax=ax,
-            )
-            stack_mc_nominal.plot(stack=True, histtype='fill', ax=ax, color=colors)
-            if not is_mc_only:
-                x = dense_axes(stack_mc_nominal)[0].centers
-                ax.errorbar(
-                    x, h_data.values(), yerr=np.sqrt(h_data.values()), **opts_data
-                )
-                # stack_data.plot(stack=True, color='black', ax=ax)
-            if rebinning:
-                syst_err2_up, syst_err2_down = get_systematic_uncertainty(
-                    stack_mc,
-                    variations,
-                    mcstat=mcstat,
-                    stat_only=stat_only,
-                    edges=cfg_plot['binning'],
-                )
-            else:
-                syst_err2_up, syst_err2_down = get_systematic_uncertainty(
-                    stack_mc, variations, mcstat=mcstat, stat_only=stat_only
-                )
-            # print("syst_err2_up", syst_err2_up)
-            # print("syst_err2_down", syst_err2_down)
-            plot_systematic_uncertainty(
-                stack_mc_nominal, syst_err2_up, syst_err2_down, ax
-            )
-            if not is_mc_only:
-                print(cat, histname)
-                ratio, unc = get_data_mc_ratio(stack_data, stack_mc_nominal)
-                rax.errorbar(x, ratio, unc, **opts_data)
-            plot_systematic_uncertainty(
-                stack_mc_nominal, syst_err2_up, syst_err2_down, rax, ratio=True, split_systematics=split_systematics, only_syst=only_syst, partial_unc_band=partial_unc_band
-            )
-            if is_mc_only:
-                maximum = max(stack_sum(stack_mc_nominal).values())
-            else:
-                maximum = max(stack_sum(stack_data).values())
-            if not np.isnan(maximum):
-                ax.set_ylim((0, 2.0 * maximum))
-            rax.set_ylim((0.5, 1.5))
-            xlabel = ax.get_xlabel()
-            ax.set_xlabel("")
-            ax.set_ylabel("Counts", fontsize=fontsize)
-            rax.set_xlabel(xlabel, fontsize=fontsize)
-            rax.set_ylabel("Data / MC", fontsize=fontsize)
-            rax.yaxis.set_label_coords(-0.075, 1)
-            ax.legend(fontsize=fontsize, ncols=2, loc="upper right")
-            if flavorsplit == '5f':
-                handles, labels = ax.get_legend_handles_labels()
-                labels_new = []
-                handles_new = []
-                for i, f in enumerate(labels):
-                    if f in nevents:
-                        labels_new.append(f"{f} [{nevents[f]}]")
-                    else:
-                        labels_new.append(f)
-                    handles_new.append(handles[i])
-                labels = labels_new
-                handles = handles_new
-                ax.legend(handles, labels, fontsize=fontsize, ncols=2, loc="upper right")
-            ax.tick_params(axis='x', labelsize=fontsize)
-            ax.tick_params(axis='y', labelsize=fontsize)
-            #rax.set_yticks((0, 0.5, 1, 1.5, 2), axis='y', labelsize=fontsize)
-            rax.tick_params(axis='x', labelsize=fontsize)
-            rax.tick_params(axis='y', labelsize=fontsize)
-
-            if log:
-                ax.set_yscale("log")
-                exp = math.floor(
-                    math.log(max(stack_sum(stack_mc_nominal).values()), 10)
-                )
-                ax.set_ylim((0.01, 10 ** (exp + 3)))
-                # if flavorsplit == '5f':
-                #    ax.legend(handles, labels, loc="upper right", fontsize=fontsize, ncols=2)
-                # else:
-                #    ax.legend(loc="upper right", fontsize=fontsize, ncols=2)
-            if config:
-                if hasattr(config, "plot_options"):
-                    if "labels" in config.plot_options:
-                        handles, labels = ax.get_legend_handles_labels()
-                        labels_new = []
-                        handles_new = []
-                        for i, l in enumerate(labels):
-                            if l in config.plot_options["labels"]:
-                                labels_new.append(f"{config.plot_options['labels'][l]}")
-                            else:
-                                labels_new.append(l)
-                            handles_new.append(handles[i])
-                        labels = labels_new
-                        handles = handles_new
-                        ax.legend(handles, labels, fontsize=fontsize, ncols=2, loc="upper right")
-                    if ("variables" in config.plot_options) & (histname in config.plot_options["variables"].keys()):
-                        cfg_plot = config.plot_options["variables"][histname]
-                        if 'xlim' in cfg_plot.keys():
-                            ax.set_xlim(*cfg_plot['xlim'])
-                        if 'scale' in cfg_plot.keys():
-                            ax.set_yscale(cfg_plot['scale'])
-                            if cfg_plot['scale'] == 'log':
-                                exp = math.floor(
-                                    math.log(
-                                        max(stack_sum(stack_mc_nominal).values()), 10
-                                    )
-                                )
-                                ax.set_ylim((0.01, 10 ** (exp + 3)))
-                                # ax.legend(handles, labels, loc="upper right", fontsize=fontsize, ncols=2)
-                        if 'ylim' in cfg_plot.keys():
-                            if isinstance(cfg_plot['ylim'], tuple):
-                                ax.set_ylim(*cfg_plot['ylim'])
-                            elif isinstance(
-                                cfg_plot['ylim'], float
-                            ) | isinstance(cfg_plot['ylim'], int):
-                                rescale = cfg_plot['ylim']
-                                ax.set_ylim(
-                                    (
-                                        0,
-                                        rescale
-                                        * max(stack_sum(stack_mc_nominal).values()),
-                                    )
-                                )
-                        if 'xlabel' in cfg_plot.keys():
-                            rax.set_xlabel(cfg_plot['xlabel'])
-                        if 'ylabel' in cfg_plot.keys():
-                            rax.set_ylabel(cfg_plot['ylabel'])
-                        if 'xticks' in cfg_plot.keys():
-                            rax.set_xticks(cfg_plot['xticks'])
-                            rax.xaxis.set_minor_locator(MultipleLocator(binwidth_x[0]))
-                else:
-                    if histname in config.variables.keys():
-                        if config.variables[histname].axes[0].lim != (0, 0):
-                            ax.set_xlim(*config.variables[histname].axes[0].lim)
-                        else:
-                            ax.set_xlim(
-                                config.variables[histname].axes[0].start,
-                                config.variables[histname].axes[0].stop,
-                            )
-                plot_dir = os.path.join(config.plots, cat)
-            if log:
-                plot_dir = os.path.join(plot_dir, "log")
-            if not os.path.exists(plot_dir):
-                os.makedirs(plot_dir)
-            filepath = os.path.join(plot_dir, f"{histname}_{year}_{cat}.png")
-
-            if save:
-                print("Saving", filepath)
-                plt.savefig(filepath, dpi=150, format="png")
-            else:
-                plt.show()
-            plt.close(fig)
-
-
-def plot_shapes_comparison(
-    df,
-    var,
-    shapes,
-    title=None,
-    ylog=False,
-    output_folder=None,
-    figsize=(8, 9),
-    dpi=100,
-    lumi_label="$137/fb$ (13 TeV)",
-    outputfile=None,
-):
-    '''
-    This function plots the comparison between different shapes, specified in the format
-    shapes = [ (sample,cat,year,variation, label),]
-
-    The sample, cat and year are used to retrive the shape from the `df`, the label is used in the plotting.
-    The ratio of all the shapes w.r.t. of the first one in the list are printed.
-
-    The plot is saved if outputfile!=None.
-    '''
-    H = df[var]
-    fig = plt.figure(figsize=figsize, dpi=dpi)
-    gs = fig.add_gridspec(nrows=2, ncols=1, hspace=0.05, height_ratios=[0.75, 0.25])
-    axs = gs.subplots(sharex=True)
-    plt.subplots_adjust(wspace=0.3)
-
-    axu = axs[0]
-    axd = axs[1]
-
-    for sample, cat, year, variation, label in shapes:
-        print(sample, cat, year, variation)
-        hep.histplot(H[sample][cat, variation, year, :], label=label, ax=axu)
-
-    if ylog:
-        axu.set_yscale("log")
-    axu.legend()
-    axu.set_xlabel('')
-    axu.set_ylabel('Events')
-    hep.plot.ylow(axu)
-    hep.plot.yscale_legend(axu)
-
-    # Ratios
-    sample, cat, year, variation, label = shapes[0]
-    nom = H[sample][cat, variation, year, :]
-    nomvalues = nom.values()
-    nom_sig2 = nom.variances()
-    centers = nom.axes[0].centers
-    edges = nom.axes[0].edges
-    minratio, maxratio = 1000.0, 0.0
-    for sample, cat, year, variation, label in shapes[:]:
-        h = H[sample][cat, variation, year, :]
-        h_val = h.values()
-        h_sig2 = h.variances()
-
-        err = np.sqrt(
-            (1 / nomvalues) ** 2 * h_sig2 + (h_val / nomvalues**2) ** 2 * nom_sig2
-        )
-        r = np.where(nomvalues > 0, h.values() / nomvalues, 1.0)
-        m, M = np.min(r), np.max(r)
-        if m < minratio:
-            minratio = m
-        if M > maxratio:
-            maxratio = M
-        axd.errorbar(
-            centers,
-            r,
-            xerr=0,
-            yerr=err,
-            label=label,
-            fmt=".",
-            linestyle='none',
-            elinewidth=1,
-        )
-
-    axd.legend(ncol=3, fontsize='xx-small')
-    hep.plot.yscale_legend(axd)
-    axd.set_xlabel(nom.axes[0].label)
-    axd.set_ylim(0.8 * minratio, 1.2 * maxratio)
-    axd.set_ylabel("ratio")
-    axd.grid(which="both", axis="y")
-
-    if title:
-        axu.text(0.5, 1.025, title, transform=axu.transAxes, fontsize='x-small')
-
-    hep.cms.label(llabel="", rlabel=lumi_label, loc=0, ax=axu)
+            d = {s : v for s, v in self.h_dict.items() if s in self.samples_data}
+        categorical_axes_dict = {s : [] for s in d.keys()}
+
+        for s, h in d.items():
+            for ax in h.axes:
+                if type(ax) in [hist.axis.StrCategory, hist.axis.IntCategory]:
+                    categorical_axes_dict[s].append(ax)
+        categorical_axes = list(categorical_axes_dict.values())
+        assert all(v == categorical_axes[0] for v in categorical_axes), "Not all the histograms in the dictionary have the same categorical dimension."
+        categorical_axes = categorical_axes[0]
+
+        return categorical_axes
+
+    @property
+    def dense_dim(self):
+        '''Returns the number of dense axes of a histogram.'''
+        return len(self.dense_axes)
+    
+    def get_axis_items(self, axis_name):
+        axis = [ax for ax in self.categorical_axes if ax.name == axis_name][0]
+        return list(axis.value(range(axis.size)))
+
+    def define_samples(self):
+        self.samples = self.h_dict.keys()
+        self.samples_data = list(filter(lambda d : self.data_key in d, self.samples))
+        self.samples_mc = list(filter(lambda d : self.data_key not in d, self.samples))
+
+    def load_attributes(self):
+        assert len(set([self.h_dict[s].ndim for s in self.samples_mc])), "Not all the MC histograms have the same dimension."
+        for ax in self.categorical_axes:
+            setattr(self, {'year': 'years', 'cat': 'categories', 'variation': 'variations'}[ax.name], self.get_axis_items(ax.name))
+        self.xaxis = self.dense_axes[0]
+        self.xedges = self.xaxis.edges
+        self.xbinwidth = np.ediff1d(self.xedges)
+        self.is_mc_only = True if len(self.samples_data) == 0 else False
 
-    if outputfile:
-        fig.savefig(outputfile.replace("*", "png"))
-        fig.savefig(outputfile.replace("*", "pdf"))
-    return fig
-- 
GitLab


From 2cf1d9ad533923b27c0899b427c059ca8f10e2cf Mon Sep 17 00:00:00 2001
From: mmarchegiani <matmarcheg@gmail.com>
Date: Thu, 16 Mar 2023 18:33:15 +0100
Subject: [PATCH 02/24] Method to plot data/MC

---
 notebooks/plotting/test_DataMC.ipynb | 283 +++++++++++++++++++++++++++
 pocket_coffea/utils/plot_utils.py    |  96 ++++++++-
 2 files changed, 372 insertions(+), 7 deletions(-)
 create mode 100644 notebooks/plotting/test_DataMC.ipynb

diff --git a/notebooks/plotting/test_DataMC.ipynb b/notebooks/plotting/test_DataMC.ipynb
new file mode 100644
index 00000000..f7cc5ef2
--- /dev/null
+++ b/notebooks/plotting/test_DataMC.ipynb
@@ -0,0 +1,283 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "65ddaec4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "from coffea.util import load\n",
+    "from pocket_coffea.utils.plot_utils import DataMC"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "eefe8b4f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<pocket_coffea.utils.plot_utils.DataMC at 0x7f57341979d0>"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "filename = \"/work/mmarcheg/PocketCoffea/output/datamc/ttHbb_ttbar_ST_WJets_datamc_2018_MuonIsoTight_bugfix/output_all.coffea\"\n",
+    "o = load(filename)\n",
+    "histname = \"ElectronGood_pt_1\"\n",
+    "h_dict = o[\"variables\"][histname]\n",
+    "datamc = DataMC(h_dict, histname)\n",
+    "datamc"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "acf4ddcc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['_categorical_axes',\n",
+       " 'build_stacks',\n",
+       " 'categorical_axes_data',\n",
+       " 'categorical_axes_mc',\n",
+       " 'categories',\n",
+       " 'data_key',\n",
+       " 'define_samples',\n",
+       " 'dense_axes',\n",
+       " 'dense_dim',\n",
+       " 'get_axis_items',\n",
+       " 'h_dict',\n",
+       " 'is_mc_only',\n",
+       " 'load_attributes',\n",
+       " 'lumi',\n",
+       " 'name',\n",
+       " 'plot_datamc',\n",
+       " 'samples',\n",
+       " 'samples_data',\n",
+       " 'samples_mc',\n",
+       " 'spliteras',\n",
+       " 'stack_sum',\n",
+       " 'stack_sum_data',\n",
+       " 'stack_sum_mc_nominal',\n",
+       " 'variations',\n",
+       " 'xaxis',\n",
+       " 'xbinwidth',\n",
+       " 'xcenters',\n",
+       " 'xedges',\n",
+       " 'years']"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "[item for item in dir(datamc) if not item.startswith(\"__\")]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "c5f3b72c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[Regular(50, 0, 500, name='ElectronGood.pt', label='$p_{T}^{e}$ [GeV]')]"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "datamc.dense_axes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "eeac458e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[StrCategory(['SingleEle_1b', 'SingleEle_2b', 'SingleEle_3b', 'SingleEle_4b', 'baseline'], name='cat', label='Category'),\n",
+       " StrCategory(['2018'], name='year', label='Year')]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "datamc.categorical_axes_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "eb91f8fe",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['2018'] ['SingleEle_1b', 'SingleEle_2b', 'SingleEle_3b', 'SingleEle_4b', 'baseline'] ['nominal', 'JERDown', 'JERUp', 'JES_TotalDown', 'JES_TotalUp', 'pileupDown', 'pileupUp', 'sf_btag_cferr1Down', 'sf_btag_cferr1Up', 'sf_btag_cferr2Down', 'sf_btag_cferr2Up', 'sf_btag_hfDown', 'sf_btag_hfUp', 'sf_btag_hfstats1Down', 'sf_btag_hfstats1Up', 'sf_btag_hfstats2Down', 'sf_btag_hfstats2Up', 'sf_btag_lfDown', 'sf_btag_lfUp', 'sf_btag_lfstats1Down', 'sf_btag_lfstats1Up', 'sf_btag_lfstats2Down', 'sf_btag_lfstats2Up', 'sf_ele_idDown', 'sf_ele_idUp', 'sf_ele_recoDown', 'sf_ele_recoUp', 'sf_ele_trigger_eraDown', 'sf_ele_trigger_eraUp', 'sf_ele_trigger_htDown', 'sf_ele_trigger_htUp', 'sf_ele_trigger_pileupDown', 'sf_ele_trigger_pileupUp', 'sf_ele_trigger_statDown', 'sf_ele_trigger_statUp', 'sf_jet_puIdDown', 'sf_jet_puIdUp', 'sf_mu_idDown', 'sf_mu_idUp', 'sf_mu_isoDown', 'sf_mu_isoUp', 'sf_mu_triggerDown', 'sf_mu_triggerUp']\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(datamc.years, datamc.categories, datamc.variations)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "5a799685",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([  0.,  10.,  20.,  30.,  40.,  50.,  60.,  70.,  80.,  90., 100.,\n",
+       "       110., 120., 130., 140., 150., 160., 170., 180., 190., 200., 210.,\n",
+       "       220., 230., 240., 250., 260., 270., 280., 290., 300., 310., 320.,\n",
+       "       330., 340., 350., 360., 370., 380., 390., 400., 410., 420., 430.,\n",
+       "       440., 450., 460., 470., 480., 490., 500.])"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "datamc.xedges"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "62416ae9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "year = '2018'\n",
+    "cat = 'SingleEle_1b'\n",
+    "datamc.build_stacks(year, cat)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "a9ede2b9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "datamc.stack_mc_nominal.plot(stack=True, histtype='fill')\n",
+    "plt.legend();\n",
+    "#plt.yscale('log')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "e5ffc260",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['plot_datamc']"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "list(filter(lambda x: 'plot' in x, dir(datamc)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "23a8834c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1200x1200 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "datamc.plot_datamc(year, cat)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "105ce019",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.15"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/pocket_coffea/utils/plot_utils.py b/pocket_coffea/utils/plot_utils.py
index 434035c2..f0323a55 100644
--- a/pocket_coffea/utils/plot_utils.py
+++ b/pocket_coffea/utils/plot_utils.py
@@ -13,13 +13,15 @@ from matplotlib.ticker import MultipleLocator, AutoMinorLocator
 import mplhep as hep
 
 from ..parameters.lumi import lumi, femtobarn
+from ..parameters.plotting import *
 
 class DataMC:
     '''This class handles the plotting of 1D data/MC histograms.'''
-    def __init__(self, h_dict, name, data_key="DATA"):
+    def __init__(self, h_dict, name, data_key="DATA", spliteras=False):
         self.h_dict = h_dict
         self.name = name
         self.data_key = data_key
+        self.spliteras = spliteras
         assert type(h_dict) == dict, "The DataMC object receives a dictionary of hist.Hist objects as argument."
         self.define_samples()
         assert self.dense_dim == 1, f"Histograms with dense dimension {self.dense_dim} cannot be plotted. Only 1D histograms are supported."
@@ -39,9 +41,8 @@ class DataMC:
         dense_axes = dense_axes[0]
 
         return dense_axes
-    
-    @property
-    def categorical_axes(self, mc=True):
+
+    def _categorical_axes(self, mc=True):
         '''Returns the list of categorical axes of a histogram.'''
         # Since MC and data have different categorical axes, the argument mc needs to specified
         if mc:
@@ -60,15 +61,48 @@ class DataMC:
 
         return categorical_axes
 
+    @property
+    def categorical_axes_mc(self):
+        return self._categorical_axes(mc=True)
+
+    @property
+    def categorical_axes_data(self):
+        return self._categorical_axes(mc=False)
+
     @property
     def dense_dim(self):
         '''Returns the number of dense axes of a histogram.'''
         return len(self.dense_axes)
     
-    def get_axis_items(self, axis_name):
-        axis = [ax for ax in self.categorical_axes if ax.name == axis_name][0]
+    def get_axis_items(self, axis_name, mc=True):
+        if mc:
+            axis = [ax for ax in self.categorical_axes_mc if ax.name == axis_name][0]
+        else:
+            axis = [ax for ax in self.categorical_axes_data if ax.name == axis_name][0]
         return list(axis.value(range(axis.size)))
 
+    def stack_sum(self, mc):
+        '''Returns the sum histogram of a stack (`hist.stack.Stack`) of histograms.'''
+        if mc:
+            stack = self.stack_mc_nominal
+        else:
+            stack = self.stack_data
+        if len(stack) == 1:
+            return stack[0]
+        else:
+            htot = stack[0]
+            for h in stack[1:]:
+                htot = htot + h
+            return htot
+
+    @property
+    def stack_sum_data(self):
+        return self.stack_sum(mc=False)
+
+    @property
+    def stack_sum_mc_nominal(self):
+        return self.stack_sum(mc=True)
+
     def define_samples(self):
         self.samples = self.h_dict.keys()
         self.samples_data = list(filter(lambda d : self.data_key in d, self.samples))
@@ -76,10 +110,58 @@ class DataMC:
 
     def load_attributes(self):
         assert len(set([self.h_dict[s].ndim for s in self.samples_mc])), "Not all the MC histograms have the same dimension."
-        for ax in self.categorical_axes:
+        for ax in self.categorical_axes_mc:
             setattr(self, {'year': 'years', 'cat': 'categories', 'variation': 'variations'}[ax.name], self.get_axis_items(ax.name))
         self.xaxis = self.dense_axes[0]
+        self.xcenters = self.xaxis.centers
         self.xedges = self.xaxis.edges
         self.xbinwidth = np.ediff1d(self.xedges)
         self.is_mc_only = True if len(self.samples_data) == 0 else False
+        if not self.is_mc_only:
+            self.lumi = {year : femtobarn(lumi[year]['tot'], digits=1) for year in self.years}
+
+    def build_stacks(self, year, cat):
+        slicing_mc = {'year': year, 'cat': cat}
+        slicing_mc_nominal = {'year': year, 'cat': cat, 'variation': 'nominal'}
+        self.h_dict_mc = {d: self.h_dict[d][slicing_mc] for d in self.samples_mc}
+        self.h_dict_mc_nominal = {d: self.h_dict[d][slicing_mc_nominal] for d in self.samples_mc}
+        self.nevents = {d: round(sum(self.h_dict_mc_nominal[d].values()), 1) for d in self.samples_mc}
+        reverse=True
+        # Here implement if log: reverse=False
+        self.nevents = dict( sorted(self.nevents.items(), key=lambda x:x[1], reverse=reverse) )
+        # Build MC stack with variations and nominal MC stack
+        self.stack_mc = hist.Stack.from_dict(self.h_dict_mc)
+        self.stack_mc_nominal = hist.Stack.from_dict(self.h_dict_mc_nominal)
+
+        if not self.is_mc_only:
+            # Sum over eras if specified as extra argument
+            if 'era' in self.categorical_axes_data:
+                if self.spliteras:
+                    slicing_data = {'year': year, 'cat': cat}
+                else:
+                    slicing_data = {'year': year, 'cat': cat, 'era': sum}
+            else:
+                if self.spliteras:
+                    raise Exception("No axis 'era' found. Impossible to split data by era.")
+                else:
+                    slicing_data = {'year': year, 'cat': cat}
+            self.h_dict_data = {d: self.h_dict[d][slicing_data] for d in self.samples_data}
+            self.stack_data = hist.Stack.from_dict(self.h_dict_data)
 
+    def plot_datamc(self, year, cat):
+        plt.style.use([hep.style.ROOT, {'font.size': fontsize}])
+        plt.rcParams.update({'font.size': fontsize})
+        fig, (ax, rax) = plt.subplots(2, 1, **opts_figure["total"])
+        fig.subplots_adjust(hspace=0.06)
+        hep.cms.text("Preliminary", fontsize=fontsize, loc=0, ax=ax)
+        hep.cms.lumitext(text=f'{self.lumi[year]}' + r' fb$^{-1}$, 13 TeV,' + f' {year}', fontsize=fontsize, ax=ax)
+        self.stack_mc_nominal.plot(stack=True, histtype='fill', ax=ax)#, color=colors)
+        if not self.is_mc_only:
+            ax.errorbar(
+                self.xcenters, self.stack_sum_data.values(), yerr=np.sqrt(self.stack_sum_data.values()), **opts_data
+            )
+            """
+            syst_err2_up, syst_err2_down = get_systematic_uncertainty(
+                stack_mc, variations, mcstat=mcstat, stat_only=stat_only
+            )
+            """
\ No newline at end of file
-- 
GitLab


From 210d8bef3d693ff3f417dac66ebff0f8b1ac9366 Mon Sep 17 00:00:00 2001
From: mmarchegiani <matmarcheg@gmail.com>
Date: Fri, 24 Mar 2023 11:13:56 +0100
Subject: [PATCH 03/24] Methods to plot data and MC separately

---
 pocket_coffea/utils/plot_utils.py | 30 +++++++++++++++++++++++++-----
 1 file changed, 25 insertions(+), 5 deletions(-)

diff --git a/pocket_coffea/utils/plot_utils.py b/pocket_coffea/utils/plot_utils.py
index f0323a55..9e5d539f 100644
--- a/pocket_coffea/utils/plot_utils.py
+++ b/pocket_coffea/utils/plot_utils.py
@@ -160,8 +160,28 @@ class DataMC:
             ax.errorbar(
                 self.xcenters, self.stack_sum_data.values(), yerr=np.sqrt(self.stack_sum_data.values()), **opts_data
             )
-            """
-            syst_err2_up, syst_err2_down = get_systematic_uncertainty(
-                stack_mc, variations, mcstat=mcstat, stat_only=stat_only
-            )
-            """
\ No newline at end of file
+            self.h_dict_data = {d: self.h_dict[d][slicing_data] for d in self.samples_data}
+            self.stack_data = hist.Stack.from_dict(self.h_dict_data)
+
+    def define_figure(self, year, ratio=True):
+        plt.style.use([hep.style.ROOT, {'font.size': fontsize}])
+        plt.rcParams.update({'font.size': fontsize})
+        if ratio:
+            fig, (self.ax, self.rax) = plt.subplots(2, 1, **opts_figure["total"])
+            fig.subplots_adjust(hspace=0.06)
+        else:
+            fig, self.ax  = plt.subplots(1, 1, **opts_figure["total"])
+        hep.cms.text("Preliminary", fontsize=fontsize, loc=0, ax=self.ax)
+        hep.cms.lumitext(text=f'{self.lumi[year]}' + r' fb$^{-1}$, 13 TeV,' + f' {year}', fontsize=fontsize, ax=self.ax)
+
+    def plot_mc(self):
+        self.stack_mc_nominal.plot(stack=True, histtype='fill', ax=self.ax)#, color=colors)
+
+    def plot_data(self):
+        self.ax.errorbar(self.xcenters, self.stack_sum_data.values(), yerr=np.sqrt(self.stack_sum_data.values()), **opts_data)
+
+    def plot_datamc(self, year, cat):
+        self.define_figure(year)
+        self.plot_mc()
+        if not self.is_mc_only:
+            self.plot_data()
-- 
GitLab


From d701a70b6076a7238bf783f0b2a243eabdcf0610 Mon Sep 17 00:00:00 2001
From: mmarchegiani <matmarcheg@gmail.com>
Date: Fri, 24 Mar 2023 15:11:12 +0100
Subject: [PATCH 04/24] Testing PlotManager

---
 notebooks/plotting/test_DataMC.ipynb | 130 +++++++++++++++++++++++++--
 pocket_coffea/utils/plot_utils.py    |  94 +++++++++++++------
 2 files changed, 191 insertions(+), 33 deletions(-)

diff --git a/notebooks/plotting/test_DataMC.ipynb b/notebooks/plotting/test_DataMC.ipynb
index f7cc5ef2..8830e0b7 100644
--- a/notebooks/plotting/test_DataMC.ipynb
+++ b/notebooks/plotting/test_DataMC.ipynb
@@ -21,7 +21,7 @@
     {
      "data": {
       "text/plain": [
-       "<pocket_coffea.utils.plot_utils.DataMC at 0x7f57341979d0>"
+       "<pocket_coffea.utils.plot_utils.DataMC at 0x7f3cb5f19be0>"
       ]
      },
      "execution_count": 2,
@@ -53,20 +53,26 @@
        " 'categorical_axes_mc',\n",
        " 'categories',\n",
        " 'data_key',\n",
+       " 'define_figure',\n",
        " 'define_samples',\n",
        " 'dense_axes',\n",
        " 'dense_dim',\n",
        " 'get_axis_items',\n",
+       " 'get_datamc_ratio',\n",
        " 'h_dict',\n",
+       " 'is_data_only',\n",
        " 'is_mc_only',\n",
        " 'load_attributes',\n",
        " 'lumi',\n",
        " 'name',\n",
+       " 'plot_data',\n",
        " 'plot_datamc',\n",
+       " 'plot_datamc_all',\n",
+       " 'plot_datamc_ratio',\n",
+       " 'plot_mc',\n",
        " 'samples',\n",
        " 'samples_data',\n",
        " 'samples_mc',\n",
-       " 'spliteras',\n",
        " 'stack_sum',\n",
        " 'stack_sum_data',\n",
        " 'stack_sum_mc_nominal',\n",
@@ -217,7 +223,7 @@
     {
      "data": {
       "text/plain": [
-       "['plot_datamc']"
+       "['plot_data', 'plot_datamc', 'plot_datamc_all', 'plot_datamc_ratio', 'plot_mc']"
       ]
      },
      "execution_count": 10,
@@ -235,9 +241,19 @@
    "id": "23a8834c",
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:168: RuntimeWarning: invalid value encountered in true_divide\n",
+      "  self.ratio = num / den\n",
+      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:169: RuntimeWarning: invalid value encountered in true_divide\n",
+      "  self.ratio_unc = np.sqrt(num) / den\n"
+     ]
+    },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 1200x1200 with 2 Axes>"
       ]
@@ -247,14 +263,116 @@
     }
    ],
    "source": [
-    "datamc.plot_datamc(year, cat)"
+    "datamc.define_figure(year)\n",
+    "datamc.plot_datamc()\n",
+    "datamc.plot_datamc_ratio()\n",
+    "#datamc.plot_datamc_ratio()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "id": "105ce019",
    "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1200x1200 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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Ea6+9ZhhG0TSj6tWrG5KMf//738Zzzz1nTiOSZERHRzuMsW/fPuO2226z/JnbtGlj/Prrry5z6NKliyHJaNWqlcPjaWlpZvy0adMc2lavXm22JSYmGr///e/dHvuFF14wCgsLjZdeesntvVydOnUy8vPznXJr1qyZIcno0aOHw+OnT582YxctWmRMmzbN5Rod9q958+a5/Tf45z//aVSrVs3y+atZs6bLdTSKP0dxcXHG/fff7xDXt29fo7Cw0JyK1qFDB7d5GIZhDB8+3JBkVKtWzUhNTbXsCwC49jz88MOGJON3v/tdqWPt6yjVr1/fst/OnTvNv1NLlizxePxjx46ZcVbTvufOnVvqK7zuPvcV/+x38cyD1NRUY8KECUajRo0Mf39/IygoyLjtttuM+fPnu50dsHHjRuP999+3/Pr5559dxpbXzINTp05ZfiaxuoJcfB0xd2uNGYbhsLZYWlraZed8OTMP0tPTjcmTJxtt2rQxAgICjBo1ahgtW7Y0YmJijL1797qNKygoMBo2bGhIMoKDgy3/XbZu3Wrm9+c//7lU+ZXk22+/Ncd2d4u2nf3Kfdu2bc3H1q5da8a/+uqrbmNnzpxp9tu4caNT++W8bq7ke9vOR6h03FWPS1u5LisXzzwoKCjQ1q1b1b17d/Oxi1cODQ0NVcOGDUt1nFmzZmnHjh0er7b622+/KT4+XvHx8XrrrbckFa1E2q9fP40bN0433HBDqY5vV3ynBU9mHuzYsUOzZ8+WJFWpUsXcCWP//v06d+6cJOndd9/V5s2bZbPZ1KtXL7Vs2VK9e/c2x0hISFDPnj3NlYibNm2q7t27KzIyUkeOHNFnn32mU6dOKSEhQcOHD9fatWsdrkTk5+ebq79enLO9Aik5bt94cdvo0aP1448/ql27drrjjjvk5+enTz75xNwudM6cOTp69KgWLFig4OBg9evXT02bNtX27du1ZMkSSUWvg7i4OA0YMMAc9+zZs9q7d6/L4xdfsfb111/X1q1b5efnpz59+qhdu3bKy8vTf/7zH3N7m0mTJunhhx922oL0rbfe0lNPPSWpaPXeP/zhD4qOjpavr6927NihZcuW6cKFC8rOztajjz6qn3/+2e3z8OKLL2rz5s3y8/PT7bffrubNm2vQoEGy2WyKiIjQrl27lJKSIne2b9+uTz75RJL09NNPq379+m77AgCuTfaZB40bN5ZUNKv04MGDysjIUP369dWkSRN5ebmeAGz/LBAWFmZ5jOJXFa1m1l0sODhYPj4+ys/Pd5o1Wlzxtiv1tywxMVG9e/fWiRMnzMdycnK0YcMGbdiwQe+8847i4uKcdkjo2rWrunbtekVyKiu1atVSdna2w2MzZszQzJkzS4yNiooy+1k99/bPR97e3goKCrqMbC/PqlWrNHz4cKdd13bs2KEdO3bozTff1Kuvvqqnn37aaRaFl5eXhg0bptdee00nT57U2rVrHT4jF3cld1lIT083vy/pHOaGG27QsWPHHHY+sH9elqS77rrLbWyfPn303HPPSSo6V7j4dXw5r5tyeW+XqtSAclF8ZfriX2V1P5MrVjMPCgsLjdDQUIfHZ8yY4RDfv39/h/Z77rnHMAz3FWhXMw8Mo2gF1RdeeMFhQZJL+apatarxr3/9q9SriObl5RlVq1Y1pKJFRkry9ddfG+Hh4eZxp0yZYrYtXLjQIaeWLVsaW7ZscRrjxIkT5mIxNWrUMBYsWOB09T49Pd1o3ry52ysMP//8s9k2f/58h7biOy1cfBV88ODBZpu3t7fTc3b27FmjcePGDj/H4MGDjRMnTjiMM3HiRLP9lVdecWgr/nr++OOPHdpee+01h7HbtWtn7Ny506HPyZMnHZ7jixeGyszMNO/5i4yMNA4dOuT0HO/Zs8dcBFMuqrbFnyNJxm233eaySt63b1/zuXI1w8IwDKN3796GJCMkJMTIyspy2QcAcG2z/9169NFHjUceecS8f93+dcMNNxgvvfSScf78eafYu+++25CKFm22UnzmwaRJk0qVn32GnCRjxYoVTu3bt283/7Z26tTJ43EPHDjgsGp/SEiIuTCkq90WIiIiDElG586djVdeecVYtGiRMX78eKNu3bpmn86dO7v9m3spKnK3heKfiz1ZNd/K7t27zc/LgwYNKvP8PJ158MMPP5gzUmvWrGk89dRTxgcffGAsWLDAGDdunMOsUPvs3Iv9+OOPZp9HHnnE7bHsa8I1bNiwzHdZ2L9/vzlr5cyZM277ZWVlmT9T8ee9+A4HmZmZbuNPnjzp9nzKndK8bq7Ue9uO4kElVHyF3uJfxafGlDWr4oFhGMaQIUMcHu/Xr58ZW1hYaNSpU8eh/R//+IdhGKUvHtjZVyUdPny409il+Zo9e3apnofExEQztlmzZsYbb7zh9PXPf/7TePzxx42OHTs6HOuuu+5y+EP05JNPmm3169c3MjIyXB7z0UcfNQseGzZscJtb8VsMLp6KVHx627Zt2xza7LcihIaGOo0ZGRlpxr3++usujxsTE+NwUu1q4aZ169aZfd566y2Htjlz5pht+/fvd2gr/gvuxhtvdPvL+vnnnzf7xcfHO7S9/fbbZpurxWns7rrrLvMD28WK367RqlUrt7+Yiy+E4+o2meK37/zrX/9ymwsA4Np1/vx5jz+n3HrrrU6fD5555hm3f9OLK36yMmrUqFLlmJ6ebjRp0sSQihZ+Gz16tPHBBx8YH374oTF+/Hhzq7qQkBCnv92e8HTBRKloge2LiwNHjhwxWrVqZfb5z3/+U+oc3Llaiwe7d+82PvzwQ2Pu3LnGiBEjzItdoaGhxi+//FLm+XlSPCgoKDBvTW3RooVx/Phxpz5JSUnmIoNVq1Z1uctAYWGhcfPNNxuS+1sXiu8qVta3LJTGCy+8YObxxhtvmI+PHTvWkIoWW7Takjw/P9+8jdndIvQXK83r5kq/tykeVELu1jxo3LjxFTtmScWDf/7znw6PBwUFmW+MX375xSnOfv/MpRYPiisoKDB+/PFH46233jIee+wxo1OnTiXe227/8vHxMY4cOeLxsd55551LKlI8+uijRk5OjsNY3bp1M9tXrVrl8ni//vqruRXmCy+8YJlb8Xug7r33Xoe2xx57zJBk+Pn5OeXRoEEDQ3JejTkjI8Mcr2XLlm4ruMW3Crp4VoDdsmXLzD7//e9/HdpGjRplSEVb1lz8y9T+y02SsWnTJrc/++TJk81+F+8tvGfPHmPt2rXG+vXrLavQ9j9K/fv3d2qzP0fe3t7Gjh073I7xyiuvuC1iFBQUGLfeeqshyYiKiqqQDyUAgIq3Y8cOh88If/rTn4yff/7ZOH/+vHHgwAFj4cKFDjPqil+QMQzH3RY6dOjg8irmt99+a149lGT07t271HlmZmYat99+u9vPNm3btjWSk5Mv6TnwtHjQpEkTt7MKij+P3bt3v6Q8XLlaiwd/+ctfnP6N7r77buPYsWNXJD9PigcrV640+1uta1D8wqj9AuPFip+UX/xZ0jAM49VXX3U6zyhPhYWFxr/+9S8zh5CQEIc14OyzeQMDA0scKzAw0JBkDBs2zKNjl/Z1cyXf26x5UAkFBwe7fPzo0aPKzc2Vn59fOWfkvO5BZmam9u/fr6ZNmzqtd+Dv769bbrmlzI7t5eWltm3bqm3btuZj+fn5SkhI0Pr16/Xll19q48aNLmPz8/P17rvv6sUXX/ToWMXXO7BStWpVhYWF6Y477tBDDz2kW2+91aG9sLBQP/30k6Si+x3vvPNOl+O8++675u4DPj4+mjdvnttj5uTkmN9HRES4zLtNmzYOr48TJ06Y90FenGPx9QYefPBBlyv5SkX3I0pF6xU0b97cZZ/iawi4W1ehXbt2Dvd3njlzxrw/rF27dvrd737ncuziOdx0001O9/Q1bdpUTZs2dRubk5OjTz75xNwRo2PHjg7txZ+jnj17qkWLFm7HKv68p6SkOKwvsWTJEnPHi1dffVU+Pvx6BYDr0eHDh821eZ555hm9+OKL5t/Yxo0bq3HjxhowYIA6deqkvXv3asWKFdqwYYNuu+02SdLvfvc7jR07Vm+++abi4+PVokULPfroo2rWrJlOnjypDRs26JNPPpG3t7d8fX2Vl5fndscqdwoKCjR37lx99913bvskJiZq9uzZmjFjhqpUqXKJz4a1iRMnytvb22VbixYtNGjQIH355ZfasWNHmR3T07W1rgarV6/WhAkTNH/+fAUGBpb78VeuXCmpaM2xqKgot/1at26tG2+8UYcPH9aGDRvMdaqKGz58uPl5/bPPPnNa98C+3kFZ77LgicOHD2vixInmTg/+/v5asmSJqlWrZvbJysqSVHSOUBL7+6k0u6R46oq/ty+p5IArzj4F6OKvi+/3LislzTzIzc01p0fZv959913DMBz3W5VkdO3a1Ry3LGYeeGLLli1GWFiYy2P16tXL43HatWtnSEVTji7nfvU9e/aYx//LX/7itl+LFi0uaaZD8VsDfvvtN3OHgpiYGIfxi1eEL945ovhqrwkJCS7zO3v2rDkz4umnn3b7cwwYMMCQZNx0000exxdflXbWrFluxy4sLDTq1atnSDKGDx/utt+5c+eM7du3G4sXLzZeeeUV4+GHHzY6derkcGVGkrF69WqHuOLPUUm3GhS/GlR854fc3FxzFkW3bt3K/D48AMC1p/jfn4v/fmdnZxv33Xef288Bfn5+xscff2ze8z506FCPj1tYWOgw9p133mn83//9n3H8+HHj5MmTxnfffWcMGzbM4er2b7/9VqqfzdOZBz/++KPlODNmzDD7Wt1HfrW43DUPCgsLjbS0NGPDhg3GPffcY47VunXrUv8blZSfJzMPis+y9fTL6j771q1bG1LRrQvFb5NNTU0148vzloUzZ84Yzz77rDnVXyqafR0XF+fUd8SIEYYko3r16iWOW6VKlSsy86A83tuul3lFhevWrZvLx7/++utSj/WnP/1JderUcfi6+Mp1SXx9fZ2u2Nr3Hf3hhx8cHre6guzOd9995/Rlv9rsiQ4dOpgr/l/s+PHjHo2Rk5NjXkFv2rSpatas6fHxL1Z89X77HrwXO3HihOVKqFaK//v9/PPPysvLk+Q8u8CTnRaqVq3qdkbBTz/9ZM6McLfzhGEY5syHi4+fkJBgxlvt9OBuVV1JSk5OVlpamtscfv75Zz3++OMKCQlR27ZtNWTIED377LP6/PPP5eXlpYkTJ+ruu+82+1s9R+7+reyKr75bfMeFd99915xF8dprr7mdxQEAgN2dd95pXvUr/rdIkmrUqKEFCxYoLi5Ow4cPV3R0tPz9/RUaGqr77rtPCQkJGjhwoM6ePStJTrsRWPnqq6/0n//8R5L08MMPa/Xq1br99ttVr149BQUFqUuXLvrkk0/00ksvSSpaSb/4fvZlKTIy0rLdvluFJB08ePCK5HA1sdlsCgkJUbdu3bR48WKNGzdOUtGV5I8++qjc88nIyCh1jP0KvSvDhw+XJHPXBbsvv/zS/H7o0KGlPual+Oabb9SiRQu98sor5uzfAQMGaOfOnerTp49Tf/sub+fOnVNubq7bcS9cuGDu0hAaGlqmOZfHe5t5tZVUr1699Pbbbzs9vmDBAj377LMeT4nOz8/XihUrnN6olzK1qUuXLg5TvTZt2qTz5887neR37ty51GMPGDDA3JrILiQkRMePH/f4RKxDhw6qUaOG+Ye0tBITE82T8ItPdEvL/iHAZrM53G5RXEJCgvn9woULNXLkyEs6ltXWkvY8QkNDnbautLe1bdvW7eup+NjupoilpKSYBZpL2SaySpUqbosXF+dQfHzDMDRjxgz99a9/lWEYatasmYYMGaLf/e53atu2rerWrWu+duxTQZs0aeJ024M9j5CQEDVo0MBtHlLRdjb2KaL24sG5c+c0ffp0SUV/0C4usgEA4IqXl5eaNGmiHTt26OTJky779OnTx+WJiiQdOXLE/N7q9r2Lvfvuu5KKtvf75z//6bbfc889pzfffFPHjh3Tu+++qyeeeMLjY3jK3S0LdgUFBeb3FOad/fWvf9Ubb7whSdqwYYMefPDBcj1+fn6+pKLPZ57eImw1rX/YsGHmNoaLFy82b/u137IQERHh0TbqlyMnJ0dPPvmk5s+fbz7WunVr/f3vf9cdd9zhNq745+xTp06pXr16LvudOnXK/L6st0Atj/c2xYNK6ve//71uuOEGp6vmv/zyi2JjYzVhwgSPxvnvf//rssJ38803lzqni4sCe/bs0f/93/+ZvzjsLmXmQWhoqFPxID09XQcOHPA41+zsbJ0/f97p8ZL2Sbaz368uOV+dLi37CWmzZs1Uo0YNl33se/NKUu3atS/5WPa8q1ev7vThwZ7HxT9PZmamDh8+LMn9jAJJio+PlyTL2SqeFC9q1aqlm266yWVb27ZtLe/VtI9vX/vC7t1339WUKVMkSa+//rpiYmJcfggpKCgw159wVQAp/hyV9MHEy8tLDRo00KFDh5ScnCxJmjNnjo4fPy5fX1/NmDHDMh4AgOLsn6ECAgJKHVv8IkTLli09jvvll18kWX9GkYpOQNq1a6evv/7aYQ/7snT48GG1adPGbXvx2QZ16tS5IjlURk8//bSSk5PVtm1bTZo0yW2/unXrKigoSJmZmUpNTS3HDIvYL8hcuHDBYZbnpbrxxhvVqVMnbd68WUuXLtWbb76p8+fPm7MQhgwZckWLSIWFhbrvvvv02WefSSqaATR79mw99NBDJRa6ihcPduzY4bZ4sGvXLvP7si4elMd7m9sWKil/f39zKtLF/vKXv+jbb78tcYzU1FSNHj3aZdsf/vCHUufkqigwZ84ch/+/6aab3L5ZrNivDF9s5MiROnfunEdjLFiwwJwiX5ynizcWPwm+nJkHxRdLtCpCFL/an5SUZDnm9u3bNW3aNE2bNs1c3M/Onnfbtm0dfrFlZGSY41788xRfLNFq0Rn72B06dHD7y9rex2azOT3XxQsExRdLzMrKMhcwLKmCbB8/Ojpa1atXlyTl5eXpr3/9q6SiQtv48ePd/lL/8ssvzdkoF/+sxZ8jTwtG9iJKSkqKMjIyNGvWLEnS2LFjnQokAIDrT58+fdSiRQuNHTvWsl9+fr75Yb/49PzExETzb37xW+Qu9vHHH0sqKtCXZtanfTHH7OzsEvvaL0BdqcW6i1+4ccV+i2xwcLDDrYPXul27dunTTz/VJ598Ytnv/Pnz5pXsWrVqlUdqDuwzRw8ePGg5Vd8wDK1evVqrVq0yX/Pu2G9dyMzM1Nq1a7VixQpzZvCQIUPKKHPXnn/+ebNw0LJlS+3YsUOPPvpoiYUDyfF8Y8WKFW77xcXFmd9bFc4uRXm8tykeVGLjxo1z+GNil5OTo759+2rGjBkuT6wLCwv16aefqnv37ua94sUFBgbqj3/8Y6nzCQwMdJpeXvx+JOnSblmQpBEjRrh8fOvWrerVq5e+/vprl4UBqegE8OWXX9aTTz7psn3YsGEe5VD8CvflvJkPHDhgvmmtTkhbt25tfv/NN9+47ZeVlaWhQ4dq+vTpWrhwoUOV8ty5c9q9e7ekS7tlwFWcXWZmplnxtzrBtz9vzZo1c1gn4vz589qzZ4/L49uLKyWNXVhYaI5fvN/evXvd3ipRXHJysp599lnz/y8uHhR/Hi6leDBjxgxlZWUpICDAnAUBALi+NWvWTLt27dI777xjue7SokWLzJOi4ldtq1atqunTp2v69OlatGiRy9jMzEwtX75cUtEFodLsttCqVStJRbt47du3z22/jIwM8++kPaaszZ492+3nu+3bt5snWnffffd1dduC/fP/nj17XH6Wt1uzZo0Mw5BU8sWYK+H222+XVDTz4K233nLbb9WqVbr77rvVp08fh9ttXBk6dKj5b/3ZZ5+ZOxxc6VsWTp06ZV4Uvfnmm7Vu3boS1+QorkWLFmaB66uvvnK45cauoKDAfN/eeOONlrftXoryeG9TPKjEatasqU8++cTlH4ScnBxNnjxZISEh6t+/v8aOHavHH39cd999tyIjIzV8+HC3lb1XXnnF6b5vT128ZePFLrV40K1bNw0aNMhlW3x8vAYMGKDIyEjdeeedGj16tJ588knde++96tGjh0JDQzVlyhTzl2dx99xzj9s1B4o7e/aseaJb0lSfknh6QhoVFWX+klm2bJk+/PBDpz5Hjx5Vz549zZP4i9e7sFrQ0JPiQWBgoNur5cWvBlgtlmjvd3Gf4oslWi1SaPWH4MCBA2ZltHg/+0IzkrRlyxanf/uCggItW7ZMnTp1cpiOFR0d7TYPT2eb2IsHZ8+eNbfWfP7556+r6ZQAAPfsFy3y8vI0YsQIh79Zdj/99JM5Hb1+/frm1Vap6MTFfsvmK6+84nSylZOTowceeEAXLlyQl5eXnn/++VLld//995vf33vvvS7XWzh79qzuv/9+8yLVfffdV6pjeGrv3r2aOHGi04nW4cOHNWrUKPP/r8R6C5WZ/WLHb7/9pokTJ5pFpuKSkpLM58XPz8/ji2Vl6Y9//KM543jatGkutzw/fvy4xo8fL6notd6zZ0/LMevXr68ePXpIKlrrwL4d5JW+ZWHRokXmwoj//Oc/S32uZLPZzNvKDx06ZM5MLW7WrFnmZ/oJEyaU+c9TLu/tUu3NgArx+eefO2wRcjlfjz32mFFQUOB0jJK2arT74IMPLMdPTEx06F+arRpTUlKMxo0bl8nPKclo1KiRcezYMY+e4w0bNphx9913n8f/Nq5MnDjRkGR4e3sb586ds+xbfJsmScYdd9xhTJ482XjppZeMIUOGGD4+Pmbbk08+6bQF4D/+8Q+z/cCBAw5tf/zjHw1JRlhYmNNxGzVqZG7h4s5LL71kjp2Wluayz/79+80+b7zxhkPb3Llz3eb2pz/9yZBk1KpVy+Xr0W7hwoXmGFu3bjUfP3funMNz061bN2P69OnGjBkzjNGjRxs33XST2VatWjXz+xEjRhgrVqxweo5CQ0Pd5nCx9957z+HfrEGDBsb58+c9jgcAXPvGjh1r/p2IiIgwZsyYYSxevNj417/+ZTz00EOGt7e3IRVtDb1q1Sqn+FWrVpnxgYGBxvTp043PP//ceOONN4yWLVuabX/7299cHr/45y9Xn7lGjhzpMP6kSZOMhQsXGosWLTImT55s3HDDDWZ7jx49jPz8/FL9/J5s1RgWFmb+je7atasxa9Ys48MPPzQmTJhgBAcHm8cfM2ZMqY5dFkp6/spiXKst93777TeHz8TNmzc3Zs6caXz22WfGu+++a4wfP95hC/WZM2eWeX6ebNVoGIaxdOlSM8bHx8d49NFHjXfeecf49NNPjSlTphh169Y1JBleXl7GypUrPRrzrbfecvpcHx8fX6r8S/vvNnToUPPz+1dffWWsXLmyxK8tW7Y4jHHu3DmjWbNmZg5/+tOfjI8//tj48MMPzfHt/56l+exYmi0+r/R7m+LBVeK7774zQkJCLvlE2tvb25g8ebLbEzVPiwcHDhxwe4yaNWs6vQBLUzwwDMM4duyY0bFjx8suHLRr185ISUnx+PmdPXu2GTt37lyP41yxP5etWrXyqP/rr79u7vfq6qt69erGiy++6FQ4MIz/7SkbGBjo1B4REWFIMgYOHOjweGZmpjn25MmT3eY1cOBAt3/47T788ENzrM2bNzu03X///WaB4OLcoqKiDEnG7bff7nZswzCM8ePHG1LRftY5OTkObcX3fnb1VbduXWP58uXGgAEDHB5/4YUXSnyOrKxZs8ZhvAULFngcCwC4PuTk5Dj9/XH1uWnp0qVux3j55ZcNLy8vt/FPP/20y88GhlHySVROTo7x5z//2fD19XU7vs1mMx588EHj9OnTpf75PSkedOnSxfjyyy8dToIv/hoxYoSRm5tb6uNfroouHhiGYezevdv8nOLuy8vLy3jppZfcvg4uJz9PiweGYRjvvPOO5WupevXqxjvvvOPxeBkZGQ4XiSIiIjz6GS/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KOeqgQUpKiiSpqqqq2eMZY4ITJk6ePLnRKg1r167V2rVr9fzzz+uJJ57QVVdd1ZbSAQAAAACIurgcedAQHvTp0ydsm4ZgoaGtlYqKCh04cECS1KtXL/3f//2fPv/8c/l8Pr3yyis67bTTtG/fPk2ePFnbtm1r+zcAAAAAAEAUxeXIg927d0uSevbsGbZNw7bq6upmj+f1ejVs2DAlJSXpiSee0Nlnnx3cNmHCBI0bN07Dhg3Tl19+qWnTpmnBggWWxzPGaN++fS35VkJKSkpSUlJSxPsDAAAAADqGuro61dXVRbz/sSPnrcTlyIOGEQe1tbVh2+zdu1eS1Lt372aPN2LECG3YsEFr165tFBw06Nmzp2bMmCFJevvtt5v94VRWVqp3794Rf8yaNavZmtuirq5ORUVFbeqgQHuij8Lt6KNwO/oo3I4+CreLZh+dNWtWm64fKysrW/R1PKalMUMMufTSS/Xqq6/qd7/7nX7zm9+EbHPfffdpxowZ+tGPfqRXX321zV9z48aNys7OlnR0pMKAAQOatMnMzFRFRYXS09O1cePGiL9We4882Ldvn3r37q29e/cqOTm53b4OECn6KNyOPgq3o4/C7eijcNpHH32kc889V2vXrtU555zTZHs0+2hbRx4MHTpUlZWVysjI0Pbt28O2i8vHFlJTUyVJNTU1Ydvs2rVLkpSWlmbL1zzppJOCn9fU1IQMDxp4PB5OggAAAACAZrX15rHH42lRu7gMDzIyMiRJK1euDNumtLRUkpSent7s8T744APV1tZq6NChjUKCY3m9XklSQkKCTj311NaWDAAAAACAY+JyzoMxY8ZIOhoehBp9UFNTEwwPxo0b1+zx5s2bp7y8PP36178O22bNmjWSpFNPPZXJDAEAAAAAHUpchgfnn3++0tPTZYwJObng7NmzFQgElJGRodGjRzd7vCuuuEKS9Pe//13r1q1rsr2urk6FhYWSpMmTJ7eteAAAAAAAoiwuw4MuXbro3nvvlSQ9+OCD+u1vf6vPP/9cmzdv1syZMzV79mxJ0owZM9S5c+fgftOnT1dWVpaysrIaHe/iiy9Wbm6u6uvrdckll+j555/Xzp07VV1drbfeeks5OTkqLy/XKaecol/96lfR+0YBAAAAALZLS0tTYWGhbXPkdQRxOeeBJE2ZMkXLly/Xs88+q8LCwuDIgAb5+fm66aabGr3m9XpVXl7e5FidO3fWggULNGrUKFVWVuqnP/1pkzapqan661//qq5du9r7jQAAAAAAoiotLU1FRUVOlxFVcRseeDwePfPMMxo3bpwef/xxlZWVSZKGDRumW2+9VZMnT27xrJOSdOKJJ6q8vFz/8z//o9dee01btmyRx+PROeeco/PPP19Tp05V37592+vbAQAAAACg3cTlYwsNPB6PbrzxRpWWlqq2tla1tbVauXKlbrjhhpDBQUlJiYwxMsaEPF7Pnj01Y8YMrVq1SjU1NaqurtbixYtVWFhoW3BQXFxsy3FihVveDzfU4YYaJPfU4RZueT/cUIcbapDcU4dbuOX9oA531eAmbnk/qMNdNbiJW94P6mjMLXW4gV3vRVyHBx0R/wkac8v74YY63FCD5J463MIt74cb6nBDDZJ76nALt7wf1OGuGtzELe8HdbirBjdxy/tBHY25pQ43IDwAAAAAAABRQXgAAAAAAAAsER4AAAAAAABLhAcAAAAAAMAS4QEAAAAAALDkMeHWHUTUdenSRYcPH1ZCQoLS0tJCtvH5fEpNTY1yZY0ZY1RZWan09PSQS1pGkxveD7fU4YYa3FIHfdSddbihBrfUQR+lDrfXQB+lDrfXQB+lDrfX0ZH6qNfrVSAQUOfOnVVfXx+2HeGBiyQmJioQCDhdBgAAAAAgziQkJMjv94fd3imKtaAZXbt21aFDh5SYmKj+/fs7XQ4AAAAAIMZVVVXJ7/era9eulu0YeQAAAAAAACwxYSIAAAAAALBEeAAAAAAAACwRHgAAAAAAAEuEBwAAAAAAwBLhAQAAAAAAsER4gBYxxujJJ5/UyJEjlZycrOTkZI0cOVJPPvmkWLADbvDSSy9p/Pjx6tu3r3r06KGzzjpLDz74oA4fPmy537JlyzRhwgT1799f3bp1U1ZWlmbMmKH9+/dHqXLEE/opomHnzp2aOnWqRo4cqeOOO04DBgzQmDFj9Pvf/151dXWW+9JH4XaR9rVPPvlEEydOVFpampKSkjRo0CD953/+p3bu3BmlyhEP2nLNFOn5N6oM0IxAIGCuu+46Iynkx09/+lMTCAScLhMx6uyzzzZDhgyxbHPPPfeE7Z9jxowxhw4dCrnf3LlzjcfjCblfdna2qampaY9vCR1cdXW1uffee824ceNMRkaG6dWrlxk5cqS5/fbbjc/nC7sf/RTR8P7775uUlJSwfW3w4MFmx44dIfelj8Jpjz76qJFkpkyZEnJ7pH3tlVdeMUlJSSH3S09PN1u2bGnPbwsd0KJFi8KeD4/9qK2tDe7TlmumSM+/0UZ4gGYVFxcHO29hYaHZvHmz2bx5syksLAy+/vDDDztdJmLQunXrjCTL8OD1118P9sPbbrvNfPLJJ+bLL780f/7zn01iYqKRZO68886Qx+7UqZORZK666iqzcuVKs2PHDvPUU0+ZXr16GUnmyiuvbM9vDx3Q5s2bTWZmZthf8Mcdd5x58cUXm+xHP0U01NfXm6ysrOCF1FtvvWVqamqM1+s18+bNC4YKV1xxRZN96aNwWnl5uenevXvY8CDSvlZZWRncPm7cOPPee++ZnTt3moULF5qMjAwjyZx33nncCEMjf/zjH1sdHkR6zRTp+dcJhAewVFdXZ9LT040kM23atCbb77rrrmBqW19f70CFiFWff/65GTZsWLPhwXnnnWckmWuuuabJL/6Gk3i3bt3Mzp07G2278sorjSRzwQUXmLq6ukbbXnvtteBJfMOGDfZ9U+jQAoGAyc3NNZJMnz59zLx588xXX31lampqzBtvvGHOPPNMI8n06tXLbN26tdG+9FNEw/PPP28kmaSkJLN9+/Ym21955ZVgn/n26AP6KJxUX18f7IPhwoNI+9qdd94ZHHWze/fuRtvWrl0bHJHw+uuv2/59oeO65ZZbjCRz7733tqh9W66ZIj3/OoHwAJbeeecdI8kkJCSEHApWXV1tEhISjCSzdOlSBypELFm/fr35xS9+YcaNGxfsV1bhwZYtW4JtPvnkkybbjxw5Yvr27WskmZKSkuDr+/fvD/6x8PLLL4c89llnnWUkmaKiInu+OXR4q1evDva3xYsXN9m+f/9+M2TIECPJ/OxnPwu+Tj9FtPzmN78xkszll18ecrvf7w/e2V2yZEnwdfoonNbQd8OFB5H2tUAgYE444QQjyfzpT38Kud/ll19uJJn8/Hz7viF0eGPHjjWSzAsvvNCi9pFeM0V6/nUKEybC0rJlyyRJo0ePVt++fZtsT0lJ0ahRoxq1BSK1Zs0a/fnPf9Z7772nQCDQbPuGPpeZmanTTz+9yfbExETl5eU1aitJq1atUl1dnZKSkvSd73wn5LF/+MMfNtkP8W39+vWSpKysLH33u99tsr1Hjx664447JB3tYw3op4iWLVu2SJIGDhwYcntCQoJ69+4tSdqzZ0/wdfoonLR8+XLNmjVL6enpmjBhQsg2kfa1bdu26auvvmq0vSX7AeXl5ZKk4cOHt6h9pNdMkZ5/nUJ4AEsVFRWSpNzc3LBtcnJyGrUFInXZZZdp/fr1wY/77rvPsv2x/dPj8YRsE6p/Nnw+fPhw9ejRo8X7Ib59/vnnkqTTTjstbH875ZRTJElbt24NvkY/RbQ8//zzMsboj3/8Y8jtW7ZskdfrlSQNGzYs+Dp9FE7Zt2+fJk2apEAgoJKSkpAXXVLkfa3h85SUlOD52Wo/wwpi0NF+6fV61blzZ1VXV2vChAnKzMxUnz59NHbsWM2YMUMHDx5stE+k10yRnn+d0snpAuBuPp9PksKezKWjJ2RJqqqqikpNiF19+vRRnz59gv9es2aNZftI+yf9GpG49NJLNWzYMA0aNChsm48++kiSGrWhn8IpxhjV1taqpqZG77//vh544AFJ0k9+8hMNHTo02I4+CqdMnTpV27Zt0+23366LL75Yzz77bMh20eij9fX12rdvX3B0DuJXw6iDI0eOaMyYMY22LVu2TMuWLdMLL7yghQsXBkcLxMt5lJEHsNTQoY+9oPu2hs7e0BaIlkj7Z2v227NnT7ProiM+jBgxQtdee23wDsC3ffnll3rwwQclSVdffXXwdfopnPLyyy+rd+/eGjRokPLz87V582b9/Oc/19NPP92oHX0UTliwYIGefvppZWdna9asWZZtI+1rrdnv2PaIbw3hgTFGw4cP1yuvvKKqqipt2bJFc+fOVa9evbR582Zdd911OnLkiKTonEfd0D8JD2Bp9+7dkqSePXuGbdOwrbq6Oio1AQ0i7Z+t2U+Sampq2lQnYt/y5cs1ZswYVVVVaeDAgZo6dWpwG/0UbvL+++/r448/bvQafRTRtn37dk2ZMkWdO3fW/Pnz1a1bN8v2kfa1luzXtWtXJSQcvSTib1lIRx9bGDZsmPLy8rRs2TJNmDBBxx9/vAYNGqRbbrlF77//vhISErR+/Xo9/vjjkqJzHnVD/yQ8gKWGFKy2tjZsm71790oSw7wQdZH2z9bsJ0nJycltqhOxa9u2bbruuut04YUXatu2bUpPT9fixYt13HHHBdvQT+GUyy+/XIFAQD6fT0uWLNH555+vTz/9VN/73ve0YcOGYDv6KKIpEAjohhtu0J49e3Tffffp7LPPbnafSPtaS/Y7cOBAcJJm/paFJN12223asGGD3njjjZCPE5x11ln66U9/Kkl6++23JUXnPOqG/kl4AEsDBgyQ9E0qFkrDtoa2QLRE2j9bs1/Pnj0t02DEp/r6es2cOVNDhgzRc889J0maOHGi1q9fr8GDBzdqSz+Fkzwej/r376/vfve7evvttzV06FAdPHhQDz30ULANfRTR9Mc//lHvvvuuLrzwQt15550t2ifSvtaa/Y5tDzRn9OjRkqSysjJJ0TmPuqF/Eh7AUmpqqiTroYa7du2SJKWlpUWlJqBBpP2Tfo22WLdunc477zwVFRWpvr5eo0eP1j/+8Q8999xzIe9Q0E/hFl27dg3eLVu3bl3wdfooomXLli2655571KtXLz399NNKTExs0X7R6KOdO3e2nLQOONZJJ50k6Zu+FS/nUcIDWMrIyJAkrVy5Mmyb0tJSSVJ6enpUagIaNPTP0tLSsMsrheqfDftt2LAh7DAx+jVC+fTTTzV27FitX79ePXr00DPPPKPly5frggsuCLsP/RTRkpGRoZ49ewaH0YbS8Ifq4cOHG+0n0UfR/r766ivV19ertrZWJ598sjweT6OPp556SpL02GOPBV976aWXIu5rDfvt3r1bmzdvbna/cEvlIX4cPnxYb775pt58803LRwkalr3NysqSFPk1U6TnX6cQHsBSw/IkK1euDJmI1dTUBDv0uHHjolobcNFFF0mSKisr9cknnzTZ7vf79dZbb0lq3D9zcnKUlJSkw4cP65133gl57EWLFjXZD/GttrZWP/jBD7R3715lZWVp1apVuv7665v9Y5N+imhJTU3VgQMH9M9//jNsm40bN0qSzjjjjOBr9FG4XaR97aSTTtKJJ54oSXrjjTdavB/iV6dOnfTzn/9ceXl5wccSQ2lYTjw7O1tS5NdMkZ5/HWMAC3V1dSY9Pd1IMr/61a+abJ82bZqRZDIyMkx9fb0DFSKWzZs3z0gyQ4YMCdtmxIgRRpK58sorTSAQaLTtkUceMZJM9+7dTXV1daNtV111lZFkRo0aZerq6hpte/31140kI8l89tln9n1D6NAee+wxI8n069fP7Ny5s1X70k8RDRMnTjSSzOmnn26OHDnSZPuOHTtMnz59jCRTXFzcaBt9FG5www03GElmypQpTbZF2tfuuusuI8mccsopZvfu3Y22rV271iQlJRlJZtGiRbZ/P+iYGvrMqaeeavbu3dtk++bNm03nzp2NJPOPf/zDGNO2a6ZIz79OIDxAs+bOnRs8Ic+cOdNs2bLFlJeXm6KiouDrjz32mNNlIga1JDx44403gv3w5z//udmwYYP54osvzJw5c0ynTp2MJDN9+vQm+33yySfB7VdffbVZvXq18Xq95umnnza9evUykszEiRPb89tDBzNmzBgjyUybNq3V+9JPEQ3r1q0zCQkJRpL57ne/a1asWGH27NljvF6v+dvf/mZOOeUUI8mcddZZTS6+6KNwA6vwINK+5vV6TXJyspFkxo8fb5YtW2Z27txp/va3v5nMzEwjyYwePbrJRRvi17Zt24JBa05Ojlm6dKnZu3ev2bZtm5k3b55JSUkxksykSZMa7RfpNVOk518nEB6gWYFAwFx33XXBTv3tj/z8fE64aBctCQ+MMeaee+4J2z8vvvjiJn8kN3j00UeNx+MJud+ZZ55p9uzZ0x7fFjqogQMHhu1n3/446aSTmuxPP0U0/Pa3vw3bXySZYcOGmbKyspD70kfhNKvwwJjI+9qrr75qunTpEnK/E044wXzxxRft+W2hA3r99deDo1JCfYwcObLJSIC2XDNFev6NNsIDtEggEDBPPPGEycnJMT179jQ9e/Y0ubm5pqSkhOAA7aal4YExxrz44otmzJgxpnfv3qZbt27mzDPPNA899JA5fPiw5X5Lly41l1xyiUlJSTFJSUlmyJAhpqioyBw4cMCubwMxonv37m0KD4yhnyI6Vq1aZa644gqTnZ1tunXrZk488UTzgx/8wDz00EPNPmJIH4WTmgsPjIm8r61bt85cffXVpn///qZLly5m4MCB5o477jA1NTV2fxuIEV988YW56aabzPDhw02PHj3MwIEDzY9//GPz2GOPhT2XtuWaKdLzbzR5jAkzrSMAAAAAAIBYbQEAAAAAADSD8AAAAAAAAFgiPAAAAAAAAJYIDwAAAAAAgCXCAwAAAAAAYInwAAAAAAAAWCI8AAAAAAAAlggPAAAAAACAJcIDAAAAAABgifAAAAAAAABYIjwAAAAAAACWCA8AAAAAAIAlwgMAAAAAAGCJ8AAAAAAAAFgiPAAAAAAAAJb+P5CZJ4P5Um8IAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 1200x1200 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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3XZN2O3fu1O7duxuVt6QdAAAAAACRICRJgK+//lqSdOGFFza5m+92wQUXSJK++eYbz2MVFRWSpJycHJ/tsrOzG9U9/fuhQ4eqW7durW6XnJzsicdfO/YFAAAAAABEkg6heJKJEydqyJAhfnfU//vf/y5Jjeo4nU5J8rqDv1tycrIkqaqqKqTt6uvrdfjwYfXowY70gNndNCvwj7qtQYgDAAAACLeQJAGysrKUlZXls3zXrl166qmnJEk33XST53H3RXnPnj19tnVfsLvrtrbdoUOHPEsHWtPO/Tz+kgCGYejw4cM+y5uTkJDg9ehDAK2z9Ztd4Q4BAAAA8Kuurs7rMfUt1dKZ6iFJAvizdu1aTZs2TVVVVerXr5/y8vI8ZQcPHpQkJSYm+mzvLjv9dIDWtJOk6upqpaamtqhd586dFRcXp4aGBu3fv18XXnihz7qVlZUBzRTIz89XQUFBm9sDAAAAACLDnDlzVFhY2O7PE7YkwM6dO/XII4/otddekySlpqbqgw8+aLQjv/uOfG1trc9+ampqJKnRxXZr2klSUlJSi9sdPXpUDQ0NTZ7Tm9TUVG3fvt1vHX+YBQAAAAAAsWHWrFm6//7729x+8ODBqqysbLZeyJMA9fX1mjNnjp588knV19dLkqZOnar58+c3WYvfp08fSd/f2ffGXeau29p2iYmJnjv/rWl35nN6Y7FYPAkGAAAAAAB8CXQ5uK/N9M8U0iTA5s2bNX36dM+RgaNGjdL/+3//T1deeaXX+larVdKp6fq+HDhwQJKUkpIS0nYdO3b0u4EgAAAAAABmE7IkwBdffKFrrrlGNTU16tatm5577jndeuutfrMVaWlpkqTi4mIZhuG1bnFxsaRTU+/PbLdt2zbV1taqe/furWp38OBBlZeXe13vf3q7lmZaAEQ++10fe3388LEDWvTRE9rpLFU/a6Z+8YNHlNTVe4LQ9tzY9gwRAAAAaFZcKJ6ktrZWP/7xj1VTU6OMjAyVlJTotttua/Yi+uqrr5Z0aoO9LVu2NCl3uVx6//33JUljxozxPJ6dna2EhASdOHFCH330kde+ly9f3qRd3759dd5550mSli1b1uJ2AGLXK6vm6p+OL3TCVa9/Or7QK6vmhjskAAAAwKeQJAEWL14sh8Ohs88+W5988okyMzNb1K5///6eowWfeOKJJkce/OlPf9KBAwfUtWtX/eQnP/E83rVrV02cOFGSNHfuXM/eA27Lli3T5s2bJUlTpkzxPG6xWHTzzTdLkubPn69Dhw41avf3v//dkwRw1wMQ23ZWlckwTm0WahgN+raqLMwRAQAAAL6FJAngPgHg3//933X22We3qq37iISlS5fq17/+tb788kvt2rVL8+fP169//WtJ0r333qvk5ORG7R599FF16NBBn332maZNm6aNGzdq7969evnll3XLLbdIOrUh4ZkJifvvv19JSUnasWOHbrjhBq1Zs0b79+/XG2+8oeuvv151dXUaNWqUfvSjH7XpvQAQXfr1HiSL5dRHqcUSp769B4U5IgAAAMA3i3Hm7fV2cP7552vnzp0tqtu3b98mdR955BE9+eSTXuuPGzdO77zzjjp16tSkbOHChbr77rubzCCQpGHDhmn16tVej/l75513dMMNNzSZQSBJ5557rtauXetZNuBNenq6KioqlJaWpj179vishyAr8H9kIxAI+943vT7+/Z4A29XPOpg9AQAAABAWLb0ODclMgKqqqoDaP/HEE3rzzTc1evRo9ejRQ126dNGwYcP09NNPa9myZV4TAJI0Y8YMrVy5Utdee62Sk5OVkJCgQYMGqaCgQOvWrfOaAJCkn/zkJyopKdFNN92k3r17q1OnTurXr5/uu+8+bd682W8CAEBsSeraS/dOeEp/+OUy3TvhKZ8JAAAAAMAMQnI6wNGjRwPuY9KkSZo0aVKr240ePVqjR49udbthw4bp9ddfb3U7AAAAAADMKiQzAQAAAAAAQPiRBAAAAAAAIEaQBAAAAAAAIEaEZE8AAIh0Y1fZgtDL9iD0AQAAALQdMwEAAAAAAIgRJAEAAAAAAIgRJAEAAAAAAIgRJAEAAAAAAIgRJAEAAAAAAIgRnA4AAC1w06zAPy63BiEOAAAAIBAkAQCgBbZ+syvcIQAAAAABYzkAAAAAAAAxgpkA7cjpdCozM9Nrmc1mk81mC3FEAMLJftfHAfdhe25sECIBAABAJLLb7bLb7V7LnE5ni/ogCdCOrFarSktLwx0GAJM7fOyAFn30hHY6S9XPmqlf/OARJXXtFe6wAAAAYDL+bianp6eroqKi2T5YDgAAYfbKqrn6p+MLnXDV65+OL/TKqrnhDgkAAABRiiQAAITZzqoyGUaDJMkwGvRtVVmYIwIAAEC0IgkAAGHWr/cgWSynPo4tljj17T0ozBEBAAAgWpEEAIAwu+2amRqQcrE6xidoQMrFuu2ameEOCQAAAFGKjQEBIMySuvbSvROeCncYAAAAiAHMBAAAAAAAIEYwEwAAQmTsKu/HubTO9iD0AQAAgFjFTAAAAAAAAGIESQAAAAAAAGIESQAAAAAAAGIESQAAiAJOp1Njx45V165dNXbsWDmdznCHBAAAABMiCQAAUSA3N1dr1qzRd999pzVr1ig3NzfcIQEAAMCEOB0AAEJk8C2V7dZ3SUmJXC6XJMnlcmnDhg3t9lwAAACIXMwEAIAokJ2drfj4eElSfHy8srKywhwRAAAAzIiZAAAQQex3fez18avPuV27Uqv1bVWZ+vYepKvPud1nXdtzY9szRAAAAJgYSQAAiAJJXXvpnmv/M9xhAAAAwORYDgAAAAAAQIwgCQAAAAAAQIwgCQAAAAAAQIwgCQAAAAAAQIxgY0AAiCBjV9mC0Mv2IPQBAACASEQSoB05nU5lZmZ6LbPZbLLZgvHHPAAAAAAgFtjtdtntdq9lTqezRX2QBGhHVqtVpaWl4Q4DAAAAABAF/N1MTk9PV0VFRbN9sCcAAAAAAAAxgiQAAAAAAAAxguUAABBBbpoV+Mf2XXd97PXxw8cO6JVVc7Wzqkz9eg/SbdfMVFLXXk3q2Z4bG3AMAAAACA+SAAAQQbZ+syvgPrxvJSO9smquvtqzSQ1Gg77as0mvrJqre679z4CfDwAAAObBcgAAgCRpZ1WZGowGSVKD0aBvq8rCHBEAAACCjSQAAECS1K/3IFksp34tWCxx6tt7UJgjAgAAQLCRBAAASJJuu2amBqRcrI7xCRqQcrFuu2ZmuEMCAABAkLEnAADEmLGrvJ8tK0mTukvqfr6k41LJYz5qbW+PsAAAABACzAQAAAAAACBGkAQAAASN0+nU+PHjlZycrPHjx8vpdIY7JAAAAJyGJAAAIGhyc3O1YsUKHThwQCtWrFBubm64QwIAAMBp2BMAAGLM4FsqA2pvv+tjn2VrVq6Ty+WSJLlcLn2ycp3X+rbnxgYUAwAAANqGmQAAgKDp13uQ4v51zGAcxwwCAACYDkkAAEDQ3HbNTGWkX6ZuCUnKSL+MYwYBAABMhuUAAIBW8XfEoCRN6iqpX6qkWo4ZBAAAMBlmAgAATIUTBgAAANoPSQAAgKlwwgAAAED7IQkAADCVkpKSRicMbNiwIcwRAQAARA/2BAAAtEqgRww2Jzs7WytWrJDL5VJ8fLyysrLa9fkAAABiCUkAAEDI2e/62GfZ1efcrl2p1fq2qkx9ew/S1efc7rW+7bmx7RkiAABAVCIJAAAwlaSuvXTPtf8Z7jAAAACiEkmAduR0OpWZmem1zGazyWbzf8wWAAAAAABudrtddrvda1lLT1SyGIZhBDMoSOnp6aqoqFBaWpr27NkT7nBiR0GPcEcAoIW2/19qwH0M/mq7zzKn06nc3FyVlJQoOztbRUVFslqtAT8nAACAWbX0OpSZAACAiORvX4Fnl/1WX+3ZpAajQR+8/4HGZk3wusSAfQUAAECsIQkAAAi5m2YF/uvnrs98l+2sKlOD0SBJajAa9G1VWcDPBwAAEA1IAgAAQm7rN7sC7sP7arhT+vUe5JkJEGeJU9/eg1rdP0sKAABANCIJAACISGNX+d5c9eJOJ/Vwly7aVndcQxM668lOB3W21/q+9xXIzc3VihUr5HK5tGLFCuXm5mr58uVBiBwAACB84sIdAMKnrq5OBQUFqqurC3cogFd1Jw0VrDquupPsX4rWObtDB/3p3HO1bsBA/encc3V2h9bnvEtKSuRyuSRJLpdLGzZsaFKHz1GYHWMUZscYhdlF4xjldIB2ECmnAxw+fFg9evRQTU2NkpKSwh1O4DgdIOocrjPU4z9rVfPb7kpKsIQ7HJjMReefF3Afd332R59lp28uGGeJU0b6ZU02F/yu/qgeXDQxej5HEXWi7nc9og5jFGYXSWOU0wEAAFGtvfcVuO2amXpl1Vx9W1Wmvr0H6bZrZra6f/YVAAAAZkMSAAAQs/ztKyBJk7pK6pcqqVYqeaxJ+ZF/LRfwhX0FAACA2ZAEAADErECPKnR9Z5Hulv70H6vVpVO3JuVrVq5rtK/AJyvXyX7Xx03q2Z4bG1AcAAAALUUSAAAQswJdUnC4zpC/3UgCPaqQ5QQAACDYSAIAABCg0Z/8Ronx8U0eD/SoQpYTAACAYCMJAABAgH7+mw6K79I0CXDq1+z5Spd0SNI9Ptrf5WWJgNTy5QQSSwoAAEDLkATwwTAMLVq0SH/6059UWloqScrMzNSdd96pX/ziF7JYOK4MAHDK+m/3BHSM5XYfGxReGu/SZ5JckuIlXRLv8rmZof0u72cdHD52QK+smqudVWXq969TDpK69vJal0QCAADRLy7cAZiRYRiaNm2abr/9dhUXF6u2tla1tbUqLi7W7bffrttuu02GYQT0HHa7v4OpYo9Z3g97SX24QzBFDJJ54jALs7wfZojDDDFI5okjGAbfUun1a+ndFo0bEK/kLqf+u/Rui8+6e9/8mcausjX5WvaXXH21e4OO1R3WV7s3aNlfcr3W83dSgtPp1Pjx45WcnKzx48fL6XT6rOvr87w1fQSDGX6vmCEGMzHL+0Ec5orBTMzyfhBHY2aJwwyC9V5YjECvZqPQs88+K5vt1B9D+fn5uvXWWyVJr776qgoLCyVJ8+fP99Q5U3p6uioqKpSWlqY9e/Z4rZOZmemZYRAuhw8fVo8ePVRTU6OkpKSwxhKU96PA3/ZcLYzDfkSltsSA+4n0GMwSx+E6Qz3+s1Y1v+0e0F3WYDDD+2GWOMwQg1niMNMYvWDOcb1zfv8mj4/8R7lqGho8/z4rPl7rBgz02sfH13j/4+LZZb9ttMFhRvpluufa//Ra177mV14/z8ePH+/Z3yA+Pl7jxo1r1/0NzPB71gwxRN3veuKIuhgYo8Rh9jgiaYy25DpUYjlAE/X19XriiSckSTNnzlRBQYGnrKCgQMeOHdN//dd/6cknn9Sdd96pjh07hilSAAC+l5B0UoNvqWzy+MhXLVqxQ3IZUrxFGnG+vNaTJP2f9+T2IxXlajBOJRIajAZVVv7d58yB3zuPed23IBj7GwTjtAROXAAAxDqSAGdYu3atKisrFRcXp4ceeqhJ+UMPPaSnnnpKlZWVWrdunUaPHh2GKAEAaJmi67so92/faUNFg7LS4lR0fRefdX0lB1qTSOg657jXBMGl8S6tk9SgU2sR/e1v0J6nJXDiAgAg1pEEOMPq1aslSaNGjVKvXk03TkpOTtbIkSP16aefavXq1SQBAACmZk2M0/JbuwXUR2sSCb5mJCw9YlHu3+JP68Mia6L3RML2jMFeH//sH+Vy/Wtpg8vl0voVK3zWVZz35RklJSWNZiRs2LDB52vxJZpmJJglDgBA6JAEOENFRYUkKScnx2ed7Oxsffrpp566MId+x18LuI9K4271O76gze13dv5ZwDEAgNkEI5HQmj6CMSOhbs5xrwmCzON1jU5cGPyd93r+3Ll7t9YdO6oGSR+8955u7H+B/nTuuU3qHfSxNEJqvM/CB+9/oLFZE7zus+DvxIZgXMAHY2ZEoHFEU1IFACIBSYAzuHcr9jYLwC05OVmSVFVVFZKYwsEsv5Aj7Ze6GRIREskIANEp1DMSfCmde0zurRYbJG03jnl9roP/W6fnRt7rtY+yV7Y32meh7ODfvdYdm3HSZxwtSUYc+deshz/9x2p16dQ0CdPSvRr8JSMCTSSYZZmHWf5uoY/o7MMMMdBH+/QRiTgd4AzZ2dnasGGDnn32Wd19991e6yxYsED33HOPRo4cqXXr1jUp79Spk06cOKG4uDj16dPHax9VVVXq3bu331gslvbdadowDFVWVio1NbXJc+3fv191dXWefyckJOjss89uVf+t6cPpdHr9gWtNH3trjrcqPm9cxw4pvutZAfcT6TGYJw5DriMHFJ/YS1Lbfx76WA4EHInzqCFrt/Du/m6WOMwQg1niMCRV1hpK7W4JYIQGhxnej1iJY/8xQ3Wu7/+dEC+d3bXpc/mLoaV9+FNZa+j0P+LiJKV0b9xHc2M0VHFI0t5aQ2d3aHr/qerkyUbtLZJ6e6nnT2v62OcylNS1Z5PHjxyv0UnXCc+/O8R3VGJn7ycPdTsrwevjof7bx5eW9uErhlDG4e/v0VDGIbXv+xFpY4M4vtfcGA02f5fnzV1D7t27Vw0NDerYsaPq630fpUwS4AwDBw7UP//5T7300kuaNm2a1zovv/yypk+froEDB6q8vLxJeXx8vBpOO44JAAAAAIBQiIuL88zy8oblAGfo2fNUZri2ttZnnZqaGklSjx7es8OdO3fW8ePHFR8fr3POOafNsYQi0wQAAAAAMIdA7tHv27dPLpdLnTt39luPJMAZ3NP3Dx486LOOu8zXVP+jR48GPzAAAAAAAAIUF+4AzMa93qS6utpnnQMHTq0vTklJCUlMAAAAAAAEA0mAM6SlpUmS1q9f77NOcXGxJCk1NTUkMQEAAAAAEAwkAc4wevRoSaeSAN5mA1RXV3uSAGPGjAlpbAAAAAAABIIkwBmuuOIKpaamyjAMzZkzp0n53Llz1dDQoLS0NI0aNSoMEQIAAAAA0DZsDHiGTp066bHHHtPdd9+tp556SklJSbrtttt08uRJLV68WHPnzpUkzZ49Wx07dgxztAAAAAAAtJzFCOQMgihlGIamTZumV1991Wt5bm6uXnjhBY7wAwAAAIB/Wb58uRYsWKBNmzbpu+++07Bhw3Tvvfdq0qRJYYnHMAx98cUXKisrU2VlpY4fP67k5GQNHjxYl19+ebNH6UUrlgN4YbFY9PLLL+v5559Xdna2EhMTlZiYqJycHBUVFZEAAAAAAIDTFBQU6Nprr9WyZct0zjnnqE+fPlq1apV++tOf6tFHH21zvxaLpclXc0mFo0ePqrCwUBdccIGGDx+um2++Wffdd59mzZqlO++8U1dddZV69eqlO++8U998802bY2uOy+VSamqqJ+5//vOfrWo/Z84cT9uHHnpIkrRq1Sqv70lRUVGL+yUJ4IPFYtHtt9+u4uJi1dbWqra2VuvXr9fPf/5zEgAAAAAA8C8bN25UYWGhMjIytG3bNm3evFmlpaX69NNPZbVa9cQTT2jt2rUhieXjjz9WZmamCgoKGl3gd+jQodFy7u+++07/+7//q4suukgvvvhiu8QSHx+vm2++2fPvP//5z61q/8Ybb3i+v+mmm4IWF0kAAAAAAECbFRQUSJJeffVVZWRkeB4fNWqU/vjHP0qSnn322YCeY/z48Zo3b57mzZunO+64w2udd955R+PHj9euXbskSRdeeKHmz5+vb7/9VsePH9exY8dUVlaml156SRdeeKGkU7MGcnNztWjRooDi82Xq1Kme75csWdLidrt379bGjRslSf3799ell14qSRo4cKDnfXC/763FngAAAAAAgDbr06ePunbtqq+//rpJ2ZEjR5SUlKT+/fu3ejq8JM8s7Pz8fL8XvaWlpbr00ktVV1cnSbr//vv15JNPKiEhwWv9EydOKD8/33MiXOfOnfX55583SmIEg2EYGjBggOe9KSsr8yQg/Jk3b55+/etfS5J++9vfej25bufOnTr//PMlSYsWLVJubm6LYmImAAAAAACgTWpra+V0OvXNN994XavevXt3GYah/fv3t1sMLpdLv/jFLzwJgAceeED//d//7TMBIEkdO3bUE0884blwPn78uAoLC4Mem8ViaTQboKVLAt58803P98FcCiAxEwAAAAAA0EYHDx5Ur169dNZZZyknJ8dnvfj4eL377rut7r8lMwH++te/6qc//akkafjw4SopKWnxce4HDx5USkqK6urqFB8fL6fTqeTk5FbH6c+XX36poUOHSpIuvvhibdmyxW/96upqWa1WuVwuDRgwQOXl5V73pWMmAAAAAACgVYqKimSxWHT22WdLkurr6zV//nzl5OTorLPOUmJiooYOHaqHHnpIDoejSfuePXuqV69eOvvss/Xee+/5/GpLAqCl7Ha75/snnniixQkA6VT8kydPlnRqRsGqVau81mtoaND//d//aeLEiUpLS1NCQoL69euncePG6ZVXXlF9fb3P5xgyZIguuugiSdIXX3yhr776ym9Mb7/9tlwul6RTswCCvTE9SQAAAAAAgKqqqnT11VcrLy9PJSUlqqmp0dGjR/Xll19q7ty5ysjI0PLly5u0u+iii/T1119rx44dTcq+/PJLTZo0SU8//XS7xFxTU6OPPvpIknTeeefpRz/6Uav7eO2112QYhgzD0A033NCkvKqqSldddZWmTp2qt99+W5WVlaqvr9e3336rDz/8UNOmTdPQoUP97nnQmiUB7XUqgBtJAAAAAACIcS6XSzfffLOKi4vVrVs3XX/99Xr88cc1ffp0paenS5IOHz6sSZMmadOmTY3aPvzww2poaNC0adO0e/duz+NVVVX693//d/3tb39T//792yXuzz77TO4V7mPHjlV8fHxQ+z927JjGjh2rdevWSZL69eunO+64Q3PmzNEvf/lL9evXT5L0j3/8QyNHjtS3337rtZ9bbrnF872/UwKOHDmiDz74QNKp0w0uvvjiIL2S73UIeo8AAAAAgIhy6NAhrVq1Sueee67ee+89ZWZmesqOHDmi6dOn680331R9fb3uuusulZSUeKap/9u//ZtmzJihhQsXauDAgRoyZIg6deqkzz//XHV1dbrzzjs1YcKEdon79PX1WVlZQe9/9uzZ+vLLLyVJDz30kAoKCtS5c2dP+fHjx/XYY4/pv//7v7V//3795je/0dKlS5v0c/7552vEiBFav369tm3bptLS0kbvsdt7773n2eCwPZYCSMwEAAAAAAD8y9tvv93k4jQxMVFLly71rGvfuHGj1q9f36jOc889p8WLF+vqq6/W7t27VV5erssvv1yLFy/WggUL2uViVjq1iZ6b1WoNat+HDh3SggULJEk33HCD5syZ0ygBIJ06WnDu3LmejQn/8pe/eF0WIbVsSUB7ngrgRhIAAAAAAKDx48dr2LBhXsvi4uL0yCOPeP791ltvNalzyy236IMPPlBVVZWqq6u1du1a3XLLLYqLa7/LzoMHD3q+T0pK8lv3gQce8HqM4elf11xzjaf+8uXLdezYsUZtvbFYLLr//vs9//7kk0+81rvppps878Xrr7+uMw/qq6+v92ygOGjQIM+JAsHGcgAAAAAAgGeXfF+uv/56z/cbN25s73BapEuXLp7v3RfswfLZZ595vl+/fr3f13z6c2/dutVrnT59+mjMmDH66KOPtH379kZHB0rSypUrVVNTI6n9lgJIJAEAAAAAAJLnzHlfOnfurNTUVFVWVqqysjJEUfmXnJzs+X7//v1+606aNMmzkd+Z/vjHPzbZ3X/Pnj2e7++7774Wx3T48GGfZVOnTvWcZrBkyZJGSYD2PhXAjSQAAAAAAECpqanN1klPT1dlZaXnjnW49e3b1/P95s2b/da98sordeWVV3ote/HFF5s85u9i3h9/7SZPnqy7775bJ06c0JIlS1RYWCiLxaKGhgb97W9/kyQNHjxYQ4YMadNztwR7AgAAAAAAGm2y58vevXslndosUJIKCgqaXWfva819MFx11VWe71etWtVknX1LGIbR6K6/W9euXSVJCQkJcrlcMgyjRV+vv/66z+fq2bOnxo8fL0kqKyvzLB347LPP5HQ6JbXvUgCJmQAAAAAAAEk7d+70eadckurq6rR7925JUu/evSVJAwYM0I9+9KNG9SoqKrRt2zalpqZ6ThRwC/a59/3799f555+vb775Rtu2bdPGjRtbfVRgWVmZJ7lxOvdpA3V1ddqzZ4/OO++8oMQ8depUz8aKS5Ys0cUXX9zoVIApU6YE5Xl8sRhtSZXAr27duun48eOKj4/3/HAAAAAAgNkcO3bMs8N+165d1bNnT591jx8/7pktkJiYqB49evjts7n+WqKiokKS1L17d5+7/x85csSzPCEhIUFnn312q57j0KFDOnr0qCSpU6dOOueccyRJR48e1aFDhyRJvXr1arQJ4ZlOnjzp2Rywa9eu6tDB9/12wzDkcDhkGIY6dOggq9WqvXv3yuVyef7dEi6Xy5O86Nmzp44cOSKXy6XOnTt7Xo83JAHaQXx8vBoaGsIdBgAAAAAgxsTFxcnlcvksZzlAO3AnAeLi4pSSkuK1jtPpbHGGp70YhqHKykqlpqa265qTljDD+2GWOMwQg1niYIyaMw4zxGCWOBijxGH2GBijxGH2GBijxGH2OCJpjDocDjU0NCg+Pt5vP8wEaAfp6emqqKhQhw4dNHDgQK91Dhw44HXdSSgdPnxYPXr0UE1Njc+pNaGSmZmp0tLSsMZgljjMEINZ4mCMmjMOM8RgljgYo8Rh9hgYo8Rh9hgYo8Rh9jjMNkZtNpvsdrvX8n/84x86efKk0tLSvG506MZMgHZktVp9DtjMzMwQRwMAAAAAiGQ2m002m81rmftmdHM4IhAAAAAAgBhBEgAAAAAAgBhBEgAAAAAAgBhBEgAAAAAAgBhBEiBMfG3mEKvM8n6YIQ4zxCCZJw6zMMv7YYY4zBCDZJ44zMIs7wdxmCsGMzHL+0Ec5orBTMzyfhBHY2aJwwyC9V5wRGA7cO/K2NzRDOFmpuMuAG8YozA7xijMjjEKs2OMwuwiaYy29DqUmQAAAAAAAMQIkgAAAAAAECMcDocKCgrkcDjCHQrChCQAAAAAAMQIh8OhwsJCkgAxjCQAAAAAAAAxokO4A4hmTqdTmZmZXstsNhs7XQIAAAAAWsxut8tut3stczqdLeqDJEA7slqtKi0tDXcYAAAAAIAo4O9msvt0gOawHAAAAAAAgBhBEiCGJSQkKD8/XwkJCeEOBfCKMQqzY4zC7BijMDvGKMwuGseoxTAMI9xBRBv3NIy0tDTt2bMn3OEAAAAAgCTp73//uy677DJt2rRJl156abjDQRC19DqUmQAAAAAAAMQIkgAAAAAAAMQIkgAAAAAAAMQIkgAAAAAAAMQIkgAAAAAAAMQIkgAAAAAAAMQIkgAAAAAAAMSIDuEOIJo5nU5lZmZ6LbPZbLLZbCGOCAAAAAAQqex2u+x2u9cyp9PZoj5IArQjq9Wq0tLScIcBAAAAAIgC/m4mp6enq6Kiotk+WA4AAAAAAECMIAkAAAAAAECMiMokwKWXXqqMjIw2tT127JgsFkuzX++8806QowYAAAAAoH1FXRJgy5Yt+vzzz9vcvry8PIjRAAAAAABgHlG1MeA333yjW2+9NaA+ysrKJElXXXWV1qxZE4ywAAAAAAAwhYhPAmzbtk3/+7//q61bt2r16tVqaGgIqL+vvvpKkjR06NBghAcAAAAAgGlEfBJg48aNeuaZZ4LWn3smAEkAAAAAAEC0ifg9Aa6//npt3brV8/X4448H1J97JkBSUpLuuOMOXXjhherWrZsuv/xy3XXXXdq1a1cwwgYAAAAAIOQifiZAz5491bNnT8+/N27c2Oa+DMPwbAw4ffp0GYbhKdu0aZM2bdqkxYsX6/nnn9eUKVPaHjQAAAA8HA6HFi5cqBkzZiglJSXc4QBAVIv4JEAwVVRU6OjRo5Kk7t276w9/+IPGjBmjbt26qbi4WA888IDKy8s1ffp0ZWVlqV+/fn77MwxDhw8fbnM8CQkJSkhIaHN7AACASOBwOFRYWKiJEyeSBAAQs+rq6lRXV9fm9qffxPaHJMBpHA6HhgwZooSEBD3//PO65JJLPGUTJkzQmDFjNGTIEO3atUszZ87UkiVL/PZXWVmpHj16tDme/Px8FRQUtLk9AAAAACAyzJkzR4WFhe3+PCQBTpOVlaVt27b5LE9MTNTs2bP1y1/+Uh9++KEMw5DFYvFZPzU1Vdu3b29zPMwCAAAAAODG0pnoNmvWLN1///1tbj948GBVVlY2W48kQCuNGjVKknTw4EE5nU716dPHZ12LxaKkpKRQhQYAAAAgirF0JroFuhzc3w3q00X86QCh1rdvX8/31dXVYYwEAAAAAIDWYSbAaT799FPV1tZq8ODBjS72T+dwOCRJcXFxGjBgQCjDAwAAAAAgIMwEOM2iRYs0fvx4/fa3v/VZx30E4YABA1izDwAAAACIKCQBTjN58mRJ0htvvKHNmzc3Ka+rq1N+fr4kafr06aEMDQAAAACAgMVkEmDWrFnKyMhQRkZGo8fHjRunnJwc1dfX69prr9XixYu1b98+7d+/X++//76ys7NVVlamCy64QL/5zW/CFD0AAAAAAG0Tk3sCOBwOlZWVNXm8Y8eOWrJkiUaOHKnKykr97Gc/a1LHarXqz3/+szp37hyKUAEAAAAACJqYTAL4c95556msrEz/8z//o3feeUc7duyQxWLRpZdeqiuuuEJ5eXnq1atXuMMEAAAAAKDVoi4JkJubq9zcXL91ioqKVFRU5LM8MTFRs2fP1uzZs4MbHAAAAAAAYRSTewIAAAAAABCLom4mgJk4nU5lZmZ6LbPZbLLZbCGOCAAAAAAQqex2u+x2u9cyp9PZoj5IArQjq9Wq0tLScIcBAAAAAIgC/m4mp6enq6Kiotk+WA4AAAAAAECMIAkAAAAAAECMIAkAAAAAAECMIAkAAAAAAECMIAkAAAAAAECMIAkAAAAAAECMIAkAAAAAAECMIAkAAACAsHE6ncrLy5Mk5eXlyel0hjkiAIhuJAEAAAAQNrm5uSouLpYkFRcXKzc3N7wBAUCU6xDuAKKZ0+lUZmam1zKbzSabzRbiiAAAAMylpKRELpdLkuRyubRhw4YwRxR+DodDCxcu1IwZM5SSkhLucACYiN1ul91u91rW0plUJAHakdVqVWlpabjDAAAAMK3s7GytWLFCLpdL8fHxysrKCndIYedwOFRYWKiJEyeSBADQiL+byenp6aqoqGi2D5YDAAAAIGyKioqUk5MjScrJyVFRUVF4AwKAKEcSAAAAAGFjtVo1b948SdK8efNktVrDHBEARDeSAAAAAAAAxAiSAAAAAAAAxAiSAAAAAAAAxAiSAAAAIKY4HA4VFBTI4XCEOxQAAEKOJAAAAIgp7uPXSAIAAGIRSQAAAAAAAGIESQAAAAAgSFhuAsDsSAIAAAAAQcJyE5iZ0+lUXl6eJCkvL09OpzPMESEcOoQ7gGjmdDqVmZnptcxms8lms4U4IgAAAACxKjc3V8XFxZKk4uJi5ebmavny5WGOCq1ht9tlt9u9lrU0qUMSoB1ZrVaVlpaGOwwAAAAAUElJiVwulyTJ5XJpw4YNYY4IreXvZnJ6eroqKiqa7YPlAAAAAAAQA7KzsxUfHy9Jio+PV1ZWVpgjQjiQBAAAAACAGFBUVKScnBxJUk5OjoqKisIbEMKCJAAAAAAAxACr1ap58+ZJkubNmyer1RrmiBAOJAEAAAAAAIgRJAEAAABiGOfaA0BsIQkAAABCwgwXm5yR3RTn2gNAbCEJAAAAQsIMF5vezshGdDBDkgkAIgFJAAAAEDM4Izt6mSHJBACRgCQAAAA+cGcx+nBGNvzhZx7+MD4QLUgCAADgA3cWow9nZMMffubhD+MD0aJDuAOIZk6nU5mZmV7LbDabbDZbiCMCgMjgcDi0cOFCzZgxQykpKeEOB1HEfUb2ZZddxhnZJpKSkqL8/Hx+3gGgGXa7XXa73WtZSze7JQnQjqxWq0pLS8MdBgBEHPfdlokTJ3JRAMSAlJQUFRQUhDsMADA9fzeT09PTVVFR0WwfLAcAgCjBWkUAAAA0hySAD6tXr9aECRPUu3dvdenSRRkZGZo9e7aOHDkS7tDQSk6nU+PHj1dycrLGjx/PmdCIWtGyVtEs57ibJY5owfsJtAw/K/CFsYFgicokwKWXXqqMjIw2t3/uuec0ZswYvfPOO9q3b5+OHz+usrIyPf7448rJydGBAweCGC3aW25urlasWKEDBw5oxYoVYTsT2ul0auzYseratavGjh0b0R/cJFbMJ5r+MDDLOe5miSNa8H4CLcPPCnxhbCBYoi4JsGXLFn3++ecBtc/Ly5NhGJoyZYrWr1+vvXv36sUXX1T37t1VWlqqGTNmBDFitDeznAmdm5urNWvW6LvvvtOaNWsi+oPbLIkVfC+a/jAwy8+sWeKIlmUeZnk/AbPjZwW+MDYQLFGVBPjmm2906623BtTH73//e508eVJXXnmlXnnlFeXk5MhqtWr69OlavHixJGnp0qX68ssvgxEyQiAYZ0IH4y5+MD64zXIHPlivJVpmRphBNP1hYJZz3M0SR7Qs8zDL+wmYHT8r8IWxgWCJ+CTAtm3bdO+992rs2LEaMGBAQBfnR48e1dtvvy1JevDBB9WpU6dG5dddd52GDx8u6VQiAJGhqKhI48aNU3JyssaNG9emM6GDcRc/GB/cwbgDH4yL72C9lmiZGWEG0fSHgVnOcQ9WHNFyJz9QZvn/CpgdPyvwhbGBYIn4JMDGjRv1zDPPaOXKlWpoaAior5KSEtXV1SkhIUE/+MEPvNa57rrrJJ3aOBCRwWq1avny5dq/f7+WL1/epjOhg3GXNRjJiGDEEYyL76KiIl199dXq0qWLrr766rC9Fnwvmv4wcJ/jLims57gHK45ouZMfKLP8fwXMjp8V+MLYQLBEfBLg+uuv19atWz1fjz/+eJv7cp+pOHToUHXr1s1rnezs7EZ1ERuCcZc1GMmIYMQRjItvq9Wqjz/+WMeOHdPHH38cltfCcoLGzPSHAXe+AQAAzCvikwA9e/bU0KFDPV/p6elt7st9EdGrVy+fdZKTkyVJVVVVbX4eRJ5g3MU3SxxmmTYe6GwClhM0lZKSovz8fKWkpIQ1jmDc+Q7GayEZAV/M8rNiBtF0sggAoGU6hDsAM3H/4uvZs6fPOu4EwaFDhzxLB3wxDEOHDx9uczwJCQl++0fouO/ih1sw4igqKlJubq42bNigrKyssCU03LMJ2orlBE2lpKSooKAgrDGceUHxxhtvtGlWQjBeizsZMXHixDZf7AV6sRjo+xGs9xONmeFnxSy8nSxiht93kYqfWQCBqKurU11dXZvbG4bRonoRPxMgmA4ePChJSkxM9Fnn9LLq6mq//VVWVqpHjx5t/pozZ05wXhhwmmAsSzADs8xokLjjfLpoOqpQ+v5isa1JgEDfj2h7P2E+JFSDi59ZAIGYM2dOQNePlZWVLXoekgCncc8AqK2t9VmnpqbG831SUpLf/lJTU1VTU9Pmr1mzZgXnhQFRKBibEwaD0+nUjTfeqMLCQt14441tnkobLYkEs1xQmGWKc6Dvh1neT0QvMyVUo0G0/cxGy+8mIFLMmjUroOvH1NTUFj0PSYDT9OnTR9L3MwK8OX22gL8ZA5JksViUlJTU5i+WAgC+BWNzwmAIxl2fYCUSgiHQP/jMckFhlrtxgb4fZnk/Eb2i6WQRM4i2n1lONwFCKyEhIaDrR4vF0qLnIQlwGvdFhL9p/gcOHJAkNhMCICl4xzaa4YJVCvwPPrNcUJjlblyg74dZ3k9ELzOdLBIN+JmFP8ysgFmQBDhNWlqaJGnbtm0+lwS4/1Bv6VQLAOYVjGMGzXJsYzAEYwq9WS4ozHI3LtD3wyzvZ7Bw6kP0Cvf/F7MsAYq2n1kEFzMrYBYkAU6TnZ2thIQEnThxQh999JHXOu4dc8eMGRPK0AC0g2AcMxiMvQnMcsEarBkJZjh+jbtx5hToRosSf0SbVbj/v5hpRhUAmB1JgNN07dpVEydOlCTNnTtX9fX1jcqXLVumzZs3S5KmTJkS6vAABFkw7sAHY28Cs1ywBmtGQjAu9ALF3bjGwn2XNhrxnpqLWWZUAUAkiMkkwKxZs5SRkaGMjIwmZY8++qg6dOigzz77TNOmTdPGjRu1d+9evfzyy7rlllskSVOnTlVmZmaowwYQZGa5A2+1WrV06VLl5+dr6dKlMT+FHsEX7ru00Yj31FyC8fllliUFANDeYjIJ4HA4VFZWprKysiZlF198sebPny+LxaIlS5YoKytLKSkpmj59umprazVs2DAtWLAgDFEDCDaz3IGXzHH33EzvRzCYYVlCMOIwy+sAzCwYn18sKQAQK2IyCdCcGTNmaOXKlbr22muVnJyshIQEDRo0SAUFBVq3bp169OgR7hABBIFZ7sCbRbRNoTdDYiUYcZjldQBmFozPL5YUAIgVHcIdQLDl5uY2m7ktKipqNkM8evRojR49OniBATAl9wUWTuGuM4BYlZ2drRUrVsjlcrEkCkBUi7okgJk4nU6fewfYbDbZbLYQRwQA/pEUARCrioqKNHnyZK1bty4qlkQBiE52u112u91rWUv3MiEJ0I6sVqtKS0vDHQYAIIadudnZG2+8EfFLPYD24F5ScNlll0XFkqho4nA4tHDhQs2YMYOZaoh5/m4mp6enq6Kiotk+2BMAAIAoFk2bnbF7OxCbOI3DfDgmNbKRBAAAIIpF02Zn0ZTQAIBIRmImspEEAAAgigXj/HSziKaEBtDeuFOLWMA4bxuSAAAARLFgnJ8umeMPLbMkNFiWgEjAnVrEAsZ525AEAAAgigXj/HTJHH9oBSuhESiWJQAAIhlJAAAAEBGCldAIVLQtS0hJSVF+fj67rgNAjCAJAAAA0ApmWZYQLCkpKSooKCAJAAAxgiQAAABAK5hlWYJZsEcCAEQWkgAAAACtYJZlCWbBHgkAEFlIAgAAEOUCXfPNnd72EYwTF8xwakO07ZFgBuzTYD58DiKakARoR06nU5mZmV6/7HZ7uMMDAMSIQNd8c6e3fQTjxAUznNoQbXskmAH7NJgPn4MwC7vd7vMas6XJqQ7tHGNMs1qtKi0tDXcYAAAEhDu98KeoqEiTJ0/WunXr2CMBUYvPQZiFzWaTzWbzWpaenq6Kiopm+2AmAAAA8MtMd3qZJm0+7JGAWGCmz0EgUCQBAACAX2baDZ9p0gDCwUyfg0CgSAIAAAC/uNMLINbxOYhoQhIAAAAAEc8sS0XMEkeg2A0fiF4kAQAAABDxzLJUxCxxBIrd8IHoRRIAAAAAQCPshg9EL5IAAAAArRQtU74BX9gNH4heJAEAAECzuOhtLNAp36y3htmxGz4QvUgCAACAZkXLOmezYL21OZHs+h674QPRiyQAAABAiAVjvTWzCYKPZBeAWNAh3AFEM6fTqczMTK9lNptNNpstxBEBAAAzyM7O1ooVK+Ryudq83trbbILly5cHO1QAgInY7XbZ7XavZS1NBpMEaEdWq1WlpaXhDgMAAJhMUVGRJk+erHXr1rV5vTW7twNA7PF3Mzk9PV0VFRXN9sFyAAAAgBALxnprdm8HIgfLd2AmJAEAAAAiELu3wxcuOM2HzUBhJiQBAAAAIhC7t8MXLjjNh+U7MBOSAAAAAAgIR+uZCxec5mOm5Tv8vIIkAAAAAALC0XrmYqYLzkBFy9IGMy3f4ecVJAEAAACAKGKmC85ARcvSBpbvwExIAgAAAABRJJouOFnaAAQfSQAAAAAAphRNSxuCgfX8CAaSAAAAAABMKZqWNgQD6/kRDCQBAAAAwoA7ekDzomlpA2AWHcIdQDRzOp3KzMz0Wmaz2WSz2UIcEQAAMAv3HT0AAFrKbrfLbrd7LWvp6RkkAdqR1WpVaWlpuMMAAAAAAEQBfzeT09PTVVFR0WwfUbEcwDAMvfDCCxoxYoSSkpKUlJSkESNG6IUXXpBhGOEODwAAoF2wpAAAAuNwOFRQUCCHwxHuUEIm4pMAhmFo2rRpuv3221VcXKza2lrV1taquLhYt99+u2677bZWJQKOHTsmi8XS7Nc777zTjq8KAACgeWwSBgCBcTgcKiwsJAkQSRYsWKBXX31VkpSfn6/y8nKVl5crPz9fkvTaa6/p2WefbXF/5eXl7RInAAAAAADhFtFJgPr6ej3xxBOSpJkzZ6qgoEADBw7UwIEDVVBQoAcffFCS9OSTT+rEiRMt6rOsrEySdNVVV8kwDJ9fP/nJT9rnRQEAAAAA0E4iOgmwdu1aVVZWKi4uTg899FCT8oceekhxcXGqrKzUunXrWtTnV199JUkaOnRoUGMFAAAAACDcIjoJsHr1aknSqFGj1KtXryblycnJGjlyZKO6zXHPBCAJAAAAAACNOZ1O5eXlSZLy8vJafCwdzCOikwDu4w9ycnJ81snOzm5UtznumQBJSUm64447dOGFF6pbt266/PLLddddd2nXrl0BRg0AAAAAkSk3N1fFxcWSpOLiYuXm5oY3ILRah3AHEAh31snbLAC35ORkSVJVVVWz/RmG4dkYcPr06Y1OFdi0aZM2bdqkxYsX6/nnn9eUKVMCCR0AAAAAIk5JSYlcLpckyeVyacOGDWGOCK0V0TMB3EmAnj17+qzjThC0ZJpKRUWFjh49Kknq3r27/r//7//T119/LafTqbfeeksXXnihDh8+rOnTp2vnzp2BvwAAAAAAiCDZ2dmKj4+XJMXHxysrKyvMEaG1InomwMGDByVJiYmJPuu4y/bv399sfw6HQ0OGDFFCQoKef/55XXLJJZ6yCRMmaMyYMRoyZIh27dqlmTNnasmSJX77MwxDhw8fbslL8SohIUEJCQltbg8AAAAAwVRUVKTJkydr3bp1ysnJUVFRUbhDihp1dXWqq6trc/vTZ7L7E9FJAPcMgNraWp91ampqJEk9evRotr+srCxt27bNZ3liYqJmz56tX/7yl/rwww9lGIYsFovP+pWVlS16Xl/y8/NVUFDQ5vYAAABAW6WkpCg/P18pKSnhDgUmYrVaNW/ePF122WWaN2+erFZrm/pxOBxauHChZsyYwRj7lzlz5qiwsLDdnyeikwB9+vSR9P2MAG/cZe66gRo1apSnX6fT6bff1NRUbd++vc3PxSwAAAAAhEtKSgo3pNBuHA6HCgsLNXHiRJIA/zJr1izdf//9bW4/ePBgVVZWNlsvopMA7qxTdXW1zzoHDhyQpKANrL59+3q+r66u9psEsFgsSkpKCsrzAgAAAACiV6DLwf3NUj9dRCcB0tLSJEnr16/3Wcd9fEVqamqz/X366aeqra3V4MGDG13sn87hcEiS4uLiNGDAgNaGDAAAACACsTwC0SKiTwcYPXq0pFNJAG+zAaqrqz1JgDFjxjTb36JFizR+/Hj99re/9Vln48aNkqQBAwYwXR8AAADww+FwqKCgwHMjLZK5l0eQBECki+gkwBVXXKHU1FQZhqE5c+Y0KZ87d64aGhqUlpbmWcvvz+TJkyVJb7zxhjZv3tykvK6uTvn5+ZKk6dOnBxY8AAAA0E7Mctfave47GpIAMBen06m8vDxJUl5eXouOhMcpEZ0E6NSpkx577DFJ0lNPPaXf/e53+vrrr1VeXq7CwkLNnTtXkjR79mx17NjR027WrFnKyMhQRkZGo/7GjRunnJwc1dfX69prr9XixYu1b98+7d+/X++//76ys7NVVlamCy64QL/5zW9C90IBAACAVuCuNaJdbm6uZ9Z3cXGxcnNzwxtQBInoPQEkacaMGVq7dq1effVV5efne+7Uu+Xm5uqOO+5o9JjD4VBZWVmTvjp27KglS5Zo5MiRqqys1M9+9rMmdaxWq/785z+rc+fOwX0hAAAAAIAWKSkpkcvlkiS5XC5t2LAhzBFFjoieCSCd2gHx5Zdf1vPPP6/s7GwlJiYqMTFROTk5Kioq0gsvvNDiXRIl6bzzzlNZWZkKCwuVlZWlXr16KTk5WePGjVNBQYFKS0t1ySWXtOMrAgAAAAD4k52drfj4eElSfHy8srKywhxR5Ij4mQDSqUTA7bffrttvv71F9YuKilRUVOSzPDExUbNnz9bs2bODFCEAAAAAIFiKioo0efJkrVu3znMDGC0T8TMBAAAAAACxxWq1at68eZKkefPmyWq1hjmiyBEVMwHMyul0KjMz02uZzWaTzWYLcUQAAAAAgEhlt9tlt9u9lrX0hASSAO3IarWqtLQ03GEAAAAAAKKAv5vJ6enpqqioaLYPlgMAAAAAABAjSAIAAAAAMK2UlBTl5+crJSUl3KEAUYHlAAAAAABMKyUlRQUFBeEOI2AkM2AWJAEAAAAAoJ1FSzIDkY/lAAAAAAAAxAiSAAAAAAAAxAiSAAAAAAAAxAiSAAAAAAAAxAiSAAAAAAAAxAiSAAAAAACCzul0Ki8vT5KUl5cnp9MZ5oiAxmJ1jHJEYDtyOp3KzMz0Wmaz2WSz2UIcEQAAABAaubm5Ki4uliQVFxcrNzdXy5cvD3NUwPcicYza7XbZ7XavZS1NYpAEaEdWq1WlpaXhDgMAAAAIuZKSErlcLkmSy+XShg0bwhwR0FgkjlF/N5PT09NVUVHRbB8sBwAAAAAQdNnZ2YqPj5ckxcfHKysrK8wRAY3F6hglCQAAAAAg6IqKipSTkyNJysnJUVFRUXgDAs4Qq2OUJAAAAACAoLNarZo3b54kad68ebJarWGOCGZhlg35YnWMkgQAAAAAENUcDocKCgrkcDjCHQrkfUM+hA5JAAAAAABRzeFwqLCwkCSASUTihnzRhCQAAAAAACBkYnVDPrMgCQAAAAAACJlY3ZDPLEgCAAAAAABCJlY35DMLkgAAAAAAAMQIkgAAAAAAAMSIDuEOIJo5nU5lZmZ6LbPZbLLZbCGOCAAAAAAQqex2u+x2u9cyp9PZoj5IArQjq9Wq0tLScIcBAAAAAIgC/m4mp6enq6Kiotk+WA4AAAAAAECMIAkAAAAAAECMIAkAAAAAAECMIAkAAAAAAECMIAkAAAAAIGo5nU7l5eVJkvLy8lq8gzp8S0lJUX5+vlJSUsIdCtqAJAAAAACAqJWbm6vi4mJJUnFxsXJzc8MbUBRISUlRQUEBSYAIRRIAAAAAQNQqKSmRy+WSJLlcLm3YsCHMEQHhRRIAAAAAQLsww7Tx7OxsxcfHS5Li4+OVlZUVtlgAMyAJAAAAAKBdmGHaeFFRkXJyciRJOTk5KioqClssgBmQBAAAAAAQtaxWq+bNmydJmjdvnqxWa5gjAsKrQ7gDiGZOp1OZmZley2w2m2w2W4gjAgAAAABEKrvdLrvd7rWspSdfkARoR1arVaWlpeEOAwAAAAAQBfzdTE5PT1dFRUWzfUT8cgDDMPTCCy9oxIgRSkpKUlJSkkaMGKEXXnhBhmG0qc/Vq1drwoQJ6t27t7p06aKMjAzNnj1bR44cCXL0AAAAAACETkTPBDAMQ9OmTdOrr77a6PHi4mIVFxfro48+0iuvvCKLxdLiPp977jndc889jRIIZWVlevzxx/WXv/xFn3zyiXr16hW01wAAAAAAQKhE9EyABQsWeBIA+fn5Ki8vV3l5ufLz8yVJr732mp599tkW97dlyxbl5eXJMAxNmTJF69ev1969e/Xiiy+qe/fuKi0t1YwZM9rltQAAAAAA0N4iNglQX1+vJ554QpI0c+ZMFRQUaODAgRo4cKAKCgr04IMPSpKefPJJnThxokV9/v73v9fJkyd15ZVX6pVXXlFOTo6sVqumT5+uxYsXS5KWLl2qL7/8sn1eVIjV1dWpoKBAdXV14Q4F8IoxCrNjjMLsGKMwO8YozC4ax2jEJgHWrl2ryspKxcXF6aGHHmpS/tBDDykuLk6VlZVat25ds/0dPXpUb7/9tiTpwQcfVKdOnRqVX3fddRo+fLikU4mAaFBXV6fCwsKoGtCILoxRmB1jFGbHGIXZMUZhdtE4RiM2CbB69WpJ0qhRo7yu0U9OTtbIkSMb1fWnpKREdXV1SkhI0A9+8AOvda677roW9wcAAAAAgNlEbBLAffRBTk6OzzrZ2dmN6rakv6FDh6pbt24B9wcAAAAAgNlEbBLA6XRKkt+d+pOTkyVJVVVVIe8PAAAAAACzidgjAt0X7T179vRZx31B764brP4OHTrkWTrgj2EYOnz4cLPP7UtCQkKzzwEAAAAAiHx1dXUB7T1w+jH3/kRsEuDgwYOSpMTERJ913GX79+8Pan+SVF1drdTUVL99VlZWqkePHs0+ty/5+fkqKChoc3sAAAAAUkpKivLz85WSkhLuUPAvwfh/YpY+gmXOnDkqLCxs9+eJ2CSA+459bW2tzzo1NTWS1KIL8db0J0lJSUnN9pmamqrt27c3W88XZgEAAAAAgUtJSeHmmskE4/+JWfoIllmzZun+++9vc/vBgwersrKy2XoRmwTo06ePpO/v4HvjLnPXDVZ/iYmJfmcMuFkslhYlCwAAAAAAsS3Q5eAWi6VF9SJ2Y0Cr1Srp1LR8Xw4cOCBJLZraEez+mmO32wPuI5qY5f0wQxxmiEEyTxxmYZb3wwxxmCEGyTxxmIVZ3g/iMFcMZmKW94M4zBWDmZjl/SCOxswShxkE672I2CRAWlqaJGn9+vU+6xQXF0tSs2v3T+9v27ZtPpcEtKa/5jCYGzPL+2GGOMwQg2SeOMzCLO+HGeIwQwySeeIwC7O8H8RhrhjMxCzvB3GYKwYzMcv7QRyNmSUOM4j5JMDo0aMlnUoCeLt7X11d7bloHzNmTLP9ZWdnKyEhQSdOnNBHH33ktc7y5ctb3B8AAAAAAGYTsUmAK664QqmpqTIMQ3PmzGlSPnfuXDU0NCgtLU2jRo1qtr+uXbtq4sSJnrb19fWNypctW6bNmzdLkqZMmRL4CwAAAAAAIMQiNgnQqVMnPfbYY5Kkp556Sr/73e/09ddfq7y8XIWFhZo7d64kafbs2erYsaOn3axZs5SRkaGMjIwmfT766KPq0KGDPvvsM02bNk0bN27U3r179fLLL+uWW26RJE2dOlWZmZkheIUAAAAAAARXxJ4OIEkzZszQ2rVr9eqrryo/P1/5+fmNynNzc3XHHXc0eszhcKisrMxrfxdffLHmz5+vu+++W0uWLNGSJUsalQ8bNkwLFiwI7osAAAAAACBEInYmgHTqCISXX35Zzz//vLKzsz1H9+Xk5KioqEgvvPBCi49JcJsxY4ZWrlypa6+9VsnJyUpISNCgQYNUUFCgdevWqUePHu30agAAAAAAaF8WwzCMcAcRbTp16qQTJ04oLi7O53GCTqfTcyxhuBiGocrKSqWmprY6WRJsZng/zBKHGWIwSxyMUXPGYYYYzBIHY5Q4zB4DY5Q4zB4DY5Q4zB5HJI1Rh8OhhoYGdezYscked6cjCdAO4uPj1dDQEO4wAAAAAAAxJi4uTi6Xy2d5RO8JYFadO3fW8ePHFR8fr969e4c7HAAAAABAlKuqqpLL5VLnzp391mMmAAAAAAAAMSKiNwYEAAAAAAAtRxIAAAAAAIAYQRIAAAAAAIAYQRIAAAAAAIAYQRIAAAAAAIAYQRIgxhiGoRdeeEEjRoxQUlKSkpKSNGLECL3wwgvioAiYwV//+leNHTtWvXr1Urdu3TR8+HA99dRTOnHihN92q1ev1oQJE9S7d2916dJFGRkZmj17to4cORKiyBFLGKcIhX379ikvL08jRozQWWedpT59+mj06NH6r//6L9XV1fltyxiF2bV1rG3ZskVTp05VSkqKEhIS1L9/f/3Hf/yH9u3bF6LIEQsCuWZq6+dvSBmIGQ0NDcatt95qSPL69bOf/cxoaGgId5iIUpdccokxaNAgv3Uefvhhn+Nz9OjRxvHjx722W7BggWGxWLy2y8zMNKqrq9vjJSHC7d+/33jssceMMWPGGGlpaUb37t2NESNGGPfee6/hdDp9tmOcIhTWrFljJCcn+xxrAwcONPbu3eu1LWMU4fbcc88ZkowZM2Z4LW/rWHvrrbeMhIQEr+1SU1ONHTt2tOfLQgRavny5z8/D079qa2s9bQK5Zmrr52+okQSIIXa73TMI8/PzjfLycqO8vNzIz8/3PD5//vxwh4kotHnzZkOS3yTAu+++6xmH99xzj7FlyxZj165dxjPPPGPEx8cbkowHHnjAa98dOnQwJBlTpkwx1q9fb+zdu9d48cUXje7duxuSjBtvvLE9Xx4iUHl5uZGenu7zF/VZZ51lvPnmm03aMU4RCvX19UZGRobnguj99983qqurDYfDYSxatMiTHJg8eXKTtoxRhFtZWZnRtWtXn0mAto61yspKT/mYMWOMlStXGvv27TOWLl1qpKWlGZKMyy+/nBtaaOQPf/hDq5MAbb1mauvnbziQBIgRdXV1RmpqqiHJmDlzZpPyBx980JNFra+vD0OEiFZff/21MWTIkGaTAJdffrkhybj55pub/AJ3fxh36dLF2LdvX6OyG2+80ZBkXHnllUZdXV2jsnfeecfzYbxt27bgvShEtIaGBiMnJ8eQZPTs2dNYtGiRsXv3bqO6utpYtmyZMWzYMEOS0b17d+Obb75p1JZxilBYvHixIclISEgw9uzZ06T8rbfe8oyZM2cDMEYRTvX19Z4x6CsJ0Nax9sADD3hmwRw8eLBR2aZNmzwzBN59992gvy5ErrvuusuQZDz22GMtqh/INVNbP3/DgSRAjPjoo48MSUZcXJzXKVb79+834uLiDEnGqlWrwhAhosnWrVuNX//618aYMWM848pfEmDHjh2eOlu2bGlSfvLkSaNXr16GJKOoqMjz+JEjRzy/9P/2t7957Xv48OGGJKOgoCA4Lw4Rb8OGDZ7x9sEHHzQpP3LkiDFo0CBDkvGLX/zC8zjjFKHyyCOPGJKMSZMmeS13uVyeO60rVqzwPM4YRbi5x66vJEBbx1pDQ4Nx7rnnGpKMP/7xj17bTZo0yZBk5ObmBu8FIeJdc801hiTj9ddfb1H9tl4ztfXzN1zYGDBGrF69WpI0atQo9erVq0l5cnKyRo4c2agu0FYbN27UM888o5UrV6qhoaHZ+u4xl56erosuuqhJeXx8vMaPH9+oriSVlJSorq5OCQkJ+sEPfuC17+uuu65JO8S2rVu3SpIyMjL0wx/+sEl5t27ddN9990k6NcbcGKcIlR07dkiS+vXr57U8Li5OPXr0kCQdOnTI8zhjFOG0du1azZkzR6mpqZowYYLXOm0dazt37tTu3bsblbekHVBWViZJGjp0aIvqt/Waqa2fv+FCEiBGVFRUSJJycnJ81snOzm5UF2ir66+/Xlu3bvV8Pf74437rnz4+LRaL1zrexqf7+6FDh6pbt24tbofY9vXXX0uSLrzwQp/j7YILLpAkffPNN57HGKcIlcWLF8swDP3hD3/wWr5jxw45HA5J0pAhQzyPM0YRLocPH9a0adPU0NCgoqIirxdPUtvHmvv75ORkz+ezv3YGJ15Bp8alw+FQx44dtX//fk2YMEHp6enq2bOnrrnmGs2ePVvHjh1r1Kat10xt/fwNlw7hDgCh4XQ6Jcnnh7J06oNVkqqqqkISE6JXz5491bNnT8+/N27c6Ld+W8cn4xptMXHiRA0ZMkT9+/f3Wefvf/+7JDWqwzhFuBiGodraWlVXV2vNmjV68sknJUk33HCDBg8e7KnHGEW45OXlaefOnbr33ns1btw4vfrqq17rhWKM1tfX6/Dhw57ZMohd7lkAJ0+e1OjRoxuVrV69WqtXr9brr7+upUuXeu7ex8rnKDMBYoR7YJ5+YXYm96B11wVCpa3jszXtDh061Oy52ogNWVlZuuWWWzwZ+TPt2rVLTz31lCTppptu8jzOOEW4/O1vf1OPHj3Uv39/5ebmqry8XL/61a/00ksvNarHGEU4LFmyRC+99JIyMzM1Z84cv3XbOtZa0+70+oht7iSAYRgaOnSo3nrrLVVVVWnHjh1asGCBunfvrvLyct166606efKkpNB8jpphfJIEiBEHDx6UJCUmJvqs4y7bv39/SGIC3No6PlvTTpKqq6sDihPRb+3atRo9erSqqqrUr18/5eXlecoYpzCTNWvW6PPPP2/0GGMUobZnzx7NmDFDHTt21CuvvKIuXbr4rd/WsdaSdp07d1Zc3KlLG/6WhXRqOcCQIUM0fvx4rV69WhMmTNA555yj/v3766677tKaNWsUFxenrVu36k9/+pOk0HyOmmF8kgSIEe6sVG1trc86NTU1ksT0KYRcW8dna9pJUlJSUkBxInrt3LlTt956q6666irt3LlTqamp+uCDD3TWWWd56jBOES6TJk1SQ0ODnE6nVqxYoSuuuEJffPGF/u3f/k3btm3z1GOMIpQaGhr085//XIcOHdLjjz+uSy65pNk2bR1rLWl39OhRz2bE/C0LSbrnnnu0bds2LVu2zOs0/eHDh+tnP/uZJOnDDz+UFJrPUTOMT5IAMaJPnz6Svs9SeeMuc9cFQqWt47M17RITE/1mZxGb6uvrVVhYqEGDBum1116TJE2dOlVbt27VwIEDG9VlnCKcLBaLevfurR/+8If68MMPNXjwYB07dkxPP/20pw5jFKH0hz/8QR9//LGuuuoqPfDAAy1q09ax1pp2p9cHmjNq1ChJUmlpqaTQfI6aYXySBIgRVqtVkv8pfAcOHJAkpaSkhCQmwK2t45NxjUBs3rxZl19+uQoKClRfX69Ro0bpk08+0Wuvveb1jgHjFGbRuXNnz92rzZs3ex5njCJUduzYoYcffljdu3fXSy+9pPj4+Ba1C8UY7dixo9/N2YDT9e3bV9L3YytWPkdJAsSItLQ0SdL69et91ikuLpYkpaamhiQmwM09PouLi30e6+NtfLrbbdu2zef0K8Y1vPniiy90zTXXaOvWrerWrZtefvllrV27VldeeaXPNoxThEpaWpoSExM901O9cf/BeeLEiUbtJMYo2t/u3btVX1+v2tpanX/++bJYLI2+XnzxRUnSwoULPY/99a9/bfNYc7c7ePCgysvLm23n64g2xI4TJ07ovffe03vvved3ir77uNWMjAxJbb9mauvnb7iQBIgR7mMx1q9f7zVDVV1d7RmYY8aMCWlswNVXXy1Jqqys1JYtW5qUu1wuvf/++5Iaj8/s7GwlJCToxIkT+uijj7z2vXz58ibtENtqa2v14x//WDU1NcrIyFBJSYluu+22Zv9oZJwiVKxWq44ePap//OMfPuts375dknTxxRd7HmOMwuzaOtb69u2r8847T5K0bNmyFrdD7OrQoYN+9atfafz48Z7lft64j7HOzMyU1PZrprZ+/oaNgZhQV1dnpKamGpKM3/zmN03KZ86caUgy0tLSjPr6+jBEiGi2aNEiQ5IxaNAgn3WysrIMScaNN95oNDQ0NCp79tlnDUlG165djf379zcqmzJliiHJGDlypFFXV9eo7N133zUkGZKML7/8MngvCBFt4cKFhiTj7LPPNvbt29eqtoxThMLUqVMNScZFF11knDx5skn53r17jZ49exqSDLvd3qiMMQoz+PnPf25IMmbMmNGkrK1j7cEHHzQkGRdccIFx8ODBRmWbNm0yEhISDEnG8uXLg/56EJncY2bAgAFGTU1Nk/Ly8nKjY8eOhiTjk08+MQwjsGumtn7+hgNJgBiyYMECzwdrYWGhsWPHDqOsrMwoKCjwPL5w4cJwh4ko1JIkwLJlyzzj8Fe/+pWxbds249tvvzXmzZtndOjQwZBkzJo1q0m7LVu2eMpvuukmY8OGDYbD4TBeeuklo3v37oYkY+rUqe358hBhRo8ebUgyZs6c2eq2jFOEwubNm424uDhDkvHDH/7QWLdunXHo0CHD4XAYf/nLX4wLLrjAkGQMHz68yUUUYxRm4C8J0Nax5nA4jKSkJEOSMXbsWGP16tXGvn37jL/85S9Genq6IckYNWpUk4svxK6dO3d6EqbZ2dnGqlWrjJqaGmPnzp3GokWLjOTkZEOSMW3atEbt2nrN1NbP33AgCRBDGhoajFtvvdUzOM/8ys3N5YMT7aIlSQDDMIyHH37Y5/gcN25ckz923Z577jnDYrF4bTds2DDj0KFD7fGyEKH69evnc5yd+dW3b98m7RmnCIXf/e53PseLJGPIkCFGaWmp17aMUYSbvySAYbR9rL399ttGp06dvLY799xzjW+//bY9XxYi0LvvvuuZJeLta8SIEU3uzAdyzdTWz99QIwkQYxoaGoznn3/eyM7ONhITE43ExEQjJyfHKCoqIgGAdtPSJIBhGMabb75pjB492ujRo4fRpUsXY9iwYcbTTz9tnDhxwm+7VatWGddee62RnJxsJCQkGIMGDTIKCgqMo0ePButlIEp07do1oCSAYTBOERolJSXG5MmTjczMTKNLly7GeeedZ/z4xz82nn766WaX7jFGEU7NJQEMo+1jbfPmzcZNN91k9O7d2+jUqZPRr18/47777jOqq6uD/TIQJb799lvjjjvuMIYOHWp069bN6Nevn/HTn/7UWLhwoc/P0kCumdr6+RtKFsPwsX0hAAAAAACIKpwOAAAAAABAjCAJAAAAAABAjCAJAAAAAABAjCAJAAAAAABAjCAJAAAAAABAjCAJAAAAAABAjCAJAAAAAABAjCAJAAAAAABAjCAJAAAAAABAjCAJAAAAAABAjCAJAAAAAABAjCAJAAAAAABAjCAJAAAAAABAjCAJAAAAAABAjCAJAAAAAABAjPj/ARcHU5R+Sf+LAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 1200x1200 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1200x1200 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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l14Z46aWXjDGlw4xCQ0ONJPPPf/7TPP7449YwIkkmPj7e5Rw//PCDufrqq20fc5cuXcz+/fs95nDVVVcZSaZTp04uxx0OhxU/depUl7bly5dbbenp6eamm27yeu0nn3zSlJSUmGeeecbrXK4rr7zSnDp1yi23du3aGUmmT58+LsePHj1qxc6bN89MnTrV4xodzq9Zs2Z5/Rm88sorpk6dOrbPX7169Tyuo1H2OUpOTjZ33HGHS9zAgQNNSUmJNRSte/fuXvMwxpgRI0YYSaZOnTrmwIEDtn0BABeeu+++20gyv/vd7/yOda6j1KRJE9t+W7dutf5OLViwwOfzZ2VlWXF2w75fe+01vz/h9fa+r+x7v9NHHhw4cMA8+OCDpmXLliYkJMSEh4ebq6++2rzxxhteRwesXbvWvPvuu7Zf3333ncfYczXy4MiRI7bvSew+QS67jpi3tcaMMS5rizkcjjPO+UxGHhw6dMhMmjTJdOnSxdSvX9/UrVvXdOzY0SQmJpodO3Z4jSsuLjbNmjUzkkxERITtzyU1NdXK709/+pNf+ZXnyy+/tM7tbYq2k/OT+65du1rHVq1aZcW/+OKLXmOff/55q9/atWvd2s/kdXM2f7edgoRqx1v12N/KdWU5feRBcXGxUlNT1bt3b+vY6SuHRkdHq1mzZn5dZ/r06dqyZYvPq63++uuvSklJUUpKit58801JpSuRDho0SBMmTNBFF13k1/Wdyu604MvIgy1btmjGjBmSpFq1alk7Yfz44486efKkJOmdd97R+vXrFRAQoH79+qljx44aMGCAdY60tDT17dvXWom4bdu26t27t5o3b669e/fqP//5j44cOaK0tDSNGDFCq1atcvkk4tSpU9bqr6fn7KxASq7bN57edtddd+nbb7/VZZddpv79+6tmzZr68MMPre1CZ86cqZ9//llz5sxRRESEBg0apLZt22rTpk1asGCBpNLXQXJysq6//nrrvCdOnNCOHTs8Xr/sirWvvvqqUlNTVbNmTSUkJOiyyy5TUVGR/v3vf1vb2/z5z3/W3Xff7bYF6ZtvvqmHH35YUunqvTfffLPi4+MVHBysLVu2aOHChcrPz9fx48d177336rvvvvP6PDz99NNav369atasqWuuuUbt27fXjTfeqICAAMXFxen7779XZmamvNm0aZM+/PBDSdIjjzyiJk2aeO0LALgwOUceXHLJJZJKR5Xu2rVL2dnZatKkiVq1aqUaNTwPAHa+F4iJibG9RtlPFe1G1p0uIiJCQUFBOnXqlNuo0bLKtp2tv2Xp6ekaMGCADh8+bB0rKCjQmjVrtGbNGr399ttKTk522yGhZ8+e6tmz51nJqbI0aNBAx48fdzk2bdo0Pf/88+XGtmnTxupn99w73x8FBgYqPDz8DLI9M8uWLdOIESPcdl3bsmWLtmzZor///e968cUX9cgjj7iNoqhRo4aGDx+ul156STk5OVq1apXLe+SyzuYuC4cOHbK+L+8e5qKLLlJWVpbLzgfO98uS9Pvf/95rbEJCgh5//HFJpfcKp7+Oz+R1c05+t/0qNeCcKLsyfdmvyprP5IndyIOSkhITHR3tcnzatGku8YMHD3ZpHzp0qDHGewXa08gDY0pXUH3yySddFiSpyFft2rXNP/7xD79XES0qKjK1a9c2UukiI+VZvHixiY2Nta47efJkq23u3LkuOXXs2NFs2LDB7RyHDx+2FoupW7eumTNnjtun94cOHTLt27f3+gnDd999Z7W98cYbLm1ld1o4/VPwIUOGWG2BgYFuz9mJEyfMJZdc4vI4hgwZYg4fPuxynokTJ1rtL7zwgktb2dfzBx984NL20ksvuZz7sssuM1u3bnXpk5OT4/Icn74wVG5urjXnr3nz5mb37t1uz/H27dutRTDloWpb9jmSZK6++mqPVfKBAwdaz5WnERbGGDNgwAAjyURGRpq8vDyPfQAAFzbn3617773X3HPPPdb8defXRRddZJ555hnzyy+/uMVed911RipdtNlO2ZEHf/7zn/3KzzlCTpJZsmSJW/umTZusv61XXnmlz+fduXOny6r9kZGR1sKQnnZbiIuLM5JMjx49zAsvvGDmzZtnHnjgAdO4cWOrT48ePbz+za2Iqtxtoez7Yl9Wzbezbds26/3yjTfeWOn5+Try4JtvvrFGpNarV888/PDDZvbs2WbOnDlmwoQJLqNCnaNzT/ftt99afe655x6v13KuCdesWbNK32Xhxx9/tEatHDt2zGu/vLw86zGVfd7L7nCQm5vrNT4nJ8fr/ZQ3/rxuztbvthPFg2qo7Aq9Zb/KDo2pbHbFA2OMGTZsmMvxQYMGWbElJSWmUaNGLu0vv/yyMcb/4oGTc1XSESNGuJ3bn68ZM2b49Tykp6dbse3atTOvv/6629crr7xi7rvvPnPFFVe4XOv3v/+9yx+ihx56yGpr0qSJyc7O9njNe++91yp4rFmzxmtuZacYnD4Uqezwto0bN7q0OaciREdHu52zefPmVtyrr77q8bqJiYkuN9WeFm763//+Z/V58803Xdpmzpxptf34448ubWX/g2vRooXX/6yfeOIJq19KSopL21tvvWW1eVqcxun3v/+99YbtdGWna3Tq1Mnrf8xlF8LxNE2m7PSdf/zjH15zAQBcuH755Ref36dcfvnlbu8PHn30Ua9/08sqe7MyevRov3I8dOiQadWqlZFKF3676667zOzZs817771nHnjgAWurusjISLe/3b7wdcFEqXSB7dOLA3v37jWdOnWy+vz73//2OwdvztfiwbZt28x7771nXnvtNTNy5Ejrw67o6Gjz008/VXp+vhQPiouLrampHTp0MAcPHnTrs2/fPmuRwdq1a3vcZaCkpMS0bt3aSN6nLpTdVayypyz448knn7TyeP31163j48ePN1LpYot2W5KfOnXKmsbsbRH60/nzujnbv9sUD6ohb2seXHLJJWftmuUVD1555RWX4+Hh4dYvxk8//eQW55w/U9HiQVnFxcXm22+/NW+++ab54x//aK688spy57Y7v4KCgszevXt9vtbbb79doSLFvffeawoKClzO1atXL6t92bJlHq+3f/9+ayvMJ5980ja3snOgbr/9dpe2P/7xj0aSqVmzplseTZs2NZL7aszZ2dnW+Tp27Oi1glt2q6DTRwU4LVy40Orz3//+16Vt9OjRRirdsub0/0yd/7lJMuvWrfP62CdNmmT1O31v4e3bt5tVq1aZ1atX21ahnX+UBg8e7NbmfI4CAwPNli1bvJ7jhRde8FrEKC4uNpdffrmRZNq0aVMlb0oAAFVvy5YtLu8RbrvtNvPdd9+ZX375xezcudPMnTvXZURd2Q9kjHHdbaF79+4eP8X88ssvrU8PJZkBAwb4nWdubq655pprvL636dq1q8nIyKjQc+Br8aBVq1ZeRxWUfR579+5doTw8OV+LB3/5y1/cfkbXXXedycrKOiv5+VI8WLp0qdXfbl2Dsh+MOj9gPF3Zm/LT30saY8yLL77odp9xLpWUlJh//OMfVg6RkZEua8A5R/OGhYWVe66wsDAjyQwfPtyna/v7ujmbv9useVANRUREeDz+888/q7CwUDVr1jzHGbmve5Cbm6sff/xRbdu2dVvvICQkRJdeemmlXbtGjRrq2rWrunbtah07deqU0tLStHr1an322Wdau3atx9hTp07pnXfe0dNPP+3Ttcqud2Cndu3aiomJUf/+/fWHP/xBl19+uUt7SUmJNm/eLKl0vuO1117r8TzvvPOOtftAUFCQZs2a5fWaBQUF1vdxcXEe8+7SpYvL6+Pw4cPWPMjTcyy73sCdd97pcSVfqXQ+olS6XkH79u099im7hoC3dRUuu+wyl/mdx44ds+aHXXbZZfrd737n8dxlc7j44ovd5vS1bdtWbdu29RpbUFCgDz/80NoR44orrnBpL/sc9e3bVx06dPB6rrLPe2Zmpsv6EgsWLLB2vHjxxRcVFMR/rwDwW7Rnzx5rbZ5HH31UTz/9tPU39pJLLtEll1yi66+/XldeeaV27NihJUuWaM2aNbr66qslSb/73e80fvx4/f3vf1dKSoo6dOige++9V+3atVNOTo7WrFmjDz/8UIGBgQoODlZRUZHXHau8KS4u1muvvaavvvrKa5/09HTNmDFD06ZNU61atSr4bNibOHGiAgMDPbZ16NBBN954oz777DNt2bKl0q7p69pa54Ply5frwQcf1BtvvKGwsLBzfv2lS5dKKl1zrE2bNl77de7cWS1atNCePXu0Zs0aa52qskaMGGG9X//Pf/7jtu6Bc72Dyt5lwRd79uzRxIkTrZ0eQkJCtGDBAtWpU8fqk5eXJ6n0HqE8zt8nf3ZJ8dVZ/92uUMkBZ51zCNDpX6fP964s5Y08KCwstIZHOb/eeecdY4zrfquSTM+ePa3zVsbIA19s2LDBxMTEeLxWv379fD7PZZddZqTSIUdnMl99+/bt1vX/8pe/eO3XoUOHCo10KDs14Ndff7V2KEhMTHQ5f9mK8Ok7R5Rd7TUtLc1jfidOnLBGRjzyyCNeH8f1119vJJmLL77Y5/iyq9JOnz7d67lLSkpMVFSUkWRGjBjhtd/JkyfNpk2bzPz5880LL7xg7r77bnPllVe6fDIjySxfvtwlruxzVN5Ug7KfBpXd+aGwsNAaRdGrV69Kn4cHALjwlP37c/rf7+PHj5sxY8Z4fR9Qs2ZN88EHH1hz3m+99Vafr1tSUuJy7muvvdZ88cUX5uDBgyYnJ8d89dVXZvjw4S6fbv/6669+PTZfRx58++23tueZNm2a1dduHvn54kzXPCgpKTEOh8OsWbPGDB061DpX586d/f4ZlZefLyMPyo6y9fXLbp59586djVQ6daHsNNkDBw5Y8edyysKxY8fMY489Zg31l0pHXycnJ7v1HTlypJFkQkNDyz1vrVq1zsrIg3Pxu+15mVdUuV69enk8vnjxYr/Pddttt6lRo0YuX6d/cl2e4OBgt09snfuOfvPNNy7H7T5B9uarr75y+3J+2uyL7t27Wyv+n+7gwYM+naOgoMD6BL1t27aqV6+ez9c/XdnV+5178J7u8OHDtiuh2in78/vuu+9UVFQkyX10gS87LdSuXdvriILNmzdbIyO87TxhjLFGPpx+/bS0NCvebqcHb6vqSlJGRoYcDofXHL777jvdd999ioyMVNeuXTVs2DA99thj+vjjj1WjRg1NnDhR1113ndXf7jny9rNyKrv6btkdF9555x1rFMVLL73kdRQHAABO1157rfWpX9m/RZJUt25dzZkzR8nJyRoxYoTi4+MVEhKi6OhojRkzRmlpabrhhht04sQJSXLbjcDO559/rn//+9+SpLvvvlvLly/XNddco6ioKIWHh+uqq67Shx9+qGeeeUZS6Ur6Zfezr0zNmze3bXfuViFJu3btOis5nE8CAgIUGRmpXr16af78+ZowYYKk0k+S33///XOeT3Z2tt8xzk/oPRkxYoQkWbsuOH322WfW97feeqvf16yIFStWqEOHDnrhhRes0b/XX3+9tm7dqoSEBLf+zl3eTp48qcLCQq/nzc/Pt3ZpiI6OrtScz8XvNuNqq6l+/frprbfecjs+Z84cPfbYYz4PiT516pSWLFni9otakaFNV111lctQr3Xr1umXX35xu8nv0aOH3+e+/vrrra2JnCIjI3Xw4EGfb8S6d++uunXrWn9I/ZWenm7dhJ9+o+sv55uAgIAAl+kWZaWlpVnfz507V6NGjarQtey2lnTmER0d7bZ1pbOta9euXl9PZc/tbYhYZmamVaCpyDaRtWrV8lq8OD2Hsuc3xmjatGn661//KmOM2rVrp2HDhul3v/udunbtqsaNG1uvHedQ0FatWrlNe3DmERkZqaZNm3rNQyrdzsY5RNRZPDh58qSeeuopSaV/0E4vsgEA4EmNGjXUqlUrbdmyRTk5OR77JCQkeLxRkaS9e/da39tN3zvdO++8I6l0e79XXnnFa7/HH39cf//735WVlaV33nlH999/v8/X8JW3KQtOxcXF1vcU5t399a9/1euvvy5JWrNmje68885zev1Tp05JKn1/5usUYbth/cOHD7e2MZw/f7417dc5ZSEuLs6nbdTPREFBgR566CG98cYb1rHOnTvrb3/7m/r37+81ruz77CNHjigqKspjvyNHjljfV/YWqOfid5viQTV100036aKLLnL71Pynn35SUlKSHnzwQZ/O89///tdjha9169Z+53R6UWD79u364osvrP84nCoy8iA6OtqteHDo0CHt3LnT51yPHz+uX375xe14efskOznnq0vun077y3lD2q5dO9WtW9djH+fevJLUsGHDCl/LmXdoaKjbmwdnHqc/ntzcXO3Zs0eS9xEFkpSSkiJJtqNVfCleNGjQQBdffLHHtq5du9rO1XSe37n2hdM777yjyZMnS5JeffVVJSYmenwTUlxcbK0/4akAUvY5Ku+NSY0aNdS0aVPt3r1bGRkZkqSZM2fq4MGDCg4O1rRp02zjAQAoy/keqn79+n7Hlv0QomPHjj7H/fTTT5Ls36NIpTcgl112mRYvXuyyh31l2rNnj7p06eK1vexog0aNGp2VHKqjRx55RBkZGeratav+/Oc/e+3XuHFjhYeHKzc3VwcOHDiHGZZyfiCTn5/vMsqzolq0aKErr7xS69ev1yeffKK///3v+uWXX6xRCMOGDTurRaSSkhKNGTNG//nPfySVjgCaMWOG/vCHP5Rb6CpbPNiyZYvX4sH3339vfV/ZxYNz8bvNtIVqKiQkxBqKdLq//OUv+vLLL8s9x4EDB3TXXXd5bLv55pv9zslTUWDmzJku/7744ou9/rLYcX4yfLpRo0bp5MmTPp1jzpw51hD5snxdvLHsTfCZjDwou1iiXRGi7Kf9+/btsz3npk2bNHXqVE2dOtVa3M/JmXfXrl1d/mPLzs62znv64ym7WKLdojPOc3fv3t3rf9bOPgEBAW7PddkCQdnFEvPy8qwFDMurIDvPHx8fr9DQUElSUVGR/vrXv0oqLbQ98MADXv9T/+yzz6zRKKc/1rLPka8FI2cRJTMzU9nZ2Zo+fbokafz48W4FEgDAb09CQoI6dOig8ePH2/Y7deqU9Wa/7PD89PR0629+2Slyp/vggw8klRbo/Rn16VzM8fjx4+X2dX4AdbYW6y77wY0nzimyERERLlMHL3Tff/+9PvroI3344Ye2/X755Rfrk+wGDRqci9RcOEeO7tq1y3aovjFGy5cv17Jly6zXvDfOqQu5ublatWqVlixZYo0MHjZsWCVl7tkTTzxhFQ46duyoLVu26N577y23cCC53m8sWbLEa7/k5GTre7vCWUWci99tigfV2IQJE1z+mDgVFBRo4MCBmjZtmscb65KSEn300Ufq3bu3NVe8rLCwMN1yyy1+5xMWFuY2vLzsfCSpYlMWJGnkyJEej6empqpfv35avHixx8KAVHoD+Nxzz+mhhx7y2D58+HCfcij7CfeZ/DLv3LnT+qW1uyHt3Lmz9f2KFSu89svLy9Ott96qp556SnPnznWpUp48eVLbtm2TVLEpA57inHJzc62Kv90NvvN5a9euncs6Eb/88ou2b9/u8frO4kp55y4pKbHOX7bfjh07vE6VKCsjI0OPPfaY9e/Tiwdln4eKFA+mTZumvLw81a9f3xoFAQD4bWvXrp2+//57vf3227brLs2bN8+6KSr7qW3t2rX11FNP6amnntK8efM8xubm5mrRokWSSj8Q8me3hU6dOkkq3cXrhx9+8NovOzvb+jvpjKlsM2bM8Pr+btOmTdaN1nXXXfebmrbgfP+/fft2j+/lnVauXCljjKTyP4w5G6655hpJpSMP3nzzTa/9li1bpuuuu04JCQku0208ufXWW62f9X/+8x9rh4OzPWXhyJEj1oeirVu31v/+979y1+Qoq0OHDlaB6/PPP3eZcuNUXFxs/d62aNHCdtpuRZyL322KB9VYvXr19OGHH3r8g1BQUKBJkyYpMjJSgwcP1vjx43XffffpuuuuU/PmzTVixAivlb0XXnjBbd63r07fsvF0FS0e9OrVSzfeeKPHtpSUFF1//fVq3ry5rr32Wt1111166KGHdPvtt6tPnz6Kjo7W5MmTrf88yxo6dKjXNQfKOnHihHWjW95Qn/L4ekPapk0b6z+ZhQsX6r333nPr8/PPP6tv377WTfzp613YLWjoS/EgLCzM66flZT8NsFss0dnv9D5lF0u0W6TQ7g/Bzp07rcpo2X7OhWYkacOGDW4/++LiYi1cuFBXXnmly3Cs+Ph4r3n4OtrEWTw4ceKEtbXmE0888ZsaTgkA8M75oUVRUZFGjhzp8jfLafPmzdZw9CZNmliftkqlNy7OKZsvvPCC281WQUGBxo4dq/z8fNWoUUNPPPGEX/ndcccd1ve33367x/UWTpw4oTvuuMP6kGrMmDF+XcNXO3bs0MSJE91utPbs2aPRo0db/z4b6y1UZ84PO3799VdNnDjRKjKVtW/fPut5qVmzps8fllWmW265xRpxPHXqVI9bnh88eFAPPPCApNLXet++fW3P2aRJE/Xp00dS6VoHzu0gz/aUhXnz5lkLI77yyit+3ysFBARY08p3795tjUwta/r06dZ7+gcffLDSH885+d32a28GVImPP/7YZYuQM/n64x//aIqLi92uUd5WjU6zZ8+2PX96erpLf3+2aszMzDSXXHJJpTxOSaZly5YmKyvLp+d4zZo1VtyYMWN8/tl4MnHiRCPJBAYGmpMnT9r2LbtNkyTTv39/M2nSJPPMM8+YYcOGmaCgIKvtoYcectsC8OWXX7bad+7c6dJ2yy23GEkmJibG7botW7a0tnDx5plnnrHO7XA4PPb58ccfrT6vv/66S9trr73mNbfbbrvNSDINGjTw+Hp0mjt3rnWO1NRU6/jJkyddnptevXqZp556ykybNs3cdddd5uKLL7ba6tSpY30/cuRIs2TJErfnKDo62msOp/vXv/7l8jNr2rSp+eWXX3yOBwBc+MaPH2/9nYiLizPTpk0z8+fPN//4xz/MH/7wBxMYGGik0q2hly1b5ha/bNkyKz4sLMw89dRT5uOPPzavv/666dixo9X27LPPerx+2fdfnt5zjRo1yuX8f/7zn83cuXPNvHnzzKRJk8xFF11ktffp08ecOnXKr8fvy1aNMTEx1t/onj17munTp5v33nvPPPjggyYiIsK6/rhx4/y6dmUo7/mrjPPabbn366+/urwnbt++vXn++efNf/7zH/POO++YBx54wGUL9eeff77S8/Nlq0ZjjPnkk0+smKCgIHPvvfeat99+23z00Udm8uTJpnHjxkaSqVGjhlm6dKlP53zzzTfd3tenpKT4lb+/P7dbb73Vev/++eefm6VLl5b7tWHDBpdznDx50rRr187K4bbbbjMffPCBee+996zzO3+e/rx39GeLz7P9u03x4Dzx1VdfmcjIyArfSAcGBppJkyZ5vVHztXiwc+dOr9eoV6+e2wvQn+KBMcZkZWWZK6644owLB5dddpnJzMz0+fmdMWOGFfvaa6/5HOeJ87ns1KmTT/1fffVVa79XT1+hoaHm6aefdiscGPN/e8qGhYW5tcfFxRlJ5oYbbnA5npuba5170qRJXvO64YYbvP7hd3rvvfesc61fv96l7Y477rAKBKfn1qZNGyPJXHPNNV7PbYwxDzzwgJFK97MuKChwaSu797Onr8aNG5tFixaZ66+/3uX4k08+We5zZGflypUu55szZ47PsQCA34aCggK3vz+e3jd98sknXs/x3HPPmRo1aniNf+SRRzy+NzCm/JuogoIC86c//ckEBwd7PX9AQIC58847zdGjR/1+/L4UD6666irz2WefudwEn/41cuRIU1hY6Pf1z1RVFw+MMWbbtm3W+xRvXzVq1DDPPPOM19fBmeTna/HAGGPefvtt29dSaGioefvtt30+X3Z2tsuHRHFxcT4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\n",
+      "text/plain": [
+       "<Figure size 1200x1200 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "datamc.plot_datamc_all()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "70efe610-3668-43e2-8bc4-d0eaaaac5d2d",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<pocket_coffea.utils.plot_utils.PlotManager at 0x7f3bdef04d90>"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from pocket_coffea.utils.plot_utils import PlotManager\n",
+    "\n",
+    "plotter = PlotManager(o[\"variables\"])\n",
+    "plotter"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "c922cbf7-0bdd-45fc-843d-5667c9e6a968",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "#plotter.plot_datamc_all()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8d712bd2-e9be-4410-aa27-f06b6b057460",
+   "metadata": {},
    "outputs": [],
    "source": []
   }
diff --git a/pocket_coffea/utils/plot_utils.py b/pocket_coffea/utils/plot_utils.py
index 9e5d539f..45f9afc3 100644
--- a/pocket_coffea/utils/plot_utils.py
+++ b/pocket_coffea/utils/plot_utils.py
@@ -15,13 +15,25 @@ import mplhep as hep
 from ..parameters.lumi import lumi, femtobarn
 from ..parameters.plotting import *
 
+
+class PlotManager:
+    '''This class manages multiple DataMC objects and their plotting.'''
+    def __init__(self, hist_cfg, data_key="DATA"):
+        self.datamc_objects = {}
+        for name, h_dict in hist_cfg.items():
+            self.datamc_objects[name] = DataMC(h_dict, name, data_key=data_key)
+
+    def plot_datamc_all(self):
+        for name, datamc in self.datamc_objects.items():
+            datamc.plot_datamc_all(self)
+
+
 class DataMC:
     '''This class handles the plotting of 1D data/MC histograms.'''
-    def __init__(self, h_dict, name, data_key="DATA", spliteras=False):
+    def __init__(self, h_dict, name, data_key="DATA"):
         self.h_dict = h_dict
         self.name = name
         self.data_key = data_key
-        self.spliteras = spliteras
         assert type(h_dict) == dict, "The DataMC object receives a dictionary of hist.Hist objects as argument."
         self.define_samples()
         assert self.dense_dim == 1, f"Histograms with dense dimension {self.dense_dim} cannot be plotted. Only 1D histograms are supported."
@@ -117,10 +129,11 @@ class DataMC:
         self.xedges = self.xaxis.edges
         self.xbinwidth = np.ediff1d(self.xedges)
         self.is_mc_only = True if len(self.samples_data) == 0 else False
-        if not self.is_mc_only:
+        self.is_data_only = True if len(self.samples_mc) == 0 else False
+        if self.is_data_only | (not self.is_mc_only):
             self.lumi = {year : femtobarn(lumi[year]['tot'], digits=1) for year in self.years}
 
-    def build_stacks(self, year, cat):
+    def build_stacks(self, year, cat, spliteras=False):
         slicing_mc = {'year': year, 'cat': cat}
         slicing_mc_nominal = {'year': year, 'cat': cat, 'variation': 'nominal'}
         self.h_dict_mc = {d: self.h_dict[d][slicing_mc] for d in self.samples_mc}
@@ -136,41 +149,34 @@ class DataMC:
         if not self.is_mc_only:
             # Sum over eras if specified as extra argument
             if 'era' in self.categorical_axes_data:
-                if self.spliteras:
+                if spliteras:
                     slicing_data = {'year': year, 'cat': cat}
                 else:
                     slicing_data = {'year': year, 'cat': cat, 'era': sum}
             else:
-                if self.spliteras:
+                if spliteras:
                     raise Exception("No axis 'era' found. Impossible to split data by era.")
                 else:
                     slicing_data = {'year': year, 'cat': cat}
             self.h_dict_data = {d: self.h_dict[d][slicing_data] for d in self.samples_data}
             self.stack_data = hist.Stack.from_dict(self.h_dict_data)
 
-    def plot_datamc(self, year, cat):
-        plt.style.use([hep.style.ROOT, {'font.size': fontsize}])
-        plt.rcParams.update({'font.size': fontsize})
-        fig, (ax, rax) = plt.subplots(2, 1, **opts_figure["total"])
-        fig.subplots_adjust(hspace=0.06)
-        hep.cms.text("Preliminary", fontsize=fontsize, loc=0, ax=ax)
-        hep.cms.lumitext(text=f'{self.lumi[year]}' + r' fb$^{-1}$, 13 TeV,' + f' {year}', fontsize=fontsize, ax=ax)
-        self.stack_mc_nominal.plot(stack=True, histtype='fill', ax=ax)#, color=colors)
-        if not self.is_mc_only:
-            ax.errorbar(
-                self.xcenters, self.stack_sum_data.values(), yerr=np.sqrt(self.stack_sum_data.values()), **opts_data
-            )
-            self.h_dict_data = {d: self.h_dict[d][slicing_data] for d in self.samples_data}
-            self.stack_data = hist.Stack.from_dict(self.h_dict_data)
+    def get_datamc_ratio(self):
+        '''Computes the data/MC ratio and the corresponding uncertainty.'''
+        num = self.stack_sum_data.values()
+        den = self.stack_sum_mc_nominal.values()
+        self.ratio = num / den
+        self.ratio_unc = np.sqrt(num) / den
+        self.ratio_unc[np.isnan(self.ratio_unc)] = np.inf
 
     def define_figure(self, year, ratio=True):
         plt.style.use([hep.style.ROOT, {'font.size': fontsize}])
         plt.rcParams.update({'font.size': fontsize})
         if ratio:
-            fig, (self.ax, self.rax) = plt.subplots(2, 1, **opts_figure["total"])
-            fig.subplots_adjust(hspace=0.06)
+            self.fig, (self.ax, self.rax) = plt.subplots(2, 1, **opts_figure["datamc_ratio"])
+            self.fig.subplots_adjust(hspace=0.06)
         else:
-            fig, self.ax  = plt.subplots(1, 1, **opts_figure["total"])
+            self.fig, self.ax  = plt.subplots(1, 1, **opts_figure["datamc"])
         hep.cms.text("Preliminary", fontsize=fontsize, loc=0, ax=self.ax)
         hep.cms.lumitext(text=f'{self.lumi[year]}' + r' fb$^{-1}$, 13 TeV,' + f' {year}', fontsize=fontsize, ax=self.ax)
 
@@ -180,8 +186,42 @@ class DataMC:
     def plot_data(self):
         self.ax.errorbar(self.xcenters, self.stack_sum_data.values(), yerr=np.sqrt(self.stack_sum_data.values()), **opts_data)
 
-    def plot_datamc(self, year, cat):
-        self.define_figure(year)
-        self.plot_mc()
-        if not self.is_mc_only:
+    def plot_datamc_ratio(self):
+        self.get_datamc_ratio()
+        self.rax.errorbar(self.xcenters, self.ratio, yerr=self.ratio_unc, **opts_data)
+
+    def plot_datamc(self, year=None, ratio=True):
+        if ratio:
+            if self.is_mc_only:
+                raise Exception("The Data/MC ratio cannot be plotted if the histogram is MC only.")
+            if self.is_data_only:
+                raise Exception("The Data/MC ratio cannot be plotted if the histogram is Data only.")
+
+        if not 'fig' in dir(self):
+            self.define_figure(year, ratio=ratio)
+        if (not self.is_mc_only) & (not self.is_data_only):
+            self.plot_mc()
             self.plot_data()
+        elif self.is_mc_only:
+            self.plot_mc()
+        elif self.is_mc_only:
+            self.plot_data()
+
+        if ratio:
+            self.plot_datamc_ratio()
+
+        plt.show(self.fig)
+        plt.close(self.fig)
+
+    def plot_datamc_all(self, ratio=True, spliteras=False):
+        for year in self.years:
+            for cat in self.categories:
+                self.define_figure(year, ratio)
+                self.build_stacks(year, cat, spliteras)
+                self.plot_datamc(year, ratio)
+
+class SystUnc:
+    '''This class handles the systematic uncertainties of 1D MC histograms.'''
+    def __init__(self, stack_mc, name):
+        self.stack_mc = stack_mc
+        self.name = name
-- 
GitLab


From 4d980b1be65ae98319d82adb2117e95227a39f6e Mon Sep 17 00:00:00 2001
From: mmarchegiani <matmarcheg@gmail.com>
Date: Tue, 28 Mar 2023 02:17:23 +0200
Subject: [PATCH 05/24] Refactoring of systematics plotting and formatting

---
 pocket_coffea/utils/plot_utils.py | 308 +++++++++++++++++++++++++++---
 1 file changed, 286 insertions(+), 22 deletions(-)

diff --git a/pocket_coffea/utils/plot_utils.py b/pocket_coffea/utils/plot_utils.py
index 45f9afc3..36eab447 100644
--- a/pocket_coffea/utils/plot_utils.py
+++ b/pocket_coffea/utils/plot_utils.py
@@ -13,12 +13,17 @@ from matplotlib.ticker import MultipleLocator, AutoMinorLocator
 import mplhep as hep
 
 from ..parameters.lumi import lumi, femtobarn
-from ..parameters.plotting import *
+from ..parameters.plotting import style_cfg
 
+class Style:
+    '''This class manages all the style options for Data/MC plots.'''
+    def __init__(self, style_cfg=style_cfg) -> None:
+        for key, item in style_cfg.items():
+            setattr(self, key, item)
 
 class PlotManager:
     '''This class manages multiple DataMC objects and their plotting.'''
-    def __init__(self, hist_cfg, data_key="DATA"):
+    def __init__(self, hist_cfg, data_key="DATA") -> None:
         self.datamc_objects = {}
         for name, h_dict in hist_cfg.items():
             self.datamc_objects[name] = DataMC(h_dict, name, data_key=data_key)
@@ -29,10 +34,16 @@ class PlotManager:
 
 
 class DataMC:
-    '''This class handles the plotting of 1D data/MC histograms.'''
-    def __init__(self, h_dict, name, data_key="DATA"):
+    '''This class handles the plotting of 1D data/MC histograms.
+    The constructor requires as arguments:
+    - h_dict: dictionary of histograms, with each entry corresponding to a different MC sample.
+    - name: name that identifies the DataMC object.
+    - style_cfg: dictionary with style and plotting options.
+    - data_key: prefix for data samples (e.g. default in PocketCoffea: "DATA_SingleEle")'''
+    def __init__(self, h_dict, name, style_cfg=style_cfg, data_key="DATA") -> None:
         self.h_dict = h_dict
         self.name = name
+        self.style = Style(style_cfg)
         self.data_key = data_key
         assert type(h_dict) == dict, "The DataMC object receives a dictionary of hist.Hist objects as argument."
         self.define_samples()
@@ -41,7 +52,7 @@ class DataMC:
 
     @property
     def dense_axes(self):
-        '''Returns the list of dense axes of a histogram.'''
+        '''Returns the list of dense axes of a histogram, defined as the axes that are not categorical axes.'''
         dense_axes_dict = {s : [] for s in self.h_dict.keys()}
 
         for s, h in self.h_dict.items():
@@ -75,10 +86,12 @@ class DataMC:
 
     @property
     def categorical_axes_mc(self):
+        '''Returns the list of categorical axes of a MC histogram.'''
         return self._categorical_axes(mc=True)
 
     @property
     def categorical_axes_data(self):
+        '''Returns the list of categorical axes of a data histogram.'''
         return self._categorical_axes(mc=False)
 
     @property
@@ -87,6 +100,7 @@ class DataMC:
         return len(self.dense_axes)
     
     def get_axis_items(self, axis_name, mc=True):
+        '''Returns the list of values contained in a Hist axis.'''
         if mc:
             axis = [ax for ax in self.categorical_axes_mc if ax.name == axis_name][0]
         else:
@@ -109,18 +123,22 @@ class DataMC:
 
     @property
     def stack_sum_data(self):
+        '''Returns the sum histogram of a stack (`hist.stack.Stack`) of data histograms.'''
         return self.stack_sum(mc=False)
 
     @property
     def stack_sum_mc_nominal(self):
+        '''Returns the sum histogram of a stack (`hist.stack.Stack`) of MC histograms.'''
         return self.stack_sum(mc=True)
 
     def define_samples(self):
+        '''Defines the data and MC samples.'''
         self.samples = self.h_dict.keys()
         self.samples_data = list(filter(lambda d : self.data_key in d, self.samples))
         self.samples_mc = list(filter(lambda d : self.data_key not in d, self.samples))
 
     def load_attributes(self):
+        '''Loads the attributes from the dictionary of histograms.'''
         assert len(set([self.h_dict[s].ndim for s in self.samples_mc])), "Not all the MC histograms have the same dimension."
         for ax in self.categorical_axes_mc:
             setattr(self, {'year': 'years', 'cat': 'categories', 'variation': 'variations'}[ax.name], self.get_axis_items(ax.name))
@@ -134,14 +152,23 @@ class DataMC:
             self.lumi = {year : femtobarn(lumi[year]['tot'], digits=1) for year in self.years}
 
     def build_stacks(self, year, cat, spliteras=False):
+        '''Builds the data and MC stacks, applying a slicing by year and category.
+        If spliteras is True, the extra axis "era" is kept in the data stack to
+        distinguish between data samples from different data-taking eras.'''
         slicing_mc = {'year': year, 'cat': cat}
         slicing_mc_nominal = {'year': year, 'cat': cat, 'variation': 'nominal'}
         self.h_dict_mc = {d: self.h_dict[d][slicing_mc] for d in self.samples_mc}
         self.h_dict_mc_nominal = {d: self.h_dict[d][slicing_mc_nominal] for d in self.samples_mc}
+        # Store number of weighted MC events
         self.nevents = {d: round(sum(self.h_dict_mc_nominal[d].values()), 1) for d in self.samples_mc}
         reverse=True
-        # Here implement if log: reverse=False
+        # Order the events dictionary by decreasing number of events if linear scale, increasing if log scale
+        # N.B.: Here implement if log: reverse=False
         self.nevents = dict( sorted(self.nevents.items(), key=lambda x:x[1], reverse=reverse) )
+        self.colors = [self.style.colors[d] for d in self.nevents.keys()]
+        # Order the MC dictionary by number of events
+        self.h_dict_mc = {d: self.h_dict_mc[d] for d in self.nevents.keys()}
+        self.h_dict_mc_nominal = {d: self.h_dict_mc_nominal[d] for d in self.nevents.keys()}
         # Build MC stack with variations and nominal MC stack
         self.stack_mc = hist.Stack.from_dict(self.h_dict_mc)
         self.stack_mc_nominal = hist.Stack.from_dict(self.h_dict_mc_nominal)
@@ -166,31 +193,91 @@ class DataMC:
         num = self.stack_sum_data.values()
         den = self.stack_sum_mc_nominal.values()
         self.ratio = num / den
+        # TO DO: Implement Poisson interval valid also for num~0
+        # np.sqrt(num) is just an approximation of the uncertainty valid at large num
         self.ratio_unc = np.sqrt(num) / den
         self.ratio_unc[np.isnan(self.ratio_unc)] = np.inf
 
+    def get_systematic_uncertainty(self):
+        '''Instantiates the `SystUnc` objects and stores them in a dictionary with one entry for each systematic uncertainty.'''
+        self.syst_manager = SystManager(self)
+
     def define_figure(self, year, ratio=True):
-        plt.style.use([hep.style.ROOT, {'font.size': fontsize}])
-        plt.rcParams.update({'font.size': fontsize})
+        '''Defines the figure for the Data/MC plot.
+        If ratio is True, a subplot is defined to include the Data/MC ratio plot.'''
+        plt.style.use([hep.style.ROOT, {'font.size': self.style.fontsize}])
+        plt.rcParams.update({'font.size': self.style.fontsize})
         if ratio:
-            self.fig, (self.ax, self.rax) = plt.subplots(2, 1, **opts_figure["datamc_ratio"])
+            self.fig, (self.ax, self.rax) = plt.subplots(2, 1, **self.style.opts_figure["datamc_ratio"])
             self.fig.subplots_adjust(hspace=0.06)
         else:
-            self.fig, self.ax  = plt.subplots(1, 1, **opts_figure["datamc"])
-        hep.cms.text("Preliminary", fontsize=fontsize, loc=0, ax=self.ax)
-        hep.cms.lumitext(text=f'{self.lumi[year]}' + r' fb$^{-1}$, 13 TeV,' + f' {year}', fontsize=fontsize, ax=self.ax)
+            self.fig, self.ax  = plt.subplots(1, 1, **self.style.opts_figure["datamc"])
+        hep.cms.text("Preliminary", fontsize=self.style.fontsize, loc=0, ax=self.ax)
+        hep.cms.lumitext(text=f'{self.lumi[year]}' + r' fb$^{-1}$, 13 TeV,' + f' {year}', fontsize=self.style.fontsize, ax=self.ax)
+
+    def format_figure(self, ratio=True):
+        '''Formats the figure's axes, labels, ticks, xlim and ylim.'''
+        self.ax.set_ylabel("Counts", fontsize=self.style.fontsize)
+        self.ax.legend(fontsize=self.style.fontsize, ncols=2, loc="upper right")
+        self.ax.tick_params(axis='x', labelsize=self.style.fontsize)
+        self.ax.tick_params(axis='y', labelsize=self.style.fontsize)
+        self.ax.set_xlim(self.xedges[0], self.xedges[-1])
+        if self.is_mc_only:
+            maximum = max(self.stack_sum_mc_nominal.values())
+        else:
+            maximum = max(self.stack_sum_data.values())
+        if not np.isnan(maximum):
+            self.ax.set_ylim((0, 2.0 * maximum))
+        if ratio:
+            xlabel = self.ax.get_xlabel()
+            self.ax.set_xlabel("")
+            self.rax.set_xlabel(xlabel, fontsize=self.style.fontsize)
+            self.rax.set_ylabel("Data / MC", fontsize=self.style.fontsize)
+            self.rax.yaxis.set_label_coords(-0.075, 1)
+            self.rax.tick_params(axis='x', labelsize=self.style.fontsize)
+            self.rax.tick_params(axis='y', labelsize=self.style.fontsize)
+            self.rax.set_ylim((0.5, 1.5))
 
     def plot_mc(self):
-        self.stack_mc_nominal.plot(stack=True, histtype='fill', ax=self.ax)#, color=colors)
+        '''Plots the MC histograms as a stacked plot.'''
+        self.stack_mc_nominal.plot(stack=True, histtype='fill', ax=self.ax, color=self.colors)
 
     def plot_data(self):
-        self.ax.errorbar(self.xcenters, self.stack_sum_data.values(), yerr=np.sqrt(self.stack_sum_data.values()), **opts_data)
+        '''Plots the data histogram as an errorbar plot.'''
+        self.ax.errorbar(self.xcenters, self.stack_sum_data.values(), yerr=np.sqrt(self.stack_sum_data.values()), **self.style.opts_data)
 
     def plot_datamc_ratio(self):
+        '''Plots the Data/MC ratio as an errorbar plot.'''
         self.get_datamc_ratio()
-        self.rax.errorbar(self.xcenters, self.ratio, yerr=self.ratio_unc, **opts_data)
+        self.rax.errorbar(self.xcenters, self.ratio, yerr=self.ratio_unc, **self.style.opts_data)
+
+    def plot_systematic_uncertainty(self, ratio=False):
+        '''Plots the asymmetric systematic uncertainty band on top of the MC stack, if `ratio` is set to False.
+        To plot the systematic uncertainty in a ratio plot, `ratio` has to be set to True and the uncertainty band will be plotted around 1 in the ratio plot.'''
+        ax = self.ax
+        up = self.syst_manager.total.up
+        down = self.syst_manager.total.down
+        if ratio:
+            # In order to get a consistent uncertainty band, the up/down variations of the ratio are set to 1 where the nominal value is 0
+            ax = self.rax
+            up = self.syst_manager.total.ratio_up
+            down = self.syst_manager.total.ratio_down
+
+        unc_band = np.array([down, up])
+        ax.fill_between(
+            self.xedges,
+            np.r_[unc_band[0], unc_band[0, -1]],
+            np.r_[unc_band[1], unc_band[1, -1]],
+            **self.style.opts_unc['total'],
+            label="syst. unc.",
+        )
+        if ratio:
+            ax.hlines(1.0, *ak.Array(self.xedges)[[0,-1]], colors='gray', linestyles='dashed')
 
-    def plot_datamc(self, year=None, ratio=True):
+    def plot_datamc(self, year=None, ratio=True, syst=True):
+        '''Plots the data histogram as an errorbar plot on top of the MC stacked histograms.
+        If ratio is True, also the Data/MC ratio plot is plotted.
+        If syst is True, also the total systematic uncertainty is plotted.'''
         if ratio:
             if self.is_mc_only:
                 raise Exception("The Data/MC ratio cannot be plotted if the histogram is MC only.")
@@ -202,26 +289,203 @@ class DataMC:
         if (not self.is_mc_only) & (not self.is_data_only):
             self.plot_mc()
             self.plot_data()
+            if syst:
+                self.plot_systematic_uncertainty()
         elif self.is_mc_only:
             self.plot_mc()
-        elif self.is_mc_only:
+            if syst:
+                self.plot_systematic_uncertainty()
+        elif self.is_data_only:
             self.plot_data()
 
         if ratio:
             self.plot_datamc_ratio()
+            if syst:
+                self.plot_systematic_uncertainty(ratio)
 
+        self.format_figure(ratio)
         plt.show(self.fig)
         plt.close(self.fig)
 
-    def plot_datamc_all(self, ratio=True, spliteras=False):
+    def plot_datamc_all(self, ratio=True, syst=True, spliteras=False):
+        '''Plots the data and MC histograms for each year and category contained in the histograms.
+        If ratio is True, also the Data/MC ratio plot is plotted.
+        If syst is True, also the total systematic uncertainty is plotted.'''
         for year in self.years:
             for cat in self.categories:
                 self.define_figure(year, ratio)
                 self.build_stacks(year, cat, spliteras)
-                self.plot_datamc(year, ratio)
+                self.plot_datamc(year, ratio, syst)
 
 class SystUnc:
-    '''This class handles the systematic uncertainties of 1D MC histograms.'''
-    def __init__(self, stack_mc, name):
-        self.stack_mc = stack_mc
+    '''This class stores the information of a single systematic uncertainty of a 1D MC histogram.
+    The built-in __add__() method implements the sum in quadrature of two systematic uncertainties,
+    returning a `SystUnc` instance corresponding to their sum in quadrature.'''
+    def __init__(self, datamc : DataMC = None, name : str = None, syst_list : list = None) -> None:
+        self.datamc = datamc
         self.name = name
+        self.is_mcstat = self.name == "mcstat"
+
+        # Initialize the arrays of the nominal yield and squared errors as 0
+        self.nominal = 0.0
+        self.err2_up = 0.0
+        self.err2_down = 0.0
+        if datamc:
+            if syst_list:
+                raise Exception("The initialization of the instance is ambiguous. Either a `DataMC` object or a list of `SystUnc` objects should be passed to the constructor.")
+            else:
+                self.syst_list = [self]
+            self._get_err2()
+            # Inherit style from DataMC object
+            self.style = self.datamc.style
+            # Full nominal MC including all MC samples
+            self.h_mc_nominal = self.datamc.stack_sum_mc_nominal
+            self.nominal = self.h_mc_nominal.values()
+            self.xcenters = self.datamc.xcenters
+            self.xedges = self.datamc.xedges
+            self.xbinwidth = self.datamc.xbinwidth
+        elif syst_list:
+            self.syst_list = syst_list
+            assert self.nsyst > 0, "Attempting to initialize a `SystUnc` instance with an empty list of systematic uncertainties."
+            assert not ((self._n_empty == 1) & (self.nsyst == 1)), "Attempting to intialize a `SystUnc` instance with an empty systematic uncertainty."
+            self._get_err2_from_syst()
+            # Get default style
+            self.style = Style()
+
+    def __add__(self, other):
+        '''Sum in quadrature of two systematic uncertainties.
+        In case multiple objects are summed, the information on the systematic uncertainties that
+        have been summed is stored in self.syst_list.'''
+        return SystUnc(name=f"{self.name}_{other.name}", syst_list=[self, other])
+
+    @property
+    def up(self):
+        return self.nominal + np.sqrt(self.err2_up)
+
+    @property
+    def down(self):
+        return self.nominal - np.sqrt(self.err2_down)
+
+    @property
+    def ratio_up(self):
+        return np.where(self.nominal != 0, self.up / self.nominal, 1)
+
+    @property
+    def ratio_down(self):
+        return np.where(self.nominal != 0, self.down / self.nominal, 1)
+
+    @property
+    def nsyst(self):
+        return len(self.syst_list)
+
+    @property
+    def _is_empty(self):
+        return np.sum(self.nominal) == 0
+
+    @property
+    def _n_empty(self):
+        return len([s for s in self.syst_list if s._is_empty])
+
+    def _get_err2_from_syst(self):
+        '''Method used in the constructor to instanstiate a SystUnc object from
+        a list of SystUnc objects. The sytematic uncertainties in self.syst_list,
+        are summed in quadrature to define a new SystUnc object.'''
+        index_non_empty = [i for i, s in enumerate(self.syst_list) if not s._is_empty][0]
+        self.nominal = self.syst_list[index_non_empty].nominal
+        self.xcenters = self.syst_list[index_non_empty].xcenters
+        self.xedges = self.syst_list[index_non_empty].xedges
+        self.xbinwidth = self.syst_list[index_non_empty].xbinwidth
+        for syst in self.syst_list:
+            if not ((self._is_empty) | (syst._is_empty)):
+                assert all(np.equal(self.nominal, syst.nominal)), "Attempting to sum systematic uncertainties with different nominal MC."
+                assert all(np.equal(self.xcenters, syst.xcenters)), "Attempting to sum systematic uncertainties with different bin centers."
+            self.err2_up += syst.err2_up
+            self.err2_down += syst.err2_up
+
+    def _get_err2(self):
+        '''Method used in the constructor to instanstiate a SystUnc object from
+        a DataMC object. The corresponding up/down squared uncertainties are stored and take
+        into account the possibility for the uncertainty to be one-sided.'''
+        # Loop over all the MC samples and sum the systematic uncertainty in quadrature
+        for h in self.datamc.stack_mc:
+            # Nominal variation for a single MC sample
+            h_nom = h[{'variation': 'nominal'}]
+            nom = h_nom.values()
+            # Sum in quadrature of mcstat
+            if self.is_mcstat:
+                mcstat_err2 = h_nom.variances()
+                self.err2_up += mcstat_err2
+                self.err2_down += mcstat_err2
+                continue
+            # Up/down variations for a single MC sample
+            var_up = h[{'variation': f'{self.name}Up'}].values()
+            var_down = h[{'variation': f'{self.name}Down'}].values()
+            # Compute the uncertainties corresponding to the up/down variations
+            err_up = var_up - nom
+            err_down = var_down - nom
+            # Compute the flags to check which of the two variations (up and down) are pushing the nominal value up and down
+            up_is_up = err_up > 0
+            down_is_down = err_down < 0
+            # Compute the flag to check if the uncertainty is one-sided, i.e. when both variations are up or down
+            is_onesided = (up_is_up ^ down_is_down)
+
+            # Sum in quadrature of the systematic uncertainties taking into account if the uncertainty is one- or double-sided
+            err2_up_twosided = np.where(up_is_up, err_up**2, err_down**2)
+            err2_down_twosided = np.where(up_is_up, err_down**2, err_up**2)
+            err2_max = np.maximum(err2_up_twosided, err2_down_twosided)
+            err2_up_onesided = np.where(is_onesided & up_is_up, err2_max, 0)
+            err2_down_onesided = np.where(is_onesided & down_is_down, err2_max, 0)
+            err2_up_combined = np.where(is_onesided, err2_up_onesided, err2_up_twosided)
+            err2_down_combined = np.where(is_onesided, err2_down_onesided, err2_down_twosided)
+            # Sum in quadrature of the systematic uncertainty corresponding to a MC sample
+            self.err2_up += err2_up_combined
+            self.err2_down += err2_down_combined
+
+    def plot(self, ax=None):
+        '''Plots the nominal, up and down systematic variations on the same plot.'''
+        plt.style.use([hep.style.ROOT, {'font.size': self.style.fontsize}])
+        plt.rcParams.update({'font.size': self.style.fontsize})
+        if not ax:
+            self.fig, self.ax  = plt.subplots(1, 1, **self.style.opts_figure["datamc"])
+        else:
+            self.ax = ax
+            self.fig = self.ax.get_figure
+        hep.cms.text("Preliminary", fontsize=self.style.fontsize, loc=0, ax=self.ax)
+        #hep.cms.lumitext(text=f'{self.lumi[year]}' + r' fb$^{-1}$, 13 TeV,' + f' {year}', fontsize=self.style.fontsize, ax=self.ax)
+        plt.plot(self.xcenters, self.nominal, label="nominal")
+        plt.plot(self.xcenters, self.up, label=f"{self.name} up")
+        plt.plot(self.xcenters, self.down, label=f"{self.name} down")
+        plt.legend()
+        #plt.show()
+        #plt.close()
+        return self.fig, self.ax
+
+class SystManager:
+    '''This class handles the systematic uncertainties of 1D MC histograms.'''
+    def __init__(self, datamc : DataMC, has_mcstat=True) -> None:
+        self.datamc = datamc
+        assert all([(var == "nominal") | var.endswith(("Up", "Down")) for var in self.datamc.variations]), "All the variations names that are not 'nominal' must end in 'Up' or 'Down'."
+        self.variations_up = [var for var in self.datamc.variations if var.endswith("Up")]
+        self.variations_down = [var for var in self.datamc.variations if var.endswith("Down")]
+        assert len(self.variations_up) == len(self.variations_down), "The number of up and down variations is mismatching."
+        self.systematics = [s.split("Up")[0] for s in self.variations_up]
+        if has_mcstat:
+            self.systematics.append("mcstat")
+        self.syst_dict = {}
+
+        for syst_name in self.systematics:
+            self.syst_dict[syst_name] = SystUnc(self.datamc, syst_name)
+
+    @property
+    def total(self):
+        total = SystUnc(name="total", syst_list=list(self.syst_dict.values()))
+        return total
+
+    @property
+    def mcstat(self):
+        return self.syst_dict["mcstat"]
+
+    def get_syst(self, syst_name : str):
+        '''Returns the SystUnc object corresponding to a given systematic uncertainty,
+        passed as the argument `syst_name`.'''
+        return self.syst_dict[syst_name]
-- 
GitLab


From c9c20b3f25ae7df2766a27810ce93b389f5da07c Mon Sep 17 00:00:00 2001
From: mmarchegiani <matmarcheg@gmail.com>
Date: Tue, 28 Mar 2023 02:17:49 +0200
Subject: [PATCH 06/24] Notebook to test the plotting code

---
 notebooks/plotting/test_DataMC.ipynb | 805 +++++++++++++++++++++++++--
 1 file changed, 766 insertions(+), 39 deletions(-)

diff --git a/notebooks/plotting/test_DataMC.ipynb b/notebooks/plotting/test_DataMC.ipynb
index 8830e0b7..5c6afc9d 100644
--- a/notebooks/plotting/test_DataMC.ipynb
+++ b/notebooks/plotting/test_DataMC.ipynb
@@ -21,7 +21,7 @@
     {
      "data": {
       "text/plain": [
-       "<pocket_coffea.utils.plot_utils.DataMC at 0x7f3cb5f19be0>"
+       "<pocket_coffea.utils.plot_utils.DataMC at 0x7f1c2f805850>"
       ]
      },
      "execution_count": 2,
@@ -57,8 +57,10 @@
        " 'define_samples',\n",
        " 'dense_axes',\n",
        " 'dense_dim',\n",
+       " 'format_figure',\n",
        " 'get_axis_items',\n",
        " 'get_datamc_ratio',\n",
+       " 'get_systematic_uncertainty',\n",
        " 'h_dict',\n",
        " 'is_data_only',\n",
        " 'is_mc_only',\n",
@@ -70,12 +72,14 @@
        " 'plot_datamc_all',\n",
        " 'plot_datamc_ratio',\n",
        " 'plot_mc',\n",
+       " 'plot_systematic_uncertainty',\n",
        " 'samples',\n",
        " 'samples_data',\n",
        " 'samples_mc',\n",
        " 'stack_sum',\n",
        " 'stack_sum_data',\n",
        " 'stack_sum_mc_nominal',\n",
+       " 'style',\n",
        " 'variations',\n",
        " 'xaxis',\n",
        " 'xbinwidth',\n",
@@ -188,7 +192,8 @@
    "source": [
     "year = '2018'\n",
     "cat = 'SingleEle_1b'\n",
-    "datamc.build_stacks(year, cat)"
+    "datamc.build_stacks(year, cat)\n",
+    "datamc.get_systematic_uncertainty()"
    ]
   },
   {
@@ -199,7 +204,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -223,7 +228,12 @@
     {
      "data": {
       "text/plain": [
-       "['plot_data', 'plot_datamc', 'plot_datamc_all', 'plot_datamc_ratio', 'plot_mc']"
+       "['plot_data',\n",
+       " 'plot_datamc',\n",
+       " 'plot_datamc_all',\n",
+       " 'plot_datamc_ratio',\n",
+       " 'plot_mc',\n",
+       " 'plot_systematic_uncertainty']"
       ]
      },
      "execution_count": 10,
@@ -245,15 +255,19 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:168: RuntimeWarning: invalid value encountered in true_divide\n",
+      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:180: RuntimeWarning: invalid value encountered in true_divide\n",
       "  self.ratio = num / den\n",
-      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:169: RuntimeWarning: invalid value encountered in true_divide\n",
-      "  self.ratio_unc = np.sqrt(num) / den\n"
+      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:181: RuntimeWarning: invalid value encountered in true_divide\n",
+      "  self.ratio_unc = np.sqrt(num) / den\n",
+      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:337: RuntimeWarning: invalid value encountered in true_divide\n",
+      "  return np.where(self.nominal != 0, self.up / self.nominal, 1)\n",
+      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:341: RuntimeWarning: invalid value encountered in true_divide\n",
+      "  return np.where(self.nominal != 0, self.down / self.nominal, 1)\n"
      ]
     },
     {
      "data": {
-      "image/png": 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z5s3zqE/RtSHefPNNwzAKpxkFBwcbkoz//e9/xnPPPWdOI5JkJCQkOIyxc+dO45ZbbrH8nps1a2b8+eefLmu4+eabDUnG9ddf7/C4zWYz+48dO9ahbdGiRWbb5s2bjb/97W9uz/3CCy8YBQUFxssvv+z2Xq42bdoYeXl5TrU1bNjQkGQkJiY6PH78+HGz74wZM4yxY8e6XKPD/jV58mS3/wb/+c9/jCpVqlg+f9WqVXO5jkbR5yglJcV48MEHHfp17drVKCgoMKeitWrVym0dhmEYffv2NSQZVapUMQ4ePGh5LADg8vPII48YkoybbrqpxH3t6yjVrl3b8rjffvvN/D01a9Ysj8c/dOiQ2c9q2vekSZNK/Amvu/d9Rd/7nT/z4ODBg8bw4cONevXqGUFBQUZYWJhxyy23GFOmTHE7O2DlypXGJ598Yvn166+/uuxbXjMPjh07ZvmexOoT5KLriLlba8wwDIe1xWw2W6lrLs3Mg4yMDGPUqFFGs2bNjJCQEKNq1apGkyZNjKSkJGPHjh1u++Xn5xt169Y1JBnh4eGW/y5r16416/vnP/9ZovqK8+OPP5pju7tF287+yX3z5s3Nx5YuXWr2f+ONN9z2fe2118zjVq5c6dRemtfNxfzZtvMXKhx36XFJk+uycv7Mg/z8fK1du1YdOnQwHzt/5dCoqCjVrVu3ROcZP368tmzZ4vFqq3/99ZdSU1OVmpqq999/X1LhSqR33XWXhg4dqquuuqpE57crutOCJzMPtmzZogkTJkiSKlWqZO6EsWvXLp0+fVqS9NFHH2n16tXy8fFRp06d1KRJE3Xu3NkcY9OmTerYsaO5EnGDBg3UoUMHxcXFad++ffrqq6907Ngxbdq0SX379tXSpUsdPonIy8szV389v2Z7Aik5bt94ftvDDz+s9evXq0WLFrrtttsUGBioL774wtwudOLEidq/f7+mTZum8PBw3XXXXWrQoIE2bNigWbNmSSp8HaSkpKh79+7muKdOndKOHTtcnr/oirXvvPOO1q5dq8DAQHXp0kUtWrTQuXPn9H//93/m9jYjR47UI4884rQF6fvvv6+nnnpKUuHqvX//+9+VkJCggIAAbdmyRXPmzNHZs2d18uRJPfbYY/r111/dPg8vvfSSVq9ercDAQN16661q1KiRevToIR8fH8XGxmrr1q1KT0+XOxs2bNAXX3whSXr66adVu3Ztt8cCAC5P9pkH1157raTCWaV//PGHMjMzVbt2bdWvX1++vq4nANvfC0RHR1ueo+inilYz684XHh4uf39/5eXlOc0aLapo28X6XbZ582Z17txZR44cMR/LycnRihUrtGLFCn344YdKSUlx2iGhXbt2ateu3UWpqaxUr15dJ0+edHhs3Lhxeu2114rtGx8fbx5n9dzb3x/5+fkpLCysFNWWzsKFC9W3b1+nXde2bNmiLVu26L333tMbb7yhp59+2mkWha+vr/r06aM333xTR48e1dKlSx3eIxd1MXdZyMjIMP9c3DXMVVddpUOHDjnsfGB/vyxJd9xxh9u+Xbp00XPPPSep8Frh/NdxaV435fKzXaKoAeWi6Mr0Rb/K6n4mV6xmHhQUFBhRUVEOj48bN86hf7du3Rza7733XsMw3CfQrmYeGEbhCqovvPCCw4IkF/JVuXJl47///W+JVxE9d+6cUblyZUMqXGSkOPPmzTNiYmLM844ePdpsmz59ukNNTZo0MdasWeM0xpEjR8zFYqpWrWpMmzbN6dP7jIwMo1GjRm4/Yfj111/NtilTpji0Fd1p4fxPwXv27Gm2+fn5OT1np06dMq699lqH76Nnz57GkSNHHMYZMWKE2f766687tBV9PX/++ecObW+++abD2C1atDB+++03h2OOHj3q8ByfvzBUVlaWec9fXFycsWfPHqfnePv27eYimHKR2hZ9jiQZt9xyi8uUvGvXruZz5WqGhWEYRufOnQ1JRkREhJGdne3yGADA5c3+e+uxxx4zHn30UfP+dfvXVVddZbz88svGmTNnnPreeeedhlS4aLOVojMPRo4cWaL67DPkJBnz5893at+wYYP5u7VNmzYej7t7926HVfsjIiLMhSFd7bYQGxtrSDLatm1rvP7668aMGTOMYcOGGbVq1TKPadu2rdvfuRfCm7stFH1f7Mmq+Va2bdtmvl/u0aNHmdfn6cyDX375xZyRWq1aNeOpp54ypk6dakybNs0YOnSow6xQ++zc861fv9485tFHH3V7LvuacHXr1i3zXRZ27dplzlo5ceKE2+Oys7PN76no8150h4OsrCy3/Y8ePer2esqdkrxuLtbPth3hQQVUdIXeol9Fp8aUNavwwDAMo1evXg6P33XXXWbfgoICo2bNmg7tb7/9tmEYJQ8P7Oyrkvbt29dp7JJ8TZgwoUTPw+bNm82+DRs2NN59912nr//85z/G4MGDjdatWzuc64477nD4RfTkk0+abbVr1zYyMzNdnvOxxx4zA48VK1a4ra3oLQbnT0UqOr1t3bp1Dm32WxGioqKcxoyLizP7vfPOOy7Pm5SU5HBR7WrhpmXLlpnHvP/++w5tEydONNt27drl0Fb0P7irr77a7X/Wzz//vHlcamqqQ9sHH3xgtrlanMbujjvuMN+wna/o7RrXX3+92/+Yiy6E4+o2maK37/z3v/91WwsA4PJ15swZj9+n3HjjjU7vD5555hm3v9OLKnqxMmDAgBLVmJGRYdSvX9+QChd+e/jhh42pU6can376qTFs2DBzq7qIiAin392e8HTBRKlwge3zw4F9+/YZ119/vXnM//3f/5W4Bncu1fBg27ZtxqeffmpMmjTJ6Nevn/lhV1RUlPH777+XeX2ehAf5+fnmramNGzc2Dh8+7HTMgQMHzEUGK1eu7HKXgYKCAuO6664zJPe3LhTdVaysb1koiRdeeMGs49133zUfHzJkiCEVLrZotSV5Xl6eeRuzu0Xoz1eS183F/tkmPKiA3K15cO211160cxYXHvznP/9xeDwsLMz8wfj999+d+tnvn7nQ8KCo/Px8Y/369cb7779vPP7440abNm2Kvbfd/uXv72/s27fP43N9+OGHFxRSPPbYY0ZOTo7DWO3btzfbFy5c6PJ8f/75p7kV5gsvvGBZW9F7oO6//36Htscff9yQZAQGBjrVUadOHUNyXo05MzPTHK9JkyZuE9yiWwWdPyvAbs6cOeYx33//vUPbgAEDDKlwy5rz/zO1/+cmyVi1apXb733UqFHmcefvLbx9+3Zj6dKlxvLlyy1TaPsvpW7dujm12Z8jPz8/Y8uWLW7HeP31192GGPn5+caNN95oSDLi4+O98qYEAOB9W7ZscXiPcN999xm//vqrcebMGWP37t3G9OnTHWbUFf1AxjAcd1to1aqVy08xf/zxR/PTQ0lG586dS1xnVlaWceutt7p9b9O8eXMjLS3tgp4DT8OD+vXru51VUPR57NChwwXV4cqlGh7861//cvo3uvPOO41Dhw5dlPo8CQ8WLFhgHm+1rkHRD0btHzCer+hF+fnvJQ3DMN544w2n64zyVFBQYPz3v/81a4iIiHBYA84+mzc0NLTYsUJDQw1JRp8+fTw6d0lfNxfzZ5s1Dyqg8PBwl4/v379fubm5CgwMLOeKnNc9yMrK0q5du9SgQQOn9Q6CgoJ0ww03lNm5fX191bx5czVv3tx8LC8vT5s2bdLy5cv17bffauXKlS775uXl6aOPPtJLL73k0bmKrndgpXLlyoqOjtZtt92mf/zjH7rxxhsd2gsKCrRx40ZJhfc73n777S7H+eijj8zdB/z9/TV58mS358zJyTH/HBsb67LuZs2aObw+jhw5Yt4HeX6NRdcbeOihh1yu5CsV3o8oFa5X0KhRI5fHFF1DwN26Ci1atHC4v/PEiRPm/WEtWrTQTTfd5HLsojVcc801Tvf0NWjQQA0aNHDbNycnR1988YW5I0br1q0d2os+Rx07dlTjxo3djlX0eU9PT3dYX2LWrFnmjhdvvPGG/P357xUArkR79+411+Z55pln9NJLL5m/Y6+99lpde+216t69u9q0aaMdO3Zo/vz5WrFihW655RZJ0k033aQhQ4bovffeU2pqqho3bqzHHntMDRs21NGjR7VixQp98cUX8vPzU0BAgM6dO+d2xyp38vPzNWnSJP30009uj9m8ebMmTJigcePGqVKlShf4bFgbMWKE/Pz8XLY1btxYPXr00LfffqstW7aU2Tk9XVvrUrBo0SINHz5cU6ZMUWhoaLmff8GCBZIK1xyLj493e1zTpk119dVXa+/evVqxYoW5TlVRffv2Nd+vf/XVV07rHtjXOyjrXRY8sXfvXo0YMcLc6SEoKEizZs1SlSpVzGOys7MlFV4jFMf+81SSXVI8ddF/ti8ocsBFZ58CdP7X+fd7l5XiZh7k5uaa06PsXx999JFhGI77rUoy2rVrZ45bFjMPPLFmzRojOjra5bk6derk8TgtWrQwpMIpR6W5X3379u3m+f/1r3+5Pa5x48YXNNOh6K0Bf/31l7lDQVJSksP4RRPh83eOKLra66ZNm1zWd+rUKXNmxNNPP+32++jevbshybjmmms87l90Vdrx48e7HbugoMCIjIw0JBl9+/Z1e9zp06eNDRs2GDNnzjRef/1145FHHjHatGnj8MmMJGPRokUO/Yo+R8XdalD006CiOz/k5uaasyjat29f5vfhAQAuP0V//5z/+/vkyZPGAw884PZ9QGBgoPH555+b97z37t3b4/MWFBQ4jH377bcbP/zwg3H48GHj6NGjxk8//WT06dPH4dPtv/76q0Tfm6czD9avX285zrhx48xjre4jv1SUds2DgoICw2azGStWrDDuvfdec6ymTZuW+N+ouPo8mXlQdJatp19W99k3bdrUkApvXSh6m+zBgwfN/uV5y8KJEyeMZ5991pzqLxXOvk5JSXE6tl+/foYkIzg4uNhxK1WqdFFmHpTHz7brZV7hde3bt3f5+Lx580o81n333aeaNWs6fJ3/yXVxAgICnD6xte87+ssvvzg8bvUJsjs//fST05f902ZPtGrVylzx/3yHDx/2aIycnBzzE/QGDRqoWrVqHp//fEVX77fvwXu+I0eOWK6EaqXov9+vv/6qc+fOSXKeXeDJTguVK1d2O6Ng48aN5swIdztPGIZhznw4//ybNm0y+1vt9OBuVV1JSktLk81mc1vDr7/+qsGDBysiIkLNmzdXr1699Oyzz+rrr7+Wr6+vRowYoTvvvNM83uo5cvdvZVd09d2iOy589NFH5iyKN9980+0sDgAA7G6//XbzU7+iv4skqWrVqpo2bZpSUlLUt29fJSQkKCgoSFFRUXrggQe0adMm3X333Tp16pQkOe1GYOW7777T//3f/0mSHnnkES1atEi33nqrIiMjFRYWpptvvllffPGFXn75ZUmFK+kX3c++LMXFxVm223erkKQ//vjjotRwKfHx8VFERITat2+vmTNnaujQoZIKP0n+7LPPyr2ezMzMEvexf0LvSt++fSXJ3HXB7ttvvzX/3Lt37xKf80IsXrxYjRs31uuvv27O/u3evbt+++03denSxel4+y5vp0+fVm5urttxz549a+7SEBUVVaY1l8fPNvNqK6hOnTrpgw8+cHp82rRpevbZZz2eEp2Xl6f58+c7/aBeyNSmm2++2WGq16pVq3TmzBmni/y2bduWeOzu3bubWxPZRURE6PDhwx5fiLVq1UpVq1Y1f5GW1ObNm82L8PMvdEvK/ibAx8fH4XaLojZt2mT+efr06erfv/8Fnctqa0l7HVFRUU5bV9rbmjdv7vb1VHRsd1PE0tPTzYDmQraJrFSpktvw4vwaio5vGIbGjRunf//73zIMQw0bNlSvXr100003qXnz5qpVq5b52rFPBa1fv77TbQ/2OiIiIlSnTh23dUiF29nYp4jaw4PTp0/rxRdflFT4C+38kA0AAFd8fX1Vv359bdmyRUePHnV5TJcuXVxeqEjSvn37zD9b3b53vo8++khS4fZ+//nPf9we99xzz+m9997ToUOH9NFHH+mJJ57w+ByecnfLgl1+fr75Z4J5Z//+97/17rvvSpJWrFihhx56qFzPn5eXJ6nw/ZmntwhbTevv06ePuY3hzJkzzdt+7bcsxMbGerSNemnk5OToySef1JQpU8zHmjZtqrfeeku33Xab235F32cfO3ZMkZGRLo87duyY+eey3gK1PH62CQ8qqL/97W+66qqrnD41//3335WcnKzhw4d7NM7333/vMuG77rrrSlzT+aHA9u3b9cMPP5j/cdhdyMyDqKgop/AgIyNDu3fv9rjWkydP6syZM06PF7dPsp39fnXJ+dPpkrJfkDZs2FBVq1Z1eYx9b15JqlGjxgWfy153cHCw05sHex3nfz9ZWVnau3evJPczCiQpNTVVkixnq3gSXlSvXl3XXHONy7bmzZtb3qtpH9++9oXdRx99pNGjR0uS3nnnHSUlJbl8E5Kfn2+uP+EqACn6HBX3xsTX11d16tTRnj17lJaWJkmaOHGiDh8+rICAAI0bN86yPwAARdnfQ4WEhJS4b9EPIZo0aeJxv99//12S9XsUqfACpEWLFpo3b57DHvZlae/evWrWrJnb9qKzDWrWrHlRaqiInn76aaWlpal58+YaOXKk2+Nq1aqlsLAwZWVl6eDBg+VYYSH7BzJnz551mOV5oa6++mq1adNGq1ev1uzZs/Xee+/pzJkz5iyEXr16XdQQqaCgQA888IC++uorSYUzgCZMmKB//OMfxQZdRcODLVu2uA0Ptm7dav65rMOD8vjZ5raFCiooKMicinS+f/3rX/rxxx+LHePgwYN6+OGHXbb9/e9/L3FNrkKBiRMnOvz9mmuucfvDYsX+yfD5+vfvr9OnT3s0xrRp08wp8kV5unhj0Yvg0sw8KLpYolUIUfTT/gMHDliOuWHDBo0dO1Zjx441F/ezs9fdvHlzh//YMjMzzXHP/36KLpZoteiMfexWrVq5/c/afoyPj4/Tc100ICi6WGJ2dra5gGFxCbJ9/ISEBAUHB0uSzp07p3//+9+SCoO2YcOGuf1P/dtvvzVno5z/vRZ9jjwNjOwhSnp6ujIzMzV+/HhJ0pAhQ5wCEgDAladLly5q3LixhgwZYnlcXl6e+Wa/6PT8zZs3m7/zi94id77PP/9cUmFAX5JZn/bFHE+ePFnssfYPoC7WYt1FP7hxxX6LbHh4uMOtg5e7rVu36ssvv9QXX3xhedyZM2fMT7KrV69eHqU5sM8c/eOPPyyn6huGoUWLFmnhwoXma94d+60LWVlZWrp0qebPn2/ODO7Vq1cZVe7a888/bwYHTZo00ZYtW/TYY48VGxxIjtcb8+fPd3tcSkqK+Wer4OxClMfPNuFBBTZ06FCHXyZ2OTk56tq1q8aNG+fywrqgoEBffvmlOnToYN4rXlRoaKjuueeeEtcTGhrqNL286P1I0oXdsiBJ/fr1c/n42rVr1alTJ82bN89lMCAVXgC++uqrevLJJ1229+nTx6Main7CXZof5t27d5s/tFYXpE2bNjX/vHjxYrfHZWdnq3fv3nrxxRc1ffp0h5Ty9OnT2rZtm6QLu2XAVT+7rKwsM/G3usC3P28NGzZ0WCfizJkz2r59u8vz28OV4sYuKCgwxy963I4dO9zeKlFUWlqann32WfPv54cHRZ+HCwkPxo0bp+zsbIWEhJizIAAAV7aGDRtq69at+vDDDy3XXZoxY4Z5UVT0U9vKlSvrxRdf1IsvvqgZM2a47JuVlaW5c+dKKvxAqCS7LVx//fWSCnfx2rlzp9vjMjMzzd+T9j5lbcKECW7f323YsMG80LrzzjuvqNsW7O//t2/f7vK9vN2SJUtkGIak4j+MuRhuvfVWSYUzD95//323xy1cuFB33nmnunTp4nC7jSu9e/c2/62/+uorc4eDi33LwrFjx8wPRa+77jotW7as2DU5imrcuLEZcH333XcOt9zY5efnmz+3V199teVtuxeiPH62CQ8qsGrVqumLL75w+QshJydHo0aNUkREhLp166YhQ4Zo8ODBuvPOOxUXF6e+ffu6TfZef/11p/u+PXX+lo3nu9DwoH379urRo4fLttTUVHXv3l1xcXG6/fbb9fDDD+vJJ5/U/fffr8TEREVFRWn06NHmf55F3XvvvW7XHCjq1KlT5oVucVN9iuPpBWl8fLz5n8ycOXP06aefOh2zf/9+dezY0byIP3+9C6sFDT0JD0JDQ91+Wl700wCrxRLtx51/TNHFEq0WKbT6RbB7924zGS16nH2hGUlas2aN0799fn6+5syZozZt2jhMx0pISHBbh6ezTezhwalTp8ytNZ9//vkrajolAMA9+4cW586dU79+/Rx+Z9lt3LjRnI5eu3Zt89NWqfDCxX7L5uuvv+50sZWTk6OBAwfq7Nmz8vX11fPPP1+i+h588EHzz/fff7/L9RZOnTqlBx980PyQ6oEHHijROTy1Y8cOjRgxwulCa+/evRowYID594ux3kJFZv+w46+//tKIESPMkKmoAwcOmM9LYGCgxx+WlaV77rnHnHE8duxYl1ueHz58WMOGDZNU+Frv2LGj5Zi1a9dWYmKipMK1DuzbQV7sWxZmzJhhLoz4n//8p8TXSj4+PuZt5Xv27DFnphY1fvx48z398OHDy/z7KZef7RLtzQCv+Prrrx22CCnN1+OPP27k5+c7naO4rRrtpk6dajn+5s2bHY4vyVaN6enpxrXXXlsm36cko169esahQ4c8eo5XrFhh9nvggQc8/rdxZcSIEYYkw8/Pzzh9+rTlsUW3aZJk3HbbbcaoUaOMl19+2ejVq5fh7+9vtj355JNOWwC+/fbbZvvu3bsd2u655x5DkhEdHe103nr16plbuLjz8ssvm2PbbDaXx+zatcs85t1333VomzRpktva7rvvPkOSUb16dZevR7vp06ebY6xdu9Z8/PTp0w7PTfv27Y0XX3zRGDdunPHwww8b11xzjdlWpUoV88/9+vUz5s+f7/QcRUVFua3hfB9//LHDv1mdOnWMM2fOeNwfAHD5GzJkiPl7IjY21hg3bpwxc+ZM47///a/xj3/8w/Dz8zOkwq2hFy5c6NR/4cKFZv/Q0FDjxRdfNL7++mvj3XffNZo0aWK2vfLKKy7PX/T9l6v3XP3793cYf+TIkcb06dONGTNmGKNGjTKuuuoqsz0xMdHIy8sr0ffvyVaN0dHR5u/odu3aGePHjzc+/fRTY/jw4UZ4eLh5/kGDBpXo3GWhuOevLMa12nLvr7/+cnhP3KhRI+O1114zvvrqK+Ojjz4yhg0b5rCF+muvvVbm9XmyVaNhGMbs2bPNPv7+/sZjjz1mfPjhh8aXX35pjB492qhVq5YhyfD19TUWLFjg0Zjvv/++0/v61NTUEtVf0n+33r17m+/fv/vuO2PBggXFfq1Zs8ZhjNOnTxsNGzY0a7jvvvuMzz//3Pj000/N8e3/niV571iSLT4v9s824cEl4qeffjIiIiIu+ELaz8/PGDVqlNsLNU/Dg927d7s9R7Vq1ZxegCUJDwzDMA4dOmS0bt261MFBixYtjPT0dI+f3wkTJph9J02a5HE/V+zP5fXXX+/R8e+8846536urr+DgYOOll15yCg4M4//tKRsaGurUHhsba0gy7r77bofHs7KyzLFHjRrltq67777b7S9+u08//dQca/Xq1Q5tDz74oBkQnF9bfHy8Icm49dZb3Y5tGIYxbNgwQyrczzonJ8ehrejez66+atWqZcydO9fo3r27w+MvvPBCsc+RlSVLljiMN23aNI/7AgCuDDk5OU6/f1y9b5o9e7bbMV599VXD19fXbf+nn37a5XsDwyj+IionJ8f45z//aQQEBLgd38fHx3jooYeM48ePl/j79yQ8uPnmm41vv/3W4SL4/K9+/foZubm5JT5/aXk7PDAMw9i2bZv5PsXdl6+vr/Hyyy+7fR2Upj5PwwPDMIw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\n",
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\n",
       "text/plain": [
        "<Figure size 1200x1200 with 2 Axes>"
       ]
@@ -274,52 +288,619 @@
    "execution_count": 12,
    "id": "105ce019",
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "#datamc.plot_datamc_all()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "70efe610-3668-43e2-8bc4-d0eaaaac5d2d",
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "data": {
-      "image/png": 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mKiEhwTOM1pv6L6rHjh1rcJxEH0Xr27Ztm2pra1VdXa0+ffooJiamwWP27NmSpJkzZ3qe+/vf/x50X6s/bt++fdq0aVOTx/naKg/R49ixY3r//ff1/vvv+51KUL/tbXp6uqTgr5mC/fwNF5IH8Kt+e5Lly5d7zYjt2bPH06FHjhwZ0tiAiy++WJJUWVmptWvXNip3u936xz/+Ialh/8zMzFR8fLyOHTumDz/80GvbCxYsaHQcolt1dbV+/vOfq6qqSunp6VqxYoWuv/76Jr9s0k8RKg6HQ4cOHdJXX33ls86XX34pSTrrrLM8z9FHYXfB9rXTTz9dp512miTpvffeC/g4RK927drpt7/9rbKzsz3TEr2p3048IyNDUvDXTMF+/oaNAfyoqakxKSkpRpL5/e9/36h8ypQpRpJJTU01tbW1YYgQkWzWrFlGkhkwYIDPOsOGDTOSzLhx40xdXV2DsmeffdZIMp07dza7d+9uUHbNNdcYSeaCCy4wNTU1Dcrmz59vJBlJZsOGDda9IbRpM2fONJLMySefbHbt2tWsY+mnCIUJEyYYSWbIkCHm+PHjjcp37NhhunfvbiSZ4uLiBmX0UdjBjTfeaCSZyZMnNyoLtq/de++9RpI544wzzL59+xqUffbZZyY+Pt5IMgsWLLD8/aBtqu8z/fr1M1VVVY3KN23aZNq3b28kmU8++cQY07JrpmA/f8OB5AGaNGPGDM8HcmFhodm8ebMpLy83BQUFnudnzpwZ7jARgQJJHrz33nuefvjb3/7WrF+/3nzzzTemqKjItGvXzkgyU6dObXTc2rVrPeXjx483K1euNE6n07z44ouma9euRpKZMGFCa749tDEjRowwksyUKVOafSz9FKGwZs0aExsbaySZn/70p2bZsmVm//79xul0mtdff92cccYZRpI555xzGl180UdhB/6SB8H2NafTaRITE40kM2rUKLNkyRKza9cu8/rrr5u0tDQjyQwfPrzRRRui19atWz2J1szMTLN48WJTVVVltm7dambNmmWSkpKMJDNp0qQGxwV7zRTs5284kDxAk+rq6szEiRM9nfqHj5ycHD5w0SoCSR4YY8wDDzzgs3+OHj260Zfkes8995yJiYnxetzZZ59t9u/f3xpvC21U7969ffazHz5OP/30RsfTTxEKf/jDH3z2F0lm0KBBpqyszOux9FGEm7/kgTHB97V33nnHdOjQwetxp556qvnmm29a822hDZo/f75nVIq3x/nnn99oJEBLrpmC/fwNNZIHCEhdXZ3561//ajIzM01CQoJJSEgwWVlZpqSkhMQBWk2gyQNjjHnzzTfNiBEjTLdu3UynTp3M2WefbZ566ilz7Ngxv8ctXrzY/OIXvzBJSUkmPj7eDBgwwBQUFJhDhw5Z9TYQITp37tyi5IEx9FOExooVK8xVV11lMjIyTKdOncxpp51mfv7zn5unnnqqySmG9FGEU1PJA2OC72tr1qwx48ePNz179jQdOnQwvXv3NnfddZfZs2eP1W8DEeKbb74xt9xyixk8eLDp0qWL6d27t7nyyivNzJkzfX6WtuSaKdjP31CKMcbHso4AAAAAAABitwUAAAAAANAEkgcAAAAAAMAvkgcAAAAAAMAvkgcAAAAAAMAvkgcAAAAAAMAvkgcAAAAAAMAvkgcAAAAAAMAvkgcAAAAAAMAvkgcAAAAAAMAvkgcAAAAAAMAvkgcAAAAAAMAvkgcAAAAAAMAvkgcAAAAAAMAvkgcAAAAAAMAvkgcAAAAAAMCv/w/+SGySIqtIDQAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<Figure size 1200x1200 with 2 Axes>"
+       "<pocket_coffea.utils.plot_utils.PlotManager at 0x7f1c23e16c70>"
       ]
      },
+     "execution_count": 13,
      "metadata": {},
-     "output_type": "display_data"
-    },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from pocket_coffea.utils.plot_utils import PlotManager\n",
+    "\n",
+    "plotter = PlotManager(o[\"variables\"])\n",
+    "plotter"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "c922cbf7-0bdd-45fc-843d-5667c9e6a968",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
     {
      "data": {
-      "image/png": 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\n",
       "text/plain": [
-       "<Figure size 1200x1200 with 2 Axes>"
+       "<pocket_coffea.utils.plot_utils.SystManager at 0x7f1c23dd8580>"
       ]
      },
+     "execution_count": 14,
      "metadata": {},
-     "output_type": "display_data"
-    },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from pocket_coffea.utils.plot_utils import SystUnc, SystManager\n",
+    "\n",
+    "syst_manager = SystManager(datamc)\n",
+    "syst_manager"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "8d712bd2-e9be-4410-aa27-f06b6b057460",
+   "metadata": {},
+   "outputs": [
     {
      "data": {
-      "image/png": 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\n",
       "text/plain": [
-       "<Figure size 1200x1200 with 2 Axes>"
+       "['__class__',\n",
+       " '__delattr__',\n",
+       " '__dict__',\n",
+       " '__dir__',\n",
+       " '__doc__',\n",
+       " '__eq__',\n",
+       " '__format__',\n",
+       " '__ge__',\n",
+       " '__getattribute__',\n",
+       " '__gt__',\n",
+       " '__hash__',\n",
+       " '__init__',\n",
+       " '__init_subclass__',\n",
+       " '__le__',\n",
+       " '__lt__',\n",
+       " '__module__',\n",
+       " '__ne__',\n",
+       " '__new__',\n",
+       " '__reduce__',\n",
+       " '__reduce_ex__',\n",
+       " '__repr__',\n",
+       " '__setattr__',\n",
+       " '__sizeof__',\n",
+       " '__str__',\n",
+       " '__subclasshook__',\n",
+       " '__weakref__',\n",
+       " 'datamc',\n",
+       " 'get_syst',\n",
+       " 'mcstat',\n",
+       " 'syst_dict',\n",
+       " 'systematics',\n",
+       " 'total',\n",
+       " 'variations_down',\n",
+       " 'variations_up']"
       ]
      },
+     "execution_count": 15,
      "metadata": {},
-     "output_type": "display_data"
-    },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dir(syst_manager)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "5f139750-b13f-45fa-9ae3-18f01726cd2d",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
     {
      "data": {
-      "image/png": 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\n",
       "text/plain": [
-       "<Figure size 1200x1200 with 2 Axes>"
+       "{'JER': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23dd8370>,\n",
+       " 'JES_Total': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23e168b0>,\n",
+       " 'pileup': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23dd8fa0>,\n",
+       " 'sf_btag_cferr1': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23dd8ee0>,\n",
+       " 'sf_btag_cferr2': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23de4f10>,\n",
+       " 'sf_btag_hf': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23de6fa0>,\n",
+       " 'sf_btag_hfstats1': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23de47c0>,\n",
+       " 'sf_btag_hfstats2': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23deab20>,\n",
+       " 'sf_btag_lf': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23deaaf0>,\n",
+       " 'sf_btag_lfstats1': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23decc40>,\n",
+       " 'sf_btag_lfstats2': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23decd00>,\n",
+       " 'sf_ele_id': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23defe20>,\n",
+       " 'sf_ele_reco': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23defd30>,\n",
+       " 'sf_ele_trigger_era': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23df0e80>,\n",
+       " 'sf_ele_trigger_ht': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23df0e50>,\n",
+       " 'sf_ele_trigger_pileup': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23df2d60>,\n",
+       " 'sf_ele_trigger_stat': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23df2fa0>,\n",
+       " 'sf_jet_puId': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23df6e50>,\n",
+       " 'sf_mu_id': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23df8fa0>,\n",
+       " 'sf_mu_iso': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23df6f70>,\n",
+       " 'sf_mu_trigger': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23dfaa90>,\n",
+       " 'mcstat': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23dfab50>}"
       ]
      },
+     "execution_count": 16,
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "syst_manager.syst_dict"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "9760a85f-9ae9-43b5-b8f7-9df57e2ac350",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23dd8370>"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s = syst_manager.syst_dict[\"JER\"]\n",
+    "s"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "bdfabb2c-8023-4921-bb21-6cfd64c0395e",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['__add__',\n",
+       " '__class__',\n",
+       " '__delattr__',\n",
+       " '__dict__',\n",
+       " '__dir__',\n",
+       " '__doc__',\n",
+       " '__eq__',\n",
+       " '__format__',\n",
+       " '__ge__',\n",
+       " '__getattribute__',\n",
+       " '__gt__',\n",
+       " '__hash__',\n",
+       " '__init__',\n",
+       " '__init_subclass__',\n",
+       " '__le__',\n",
+       " '__lt__',\n",
+       " '__module__',\n",
+       " '__ne__',\n",
+       " '__new__',\n",
+       " '__reduce__',\n",
+       " '__reduce_ex__',\n",
+       " '__repr__',\n",
+       " '__setattr__',\n",
+       " '__sizeof__',\n",
+       " '__str__',\n",
+       " '__subclasshook__',\n",
+       " '__weakref__',\n",
+       " '_get_err2',\n",
+       " '_get_err2_from_syst',\n",
+       " '_is_empty',\n",
+       " '_n_empty',\n",
+       " 'datamc',\n",
+       " 'down',\n",
+       " 'err2_down',\n",
+       " 'err2_up',\n",
+       " 'h_mc_nominal',\n",
+       " 'is_mcstat',\n",
+       " 'name',\n",
+       " 'nominal',\n",
+       " 'nsyst',\n",
+       " 'plot',\n",
+       " 'ratio_down',\n",
+       " 'ratio_up',\n",
+       " 'style',\n",
+       " 'syst_list',\n",
+       " 'up',\n",
+       " 'xbinwidth',\n",
+       " 'xcenters',\n",
+       " 'xedges']"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dir(s)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "61768a25-1746-43d7-9c04-e3c41f00f8ea",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 9.11607005e+04,\n",
+       "       9.27834477e+04, 6.29315906e+04, 4.61562579e+04, 2.50884140e+04,\n",
+       "       1.65060009e+04, 8.42179789e+03, 4.90902698e+03, 2.78566432e+03,\n",
+       "       2.03306476e+03, 8.38858990e+02, 9.43239715e+02, 4.16501352e+02,\n",
+       "       1.79748982e+02, 1.95682225e+02, 8.38990053e+01, 5.61078601e+01,\n",
+       "       5.56000035e+01, 2.27633727e+01, 1.01967449e+01, 1.09760809e+01,\n",
+       "       5.41495368e+00, 3.35182865e+00, 1.43706500e+00, 2.27116756e+00,\n",
+       "       9.23500623e-01, 2.86470865e+00, 1.61542858e+00, 3.73156545e+00,\n",
+       "       3.75386511e-01, 9.32838941e-02, 4.29123357e-01, 1.67206829e-01,\n",
+       "       1.83280950e-01, 3.73368079e-01, 1.05669519e-01, 2.28578684e-01,\n",
+       "       4.12464014e-02, 8.08846763e-02, 2.34777494e-03, 5.30243379e-01,\n",
+       "       1.41417242e-02, 5.89701090e-02, 4.24611167e-02, 7.62562183e-03,\n",
+       "       1.96446709e-03, 1.32531336e-04])"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s.err2_up"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "51d6a9d3-558d-456e-acd8-0eafd709465b",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 7.41242369e+04,\n",
+       "       8.09454378e+04, 5.40108696e+04, 3.60821576e+04, 2.28405727e+04,\n",
+       "       1.40913789e+04, 5.86729880e+03, 4.68657214e+03, 2.18757198e+03,\n",
+       "       1.37022324e+03, 5.75498003e+02, 3.97617586e+02, 2.25555410e+02,\n",
+       "       2.49669601e+02, 1.16870573e+02, 7.06620646e+01, 7.31059356e+01,\n",
+       "       7.65567795e+01, 9.78685695e+00, 8.27260567e+00, 6.23340071e+00,\n",
+       "       8.40457030e+00, 4.09596249e+00, 3.02646043e+00, 4.65513298e-01,\n",
+       "       9.92518495e-01, 1.36529415e+00, 2.23643313e+00, 4.26888194e-01,\n",
+       "       9.70024040e-02, 1.36686974e-01, 1.55945087e-01, 5.11404522e-01,\n",
+       "       7.24108291e-01, 9.02205778e-02, 5.09569857e-01, 1.66685832e-01,\n",
+       "       4.58136166e-03, 1.27170636e+00, 3.42679028e-02, 5.48085905e-02,\n",
+       "       2.57202616e-02, 1.68608805e-03, 2.75366000e-03, 4.83758276e-02,\n",
+       "       9.16379761e-02, 5.18220977e-02])"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s.err2_down"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "14e3f8df-a720-4bf1-9964-51d362256511",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'JER'"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s.name"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "7752ee8b-0dbd-4ded-bb88-06725af4267b",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s1 = syst_manager.syst_dict[\"JER\"]\n",
+    "s2 = syst_manager.syst_dict[\"pileup\"]\n",
+    "s1._n_empty"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "a62e6c6b-e08e-4387-af71-81eb1ea902c5",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<pocket_coffea.utils.plot_utils.SystUnc at 0x7f1cfaef1190>"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s_sum = s1 + s2\n",
+    "s_sum"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "a1e65a02-632d-44e3-a9b3-b1062ae2d2e2",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'JER_pileup'"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s_sum.name"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "0f39e4ac-627a-4a54-813f-e769c2c5b371",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 9.11607005e+04,\n",
+       "       9.27834477e+04, 6.29315906e+04, 4.61562579e+04, 2.50884140e+04,\n",
+       "       1.65060009e+04, 8.42179789e+03, 4.90902698e+03, 2.78566432e+03,\n",
+       "       2.03306476e+03, 8.38858990e+02, 9.43239715e+02, 4.16501352e+02,\n",
+       "       1.79748982e+02, 1.95682225e+02, 8.38990053e+01, 5.61078601e+01,\n",
+       "       5.56000035e+01, 2.27633727e+01, 1.01967449e+01, 1.09760809e+01,\n",
+       "       5.41495368e+00, 3.35182865e+00, 1.43706500e+00, 2.27116756e+00,\n",
+       "       9.23500623e-01, 2.86470865e+00, 1.61542858e+00, 3.73156545e+00,\n",
+       "       3.75386511e-01, 9.32838941e-02, 4.29123357e-01, 1.67206829e-01,\n",
+       "       1.83280950e-01, 3.73368079e-01, 1.05669519e-01, 2.28578684e-01,\n",
+       "       4.12464014e-02, 8.08846763e-02, 2.34777494e-03, 5.30243379e-01,\n",
+       "       1.41417242e-02, 5.89701090e-02, 4.24611167e-02, 7.62562183e-03,\n",
+       "       1.96446709e-03, 1.32531336e-04])"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s1.err2_up"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "3b2968aa-3aac-4af0-b534-2178dc5d277c",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 8.51337422e+07,\n",
+       "       8.90241147e+07, 6.64709598e+07, 4.59969080e+07, 2.82356043e+07,\n",
+       "       1.78276167e+07, 1.00355040e+07, 6.55987354e+06, 3.78138649e+06,\n",
+       "       2.23447858e+06, 1.30466117e+06, 8.02222623e+05, 4.72369448e+05,\n",
+       "       2.87164680e+05, 1.77262956e+05, 1.06025114e+05, 6.91775404e+04,\n",
+       "       4.31903425e+04, 2.70651251e+04, 1.81530320e+04, 1.08317567e+04,\n",
+       "       7.50194295e+03, 4.49418414e+03, 3.24486251e+03, 2.19998961e+03,\n",
+       "       1.12964046e+03, 8.97573917e+02, 7.08310409e+02, 5.53588187e+02,\n",
+       "       3.30488474e+02, 2.01758672e+02, 1.44288738e+02, 1.02800902e+02,\n",
+       "       8.86509731e+01, 7.86310281e+01, 4.85163362e+01, 4.51786076e+01,\n",
+       "       3.98595327e+01, 2.01625029e+01, 1.37058162e+01, 2.92223969e+01,\n",
+       "       1.37124958e+01, 6.93892325e+00, 5.89023492e+00, 4.93240838e+00,\n",
+       "       3.26040344e+00, 6.62067888e+00])"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s2.err2_up"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "214b41fb-36f2-472d-b0aa-b2f422189d85",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 8.52249029e+07,\n",
+       "       8.91168981e+07, 6.65338914e+07, 4.60430642e+07, 2.82606927e+07,\n",
+       "       1.78441227e+07, 1.00439258e+07, 6.56478257e+06, 3.78417215e+06,\n",
+       "       2.23651164e+06, 1.30550002e+06, 8.03165862e+05, 4.72785950e+05,\n",
+       "       2.87344429e+05, 1.77458638e+05, 1.06109013e+05, 6.92336482e+04,\n",
+       "       4.32459425e+04, 2.70878884e+04, 1.81632288e+04, 1.08427328e+04,\n",
+       "       7.50735791e+03, 4.49753597e+03, 3.24629957e+03, 2.20226078e+03,\n",
+       "       1.13056396e+03, 9.00438626e+02, 7.09925838e+02, 5.57319752e+02,\n",
+       "       3.30863861e+02, 2.01851956e+02, 1.44717861e+02, 1.02968109e+02,\n",
+       "       8.88342540e+01, 7.90043962e+01, 4.86220057e+01, 4.54071863e+01,\n",
+       "       3.99007791e+01, 2.02433876e+01, 1.37081639e+01, 2.97526402e+01,\n",
+       "       1.37266376e+01, 6.99789336e+00, 5.93269604e+00, 4.94003400e+00,\n",
+       "       3.26236791e+00, 6.62081142e+00])"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s_sum.err2_up"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "e16231fd-8879-4e63-8e86-daebf77cd6c6",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['__add__',\n",
+       " '__class__',\n",
+       " '__delattr__',\n",
+       " '__dict__',\n",
+       " '__dir__',\n",
+       " '__doc__',\n",
+       " '__eq__',\n",
+       " '__format__',\n",
+       " '__ge__',\n",
+       " '__getattribute__',\n",
+       " '__gt__',\n",
+       " '__hash__',\n",
+       " '__init__',\n",
+       " '__init_subclass__',\n",
+       " '__le__',\n",
+       " '__lt__',\n",
+       " '__module__',\n",
+       " '__ne__',\n",
+       " '__new__',\n",
+       " '__reduce__',\n",
+       " '__reduce_ex__',\n",
+       " '__repr__',\n",
+       " '__setattr__',\n",
+       " '__sizeof__',\n",
+       " '__str__',\n",
+       " '__subclasshook__',\n",
+       " '__weakref__',\n",
+       " '_get_err2',\n",
+       " '_get_err2_from_syst',\n",
+       " '_is_empty',\n",
+       " '_n_empty',\n",
+       " 'datamc',\n",
+       " 'down',\n",
+       " 'err2_down',\n",
+       " 'err2_up',\n",
+       " 'is_mcstat',\n",
+       " 'name',\n",
+       " 'nominal',\n",
+       " 'nsyst',\n",
+       " 'plot',\n",
+       " 'ratio_down',\n",
+       " 'ratio_up',\n",
+       " 'style',\n",
+       " 'syst_list',\n",
+       " 'up',\n",
+       " 'xbinwidth',\n",
+       " 'xcenters',\n",
+       " 'xedges']"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dir(s_sum)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "881d8932-6df6-4596-baa6-f0ad6e05bffc",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(<Figure size 1200x900 with 1 Axes>, <AxesSubplot: >)"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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+Zs6cqdTU1FiHAwuqra1VbW1t2O0NwwipHskDk9TX1+vqq6/Wvn375HQ6NWzYsLD7qqioUO/evcNuP3fuXOXn54fdHgAAAIA1NE71v+iii8JOHpCAiG/z5s1TQUFBm78OyQOTPPzww1qxYoVyc3N10003RdRXWlqavvnmm7DbM+sAAAAAQKNIExAej0ezZ8+WJM2ePVuvv/667Ha72WEiTHPmzNEdd9wRdvsRI0aooqKixXokD0ywYsUKPfjgg7LZbPrrX/+qhISEiPpLSEhQr169TIoOAAAAAMLncDhUXFwsSSouLpbD4VBhYWGMo0KjSJeth3r92mE3TDTT1VdfLa/Xq+eee45pQAAAAADiSklJibxeryTJ6/Vq5cqVMY4IsUDywAQbN26UJE2ZMkUJCQlNHtddd50kqayszPfcbbfdFsNoAQAAAOv66RR5j8cT44iQnZ2tpKQkSVJSUpKysrJiHBFigeQBAAAAEENcLDflb4p8a5n1mbrdbuXn58vtdofVPl64XC6NGzdOkjRu3Di5XK7YBoSYIHlgAsMwAj5eeOEFSdKwYcN8zz3++OOxDRgAAACWYcbFcjwxY4q8WZ9p40aDHT15YLfb9eSTT0qSnnzySTZL7KBIHrTCnDlzNHz4cA0fPjzWoQAAACBOsJ68KTOmyPOZAuYjedAKbrdbZWVlKisri3UoAAAAiBOsJ2/KjCnyfKaA+UgeAAAAADHEevKmzJgiz2cKmI/kwX84HA4ZhqFvv/02YB2Xy+Xbt8DMfgEAANA68bTJIOvJzcdnCpiP5AEAAADaHTYZBIDoInkAAACAdsdKG+JxnB+AjoDkAQAAANodK22Ix3F+QMeTmpqquXPnKjU1NdahRA3JAwAAALQ7bIjXHDMggOhJTU1Vfn4+yQMAAAAgmFhfqLIhXnPMgLCeeNrYEyB5AAAAgFbjQhVoGRt7Ip6QPAAAAACANmCljT2BSJE8AAAAAIA2YKWNPYFIkTwAAAAAgDbAxp6IJ51iHQCa83g8yszM9FuWl5envLy8KEcEAAAAoLUaN/Y87bTT2NgTMeV0OuV0Ov2WhbqRJ8kDC7Lb7SotLY11GAAAAACAOBDsJnRGRobKy8tb7INlCwAAAABME+tjPAG0DZIHAAAAAEzDMZ6wOhJc4SF5AAAAAADoMEhwhYfkAQAAAAAACIrkAQAAAFrF4/Fo9uzZkqTZs2eHvFM3AKD9InkAAACAVnE4HCouLpYkFRcXy+FwxDagOJCamqq5c+cqNTU1pnGwFhxAICQPgAA8Ho9yc3Nls9mUm5vLXRUAAP6jpKREXq9XkuT1erVy5cqYxGGFC26zZmGkpqYqPz/fEskD1oID8IfkARCAw+FQUVGRqqqqVFRUxF0VAIAlWOHOcHZ2tpKSkiRJSUlJysrKikkcVrjgZhYGgI6C5AEQgFXuqgAAImeFC26zWOHOsMvl0rhx4yRJ48aNk8vlilksscbfCwA6CpIHQABWuasCAIicFS6444ndbteTTz4pSXryySdlt9tjHFHs8PcC2hKbk8JKSB4AAbhcLuXk5MhmsyknJ6dD31UBAJgjnmZA4AhmYaAtsSwGVkLyAAjAbrersLBQlZWVKiws7NB3VQAA5lz4MwPCeiL972qVWRjxdoc6njbDjATLYmAlJA8AAIClWeVuPRf+8Sle/rvG2x1qNsM8woxlMVZIgpjJKv8mdEQkDwAAgKXFy8Ud0Ja4Q20+K3ymZiyLsUISxEz8mxA7JA8AAEBci7e7bmbgzl38YePG5iJd+mCFz9SMZTFWSIJIfBfHA5IHAAAgrsXbXTczcOcu/rBxY3ORLn2Il8/UCkkQie/ieEDyAAAAxDWr3HUzA3fuEIhVNm6MJ/HymVolCRJP38UdFckDAAAQ16xy180M3LkD0FpWSYLE03dxR0XywII8Ho8yMzP9PpxOZ6zDAwAgasy4027GXTcz4jCjD+7cAWivrDIDoqNyOp0BrzFD/feoUxvHiDDY7XaVlpbGOgwAAGLO3532wsLCVvXReNfttNNOC/uumxlxmNFHdna2ioqK5PV6uXMHoF0x47sY4cvLy1NeXp7fsoyMDJWXl7fYBzMPAACAZVnlTrsZcZjRh5Xu3EW6kz0AoH0heQAAACzLKmtkzYjDjD6ssnZZinwne8QnNvWMXyQMQfIAAABYllXutJsRh1XeC9CW2NQzfpEwBMkDAABgWVa5025GHFZ5L0BbsspSIwDmI3kAAAAAwBRWWWoEwHwkDwAAQNxjre6PWJOOQKxyNCoAayJ5AAAA4h5rdX/EmvQfkUhpyoyxwfIcIH6RPAAAAOhAWJP+I7MSKfEys4Wx0TbiZXwAJA8AALAgt9ut/Px8ud3uWIcSc/zhbS7WpP/IrIvleJnZwthoG/EyPgCSBwAAWJDb7VZBQQHJA/GH909Fmkyx0pr0WCfJuFhuykpjA4D1kDwAAABtJtYXh2ayygyISJMpVlqTHuskGRfLTVlpbACwHpIHAABYTDxt4hbri0MzmTEDwioJCBzBxTIAhI7kAQAAFsNu+PGLJRgAgPaK5AHQhjwej3Jzc2Wz2ZSbm9uu7x4CiB52PAcAAFZD8gBoQw6HQ0VFRaqqqlJRURF3DwGEhE3cAISDZTEA2hLJA6ANcfcQQDjiZRO3eNq7AWgPWBYDoC2RPADaEHcPAYQjXjZxY+8GAADiB8kDoA25XC7l5OTIZrMpJyen3d49BIBwMPsKAID40SnWAaA5j8ejzMxMv2V5eXnKy8uLckQIl91uV2FhYazDANAOxcPa5ezsbBUVFcnr9TL7CgCAGHI6nXI6nX7LQl1WSPLAgux2u0pLS2MdBgAghhrXLrdnLpdLl112mZYvX96u926IR/GQnAIAhC7YTeiMjAyVl5e32AfLFgAAQJuIl70b4hEb6wEAWovkAQAAccjtdis/P19utzumfQCBcBoHALQvJA8AAIhDbrdbBQUFEScPIu0DCITTONAesMQH+BHJAwAAAEQdp3GgPWCJT/xh1lP4SB4AAIA2w107BJKdna2kpCRJiulpHIxRWB1j1FzMegofyQMAAI4SD+v8zbirYtadGe7aIRCXy6Vx48ZJUkxP42CMwuoYo+Zi1lP4SB4AAHAUs/YKiGUCwoy7KtyZQVvjNA4AsWCVWU/tEckDAAD+w6y77bHeaNCMuyrcmQEQLqbZw8qsMuupPSJ5AACIG5He8Y+Xu+1m3FXhzgyAcDHNHlbGrKfwkTw4ytixYzV8+PCw2x8+fFjPPfecLrjgAg0dOlTdunXTySefrKuvvlqrV682L1AAQDMej0eXX365CgoKdPnll4c1a8CMu+1W2MXZjLsq3JkBOiZmDcQn/rvCDCQP/mPNmjX66quvwm5/6NAhnXvuuZo5c6YWL16sf//73zp48KDWrl2rV155RaeddpoeeOABEyMGABzNjFkDZtxtt8LsBTPuqnBnBuiYmDUQn+Llv6sVEvQdGckDSZs2bdL06dMj6mPu3LlaunSpEhMTdd9996msrEzV1dUqLi7WlClT1NDQoAcffFCvv/66SVEDAI5mxqwBM+62s1cAAABtwwoJ+o6swyYP1q1bp1tvvVWTJ0/WiSeeqPXr14fdV319vZ599llJ0u9//3s99NBDOumkk9SzZ09lZ2dr4cKFmjFjhiTpzjvvNCV+dBwej0e5ubmy2WzKzc0lwwoEYMasATPutltlrwCmqAIA4g0J+tjqsMmDVatW6YknntBHH32khoaGiPr64YcfVF1dLUm65ZZb/Na57777JB2Z5VBZWRnR66FjcTgcKioqUlVVlYqKisiwAgGYtUY/0otuq+wVEC9TVAEAaGSVBH1H1WGTBxdffLHWrl3rezz44INh9/X9999Lknr16hXwLtXgwYN9P2/atCns10LHQ4YVCI1Za/QjveiOp70CmL0AALASqyToO6pOsQ4gVvr06aM+ffr4fl+1alXYfZ144olasGCBevToEbDO0actDBkyJOzXQseTnZ2toqIieb1eMqxAC6xysWuVOCLVmEgBAMAKGhP0p512WrtP0LdHHTZ5YKaBAwdq4MCBActra2t19913S5ImT54sm80WtD/DMHzLIMKRkpKilJSUsNvDWlwulxwOh1auXKmsrCwyrIhbbrdb8+fP18yZM8O+6LbKxa5V4gAAAPGvtrZWtbW1Ybc3DCOkeiQP2tjWrVvlcDi0bNkypaSkaN68eS22qaioUO/evcN+zblz5/JHaxyx2+0qLCyMdRhAm/J4PLr88su1fPlyFRUV6fXXX+duAtABxMssHQCIpXnz5qmgoKDNX4fkQRupqanRH//4R/3pT3/SwYMH1blzZy1YsEDZ2dkttk1LS9M333wT9msz6wBANHk8Hk2bNk0rVqzQ+PHjtWDBglZf+Ps7eomkGRD/mKUDdCwkDNvGnDlzdMcdd4TdfsSIEaqoqGixHskDkxmGoYULF2r27Nm+I/VOO+00vfjiixo5cmRIfSQkJKhXr15tGSYAmMbhcOjjjz+W1+vVxx9/HNaFPxuDAgAQ/0gYto1Il60nJCSEVK/DnrbQFnbu3KkpU6Zo6tSp8ng8GjBggF588UUVFxeHnDgAgPbGjAt/jl4CAACwNpIHJtm7d6/OPfdcvfHGG5Kku+66S2VlZbrmmmt8fxADseLxeJSbmyubzabc3FzfrJj2KJ7eS7ww48Kfo5cAAACsjeSBSWbMmKHVq1erV69eeuONN/Too4+qS5cusQ4LkHRkWnlRUZGqqqpUVFQkh8MR65DCFk/vJV6YceFvt9u1cOFCzZ07VwsXLmSzRAAAAIsheWCCsrIyLVq0SJL01ltv6ZJLLoltQMBPxNN68nh6L1bg8Xg0efJkdevWTZMnTw5rJodZF/6N6yDZRAkAAMB6SB60wpw5czR8+HANHz68yfMLFiyQdGTq7jnnnBODyIDgzJhWbpXlAqyNN1fjZocHDx70bXYYDi78AQAA4hvJg1Zwu90qKytTWVlZk+e3bNki6cgd0YSEhBYfmzdvjkH06MhcLpdycnJks9mUk5MT1rRyqywXcLlcOvvss9W1a1edffbZrI2PEDM5AAAAEAqOajTBjh07Yh0CEJTdbm/10Xk/ZZWLTLvdrg8//DAmrx2PsrOzVVRUJK/Xy0wOAAAABMTMg/9wOBwyDEPffvttwDoul0uGYcgwjCbPL1682Pd8KI9Bgwa18bsBzBdPSx/wI045AAAAQChIHgAIiRnLBayy9AE/4pQDAAAAhIJlCwBCYsZyAassfUBTjZsdAgAAAIEw8wBA1HBSwo/MOCIRAAAAiBaSBwCixoxTH+KFWUckut1u5efny+12mxsgAAAAcBSWLQCIGjNOfYgXZizh8Hg8uvzyy7V8+XIVFRXp9ddfZ88CAAAAtAlmHgBADJixhMPhcKi4uFiSVFxczAaUAAAAaDMkDwAgBsw4vYINKAEAABAtLFsAgBgw4/SK7OxsFRUVyev1dvgNKAEAANC2mHkAAK1klZMSzJi9AAAAAISCmQcW5PF4lJmZ6bcsLy9PeXl5UY4IwNEaT0rwer2+kxJisRGkGbMXAAAAEP+cTqecTqffslBvhJE8sCC73a7S0tJYhwHEJY/Ho2nTpmnFihUaP368FixY0OoTCthrAAAAAO1JsJvQGRkZKi8vb7EPli0A6FAaZw0cPHjQN2ugtcw4KQEAAABoT0geAOhQzJg1wF4DAAAA6GhYtgCgQzHjhAL2GgAAAEBHw8wDAB2Ky+VSTk6ObDabcnJymDUAAAAAhICZBwA6FLvdHpOTEQAAAID2jJkHAAAAAAAgKJIHaLXa2lrl5+ertrY21qEAfjFGYXWMUVgdYxRWxxiF1cXjGCV5gFarra1VQUFBXP2PgPjCGIXVMUZhdYxRWB1jFFYXj2OU5AEAAAAAAAiK5AEAAAAAoMNITU3V3LlzlZqaGutQ2hVOWwAAAAAAdBipqanKz8+PdRjtDjMPAAAAAABAUCQPAAAAAADtAksOYodlCwAAAACAdoElB7HDzAMAAAAAABAUyYN2xul0xjoES7HK52GFOKwQg2SdOKzCKp+HFeKwQgySdeKwCqt8HsRhrRisxCqfB3FYKwYrscrnQRxNWSUOKzDrsyB50M7wP0FTVvk8rBCHFWKQrBOHVVjl87BCHFaIQbJOHFZhlc+DOKwVg5VY5fMgDmvFYCVW+TyIoymrxGEFJA8AAAAAAEBUsGGiBXk8HmVmZvotq6qqinI0AAAAAID2zOl0BpyB4PF4QuqD5IEF2e12lZaW+i0LlFQAAAAAAMCfvLw85eXl+S3LyMhQeXl5i32wbAEAAAAAAARF8gAAAAAAAASVYBiGEesgcETnzp11+PBhJSYmKjU11W8dj8cju90e5ciaMgxDFRUVSktLU0JCQkxjscLnYZU4rBCDVeJgjFozDivEYJU4GKPEYfUYGKPEYfUYGKPEYfU42tMYdbvdamhoUHJysurq6gLWI3lgIUlJSWpoaIh1GAAAAACADiYxMVFerzdgORsmWkiXLl106NAhJSUlqX///rEOBwAAAAAQ53bs2CGv16suXboErcfMAwAAAAAAEBQbJgIAAAAAgKBIHgAAAAAAgKBIHgAAAAAAgKBIHgAAAAAAgKBIHgAAAAAAgKBIHiAkhmHo+eef1/jx49WrVy/16tVL48eP1/PPPy8O7IAVvPnmm5o8ebL69u2r7t27a8yYMXrsscd0+PDhoO2WLVumCy+8UP3791fXrl01fPhwPfDAA9q3b1+UIkdHwjhFNOzcuVOzZ8/W+PHjdcwxx+i4447TxIkT9cc//lG1tbVB2zJGYXXhjrU1a9Zo2rRpSk1NVUpKioYMGaLbbrtNO3fujFLk6AgiuWYK9/s3qgygBQ0NDcb06dMNSX4fv/71r42GhoZYh4k4deqppxrDhg0LWufee+8NOD4nTpxoHDp0yG+7Z555xkhISPDbLjMz09i1a1dbvCW0c5WVlcb9999vTJo0yUhPTzd69uxpjB8/3rj11lsNj8cTsB3jFNHw8ccfGzabLeBYGzp0qLF9+3a/bRmjiLVnn33WkGTMnDnTb3m4Y+3tt982UlJS/LZLS0szNm7c2JZvC+1QYWFhwO/Dox81NTW+NpFcM4X7/RttJA/QIqfT6Ru8c+fONTZs2GBs2LDBmDt3ru/5p556KtZhIg6tXr3akBQ0ebB48WLfOJw1a5axZs0aY+vWrcYTTzxhJCUlGZKMO++802/fnTp1MiQZV1xxhbFixQpj+/btxosvvmj07NnTkGRcfvnlbfn20A5t2LDByMjICPgP/DHHHGO88cYbzdoxThENdXV1xvDhw30XUu+9956xa9cuw+12Gy+88IIvqXDZZZc1a8sYRayVlZUZ3bp1C5g8CHesVVRU+MonTZpkfPTRR8bOnTuNhQsXGunp6YYk4/TTT+dGGJr485//3OrkQbjXTOF+/8YCyQMEVVtba6SlpRmSjLvvvrtZ+V133eXL2tbV1cUgQsSr77//3hg5cmSLyYPTTz/dkGRceeWVzf7hb/wS79q1q7Fz584mZZdffrkhyTjzzDON2traJmXvvPOO70t83bp15r0ptGsNDQ3GuHHjDElGnz59jBdeeMH44YcfjF27dhlLliwxTjnlFEOS0bNnT2PTpk1N2jJOEQ0LFiwwJBkpKSnGtm3bmpW//fbbvjHz09kHjFHEUl1dnW8MBkoehDvW7rzzTt+sm927dzcp++KLL3wzEhYvXmz6+0L7deONNxqSjPvvvz+k+pFcM4X7/RsLJA8Q1AcffGBIMhITE/1OBausrDQSExMNScbSpUtjECHiydq1a41bbrnFmDRpkm9cBUsebNy40VdnzZo1zcrr6+uNvn37GpIMl8vle37fvn2+Pxbeeustv32PGTPGkGTk5+eb8+bQ7q1cudI33t5///1m5fv27TOGDRtmSDKuu+463/OMU0TLfffdZ0gyLrnkEr/lXq/Xd2e3qKjI9zxjFLHWOHYDJQ/CHWsNDQ3G8ccfb0gy/vKXv/htd8kllxiSDIfDYd4bQrt3zjnnGJKMV199NaT64V4zhfv9GytsmIigli1bJkmaMGGC+vbt26zcZrPpjDPOaFIXCNeqVav0xBNP6KOPPlJDQ0OL9RvHXEZGhkaPHt2sPCkpSbm5uU3qSlJJSYlqa2uVkpKin//85377Pv/885u1Q8e2du1aSdLw4cP1i1/8oll59+7ddfvtt0s6MsYaMU4RLRs3bpQkDRo0yG95YmKievfuLUnas2eP73nGKGLp008/1bx585SWlqYLL7zQb51wx9rmzZv1ww8/NCkPpR1QVlYmSRo1alRI9cO9Zgr3+zdWSB4gqPLycknSuHHjAtbJzs5uUhcI18UXX6y1a9f6Hg8++GDQ+kePz4SEBL91/I3Pxp9HjRql7t27h9wOHdv3338vSTrppJMCjrcTTjhBkrRp0ybfc4xTRMuCBQtkGIb+/Oc/+y3fuHGj3G63JGnkyJG+5xmjiJXq6mrNmDFDDQ0Ncrlcfi+6pPDHWuPPNpvN9/0crJ3BCWLQkXHpdruVnJysyspKXXjhhcrIyFCfPn10zjnn6IEHHtCBAweatAn3minc799Y6RTrAGBtHo9HkgJ+mUtHvpAlaceOHVGJCfGrT58+6tOnj+/3VatWBa0f7vhkXCMcF110kUaOHKkhQ4YErPPll19KUpM6jFPEimEYqqmp0a5du/Txxx/rkUcekSRNmTJFI0aM8NVjjCJWZs+erc2bN+vWW29VTk6OXnnlFb/1ojFG6+rqVF1d7Zudg46rcdZBfX29Jk6c2KRs2bJlWrZsmV599VUtXLjQN1ugo3yPMvMAQTUO6KMv6H6qcbA31gWiJdzx2Zp2e/bsafFcdHQMWVlZuuqqq3x3AH5q69ateuyxxyRJU6dO9T3POEWsvPXWW+rdu7eGDBkih8OhDRs26Oabb9ZLL73UpB5jFLHw2muv6aWXXlJmZqbmzZsXtG64Y6017Y6uj46tMXlgGIZGjRqlt99+Wzt27NDGjRv1zDPPqGfPntqwYYOmT5+u+vp6SdH5HrXC+CR5gKB2794tSerRo0fAOo1llZWVUYkJaBTu+GxNO0natWtXRHEi/n366aeaOHGiduzYoUGDBmn27Nm+MsYprOTjjz/WV1991eQ5xiiibdu2bZo5c6aSk5P18ssvq2vXrkHrhzvWQmnXpUsXJSYeuSTib1lIR5YtjBw5Urm5uVq2bJkuvPBCHXvssRoyZIhuvPFGffzxx0pMTNTatWv13HPPSYrO96gVxifJAwTVmAWrqakJWGfv3r2SxDQvRF2447M17SSpV69eEcWJ+LV582ZNnz5dZ511ljZv3qy0tDS9//77OuaYY3x1GKeIlUsuuUQNDQ3yeDwqKirSz372M3399dc699xztW7dOl89xiiiqaGhQddee6327NmjBx98UKeeemqLbcIda6G0279/v2+TZv6WhSTNmjVL69at05IlS/wuJxgzZox+/etfS5L+9a9/SYrO96gVxifJAwR13HHHSfoxK+ZPY1ljXSBawh2frWnXo0ePoNlgdEx1dXUqKCjQsGHD9Pe//12SNG3aNK1du1ZDhw5tUpdxilhKSEhQ//799Ytf/EL/+te/NGLECB04cECPP/64rw5jFNH05z//WR9++KHOOuss3XnnnSG1CXestabd0fWBlkyYMEGSVFpaKik636NWGJ8kDxCU3W6XFHyqYVVVlSQpNTU1KjEBjcIdn4xrRGL16tU6/fTTlZ+fr7q6Ok2YMEGffPKJ/v73v/u9Q8E4hVV06dLFd7ds9erVvucZo4iWjRs36t5771XPnj310ksvKSkpKaR20RijycnJQTetA442cOBAST+OrY7yPUryAEGlp6dLklasWBGwTnFxsSQpLS0tKjEBjRrHZ3FxccDjlfyNz8Z269atCzhNjHENf77++mudc845Wrt2rbp3766//e1v+vTTT3XmmWcGbMM4RbSkp6erR48evmm0/jT+oXr48OEm7STGKNreDz/8oLq6OtXU1Gjw4MFKSEho8njxxRclSfPnz/c99+abb4Y91hrb7d69Wxs2bGixXaCj8tBxHD58WO+++67efffdoEsJGo+9HT58uKTwr5nC/f6NFZIHCKrxeJIVK1b4zYjt2rXLN6AnTZoU1diAs88+W5JUUVGhNWvWNCv3er167733JDUdn9nZ2UpJSdHhw4f1wQcf+O27sLCwWTt0bDU1NfrVr36lvXv3avjw4SopKdHVV1/d4h+bjFNEi91u1/79+/Xdd98FrPPNN99Ikk4++WTfc4xRWF24Y23gwIEaMGCAJGnJkiUht0PH1alTJ918883Kzc31LUv0p/E48czMTEnhXzOF+/0bMwYQRG1trZGWlmZIMn73u981K7/77rsNSUZ6erpRV1cXgwgRz1544QVDkjFs2LCAdbKysgxJxuWXX240NDQ0KXv66acNSUa3bt2MysrKJmVXXHGFIck444wzjNra2iZlixcvNiQZkoz169eb94bQrs2fP9+QZPTr18/YuXNnq9oyThEN06ZNMyQZo0ePNurr65uVb9++3ejTp48hyXA6nU3KGKOwgmuvvdaQZMycObNZWbhj7a677jIkGSeccIKxe/fuJmVffPGFkZKSYkgyCgsLTX8/aJ8ax8yJJ55o7N27t1n5hg0bjOTkZEOS8cknnxiGEdk1U7jfv7FA8gAteuaZZ3xfyAUFBcbGjRuNsrIyIz8/3/f8/PnzYx0m4lAoyYMlS5b4xuHNN99srFu3ztiyZYvx5JNPGp06dTIkGXPmzGnWbs2aNb7yqVOnGitXrjTcbrfx0ksvGT179jQkGdOmTWvLt4d2ZuLEiYYk4+677251W8YpomH16tVGYmKiIcn4xS9+YSxfvtzYs2eP4Xa7jX/+85/GCSecYEgyxowZ0+ziizEKKwiWPAh3rLndbqNXr16GJGPy5MnGsmXLjJ07dxr//Oc/jYyMDEOSMWHChGYXbei4Nm/e7Eu0ZmdnG0uXLjX27t1rbN682XjhhRcMm81mSDJmzJjRpF2410zhfv/GAskDtKihocGYPn26b1D/9OFwOPjCRZsIJXlgGIZx7733BhyfOTk5zf5IbvTss88aCQkJftudcsopxp49e9ribaGdGjRoUMBx9tPHwIEDm7VnnCIa/t//+38Bx4skY+TIkUZpaanftoxRxFqw5IFhhD/WFi1aZHTu3Nlvu+OPP97YsmVLW74ttEOLFy/2zUrx9xg/fnyzmQCRXDOF+/0bbSQPEJKGhgbjf//3f43s7GyjR48eRo8ePYxx48YZLpeLxAHaTKjJA8MwjDfeeMOYOHGi0bt3b6Nr167GKaecYjz++OPG4cOHg7ZbunSpcd555xk2m81ISUkxhg0bZuTn5xv79+83620gTnTr1i2i5IFhME4RHSUlJcZll11mZGZmGl27djUGDBhg/OpXvzIef/zxFpcYMkYRSy0lDwwj/LG2evVqY+rUqUb//v2Nzp07G4MGDTJuv/12Y9euXWa/DcSJLVu2GNdff70xatQoo3v37sagQYOMSy+91Jg/f37A79JIrpnC/f6NpgTDCLCtIwAAAAAAgDhtAQAAAAAAtIDkAQAAAAAACIrkAQAAAAAACIrkAQAAAAAACIrkAQAAAAAACIrkAQAAAAAACIrkAQAAAAAACIrkAQAAAAAACIrkAQAAAAAACIrkAQAAAAAACIrkAQAAAAAACIrkAQAAAAAACIrkAQAAAAAACIrkAQAAAAAACIrkAQAAAAAACOr/B/JGIOq+RT3XAAAAAElFTkSuQmCC\n",
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\n",
       "text/plain": [
-       "<Figure size 1200x1200 with 2 Axes>"
+       "<Figure size 1200x900 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -327,13 +908,13 @@
     }
    ],
    "source": [
-    "datamc.plot_datamc_all()"
+    "s2.plot()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
-   "id": "70efe610-3668-43e2-8bc4-d0eaaaac5d2d",
+   "execution_count": 30,
+   "id": "3787a08f-a9e9-467c-ac70-545b428c845c",
    "metadata": {
     "tags": []
    },
@@ -341,37 +922,183 @@
     {
      "data": {
       "text/plain": [
-       "<pocket_coffea.utils.plot_utils.PlotManager at 0x7f3bdef04d90>"
+       "['__add__',\n",
+       " '__class__',\n",
+       " '__delattr__',\n",
+       " '__dict__',\n",
+       " '__dir__',\n",
+       " '__doc__',\n",
+       " '__eq__',\n",
+       " '__format__',\n",
+       " '__ge__',\n",
+       " '__getattribute__',\n",
+       " '__gt__',\n",
+       " '__hash__',\n",
+       " '__init__',\n",
+       " '__init_subclass__',\n",
+       " '__le__',\n",
+       " '__lt__',\n",
+       " '__module__',\n",
+       " '__ne__',\n",
+       " '__new__',\n",
+       " '__reduce__',\n",
+       " '__reduce_ex__',\n",
+       " '__repr__',\n",
+       " '__setattr__',\n",
+       " '__sizeof__',\n",
+       " '__str__',\n",
+       " '__subclasshook__',\n",
+       " '__weakref__',\n",
+       " '_get_err2',\n",
+       " '_get_err2_from_syst',\n",
+       " '_is_empty',\n",
+       " '_n_empty',\n",
+       " 'datamc',\n",
+       " 'down',\n",
+       " 'err2_down',\n",
+       " 'err2_up',\n",
+       " 'is_mcstat',\n",
+       " 'name',\n",
+       " 'nominal',\n",
+       " 'nsyst',\n",
+       " 'plot',\n",
+       " 'ratio_down',\n",
+       " 'ratio_up',\n",
+       " 'style',\n",
+       " 'syst_list',\n",
+       " 'up',\n",
+       " 'xbinwidth',\n",
+       " 'xcenters',\n",
+       " 'xedges']"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 30,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "from pocket_coffea.utils.plot_utils import PlotManager\n",
-    "\n",
-    "plotter = PlotManager(o[\"variables\"])\n",
-    "plotter"
+    "syst_tot = syst_manager.total\n",
+    "dir(syst_tot)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
-   "id": "c922cbf7-0bdd-45fc-843d-5667c9e6a968",
+   "execution_count": 31,
+   "id": "94d67dde-bb55-4df8-b166-648330d54212",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['JER',\n",
+       " 'JES_Total',\n",
+       " 'pileup',\n",
+       " 'sf_btag_cferr1',\n",
+       " 'sf_btag_cferr2',\n",
+       " 'sf_btag_hf',\n",
+       " 'sf_btag_hfstats1',\n",
+       " 'sf_btag_hfstats2',\n",
+       " 'sf_btag_lf',\n",
+       " 'sf_btag_lfstats1',\n",
+       " 'sf_btag_lfstats2',\n",
+       " 'sf_ele_id',\n",
+       " 'sf_ele_reco',\n",
+       " 'sf_ele_trigger_era',\n",
+       " 'sf_ele_trigger_ht',\n",
+       " 'sf_ele_trigger_pileup',\n",
+       " 'sf_ele_trigger_stat',\n",
+       " 'sf_jet_puId',\n",
+       " 'sf_mu_id',\n",
+       " 'sf_mu_iso',\n",
+       " 'sf_mu_trigger',\n",
+       " 'mcstat']"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "[s.name for s in syst_tot.syst_list]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "36cfc805-5d95-4546-862d-bfe8287bb492",
    "metadata": {
     "tags": []
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(<bound method Artist.get_figure of <AxesSubplot: >>, <AxesSubplot: >)"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1200x900 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "#plotter.plot_datamc_all()"
+    "syst_list_btag = [s for s in syst_tot.syst_list if s.name.startswith(\"sf_btag\")]\n",
+    "syst_btag = SystUnc(name=\"btag\", syst_list=syst_list_btag)\n",
+    "fig, ax = syst_tot.plot()\n",
+    "syst_btag.plot(ax=ax)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "a3874d45-10d5-43bf-aa82-7479b48a9e71",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 2.38378415e+05,\n",
+       "       2.37628049e+05, 2.00992189e+05, 1.63296976e+05, 1.27664658e+05,\n",
+       "       9.98019590e+04, 7.59419451e+04, 6.01856752e+04, 4.62802357e+04,\n",
+       "       3.56882614e+04, 2.77513957e+04, 2.16801587e+04, 1.69295329e+04,\n",
+       "       1.32757362e+04, 1.04277639e+04, 8.31632294e+03, 6.68277165e+03,\n",
+       "       5.37253263e+03, 4.34722996e+03, 3.51209968e+03, 2.86437024e+03,\n",
+       "       2.33327176e+03, 1.90469949e+03, 1.57580711e+03, 1.28901482e+03,\n",
+       "       1.06841478e+03, 9.08351392e+02, 7.71220244e+02, 6.33041587e+02,\n",
+       "       5.17515526e+02, 4.61499958e+02, 3.83540757e+02, 3.19845397e+02,\n",
+       "       2.83522777e+02, 2.39171695e+02, 2.12657796e+02, 1.80037133e+02,\n",
+       "       1.53940332e+02, 1.34781246e+02, 1.20977158e+02, 1.05021016e+02,\n",
+       "       8.65065829e+01, 7.81180913e+01, 6.60693264e+01, 6.33138114e+01,\n",
+       "       5.62289338e+01, 4.97717261e+01])"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "syst_manager.total.up"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "8d712bd2-e9be-4410-aa27-f06b6b057460",
+   "id": "d00bfe3a-6a60-4725-a8c6-8345a6bd2a12",
    "metadata": {},
    "outputs": [],
    "source": []
-- 
GitLab


From d62710f9c984490a2273dfa55cf581a7442767b9 Mon Sep 17 00:00:00 2001
From: mmarchegiani <matmarcheg@gmail.com>
Date: Tue, 28 Mar 2023 13:35:08 +0200
Subject: [PATCH 07/24] New implementation of plotting script

---
 notebooks/plotting/test_DataMC.ipynb | 107 +++++++++++++++++----------
 pocket_coffea/parameters/plotting.py |  88 ++++++++++++++++++++++
 pocket_coffea/utils/plot_utils.py    |  91 ++++++++++++++++++-----
 scripts/plot/make_plots.py           |  49 +++++-------
 4 files changed, 244 insertions(+), 91 deletions(-)
 create mode 100644 pocket_coffea/parameters/plotting.py

diff --git a/notebooks/plotting/test_DataMC.ipynb b/notebooks/plotting/test_DataMC.ipynb
index 5c6afc9d..03e59d6d 100644
--- a/notebooks/plotting/test_DataMC.ipynb
+++ b/notebooks/plotting/test_DataMC.ipynb
@@ -21,7 +21,7 @@
     {
      "data": {
       "text/plain": [
-       "<pocket_coffea.utils.plot_utils.DataMC at 0x7f1c2f805850>"
+       "<pocket_coffea.utils.plot_utils.DataMC at 0x7f7fed685400>"
       ]
      },
      "execution_count": 2,
@@ -85,6 +85,7 @@
        " 'xbinwidth',\n",
        " 'xcenters',\n",
        " 'xedges',\n",
+       " 'xlabel',\n",
        " 'years']"
       ]
      },
@@ -255,19 +256,19 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:180: RuntimeWarning: invalid value encountered in true_divide\n",
+      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:200: RuntimeWarning: invalid value encountered in true_divide\n",
       "  self.ratio = num / den\n",
-      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:181: RuntimeWarning: invalid value encountered in true_divide\n",
+      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:203: RuntimeWarning: invalid value encountered in true_divide\n",
       "  self.ratio_unc = np.sqrt(num) / den\n",
-      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:337: RuntimeWarning: invalid value encountered in true_divide\n",
+      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:389: RuntimeWarning: invalid value encountered in true_divide\n",
       "  return np.where(self.nominal != 0, self.up / self.nominal, 1)\n",
-      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:341: RuntimeWarning: invalid value encountered in true_divide\n",
+      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:393: RuntimeWarning: invalid value encountered in true_divide\n",
       "  return np.where(self.nominal != 0, self.down / self.nominal, 1)\n"
      ]
     },
     {
      "data": {
-      "image/png": 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uAAAAAELWY489ptmzZwe6DMOEZeiyb98+PfTQQ5ozZ46OHTsmSerYsaPeeOMNlwVfO3To4Lx94MABr33u37/febvprAv6UIuzUPr27astW7Z4beNNMM9yCbrAJS2NwAUAAABAyPrDH/6ge+65p833HzhwoHbt2mVgRe0TVqGLw+HQwoULddddd6m6utr59czMTP3nP//RwIEDXdp37tzZebu2ttZr302PN53lQR8tz4oxmUyKj4/32iZUBV3g4m4MAhcAAAAAIaK9y0uYTCYDq2m/sNn2pLq6Wtdee61uvPFGZ+DSvXt3Pfnkk/r000+bBS6SlNjkQ25LIcO+ffuct5suIksfrn1EGgIXAAAAAIAnYTHTZdu2bbrgggu0Z88eSVJ0dLTuuOMOPfjggy5BwonOOuss5+3du3d7HaOxb0nq378/fXjoI9KEc+DS0NBACAMAAAAA7RDyM12qqqqUnZ3tDAHOPvtsffrpp5ozZ47XwEWSMjIynLfff/99r23fe+89SVJUVJRLyEAfUREduoRz4GKxWFr1HAAAAAAA3Av50OWnP/2ptm3bJkmaMGGCioqKNHz48Fbd9+yzz1ZKSookadWqVWpoaHDbzmq1OrecHjVqlLp160YfHvqIZOEWuLR0iRkAAAAAwLuQDl3Kysq0bNkyScdXKF6yZEmLi7o2ZTKZNGXKFElSXV2ds68TLVy40Hn7iiuuoA8vfUSqoAlcqqsNC1zMZvPJPg0AAAAAgCZMDofDEegi2urhhx/WAw88IEl6/fXXdfXVV590H9u3b1f//v1lt9uVlpamjz76SGlpac7jJSUlGj9+vOrq6tSjRw/t3Lmz2U489OF+Z6LU1FRVVFQoJSVF5eXlLb0Uoen224MrcKmqUtZf/2pI4OJu62kAAAAACGbB9jk0pBfS3bRpk/P2V199peeee65V97v44ouduxmdccYZuv/++/XII4+orKxMQ4cO1S233KLU1FRt3rxZCxcuVH19vSTp6aefdhsw0EfkCrrApXdvAhcAAAAACBIhPdNl/PjxWr169Unf78UXX1ROTo7z3zabTdOnT9c///lPt+1NJpMeeeQR3X///R77pI/mgi1h9IXFl14aXIFLYqI0d67rGAQuAAAAACJEsH0ODek1XSorKw3pJzo6Wv/4xz+0dOlSTZo0SX369FGHDh106qmn6oYbbtCaNWtaDBjoIzIFXeBy4hgELgAAAAAQMCE90wXBLdgSRl+ovOWW4Atc/jvThcAFAAAAQKQJts+hIT3TBQi0oAtcGscwIHApKSlp8fEDAAAAADwjdAEMFE6BS1FR0ck+fAAAAABAE4QugEGCInA5fNiwwCUrK+tknwIAAAAAQBMhvWU0ECyMCFxio6I0JT3d6ziZiYlu+2+U1KmTYYGLu62nAQAAAACtx0wXoJ2MmuFiFAIXAAAAAAgOhC5AOxh5SZFRCFwAAAAAIDhweRHQDsvufeP43//948l3kr5ooa+HDappZpPbBC4AAAAAEDjMdAHCFIELAAAAAAQWoQsQhowIXCorK/1RKgAAAACELUIXIMwYFbhYLBZ/lAsAAAAAYYvQBQgzRgUuCQkJ/igXAAAAAMIWoQsQZloKXN577z299NJLmjBhgrKzs2W1Wp3HmwYuZrPZn2UDAAAAQNghdAHCTEszXN566y2tXbtWNTU1KigoUE5OjqTmgcuJW08DAAAAAE4OoQsQZlq6pOjLL7+UzWaTJNlsNhUWFhK4AAAAAIAPELoAYe7ENVxGjBih6OhoSVJ0dLSGDh1K4AIAAAAAPkDoAoQxd4vm5ufna8KECerVq5fGjRunyZMnE7gAAAAAgA/EBLoAAMYqnnf87y/LSlS6o0gZ6VlyKFPFRY0tkvXIlctVc3Gl1myy6NhXCTqlg1lfvOgauByzNWjkHYQwAAAAANBWhC7wOavVqoyMDLfHcnNzlZub6+eKwl/TwOXstObbQtfUHQ9cunVO0JghZsVENw9cPt5o0UhN8VfJAAAAANAqeXl5ysvLc3us6e6swYDQBT6XnJys0tLSQJcRMYwKXL4/VOuvkgEAAACg1bz9531qaqoqKir8XJFnrOkChBmjApfRg83+KhkAAAAAwhKhCxBmjApcesY333oaAAAAANB6hC5AmCFwAQAAAIDgQOgChDkCFwAAAAAIDEIXIIwRuAAAAABA4BC6AGGKwAUAAAAAAovQBQhDRgQuX5aV+KtcAAAAAAhLhC5AmDEqcCndUeSvkgEAAAAgLBG6AGHGqMAlIz3LXyUDAAAAQFgidAHCjFGBi7utpwEAAAAArUfoAoQZAhcAAAAACA4xgS4AgLFGrr/T5d8NdrssZWXqVV+vn6SlKWnrp83uU1JdrYNVVbq6d29lVhVLVY1H5vq+YAAAAAAIU8x0AcJYY+BSW18vc1qakjp1atampLpaRVVVyurdW5mJiQGoEgAAAADCE6ELEKYIXAAAAAAgsAhdgDBkROBSefiwP0oFAAAAgLBF6AKEGaMCF0tZmT/KBQAAAICwRegChBmjApeEuDh/lAsAAAAAYYvdi4B2mFk9NtAlNJNfH2VI4GJOS/NHuQAAAAAQtpjpAoQZowKX2ChODwAAAADQHnyqAsIMgQsAAAAABAc+WQFhjsAFAAAAAAKDT1dAGCNwAQAAAIDA4RMWEKbaG7g02O3+KhUAAAAAwhKhCxCGjAhcLGVlys/PV2VlpfsxSko0b948lZSUuD1eWVmp/Px8LV68WA0NDe1/UAAAAAAQYghdgDBjVOBSW18vs9mspKSk5mOUlKioqEhZWVnKzMxsPkZlpSwWixISEmQ2mxUbG2vcAwQAAACAEEHoAoQZwwKXtDQCFwAAAABoB0IXIMwYFri423qawAUAAAAAWo3QBQgzBC4AAAAAEBxiAl0Awp/ValVGRobbY7m5ucrNzfVzRZEnqVMn5QwY4PF4bFSUpqSnezze3sCloaGBEAYAAACAIfLy8pSXl+f2mNVq9XM13hG6wOeSk5NVWloa6DLQRkYELhaLRVOmTPFXyQAAAADCmLf/vE9NTVVFRYWfK/KM0AUIMw//bK5hfV1uUOBSW1trWE0AAAAAECpY0wWAR0YFLmaz2V8lAwAAAEDQIHQB4JFRgYu7racBAAAAINwRugDwiMAFAAAAANqO0AVAqxG4AAAAAEDrEboAaBUCFwAAAAA4OYQuAFpE4AIAAAAAJ4/QBYBXRgQuJSUl/ioXAAAAAIIGoQsAj4wKXIqKivxVMgAAAAAEDUIXAB4ZFbhkZWX5q2QAAAAACBqELgA8Mipwcbf1NAAAAACEO0IXAB4RuAAAAABA2xG6APCIwAUAAAAA2o7QBUCrELgAAAAAwMkhdAHQIgIXAAAAADh5hC4AvDIicKmsrPRHqQAAAAAQVAhdAHhkVOBisVj8US4AAAAABBVCFwAeeQtcrFarRo8erbFjx+qll15SSkpKs/s3Bi4JCQn+KhkAAAAAgkZMoAsAELw+f6tWoweb9d2iJH13wrGf/u9V2vjtZ3I47Prss7W66uIcPXvXcufxmrpKrdlkUbfOCRo4xOzfwgEAAAAgCDDTBYBHoweb1TO++SVFX5aVaGv5BjkcdkmS3W7T5h2FzuNNA5cxQ8yKiY5t1gcAAAAAhDtCFwAeeQpcSncU6azUoYqOipYkRUdFa1D6cEkELgAAAADQiNAFQKs1Bi4Z6Vl64o43NXLgBHXv0ksjB07Qgzn5BC4AAAAA0ARrugBolaaBy9lpx3cp8rSGC4ELAAAAADDTBUAruAtcmmopcDlma/BXqQAAAAAQNAhdAHhlRODy8UaLv8oFAAAAgKBB6ALAI6MCl+8P1fqrZAAAAAAIGqzpAoSZmdVjDevrjztuNiRwGT3YbFhNAAAAABAqmOkCwCOjAhd3W08DAAAAQLhjpgt8zmq1KiMjw+2x3Nxc5ebm+rkitBaBCwAAAIBgk5eXp7y8PLfHrFarn6vxzuRwOByBLgLhKTU1VRUVFUpJSVF5eXmgy/ENi3GX8gSlxQNd/ll5+LAsZWVKiIuTOS1NsVGuk+Ua7HZZyspUW18vc1qakjp1+uHg3Ln+qBgAAABABAu2z6FcXgSgVdoVuAAAAABABCJ0AdAiAhcAAAAAOHmELgC8MiJwKamu9le5AAAAABA0CF0AeGRU4FJUVeWvkgEAAAAgaBC6APDIqMAlq3dvf5UMAAAAAEGD0AWAR0YFLpmJif4qGQAAAACCBqELAI8IXAAAAACg7QhdAHhE4AIAAAAAbUfoAqBVCFwAAAAA4OQQugBoEYELAAAAAJw8QhcAXhkRuFQePuyPUgEAAAAgqBC6APDIqMDFUlbmj3IBAAAAIKgQugDwyKjAJSEuzh/lAgAAAEBQiQl0AQCC15T0dK/HMxMTva7fktSpk3IGDDC4KgAAAAAIDcx0AQAAAAAA8AFmugDw6OGfzTWsr5mG9QQAAAAAoYHQBYDfNDQ0yGKxqLa2VmazWUlJSc3alJSUqKioSFlZWcrMzAxAlQAAAABgDC4vAuAXRgQulZWV/igVAAAAAAxB6ALAL4wIXCwWiz9KBQAAAABDELoA8AsjApeEhAR/lAoAAAAAhiB0AeAXRgQuZrPZH6UCAAAAgCEIXQD4hRGBS2xsrD9KBQAAAABDELoACAgCFwAAAADhjtAFgN8RuAAAAACIBIQuAPyKwAUAAABApCB0AeA37Q1cGhoa/FUqAAAAALQboQsAvzAicLFYLP4qFwAAAADaLSbQBSD8Wa1WZWRkuD2Wm5ur3NxcP1eEQDAicKmtrfVXuQAAAACCVF5envLy8twes1qtfq7GO0IX+FxycrJKS0sDXQYCzIjAxWw2+6tcAAAAAEHK23/ep6amqqKiws8VecblRQD8wojAJSkpyV/lAgAAAEC7EboACAgCFwAAAADhjtAFgN8RuAAAAACIBIQuAPyKwAUAAABApCB0AeA3BC4AAAAAIgmhCwC/8Ba4WK1WXXbZZerVq5dmzpyprKwst4FLSUmJP0sGAAAAgHYhdAHgF95muNx6660qKCjQ999/r9LSUv3ud79rdv+SkhIVFRX5q1wAAAAAaLeYQBcAIHjNrB5rWF9PrfuNBg4x64sXXQOXY7YGfbT6E9ntdkmSzWbTpx8VqnjeD22+LCtR6Y4iZaRnGVYPAAAAAPgaM10A+MWYIWbFRDcPXD7eaFHfXumKMkVLkqKiojUofbizTdPA5ey0TL/WDAAAAADtQegCwC88BS7fH6rVoz9foPMzJqh7l146f+AEPZiTL4nABQAAAEBo4/IiAH7XNHAZPdisnvFJevau5S5tCFwAAAAAhDpmugDwK3eBy4kIXAAAAACEA0IXAH5D4AIAAAAgkhC6APALIwKXmrpKf5QKAAAAAIYgdAHgF0YELms2WfxRKgAAAAAYgoV0AfhFr9Kn9ZO0NCVt/bTZsZLqah2sqtLVvXsrs6pYqnI9Xnn4sDaWlem8uDhJOX6pFwAAAADai5kuAPzCnJampE6dmn29pLpaRVVVyurdW5mJic2OVx4+LEtZmRLi4mROS/NHqQAAAABgCEKX/7Lb7VqwYIEmTJigU045RR07dtQZZ5yhadOm6YsvvqCPNvQBNGVE4BIbxSkLAAAAQOgwORwOR6CL8IX58+dr+vTpuvfee/X44497bXvo0CFdd911Wrp0qdvjsbGxeu655zR9+nT6aGUfkpSamqqKigqlpKSovLzca9uQZRkb6ApCx+KBLv9sc+Ayd64/qgUAAAAQgoLtc2jYrumyYMGCVrVzOBy6/fbbnQFDcnKybrrpJiUlJam4uFhvvPGGGhoa9Itf/EJpaWm67LLL6KOFPoCWMMMFAAAAQCQIy9Bl6dKlWr16davafvjhh/rPf/4jSTrvvPO0atUq9ezZ03n8nXfe0aRJk2Sz2XTnnXfqyy+/VExMDH146QPwhsAFAAAAQKQIq08zNTU1euKJJ3TTTTe1+j5PPPGE83Z+fr5LwCBJl112mWbMmCFJ2r59uxYvXkwfLfQBeNLewKXBbvdXqQAAAADQbmERulx33XU6/fTT1atXL/3+979XXV1dq+534MABFRQUSJKGDBmic845x227piHOkiVL6MNLH4AnRgQulrIyf5ULAAAAAO0WFqHLihUr9O233570/dasWaOjR49KkrKzsz22y8zMVFJSkiQ5Qwn6cN8H4IkRgUttfb2/ygUAAACAdguL0OWll17Sa6+95vyTl5fXqvuVNflf8/Hjx3tsFxUVpQsvvFCStHv3bu3bt48+PPQBeGJE4GJOS/NXuQAAAADQbmGxAuqUKVNc/r1jx45W3c9qtTpvJycne23bOLNDOr6WybBhw+jDTR+AJ0YELkmdOvmrXAAAAABot7AIXdqqaciQkJDgtW3TBWUrKyvpw0MfwMlI6tRJOQMGeDweGxWlKenp/isIAAAAAAxE6PJfPXr08Nq2aQhx6NAh+vDQhzsOh6PVixu7ExcXp7i4uDbfHwAAAAAQGurr61XfjrUcHQ6HgdW0X0SHLjU1Nc7bXbp08dq26fGmIQN9tBy67Nq1S927d/faxpsHH3xQs2bNavP9ERwe/tlcQ/qZaUgvAAAAAILRY489ptmzZwe6DMNEdOjSoUMH5+0DBw54vaRm//79zttNZ13Qh1qchdK3b19t2bLFaxtvmOWCpkpKSlRUVKSsrCxlZmY2O15ZWSmLxaKEhASZzWbFxsa6HG9oaJDFYlFtba1ycnL8VDUAAACA1vjDH/6ge+65p833HzhwoHbt2mVgRe0T0aFL586dnbdra2u9hgy1tbXO201nedBHy7NiTCaT4uPjvbYBWsuowMVsNvurZAAAAACt1N7lJUwmk4HVtF9YbBndVolNdlNpGiK403Rb5KaLyNKHax+ArxkVuDTdgQsAAAAAfCGiQ5ezzjrLeXv37t1e2+7Zs8d5u3///vThoQ/A1whcAAAAAISKiA5dMjIynLfff/99j+1sNptWr14tSUpKSlKvXr3ow0MfgL8RuAAAAAAIVhEdulxwwQXOxWPfeecdj+2Ki4udO/tMmDCBPrz0AfgTgQsAAACAYBbRoUvXrl11ySWXSJJKS0v1+eefu233yiuvOG9fccUV9OGlD8BfCFwAAAAABLuIDl0k6fe//73z9k9/+tNmC8iuWLFCc+bMkXR8zZMrr7ySPlroA/A1IwKXkpISf5ULAAAAIEJF9JbRkjR27FjdfPPN+s9//qP169dr0KBB+slPfqJevXqpqKhIb775pmw2m6KiovS3v/1N0dHR9NFCH4AvGRW4FBUVuV2UFwAAAACMYnI4HI5AF2G0HTt2qF+/fpKke++9V48//rjX9ocOHdI111wji8Xi9nhcXJxeeOEF5eTk0Ecr+5Ck1NRUVVRUKCUlReXl5V7bhizL2EBXEDIeTvzQkH5OLc03JHDxtPU0AAAAgNAVbJ9DI/7yIknq3Lmz3n77bf373//W+PHj1bt3b3Xo0EHp6emaNm2aiouLWwwY6APwDwIXAAAAAKEiLGe6IDgEW8LoE8x0aTWjZrrcd14DgQsAAAAAt4LtcygzXQCEFAIXAAAAAKGC0AVAyCJwAQAAABDMCF0AhCRPgYvValV2drZ69eql0aNH67333iNwAQAAABAQEb9lNIDQUjxPOmZr0McbLfr+UK1GDzbru0VJ+u6/x+96NkdrtxTIZrfp008/04E90vj436q4yLWfmrpKTfht85kxAAAAAGAUQhcAfjGz2phFh9fa3nUJXHrGuwYnm3esk81ukyQ5HHbttH7VrI+aukqt2WTRBOUYUhMAAAAAuMPlRQBCirfARZJOSz5bJtPxU1tUVLQGpQ93Od4YuHTrnOCXegEAAABELma6AAgp3gKXL8tKdOG5V0qSdlq/0qD04XowJ995vGngMmaI2V8lAwAAAIhQhC4AQoq3wKV0R5FGDLxIt1z622bHTwxcYqJjm7UBAAAAACNxeRGAkOItcMlIz9LZac13KSJwAQAAABAIhC4AQhqBCwAAAIBgxeVFAELKsOLbnbdLqqt1sKpKV/furcyqYqnKtW3l4cPaWFam8+LiZE5LU+x6ywm9zfV9wQAAAAAiFjNdAISkkupqFVVVKat3b2UmJjY7Xnn4sCxlZUpoDFyiXE93DXa7v0oFAAAAEKEIXQCEHCMCF0tZmb/KBQAAABChCF0AhBSjApfa+np/lQwAAAAgQhG6AAgpRgUu5rQ0f5UMAAAAIEIRugAIKUYFLkmdOvmrZAAAAAARitAFQEghcAEAAAAQKtgyGj5ntVqVkZHh9lhubq5yc3P9XBHCCYELAAAAEFny8vKUl5fn9pjVavVzNd6ZHA6HI9BFIDylpqaqoqJCKSkpKi8vD3Q5vmEZG+gKIs/igcb1NXeucX0BAAAACLhg+xzK5UUAAAAAAAA+QOgCAAAAAADgA6zpAiCkPPwz4y4JmmlYTwAAAADQHDNdAAAAAAAAfICZLgDwX5WVlbJYLEpISJDZbFZsbKzL8YaGBlksFtXW1spsNispKSlAlQIAAAAIBcx0AQARuAAAAAAwHqELgIhH4AIAAADAFwhdAEQ0AhcAAAAAvkLoAiBiGRG4lJSU+KtcAAAAACGG0AVAxDIicCkqKvJXuQAAAABCDKELgIhlROCSlZXlr3IBAAAAhBhCFwARy4jAJTMz01/lAgAAAAgxhC4AIhaBCwAAAABfInQBADUPXBwOh7Kzs9WrVy9lZ2fLarUSuAAAAAA4KYQuACKeuxkuOTk5KigoUE1NjQoKCnTVVVcRuAAAAAA4KTGBLgAATsbM6rEG9vahx0uK1q1bJ5vNJkmy2WzasGEDgQsAAACAk0LoAiBirX2+QR9vtOj7Q7UaPdis7xYl6bv/Hju7zwh9tq9AdrtNJlOUzkgeKkdRpopP2CG6pq5SE37bfO0XAAAAAODyIgARq2ng0jPeNTh5MCdfg9NHqlNcFw3pd76euOPNZvevqavUmk0Wf5ULAAAAIMQw0wVAxPIUuEhS1b4KTRp1qzLSs3R2WvNLihoDl26dE/xRKgAAAIAQxEwXABHLU+DyZVmJSncUtSpwGTPE7I9SAQAAAIQgQhcAEcuIwCUmOtYfpQIAAAAIQYQuAPBfBC4AAAAAjMSaLgAi1rDi2523S6qrdbCqSlf37q3MqmKpyrVt5eHD2lhWpvPi4mROS1Ps+qYL6M71T8EAAAAAQgozXQBEvJLqahVVVSmrd29lJiY2O155+LAsZWVKaAxcojh1AgAAAGgZnxwARLT2Bi4Ndru/SgUAAAAQYghdAEQsIwIXS1mZv8oFAAAAEGIIXQBELCMCl9r6en+VCwAAACDEELoAiFhGBC7mtDR/lQsAAAAgxLB7EXzOarUqIyPD7bHc3Fzl5ub6uSLgOHeBiyQldeqknAEDPN4vNipKU9LTPR4vKSlRUVGRsrKylJnZfOvpyspKWSwWJSQkyGw2KzaWracBAACA1srLy1NeXp7bY1ar1c/VeEfoAp9LTk5WaWlpoMsA/ILABQAAAPAtb/95n5qaqoqKCj9X5BmhC4CI9fDP5hrSz8z//t3ewKWhoYEQBgAAAAgjrOkCAAYwInCxWCz+KhcAAACAHxC6AEA7GRW41NbW+qtkAAAAAH5A6AIA7WRU4GI2m/1VMgAAAAA/IHQBgHYyKnBJSkryV8kAAAAA/IDQBQDaicAFAAAAgDuELgBgMAIXAAAAABJbRgNAuxXP++F2TV2l1myyqFvnBA0cYtYXL7oGLsdsDfp4o0XfH6rV6MFmfbcoSd81OT5sun9qBgAAAOB7hC4AYJCmgcuYIWbFRB8PXPbWWTU7P0ebdqxTn57pmjTqFl06/Ab1jGeGCwAAABDOuLwIAAzgKXCRpNn5OVq7pUB1B2v0dfl6fbBhidvA5cuyEn+WDAAAAMDHmOkCIGLNrB5rSD8Fda97DFwkadOOdbLZbZIkh8OureUbmvXxZVmJSncUSWq+KC8AAACA0EToAgDtVLH0Wp0XFydzWppi11tcjjXY7Tqzo0nrD0p2SdEmk0b17Kxhxbc725RUV+tgVZWu7t1bEou6AAAAAOGC0AUA2imhMXCJcr1is8Ful6WsTLf0768eO3dqw969Gp6UpPxx45xtSqqrVVRVpazevZWZmOjv0gEAAAD4EKELALSTt8Cltr5eN5x5pn41ZEiz+xG4AAAAAOGNhXQBoJ28BS7mtDQlderU7D4ELgAAAED4I3QBAAMRuAAAAABoxOVFAGCg2KgoTUlP99omMzGRsAUAAACIAMx0AQAAAAAA8AFmugBAOz38s7mG9XXO4sUym82KjY11+XpDQ4MsFotqa2tlNpuVlJTU7L4lJSUqKipSVlaWMjMzDasJAAAAQNsw0wUAggiBCwAAABA+CF0AIIgQuAAAAADhg9AFAIIUgQsAAAAQ2ghdACAIEbgAAAAAoY/QBQCCjBGBS2VlpT9KBQAAAOAFoQsABBGjAheLxeKPcgEAAAB4wZbRABBEnv2VRd8fqtXowWZ9tyhJ351w/MuyEpXuKFJGepYcylRxkevxmrpKrdlkUbfOCVKOv6oGAAAA4A6hCwC008zqsYb1NevQTzV6sFk945vPcFlbWqCnXr1blfvKdc7po/RgTr56xSc7jzcNXMYMMRtWEwAAAIC24fIiAAgingKXL8tK9NSrd2vHni914PB+rd1SoNn5Oc7jJwYuMdGxzfoAAAAA4F/MdIHPWa1WZWRkuD2Wm5ur3NxcP1cEBC9PgUvpjiJV7iuX3WGTJNnsNm3eUSiJwAUAAACRJS8vT3l5eW6PWa1WP1fjncnhcDgCXQTCU2pqqioqKpSSkqLy8vJAl+MbFuMuKwEkSYsHuvyzpLpaRVVVyurdW38sLFRBeblsDoeiTSZNSE3VSxdeKEtZmRLi4mROS1NsVJMJjHPn+rl4AAAAILCC7XMolxcBQJBqGrhkJiYqf9w4TUhNVa+4OE1ITdUTI0d6DlwAAAAABByXFwFAEDoxcJGk5M6dtTw7W5JUefiw18ClwW4XFxkBAAAAgUXoAgBBKDMx0Rm2uJPUqZNyBgzweJxZLwAAAEDg8Vs5AAAAAACADzDTBQAiSElJiYqKipSVlaXMzMxmxysrK2WxWJSQkCCz2azYWC5SAgAAANqK0AUAgsjDPzNux6GZJ/ybwAUAAADwLy4vAoAIQOACAAAA+B+hCwCEOQIXAAAAIDAIXQAgjLU3cGloaPBXqQAAAEDYIXQBgDDlLXCxWq26+OKLdfrpp2vOnDkaNmyY28DFYrH4s2QAAAAgrLCQLgCEqTf+UqSM9Cw5lKniItdjv/jLjSr+erUcDrs2rN+g6y6bpmfvWu48fszWoI83WvT9oVpNmeLnwgEAAIAwQegCAEFkZvVYw/p6Of2vOjut+SVFNXWV2rxjrRwOuyTJZrdp845C5/GmgcvowWbD6gEAAAAiDZcXAUCY8hS4rNlkUVrSAEVFRUuSoqKiNSh9uKTmgUvP+CS/1gwAAACEE2a6AECYGlZ8u8u/Kw8f1sayMp0XF6efX3C2pn1UpcLKSg1PSlL+eYnqWThNlrIy9aqv10/S0pS09dP/3nOu/4sHAAAAwgChCwBEgMrDh2UpK1NCXJzMaWmKjYrS8uxs5/EGu12WsjLV1tfLnJampE6dAlgtAAAAEB4IXQAgAiR16qScAQM8Ho+NitKU9HT/FQQAAABEANZ0AQB4VVJSonnz5qmkpMTt8crKSuXn52vx4sVqaGhodryhoUGLFy9Wfn6+jysFAAAAggszXQAgTD38M2PWYkkumqesrCxlZjZfmLeyslIWi0UJCQkym82KjY11Od7Q0CCLxaLa2lqZzeyEBAAAgMjCTBcAgFdGBS5JSeyEBAAAgMhC6AIA8IrABQAAAGgbLi8CAHhVPM/13zV1lVqzyaJunRM0cIhZ7z9To9n5Odq8Y50GpY/QH38yX1t2Fuv7Q7UaPdis7xYl6bv/3nfYdL+XDwAAAAQMM10AAK3WNHAZM8SsmOhYzc7P0WdbCrT/YI0+21Kge/KmOAOXnvHMcAEAAEDkYqYLAISpmdVjDemnWB9Kch+4SNLmHetkt9skSXa7TWWVXxO4AAAAACJ0AQC0YFjx7ao8fFgby8p0XlyczGlpil1vcR4f1bOLCg7VyuZwKErSqF7xmrB1ZrN+Sqqrpelv+LFyAAAAILAIXQAALUrq1Ek5Awa4PZY/bpxyPvhAhZWVGp6UpPxx49y2y0xM9GWJAAAAQNAhdAEAtEty585anp3d5vuzExIAAADCFaELAMCrh38217C+TrzoiMAFAAAA4YzdiwAAAXFi4FJTU6Ps7Gz16tVL2dnZKi8vJ3ABAABASGOmC3zOarUqIyPD7bHc3Fzl5ub6uSIAgVI87/jfTXdCGjjErC9ejNVdz+Zo7ZYC2ew2Faws0CU/mqLrL5qh0YPN+m5Rkr5r0s+w6QEpHwAAAEEgLy9PeXl5bo9ZrVY/V+MdoQt8Ljk5WaWlpYEuA0CQ8Lb1tO2/W0/b2HoaAAAAHnj7z/vU1FRVVFT4uSLPCF0AAF7NrB5rWF+VH6ez9TQAAAAiBmu6AAD8xlJWpoTGwCXK9UfQ/Asu0NCePdU1JkYX9u2rBRdd1Oz+JdXVKqqq8le5AAAAQLsw0wUA4Dc5AwZ4PJbatauKr77a6/0zExOVmZjo9hg7IQEAACDYELoAAPzGqO2nW9p6uqamRjk5OVq3bp1GjBih+fPnq7i4mMAFAAAAfsXlRQCAkOZuhktOTo4KCgpUU1OjgoICTZkyhcAFAAAAfsdMFwBAyPG29bQkffrROtls/90JyWbTls1fK6W6+dbTEttPAwAAwHcIXQAAfmPYTkjFA1V5+DA7IQEAACCoEboAAEJSUqdOHhfmzR83TjkffKDCykoNT0pS/rhxbtt5WpQXAAAAMAKhCwAg7CR37qzl2dltvn/jOjEmk0mvvPKKCgsLNWLECOXn5ys5OZmdkAAAANAqhC4AgJBj1C5IkvedkJ5//nmtWrVKNptNBQUFysnJ0ZIlSwhcAAAA0CrsXgQA7VDfYNesl3eqvsEe6FLQRsXzfvhT8GSl/vZ7i/auS9Apu8z67ONClwV5P/2oUM/+yqLP36p1Lszb9P7hqr6+XrNmzVJ9fX2gSwF8hvc5IgHvc8D/TA6HwxHoIhCeUlJStGvXLvXt21cVFRWBLsc3LAYtCoqQVXfomLpf86n2vzZK8Z2ZPBiSFg+UJFUePixLWZkSGhfmjYpS9vLlKigvl83hULTJpKE9e2rG4MEyp6UpqVOn5n3NNW4GTjCpq6tT9+7dtX//fsXHxwe6HMAneJ8jEvA+RyQIts+hzHQBAEA/LMw7JT1dsVHHfzzmjxunCamp6hUXpwmpqbJkZytnwAD3gYukefPmqaSkxO2xTZs26ZxzzlF8fLwuu+wyWa1Wl+MNDQ1avHix8vPzDX1cAAAACBz+WxYAENFaWh/mRzOkH/33dktXEJ2+pEQOZaq4yPXrNXWV+uXTN2r77s1yOOwqKFilqy7O0bN3LZckHbM16OONFn1/qFajB5vb9kAAAAAQdJjpAgCAQc5Oy2z2tZq6Sq3ZZNGuvTvkcBxf+8dut2nzjkJJzQOXnvEtL8xrtVqVnZ2tXr16KTs7u9msGQAAAAQHZroAACLazGoD12YqHuj2yxPipLVJPVRQfsC5Psyonp01rPh2SdJISYqTtPXT/97jh9k3JSUlKioqUlZWljIzj4c6OTk5KigocO6qNGHCBD388MMym82KjY017vEAAACgXQhd4JXFYtELL7ygkpISVVVV6ZRTTtGPfvQj5ebmasyYMYEuDwCCirdLlc65wqptD+doV2mh+mYM1zkz8/Vwr2S3bc3/vY7py7ISle4oUkZ6lstlS59+tM5lV6XtW3folF1mffGia+ByzNagkXcQwgAAAAQKoQvcstlsuuOOOzR//nyXr5eVlamsrEwLFy7UAw88oNmzZweoQgAILV17JeuWvy5vVdvGGTDDJKmLpKpiqeqH46N6dlHBoVrnrJmxvXto5Po73faVnz9KZrNZSUnNL1sqKCjQ3XffrfLyco0aNUr5+flKTv4hCKqsrJTFYlFcXFxrHyYAAACaIHSBW7NmzXIGLvHx8br55pt12mmnqbS0VAsXLlR9fb0eeughpaamatq0aQGuFgCCg3GXKrm/TKlR/rhxyvngAxVWVmp4UpLyx43z2Dal2qzvFiXpuxO+/mVZiR74593asedL2R02FawscFnct3Etmm6dE3TumS3PbLRarcrJydG6des0YsSIZgEOAABAJCJ0QTPbt2/Xn/70J0lSWlqaPvjgA6WnpzuPz5gxQ+PHj9f333+v3/72t7r22mvVvXv3AFXbNnl5ecrNzQ10GS7ylu5S7qS+gS7DBTWFtmB8rqipdSbFn6OR13g/R7V2V6WZ/7jd7deHSbqrZpvsjv9epmS36att7ztn2UjH16KRTarbuMjlvg0NDbJYLKqtrXXOojlxnZmrrrpKt956q8taNL4QlOdzamqVYKwpWAXjc0VNrROMNQWrYHyuqKl1grGmYGJyOByOQBeB4HLnnXcqLy9PkrRkyRL9+Mc/btbmmWee0a9//WtJ0pNPPqnf/OY3zdqkpKRo165d6tu3ryoqKnxa88nKyMhQaWlp+zuyGLcAZ8YvilT6QpZh/RmBmlpWd+iYul/zqfa/NkrxnYMrxw6250qiptYytKbFnmfNZC9froLycudlShNSU7U8O7tZu7qjR9U9P1+r/7pfHTt0crvb0sX39NL+gzXO+3SK66L5v/3Q7Y5Ow6Z7LvdkZ8wYdj43EDW1TrDVVFdXp+7du2v//v2Kj48PdDkugu25kqiptYKtJt7nJ4eaWifYagq2z6HB9QkBAedwOLRo0SJJUo8ePZTt5pdvSbrhhhucocuSJUvchi4AgCAwZYvHQ/lj+yrn6QMq3Pq9hp/VTfl395US3LQ/dEzKl85b/yvFd+jgZrel5uvMjEvqqZuq5rqsReMcN3+UEhIS3O62dOutt6qgoEB2u10FBQXKycnR8uWua+E03dHJGy55AgAAgUboAhdff/21Mw2cOHGiYmLcv0WSkpI0fPhwFRYW6pNPPtHBgwfVpUsXf5YKAGin5IQOWv7Q4Fa3/9+fPKOOXd3/z+jJ7M7kvOTJYml2rHD1atntdknHF3UvfP996XbXS6Qy//tHxcXN7t+4+G9CQoKef/55rVq1ynnJU05OjpYsWdLs0qjWMCrAIQgCACCyELrARVlZmfP2+PHjvbYdP368CgsLdezYMW3btk1Dhw71dXkAgAC6t+YyxR/x/KvD//6PJGVIOig5rpGq3bd7+Gcfeuyj58Yy1a4rkMNmkyk6WgmZ471uxa1XE1xCmSRJOf+9/dPVq1221i58/33F3nmnpjQ2/vSHmTqae3yMprNomq5F03TNmpUrV8psNuuzzz5rNlOnoaHBc60n9ONpJk9rEQQBABD8CF3gwmq1Om+39AtX0/8dJHQBALSWt12epuceVc7R+B8uecqtVbKX9q90q/d4CdWI4s4q+LxeNrsUHSUNH9zZ8+VW/w1uPM2iWff++84Ax263a+fmzYq9s/k23bGSqnbtU8GTlc71bpr6+INPXYKgTz8qVHGTlZCb7hr1m79NaXb/powKcIIxCDKyr2CsCQAQOaICXQCCS9PQJSEhwWvbnj17Om9XVla2ebzs7Gz16tVL2dnZLuMHoh+j+wIAnJzGS56qXxml5Q8NVnJChzb3lX93f004L0G94mM04bwE5d/d33PjKVu8/hkxuLOi//tbk0uA4+ZP7/h9mpAxVcNSxzb7MyYjyqWfUWfbXY5PyJiqWdf+U7+Z9NTxIMjLn6ZBkMulWG7+HNknFc+TCp6s1KycfD31y8Va+3yDiudJn360zqWfD1ev0aycfBU8WanieWr2x5vGAKempsYZ4LSVUX0FY03B+ntLOP9eFow1GdkXNfm/L2ryf1+h+jmN3Yvg4ve//72eeOIJSdLnn3+uc88912PbRYsW6corr5TkfgejDh06qKGhQVFRUTrllFPc9rF3717V19c7/x0XF6devXq5tDGZTC3WXV1d3ayfxMREj+2tVqvH/5k6qb6OuFkhso2s+44quUfbP1z4AjW1zOGQdtUcVd+eHdSKt6pfBdtzJVFTawVbTbzPJbvdoZoDx9RwzKHYGJN6do1RVJT7J8NbTSfTT0uq6xpU3/DDr3FxsSYlxse6beutppPppyW7ao6q6W+WUSapT0/34+7eZ1fXnp5nidRV71LTzkymKHVL7OO2bbdD+zzXdPCgmv6yGyWpj5t16BwOh3YdOqTE7n0V5eGNXrV/lxwn1NS7u/ua1KFBR48eVYcOHZpdhtba3zWOHDkiu92u77//3pjfW1pwMn0Z9rtUBNdkZF2t7cfhcDh3dfH0O7a/a2oUaq8fNbWuprbW5S6maM1nR0nas2eP7Ha7YmNjdfToUa/j+AOhC1z8/Oc/1z/+8Q9JxxfVPeusszy2LSgo0MSJEyVJDz30kGbOnOlyPDo62rkYIgAAAAAA/hIVFeWcyRlIrOkCFx06/PC/UQcOHPDadv/+/c7bcXFxzY537NhRR44cUXR0tHr37t3mmloz0wUAAAAAEB7aMzekqqpKNptNHTt2NLCitiN0gYvOnTs7b9fW1npt2/S4u+2iDx48aFxhAAAAAACEGBbShYum19a1FLrs27fPebvporoAAAAAAIDQBSdouobL7t27vbbds2eP83b//l52hAAAAAAAIAIRusBFRkaG8/b777/vte17770n6fgCRYQuAAAAAAC4YvciuHA4HDr11FNVUVGh+Ph4VVdXN9vmUDq+LVjjNtCjR4/Wxx9/7O9SAQAAAAAIasx0gQuTyaQpU6ZIkurq6rRs2TK37RYuXOi8fcUVV/ijNAAAAAAAQgozXdDM9u3b1b9/f9ntdqWlpemjjz5SWlqa83hJSYnGjx+vuro69ejRQzt37lR8fHwAKwYAAAAAIPgQusCtmTNn6pFHHpEk9ejRQ7fccotSU1O1efNmLVy4UPX19ZKkF198UTk5OQGsFAAAAACA4EToArdsNpumT5+uf/7zn26Pm0wmPfLII7r//vv9XBkAAAAAAKGB0AVeLVu2TC+88IKKi4u1d+9eJScna8yYMZoxY4ZGjRoV6PIAAAAAAAhahC4AAAAAAAA+wO5FAAAAAAAAPkDoAgAAAAAA4AOELgAAAAAAAD5A6AIAAAAAAOADhC5hYP78+TKZTLrvvvva3dfMmTNlMpla9efCCy9sf/EAAAAAAIQpQpcwsGDBAsP62rZtm2F9AQAAAAAQyWICXQDaZ+nSpVq9erVh/TWGLoMHD9btt9/utW1KSoph4wIAAAAAEG4IXUJUTU2N/vGPf+iRRx4xrE+Hw6GtW7dKksaNG6c777zTsL4BAAAAAIg0hC4h5rrrrlNhYaG+/fZbw/veu3ev9u/fL0nq37+/4f0DAAAAABBJCF1CzIoVK5zBiNGarudy1lln+WQMAAAAAAAiBaFLiHnppZfU0NDg/HdlZaVyc3MN6ZvQBQAAAAAA4xC6hJgpU6a4/HvHjh2G9d24nktMTIzi4+N133336d1339XXX38tSerXr58uu+wyzZgxg0V0AQAAAABoAaELnBpnukRFRal///7NLmPasGGDNmzYoGeeeUbPP/+8cnJyAlAlAAAAAAChgdAFTo2hy9GjR3X06FFlZWXp0ksvVbdu3fTll1/q/fff186dO3XkyBHddttt6ty5s6699lqP/XXp0kVHjhxRdHS0evfu3ea6TCZTm+8LAAAAAAgtDoejzfetqqqSzWZTx44ddfDgQQOrahtCFzg1hi4mk0l5eXn6xS9+4RJ4HD58WPfdd5+effZZSdIvfvELXXbZZYqPj3fb35EjR2S322W327Vr1y7fPwAAAAAAAHT882gwIHSBJOnYsWP63e9+J0nKyMjQ5MmTm7Xp1KmT/vrXv2rjxo16//33VVtbq3//+98eF/KNjo6W3W5XVFSUTjnllDbX5ouZLlarVcnJyYb32x7U1DrBVpPD4dCuXbvUt2/foJuVFWzPlURNrRVsNfE+PznU1DrBVhPv85NDTa0TbDXxPj851NQ6vqipPTNd9uzZI7vdrujoaAMrajtCF0n19fXq0KFD0J14/CkmJkb33Xdfi+1MJpMeeughXXDBBZKkgoICj6FL7969tWvXLp1yyimqqKgwtN72ysjIUGlpaaDLcEFNrRNsNdXV1al79+7asmWLx1lfgRJsz5VETa0VbDXxPj851NQ6wVYT7/OTQ02tE2w18T4/OdTUOsFWU0pKinbt2tWuJS6MFBXoAnyttLRUjz76qA4cOOCxzeuvv66uXbtq5MiRmj17tr788ks/Vhh6hg4d6rxt5O5JAAAAAACEk7AMXWw2m55++mkNGDBAQ4YM0QMPPKCjR496vc/hw4dVVFSkhx56SIMGDdLNN98sq9Xqp4pDS7du3ZSYmCjp+PMGAAAAAACaC7vLi6qrqzVp0iQVFhZKOn4tWEuXDXXt2lXR0dGy2WzOr73yyiv66KOPtHz5cmVkZPi05mBgtVqdAUp6errXtkeOHNHevXslKWimbAEAAAAAEGzCaqbL0aNHNXHiRK1bt8658M7YsWP1zDPPqHv37h7vN2XKFNXW1mrZsmW64447FBMTI4fDoe+++05TpkzR/v37/fUQAuaZZ55Rv3791K9fP5WUlHhtu2XLFufzm5mZ6Y/yAAAAAAAIOWEVujzxxBNav369TCaTTj31VK1Zs0arV6/WnXfe2eLKxV27dlV2drby8vK0fv16jRw5UpL0zTff6M9//rM/yg+o6667znn7L3/5i9e2jzzyiPP2j3/8Y5/VBAAAAABAKAub0OXYsWN69tlnJUnx8fEqLCzU+eef36a+MjIytGTJEiUmJsrhcOj55593ufQoHJ1zzjk655xzJEkvv/yynnzySdntdpc2R48e1axZs/Tmm29KkkaMGKFLLrnE77UawdOOS4FETa0TjDUFq2B8rqipdYKxpmAVjM8VNbVOMNYUrILxuaKm1gnGmoJVMD5X1NQ6wVhTMDE52rMBdhApLCzUyJEjZTKZ9Oijj7Zq++OW/P3vf9f06dNlMpn06aefasSIEQZUaqwdO3aoX79+kqR7771Xjz/+uMe2s2bN0uzZsyVJt956q/Lz812Ob9q0Seeff74OHjwo6fguRZdccol69+6trVu36sMPP9TWrVsl/RBs9e/f3+N4jVt19e3bN+i2jAaM0rj14v79+4Nu60XAKLzPEQl4nyMS8D5HJAi2z6Fhs5Duhg0bnLevvPJKQ/q84IILnLc3btwYlKGLkQYPHqyFCxcqJydHe/fu1YYNG1ye10Znnnmm3nzzTa+BCwAAAAAAkS5sQpfG3XSklnffaa3TTz9d0dHRstvtqqmpMaTPYDdp0iR98803evbZZ7Vq1Sp9++232r17txISEjR06FBNnTpVOTk56tChQ6BLBQAAAAAgqIVN6NKxY0dJUqdOnRQXF2dIn7GxsYqJidHRo0db3HY6UNLT09XaK8RmzZqlWbNmtdguPj5e//M//6P/+Z//aWd1AAAAAABErrBZSDc1NVWSdPjwYcNmpVRWVqq+vl6S1KdPH0P6BAAAAAAAkSFsQpeBAwc6by9btsyQPpcuXeq8fdZZZxnSJwAAAAAAiAxhE7pkZGQoIyNDDodDf/7zn3X06NF29Xf06FE98cQTko7Pcgn3RXQBAAAAAICxwiZ0kaTbb79dklRaWqrbb79ddru9zX3NmDFDX331lUwmk2699VajSgQAAAAAABEirEKX3NxcDR8+XA6HQ//6179kNpv1zTffnFQflZWVuuaaa/T3v/9dJpNJKSkpuv/++31UcXhrXHw4WBchBowQFxenBx980LAFvIFgxPsckYD3OSIB73NEgmD7HGpytHbrmxCxY8cOjR8/Xjt37pTJZFJ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\n",
       "text/plain": [
        "<Figure size 1200x1200 with 2 Axes>"
       ]
@@ -304,7 +305,7 @@
     {
      "data": {
       "text/plain": [
-       "<pocket_coffea.utils.plot_utils.PlotManager at 0x7f1c23e16c70>"
+       "<pocket_coffea.utils.plot_utils.PlotManager at 0x7f7f166f83d0>"
       ]
      },
      "execution_count": 13,
@@ -330,7 +331,7 @@
     {
      "data": {
       "text/plain": [
-       "<pocket_coffea.utils.plot_utils.SystManager at 0x7f1c23dd8580>"
+       "<pocket_coffea.utils.plot_utils.SystManager at 0x7f7f166ecd00>"
       ]
      },
      "execution_count": 14,
@@ -410,28 +411,28 @@
     {
      "data": {
       "text/plain": [
-       "{'JER': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23dd8370>,\n",
-       " 'JES_Total': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23e168b0>,\n",
-       " 'pileup': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23dd8fa0>,\n",
-       " 'sf_btag_cferr1': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23dd8ee0>,\n",
-       " 'sf_btag_cferr2': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23de4f10>,\n",
-       " 'sf_btag_hf': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23de6fa0>,\n",
-       " 'sf_btag_hfstats1': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23de47c0>,\n",
-       " 'sf_btag_hfstats2': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23deab20>,\n",
-       " 'sf_btag_lf': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23deaaf0>,\n",
-       " 'sf_btag_lfstats1': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23decc40>,\n",
-       " 'sf_btag_lfstats2': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23decd00>,\n",
-       " 'sf_ele_id': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23defe20>,\n",
-       " 'sf_ele_reco': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23defd30>,\n",
-       " 'sf_ele_trigger_era': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23df0e80>,\n",
-       " 'sf_ele_trigger_ht': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23df0e50>,\n",
-       " 'sf_ele_trigger_pileup': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23df2d60>,\n",
-       " 'sf_ele_trigger_stat': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23df2fa0>,\n",
-       " 'sf_jet_puId': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23df6e50>,\n",
-       " 'sf_mu_id': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23df8fa0>,\n",
-       " 'sf_mu_iso': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23df6f70>,\n",
-       " 'sf_mu_trigger': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23dfaa90>,\n",
-       " 'mcstat': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23dfab50>}"
+       "{'JER': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f166ec460>,\n",
+       " 'JES_Total': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f166ecfd0>,\n",
+       " 'pileup': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f166c8550>,\n",
+       " 'sf_btag_cferr1': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f1691f130>,\n",
+       " 'sf_btag_cferr2': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f167383a0>,\n",
+       " 'sf_btag_hf': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f16924310>,\n",
+       " 'sf_btag_hfstats1': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f166ecf40>,\n",
+       " 'sf_btag_hfstats2': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f166b6ee0>,\n",
+       " 'sf_btag_lf': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f166b6eb0>,\n",
+       " 'sf_btag_lfstats1': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f1666cdc0>,\n",
+       " 'sf_btag_lfstats2': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f1666cfd0>,\n",
+       " 'sf_ele_id': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f1666f790>,\n",
+       " 'sf_ele_reco': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f16671fd0>,\n",
+       " 'sf_ele_trigger_era': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f1666ffd0>,\n",
+       " 'sf_ele_trigger_ht': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f16673af0>,\n",
+       " 'sf_ele_trigger_pileup': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f16673160>,\n",
+       " 'sf_ele_trigger_stat': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f16675be0>,\n",
+       " 'sf_jet_puId': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f16675cd0>,\n",
+       " 'sf_mu_id': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f16678df0>,\n",
+       " 'sf_mu_iso': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f16678d00>,\n",
+       " 'sf_mu_trigger': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f1667ae50>,\n",
+       " 'mcstat': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f1667a4c0>}"
       ]
      },
      "execution_count": 16,
@@ -454,7 +455,7 @@
     {
      "data": {
       "text/plain": [
-       "<pocket_coffea.utils.plot_utils.SystUnc at 0x7f1c23dd8370>"
+       "<pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f166ec460>"
       ]
      },
      "execution_count": 17,
@@ -526,7 +527,8 @@
        " 'up',\n",
        " 'xbinwidth',\n",
        " 'xcenters',\n",
-       " 'xedges']"
+       " 'xedges',\n",
+       " 'xlabel']"
       ]
      },
      "execution_count": 18,
@@ -667,7 +669,7 @@
     {
      "data": {
       "text/plain": [
-       "<pocket_coffea.utils.plot_utils.SystUnc at 0x7f1cfaef1190>"
+       "<pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f166eca90>"
       ]
      },
      "execution_count": 23,
@@ -866,7 +868,8 @@
        " 'up',\n",
        " 'xbinwidth',\n",
        " 'xcenters',\n",
-       " 'xedges']"
+       " 'xedges',\n",
+       " 'xlabel']"
       ]
      },
      "execution_count": 28,
@@ -889,7 +892,8 @@
     {
      "data": {
       "text/plain": [
-       "(<Figure size 1200x900 with 1 Axes>, <AxesSubplot: >)"
+       "(<Figure size 1200x900 with 1 Axes>,\n",
+       " <AxesSubplot: xlabel='$p_{T}^{e}$ [GeV]', ylabel='Counts'>)"
       ]
      },
      "execution_count": 29,
@@ -898,7 +902,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 1200x900 with 1 Axes>"
       ]
@@ -969,7 +973,8 @@
        " 'up',\n",
        " 'xbinwidth',\n",
        " 'xcenters',\n",
-       " 'xedges']"
+       " 'xedges',\n",
+       " 'xlabel']"
       ]
      },
      "execution_count": 30,
@@ -1035,7 +1040,8 @@
     {
      "data": {
       "text/plain": [
-       "(<bound method Artist.get_figure of <AxesSubplot: >>, <AxesSubplot: >)"
+       "(<bound method Artist.get_figure of <AxesSubplot: xlabel='$p_{T}^{e}$ [GeV]', ylabel='Counts'>>,\n",
+       " <AxesSubplot: xlabel='$p_{T}^{e}$ [GeV]', ylabel='Counts'>)"
       ]
      },
      "execution_count": 32,
@@ -1044,7 +1050,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 1200x900 with 1 Axes>"
       ]
@@ -1097,9 +1103,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 34,
    "id": "d00bfe3a-6a60-4725-a8c6-8345a6bd2a12",
    "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'$p_{T}^{e}$ [GeV]'"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "h_dict[\"ttHTobb\"].axes[-1].label"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "baf0d172-045e-45f4-9756-8c59b1c65536",
+   "metadata": {},
    "outputs": [],
    "source": []
   }
diff --git a/pocket_coffea/parameters/plotting.py b/pocket_coffea/parameters/plotting.py
new file mode 100644
index 00000000..09603710
--- /dev/null
+++ b/pocket_coffea/parameters/plotting.py
@@ -0,0 +1,88 @@
+hatch_density = 4
+
+style_cfg = {
+    "fontsize" : 22,
+    "fontsize_legend_ratio" : 12,
+    "opts_figure" : {
+        "datamc" : {
+            'figsize' : (12,9),
+        },
+        "datamc_ratio" : {
+            'figsize' : (12,12),
+            'gridspec_kw' : {"height_ratios": (3, 1)},
+            'sharex' : True,
+        },
+        "partial" : {
+            'figsize' : (12,15),
+            'gridspec_kw' : {"height_ratios": (3, 1)},
+            'sharex' : True,
+        },
+    },
+    "opts_data" : {
+        'linestyle': 'solid',
+        'linewidth': 0,
+        'marker': '.',
+        'markersize': 5.0,
+        'color': 'black',
+        'elinewidth': 1,
+        'label': 'Data',
+    },
+    "opts_unc" : {
+        "total" : {
+            "step": "post",
+            "color": (0, 0, 0, 0.4),
+            "facecolor": (0, 0, 0, 0.0),
+            "linewidth": 0,
+            "hatch": '/' * hatch_density,
+            "zorder": 2,
+        },
+        'Up': {
+            'linestyle': 'dashed',
+            'linewidth': 1,
+            'marker': '.',
+            'markersize': 1.0,
+            #'color': 'red',
+            'elinewidth': 1,
+        },
+        'Down': {
+            'linestyle': 'dotted',
+            'linewidth': 1,
+            'marker': '.',
+            'markersize': 1.0,
+            #'color': 'red',
+            'elinewidth': 1,
+        },
+    },
+    "opts_syst" : {
+        'nominal': {
+            'linestyle': 'solid',
+            'linewidth': 1,
+            'color': 'black',
+        },
+        'up': {
+            'linestyle': 'dashed',
+            'linewidth': 1,
+            'color': 'red',
+        },
+        'down': {
+            'linestyle': 'dotted',
+            'linewidth': 1,
+            'color': 'blue',
+        },
+    },
+    "labels": {
+        "ttHTobb": "$t\\bar{t}H\\rightarrow b\\bar{b}$",
+        "TTToSemiLeptonic": "$t\\bar{t}$ semilep.",
+        "TTTo2L2Nu" : "$t\\bar{t}$ dilepton",
+        "SingleTop" : "Single t",
+        "WJetsToLNu_HT" : "W+jets",
+    },
+    "colors" : {
+        'ttHTobb': 'pink',
+        'TTTo2L2Nu': (0.51, 0.79, 1.0),  # blue
+        'TTToSemiLeptonic': (1.0, 0.71, 0.24),  # orange
+        'SingleTop' : (1.0, 0.4, 0.4), #red
+        'ST' : (1.0, 0.4, 0.4), #red
+        'WJetsToLNu_HT' : '#cc99ff', #violet
+    }
+}
diff --git a/pocket_coffea/utils/plot_utils.py b/pocket_coffea/utils/plot_utils.py
index 36eab447..ebdbba93 100644
--- a/pocket_coffea/utils/plot_utils.py
+++ b/pocket_coffea/utils/plot_utils.py
@@ -15,22 +15,32 @@ import mplhep as hep
 from ..parameters.lumi import lumi, femtobarn
 from ..parameters.plotting import style_cfg
 
+
 class Style:
     '''This class manages all the style options for Data/MC plots.'''
     def __init__(self, style_cfg=style_cfg) -> None:
         for key, item in style_cfg.items():
             setattr(self, key, item)
+        if "labels" in style_cfg:
+            self.has_labels = True
+
 
 class PlotManager:
     '''This class manages multiple DataMC objects and their plotting.'''
-    def __init__(self, hist_cfg, data_key="DATA") -> None:
+    def __init__(self, hist_cfg, plot_dir, only_cat=[], data_key="DATA", log=False, save=True) -> None:
         self.datamc_objects = {}
+        self.plot_dir = plot_dir
+        self.only_cat = only_cat
+        self.data_key = data_key
+        self.log = log
+        self.save = save
         for name, h_dict in hist_cfg.items():
-            self.datamc_objects[name] = DataMC(h_dict, name, data_key=data_key)
+            self.datamc_objects[name] = DataMC(h_dict, name, plot_dir, only_cat, data_key=self.data_key, log=self.log)
 
-    def plot_datamc_all(self):
+    def plot_datamc_all(self, ratio=True, syst=True, spliteras=False):
+        '''Plots all the histograms containted in the dictionary, for all years and categories.'''
         for name, datamc in self.datamc_objects.items():
-            datamc.plot_datamc_all(self)
+            datamc.plot_datamc_all(ratio, syst, spliteras, save=self.save)
 
 
 class DataMC:
@@ -40,11 +50,14 @@ class DataMC:
     - name: name that identifies the DataMC object.
     - style_cfg: dictionary with style and plotting options.
     - data_key: prefix for data samples (e.g. default in PocketCoffea: "DATA_SingleEle")'''
-    def __init__(self, h_dict, name, style_cfg=style_cfg, data_key="DATA") -> None:
+    def __init__(self, h_dict, name, plot_dir, only_cat=[], style_cfg=style_cfg, data_key="DATA", log=False) -> None:
         self.h_dict = h_dict
         self.name = name
+        self.plot_dir = plot_dir
+        self.only_cat = only_cat
         self.style = Style(style_cfg)
         self.data_key = data_key
+        self.log = log
         assert type(h_dict) == dict, "The DataMC object receives a dictionary of hist.Hist objects as argument."
         self.define_samples()
         assert self.dense_dim == 1, f"Histograms with dense dimension {self.dense_dim} cannot be plotted. Only 1D histograms are supported."
@@ -143,6 +156,7 @@ class DataMC:
         for ax in self.categorical_axes_mc:
             setattr(self, {'year': 'years', 'cat': 'categories', 'variation': 'variations'}[ax.name], self.get_axis_items(ax.name))
         self.xaxis = self.dense_axes[0]
+        self.xlabel = self.xaxis.label
         self.xcenters = self.xaxis.centers
         self.xedges = self.xaxis.edges
         self.xbinwidth = np.ediff1d(self.xedges)
@@ -222,21 +236,41 @@ class DataMC:
         self.ax.tick_params(axis='x', labelsize=self.style.fontsize)
         self.ax.tick_params(axis='y', labelsize=self.style.fontsize)
         self.ax.set_xlim(self.xedges[0], self.xedges[-1])
-        if self.is_mc_only:
-            maximum = max(self.stack_sum_mc_nominal.values())
+        if self.log:
+            self.ax.set_yscale("log")
+            if self.is_mc_only:
+                exp = math.floor(math.log(max(self.stack_sum_mc_nominal.values()), 10))
+            else:
+                exp = math.floor(math.log(max(self.stack_sum_data.values()), 10))
+            self.ax.set_ylim((0.01, 10 ** (exp + 3)))
         else:
-            maximum = max(self.stack_sum_data.values())
-        if not np.isnan(maximum):
-            self.ax.set_ylim((0, 2.0 * maximum))
+            if self.is_mc_only:
+                maximum = max(self.stack_sum_mc_nominal.values())
+            else:
+                maximum = max(self.stack_sum_data.values())
+            if not np.isnan(maximum):
+                self.ax.set_ylim((0, 2.0 * maximum))
         if ratio:
-            xlabel = self.ax.get_xlabel()
             self.ax.set_xlabel("")
-            self.rax.set_xlabel(xlabel, fontsize=self.style.fontsize)
+            self.rax.set_xlabel(self.xlabel, fontsize=self.style.fontsize)
             self.rax.set_ylabel("Data / MC", fontsize=self.style.fontsize)
             self.rax.yaxis.set_label_coords(-0.075, 1)
             self.rax.tick_params(axis='x', labelsize=self.style.fontsize)
             self.rax.tick_params(axis='y', labelsize=self.style.fontsize)
             self.rax.set_ylim((0.5, 1.5))
+        if self.style.has_labels:
+            handles, labels = self.ax.get_legend_handles_labels()
+            labels_new = []
+            handles_new = []
+            for i, l in enumerate(labels):
+                if l in self.style.labels:
+                    labels_new.append(f"{self.style.labels[l]}")
+                else:
+                    labels_new.append(l)
+                handles_new.append(handles[i])
+            labels = labels_new
+            handles = handles_new
+            self.ax.legend(handles, labels, fontsize=self.style.fontsize, ncols=2, loc="upper right")
 
     def plot_mc(self):
         '''Plots the MC histograms as a stacked plot.'''
@@ -304,18 +338,31 @@ class DataMC:
                 self.plot_systematic_uncertainty(ratio)
 
         self.format_figure(ratio)
-        plt.show(self.fig)
-        plt.close(self.fig)
 
-    def plot_datamc_all(self, ratio=True, syst=True, spliteras=False):
+    def plot_datamc_all(self, ratio=True, syst=True, spliteras=False, save=True):
         '''Plots the data and MC histograms for each year and category contained in the histograms.
         If ratio is True, also the Data/MC ratio plot is plotted.
         If syst is True, also the total systematic uncertainty is plotted.'''
         for year in self.years:
             for cat in self.categories:
+                if not any([c in cat for c in self.only_cat]):
+                    continue
                 self.define_figure(year, ratio)
                 self.build_stacks(year, cat, spliteras)
+                self.get_systematic_uncertainty()
                 self.plot_datamc(year, ratio, syst)
+                if save:
+                    plot_dir = os.path.join(self.plot_dir, cat)
+                    if self.log:
+                        plot_dir = os.path.join(plot_dir, "log")
+                    if not os.path.exists(plot_dir):
+                        os.makedirs(plot_dir)
+                    filepath = os.path.join(plot_dir, f"{self.name}_{year}_{cat}.png")
+                    print("Saving", filepath)
+                    plt.savefig(filepath, dpi=150, format="png")
+                else:
+                    plt.show(self.fig)
+                plt.close(self.fig)
 
 class SystUnc:
     '''This class stores the information of a single systematic uncertainty of a 1D MC histogram.
@@ -341,6 +388,7 @@ class SystUnc:
             # Full nominal MC including all MC samples
             self.h_mc_nominal = self.datamc.stack_sum_mc_nominal
             self.nominal = self.h_mc_nominal.values()
+            self.xlabel = self.datamc.xlabel
             self.xcenters = self.datamc.xcenters
             self.xedges = self.datamc.xedges
             self.xbinwidth = self.datamc.xbinwidth
@@ -392,6 +440,7 @@ class SystUnc:
         are summed in quadrature to define a new SystUnc object.'''
         index_non_empty = [i for i, s in enumerate(self.syst_list) if not s._is_empty][0]
         self.nominal = self.syst_list[index_non_empty].nominal
+        self.xlabel = self.syst_list[index_non_empty].xlabel
         self.xcenters = self.syst_list[index_non_empty].xcenters
         self.xedges = self.syst_list[index_non_empty].xedges
         self.xbinwidth = self.syst_list[index_non_empty].xbinwidth
@@ -450,12 +499,14 @@ class SystUnc:
         else:
             self.ax = ax
             self.fig = self.ax.get_figure
-        hep.cms.text("Preliminary", fontsize=self.style.fontsize, loc=0, ax=self.ax)
+        hep.cms.text("Simulation Preliminary", fontsize=self.style.fontsize, loc=0, ax=self.ax)
         #hep.cms.lumitext(text=f'{self.lumi[year]}' + r' fb$^{-1}$, 13 TeV,' + f' {year}', fontsize=self.style.fontsize, ax=self.ax)
-        plt.plot(self.xcenters, self.nominal, label="nominal")
-        plt.plot(self.xcenters, self.up, label=f"{self.name} up")
-        plt.plot(self.xcenters, self.down, label=f"{self.name} down")
-        plt.legend()
+        self.ax.hist(self.xcenters, weights=self.nominal, histtype="step", label="nominal", **self.style.opts_syst["nominal"])
+        self.ax.hist(self.xcenters, weights=self.up, histtype="step", label=f"{self.name} up", **self.style.opts_syst["up"])
+        self.ax.hist(self.xcenters, weights=self.down, histtype="step", label=f"{self.name} down", **self.style.opts_syst["down"])
+        self.ax.set_xlabel(self.xlabel)
+        self.ax.set_ylabel("Counts")
+        self.ax.legend()
         #plt.show()
         #plt.close()
         return self.fig, self.ax
diff --git a/scripts/plot/make_plots.py b/scripts/plot/make_plots.py
index 3f199f45..2cd96f09 100644
--- a/scripts/plot/make_plots.py
+++ b/scripts/plot/make_plots.py
@@ -1,52 +1,48 @@
 import os
 import sys
 import time
-import json
 import argparse
 
 import numpy as np
 
 import matplotlib
-import matplotlib.pyplot as plt
-from matplotlib.offsetbox import AnchoredText
 matplotlib.use('Agg')
 
-
-import matplotlib.pyplot as plt
-import math
-import mplhep as hep
 from coffea.util import load
-from coffea.hist import plot
-import coffea.hist as hist
 
 from multiprocessing import Pool
-from pocket_coffea.parameters.lumi import lumi, femtobarn
 
 from pocket_coffea.utils.configurator import Configurator
-from pocket_coffea.utils.plot_utils import slice_accumulator, plot_data_mc_hist1D
+from pocket_coffea.utils.plot_utils import PlotManager
+
+def slice_accumulator(accumulator, entrystart, entrystop):
+    '''Returns an accumulator containing only a reduced set of histograms, i.e. those between the positions `entrystart` and `entrystop`.'''
+    _accumulator = dict([(key, value) for key, value in accumulator.items()])
+    _accumulator['variables'] = dict(
+        [(key, value) for key, value in accumulator['variables'].items()][
+            entrystart:entrystop
+        ]
+    )
+    return _accumulator
 
 parser = argparse.ArgumentParser(description='Plot histograms from coffea file')
 parser.add_argument('--cfg', default=os.getcwd() + "/config/test.json", help='Config file with parameters specific to the current run', required=False)
 parser.add_argument("-i", "--inputfile", required=True, type=str, help="Input file")
 parser.add_argument('--plot_dir', default=None, help='Sub-directory inside the plots folder to save plots', required=False)
 parser.add_argument('-v', '--version', type=str, default=None, help='Version of output (e.g. `v01`, `v02`, etc.)')
-parser.add_argument('--test', default=False, action='store_true', help='Test mode')
 parser.add_argument('-j', '--workers', type=int, default=8, help='Number of parallel workers to use for plotting')
 parser.add_argument('-o', '--only', type=str, default='', help='Filter histograms name with string', required=False)
-parser.add_argument('-oc', '--only_cat', type=str, default='', help='Filter categories with string', required=False)
+parser.add_argument('-oc', '--only_cat', type=str, nargs="+", help='Filter categories with string', required=False)
 parser.add_argument('-os', '--only_syst', type=str, nargs="+", default='', help='Filter systematics with a list of strings', required=False)
 parser.add_argument('--split_systematics', action='store_true', help='Split systematic uncertainties in the ratio plot')
 parser.add_argument('--partial_unc_band', action='store_true', help='Plot only the partial uncertainty band corresponding to the systematics specified as the argument `only_syst`')
 parser.add_argument('--overwrite', action='store_true', help='Overwrite plots in output folder')
 parser.add_argument('--log', action='store_true', help='Set y-axis scale to log')
+parser.add_argument('-d', '--data_key', type=str, default='DATA', help='Prefix for data samples', required=False)
 
 args = parser.parse_args()
 config = Configurator(args.cfg, plot=True, plot_version=args.version)
 
-#finalstate = config.finalstate
-#categories_to_sum_over = config.plot_options["sum_over"]
-#var = config.plot_options["var"]
-
 print("Starting ", end='')
 print(time.ctime())
 start = time.time()
@@ -65,22 +61,12 @@ if not args.overwrite:
 if not os.path.exists(config.plots):
     os.makedirs(config.plots)
 
+
 def make_plots(entrystart, entrystop):
+    '''Function that instantiates multiple PlotManager objects each managing a different subset of histograms.'''
     _accumulator = slice_accumulator(accumulator, entrystart, entrystop)
-    for (histname, h) in _accumulator['variables'].items():
-        plot_data_mc_hist1D(
-            h,
-            histname,
-            config,
-            plot_dir=args.plot_dir,
-            flavorsplit=None,
-            only_cat=args.only_cat,
-            mcstat=True,
-            stat_only=False,
-            split_systematics=args.split_systematics,
-            only_syst=args.only_syst,
-            partial_unc_band=args.partial_unc_band,
-            log=args.log)
+    plotter = PlotManager(hist_cfg=_accumulator['variables'], plot_dir=config.plots, only_cat=args.only_cat, data_key=args.data_key, log=args.log, save=True)
+    plotter.plot_datamc_all(ratio=True, syst=True, spliteras=False)
 
 # Filter dictionary of histograms with `args.only`
 accumulator['variables'] = { k : v for k,v in accumulator['variables'].items() if args.only in k }
@@ -96,6 +82,7 @@ print("Histograms to plot:", HistsToPlot)
 delimiters = np.linspace(0, NtotHists, args.workers + 1).astype(int)
 chunks = [(delimiters[i], delimiters[i+1]) for i in range(len(delimiters[:-1]))]
 pool = Pool()
+# Parallel calls of make_plots on different subsets of histograms
 pool.starmap(make_plots, chunks)
 pool.close()
 
-- 
GitLab


From cbd5bf9668a8626e0605ec4f8b67e0db1408ff7a Mon Sep 17 00:00:00 2001
From: mmarchegiani <matmarcheg@gmail.com>
Date: Tue, 28 Mar 2023 14:06:53 +0200
Subject: [PATCH 08/24] Cleaning code

---
 pocket_coffea/utils/plot_utils.py | 68 ++++++++++++++++---------------
 1 file changed, 35 insertions(+), 33 deletions(-)

diff --git a/pocket_coffea/utils/plot_utils.py b/pocket_coffea/utils/plot_utils.py
index ebdbba93..dd5fa831 100644
--- a/pocket_coffea/utils/plot_utils.py
+++ b/pocket_coffea/utils/plot_utils.py
@@ -27,7 +27,7 @@ class Style:
 
 class PlotManager:
     '''This class manages multiple DataMC objects and their plotting.'''
-    def __init__(self, hist_cfg, plot_dir, only_cat=[], data_key="DATA", log=False, save=True) -> None:
+    def __init__(self, hist_cfg, plot_dir, only_cat=[], style_cfg=style_cfg, data_key="DATA", log=False, save=True) -> None:
         self.datamc_objects = {}
         self.plot_dir = plot_dir
         self.only_cat = only_cat
@@ -35,10 +35,10 @@ class PlotManager:
         self.log = log
         self.save = save
         for name, h_dict in hist_cfg.items():
-            self.datamc_objects[name] = DataMC(h_dict, name, plot_dir, only_cat, data_key=self.data_key, log=self.log)
+            self.datamc_objects[name] = DataMC(h_dict, name, plot_dir, only_cat=self.only_cat, style_cfg=style_cfg, data_key=self.data_key, log=self.log)
 
     def plot_datamc_all(self, ratio=True, syst=True, spliteras=False):
-        '''Plots all the histograms containted in the dictionary, for all years and categories.'''
+        '''Plots all the histograms contained in the dictionary, for all years and categories.'''
         for name, datamc in self.datamc_objects.items():
             datamc.plot_datamc_all(ratio, syst, spliteras, save=self.save)
 
@@ -364,6 +364,38 @@ class DataMC:
                     plt.show(self.fig)
                 plt.close(self.fig)
 
+
+class SystManager:
+    '''This class handles the systematic uncertainties of 1D MC histograms.'''
+    def __init__(self, datamc : DataMC, has_mcstat=True) -> None:
+        self.datamc = datamc
+        assert all([(var == "nominal") | var.endswith(("Up", "Down")) for var in self.datamc.variations]), "All the variations names that are not 'nominal' must end in 'Up' or 'Down'."
+        self.variations_up = [var for var in self.datamc.variations if var.endswith("Up")]
+        self.variations_down = [var for var in self.datamc.variations if var.endswith("Down")]
+        assert len(self.variations_up) == len(self.variations_down), "The number of up and down variations is mismatching."
+        self.systematics = [s.split("Up")[0] for s in self.variations_up]
+        if has_mcstat:
+            self.systematics.append("mcstat")
+        self.syst_dict = {}
+
+        for syst_name in self.systematics:
+            self.syst_dict[syst_name] = SystUnc(self.datamc, syst_name)
+
+    @property
+    def total(self):
+        total = SystUnc(name="total", syst_list=list(self.syst_dict.values()))
+        return total
+
+    @property
+    def mcstat(self):
+        return self.syst_dict["mcstat"]
+
+    def get_syst(self, syst_name : str):
+        '''Returns the SystUnc object corresponding to a given systematic uncertainty,
+        passed as the argument `syst_name`.'''
+        return self.syst_dict[syst_name]
+
+
 class SystUnc:
     '''This class stores the information of a single systematic uncertainty of a 1D MC histogram.
     The built-in __add__() method implements the sum in quadrature of two systematic uncertainties,
@@ -510,33 +542,3 @@ class SystUnc:
         #plt.show()
         #plt.close()
         return self.fig, self.ax
-
-class SystManager:
-    '''This class handles the systematic uncertainties of 1D MC histograms.'''
-    def __init__(self, datamc : DataMC, has_mcstat=True) -> None:
-        self.datamc = datamc
-        assert all([(var == "nominal") | var.endswith(("Up", "Down")) for var in self.datamc.variations]), "All the variations names that are not 'nominal' must end in 'Up' or 'Down'."
-        self.variations_up = [var for var in self.datamc.variations if var.endswith("Up")]
-        self.variations_down = [var for var in self.datamc.variations if var.endswith("Down")]
-        assert len(self.variations_up) == len(self.variations_down), "The number of up and down variations is mismatching."
-        self.systematics = [s.split("Up")[0] for s in self.variations_up]
-        if has_mcstat:
-            self.systematics.append("mcstat")
-        self.syst_dict = {}
-
-        for syst_name in self.systematics:
-            self.syst_dict[syst_name] = SystUnc(self.datamc, syst_name)
-
-    @property
-    def total(self):
-        total = SystUnc(name="total", syst_list=list(self.syst_dict.values()))
-        return total
-
-    @property
-    def mcstat(self):
-        return self.syst_dict["mcstat"]
-
-    def get_syst(self, syst_name : str):
-        '''Returns the SystUnc object corresponding to a given systematic uncertainty,
-        passed as the argument `syst_name`.'''
-        return self.syst_dict[syst_name]
-- 
GitLab


From 8b19d929f525833cdac640aa08222b0aceb82961 Mon Sep 17 00:00:00 2001
From: mmarchegiani <matmarcheg@gmail.com>
Date: Tue, 28 Mar 2023 14:07:33 +0200
Subject: [PATCH 09/24] Include style as input argument of PlotManager

---
 scripts/plot/make_plots.py | 11 ++++++++++-
 1 file changed, 10 insertions(+), 1 deletion(-)

diff --git a/scripts/plot/make_plots.py b/scripts/plot/make_plots.py
index 2cd96f09..8cebfac7 100644
--- a/scripts/plot/make_plots.py
+++ b/scripts/plot/make_plots.py
@@ -14,6 +14,7 @@ from multiprocessing import Pool
 
 from pocket_coffea.utils.configurator import Configurator
 from pocket_coffea.utils.plot_utils import PlotManager
+from pocket_coffea.parameters.plotting import style_cfg
 
 def slice_accumulator(accumulator, entrystart, entrystop):
     '''Returns an accumulator containing only a reduced set of histograms, i.e. those between the positions `entrystart` and `entrystop`.'''
@@ -65,7 +66,15 @@ if not os.path.exists(config.plots):
 def make_plots(entrystart, entrystop):
     '''Function that instantiates multiple PlotManager objects each managing a different subset of histograms.'''
     _accumulator = slice_accumulator(accumulator, entrystart, entrystop)
-    plotter = PlotManager(hist_cfg=_accumulator['variables'], plot_dir=config.plots, only_cat=args.only_cat, data_key=args.data_key, log=args.log, save=True)
+    plotter = PlotManager(
+        hist_cfg=_accumulator['variables'],
+        plot_dir=config.plots,
+        style_cfg=style_cfg,
+        only_cat=args.only_cat,
+        data_key=args.data_key,
+        log=args.log,
+        save=True
+    )
     plotter.plot_datamc_all(ratio=True, syst=True, spliteras=False)
 
 # Filter dictionary of histograms with `args.only`
-- 
GitLab


From 1fc70ac5c07cf6bc97fad5263747ebd115fbe6c1 Mon Sep 17 00:00:00 2001
From: mmarchegiani <matmarcheg@gmail.com>
Date: Tue, 28 Mar 2023 14:42:48 +0200
Subject: [PATCH 10/24] Renaming DataMC -> Shape

---
 pocket_coffea/utils/plot_utils.py | 20 +++++++++-----------
 1 file changed, 9 insertions(+), 11 deletions(-)

diff --git a/pocket_coffea/utils/plot_utils.py b/pocket_coffea/utils/plot_utils.py
index dd5fa831..dca8fb3f 100644
--- a/pocket_coffea/utils/plot_utils.py
+++ b/pocket_coffea/utils/plot_utils.py
@@ -1,11 +1,9 @@
 import os
-import sys
 
 import math
 import numpy as np
 import awkward as ak
 import hist
-from coffea.util import load
 
 import matplotlib.pyplot as plt
 from matplotlib.pyplot import cm
@@ -26,7 +24,7 @@ class Style:
 
 
 class PlotManager:
-    '''This class manages multiple DataMC objects and their plotting.'''
+    '''This class manages multiple Shape objects and their plotting.'''
     def __init__(self, hist_cfg, plot_dir, only_cat=[], style_cfg=style_cfg, data_key="DATA", log=False, save=True) -> None:
         self.datamc_objects = {}
         self.plot_dir = plot_dir
@@ -35,7 +33,7 @@ class PlotManager:
         self.log = log
         self.save = save
         for name, h_dict in hist_cfg.items():
-            self.datamc_objects[name] = DataMC(h_dict, name, plot_dir, only_cat=self.only_cat, style_cfg=style_cfg, data_key=self.data_key, log=self.log)
+            self.datamc_objects[name] = Shape(h_dict, name, plot_dir, only_cat=self.only_cat, style_cfg=style_cfg, data_key=self.data_key, log=self.log)
 
     def plot_datamc_all(self, ratio=True, syst=True, spliteras=False):
         '''Plots all the histograms contained in the dictionary, for all years and categories.'''
@@ -43,11 +41,11 @@ class PlotManager:
             datamc.plot_datamc_all(ratio, syst, spliteras, save=self.save)
 
 
-class DataMC:
+class Shape:
     '''This class handles the plotting of 1D data/MC histograms.
     The constructor requires as arguments:
     - h_dict: dictionary of histograms, with each entry corresponding to a different MC sample.
-    - name: name that identifies the DataMC object.
+    - name: name that identifies the Shape object.
     - style_cfg: dictionary with style and plotting options.
     - data_key: prefix for data samples (e.g. default in PocketCoffea: "DATA_SingleEle")'''
     def __init__(self, h_dict, name, plot_dir, only_cat=[], style_cfg=style_cfg, data_key="DATA", log=False) -> None:
@@ -58,7 +56,7 @@ class DataMC:
         self.style = Style(style_cfg)
         self.data_key = data_key
         self.log = log
-        assert type(h_dict) == dict, "The DataMC object receives a dictionary of hist.Hist objects as argument."
+        assert type(h_dict) == dict, "The Shape object receives a dictionary of hist.Hist objects as argument."
         self.define_samples()
         assert self.dense_dim == 1, f"Histograms with dense dimension {self.dense_dim} cannot be plotted. Only 1D histograms are supported."
         self.load_attributes()
@@ -367,7 +365,7 @@ class DataMC:
 
 class SystManager:
     '''This class handles the systematic uncertainties of 1D MC histograms.'''
-    def __init__(self, datamc : DataMC, has_mcstat=True) -> None:
+    def __init__(self, datamc : Shape, has_mcstat=True) -> None:
         self.datamc = datamc
         assert all([(var == "nominal") | var.endswith(("Up", "Down")) for var in self.datamc.variations]), "All the variations names that are not 'nominal' must end in 'Up' or 'Down'."
         self.variations_up = [var for var in self.datamc.variations if var.endswith("Up")]
@@ -400,7 +398,7 @@ class SystUnc:
     '''This class stores the information of a single systematic uncertainty of a 1D MC histogram.
     The built-in __add__() method implements the sum in quadrature of two systematic uncertainties,
     returning a `SystUnc` instance corresponding to their sum in quadrature.'''
-    def __init__(self, datamc : DataMC = None, name : str = None, syst_list : list = None) -> None:
+    def __init__(self, datamc : Shape = None, name : str = None, syst_list : list = None) -> None:
         self.datamc = datamc
         self.name = name
         self.is_mcstat = self.name == "mcstat"
@@ -415,7 +413,7 @@ class SystUnc:
             else:
                 self.syst_list = [self]
             self._get_err2()
-            # Inherit style from DataMC object
+            # Inherit style from Shape object
             self.style = self.datamc.style
             # Full nominal MC including all MC samples
             self.h_mc_nominal = self.datamc.stack_sum_mc_nominal
@@ -485,7 +483,7 @@ class SystUnc:
 
     def _get_err2(self):
         '''Method used in the constructor to instanstiate a SystUnc object from
-        a DataMC object. The corresponding up/down squared uncertainties are stored and take
+        a Shape object. The corresponding up/down squared uncertainties are stored and take
         into account the possibility for the uncertainty to be one-sided.'''
         # Loop over all the MC samples and sum the systematic uncertainty in quadrature
         for h in self.datamc.stack_mc:
-- 
GitLab


From 2e972018859ec2249bfd12d3c7517fe9ccb0c064 Mon Sep 17 00:00:00 2001
From: mmarchegiani <matmarcheg@gmail.com>
Date: Tue, 28 Mar 2023 14:43:01 +0200
Subject: [PATCH 11/24] Update notebook

---
 notebooks/plotting/test_DataMC.ipynb | 433 ++++++++-------------------
 1 file changed, 128 insertions(+), 305 deletions(-)

diff --git a/notebooks/plotting/test_DataMC.ipynb b/notebooks/plotting/test_DataMC.ipynb
index 03e59d6d..b9ea0f6b 100644
--- a/notebooks/plotting/test_DataMC.ipynb
+++ b/notebooks/plotting/test_DataMC.ipynb
@@ -9,7 +9,7 @@
    "source": [
     "import matplotlib.pyplot as plt\n",
     "from coffea.util import load\n",
-    "from pocket_coffea.utils.plot_utils import DataMC"
+    "from pocket_coffea.utils.plot_utils import Shape"
    ]
   },
   {
@@ -21,7 +21,7 @@
     {
      "data": {
       "text/plain": [
-       "<pocket_coffea.utils.plot_utils.DataMC at 0x7f7fed685400>"
+       "<pocket_coffea.utils.plot_utils.Shape at 0x7f61abd440d0>"
       ]
      },
      "execution_count": 2,
@@ -34,7 +34,7 @@
     "o = load(filename)\n",
     "histname = \"ElectronGood_pt_1\"\n",
     "h_dict = o[\"variables\"][histname]\n",
-    "datamc = DataMC(h_dict, histname)\n",
+    "datamc = Shape(h_dict, histname, plot_dir='plots/')\n",
     "datamc"
    ]
   },
@@ -65,12 +65,15 @@
        " 'is_data_only',\n",
        " 'is_mc_only',\n",
        " 'load_attributes',\n",
+       " 'log',\n",
        " 'lumi',\n",
        " 'name',\n",
+       " 'only_cat',\n",
        " 'plot_data',\n",
        " 'plot_datamc',\n",
        " 'plot_datamc_all',\n",
        " 'plot_datamc_ratio',\n",
+       " 'plot_dir',\n",
        " 'plot_mc',\n",
        " 'plot_systematic_uncertainty',\n",
        " 'samples',\n",
@@ -233,6 +236,7 @@
        " 'plot_datamc',\n",
        " 'plot_datamc_all',\n",
        " 'plot_datamc_ratio',\n",
+       " 'plot_dir',\n",
        " 'plot_mc',\n",
        " 'plot_systematic_uncertainty']"
       ]
@@ -256,19 +260,19 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:200: RuntimeWarning: invalid value encountered in true_divide\n",
+      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:207: RuntimeWarning: invalid value encountered in true_divide\n",
       "  self.ratio = num / den\n",
-      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:203: RuntimeWarning: invalid value encountered in true_divide\n",
+      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:210: RuntimeWarning: invalid value encountered in true_divide\n",
       "  self.ratio_unc = np.sqrt(num) / den\n",
-      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:389: RuntimeWarning: invalid value encountered in true_divide\n",
+      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:449: RuntimeWarning: invalid value encountered in true_divide\n",
       "  return np.where(self.nominal != 0, self.up / self.nominal, 1)\n",
-      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:393: RuntimeWarning: invalid value encountered in true_divide\n",
+      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:453: RuntimeWarning: invalid value encountered in true_divide\n",
       "  return np.where(self.nominal != 0, self.down / self.nominal, 1)\n"
      ]
     },
     {
      "data": {
-      "image/png": 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0aVMRgFirVi2F+6Ojo6X+vr6+CseOHz8uHbt165bYrVs3teeeMWOGmJmZKf7yyy9q16k2atRITE9PV4rN1dVVBCB6enoq3B8fHy/13bZtm+jr66uy/pDsa8WKFWp/BosXLxbNzMw0Pn+WlpYqawTJP0dHjhwRvb29Ffp16NBBzMzMlKaLuru7q41DFEWxX79+IgDRzMxMfP78uca2RET0eRo+fLgIQGzcuLHOfWW14kqXLq2x3Z07d6T/VXv27NF6/BcvXkj9NC3PWLZsmc4zCtS975N/7/fxTJfnz5+LEyZMECtUqCCamJiINjY2YosWLcQ1a9aonY1y4cIFcdOmTRq/bt++rbJvfs10iYuL0/i+RNOMBfk6iepqKYqiqFA7MTo6Otcx52amy6tXr8Qff/xRrFOnjlisWDHRwsJCrFmzpjh27Fjx3r17avtlZGSI5cqVEwGIJUqU0PhzuX79uhTf5MmTdYovO6dPn5bGVldKQUY2U6RevXrSfWfOnJH6//bbb2r7zps3T2p34cIFpeO5ed3k5e92fioConyg7tMKXT8p0ZePZ7pkZGTg+vXr8PDwkO77uBJ3mTJlUK5cOZ3OM3/+fAQHB2tdvTw5ORnXrl3DtWvXsHbtWgBZlb07duyIcePGwd7eXqfzA4o7F2kz0yU4OBiLFi0CAJiamkq7Sj148AAfPnwAAGzcuBFXrlyBIAho1aoVatasidatW0tjBAUFoWXLllJV/6pVq8LDwwPOzs6IiIjArl27EBcXh6CgIPTr1w9nzpxR+NQrPT1dqqT+ccyybDeguI30x8eGDh2KGzduwM3NDV5eXjA2Noa/v7+0ZfmSJUvw5MkTbNmyBSVKlEDHjh1RtWpVBAYGYs+ePQCyXgNHjhxB586dpXHfv3+Pe/fuqTy/fPX3pUuX4vr16zA2Nkb79u3h5uaGtLQ0/Pnnn9IWe99//z2GDx+utA362rVr8d133wHIqoTfvXt3VKtWDUZGRggODsb+/fuRlJSEd+/eYeTIkbh9+7ba52HWrFm4cuUKjI2N8dVXX6F69ero2rUrBEGAk5MTQkJCEBUVBXUCAwPh7+8PAJgyZQpKly6tti0REX2+ZDNdKlWqBCBrFvPDhw8RExOD0qVLo3LlyjAwUD2JXvZ+wMHBQeM55D/F1jSb82MlSpRAkSJFkJ6erjRLWZ78sbz6f3br1i20bt0ar1+/lu5LSUnB+fPncf78eWzYsAFHjhxR2nGoWbNmaNasWZ7EpC9WVlZ49+6dwn1z587FvHnzsu3r4uIitdP03MveIxkaGsLGxiYX0ebOsWPH0K9fP6VdTIODgxEcHIxVq1bht99+w5QpU5Rm7RgYGKBv375YsGABYmNjcebMGYX3yfLycteiV69eSbezu4axt7fHixcvFHYSkr1nBoC2bduq7du+fXv88MMPALKuFz5+HefmdVOYfrdzpaCzPvRlkN/tRf5LX+s1VdE00yUzM1MsU6aMwv1z585V6N+pUyeF47169RJFUf0nHqpmuohiVkXyGTNmKBSqyslX0aJFxdWrV+tUlTstLU0sWrSoCGQVnsrO4cOHxbJly0rn/Omnn6RjW7duVYinZs2a4tWrV5XGeP36tVRAzMLCQtyyZYvSbJFXr16J1atXV/tp1u3bt6Vja9asUTgmv3PRx7MuevbsKR0zNDRUer7ev38vVqpUSeFx9OzZU3z9+rXCOJMmTZKO//rrrwrH5F/LO3bsUDi2YMEChbHd3NzEO3fuKLSJjY1VeI4/Lhb45s0baT2zs7Oz+OjRI6XnODQ0VCqODBWfEMg/RwDEFi1aqPxEpkOHDtJzpWpGjyiKYuvWrUUAYsmSJcWEhASVbYiI6PMn+981cuRIccSIEVJ9DtmXvb29+Msvv4iJiYlKfdu1aycCWQX9NZGf6fL999/rFJ9sViYA8Z9//lE6HhgYKP1/bdSokdbjhoWFKeyCU7JkSalgsKrdi5ycnEQAYpMmTcRff/1V3LZtmzh+/HjRzs5OatOkSRO1/3dzoiB3L5J/X6zNLjSa3L17V3q/3LVrV73Hp+1Ml//++0+aBW1paSl+99134ubNm8UtW7aI48aNU5iJLJsR/rEbN25IbUaMGKH2XLKal+XKldP7zjsPHjyQZkm9fftWbbuEhATpMck/7/I7Br1580Zt/9jYWLXXU+ro8rrJq9/t/MSkC+UL+Yr38l/yU9j0TVPSRRRFsXfv3gr3d+zYUeqbmZkp2traKhz//fffRVHUPekiI6vy3a9fP6WxdflatGiR1s/BrVu3pH6urq7i8uXLlb4WL14sjhkzRmzYsKHCedq2bavwz3vixInSsdKlS4sxMTEqzzly5EgpSXT+/Hm1sckvBfp4uqD8FNSAgACFY7IlQ2XKlFEa09nZWeq3dOlSlecdO3asQjJCVTG/s2fPSm3Wrl2rcGzJkiXSsQcPHigck/+nUL58ebX/4KZPny61u3btmsKxdevWScdUFSyTadu2rfQm92Pyy6pq1aql9p+ZfHE0VUvZ5JfYrV69Wm0sRET0eUtMTNT6fUr9+vWV3iP873//U/t/XZ78Rd7XX3+tU4yvXr0SK1euLAJZBUGHDh0qbt68Wdy+fbs4fvx4acvckiVLKv3/1oa2hXSBrI0XPk6qREREiLVq1ZLa/PnnnzrHoM6nmnS5e/euuH37dnHZsmVi//79pQ8Ky5QpI4aHh+s9Pm2SLhkZGdIy8ho1aogvX75UavP06VOp+GzRokVV7tqTmZkpVqlSRQTULzGS36lT30uLdDFjxgwpjuXLl0v3f/PNNyKQVYQ3IyNDbf/09HSp5IC6zUk+psvrJq9/t/MDky6UL9TVdKlUqVKenTO7pMvixYsV7rexsZH+oISHhyv1k60PzGnSRV5GRoZ448YNce3ateLo0aPFRo0aZVu/Q/ZVpEgRMSIiQqvzbNiwIUeJnZEjR4opKSkKYzVv3lw6fuzYMZXne/bsmbQd94wZMzTGJr++c+DAgQrHRo8eLQIQjY2NleJwdHQUAeWdDWJiYqTxatasqfbTAvntCj+ehSKzf/9+qc2///6rcOzrr78Wgaxt8z7+ByT7hwBAvHz5strH/uOPP0rtYmNjFY6FhoaKZ86cEc+dO6fxEw/ZP/JOnTopHZM9R4aGhmJwcLDaMX799Ve1yZ+MjAyxfv36IgDRxcWlQN7IERFR4RAcHKzwPmHAgAHi7du3xcTERDEsLEzcunWrwixO+Q+yRFFx9yJ3d3eVn5qfPn1a+rQagNi6dWud43zz5o341VdfqX1/U69ePTEyMjJHz4G2SZfKlSurncUi/zx6eHjkKA5VPtWky9SpU5V+Ru3atRNfvHiRJ/Fpk3Q5evSo1F5T3Rb5D5RlH8x+TD6Z8fH7SVEUxd9++03pOiM/ZWZmiqtXr5ZiKFmypEKNS9kMcmtr62zHsra2FgGIffv21ercur5u8vJ3Oz+wpgvlixIlSqi8/8mTJ0hNTYWxsXE+R6Rc1+XNmzd48OABqlatqlTPxcTEBHXr1tXbuQ0MDFCvXj3Uq1dPui89PR1BQUE4d+4cDhw4gAsXLqjsm56ejo0bN2LWrFnZnke+nosmRYsWhYODA7y8vDBs2DDUr19f4XhmZiZu3rwJIGstd5s2bVSOs3HjRmk3nyJFimDFihVqz5mSkiLddnJyUhl3nTp1FF4br1+/ltZ4fxyjfD2VIUOGqKyKD2SttQay6rFUr15dZRv5Ginq6sa4ubkprF1/+/attPbVzc0NjRs3Vjm2fAwVK1ZUWq9ctWpVVK1aVW3flJQU+Pv7SztMNWzYUOG4/HPUsmVL1KhRQ+1Y8s97VFSUQv2cPXv2SDtI/fbbbyhShP8uiIi+VI8fP5bqj/3vf//DrFmzpP+zlSpVQqVKldC5c2c0atQI9+7dwz///IPz58+jRYsWAIDGjRvjm2++wapVq3Dt2jXUqFEDI0eOhKurK2JjY3H+/Hn4+/vD0NAQRkZGSEtLU7sDpDoZGRlYtmwZLl68qLbNrVu3sGjRIsydOxempqY5fDY0mzRpEgwNDVUeq1GjBrp27YoDBw4gODhYb+fUtnbgp+D48eOYMGEC1qxZA2tr63w//9GjRwFk1VR0cXFR26527dooX748Hj9+jPPnz0u1+OT169dPer++a9cupbousnou+t61SBuPHz/GpEmTpJ2TTExMsGfPHpiZmUltEhISAGRdJ2RH9vuky65j2iosv9u5wXfRlC9k2/CGhoYq3J+Wloa7d+8WyLbRderUQdGiRZGUlCTdd/nyZZVJlwYNGuR5YqhIkSKoX78+6tevj8mTJ+PatWvo0aOHyiKnly5d0mpM2UWzIAh4+/YtLC0tcxTbgwcPpO2Te/bsqTahIStACwAzZszQenz5i/+UlBQp6ZHTIrqqtrQDgA8fPiAkJARAVkJCHVnS5+OkyIcPH9QW0ZUlpQCgb9++ascWRVEaX1Nh48TERNy/fx8PHz7Ew4cPER4ejjt37iAwMBCpqalSu4//Scs/Dz179lQ7PqCcdJFJS0vDTz/9BABo3ry50tbcRET0ZencubNCgU1VrKyssHjxYrRv3x5A1kWmLOkCZCXw379/jz///BPPnz+Hr6+vQn9jY2Ns2bIFI0aMQFpaGiwsLLSOTxRFDB06FH/++ScAoE2bNvj+++9Ro0YNGBkZITQ0FMuXL8fOnTuxePFihIaGYv/+/UqF7PUhu4vnhg0b4sCBA3jz5g3i4uIKJLFQWPz666+YN28eXr9+jfv372PZsmXYs2cPdu3ahfv37+Pq1at58jPSRPZ+7tatW2rf737s5cuXKu93dXVF7dq1cevWLezbtw+rVq2SkokvXryQrjd69+6t9blyKyEhAfPmzcPixYulD0BtbGywbds2NG/eXKGtra0tACgVE1YlLi5OGkufCtPvdm6oLjFOlAc+/kWWOXz4sM5jDRgwALa2tgpfH8+WyI6RkZHSLAHZvvH//fefwv2aZi2oc/HiRaUv2QwHbbi7uyskMeSp++MuTz55UbVq1RwnXADFC/kOHTqobPP69WuNVcU1kf/Z3b59G2lpaQCUZ7Nok3QpWrSo2hksN2/elGbiqEt4yCdFPj5/UFCQ1F9T0kddhXoAiIyMRHR0tNoYbt++jTFjxqBkyZKoV68eevfujWnTpmHv3r0wMDDApEmT0K5dO6m9pudI3c9KRr6SvXzSZePGjdKsnQULFuTbGwEiIvq0tWnTRvqUWf7/EQBYWFhgy5YtOHLkCPr164dq1arBxMQEZcqUweDBgxEUFIQuXbpIH/J8vLuPJgcPHpQuyoYPH47jx4/jq6++QqlSpWBjY4OmTZvC398fv/zyC4CsnWnWr1+vj4esxNnZWeNx2e5PAPDw4cM8ieFTIggCSpYsiebNm2P37t0YN24cgKykx19//ZXv8cTExOjcRzYjRJV+/foBgLSLkcyBAwek23369NH5nDlx4sQJ1KhRA7/++quUcOncuTPu3LkjJUvlyXZN/fDhg8IHfh9LSkqSkrJlypTRa8yF6Xc7NzjThfJNq1atsG7dOqX7t2zZgmnTpmm9fCE9PR3//POP0h+4nHxS0LRpU4UpmZcvX0ZiYqJScqRJkyY6j925c2dpi0SZkiVL4uXLl1pfxLq7u8PCwkJ6A6KLW7duScmLjxMEupK9cRIEQWFJlLygoCDp9tatWzFo0KAcnUvTFteyOMqUKaO0fbbsWL169dS+luTHVvdJVFRUlJTUyslMG1NTU7VJn49jkB9fFEXMnTsXP//8M0RRhKurK3r37o3GjRujXr16sLOzk143sk8OK1eurPSJgiyOkiVLwtHRUW0cQNaWerJp3LKky4cPH+Dn5wcg603Ax4lJIiIidQwMDFC5cmUEBwcjNjZWZZv27durvMADgIiICOm2pqW2H9u4cSOArG2GFy9erLbdDz/8gFWrVuHFixfYuHEjvv32W63PoS11S4tkMjIypNv8UEPZzz//jOXLlwMAzp8/jyFDhuTr+dPT0wFkvUfTZik/oHn5Td++faXtlHfv3i0t0ZctLXJyctI481kfUlJSMHHiRKxZs0a6r3bt2li4cCG8vLzU9pN/rx0XF4dSpUqpbCeb5QLof7vmwvS7nRtMulC+6datG+zt7ZVmaYSHh2PlypWYMGGCVuP8+++/KjPKVapU0Tmmj5MpoaGhOHnypPQHVyYnM13KlCmjlHR59eoVwsLCtI713bt3SExMVLrfwcEh276ypUWA8mwIXcku5F1dXdVO933x4oV0u3jx4jk+lyxuc3NzpTdcsjg+fjxv3rzB48ePAWhesnPt2jUA0DgzSpukj5WVFSpWrKjyWL169TSuQ5eNL6vrI7Nx40ZpSc/SpUsxduxYlW/cMjIypKmvqhJH8s9Rdm/mDAwM4OjoiEePHiEyMhIAsGTJErx8+RJGRkaYO3euxv5EREQfk72HKlasmM595T/AqVmzptb9wsPDAWh+nwJkXbi5ubnh8OHD0oxOfXv8+LHGZfPys1tkyze+BFOmTEFkZCTq1auH77//Xm07Ozs72NjY4M2bN3j+/Hk+RphF9mFWUlKSwszinCpfvjwaNWqEK1eu4O+//8aqVauQmJgozXrJ66VFmZmZGDx4MHbt2gUga8bZokWLMGzYsGwThPJJl+DgYLVJF9nSfUD/SZfC9LudG1xeRPnGxMREmjL4salTp+L06dPZjvH8+XMMHTpU5bHu3bvrHJOqZMqSJUsUvq9YsaLaPzKayK9jljdo0CB8+PBBqzG2bNkiLWeRp01RX/nkQW5musgX0dWUvJGfXfL06VONYwYGBsLX1xe+vr5S0VcZWdz16tVT+GcQExMjjfvx45EvoqtpLbVsbHd3d7X/4GRtBEFQep7lEyvyRXQTEhKkwrbZfVohG79atWowNzcHkFVD5eeffwaQlZwcP3682n+EBw4ckGY+ffxY5Z8jbRNtsuRTVFQUYmJiMH/+fADAN998o5RYIiKiL1P79u1Ro0YNfPPNNxrbpaenSxdJ8stobt26Jf3fV1WrTmbHjh0Asj7c0GWWsax+w7t377JtK/vgLq9q9cl/6KWKbCl7iRIlFJb5fu5CQkKwc+dO+Pv7a2yXmJgozZywsrLKj9AUyGYrP3z4UOOSGlEUcfz4cRw7dkx6zasjW2L05s0bnDlzBv/88480G7137956ily16dOnSwmXmjVrIjg4GCNHjsw24QIoXm/8888/atsdOXJEuq3vOp2F6Xc7N5h0oXw1btw4hX/CMikpKejQoQPmzp2rMiGRmZmJnTt3wsPDQ6qHIc/a2ho9evTQOR5ra2ulpSDy6y2BnC0tAoD+/furvP/69eto1aoVDh8+rDKhAmRdPM+ZMwcTJ05UeVxToVb58wBZsxly8wcwLCxM+kOn6UK+du3a0u0TJ06obZeQkIA+ffrAz88PW7duVciIf/jwAXfv3gWQ8yK66pIeb968kT5d0pQYkT1vrq6uCnVwEhMTpULQmoroaho7MzNTZRHde/fuqV3SJC8yMhLTpk2TvtdURDcnSZe5c+ciISEBxYoVk2bdEBERubq6IiQkBBs2bNBYV27btm3SxaT8LIGiRYvCz88Pfn5+2LZtm8q+b968waFDhwBkfZCmy+5FtWrVApC1K+b9+/fVtouJiZH+V8r66NuiRYvUvr8LDAyULlDbtWv3RS0vkr3/Dw0NVfleXubUqVMQRRFA9h9k5YWvvvoKQNZMl7Vr16ptd+zYMbRr1w7t27dXWBanSp8+faSf9a5du6Qdg/J6aVFcXJz0YXKVKlVw9uzZbGsOyatRo4aUGDx48KDC0jiZjIwM6fe2fPnyGpfY50Rh+t3ODSZdKF9ZWlrC399f5T/SlJQU/PjjjyhZsiQ6deqEb775BmPGjEG7du3g7OyMfv36qc0k//rrrzmulv3x1tEfy2nSpXnz5ujatavKY9euXUPnzp3h7OyMNm3aYOjQoZg4cSIGDhwIT09PlClTBj/99JP0T0der1691NZVkXn//r2UIMhuOl52tL2Qd3Fxkf4w79+/H9u3b1dq8+TJE7Rs2VJKfnxcy0dToVttki7W1tZqZ2fIf/KkqYiurN3HbeSL6GoqXqvpn2dYWJiUhZdvJ78jxNWrV5V+7hkZGdi/fz8aNWqkMGWyWrVqauPQdnaTLOny/v17aYvv6dOnf1FTnomISDPZhz1paWno37+/yp2Mbt68KS0bKV26tPTpPpB1wSdbWv3rr78qXaSmpKTAx8cHSUlJMDAwwPTp03WKz9vbW7o9cOBAlfVk3r9/D29vb+nDvcGDB+t0Dm3du3cPkyZNUrpAffz4Mb7++mvp+8JWcyKvyT4oSk5OxqRJk6TknLynT59Kz4uxsbFWHzLqW48ePaQZ7r6+vgozx2VevnyJ8ePHA8h6rWvaEVPWxtPTE0BWLRfZttR5vbRo27ZtUsHcxYsX63ytJAiCVP7h0aNH0mxoefPnz5fe10+YMEHvj6cw/W7nBmu6UL5zc3ODv78/BgwYIP0hkJeYmKhxCtvHRo8ejeHDh+c4niZNmqgs8Ct/PCcEQcCqVasQEhKiNln07NkzpeU1mlSoUEEqLqaJfPJCX0V0DQ0NFWazfKxIkSJYu3atVBxv0KBB2Lx5Mxo2bAhTU1Pcvn0b+/btk9Z6T5w4UennJv+PTV1iw8HBQW0R3QYNGqj9Yy+r5yJrp0p4eLhUhycnOydZWVmpnMklo65eTPXq1VGkSBGkp6fj4MGD8PDwgJeXF4yMjBAeHo5z585J/9DMzMykOj+jR4/GoEGDpF2K5AsNa1s9Xr62TVpaGhwdHaU3EkREREDWNsfffPMNVq1ahbNnz6Jq1aoYNWoUKleujJiYGAQEBGDz5s3IyMiAIAjYtGmTtIuRzLJly9CuXTvEx8ejXr16mDhxImrUqIHnz59j3bp1CA4OBgDMmjULlStXVorB19dXKvQ+c+ZMhS2nW7VqhUGDBmHbtm24ceMGKleujBEjRqBmzZoQBAGhoaHYuHGjNEvH09NT4WJOXxwcHBAXF4elS5fixo0b6NKlCxwcHHDt2jVs27ZNumAcNWoUGjVqpPfza6Lp+csPffr0waxZsxAeHo6//voLt27dwqBBg1CxYkW8e/cOt27dwvr165GUlAQA8PPzK5DlV6ampli9ejV69OiBN2/eoEmTJhg6dCjc3d1haWmJ4OBgrF27Fq9fv4aBgQH++OMPrZbq9OvXD2fOnMGbN2+k+7TZtSg3P7eLFy8CyHoPn5GRgWPHjmXbx8bGRmEm9ejRo7FhwwaEhoZi+vTpuHPnDjp37ozMzEwcOHBAWrpUvXp1jBw5UuvYtFVYfrdzTSQqIBcvXhRLliwpAsjRl6Ghofjjjz+KGRkZKsf38PBQ2e/MmTMK7cLCwtSew9LSUkxPT1doP3PmTJVtZ86cqTKOFy9eiA0bNszx45R9ubm5iVFRUVo9t4sWLZL6LVu2TKs+6siex1q1amnVfunSpaKpqanax2Fubi7OmjVLzMzMVOrbv39/EYBobW2tdNzJyUkEIHbp0kXh/jdv3khj//jjj2rj6tKliwhAdHJyUttm+/bt0lhXrlxROObt7S0CEK2srJRic3FxEQGIX331ldqxRVEUx48fLwIQjY2NxZSUFIVjc+fO1fjzt7OzEw8dOiR27txZ4f4ZM2Zk+xxpcurUKYXxtmzZonVfIiL6cqSkpCj9D1L1vunvv/9WO8acOXNEAwMDtf2nTJmi8v2BKCq+/1L1nislJUWcPHmyaGRkpHZ8QRDEIUOGiPHx8To/ftn5Vb2P2LRpkwhAbNq0qXjgwAGxaNGiamPo37+/mJqaqvP5cyu7508f4yYlJWlse/fuXem9irovAwMD8ZdfflH7OshNfB9fA2iyYcMGja8lc3NzccOGDVqPFxMTIxYpUkTq7+TkpNVjzM3PzdPTU+frDQ8PD6VxHjx4IFaoUEFtn8qVK4uPHj3SKTZdXjd5/budH7i8iApM06ZNERYWhhkzZkgFRbVhYGCADh064Pr165g9e7ZCQdOcqFixIkqWLKnyWKNGjbTKXmtib2+Py5cvY926dTkqTOrk5IRVq1bh6tWrWs9ekF9Kk9siurIitdqOM378eAQFBWHkyJFo0KABzM3N4ejoiFatWmHmzJmIiIjAzz//rHJGiizuj3feiY2NxZMnT1TGIV9EV5taLZrayM5fpEgRpVk98kV05WN79+6dzkV0a9eurVTka9q0adi9ezeaNWsGOzs7GBoawsbGBi1btsTSpUvx6NEjdOrUCZMnT4aLiwuMjIxQuXJlabqqpudIE/lPkWrXro2BAwdq3ZeIiL4cxsbGOHjwIE6dOoWuXbvC1dUVRYsWRbFixVC3bl389NNPCA8P17ixwfTp03Ht2jX06tULlStXhomJCcqVK4f+/fvjwoULWLBgQY6XJxgbG2PhwoW4c+cOxowZg+bNm8POzg7FixdHo0aNMHToUFy7dg1//PFHnhZo7dKlCwIDAzF06FA4OjrCyMhIWjp/4MABbN++Xad6NZ8TV1dX3Lp1CwsWLEDHjh1RtWpVFC1aFE5OTmjbti2mTJmC0NBQ/PTTTwVe72bYsGG4d+8exo8fj6pVq8Lc3Fx6LU2YMAFhYWEYNmyY1uOVKFFC2i4ayPulRUDWrqn6ULlyZdy8eROzZs1CzZo1YWFhAQsLC9SuXRtz5sxBYGAgypcvr5dzqVJYfrdzQxBFFUUjiPLZu3fvcOrUKRw5cgSBgYF4/fq19IeiePHisLW1Rd26deHu7o6uXbvC0dEx2zE9PT1x7tw5pfvPnDkjXajK9OjRA/v27VNqO2PGDGlKn4z8ND952kz5E0URV65cwfHjx3Hz5k3cvXsX8fHxSEhIgCiKKFasGIoXLw5XV1fUrVsXbdq0QZMmTXKdWCJS59KlS2jWrBkA4Pjx4wpvCIiIiOjz0rx5c7Rv317nujlUsPhz+7Qx6UJE9IXKyMiAu7s7AgMD0aZNGxw/frygQyIiIqI8VL16dUybNk2hqC8Vfvy5fdpYSJeI6Au1fv16BAYGQhAElRXpiYiI6POQlpaGU6dO4enTpwrbeVPhxp/b54FJFyKiL9CtW7cwefJkAMDQoUM17kxFREREn7b58+dj165d+Pvvv2FnZ1fQ4ZCW+HP7PHB5ERHRF+L06dMICAhAVFQUdu7ciejoaJQpUwZ37tyBtbV1QYdHRERERPTZ4UwXIqIvxPr16+Hv7y99X6JECRw4cIAJFyIiIiKiPMItUYiIvhDp6ekwMzNDuXLlMHz4cAQEBKB+/foFHRYRERER0WeLy4uIiIiIiIiIiPIAZ7oQEREREREREeUB1nShPGNubo7k5GQYGhqiZMmSBR0OERERERERfeZevXqFjIwMmJqa4sOHDwUdDpcXUd4xNDREZmZmQYdBREREREREXxgDAwNkZGQUdBic6UJ5R5Z0MTAwQOnSpQs6HAXR0dEoVapUQYehgDFpp7DFJIoinj9/jjJlykAQhIIOR0Fhe64AxqStwhYTX+e6YUzaKWwx8XWuG8akncIWE1/numFM2ilsMb148QKZmZkwNDQs6FAAcKYL5SEHBwfpj3pUVFRBh6OgWrVquHv3bkGHoYAxaaewxZSQkAArKyu8ffsWxYoVK+hwFBS25wpgTNoqbDHxda4bxqSdwhYTX+e6YUzaKWwx8XWuG8akncIWU2G7DmUhXSIiIiIiIiKiPJBvy4sOHTqEy5cvw9DQEE2aNEGrVq1gamqaX6cnIiIiIiIiIspXeku6nDlzBps3b8bdu3dx/fp16X5RFNGvXz/s2bNHob2bmxsOHjwIe3t7fYVARERERERERFRo6CXp4ufnh1mzZgGAUrGaP/74A7t371bqExAQgHbt2iEoKEgfIRARERERERERFSq5rukSFBQEPz8/AFmzWlxcXBSOL168GABgb2+PK1eu4PHjx/Dx8QEABAcH4/Dhw7kNgYiIiIiIiIio0Ml10mXBggUAsma4nDx5EsHBwdKx0NBQ3L17F4IgYMyYMXB3d4eTkxM2bNgAJycnAMCmTZtyGwKRzsaOHVvQIShhTNopjDEVVoXxuWJM2imMMRVWhfG5YkzaKYwxFVaF8bliTNopjDEVVoXxuWJM2imMMRUmud4yuk6dOggODkbfvn3x119/KRxbtmwZJk6cCEEQ8OzZM5QpU0Y6NnHiRCxbtgy1a9fGzZs3cxMCFVKFbasuorxQmLdeJNIXvs7pS8DXOX0J+DqnL0Fhuw7N9UyXR48eAQBq1aqldOzChQsAABcXF4WECwCULVsWABAREZHbEIiIiIiIiIiICp1cJ12KFi0KAEhLS1O4Py0tDWfPnoUgCGjRooVSv9TUVABAZmZmbkMgIiIiIiIiIip0cp10qVSpEgAgMDBQ4f5Dhw4hNjYWANC+fXulfvfv3wcAlCtXLrchEBEREREREREVOrlOutSvXx+iKOLw4cO4ePEigKzZK8uWLQMAmJqaok2bNgp97t+/j71790IQBDg7O+c2BCIiIiIiIiKiQifXSZfJkyfDyMgImZmZ8PLywldffYVatWrh/PnzEAQB/fr1k5YghYeHY8qUKWjSpAkSExMBAEOHDs1tCEREREREREREhU6uky7lypXD/PnzAWTVaTl79ixCQ0MBANbW1vj111+ltqdOncLvv/+O+Ph4AICbmxu6d++e2xCIiIiIiIiIiAqdIvoYZMKECahatSqWL1+Oa9euwdDQEO7u7liyZAns7OyU2hsYGKBbt25YtWqVPk5PhdyrV69QrVo1lcfGjh3Lfd2JiIiIiIhIaytXrsTKlStVHnv16lU+R6OZXpIuANC2bVu0bdtWY5sOHTrgzp07qFy5MoyMjPR1aiqkBEEAAJQqVQp3794t4GiI8oaJiQlmzpwJExOTgg6FKM/wdU5fAr7O6UvA1zl9LjR9eF+2bFlERUVJ16MFTRBFUSzoIOjzJHuxOzg4IDIysqDDISIiIiIios9cYbsOzXVNlwoVKqBixYrYunWrTv327NmDChUqqNxOmoiIiIiIiIjoU5fr5UUREREQBAHv3r3TqV9ycjIiIiKQkJCQ2xCIiIiIiIiIiAodnZIuT58+RUREhMpjYWFhOH/+vFbjxMTEYO3atQCAlJQUXUIgIiIiIiIiIvok6JR02bRpE2bNmqVwn6w4zbJly7Bs2TKdTi4IAmrWrKlTHyIiIiIiIiKiT4HOy4v0WXfXysoK8+fP19t4RERERERERESFhU5JFx8fH3h6ekrfi6KIVq1aQRAEjB8/Ht26ddN6LFNTU1SrVg2Wlpa6hEBERERERERE9EnQKeni5OQEJycnlccqV64MDw8PvQRFRERERERERPSpy/XuRTNnzgQAuLu75zoYIiIiIiIiIqLPhd6SLkRERERERERE9H8MCjoAIiIiIiIiIqLPkV6SLhkZGZg1axYaNGgAU1NTGBoaav1VpEiuJ9sQERERERERERU6uc54ZGRkoFWrVrh48SIA/W4pTURERERERET6tW/fPkRFRak9XrVqVXh5eeVjRJ+vXCdd/vjjD1y4cAGCIEAURXh5eaFu3bowMzPTR3xERERE9AnhG3ki0hX/buS/pUuX4ty5c2qPe3t78znXk1wnXbZv3y7d3rdvH7p27ZrbIYmIiIjoE8U38kSkK/7doM9ZrpMu9+/fhyAI6NKlCxMuRERERERERIXc2bNnCzqEL0auky7v378HADRo0CDXwRARERHRp41v5IlIV/y7QZ+zXO9e5OzsDAB49epVbociIiIiIiIiIvps5Drp0rdvX4iiiDNnznDnIiIiIiIiIiKi/y/XSZfx48ejatWquHPnDnx9ffUQEhERERHRl83Z2RmCIMDHx6egQyEqFHx9fSEIAgRBwObNm7Xud/bsWanfp/j7tHnzZin+iIiIAhuDci7XNV2KFSuGY8eOoXv37pg9ezbu3r2LmTNnokaNGvqIj4iIiIgKmaCgIOzfvx8AMHHiRBQvXlyn45QlIiIC5cuXl77nrHH6nPHvBn2pcp10mTRpEgCgUaNGuH//Pv7++2/8/fffsLCwQMWKFbP9ZREEAadOncptGERERET6caRFQUeQMx3O59upgoKC4OfnBwDw8fFRefGk6TjRZ+dcQEFHkDMe9fPtVPy7QV+qXCddlixZAkEQAChm59+9e4egoCC1/QRBgCiKUl8iIiIiIiIios9JrpMuLVq0YOKEiIiIiEhHzs7OXFJERPSZy3XShXuqExEREREREREpy/XuRURERET0ZfDx8YEgCBgyZIh0X/ny5SEIAjw9PbM9rquUlBSsXr0abdu2RaVKlVC0aFFUqFABrVu3xh9//IH09HSN/TMzM+Hv748uXbrAwcEBJiYmcHZ2RuvWrbFt2zakpqaq7SvbPWjFihUAgEuXLqFbt26wt7eHqakpKlasiO+//x7v3r2T+ty6dQsDBgxAmTJlYGJigipVqmDAgAF49OiR2vN4enrm+PnJ6eOT7WRia2sLAEhNTcWKFSvQsGFDFC9eHBYWFqhRowamTp2KFy9e6BwXkbz8/rvxuUtLS8PSpUvh7u4Oa2trmJmZwcXFBd9++y0ePHiQb2OQ9nI904WIiIiISN/u37+PNm3a4OnTpwr3P378GI8fP8bJkyexZMkSXLx4EcWKFVPq/+rVK3Tv3h2XL19WuP/Jkyd48uQJTp48iVmzZuHIkSOoVKmSxljWrl2Lb775BpmZmdJ9jx49woIFC3Dq1ClcvHgRBw4cgLe3t0KiIywsDGFhYdi3bx8CAgJQvXr1nDwVKunr8b169QpdunTB1atXFe4PCQlBSEgI1qxZA39/f7Rv315vsRN9aRISEvDy5UtUqVIlV+O8ffsW/fv3x5UrVxTuf/DgAR48eIB169Zh2bJlGD16dJ6OQbph0oWIiIiItDJo0CDUr18fV65cwfbt2wEAvr6+KFGiBBwcHGBpaanxuLbevXuHrl27SgkXV1dXdOzYESVLlsTz58+xc+dOvHjxAsHBwfj222/x559/KvRPTExEq1atEBISAgDS7I8KFSrg4cOHOHnyJCIiIhAWFobGjRsjICAATk5OKmM5deoUDh48CHNzc3Tr1g2urq64c+cO/P39kZmZicDAQPTq1QsnTpxAWloaOnTogEaNGuHVq1fYunUr3r59i+TkZEyePBnHjh3T+TlXRV+PLyMjA3379sXVq1dhbm4OLy8v1K9fH2FhYTh9+jQiIyORkJCAbt264fLly3Bzc9NL/PRlya+/G4XV/fv30bFjRwiCgMDAQFhaWuZ4rGHDhuHGjRswNzfHV199hQYNGiA8PBxnzpzB06dPkZaWhjFjxsDGxgZ9+vTJszFIN7lOulSoUCFX/QVBwMOHD3MbBhVi0dHRqFatmspjY8eOxdixY/M5IiIiIsoJLy8veHl5wcLCQro48vb2hrOzs0IbTce1cezYMdy/fx8AMHr0aKxcuRIGBv+3Kv6XX36Bu7s7QkND8ddff2HdunUwNTWVjs+YMUNKSEydOhW+vr4Kx5OTk/Hzzz9j4cKFiImJweTJk7Fnzx6Vsezfvx+VKlXCP//8o/Apda9evdCjRw8AwJEjR2BiYoIDBw6gS5cuUpvJkyejZs2aeP/+PS5cuKC3nTv19fji4+Nx9uxZODo64tixYwrv196/f4/Bgwdj3759SE1NxejRo3Ht2jVuoEE6y6+/G4WVvb09MjMz8fjxY4wdO1YpSayLGzduoFy5cjhy5IjCzLnk5GQMHz5cev7Gjh2LTp06wczMLE/GKAxWrlyJlStXqjwWHR2dz9FoluuaLhEREVp/PXnyROX99HkrVaoU7t69q/KLCRciIiL62LVr16Tb06ZNU0i4AICFhQW8vb1haGgIAAgNDZWOxcfHY/Xq1QCAnj17Yt68eQoJCQAwNTXF/Pnz0b17dwDA3r17NX4IuHHjRqVlAd27d0eNGjWk73/44QeFhAuQNQPF29sbQNbslJcvX2p+4FrIi8d36NAhpQ/ILCwssGfPHtSsWRMAEBAQoLQcgaigDBkyBIIgaPXVsmXLAo3VysoKO3bsQJEiRbB161Zs3bo1V+MdOnRIaamiqakptm7dCg8PDwBATEwM/P3983SMgjZ27Fi115ilSpUq6PAU5Drp4u3tne1X9+7dUatWLekfgiAIGD58ONavX49169bl+kEQERER0edDlkwBgKioKJVtpk6divT0dKSnp6Nu3brS/UePHkViYiIAYMqUKWpnZgiCgEmTJknfX7hwQWW7qlWrokWLFiqPubq6SrdHjRqlso18MiMlJUVlG13o+/G1b98etWvXVnnMwMAAP/74o/T9wYMHcxo20RetYcOGmDNnDgBgzJgxOS5W26lTJ9SqVUvlMUEQMHPmTOl7dcsZ9TEG6SbXy4s2bdqkddt3795hyZIlWLBgAbZu3YqOHTuia9euuQ2BiIiIiD4j7u7u0u0ePXpgwoQJ8PHxQenSpbPt+99//0m3r1y5goCAALVtZckLAAgODlbZRlPxW9m0+xIlSsDe3l5jG33R9+OTLZFSR/69uqZzEeWngQMHolGjRlq1DQsLw7Jly/I4ouxNmTIFJ06cwMmTJ9GvXz/8999/MDEx0WmMbt26aTzu6ekJa2trxMXF4caNG3k2BukmXwvpWlpa4ueff4abmxs6d+6Mr7/+Gjdu3EDlypXzMwwiIiIiKsS6d++Orl274sCBA4iOjsb06dPx888/o3HjxmjevDk8PDzQsmVLGBsbK/WNjIyUbn/33XdanzMhIUHl/RYWFtn21aaNvuj78ZUvX15jP1NTU5QpUwbPnz/H8+fPtT4fUV7y8vKCj4+PVm3Pnj1bKJIuBgYG+PPPP1G7dm3cvHkT06ZNw+LFi3UaI7vfV0EQULFiRQQEBOD169d5NgbpJtfLi3KiQ4cO6NevH96/f6/zC42IiIiIPm+CIGDv3r1YvXo1HB0dAWTttHPx4kXMmzcP7dq1Q6lSpTB69GjExMQo9FWXXMhOTvvlN30/vjJlymTbt2zZsgCytpol+tJUrVpV6/ox2X2VKVNGSmQsWbIE//zzj06xaDPbT9YmKSkpz8Yg3RRI0gUAmjdvDoDrxIiIiIhImaGhIUaPHo0nT54gICAAM2bMgIeHhzQdPz4+HmvXroWrqyseP34s9ZMt5zExMUFGRgZEUdTqa+fOnQXyOHWl78cXGxub7TllBYDzc0YP0ZcgPj5ep/avXr3Kto2sDpa1tXWejUG6ydflRfKKFi0KAHqp4k5EREREnydBEODm5gY3NzcAWdua7t+/HytWrMClS5cQExODSZMmYd++fQAg7VqRkpKCyMhIlCtXrsBizwv6fnwRERFo1qyZ2uMpKSl49uwZAKBkyZK5OhfRp+jChQvIyMjQy1jx8fFo0aIFXr9+DW9vbwwcOFCn/o8fP5Z2F1JFFEWEh4cDgNq/DfoYg3RTYEkXWQV1W1vbggqBiIiIiAqhLVu2ICkpCWXLlkWnTp0UjpmamqJfv37o3bs3ateujZCQEFy+fFk67u7ujg0bNgAAbty4ofGi4d69e9KWqF9//TUqVqyYB49Gv/T9+E6dOoVBgwapHePo0aMQRREA0KBBg9yETvRJsrOz08s4oihi/PjxeP36NSpXrowVK1boPMahQ4c01rI5ceKEtJRQXaFhfYxBuimQ5UV///03Nm3aBEEQ4OLiUhAhEBEREVEhtWLFCowZMwY+Pj5qP2E2NDSUPryT32K6Xbt2MDDIeos7c+ZMpKenqz3Pzz//DD8/PyxcuFDt7kOFjb4f37Zt2xAREaHyWGZmJvz8/KTvO3bsmPPAib5wGzZswO7du2FsbIydO3fmaLne33//jZCQEJXHMjMz4evrK33fp0+fPBuDdJPrmS5Dhw7Vum1KSgpCQ0Nx69YtiKIIQRAwevTo3IZARERERAUkJiYGzs7OOT6uiqurKwICAhAbG4uFCxdi6tSpSm3+/fdfXLp0CQDQpEkT6X5HR0f06dMH/v7+CA4OxogRI7B8+XKFCxxRFPH7779jz549AIDevXvD3NxcpxgLir4fX3p6Orp06YJDhw7ByclJuv/Dhw/w9vZGUFAQAKBWrVpo2bJl3j0w+qLkxd+Nwuzu3buYMGECAGD+/PmoW7dujsfq1KkTjhw5AldXV+m+xMREDBkyRNpSvkGDBlIN1bwag7SX66TL5s2bIQiCTn1kUxT79OmDnj175jYEIiIiIspHpqam0m0/Pz8MGDAAVlZW6NChg1bHs9OnTx9s3boVADBt2jQcOnQILVu2hLW1Nd68eYMrV67g1KlTAAAjIyPpYkZmyZIlOHv2LF6+fInNmzfj1KlT8PLygouLC+Li4nD06FHcvn0bAFCpUiUsXLgw509GAdDn47O1tUVwcDDq1KmDtm3bombNmggLC8Pp06elWi5GRkbYsGGD0nv+zZs3Y8iQIQAADw8PnD17Nm8eMH0W8vrvRmGVnJyMfv36ISkpCZ06dcL48eNzNI6NjQ1KlSqF0NBQuLu7w8vLC25ubnj48CFOnTol/b6amZmp/H3V1xiku1wnXcqVK6fTD8PY2BjVq1dH586dpT/SRERERPTpaNCgAYoUKYL09HQcPnwYhw8fhoeHh3RxlN3x7HTs2BHTp0/Hr7/+iszMTFy6dEma1SLPwsICa9euVfo0tlSpUjh37hw6deqEsLAwPHv2DJs2bVLqX6tWLezatQslSpTIwbNQcPT5+Pbs2YMRI0YgLCwMO3fuVNrlqFixYvD392c9F8q1vP67UViFhYUhOjoaZcqUkUps5ETRokVx4MABtG/fHg8fPsT+/fuxf/9+hTa2trbYs2cPatWqlWdjkO5ynXRRtwaUiIiIiD5PFStWxM6dO+Hr64uwsDBYWFigQoUKWh/PjiAImDNnDgYPHoyFCxfi1q1bePr0KeLj4+Hg4AAnJye0atUKY8eOVbulaZUqVRAcHIxNmzZh9+7dCA4Oxtu3b1GuXDm4uLigT58+GDhwoEI9mE+Jvh6fk5MTgoKCsGTJEuzcuROPHj1CRkYGnJ2d0alTJ0yaNOmTqXdDhVte/90orGrWrIlbt24hMjIy15vIVK5cGYGBgViyZAl2796Nx48fQxAEVKhQAd26dcP48eOzTSLrYwzSjSDK1voQ6VnZsmURFRUFBwcHREZGFnQ4RERERATFZUGPHz/+rGpnEBEVtuvQAtm9iIiIiIiIiIjoc5fr5UUfe/nyJY4fP46AgAC8fPkSb9++hYWFBUqWLIkGDRqgbdu2KFu2rL5PS0RERERERERUqOgt6fLq1St899132L17NzIyMlS2Wb9+PQwMDNC7d28sWbIEJUuW1NfpiYiIiIiIiIgKFb0sL7p37x5q1qwJf39/pKenQxRF6cvS0lLh+4yMDOzcuRO1a9dGWFiYPk5PRERERERERFTo5DrpkpKSgk6dOuH169cQRREODg5YtGgRQkJC8P79e8THxyMpKQmhoaFYunQpypYtC1EUER0djU6dOiE1NVUfj0Mvjhw5gi5duqBs2bIwMTGBk5MT+vfvj4sXL3KMHI5BRERERERE9MUSc2nlypWiIAiigYGB2KFDBzE1NVVj+5SUFLFdu3ZSn1WrVuU2BLUyMzPFPn36iADEvn37qm2Xnp4ujhgxQgSg9mvGjBkaz8UxlDk4OIgARAcHh2zbEhEREVH+2LRpk/Se7vHjxwUdDhGRXhW269Bcbxnt5eWF06dPw8HBAXfv3oWlpWW2fd6+fYtq1arh5cuX8PT0xKlTp3ITglobN27E8OHDAQB9+/aFv7+/ynY///wzZs+eDQAoVqwYBg0aBCcnJ9y9exf+/v5ISUkBAKxbtw4jRozgGFqMARS+rbqIiIiIiIjo81borkNzm7Wxt7cXDQwMxK+//lqnfl9//bUoCIJYqlSp3Iag0r1790QzMzMpi69upkt4eLhoYGAgAhDLlSunlO0PCAgQLS0tRQBisWLFxPj4eI6RzRgyhS3DSERERERERJ+3wnYdmuuaLm/evAEAVKtWTad+rq6uAIC4uLjchqAkJSUF/fr1Q2JiYrZtFy9ejMzMTADAihUr4OzsrHDczc0Nv/zyCwAgISEBGzZs4BjZjEFEREREREREeiika21tDQC4e/euTv3u3bun0F+fpk2bhqCgIBQvXlxjO1EUsX//fgBA8eLF0b59e5Xt+vfvL90+ePAgx9AwBhERERERERFlyXXSpXr16hBFEadPn0ZCQoJWfRISEnD69GkIgqDzDJnsHD16FEuWLAEArF+/XmPbBw8eICoqCgDQpk0bFClSRGW7kiVLokGDBgCAy5cv48OHDxxDzRhERERERERElCXXSZcePXoAAF68eIH+/fsjLS1NY/v09HQMHDhQuriX9deHly9fwtvbGwAwfPhw9OrVS2P7p0+fSrdbtmypsa3seHp6OsLDwzmGmjGIiIiIiIiIKEuuky7Dhw9HhQoVAADHjh1DpUqVsGLFCoSFhUm73KSkpCAsLAwrVqxApUqVcOTIEQCAs7Ozxt1vdJGZmQlvb2+8fv0aVapUkWa7aBIdHS3dLlWqlMa2JUuWlG7LJxk4Bph0ISIiIiIiIlJB9foRHZiYmODw4cNo0aIFYmJiEBkZiQkTJkjHrays8PbtW4U+oijC1tYWhw8fhomJSW5DAAD8/vvv+Pfff2FkZIQdO3bA3Nw82z7ySYbsasvY2NhIt1+9esUx1IxBRERERERERFlynXQBgKpVqyI4OBgTJ07Enj17kJGRIR2Lj49XaGtgYICePXti6dKlKF26tD5Ojxs3bmD69OkAgHnz5qFevXpa9ZNPMmRXdFc+CSG/KxLHQLa7RImiqHW9H1VMTEz0lpwjIiIiIiKiwislJUVaNZMToijqMZrc00vSBchajrJjxw4sXLgQx44dw/Xr1xEdHY3379/DwsJCKr7arl07lC1bVl+nxbt376RaMq1bt8Z3332ndV/ZdtcAsp0ZI39cPsnAMbJPujx//hxWVlYa22gyc+ZM+Pr65rg/ERERERERfRrmzZsHPz+/gg5Db/SWdJFxcHDAsGHDMGzYMH0PrdK4ceMQFhYGW1tbbNmyBQYG2pepMTY2lm6/f/9eY1v5JVLysy44BrKdhVKmTBmEhoZqbKMJZ7kQERERERF9GX744QdMmjQpx/1dXV3x/PlzPUaUO7lOukRGRsLe3l7t9sJnzpzBrl27ULt2bbRr1w7Ozs65PaVkx44d2LJlCwBg06ZNOi9XMjMzk27HxcVpbCt/XH6WB8fIflaMIAgoVqyYxjZEREREREREuS0vIQiCHqPJvRztXhQZGYl58+bB3d0dzs7OGut1PH/+HGvXrsXYsWNRsWJFNG3aFCdPnsxxwDJxcXEYPXo0AGDs2LHo1KmTzmPY2toqjKeJfG0a+SKyHENxDCIiIiIiIiLKonPSZfny5ahatSp++uknBAQEaF2kRhRFiKKIK1euoG3bthg5ciTS09N1Dljm7du3UrJn5cqVEARB5ZfMzp07pftks20qV64sHX/x4oXG8718+VK6XaVKFek2x1Acg4iIiIiIiIiy6JR0+fHHHzFx4kQkJSVJyZZ69eppnPrTpk0brFq1Cr1790aJEiWk5MvGjRsxdOjQ3EWfS9WqVZNunzlzRmPb06dPA8jafUk+ycAxDJh0ISIiIiIiIlJBELWcqnLixAm0bdtW+n7MmDGYMmUKypcvr/XJkpKSMHv2bCxcuBBpaWkQBAH+/v7o3bu3zoEnJCTgzz//zLbduHHjAAB169aVkjyWlpbw9vaGKIpwdHREVFQUihUrhpiYGBgZGSmNER0dDXt7ewBA06ZNcfHiRekYx1AcQ17ZsmURFRUFBwcHREZGqmxDREREREREpC+F7TpU65kusi17BUHA9u3bsXLlSp0SLgBQtGhRzJkzB0eOHJHumzt3rk5jyBQrVgzffvtttl8yVapUke7z9vaWHkvXrl0BZCVx/vnnH5Xn8vf3l25369ZN4RjH6KayDREREREREdGXTquZLk+ePEH58uUhCAK6d++OPXv25PrEY8aMwdq1ayEIAh49egQnJ6dcj6mKrK5L3759FZIFMg8fPkSVKlWQmZmJcuXK4cKFCyhXrpx0PDAwEC1btkRCQgKKFy+OJ0+eKO3EwzFU70xU2DKMRERERET5IS0tDUeOHEFcXBw6dOiAkiVLKrUJDAxEQEAA6tevj3r16ikdf/XqFY4cOQJra2t06NBBaQa6Ps5Bmu3fvx9BQUEoXrw4Jk6cWNDhkJYK23WoVltGX7lyRbqdm/2y5Q0ZMgRr166Vxs+rpEt2KlasiOnTp2P27Nl4+vQpateujcGDB6Ns2bIICQmBv78/UlJSAACLFy9WmWDgGERERERZ9u3bh6ioKLXHq1atCi8vr3yMiCh/fSoJl1evXqnsR/9n//792LJlC5ycnJh0oZwTtbB48WJREATRwMBAjI2N1aZLtuLj46Uxly5dqpcxVQEgAhD79u2rtk16ero4dOhQqe3HX4IgiHPmzNF4Ho6hzMHBQQQgOjg4ZNuWiIiIPg8eHh5q30MAEL29vQs6RKI8k5qaKu7fv1/ctGmTGB0drbLNjRs3xLVr14o3btxQeTw6OlrctGmTuH//fjE1NTVPz0GaeXt7iwBEJyengg6FdFDYrkO1qumSnJwMIKsmi42NTQ5SO8qsrKxgbm4OAPjw4YNexswpQ0NDbNy4EYcPH0anTp1QunRpGBsbw9HREf3798elS5cwffp0jqHDGEREREREX5JPaYaL7BxElPe0Wl5UpkwZAFm7D6WmpsLY2DjXJ05KSsKHDx8gCALs7OxyPZ46onabMwEAOnbsiI4dO+bqfByDiIiIvmRnz54t6BCI8t2nmHDp0KFDLh4xEWlLq5ku8oVUAwIC9HLi//77T7rt4OCglzGJiIiIiIjy26eYcPn4HHktJSUFq1evRtu2bVGpUiUULVoUFSpUQOvWrfHHH38gPT1doX1iYiLMzMwgCALatWunceznz5/DwMAAgiCgX79+SsdDQkIwbNgwNGjQADY2NrC2tkb9+vUxfPhwhIeHK7V3dnaGIAjYsmULgKyNZQRBgCAI0q6++iI7l4+Pj8Z2Pj4+EAQBzs7OSsc8PT0hCIJUd+bt27eYPXs2atSoAQsLC9jb28PDwwPr1q1Tep4/lpiYiN9//x1NmzaFra0tzM3NUadOHQwcOBBBQUE5e5BfOK1mujRp0gRWVlZISEjAmjVr0KRJk1yfeP369QAAY2NjNGvWLNfjERERERERFQQmXDS7f/8+2rRpg6dPnyrc//jxYzx+/BgnT57EkiVLcPHiRWmjDjMzM7Rt2xb79+/H6dOnkZCQoHYTj71790orHPr3769w7Pvvv8fChQuVVkDcuHEDN27cwJYtW7Bq1SqMGDFCXw+3QD158gTt27dHaGiodN+HDx8QHR2N8+fPY+vWrTh9+rTK18CdO3fQuXNnREREKNx/69Yt3Lp1Czt27MB3332HhQsXSrsEU/a0mulibGyMXr16QRRFbN++HYcOHcrVSY8cOYKdO3dKWUtLS8tcjUdEREREXyZfX1/pE2hdaPvpMpE2mHBR7927d+jatauUcHF1dcWUKVMwf/58TJw4EaVLlwYABAcH49tvv1Xo2717dwBZz8OxY8fUnmP37t0AsuqGys+K2bBhAxYsWABRFGFsbIx+/fph9uzZ8PPzQ6dOnQAA6enpGDduHEJCQqR+fn5+WL58Odzd3QEA1tbWWL58OZYvX16ol2Wlpqaie/fuCA0NRY0aNTBu3Dj88ssv6NKli9Tm4sWLmDNnjlLfyMhIeHp6SgkXV1dXjBkzBnPmzEG/fv1gaGgIURTx+++/488//8yvh/R50LbiblRUlFi8eHHRwMBANDExEbdu3Zqjyr0HDx4UzczMREEQRCMjI/H27ds5GocKv8JWNZqIiIj04+bNm+LMmTPFmTNninFxcTof16eZM2dKOyPJe/z4scKuSR9zcnIq9Lsp5efzSPpXmHYpUneO/LBr1y7p93D06NFiRkaGwvF3796Jrq6uIgDR0NBQTEpKko7FxsaKhoaGIgBxwIABKsePiooSBUEQAYhDhw5VOFatWjURgFi8eHExJCREqe8ff/whxfbTTz8pHc+P3Yu0/VukKRbZrnFmZmYiAPHHH38U09PTFdrs27dPeqz16tVTGqNLly7S8W+//Vapf1BQkGhpaSkCEC0sLMTk5GSdH2t+KWzXoVrNdAGyiumuXLkSQFam0dvbG15eXjhx4gQyMzOz7X/jxg0MGDAA3bp1Q1JSEgRBwPTp01GzZk1tQyAiIiKiQiAoKAh+fn7w8/NDfHy8zsdJO3weP12fwgyXtLS0XD5K7Vy7dk26PW3aNBgYKF6CWlhYwNvbG4aGhgCgsCzGxsYGnp6eALJWS6iKWd3Sonfv3kljdevWDdWqVVPqO3jwYFhaWsLQ0BB37tzJ4SMsPBITE9G9e3fMnj1bej5lunXrBi8vLwBZs4rk3b9/HwcPHgQAtGjRAsuWLVPqX7t2bfzyyy8AgPfv3+ut1uuXQKuaLjIDBgxAZmYmhgwZgoyMDJw5cwZnzpxBiRIl0LBhQ9SqVQt2dnawtLRESkoK4uPjERoaiitXruDRo0cA/m83oYkTJ+q9CBERERFRbv1yLfs2hdHP7gUdAREBn07C5ciRI+jatWsuH2325C/eo6Ki4OTkpNRm6tSpmDp1qsr+3bt3x6lTpxAfH4/z58/jq6++Uji+a9cuAEDJkiWlBI3svLJrz6ioKIiiqLQM0dDQEAkJCTl6XIWVpmvsunXr4uTJk0rJq7///lu6PXnyZLXLNXv06IEFCxYAyErcNG3aNPcBfwF0SroAwKBBg1C9enWMHj0a169fBwDExMTgyJEjOHLkiNp+she8ra0tli9fjr59++YwZCIiIiIizZydnZUKZxLltU8p4RIXF5fLR6sdWV0UIOuifcKECfDx8ZFquWSnW7duUq2XAwcOKCRdoqKicOnSJQBAnz59UKTI/13empmZoWbNmggODsaJEyfQrVs3jB07Fl5eXkqzbT4XFhYWGleSmJmZqbz/ypUr0u02bdqo7e/o6IjIyMicB/iFytGrrW7durhy5QqOHTuGPn36wNzcHKIoavyqU6cOli9fjvDwcCZciIiIiIjos/KpJVzyqyBs9+7dpRk10dHRmD59OhwdHdG8eXNMnz4dx48fR2pqqtr+Dg4OUuLm4MGDCslUTbsWAcDatWthYmIi9W3bti0cHR0xaNAgrF69WmmXnk9dxYoVc7SrkCyRYmdnB1NTU32H9cXLcYpPEAS0adMG/v7+ePv2LW7fvo3t27dj+fLl+OWXXzB//nysX78ex48fR1xcHAIDAzF27Fi123wRERERUeHm4+MDQRAwZMgQ6b7y5ctDEAR4enpmezwnzp07hwEDBsDR0REmJiYoXbo0OnfujH/++Sfbvp6enrk6d2ZmJvz9/dGlSxc4ODjAxMQEzs7OaN26NbZt26b2QnHz5s0QBAG2trYAsnYUWbFiBRo2bIjixYvDwsICNWrUwNSpU/HixQul/ro+jwkJCfj111/RpEkT2NrawtjYGA4ODujcuTP+/PNPZGRkqH2Msl2clixZAgB48eIFpk6dChcXF5iZmcHR0RGtW7dWuLglZZ9iwkXVOfKCIAjYu3cvVq9eDUdHRwBARkYGLl68iHnz5qFdu3YoVaoURo8ejZiYGJVjyHYxevLkCW7duiXdL9u1yMnJCY0bN1bq17hxY4SEhKBbt27SLJjnz59j+/bt+Oabb1C+fHm4u7tj3759en3MBaV48eI56vf27VsAWXVcSf90Xl6kioGBAWrUqIEaNWroYzgiIiIi+sJlZmZi/Pjx0kYOMi9fvsThw4dx+PBhjB49Os8uHF+9eoXu3bvj8uXLCvc/efIET548wcmTJzFr1iwcOXIElSpV0jhOly5dcPXqVYX7Q0JCEBISgjVr1sDf3x/t27fPUZwXL15Ez5498erVK4X7nz9/jufPn+Pw4cNYtmwZDh48mO0FVVBQEDp06KCQCIqMjERkZCROnjyJvn37YseOHTn6JP1zx4SLZoaGhhg9ejRGjRqFwMBAHDx4EOfOncOVK1ekWqBr167F3r17ce3aNZQvX16hf/fu3fHDDz8AyFpiVKdOHYWlRf369VP7uqxYsSL27duHuLg4HDlyBP/++y/Onz8vzXK5fv06evTogcmTJ2PhwoV59yTkUl7WnpEtO3rz5k2eneNLppekCxERERF9/gYNGoT69evjypUr2L59O4Csoo0lSpSAg4MDLC0tNR7XxbRp0xQSLo0aNUKzZs0gCALOnz+Pq1evYs2aNTqPq43ExES0atUKISEhACDNbqlQoQIePnyIkydPIiIiAmFhYWjcuDECAgJUFgfNyMhA3759cfXqVZibm8PLywv169dHWFgYTp8+jcjISCQkJKBbt264fPky3NzcAGT/PMuEhISgTZs2SEpKAgBUqFABnp6eqFChAoKCgnD69Gm8efMGN27cQMuWLXHz5k21NR3i4uLQuXNnvHjxAg0bNkTz5s1hbm6OCxcu4PTp0wCAnTt3ol27dvDx8dHbc/25YMJFO4IgwM3NTXqtJycnY//+/VixYgUuXbqEmJgYTJo0SWnmiYuLC1xdXREaGooDBw5g5syZCrOv+vXrl+25ra2tMXDgQAwcOBAA8ODBA6xbtw7r169HQkICFi1ahIEDB6Ju3bp6ftT68fDhwzwbW/aaiIqKQlpamtJriHKHSRciIiIi0oqXlxe8vLxgYWEhJQO8vb3h7Oys0EbTcW0EBQVJnzgbGRlh9erVGDZsmEKblStXYvz48YiKisr5A1JjxowZUsJl6tSp8PX1VahzkJycjJ9//hkLFy5ETEwMJk+ejD179iiNEx8fj7Nnz8LR0RHHjh1T2LL2/fv3GDx4MPbt24fU1FSMHj0a165dgyAIWj3Poihi+PDhUsLF29tboX4FkHUB1a1bNwQEBODBgwf45ZdfMG/ePJWPeeHChdIyqG+++UaaNSCKIpYuXYrvvvsOAHDo0CEmXVRgwkW9LVu2ICkpCWXLlkWnTp0UjpmamqJfv37o3bs3ateujZCQEKXZZTLdu3dHaGgobt68iSdPnkhLi6pWrYratWsrtQ8JCcGFCxcAZBXjtbe3VzhepUoVLFy4EA0aNJCSNleuXCmwpEtKSoraYwkJCQgLC8uzczdo0ACnTp1CZmYmLl26pHZJZmpqKuzs7JCQkIDBgwdjy5YteRbT5+TzLNtMRERERJ+s5cuXS59gz5o1SynhAgBjx47FlClT9H7u+Ph4rF69GgDQs2dPzJs3T6mwpKmpKebPny/Vmdi7d6/GT6EPHTqkkHABsnYZ2bNnj7TTSEBAgMIOItm5evWq1N7d3R2bNm1SSLgAWQVIjx49iqJFiwIA1q1bJyVpPpaYmIhx48Zh7NixCss0BEHAhAkTULlyZQBZ28RS9phw+T8rVqzAmDFj4OPjo7a+kKGhoVQDSX6LaXmy3zcAWLNmDS5evAggq4CuqqVFERERGDNmDMaMGSNtK61KqVKlFOLIb8bGxgCA0NBQtW2WLl2q9ndXHzp27Cjdnjt3rtp2J06ckJY5eXh45Fk8nxsmXYiIiIio0BBFUSqSa2Njg7Fjx6ptO2HCBOmCRV+OHj2KxMREAMCUKVPU1okQBAGTJk2Svpd9ov6x9u3bq/wUHsiqi/jjjz9K3x88eFDrOA8fPizdnj59uto4bW1tMXz4cABZ9RrUJXaMjY0xbdo0lccEQUCdOnUAQOMuM5TlU0m4BAYG5vKRasfV1RUAEBsbq7Zmyr///ivVZ2nSpInKNm5ublIhXvlx1C0tkp0XAH7//Xe8fPlSqU1SUpLC7C91546Li9NYkDo3qlevDgC4deuWyhlzR44cwfz58/Pk3DJNmzZF/fr1AWQlVqZMmaL0eF+8eCH9PTYxMUHr1q3zNKbPCZcXEREREVGhERUVhejoaABAq1atYGlpqbZtmTJl4O7uLn3irQ///fefdPvKlSsICAhQ21aWnAHUzwDp0aOHxvPJttIFoPFcH7t+/bp0u02bNhrbtmvXDsuXL5fO0bJlS6U2VapU0TgTQl0tGFL0KSVcAgICVI6vb3369MHWrVsBZNVqOnToEFq2bAlra2spEXjq1CkAWcsJJ0yYoHIcQRDQrVs3LF++HOnp6QCylnVVqVJFZfvy5cujfv36CAgIwJMnT1CtWjX06tULFSpUgCAIiIiIwN9//y0Voe7YsaPSjDTZLLeEhAR8//33aNiwISpWrCjVpImIiFAo+puTHb46d+6M/fv3S8/VkCFD0Lx5cyQlJeHixYvYsWMHjIyMMGzYMGzcuFHn8bUhCAI2btyIhg0bIjk5GYsWLcKxY8fQokULlCtXDg8fPsSOHTvw4cMHAMCCBQukBJiMs7Mznjx5AgA4c+ZMjneN+xwx6UJEREREhYYs4QJkFYbNjrOzs16TLpGRkdJtWR0TbajbWeTjXVg+ZmpqijJlyki7DWlL9jzZ29tLy4fUkS/yq+rTfiBrhxfKnU8t4SKb2ZDXOnbsiOnTp+PXX3+VaobIZrXIs7CwwNq1a9G8eXO1Y3Xv3l1KIAJZS4vUEQQBf/31F9q1a4dHjx4hLi4O69evV9nWw8MDO3bsgIGB4kKQpk2bYu3atQCyZssAwMyZM6Wkiz4MGTIEx48fx65duyCKIv744w/88ccf0nEzMzNs3boVb968ybOkCwDUqlULx44dQ8+ePREbGyvtsCbP0NAQEyZMwLfffptncXyOmHShPBcdHa2UNZYZO3asxmnDRERE9GWRr1tQunTpbNtntw2yrnK6Lau6ftrEV7ZsWTx//hxv377V+nzv378HoFiPQh35GNSdo3jx4lqfm5R9igmX/JjlAmQlP+bMmYPBgwdj4cKFuHXrFp4+fYr4+Hg4ODjAyckJrVq1wtixY2Ftba1xrObNm6NEiRKIjY0FAPTt21dj+8qVK+PevXv4888/4e/vj6dPnyIyMhKmpqZwcnJClSpVMHr0aHh4eKhcojdo0CA8fvwYGzduxMuXL2FnZ6dUkDe3BEGAv78/evXqhTVr1uD+/fuIiYmBvb092rZti0mTJsHFxQUbNmzQ63lV8fDwQFhYGJYvX44DBw7g4cOHyMjIgIuLC2rUqIFJkyahVq1aeR6HNlauXKmww508+eR9YcCkC+W5UqVK4e7duwUdBhEREX0C5JcTvXjxItv2+n5zLVtGY2JigsTERKVPvnUluzjURDb7xMLCQutxZW21efyy5RO6noO0V7JkSY27OhkZGSksJVOlXr16GhMh+XGOvOTi4qJ2pom2BEGQ6jg1b95caYmLKrKlOaoKcmtzvhkzZmDGjBkqjzs7O+doSZGq8/Tu3Ru9e/dW22b48OFSfaaPnT17Vqvz+Pr6wtfXV2Mba2trjY9ZnYiICJ3a55amD+/Lli2bJzvb5RQL6RIRERFRoSE/K+PRo0fZttf3G33ZzJGUlBSFpUY5lV18KSkpePbsGQDotLuMrO3Lly+RnJysse3jx4+V+hF9ik6dOiUlYzUtLSIqTJh0ISIiIqJCw87OTqpBcvr0abx7905t25iYGIWCsvrg7u4u3b5x44bGtvfu3ZM+OVa3ZbSsQKg6R48elT4pb9CggdZxyrf9999/NbY9ceKEyn5En5rNmzcDyKot0qtXr4INhkhLTLoQERERUaHSuXNnAFlbHK9YsUJtu2XLlinsIKQP7dq1k5YUzZw5U9olRZWff/4Zfn5+WLhwodo6D9u2bVM72yUzMxN+fn7S9x07dtQ6Tvm2c+fOVbvE4fXr11izZg0AwMrKSu2WuESFXWBgIHbu3Akg6/fUzs6ugCMi0g6TLkRERESUYzExMbk6rsqYMWNgaGgIICvxoWrHjk2bNmHevHk6j50dR0dH9OnTB0DWNtAjRoyQitbKiKKIRYsWYc+ePQCA3r17w9zcXOV46enp6NKli7SVqsyHDx/Qp08fBAUFAcjaOUTVVs4yHz+PjRs3lnafuXr1KoYNG4aUlBSFNpGRkWjfvr2UmBo1apTaOIkKoxcvXqBnz57o2bMnPD09kZmZCQCYOnVqAUdGpD0W0iUiIiIinZiamkq3/fz8MGDAAFhZWaFDhw5aHc9OtWrV8MMPP2D27NlIS0vD8OHDsWHDBjRt2hTGxsa4ePEiLly4AABo3749jh49qsdHByxZsgRnz57Fy5cvsXnzZpw6dQpeXl5wcXFBXFwcjh49itu3bwMAKlWqhIULF6ody9bWFsHBwahTpw7atm2LmjVrIiwsDKdPn5ZquRgZGWHDhg1Ku6doeh4FQcDGjRvRsGFDJCcnY9OmTTh//jxatmwJZ2dn3L59GydOnEBcXBwAoGrVqpg5c6ZenyeivJaSkoK///5b4b7Ro0dr3FaaqLBh0oWIiIiIdNKgQQMUKVIE6enpOHz4MA4fPgwPDw8pqZLdcW34+fkhISEBy5YtAwBcuXIFV65cUWgzevRoDBgwQO9Jl1KlSuHcuXPo1KkTwsLC8OzZM2zatEmpXa1atbBr1y6UKFFC7Vh79uzBiBEjEBYWhp07d0rLI2SKFSsGf39/lbVWsnsea9WqhWPHjqFnz56IjY3Fw4cPVdaWcXNzw6FDh6SdmYg+FRYWFvD09ERAQADs7e0xevRoTJgwoaDDItIJlxcRERERkU4qVqyInTt3ombNmjA1NYWtrS0qVKig9XFtGBgYYOnSpbhw4QIGDBiAsmXLwsjICLa2tvDy8sK+ffuwevVqpdkh+lKlShUEBwdj9erVaNWqFezs7GBsbIxKlSqhY8eO2LJlCwIDA+Hi4qJxHCcnJwQFBWHOnDmoVasWLCwsULRoUbi6uuJ///sf7t+/j/bt26vsq83z6OHhgfDwcMyZMwcNGzaEjY0NihQpAnt7e3To0AFbtmzB1atXUbp0ab09N0T5xdbWFmfOnMG7d+8QFhaGyZMno0gRzhugT4sg6mNjcSIVZPujOzg46GXLRSIiovzwy7WCjiBnfnbPvg3lj82bN2PIkCEAsrZrdnZ2LtiAiIi+IIXtOpRpQiIiIiI5TF4QERGRvnB5ERERERERERFRHmDShYiIiIiIiIgoDzDpQkRERERERESUB5h0ISIiIiIiIiLKA0y6EBERERERERHlASZdiIiIiIj0yMfHB6IoQhRFbhdNRPSFY9KFiIiIiIiIiCgPMOlCRERERERERJQHmHQhIiIiIiIiIsoDTLoQEREREREVQi9evICvry9evHhR0KEQUQ4x6UJERERERFQIvXjxAn5+fky6EH3CmHQhIiIiIiIiIsoDTLoQERERERFRnjp79iwEQdD4ZWxsDCcnJ7Rp0wZr167F27dvCzpsolxj0oWIiIiIiIgKXFpaGp4+fYoTJ05g9OjRqFq1Kvbt25en5wwKCoKvry98fX0RHx+fp+eiL1ORgg6AiIiIiIiIvhzu7u74+uuvFe4TRRHx8fEIDw/HP//8g9jYWLx8+RI9evTAunXrMGLEiDyJJSgoCH5+fgAAHx8fFC9ePE/OQ18uJl2IiIiIiIgo37i6uuLbb79VezwlJQVz5szBL7/8AgAYOXIkqlWrhqZNm+ZXiER6w+VFREREREREVGiYmJhg1qxZWLp0qXTfqFGjkJGRUYBREeUMky5ERERERERU6IwbNw7NmzcHAISEhOD48eMFHBGR7ph0ISIiIiIiokJHEAT873//k77ftGmTynb37t3DqFGj0KBBA9jb28PU1BTly5dH8+bN8dtvv+HNmzdKfXx8fCAIAoYMGSLdV758eQiCAE9PT6X2qamp2LRpE1q3bg0XFxeYmZnB1tYWtWvXRr9+/XDu3DmIopj7B02fHdZ0oTwXHR2NatWqqTw2duxYjB07Np8jIiIiIiKiT0GbNm1gZmaGxMREnD17FqIoQhAEAFnFd6dMmYLFixcrJTwiIiIQERGBixcvYvbs2Th37hzq1auXoxhCQkLQvn17PHv2TOH+pKQkxMbG4vbt29i5cycGDRqEP//8U4qP8s7KlSuxcuVKlceio6PzORrNmHShPFeqVCncvXu3oMMgIiIiIqJPjImJCZydnXH37l3ExMTgyZMncHZ2BgDs3LkTv//+u9S2ffv2cHNzQ7FixfDixQscPHgQDx8+xPv379GlSxc8fvwYRkZGAIBBgwahfv36uHLlCrZv3w4A8PX1RYkSJeDg4CCNmZGRgT59+kgJF3t7e/Tq1QuOjo5ITExEcHAwDh48iPT0dGzbtg1NmjTBmDFj8unZ+XJp+vC+bNmyiIqKyueI1GPShYiIiIiIiAqtsmXLSh/iyidd9uzZAwAwMDDAoUOH0KFDB4V+CxcuxKBBg7Bjxw5ERUXhzp07qFu3LgDAy8sLXl5esLCwkJIu3t7e0tgyoaGh0rk9PDxw7NgxmJqaKrQJDAxEs2bNkJSUhGPHjjHpQgpY04WIiIiIiKiQiY6Oxrhx4wBkFZQtbEsm8lPZsmWl23FxcdLt27dvAwBat26tlHABspIxkyZNkr6/c+eOzueWnQMAfv31V6WECwDUq1cPrVq1yvE56PPGmS5ERERElGOZmZkICQnBjRs38Pr1a2RkZMDa2hrVqlWDm5sbzMzMCjpEok+Sj48Prl69CgC4evUqfHx8cPTo0QKOqmDY2dlJt9+/fy/d3rBhAzIzMxWSMh+ztLSUbudky+lmzZrhzJkzAID69etnex5ua00fY9KFiIiIiHSWkZGBlStXYtGiRXj69KnKNkWLFsXAgQPh5+eHMmXK5HOE+uPj44MtW7bAyckJERERBR0OfSGuXbsmXcBnZGTg+vXrBRxRwYmJiZFuyydRWrRoobFfVFQUFi9enKtzlytXDuXKlVN7PC0tDRcuXMCJEydydR76fDHpQkRERCRv1KiCjiBn1q7Nt1O9f/8enTt3xtmzZxXuL1Ik661leno6gKydPTZs2IA9e/bgwIEDKi+QPD09ce7cOQBZ28H6+PjkaeyfqiVLliA+Ph516tRBt27dCjocygfu7u44ceIEMjIyYGhoiAYNGhR0SAUmMjJSul28eHGl46Io4vbt2wgODkZYWBjCwsIQFBSE0NBQvcYRHx+P//77TzrH/fv38d9//ynMviH6GJMuRERERKSTwYMHSwmXYsWKYerUqejZsycqVKgAAwMDREZG4vr165g9ezZu3bqF+Ph4dOnSBcHBwXB0dCzY4D9RS5YswZMnT+Dt7c2kyxdi8+bN6NGjBy5fvoyGDRti8+bNBR1SgZFPusgXuk1NTcWKFSuwaNEiPH/+XKmfoaEh6tevLy3Tyqng4GBMmzYNx48fV7l8qGzZsjAwMFA764++bEy6EBEREZHWzpw5g3379gEAbGxsEBAQgPLlyyu0cXJygpOTE3r06IGRI0di48aNePv2LXx9fbFx48aCCJvok1OqVCksX74cbm5uWL58OUqVKlXQIRWI1NRUaVmfnZ2dtNRHtpXzgQMHAABGRkZo1qwZ3NzcUKNGDbi6usLV1RWxsbFKf6N0ceHCBbRp0wbJyckAspI+TZs2RZ06daRzODs7Y+jQodiyZUvuHix9lph0ISIiIiKt7dixQ7r9+++/a7yYMTAwwLJly3Dq1ClERERg7969WLNmDYyMjKQ2Hy9RIiKS9++//+LDhw8AsrZsFgQBAKRliwDQsWNHrF+/HqVLl1bqL18PRleZmZkYNWoUkpOTYWJigu3bt6N79+4wMFDeBFgUxRyfhz5v3DKaiIiIiLR28+ZN6fZXX32VbXszMzO0bNkSAPD27Vs8fvw4z2Ijos+LKIqYP3++9P2QIUOk24cOHZJub926VWXCBQDu37+f4/M/evRIqgszZswY9OzZU2XCJbfnoc8bky5EREREpLWEhATptomJiVZ9evfujWHDhmHYsGEwNDRUOLZ582YIggBBEJR2BvL09IQgCJg4cSKArKTN7NmzUaNGDVhYWMDe3h4eHh5Yt26dVLxXnZcvX2Lq1KmoVq0azMzMYGtrizZt2uDgwYMAsmbcyOK4d++eVo9LXmZmJvz9/dGlSxc4ODjAxMQEzs7OaN26NbZt24bU1FSdx4yIiJBievLkCQBgy5Yt0n2cJUSfuxUrVuDChQsAgOrVq6Nt27bSsbi4OACAqakpihUrprK/KIr4888/c3x+2TkAoGTJkmrb3b1794veXYo0Y9KFiIiIiLQmv3Xqtm3btOrTvn17bNiwARs2bEDFihVzdN4nT56gcePG+PnnnxESEoIPHz4gOjoa58+fx6hRo9CyZUukpaWp7Hvs2DG4urpi/vz5CA0NRVJSEmJjY3HixAl07doV48aNy9XSgFevXqF58+bo378/Dh06hOfPnyM1NRVPnjzByZMn8fXXX6NGjRoIDw/P8TmIviQpKSnw9fXFhAkTAACCIGDdunUKSVtXV1cAQHJyMvbv3680RkJCAiZOnKiwJPLly5caz/vxUiQXFxfp9t69e5GSkqLU5/Lly2jdujUyMzMBZCVqVLWjLxdruhARERGR1ho1aoSTJ08CAL7//nvExcVh8uTJsLKyyrNzpqamonv37ggNDUWNGjXQsmVLlCxZEtevX5dmqly8eBFz5syBr6+vQt+AgAB069ZNugiqW7cuWrRoAQsLC1y+fBlnzpzBihUr8PDhwxzFlpiYiFatWiEkJAQApNktFSpUwMOHD3Hy5ElEREQgLCwMjRs3RkBAAJycnLQa28bGBsuXLwcAzJgxA3FxcXB3d8fXX38NAKhcuXKOYiYqaKGhoVixYoXCfaIoIiEhAeHh4Th8+LBCAmTt2rVo0qSJQvtOnTph0aJFAIB+/fqhe/fuqFOnDjIzMxEWFoaDBw8iPj4e9vb2eP36NTIyMrB48WK8e/cO3t7eqFKlCoCsmTIyfn5+GDBgAKysrNChQwcUK1YMLVu2xJkzZ3Djxg1Ur14dPXr0QMmSJfH8+XNcu3YNly5dApC1g1FkZCQSEhLQs2dP9O7dG97e3nny/NGnRRBZ8YfySNmyZREVFQUHBweFbd6IiIgKtVGjCjqCnFm7Nl9O8+bNG1SsWBHx8fHSfcbGxmjfvj06duyINm3aaJ1UALKWF8nqNDx+/FhhO1hPT0+cO3cOZmZmSExMxI8//gg/Pz+FT7v379+P7t27AwDq1auHGzduSMcyMzNRr1493Lp1CwAwe/ZsTJ8+XSrECQC7d+/GoEGDFJb/hIaGomrVqtL3Pj4+2LJlC5ycnJSWQE2ZMkW68Js6dSp8fX0VLuKSk5Px888/Y+HChQCAnj17Ys+ePVo/PzLOzs7SltFf8tbBX5rAwEC4ubnhxo0bqFevXkGHkytnz56V6jtpy97eHitWrEDPnj1VHp8+fTrmzZuntr+bmxv27NmDSZMmSbuuAcC+ffukrdcfPnyIqlWrKixR9PDwkJbvPX36FO7u7oiOjlZ5DhMTE8yePRutWrVCgwYNpBkvtWvXRlBQkA6PlvSlsF2HcnkREREREWnNxsYGZ86cQdmyZaX7UlNTceDAAYwcORLOzs6oWrUqJkyYgCNHjiAxMTHX50xMTET37t0xe/ZspZow3bp1g5eXFwAgODhY4dipU6ekhMugQYPw448/KiRcgKx6M35+fjmKKz4+HqtXrwaQlUyZN2+eQsIFyPoUff78+VJiaO/evTmeVUP0uStSpAjKli2Lr776CitXrkRoaKjahAsAzJ07F2fPnkWnTp1QsWJFGBsbw97eHp07d8aOHTtw7do1ODs7Y+3atejSpQvMzc3h6uqqUJ+lYsWK2LlzJ2rWrAlTU1PY2tqiQoUK0vFy5crh/v37+PHHH9GgQQNYW1vD3Nwc1atXx/fff4/79+9jypQpqFevHv788084OjrCxsYGdevWzdPnij4dXF5ERERERDqpU6cO7ty5g+3bt2Pjxo0IDAxUOH7//n3cv38fy5Ytg5WVFYYMGYJJkybB0dExx+f8eNmQvLp16+LkyZNKNV327t0r3f7+++/V9h85ciR++eUXnRNER48elfpMmTJFKaEjIwiCwiftFy5cyHFtG6JPlaenZ55sq+zh4QEPDw+Nbezs7KTtpVXp0aMHevToofa4lZUVZs+ejdmzZ2s8z8CBAzFw4EDNAdMXh0kXIiIiItKZlZUVvvnmG3zzzTd4+fIlTpw4gX///RcnTpxQmIb/9u1bLFmyBNu3b8eBAwfQuHFjnc9lYWGBmjVrqj1uZmam8v4rV64AAEqXLq2xv42NDdzd3XXeDei///5TOFdAQIDatvIJnY9n5BAR0eeLSRciIiIiyhV7e3t8/fXX+Prrr5GZmYng4GDs27cP27Ztk5bSvH79Gm3btsXDhw9hZ2en0/gVK1ZUO4tEk2fPngGAVjVm5Hdl0pZ8rYDvvvtO637y224TEdHnjTVdiIiIiEhvDAwMULt2bfj6+uLBgwdYs2aNNBPl3bt3mDNnjs5jFi9ePEexvH37FgBQqlSpbNuWLl1a5/Fzmjxh0oWI6MvBmS5EREREpJUbN27g+vXrAIBevXrB1tZWY3sDAwOMGjUKpqam8PHxAQCdl/DkhpmZGd69e4dXr15l2/b169c5Gh/I2r0kMTERBgb8PJOIiBTxPwMRERERaeXy5csYM2YMxowZg0uXLmndr3///jA2NgYAPHjwIK/CU2Jvbw8ga8vX7Dx58kTn8WUzaFJSUgrFtqT0+SldujRmzpyZo5lYRFQ4MOlCRERERFqR331IthWzNgwMDFCkSNYEa3Nzc73HpY67uzsAICoqCnfv3lXb7v3797hx40aOxweQbf979+7B19cXvr6+3DKatFa6dGn4+voy6UL0CWPShYiIiIi04unpCUNDQwDAypUrtV6SExwcLO3eU6tWrTyL72Ndu3aVbs+fP19tuw0bNiA+Pl7n8du1ayctKZo5cybS09PVtv3555/h5+eHhQsXSjNwiIjo88ekCxERERFppXjx4ujfvz8A4NWrV/Dx8UFcXJzGPomJiRg+fLj0/aBBg/I0RnndunVD+fLlAQBbtmzBb7/9BlEUFdocOnQIP/30U47Gd3R0RJ8+fQBkJZZGjBiB9+/fK7QRRRGLFi3Cnj17AAC9e/fO1WyfmJiYHPclIqL8x0K6RERERKS1uXPn4vjx43j9+jWOHDmCypUr48cff4SHhwcqVqwIKysrJCYmIioqCkePHsWSJUvw+PFjAEDjxo0xePDgfIvVyMgIGzZsQOvWrZGZmYlp06Zh9+7daN68OSwtLXH16lWcPHkSmZmZGD58ODZs2AAAMDU11focS5YswdmzZ/Hy5Uts3rwZp06dgpeXF1xcXBAXF4ejR4/i9u3bAIBKlSph4cKFOXosspjOnTuHxYsXw97eHi1atICDg0OOxiMiovzBpAsRERERac3R0REnTpxA586d8ezZM8TGxmLSpEnScXNzc3z48EGpX5MmTXDo0CFpeVJ+adWqFbZv344hQ4YgOTkZN27cUKi/YmxsjFWrVsHBwUFKupQsWVLr8UuVKoVz586hU6dOCAsLw7Nnz7Bp0yaldrVq1cKuXbtQokSJHD2Opk2b4v79+3j//r30fJ85c4ZJFyKiQo7Li4iIiIhIJ7Vr10ZwcDCmTp2qtG30xwmX6tWrY/Xq1Th//jxsbGzyM0xJv379cOfOHYwePRpOTk4wNjaGvb09+vXrh6tXr2LYsGF4/vw5AMDCwkLaClpbVapUQXBwMFavXo1WrVrBzs4OxsbGqFSpEjp27IgtW7YgMDAQLi4uOX4MCxYswNdffw07OzuYmpqiQoUKsLS0zPF4RESUPwTx44WtRHpStmxZREVFwcHBgdsoEhERfabS0tJw584dBAUFITY2FsnJybCyskLp0qVRv359ODk5QRCEgg4zW7NmzcLMmTNRsWJFhIeHF3Q4RESUQ4XtOpTLi4iIiIgox4yMjFC3bl3UrVu3oENRcvfuXVy7dg0A0KVLF40zbQIDAwFkLRciIiLSFyZdKM9FR0ejWrVqKo+NHTsWY8eOzeeIiIiI6Evw4sULDBkyBACwfv16hV2U5IWFheHgwYMAgGbNmuVbfERElDMrV67EypUrVR6Ljo7O52g04/IiyjOFbVoXERERfVmSkpJgY2OD5ORkVKpUCVeuXFEqZBsXF4c+ffrg5MmTAIDr16+jfv36BREuERHpQWG7DuVMFyIiIiL6LBUtWhQLFizAuHHjEB4ejnr16mH8+PGoXbs2UlNTERwcjLVr10pbWvfu3ZsJFyIi0ismXYiIiIjoszV27Fg8fPgQS5cuxdOnTzFlyhSV7Zo3by5tGU1ERKQv3DKaiIiIiD5bgiBg8eLFuH37Nry9veHm5gYrKyuYmJigTJky6Ny5M7Zu3YozZ86gWLFiBR0uERF9ZjjThYiIiIg+ezVq1MDmzZsLOgwiIvrCcKYLEREREREREVEeYNKFiIiIiIiIiCgPMOlCRERERERERJQHmHQhIiIiIiIiIsoDTLoQEREREREREeUBJl2IiIiIiIiIiPIAky5ERERERERERHmASRciIiIiIiIiojzApAsRERERERERUR5g0oWIiIiIiIiIKA8w6UJERERERERElAeYdCEiIiIiIiIiygNMuhARERERERER5QEmXYiIiIiIiIiI8gCTLkRERESklevXr0MQBAiCgGLFiiEjI0Nj+wcPHkjtBUHArVu3NLYXRRGlSpWS2p84cUKf4RMREeU7Jl2IiIiISCt169aFpaUlAODdu3cICQnR2P7kyZMK32eXRImIiMCrV68AAEWKFEGTJk1yEa2is2fPSskcZ2dnvY0rb/PmzfD19cXmzZvzZHwiIvr0FCnoAIiIiIgKkxvrCjqCnHEbmffnKFKkCJo1a4ajR48CAP777z/UqlVLbXtVSZcpU6aobX/lyhXpdv369WFubp7LiPPX5s2bce7cOXh4eMDHx6egwyEiokKAM12IiIiISGuenp7S7cuXL6ttl5GRgdOnTyvcd/78eSQnJ6vtI5908fDwyHmQREREhQSTLkRERESkNfmky3///ae23Y0bN/D27VsAQMOGDQEAycnJuHjxoto+eZl08fT0hCiKEEUREREReh2biIhIHSZdiIiIiEhr9erVg4WFBQAgLCwMr1+/VtlOfmnRr7/+Kt3+999/VbZPTk7GzZs3AQAGBgZo2rSpvkImIiIqMEy6EBEREZHWZHVdZORnp8iTJV2qVKkCT09PlC9fHoD6Yro3b95EWloagKzETrFixfQZNgDA2dkZgiBorLcSExMDPz8/NGjQADY2NjA3N0fNmjUxZMgQBAYGquwjK9B77tw5AMC5c+ek+z4uqpuRkQF/f3907NgRVatWRdGiRVGuXDm0bNkSixYtQlJSkr4eLhERFQJMuhARERGRTrJbYpSYmIhLly4BAL766isAQJs2bQAAQUFB0g5F8uTHKah6LocPH0aVKlXg6+uLgIAAxMXFITExEXfu3MHmzZvh5uaGkSNHIj09PUfjv3r1CnXr1kX//v1x5MgR3L9/H8nJyXj27BnOnj2LKVOmoEqVKnj69KmeHxkRERUU7l5ERERERDqRT4qoKqZ78eJFpKamAgC8vLwAAK1bt8batWsBZM2CGTBggEIfXeu5nD17Fi1btoSTk5NearScOnUK3bp1Q0ZGBgCgZcuWqF+/PiwsLBAUFIQjR44gJSUF69evx9u3b7Fz506p7/LlywEAS5cuRXh4OCpVqoQJEyYA+L96Nunp6ejduzeCg4MBAOXKlUP37t3h4OCA169fY9++fQgPD0dkZCQGDx6M06dPw8CAn48SEX3qmHQhIiIiIp24ubnB3NwcHz58wPXr15GWlgYjIyPpuGxpkSAI0qyYVq1awcDAAJmZmThx4oTapIsgCArLl/JDYmIifHx8kJGRARsbG+zcuVNKFsk8ePAA/fv3R2BgIHbt2oWvv/4anTp1AgB8++23AIA9e/YgPDwcDg4O0n0yN2/exPnz5wEAHTt2xL59+xSes7lz56JNmzY4c+YMzp07h8ePH6NixYp5+bCJiCgfMH1OeS46OhrVqlVT+bVy5cqCDo+IiIh0ZGRkJCVGEhMTcfv2bYXjsqSLm5sbbGxsAADW1tZo0KABgKxiuqIoSu2fP3+OZ8+eAQBq164Na2vrPH8M8v766y9ERkYCALZs2aKUcAGyatP8/fffsLKyAgDMnz9fp3Ncu3ZNuv2///1PIeECZNXKGTVqFAwNDWFoaCjNiCEiImUrV65Ue40ZHR1d0OEp4EwXynOlSpXC3bt3CzoMIiIi0iMPDw8cP34cQFY9Fjc3NwBZhWhluxDJ6rnItG7dGlevXsXz588RGhqKatWqAcjbraK1sXv3bgCAi4uLNHtFFScnJ/Tq1QsbN27E1atXkZycDFNTU63OYWhoKN2OiopS2aZv377o27evDpETEX2Zxo4di7Fjx6o8VrZsWbV/ZwsCky5EREREpLOPi+nKltOcOXNGuv/jGSNt2rTB7NmzAWTtYlQYki6iKErnt7S0xIoVKzS2j4uLAwCkpqYiLCwMNWvW1Oo8slk+ADB69GiEhIRg2LBhqFChQg4jJyKiTwGTLkRERESks/r168PMzAyJiYkKxXRlS4tMTEzQtGlThT6NGjWChYUF3r9/j3///VcqNiufdGnevLnSuVQlQsLCwgAACQkJKo87ODige/fu2T6Od+/eISEhAQAQEBCAgICAbPvIyPppw83NDRMmTMDSpUvx7t07zJ07F3PnzkX9+vXRvHlztGjRAq1bt4a5ubnWYxIRUeHHpAsRERER6czIyAhNmzbFiRMnEBERgRcvXqB06dJS0qVp06YoWrSoUh9PT08cPnwY586dQ0pKCgwMDKRER40aNWBra6t0rnHjxqmNIy4uTuVxDw8PrZIuuiROctt38eLFaNq0KWbMmIF79+4B+L9Ez+LFi1G0aFF069YN8+bNg5OTU47jIiKiwoOFdImIiIgoRz5eYvT48WM8evQIgHI9F5k2bdoAAD58+ID//vsPt2/fRlJSEoCCqediZmYm3R4xYgREUdT6q3379jqdSxAE9O7dG3fv3sXdu3cxb948tGnTBhYWFgCApKQk7NixA9WrV1eY/UNERJ8uJl2IiIiIKEc+TrrIZrkAyvVcZFq3bi3dPnHihFb1XFQlPGS1Y5ycnFQeP3v2rFaPwcrKCsbGxgCA8PBwrfrkliAIcHV1xbRp03D8+HHExcXh8OHD6NChA4CshNSYMWPyJRYiIspbXF5ERERERDlSv359FC1aFElJSbh8+TKePn0KICuRUa9ePZV9XFxc4OjoiGfPnuHEiRNwcXGRjrVo0SJf4pZnaGiI+vXr4/Lly7hz5w5SUlJgYmKitr2/vz/u3bsHS0tLTJ48Wevz/P3333j16hWsrKzQv39/hWNFihRBx44d0bFjR7Rv3x7Hjh1DUFAQPnz4wBovRESfOM50ISIiIqIcMTY2lorl3rhxQ5rp0rJlSxQpovqzPUEQpNkuAQEBUp+qVauiVKlS+RC1Mtk20a9fv8ayZcvUtnv9+jWGDh0KPz8/3LlzR6dz7NixA2PGjMGgQYPw5s0bte1kz4H8FtNERPTpYtKFiIiIiHJMtsQoJSVFSiaoq+ciI0u6iKKIly9fAiiYei4yw4cPh6WlJQDAz88P/v7+Sm3evn2L7t27S/VnvL291Y4XExOjdJ+rqysAIDMzEz/99BNEUVRqc/PmTezfvx8AUKdOHc5yISL6DHB5ERERERHlmKpkibp6LjJfffUVBEFQSDwUZNLFzs4OK1asgLe3Nz58+ID+/ftj1apVcHd3h52dHR49eoSdO3fi7du3AIBJkyYp1LORMTU1BQCEhIRg7ty5qFixIurUqQMXFxf06tULs2fPhiiKWL16NS5duoQOHTrA1tYWCQkJCAoKwj///IOMjAwAwP/+9798e/xERJR3mHQhIiIiohxr0KCBVNcFAMqUKaNQp0UVOzs71K1bF4GBgdJ9BZl0AYDBgwcjKSkJEyZMQEpKCi5cuIALFy4otBEEASNHjsT8+fNVjtG0aVMcP34cAPDjjz8CADZt2gQXFxfUqlULK1aswHfffYfU1FTcvn0bt2/fVhrD2NgYc+fORd++ffX8CImIqCBweRERERER5ZiJiQmaNGkifS+bxZId2dbRAFCpUiWUKVNGp/N6enpCFEVERETo1E+TUaNG4d69e5g8eTKqV68OS0tLWFpaws3NDT4+Prh16xbWrFmjtt7K999/j/Hjx6NMmTIwNjZGuXLlYGNjIx3/5ptv8OjRI0yYMAGNGjWCg4OD1K558+b4/vvv8fjxY50K9BIRUeEmiKoWlBLpQdmyZREVFQUHBwdERkYWdDhERET0hXN2dsaTJ0/g7e2NzZs3F3Q4RESUBwrbdShnuhARERERERER5QEmXYiIiIjoi5CamlrQIRAR0ReGSRciIiIi+uy9efMGr169ApBVrJaIiCg/cPciIiIiIvpshYSE4O7du1izZo20HXP16tULOCoiIvpSMOlCRERERJ+tBQsWYMuWLdL3ZcuWxcCBAwswIqL/x96dh0dV3v0f/0wWNtlCIBESI7iARBENAaQgiBU1UwQX1OKatgK1kbZutbU/FNRWn8daW2mqQFvjUuRRawFhEIOKiiJkkR1csBATYJKYQGQLw8z8/qBznElmJiGZfd6v6/JyyDlz399zzuTMzCf3uQ+AeBIzlxft2LFDd911l84991x1795dXbt2VU5Ojn74wx9q+fLlrWrDYrFo0qRJyszMVMeOHXX66adr6tSpWrNmTavroA0AAIDI0blzZ3Xq1Elnn322ZsyYoTVr1qh3797hLgsAEC+cMeDPf/6zMyEhwSnJ539XXnmlc8+ePV6ff/z4cee0adP8Pv+hhx7yWwNtNJeRkeGU5MzIyGhxXQAAAAAA2ivSvoeanE6nMzhxTmgsWbJEV199tfHv8ePHKzc3Vz179tSOHTv0r3/9S4cPH5Yk5ebmau3atUpK8ryqatasWXrsscckSd27d9ctt9yi008/Xdu2bdOiRYvU2NgoSZo/f76mTZvmtQ7aaC7S7o8OAAAAAIhtkfY9NKpDF4fDoezsbH322WeSpFdeeUU//OEPPdbZvXu3Lr/8cn3++eeSpIULF2rq1KnG8p07d2rgwIFyOBzKysrS+++/r/79+xvLy8rKNH78eH377bfq3r27Kioq1KNHD48+aMOzDZdIe7EDAAAAAGJbpH0Pjeo5XT7//HMjcLn++uubBS6SdPrpp6uwsND4d9P5SJ5++mk5HA5J0l/+8hePgEGShg0bpkcffVSS1NDQoL/97W/N+qANAAAAAADQVFSHLl9++aXx+IYbbvC53tixY41LijZt2mT83Ol0avHixZKknj17Ki8vz+vz3UfGLF261GMZbSz1ug4AAAAAAPEuZkKX008/3ed6HTp0UPfu3SVJ9fX1xs8///xzVVVVSZIuv/zyZnO9uKSlpWn48OGSpI8//liHDh2iDR9tAAAAAACAE6I6dLn++utVUlKikpISDRkyxOd6VqtVdXV1kqSzzjrL+HlFRYXxePz48X77ci0/fvy4R9hDG55tAAAAAACAE6I6dMnIyFBubq5yc3PVqVMnr+scPHjQ4w47P/rRj4zHVqvVeJyenu63r7S0NOOxe8hAGyJ0AQAAAADAC+/Xj0SxyspKvfTSS6qrq9Pu3bu1fPly45bRP//5zzVp0iRjXfeQISUlxW+7vXr1Mh5XV1fTho82AAAAAADACTEXunz55Zd68MEHPX6WkJCg559/XrfeeqtMJpPxc/eQoWfPnn7bdQ8hXCEObTRvwxun06mGhga/6/jTsWNHdezYsc3PBwAAAABEh8bGRjU2Nrb5+U6nM4DVtF/MhS7eOBwO3XXXXdq3b5/uv/9+I3hxzfMiSaeccorfNtyXu4cMtNFy6LJnzx716NHD7zr+PPzww5o9e3abnw8AAAAAiA6PP/645syZE+4yAibmQpdLLrlETqdThw4d0s6dO/X222/rd7/7nfbv368HHnhAR48e1UMPPSTpxF2NXA4ePOi33QMHDhiP3Udd0IZaHIXSr18/bd++3e86/jDKBQAAAADiw29+8xvdc889bX7+4MGDtWfPngBW1D4xF7q4nHLKKTr//PN1/vnn6+qrr9bQoUN1+PBhPf744/rZz36m3r17q0uXLsb67reS9sZ9ufsoD9poeVSMyWQybtkNAAAAAIAv7Z1ewn1KkUgQ1Xcvaq2zzjpLBQUFkqSjR4/qnXfekST17t3bWKelkGH//v3GY/dJZGnDsw0AAAAAAHBCVI90+eCDD3T48GF1795d3/ve9/yuO2zYMOPx119/LUk6++yzjZ/t3bvX7/P37dtnPB44cKDxmDY82wAAAAAAACdE9UiXX//618rLy9NNN93U4roJCd9tqmu4UXZ2tvGz9957z+/z3333XaMd95CBNhIIXQAAAAAA8CKqQ5czzzxT0omRK8eOHfO77rZt24zHp512miTpnHPOUUZGhiRp1apVstlsXp9rtVq1YcMGSdKoUaPUrVs3YxlteLYBAAAAAABOiInQxeFw6MUXX/S53qFDh/T8889LOjEyY/z48ZJOjHiZPHmyJKmhoUHLly/3+vxFixYZj6+++mqPZbRxtdd1AAAAAACIdyan0+kMdxFtVVpaquHDh0uS0tPTtWTJEo0cOdJjnfr6es2YMUOvvfaaJOm2227TCy+8YCzfuXOnBg4cKIfDoaysLH344YfKysoylpeXl2v8+PFqaGhQz549tXv37mZ34qEN73cmyszMVFVVlTIyMlRZWel1HQAAAAAAAiXSvodGdegiSddff71ef/11SSdGsUycOFHnnnuuunbtqh07duitt95STU2NJCkrK0vr169Xenq6RxuzZs3SY489Jknq2bOnbrvtNmVmZmrr1q1atGi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\n",
       "text/plain": [
        "<Figure size 1200x1200 with 2 Axes>"
       ]
@@ -291,7 +295,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#datamc.plot_datamc_all()"
+    "datamc.plot_datamc_all(save=False)"
    ]
   },
   {
@@ -305,7 +309,7 @@
     {
      "data": {
       "text/plain": [
-       "<pocket_coffea.utils.plot_utils.PlotManager at 0x7f7f166f83d0>"
+       "<pocket_coffea.utils.plot_utils.PlotManager at 0x7f60d4cda3a0>"
       ]
      },
      "execution_count": 13,
@@ -316,7 +320,7 @@
    "source": [
     "from pocket_coffea.utils.plot_utils import PlotManager\n",
     "\n",
-    "plotter = PlotManager(o[\"variables\"])\n",
+    "plotter = PlotManager(o[\"variables\"], plot_dir=\"plots/\")\n",
     "plotter"
    ]
   },
@@ -331,7 +335,7 @@
     {
      "data": {
       "text/plain": [
-       "<pocket_coffea.utils.plot_utils.SystManager at 0x7f7f166ecd00>"
+       "<pocket_coffea.utils.plot_utils.SystManager at 0x7f60d4cda040>"
       ]
      },
      "execution_count": 14,
@@ -355,33 +359,7 @@
     {
      "data": {
       "text/plain": [
-       "['__class__',\n",
-       " '__delattr__',\n",
-       " '__dict__',\n",
-       " '__dir__',\n",
-       " '__doc__',\n",
-       " '__eq__',\n",
-       " '__format__',\n",
-       " '__ge__',\n",
-       " '__getattribute__',\n",
-       " '__gt__',\n",
-       " '__hash__',\n",
-       " '__init__',\n",
-       " '__init_subclass__',\n",
-       " '__le__',\n",
-       " '__lt__',\n",
-       " '__module__',\n",
-       " '__ne__',\n",
-       " '__new__',\n",
-       " '__reduce__',\n",
-       " '__reduce_ex__',\n",
-       " '__repr__',\n",
-       " '__setattr__',\n",
-       " '__sizeof__',\n",
-       " '__str__',\n",
-       " '__subclasshook__',\n",
-       " '__weakref__',\n",
-       " 'datamc',\n",
+       "['datamc',\n",
        " 'get_syst',\n",
        " 'mcstat',\n",
        " 'syst_dict',\n",
@@ -397,7 +375,7 @@
     }
    ],
    "source": [
-    "dir(syst_manager)"
+    "[d for d in dir(syst_manager) if not d.startswith(\"__\")]"
    ]
   },
   {
@@ -411,28 +389,28 @@
     {
      "data": {
       "text/plain": [
-       "{'JER': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f166ec460>,\n",
-       " 'JES_Total': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f166ecfd0>,\n",
-       " 'pileup': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f166c8550>,\n",
-       " 'sf_btag_cferr1': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f1691f130>,\n",
-       " 'sf_btag_cferr2': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f167383a0>,\n",
-       " 'sf_btag_hf': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f16924310>,\n",
-       " 'sf_btag_hfstats1': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f166ecf40>,\n",
-       " 'sf_btag_hfstats2': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f166b6ee0>,\n",
-       " 'sf_btag_lf': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f166b6eb0>,\n",
-       " 'sf_btag_lfstats1': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f1666cdc0>,\n",
-       " 'sf_btag_lfstats2': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f1666cfd0>,\n",
-       " 'sf_ele_id': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f1666f790>,\n",
-       " 'sf_ele_reco': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f16671fd0>,\n",
-       " 'sf_ele_trigger_era': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f1666ffd0>,\n",
-       " 'sf_ele_trigger_ht': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f16673af0>,\n",
-       " 'sf_ele_trigger_pileup': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f16673160>,\n",
-       " 'sf_ele_trigger_stat': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f16675be0>,\n",
-       " 'sf_jet_puId': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f16675cd0>,\n",
-       " 'sf_mu_id': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f16678df0>,\n",
-       " 'sf_mu_iso': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f16678d00>,\n",
-       " 'sf_mu_trigger': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f1667ae50>,\n",
-       " 'mcstat': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f1667a4c0>}"
+       "{'JER': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4cc0d00>,\n",
+       " 'JES_Total': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4cc09d0>,\n",
+       " 'pileup': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4cc0bb0>,\n",
+       " 'sf_btag_cferr1': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4ccf6d0>,\n",
+       " 'sf_btag_cferr2': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4c8afd0>,\n",
+       " 'sf_btag_hf': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4ccffd0>,\n",
+       " 'sf_btag_hfstats1': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4c8caf0>,\n",
+       " 'sf_btag_hfstats2': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4c8c160>,\n",
+       " 'sf_btag_lf': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4c8dbe0>,\n",
+       " 'sf_btag_lfstats1': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4c8dcd0>,\n",
+       " 'sf_btag_lfstats2': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4a92df0>,\n",
+       " 'sf_ele_id': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4a92d00>,\n",
+       " 'sf_ele_reco': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4a95e50>,\n",
+       " 'sf_ele_trigger_era': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4a954c0>,\n",
+       " 'sf_ele_trigger_ht': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4a97f70>,\n",
+       " 'sf_ele_trigger_pileup': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4a97f40>,\n",
+       " 'sf_ele_trigger_stat': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4a98e20>,\n",
+       " 'sf_jet_puId': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4a98f40>,\n",
+       " 'sf_mu_id': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4a9af40>,\n",
+       " 'sf_mu_iso': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4a9dfa0>,\n",
+       " 'sf_mu_trigger': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4a9da30>,\n",
+       " 'mcstat': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d60507f0>}"
       ]
      },
      "execution_count": 16,
@@ -455,7 +433,7 @@
     {
      "data": {
       "text/plain": [
-       "<pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f166ec460>"
+       "<pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4cc0bb0>"
       ]
      },
      "execution_count": 17,
@@ -464,8 +442,9 @@
     }
    ],
    "source": [
-    "s = syst_manager.syst_dict[\"JER\"]\n",
-    "s"
+    "pileup = syst_manager.get_syst(\"pileup\")\n",
+    "JES_Total = syst_manager.get_syst(\"JES_Total\")\n",
+    "pileup"
    ]
   },
   {
@@ -479,34 +458,7 @@
     {
      "data": {
       "text/plain": [
-       "['__add__',\n",
-       " '__class__',\n",
-       " '__delattr__',\n",
-       " '__dict__',\n",
-       " '__dir__',\n",
-       " '__doc__',\n",
-       " '__eq__',\n",
-       " '__format__',\n",
-       " '__ge__',\n",
-       " '__getattribute__',\n",
-       " '__gt__',\n",
-       " '__hash__',\n",
-       " '__init__',\n",
-       " '__init_subclass__',\n",
-       " '__le__',\n",
-       " '__lt__',\n",
-       " '__module__',\n",
-       " '__ne__',\n",
-       " '__new__',\n",
-       " '__reduce__',\n",
-       " '__reduce_ex__',\n",
-       " '__repr__',\n",
-       " '__setattr__',\n",
-       " '__sizeof__',\n",
-       " '__str__',\n",
-       " '__subclasshook__',\n",
-       " '__weakref__',\n",
-       " '_get_err2',\n",
+       "['_get_err2',\n",
        " '_get_err2_from_syst',\n",
        " '_is_empty',\n",
        " '_n_empty',\n",
@@ -537,7 +489,7 @@
     }
    ],
    "source": [
-    "dir(s)"
+    "[d for d in dir(pileup) if not d.startswith(\"__\")]"
    ]
   },
   {
@@ -551,19 +503,19 @@
     {
      "data": {
       "text/plain": [
-       "array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 9.11607005e+04,\n",
-       "       9.27834477e+04, 6.29315906e+04, 4.61562579e+04, 2.50884140e+04,\n",
-       "       1.65060009e+04, 8.42179789e+03, 4.90902698e+03, 2.78566432e+03,\n",
-       "       2.03306476e+03, 8.38858990e+02, 9.43239715e+02, 4.16501352e+02,\n",
-       "       1.79748982e+02, 1.95682225e+02, 8.38990053e+01, 5.61078601e+01,\n",
-       "       5.56000035e+01, 2.27633727e+01, 1.01967449e+01, 1.09760809e+01,\n",
-       "       5.41495368e+00, 3.35182865e+00, 1.43706500e+00, 2.27116756e+00,\n",
-       "       9.23500623e-01, 2.86470865e+00, 1.61542858e+00, 3.73156545e+00,\n",
-       "       3.75386511e-01, 9.32838941e-02, 4.29123357e-01, 1.67206829e-01,\n",
-       "       1.83280950e-01, 3.73368079e-01, 1.05669519e-01, 2.28578684e-01,\n",
-       "       4.12464014e-02, 8.08846763e-02, 2.34777494e-03, 5.30243379e-01,\n",
-       "       1.41417242e-02, 5.89701090e-02, 4.24611167e-02, 7.62562183e-03,\n",
-       "       1.96446709e-03, 1.32531336e-04])"
+       "array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 8.51337422e+07,\n",
+       "       8.90241147e+07, 6.64709598e+07, 4.59969080e+07, 2.82356043e+07,\n",
+       "       1.78276167e+07, 1.00355040e+07, 6.55987354e+06, 3.78138649e+06,\n",
+       "       2.23447858e+06, 1.30466117e+06, 8.02222623e+05, 4.72369448e+05,\n",
+       "       2.87164680e+05, 1.77262956e+05, 1.06025114e+05, 6.91775404e+04,\n",
+       "       4.31903425e+04, 2.70651251e+04, 1.81530320e+04, 1.08317567e+04,\n",
+       "       7.50194295e+03, 4.49418414e+03, 3.24486251e+03, 2.19998961e+03,\n",
+       "       1.12964046e+03, 8.97573917e+02, 7.08310409e+02, 5.53588187e+02,\n",
+       "       3.30488474e+02, 2.01758672e+02, 1.44288738e+02, 1.02800902e+02,\n",
+       "       8.86509731e+01, 7.86310281e+01, 4.85163362e+01, 4.51786076e+01,\n",
+       "       3.98595327e+01, 2.01625029e+01, 1.37058162e+01, 2.92223969e+01,\n",
+       "       1.37124958e+01, 6.93892325e+00, 5.89023492e+00, 4.93240838e+00,\n",
+       "       3.26040344e+00, 6.62067888e+00])"
       ]
      },
      "execution_count": 19,
@@ -572,7 +524,7 @@
     }
    ],
    "source": [
-    "s.err2_up"
+    "pileup.err2_up"
    ]
   },
   {
@@ -586,19 +538,19 @@
     {
      "data": {
       "text/plain": [
-       "array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 7.41242369e+04,\n",
-       "       8.09454378e+04, 5.40108696e+04, 3.60821576e+04, 2.28405727e+04,\n",
-       "       1.40913789e+04, 5.86729880e+03, 4.68657214e+03, 2.18757198e+03,\n",
-       "       1.37022324e+03, 5.75498003e+02, 3.97617586e+02, 2.25555410e+02,\n",
-       "       2.49669601e+02, 1.16870573e+02, 7.06620646e+01, 7.31059356e+01,\n",
-       "       7.65567795e+01, 9.78685695e+00, 8.27260567e+00, 6.23340071e+00,\n",
-       "       8.40457030e+00, 4.09596249e+00, 3.02646043e+00, 4.65513298e-01,\n",
-       "       9.92518495e-01, 1.36529415e+00, 2.23643313e+00, 4.26888194e-01,\n",
-       "       9.70024040e-02, 1.36686974e-01, 1.55945087e-01, 5.11404522e-01,\n",
-       "       7.24108291e-01, 9.02205778e-02, 5.09569857e-01, 1.66685832e-01,\n",
-       "       4.58136166e-03, 1.27170636e+00, 3.42679028e-02, 5.48085905e-02,\n",
-       "       2.57202616e-02, 1.68608805e-03, 2.75366000e-03, 4.83758276e-02,\n",
-       "       9.16379761e-02, 5.18220977e-02])"
+       "array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 2.02656822e+07,\n",
+       "       2.17308697e+07, 1.66442304e+07, 1.18335686e+07, 7.37476730e+06,\n",
+       "       4.73021724e+06, 2.64759568e+06, 1.78458721e+06, 1.02357480e+06,\n",
+       "       6.09997298e+05, 3.51991067e+05, 2.19712149e+05, 1.29681615e+05,\n",
+       "       7.78051990e+04, 5.01615061e+04, 2.86600587e+04, 1.90775747e+04,\n",
+       "       1.20582843e+04, 7.20273063e+03, 4.89034759e+03, 3.16110538e+03,\n",
+       "       2.02555795e+03, 1.22943144e+03, 8.96961366e+02, 6.17372767e+02,\n",
+       "       2.87447372e+02, 2.37476197e+02, 2.03730107e+02, 1.60001047e+02,\n",
+       "       9.68389643e+01, 5.77194977e+01, 3.83799760e+01, 2.96710093e+01,\n",
+       "       2.65471836e+01, 2.55496134e+01, 1.25101752e+01, 1.42294449e+01,\n",
+       "       1.21007688e+01, 6.18274467e+00, 3.59160479e+00, 8.12502747e+00,\n",
+       "       5.20526733e+00, 1.85857319e+00, 1.80768379e+00, 1.74494923e+00,\n",
+       "       8.60198034e-01, 1.92928490e+00])"
       ]
      },
      "execution_count": 20,
@@ -607,13 +559,13 @@
     }
    ],
    "source": [
-    "s.err2_down"
+    "pileup.err2_down"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 21,
-   "id": "14e3f8df-a720-4bf1-9964-51d362256511",
+   "id": "7752ee8b-0dbd-4ded-bb88-06725af4267b",
    "metadata": {
     "tags": []
    },
@@ -621,7 +573,7 @@
     {
      "data": {
       "text/plain": [
-       "'JER'"
+       "0"
       ]
      },
      "execution_count": 21,
@@ -630,13 +582,13 @@
     }
    ],
    "source": [
-    "s.name"
+    "pileup._n_empty"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 22,
-   "id": "7752ee8b-0dbd-4ded-bb88-06725af4267b",
+   "id": "a62e6c6b-e08e-4387-af71-81eb1ea902c5",
    "metadata": {
     "tags": []
    },
@@ -644,7 +596,7 @@
     {
      "data": {
       "text/plain": [
-       "0"
+       "<pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4803460>"
       ]
      },
      "execution_count": 22,
@@ -653,15 +605,14 @@
     }
    ],
    "source": [
-    "s1 = syst_manager.syst_dict[\"JER\"]\n",
-    "s2 = syst_manager.syst_dict[\"pileup\"]\n",
-    "s1._n_empty"
+    "s_sum = pileup + JES_Total\n",
+    "s_sum"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 23,
-   "id": "a62e6c6b-e08e-4387-af71-81eb1ea902c5",
+   "id": "a1e65a02-632d-44e3-a9b3-b1062ae2d2e2",
    "metadata": {
     "tags": []
    },
@@ -669,7 +620,7 @@
     {
      "data": {
       "text/plain": [
-       "<pocket_coffea.utils.plot_utils.SystUnc at 0x7f7f166eca90>"
+       "'pileup_JES_Total'"
       ]
      },
      "execution_count": 23,
@@ -678,14 +629,13 @@
     }
    ],
    "source": [
-    "s_sum = s1 + s2\n",
-    "s_sum"
+    "s_sum.name"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 24,
-   "id": "a1e65a02-632d-44e3-a9b3-b1062ae2d2e2",
+   "id": "0f39e4ac-627a-4a54-813f-e769c2c5b371",
    "metadata": {
     "tags": []
    },
@@ -693,7 +643,19 @@
     {
      "data": {
       "text/plain": [
-       "'JER_pileup'"
+       "array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 2.25806757e+05,\n",
+       "       2.26535243e+05, 1.91588041e+05, 1.55574641e+05, 1.21627448e+05,\n",
+       "       9.49689294e+04, 7.21009542e+04, 5.72741375e+04, 4.40003891e+04,\n",
+       "       3.39193336e+04, 2.63300267e+04, 2.05633756e+04, 1.60511352e+04,\n",
+       "       1.25832364e+04, 9.88849950e+03, 7.87600155e+03, 6.33039723e+03,\n",
+       "       5.06530613e+03, 4.09517215e+03, 3.31261179e+03, 2.69942393e+03,\n",
+       "       2.19986359e+03, 1.79598653e+03, 1.48753835e+03, 1.21714564e+03,\n",
+       "       1.00826226e+03, 8.57665994e+02, 7.29275142e+02, 5.99958888e+02,\n",
+       "       4.91218753e+02, 4.36476528e+02, 3.63295001e+02, 3.03137107e+02,\n",
+       "       2.68162037e+02, 2.27362756e+02, 2.02136569e+02, 1.71023651e+02,\n",
+       "       1.47058240e+02, 1.27441950e+02, 1.13981028e+02, 1.00391585e+02,\n",
+       "       8.24555328e+01, 7.42288373e+01, 6.25570875e+01, 5.99941083e+01,\n",
+       "       5.30236269e+01, 4.70497157e+01])"
       ]
      },
      "execution_count": 24,
@@ -702,13 +664,13 @@
     }
    ],
    "source": [
-    "s_sum.name"
+    "s_sum.up"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 25,
-   "id": "0f39e4ac-627a-4a54-813f-e769c2c5b371",
+   "id": "3b2968aa-3aac-4af0-b534-2178dc5d277c",
    "metadata": {
     "tags": []
    },
@@ -716,19 +678,19 @@
     {
      "data": {
       "text/plain": [
-       "array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 9.11607005e+04,\n",
-       "       9.27834477e+04, 6.29315906e+04, 4.61562579e+04, 2.50884140e+04,\n",
-       "       1.65060009e+04, 8.42179789e+03, 4.90902698e+03, 2.78566432e+03,\n",
-       "       2.03306476e+03, 8.38858990e+02, 9.43239715e+02, 4.16501352e+02,\n",
-       "       1.79748982e+02, 1.95682225e+02, 8.38990053e+01, 5.61078601e+01,\n",
-       "       5.56000035e+01, 2.27633727e+01, 1.01967449e+01, 1.09760809e+01,\n",
-       "       5.41495368e+00, 3.35182865e+00, 1.43706500e+00, 2.27116756e+00,\n",
-       "       9.23500623e-01, 2.86470865e+00, 1.61542858e+00, 3.73156545e+00,\n",
-       "       3.75386511e-01, 9.32838941e-02, 4.29123357e-01, 1.67206829e-01,\n",
-       "       1.83280950e-01, 3.73368079e-01, 1.05669519e-01, 2.28578684e-01,\n",
-       "       4.12464014e-02, 8.08846763e-02, 2.34777494e-03, 5.30243379e-01,\n",
-       "       1.41417242e-02, 5.89701090e-02, 4.24611167e-02, 7.62562183e-03,\n",
-       "       1.96446709e-03, 1.32531336e-04])"
+       "array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 2.00040019e+05,\n",
+       "       2.00292883e+05, 1.69206880e+05, 1.37290504e+05, 1.07452081e+05,\n",
+       "       8.39788368e+04, 6.38926637e+04, 5.07792096e+04, 3.91324276e+04,\n",
+       "       3.02213645e+04, 2.35475409e+04, 1.84126443e+04, 1.44164748e+04,\n",
+       "       1.13255818e+04, 8.90637700e+03, 7.12786574e+03, 5.73028191e+03,\n",
+       "       4.59309349e+03, 3.72802385e+03, 3.01496591e+03, 2.46662245e+03,\n",
+       "       2.00622518e+03, 1.64674215e+03, 1.36381887e+03, 1.11278133e+03,\n",
+       "       9.32363899e+02, 7.91049485e+02, 6.71703028e+02, 5.48385797e+02,\n",
+       "       4.50671356e+02, 4.05438259e+02, 3.36839810e+02, 2.78314290e+02,\n",
+       "       2.47076839e+02, 2.08073739e+02, 1.87189350e+02, 1.56247476e+02,\n",
+       "       1.33770381e+02, 1.17515282e+02, 1.06020823e+02, 8.92708660e+01,\n",
+       "       7.47261394e+01, 6.82490816e+01, 5.71709897e+01, 5.52665686e+01,\n",
+       "       4.91861115e+01, 4.18536275e+01])"
       ]
      },
      "execution_count": 25,
@@ -737,13 +699,13 @@
     }
    ],
    "source": [
-    "s1.err2_up"
+    "s_sum.down"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 26,
-   "id": "3b2968aa-3aac-4af0-b534-2178dc5d277c",
+   "id": "e4cca839-62b8-404a-8c30-b977dc422fab",
    "metadata": {
     "tags": []
    },
@@ -751,19 +713,7 @@
     {
      "data": {
       "text/plain": [
-       "array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 8.51337422e+07,\n",
-       "       8.90241147e+07, 6.64709598e+07, 4.59969080e+07, 2.82356043e+07,\n",
-       "       1.78276167e+07, 1.00355040e+07, 6.55987354e+06, 3.78138649e+06,\n",
-       "       2.23447858e+06, 1.30466117e+06, 8.02222623e+05, 4.72369448e+05,\n",
-       "       2.87164680e+05, 1.77262956e+05, 1.06025114e+05, 6.91775404e+04,\n",
-       "       4.31903425e+04, 2.70651251e+04, 1.81530320e+04, 1.08317567e+04,\n",
-       "       7.50194295e+03, 4.49418414e+03, 3.24486251e+03, 2.19998961e+03,\n",
-       "       1.12964046e+03, 8.97573917e+02, 7.08310409e+02, 5.53588187e+02,\n",
-       "       3.30488474e+02, 2.01758672e+02, 1.44288738e+02, 1.02800902e+02,\n",
-       "       8.86509731e+01, 7.86310281e+01, 4.85163362e+01, 4.51786076e+01,\n",
-       "       3.98595327e+01, 2.01625029e+01, 1.37058162e+01, 2.92223969e+01,\n",
-       "       1.37124958e+01, 6.93892325e+00, 5.89023492e+00, 4.93240838e+00,\n",
-       "       3.26040344e+00, 6.62067888e+00])"
+       "['pileup', 'JES_Total']"
       ]
      },
      "execution_count": 26,
@@ -772,118 +722,12 @@
     }
    ],
    "source": [
-    "s2.err2_up"
+    "[s.name for s in s_sum.syst_list]"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 27,
-   "id": "214b41fb-36f2-472d-b0aa-b2f422189d85",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 8.52249029e+07,\n",
-       "       8.91168981e+07, 6.65338914e+07, 4.60430642e+07, 2.82606927e+07,\n",
-       "       1.78441227e+07, 1.00439258e+07, 6.56478257e+06, 3.78417215e+06,\n",
-       "       2.23651164e+06, 1.30550002e+06, 8.03165862e+05, 4.72785950e+05,\n",
-       "       2.87344429e+05, 1.77458638e+05, 1.06109013e+05, 6.92336482e+04,\n",
-       "       4.32459425e+04, 2.70878884e+04, 1.81632288e+04, 1.08427328e+04,\n",
-       "       7.50735791e+03, 4.49753597e+03, 3.24629957e+03, 2.20226078e+03,\n",
-       "       1.13056396e+03, 9.00438626e+02, 7.09925838e+02, 5.57319752e+02,\n",
-       "       3.30863861e+02, 2.01851956e+02, 1.44717861e+02, 1.02968109e+02,\n",
-       "       8.88342540e+01, 7.90043962e+01, 4.86220057e+01, 4.54071863e+01,\n",
-       "       3.99007791e+01, 2.02433876e+01, 1.37081639e+01, 2.97526402e+01,\n",
-       "       1.37266376e+01, 6.99789336e+00, 5.93269604e+00, 4.94003400e+00,\n",
-       "       3.26236791e+00, 6.62081142e+00])"
-      ]
-     },
-     "execution_count": 27,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "s_sum.err2_up"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 28,
-   "id": "e16231fd-8879-4e63-8e86-daebf77cd6c6",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['__add__',\n",
-       " '__class__',\n",
-       " '__delattr__',\n",
-       " '__dict__',\n",
-       " '__dir__',\n",
-       " '__doc__',\n",
-       " '__eq__',\n",
-       " '__format__',\n",
-       " '__ge__',\n",
-       " '__getattribute__',\n",
-       " '__gt__',\n",
-       " '__hash__',\n",
-       " '__init__',\n",
-       " '__init_subclass__',\n",
-       " '__le__',\n",
-       " '__lt__',\n",
-       " '__module__',\n",
-       " '__ne__',\n",
-       " '__new__',\n",
-       " '__reduce__',\n",
-       " '__reduce_ex__',\n",
-       " '__repr__',\n",
-       " '__setattr__',\n",
-       " '__sizeof__',\n",
-       " '__str__',\n",
-       " '__subclasshook__',\n",
-       " '__weakref__',\n",
-       " '_get_err2',\n",
-       " '_get_err2_from_syst',\n",
-       " '_is_empty',\n",
-       " '_n_empty',\n",
-       " 'datamc',\n",
-       " 'down',\n",
-       " 'err2_down',\n",
-       " 'err2_up',\n",
-       " 'is_mcstat',\n",
-       " 'name',\n",
-       " 'nominal',\n",
-       " 'nsyst',\n",
-       " 'plot',\n",
-       " 'ratio_down',\n",
-       " 'ratio_up',\n",
-       " 'style',\n",
-       " 'syst_list',\n",
-       " 'up',\n",
-       " 'xbinwidth',\n",
-       " 'xcenters',\n",
-       " 'xedges',\n",
-       " 'xlabel']"
-      ]
-     },
-     "execution_count": 28,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "dir(s_sum)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 29,
    "id": "881d8932-6df6-4596-baa6-f0ad6e05bffc",
    "metadata": {
     "tags": []
@@ -896,13 +740,13 @@
        " <AxesSubplot: xlabel='$p_{T}^{e}$ [GeV]', ylabel='Counts'>)"
       ]
      },
-     "execution_count": 29,
+     "execution_count": 27,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 1200x900 with 1 Axes>"
       ]
@@ -912,12 +756,12 @@
     }
    ],
    "source": [
-    "s2.plot()"
+    "s_sum.plot()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 28,
    "id": "3787a08f-a9e9-467c-ac70-545b428c845c",
    "metadata": {
     "tags": []
@@ -977,7 +821,7 @@
        " 'xlabel']"
       ]
      },
-     "execution_count": 30,
+     "execution_count": 28,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -989,7 +833,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 29,
    "id": "94d67dde-bb55-4df8-b166-648330d54212",
    "metadata": {},
    "outputs": [
@@ -1020,7 +864,7 @@
        " 'mcstat']"
       ]
      },
-     "execution_count": 31,
+     "execution_count": 29,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1031,7 +875,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 30,
    "id": "36cfc805-5d95-4546-862d-bfe8287bb492",
    "metadata": {
     "tags": []
@@ -1044,7 +888,7 @@
        " <AxesSubplot: xlabel='$p_{T}^{e}$ [GeV]', ylabel='Counts'>)"
       ]
      },
-     "execution_count": 32,
+     "execution_count": 30,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -1068,7 +912,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 31,
    "id": "a3874d45-10d5-43bf-aa82-7479b48a9e71",
    "metadata": {
     "tags": []
@@ -1092,7 +936,7 @@
        "       5.62289338e+01, 4.97717261e+01])"
       ]
      },
-     "execution_count": 33,
+     "execution_count": 31,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1101,27 +945,6 @@
     "syst_manager.total.up"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 34,
-   "id": "d00bfe3a-6a60-4725-a8c6-8345a6bd2a12",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'$p_{T}^{e}$ [GeV]'"
-      ]
-     },
-     "execution_count": 34,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "h_dict[\"ttHTobb\"].axes[-1].label"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
-- 
GitLab


From 3208b1a63c5d1eddb1104dd789b62d8c73669d7c Mon Sep 17 00:00:00 2001
From: mmarchegiani <matmarcheg@gmail.com>
Date: Tue, 28 Mar 2023 19:21:55 +0200
Subject: [PATCH 12/24] Defaults for colors

---
 pocket_coffea/utils/plot_utils.py | 76 +++++++++++++++++++++++--------
 1 file changed, 58 insertions(+), 18 deletions(-)

diff --git a/pocket_coffea/utils/plot_utils.py b/pocket_coffea/utils/plot_utils.py
index dca8fb3f..76158c9d 100644
--- a/pocket_coffea/utils/plot_utils.py
+++ b/pocket_coffea/utils/plot_utils.py
@@ -1,4 +1,5 @@
 import os
+from copy import deepcopy
 
 import math
 import numpy as np
@@ -48,16 +49,17 @@ class Shape:
     - name: name that identifies the Shape object.
     - style_cfg: dictionary with style and plotting options.
     - data_key: prefix for data samples (e.g. default in PocketCoffea: "DATA_SingleEle")'''
-    def __init__(self, h_dict, name, plot_dir, only_cat=[], style_cfg=style_cfg, data_key="DATA", log=False) -> None:
+    def __init__(self, h_dict, name, plot_dir, only_cat=[], samples_map={}, style_cfg=style_cfg, data_key="DATA", log=False) -> None:
         self.h_dict = h_dict
         self.name = name
         self.plot_dir = plot_dir
         self.only_cat = only_cat
+        self.samples_map = samples_map
         self.style = Style(style_cfg)
         self.data_key = data_key
         self.log = log
         assert type(h_dict) == dict, "The Shape object receives a dictionary of hist.Hist objects as argument."
-        self.define_samples()
+        self.group_samples()
         assert self.dense_dim == 1, f"Histograms with dense dimension {self.dense_dim} cannot be plotted. Only 1D histograms are supported."
         self.load_attributes()
 
@@ -118,12 +120,13 @@ class Shape:
             axis = [ax for ax in self.categorical_axes_data if ax.name == axis_name][0]
         return list(axis.value(range(axis.size)))
 
-    def stack_sum(self, mc):
+    def _stack_sum(self, mc=None, stack=None):
         '''Returns the sum histogram of a stack (`hist.stack.Stack`) of histograms.'''
-        if mc:
-            stack = self.stack_mc_nominal
-        else:
-            stack = self.stack_data
+        if not stack:
+            if mc:
+                stack = self.stack_mc_nominal
+            else:
+                stack = self.stack_data
         if len(stack) == 1:
             return stack[0]
         else:
@@ -135,18 +138,38 @@ class Shape:
     @property
     def stack_sum_data(self):
         '''Returns the sum histogram of a stack (`hist.stack.Stack`) of data histograms.'''
-        return self.stack_sum(mc=False)
+        return self._stack_sum(mc=False)
 
     @property
     def stack_sum_mc_nominal(self):
         '''Returns the sum histogram of a stack (`hist.stack.Stack`) of MC histograms.'''
-        return self.stack_sum(mc=True)
+        return self._stack_sum(mc=True)
+
+    @property
+    def samples(self):
+        return list(self.h_dict.keys())
+
+    @property
+    def samples_data(self):
+        return list(filter(lambda d : self.data_key in d, self.samples))
 
-    def define_samples(self):
-        '''Defines the data and MC samples.'''
-        self.samples = self.h_dict.keys()
-        self.samples_data = list(filter(lambda d : self.data_key in d, self.samples))
-        self.samples_mc = list(filter(lambda d : self.data_key not in d, self.samples))
+    @property
+    def samples_mc(self):
+        return list(filter(lambda d : self.data_key not in d, self.samples))
+
+    def group_samples(self):
+        '''Groups samples according to the dictionary self.samples_map'''
+        h_dict_grouped = {}
+        if self.samples_map == {}:
+            return
+        samples_in_map = []
+        for sample_new, samples_list in self.samples_map.items():
+            h_dict_grouped[sample_new] = self._stack_sum(stack=hist.Stack.from_dict({s : h for s, h in self.h_dict.items() if s in samples_list}))
+            samples_in_map += samples_list
+        for s, h in self.h_dict.items():
+            if s not in samples_in_map:
+                h_dict_grouped[s] = h
+        self.h_dict = deepcopy(h_dict_grouped)
 
     def load_attributes(self):
         '''Loads the attributes from the dictionary of histograms.'''
@@ -177,7 +200,15 @@ class Shape:
         # Order the events dictionary by decreasing number of events if linear scale, increasing if log scale
         # N.B.: Here implement if log: reverse=False
         self.nevents = dict( sorted(self.nevents.items(), key=lambda x:x[1], reverse=reverse) )
-        self.colors = [self.style.colors[d] for d in self.nevents.keys()]
+        color = iter(cm.gist_rainbow(np.linspace(0, 1, len(self.nevents.keys()))))
+        # Assign random colors to each sample
+        self.colors = [next(color) for d in self.nevents.keys()]
+        if hasattr(self.style, "colors"):
+            # Initialize random colors
+            for i, d in enumerate(self.nevents.keys()):
+                # If the color for a corresponding sample exists in the dictionary, assign the color to the sample
+                if d in self.style.colors:
+                    self.colors[i] = self.style.colors[d]
         # Order the MC dictionary by number of events
         self.h_dict_mc = {d: self.h_dict_mc[d] for d in self.nevents.keys()}
         self.h_dict_mc_nominal = {d: self.h_dict_mc_nominal[d] for d in self.nevents.keys()}
@@ -270,18 +301,27 @@ class Shape:
             handles = handles_new
             self.ax.legend(handles, labels, fontsize=self.style.fontsize, ncols=2, loc="upper right")
 
-    def plot_mc(self):
+    def plot_mc(self, year):
         '''Plots the MC histograms as a stacked plot.'''
+        if not 'fig' in dir(self):
+            self.define_figure(year, ratio=False)
         self.stack_mc_nominal.plot(stack=True, histtype='fill', ax=self.ax, color=self.colors)
+        self.format_figure(ratio=False)
 
-    def plot_data(self):
+    def plot_data(self, year):
         '''Plots the data histogram as an errorbar plot.'''
+        if not 'fig' in dir(self):
+            self.define_figure(year, ratio=False)
         self.ax.errorbar(self.xcenters, self.stack_sum_data.values(), yerr=np.sqrt(self.stack_sum_data.values()), **self.style.opts_data)
+        self.format_figure(ratio=False)
 
-    def plot_datamc_ratio(self):
+    def plot_datamc_ratio(self, year):
         '''Plots the Data/MC ratio as an errorbar plot.'''
         self.get_datamc_ratio()
+        if not 'fig' in dir(self):
+            self.define_figure(year, ratio=True)
         self.rax.errorbar(self.xcenters, self.ratio, yerr=self.ratio_unc, **self.style.opts_data)
+        self.format_figure(ratio=True)
 
     def plot_systematic_uncertainty(self, ratio=False):
         '''Plots the asymmetric systematic uncertainty band on top of the MC stack, if `ratio` is set to False.
-- 
GitLab


From 654ac89a48cfe878bee006195df9cc54aa73d866 Mon Sep 17 00:00:00 2001
From: mmarchegiani <matmarcheg@gmail.com>
Date: Tue, 28 Mar 2023 19:25:42 +0200
Subject: [PATCH 13/24] Default for plot_mc

---
 pocket_coffea/utils/plot_utils.py | 9 +++++----
 1 file changed, 5 insertions(+), 4 deletions(-)

diff --git a/pocket_coffea/utils/plot_utils.py b/pocket_coffea/utils/plot_utils.py
index 76158c9d..55cac573 100644
--- a/pocket_coffea/utils/plot_utils.py
+++ b/pocket_coffea/utils/plot_utils.py
@@ -245,7 +245,7 @@ class Shape:
         '''Instantiates the `SystUnc` objects and stores them in a dictionary with one entry for each systematic uncertainty.'''
         self.syst_manager = SystManager(self)
 
-    def define_figure(self, year, ratio=True):
+    def define_figure(self, year=None, ratio=True):
         '''Defines the figure for the Data/MC plot.
         If ratio is True, a subplot is defined to include the Data/MC ratio plot.'''
         plt.style.use([hep.style.ROOT, {'font.size': self.style.fontsize}])
@@ -256,7 +256,8 @@ class Shape:
         else:
             self.fig, self.ax  = plt.subplots(1, 1, **self.style.opts_figure["datamc"])
         hep.cms.text("Preliminary", fontsize=self.style.fontsize, loc=0, ax=self.ax)
-        hep.cms.lumitext(text=f'{self.lumi[year]}' + r' fb$^{-1}$, 13 TeV,' + f' {year}', fontsize=self.style.fontsize, ax=self.ax)
+        if year:
+            hep.cms.lumitext(text=f'{self.lumi[year]}' + r' fb$^{-1}$, 13 TeV,' + f' {year}', fontsize=self.style.fontsize, ax=self.ax)
 
     def format_figure(self, ratio=True):
         '''Formats the figure's axes, labels, ticks, xlim and ylim.'''
@@ -301,10 +302,10 @@ class Shape:
             handles = handles_new
             self.ax.legend(handles, labels, fontsize=self.style.fontsize, ncols=2, loc="upper right")
 
-    def plot_mc(self, year):
+    def plot_mc(self):
         '''Plots the MC histograms as a stacked plot.'''
         if not 'fig' in dir(self):
-            self.define_figure(year, ratio=False)
+            self.define_figure(ratio=False)
         self.stack_mc_nominal.plot(stack=True, histtype='fill', ax=self.ax, color=self.colors)
         self.format_figure(ratio=False)
 
-- 
GitLab


From 6ffc451cc9739c1ce0592b7695523fc532e6f1d3 Mon Sep 17 00:00:00 2001
From: mmarchegiani <matmarcheg@gmail.com>
Date: Tue, 28 Mar 2023 19:34:21 +0200
Subject: [PATCH 14/24] Pass samples_map argument to Shape object

---
 pocket_coffea/utils/plot_utils.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pocket_coffea/utils/plot_utils.py b/pocket_coffea/utils/plot_utils.py
index 55cac573..50ac6df4 100644
--- a/pocket_coffea/utils/plot_utils.py
+++ b/pocket_coffea/utils/plot_utils.py
@@ -26,7 +26,7 @@ class Style:
 
 class PlotManager:
     '''This class manages multiple Shape objects and their plotting.'''
-    def __init__(self, hist_cfg, plot_dir, only_cat=[], style_cfg=style_cfg, data_key="DATA", log=False, save=True) -> None:
+    def __init__(self, hist_cfg, plot_dir, only_cat=[], samples_map={}, style_cfg=style_cfg, data_key="DATA", log=False, save=True) -> None:
         self.datamc_objects = {}
         self.plot_dir = plot_dir
         self.only_cat = only_cat
@@ -34,7 +34,7 @@ class PlotManager:
         self.log = log
         self.save = save
         for name, h_dict in hist_cfg.items():
-            self.datamc_objects[name] = Shape(h_dict, name, plot_dir, only_cat=self.only_cat, style_cfg=style_cfg, data_key=self.data_key, log=self.log)
+            self.datamc_objects[name] = Shape(h_dict, name, plot_dir, only_cat=self.only_cat, samples_map=samples_map, style_cfg=style_cfg, data_key=self.data_key, log=self.log)
 
     def plot_datamc_all(self, ratio=True, syst=True, spliteras=False):
         '''Plots all the histograms contained in the dictionary, for all years and categories.'''
-- 
GitLab


From 02219cd3c4acc81b92628dfd295817089bc4a71c Mon Sep 17 00:00:00 2001
From: mmarchegiani <matmarcheg@gmail.com>
Date: Wed, 29 Mar 2023 12:02:24 +0200
Subject: [PATCH 15/24] Include opts_mc parameters

---
 pocket_coffea/parameters/plotting.py | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/pocket_coffea/parameters/plotting.py b/pocket_coffea/parameters/plotting.py
index 09603710..8ab6c7b4 100644
--- a/pocket_coffea/parameters/plotting.py
+++ b/pocket_coffea/parameters/plotting.py
@@ -18,6 +18,10 @@ style_cfg = {
             'sharex' : True,
         },
     },
+    "opts_mc" : {
+        'histtype': 'fill',
+        'stack' : True
+    },
     "opts_data" : {
         'linestyle': 'solid',
         'linewidth': 0,
@@ -70,6 +74,7 @@ style_cfg = {
             'color': 'blue',
         },
     },
+    "samples_map": {},
     "labels": {
         "ttHTobb": "$t\\bar{t}H\\rightarrow b\\bar{b}$",
         "TTToSemiLeptonic": "$t\\bar{t}$ semilep.",
-- 
GitLab


From 7a53ef96a25f30b7b0002894e386c3ac3a51942c Mon Sep 17 00:00:00 2001
From: mmarchegiani <matmarcheg@gmail.com>
Date: Wed, 29 Mar 2023 12:03:50 +0200
Subject: [PATCH 16/24] Density plot and samples_map as style parameter

---
 pocket_coffea/utils/plot_utils.py | 55 ++++++++++++++++++++++---------
 1 file changed, 40 insertions(+), 15 deletions(-)

diff --git a/pocket_coffea/utils/plot_utils.py b/pocket_coffea/utils/plot_utils.py
index 50ac6df4..3287b37c 100644
--- a/pocket_coffea/utils/plot_utils.py
+++ b/pocket_coffea/utils/plot_utils.py
@@ -18,15 +18,29 @@ from ..parameters.plotting import style_cfg
 class Style:
     '''This class manages all the style options for Data/MC plots.'''
     def __init__(self, style_cfg=style_cfg) -> None:
+        required_keys = ["opts_figure", "opts_mc", "opts_data", "opts_unc"]
+        for key in required_keys:
+            assert key in style_cfg, f"The key `{key}` is not defined in the style dictionary."
         for key, item in style_cfg.items():
             setattr(self, key, item)
+        self.has_labels = False
+        self.has_samples_map = False
         if "labels" in style_cfg:
             self.has_labels = True
+        if "samples_map" in style_cfg:
+            self.has_samples_map = True
+        self.set_defaults()
+
+    def set_defaults(self):
+        if not "stack" in self.opts_mc:
+            self.opts_mc["stack"] = True
+        if not hasattr(self, "fontsize"):
+            self.fontsize = 22
 
 
 class PlotManager:
     '''This class manages multiple Shape objects and their plotting.'''
-    def __init__(self, hist_cfg, plot_dir, only_cat=[], samples_map={}, style_cfg=style_cfg, data_key="DATA", log=False, save=True) -> None:
+    def __init__(self, hist_cfg, plot_dir, only_cat=[], style_cfg=style_cfg, data_key="DATA", log=False, density=False, save=True) -> None:
         self.datamc_objects = {}
         self.plot_dir = plot_dir
         self.only_cat = only_cat
@@ -34,7 +48,7 @@ class PlotManager:
         self.log = log
         self.save = save
         for name, h_dict in hist_cfg.items():
-            self.datamc_objects[name] = Shape(h_dict, name, plot_dir, only_cat=self.only_cat, samples_map=samples_map, style_cfg=style_cfg, data_key=self.data_key, log=self.log)
+            self.datamc_objects[name] = Shape(h_dict, name, plot_dir, only_cat=self.only_cat, style_cfg=style_cfg, data_key=self.data_key, log=self.log, density=False)
 
     def plot_datamc_all(self, ratio=True, syst=True, spliteras=False):
         '''Plots all the histograms contained in the dictionary, for all years and categories.'''
@@ -49,15 +63,15 @@ class Shape:
     - name: name that identifies the Shape object.
     - style_cfg: dictionary with style and plotting options.
     - data_key: prefix for data samples (e.g. default in PocketCoffea: "DATA_SingleEle")'''
-    def __init__(self, h_dict, name, plot_dir, only_cat=[], samples_map={}, style_cfg=style_cfg, data_key="DATA", log=False) -> None:
+    def __init__(self, h_dict, name, plot_dir, only_cat=[], style_cfg=style_cfg, data_key="DATA", log=False, density=False) -> None:
         self.h_dict = h_dict
         self.name = name
         self.plot_dir = plot_dir
         self.only_cat = only_cat
-        self.samples_map = samples_map
         self.style = Style(style_cfg)
         self.data_key = data_key
         self.log = log
+        self.density = density
         assert type(h_dict) == dict, "The Shape object receives a dictionary of hist.Hist objects as argument."
         self.group_samples()
         assert self.dense_dim == 1, f"Histograms with dense dimension {self.dense_dim} cannot be plotted. Only 1D histograms are supported."
@@ -158,12 +172,12 @@ class Shape:
         return list(filter(lambda d : self.data_key not in d, self.samples))
 
     def group_samples(self):
-        '''Groups samples according to the dictionary self.samples_map'''
-        h_dict_grouped = {}
-        if self.samples_map == {}:
+        '''Groups samples according to the dictionary self.style.samples_map'''
+        if not self.style.has_samples_map:
             return
+        h_dict_grouped = {}
         samples_in_map = []
-        for sample_new, samples_list in self.samples_map.items():
+        for sample_new, samples_list in self.style.samples_map.items():
             h_dict_grouped[sample_new] = self._stack_sum(stack=hist.Stack.from_dict({s : h for s, h in self.h_dict.items() if s in samples_list}))
             samples_in_map += samples_list
         for s, h in self.h_dict.items():
@@ -261,7 +275,8 @@ class Shape:
 
     def format_figure(self, ratio=True):
         '''Formats the figure's axes, labels, ticks, xlim and ylim.'''
-        self.ax.set_ylabel("Counts", fontsize=self.style.fontsize)
+        ylabel = "Counts" if not self.density else "A.U."
+        self.ax.set_ylabel(ylabel, fontsize=self.style.fontsize)
         self.ax.legend(fontsize=self.style.fontsize, ncols=2, loc="upper right")
         self.ax.tick_params(axis='x', labelsize=self.style.fontsize)
         self.ax.tick_params(axis='y', labelsize=self.style.fontsize)
@@ -275,11 +290,15 @@ class Shape:
             self.ax.set_ylim((0.01, 10 ** (exp + 3)))
         else:
             if self.is_mc_only:
-                maximum = max(self.stack_sum_mc_nominal.values())
+                reference_shape = self.stack_sum_mc_nominal.values()
             else:
-                maximum = max(self.stack_sum_data.values())
-            if not np.isnan(maximum):
-                self.ax.set_ylim((0, 2.0 * maximum))
+                reference_shape = self.stack_sum_data.values()
+            if self.density:
+                integral = sum(reference_shape) * self.xbinwidth
+                reference_shape = reference_shape / integral
+            ymax = max(reference_shape)
+            if not np.isnan(ymax):
+                self.ax.set_ylim((0, 2.0 * ymax))
         if ratio:
             self.ax.set_xlabel("")
             self.rax.set_xlabel(self.xlabel, fontsize=self.style.fontsize)
@@ -306,14 +325,20 @@ class Shape:
         '''Plots the MC histograms as a stacked plot.'''
         if not 'fig' in dir(self):
             self.define_figure(ratio=False)
-        self.stack_mc_nominal.plot(stack=True, histtype='fill', ax=self.ax, color=self.colors)
+        self.stack_mc_nominal.plot(ax=self.ax, color=self.colors, density=self.density, **self.style.opts_mc)
         self.format_figure(ratio=False)
 
     def plot_data(self, year):
         '''Plots the data histogram as an errorbar plot.'''
         if not 'fig' in dir(self):
             self.define_figure(year, ratio=False)
-        self.ax.errorbar(self.xcenters, self.stack_sum_data.values(), yerr=np.sqrt(self.stack_sum_data.values()), **self.style.opts_data)
+        y = self.stack_sum_data.values()
+        yerr = np.sqrt(y)
+        integral = (sum(y) * self.xbinwidth)
+        if self.density:
+            y = y / integral
+            yerr = yerr / integral
+        self.ax.errorbar(self.xcenters, y, yerr=yerr, **self.style.opts_data)
         self.format_figure(ratio=False)
 
     def plot_datamc_ratio(self, year):
-- 
GitLab


From 493ff0dbf5a1c184e952b9b31a2e72ace86cff29 Mon Sep 17 00:00:00 2001
From: mmarchegiani <matmarcheg@gmail.com>
Date: Wed, 29 Mar 2023 12:04:18 +0200
Subject: [PATCH 17/24] Density plot

---
 scripts/plot/make_plots.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/scripts/plot/make_plots.py b/scripts/plot/make_plots.py
index 8cebfac7..3b565783 100644
--- a/scripts/plot/make_plots.py
+++ b/scripts/plot/make_plots.py
@@ -39,6 +39,7 @@ parser.add_argument('--split_systematics', action='store_true', help='Split syst
 parser.add_argument('--partial_unc_band', action='store_true', help='Plot only the partial uncertainty band corresponding to the systematics specified as the argument `only_syst`')
 parser.add_argument('--overwrite', action='store_true', help='Overwrite plots in output folder')
 parser.add_argument('--log', action='store_true', help='Set y-axis scale to log')
+parser.add_argument('--density', action='store_true', help='Set density parameter to have a normalized plot')
 parser.add_argument('-d', '--data_key', type=str, default='DATA', help='Prefix for data samples', required=False)
 
 args = parser.parse_args()
@@ -73,6 +74,7 @@ def make_plots(entrystart, entrystop):
         only_cat=args.only_cat,
         data_key=args.data_key,
         log=args.log,
+        density=args.density,
         save=True
     )
     plotter.plot_datamc_all(ratio=True, syst=True, spliteras=False)
-- 
GitLab


From 55fbc84bda99e3ff82c078017af4e71ea55827c3 Mon Sep 17 00:00:00 2001
From: mmarchegiani <matmarcheg@gmail.com>
Date: Wed, 29 Mar 2023 13:18:14 +0200
Subject: [PATCH 18/24] Passing density argument to Shape constructor

---
 pocket_coffea/utils/plot_utils.py | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/pocket_coffea/utils/plot_utils.py b/pocket_coffea/utils/plot_utils.py
index 3287b37c..06298f79 100644
--- a/pocket_coffea/utils/plot_utils.py
+++ b/pocket_coffea/utils/plot_utils.py
@@ -41,18 +41,19 @@ class Style:
 class PlotManager:
     '''This class manages multiple Shape objects and their plotting.'''
     def __init__(self, hist_cfg, plot_dir, only_cat=[], style_cfg=style_cfg, data_key="DATA", log=False, density=False, save=True) -> None:
-        self.datamc_objects = {}
+        self.shape_objects = {}
         self.plot_dir = plot_dir
         self.only_cat = only_cat
         self.data_key = data_key
         self.log = log
+        self.density = density
         self.save = save
         for name, h_dict in hist_cfg.items():
-            self.datamc_objects[name] = Shape(h_dict, name, plot_dir, only_cat=self.only_cat, style_cfg=style_cfg, data_key=self.data_key, log=self.log, density=False)
+            self.shape_objects[name] = Shape(h_dict, name, plot_dir, only_cat=self.only_cat, style_cfg=style_cfg, data_key=self.data_key, log=self.log, density=self.density)
 
     def plot_datamc_all(self, ratio=True, syst=True, spliteras=False):
         '''Plots all the histograms contained in the dictionary, for all years and categories.'''
-        for name, datamc in self.datamc_objects.items():
+        for name, datamc in self.shape_objects.items():
             datamc.plot_datamc_all(ratio, syst, spliteras, save=self.save)
 
 
-- 
GitLab


From 486d1f71e57ec303debefec10c121e33375fb602 Mon Sep 17 00:00:00 2001
From: mmarchegiani <matmarcheg@gmail.com>
Date: Wed, 29 Mar 2023 13:54:34 +0200
Subject: [PATCH 19/24] Improve assertion error

---
 pocket_coffea/utils/plot_utils.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pocket_coffea/utils/plot_utils.py b/pocket_coffea/utils/plot_utils.py
index 06298f79..d5f4c67f 100644
--- a/pocket_coffea/utils/plot_utils.py
+++ b/pocket_coffea/utils/plot_utils.py
@@ -75,7 +75,7 @@ class Shape:
         self.density = density
         assert type(h_dict) == dict, "The Shape object receives a dictionary of hist.Hist objects as argument."
         self.group_samples()
-        assert self.dense_dim == 1, f"Histograms with dense dimension {self.dense_dim} cannot be plotted. Only 1D histograms are supported."
+        assert self.dense_dim == 1, f"The dimension of the histogram '{self.name}' is {self.dense_dim}. Only 1D histograms are supported."
         self.load_attributes()
 
     @property
-- 
GitLab


From 48ecf9edf99a5c0652759a6d4776230c0953759f Mon Sep 17 00:00:00 2001
From: mmarchegiani <matmarcheg@gmail.com>
Date: Wed, 29 Mar 2023 15:12:08 +0200
Subject: [PATCH 20/24] Fix axes management

---
 pocket_coffea/utils/plot_utils.py | 36 +++++++++++++++----------------
 1 file changed, 18 insertions(+), 18 deletions(-)

diff --git a/pocket_coffea/utils/plot_utils.py b/pocket_coffea/utils/plot_utils.py
index d5f4c67f..dea08038 100644
--- a/pocket_coffea/utils/plot_utils.py
+++ b/pocket_coffea/utils/plot_utils.py
@@ -322,17 +322,17 @@ class Shape:
             handles = handles_new
             self.ax.legend(handles, labels, fontsize=self.style.fontsize, ncols=2, loc="upper right")
 
-    def plot_mc(self):
+    def plot_mc(self, ax=None):
         '''Plots the MC histograms as a stacked plot.'''
-        if not 'fig' in dir(self):
-            self.define_figure(ratio=False)
+        if ax:
+            self.ax = ax
         self.stack_mc_nominal.plot(ax=self.ax, color=self.colors, density=self.density, **self.style.opts_mc)
         self.format_figure(ratio=False)
 
-    def plot_data(self, year):
+    def plot_data(self, year=None, ax=None):
         '''Plots the data histogram as an errorbar plot.'''
-        if not 'fig' in dir(self):
-            self.define_figure(year, ratio=False)
+        if ax:
+            self.ax = ax
         y = self.stack_sum_data.values()
         yerr = np.sqrt(y)
         integral = (sum(y) * self.xbinwidth)
@@ -342,15 +342,15 @@ class Shape:
         self.ax.errorbar(self.xcenters, y, yerr=yerr, **self.style.opts_data)
         self.format_figure(ratio=False)
 
-    def plot_datamc_ratio(self, year):
+    def plot_datamc_ratio(self, year=None, ax=None):
         '''Plots the Data/MC ratio as an errorbar plot.'''
         self.get_datamc_ratio()
-        if not 'fig' in dir(self):
-            self.define_figure(year, ratio=True)
+        if ax:
+            self.rax = rax
         self.rax.errorbar(self.xcenters, self.ratio, yerr=self.ratio_unc, **self.style.opts_data)
         self.format_figure(ratio=True)
 
-    def plot_systematic_uncertainty(self, ratio=False):
+    def plot_systematic_uncertainty(self, ratio=False, ax=None):
         '''Plots the asymmetric systematic uncertainty band on top of the MC stack, if `ratio` is set to False.
         To plot the systematic uncertainty in a ratio plot, `ratio` has to be set to True and the uncertainty band will be plotted around 1 in the ratio plot.'''
         ax = self.ax
@@ -373,7 +373,7 @@ class Shape:
         if ratio:
             ax.hlines(1.0, *ak.Array(self.xedges)[[0,-1]], colors='gray', linestyles='dashed')
 
-    def plot_datamc(self, year=None, ratio=True, syst=True):
+    def plot_datamc(self, year=None, ratio=True, syst=True, ax=None, rax=None):
         '''Plots the data histogram as an errorbar plot on top of the MC stacked histograms.
         If ratio is True, also the Data/MC ratio plot is plotted.
         If syst is True, also the total systematic uncertainty is plotted.'''
@@ -383,11 +383,13 @@ class Shape:
             if self.is_data_only:
                 raise Exception("The Data/MC ratio cannot be plotted if the histogram is Data only.")
 
-        if not 'fig' in dir(self):
-            self.define_figure(year, ratio=ratio)
+        if ax:
+            self.ax = ax
+        if rax:
+            self.rax = rax
         if (not self.is_mc_only) & (not self.is_data_only):
             self.plot_mc()
-            self.plot_data()
+            self.plot_data(year)
             if syst:
                 self.plot_systematic_uncertainty()
         elif self.is_mc_only:
@@ -395,10 +397,10 @@ class Shape:
             if syst:
                 self.plot_systematic_uncertainty()
         elif self.is_data_only:
-            self.plot_data()
+            self.plot_data(year)
 
         if ratio:
-            self.plot_datamc_ratio()
+            self.plot_datamc_ratio(year)
             if syst:
                 self.plot_systematic_uncertainty(ratio)
 
@@ -604,6 +606,4 @@ class SystUnc:
         self.ax.set_xlabel(self.xlabel)
         self.ax.set_ylabel("Counts")
         self.ax.legend()
-        #plt.show()
-        #plt.close()
         return self.fig, self.ax
-- 
GitLab


From 5b58cc786bc9394bb4eb0647c7abfc3cefadf39e Mon Sep 17 00:00:00 2001
From: mmarchegiani <matmarcheg@gmail.com>
Date: Wed, 29 Mar 2023 16:04:33 +0200
Subject: [PATCH 21/24] Fix lumi label in MC

---
 pocket_coffea/utils/plot_utils.py | 9 ++++++---
 1 file changed, 6 insertions(+), 3 deletions(-)

diff --git a/pocket_coffea/utils/plot_utils.py b/pocket_coffea/utils/plot_utils.py
index dea08038..809b3caf 100644
--- a/pocket_coffea/utils/plot_utils.py
+++ b/pocket_coffea/utils/plot_utils.py
@@ -272,7 +272,10 @@ class Shape:
             self.fig, self.ax  = plt.subplots(1, 1, **self.style.opts_figure["datamc"])
         hep.cms.text("Preliminary", fontsize=self.style.fontsize, loc=0, ax=self.ax)
         if year:
-            hep.cms.lumitext(text=f'{self.lumi[year]}' + r' fb$^{-1}$, 13 TeV,' + f' {year}', fontsize=self.style.fontsize, ax=self.ax)
+            if not self.is_mc_only:
+                hep.cms.lumitext(text=f'{self.lumi[year]}' + r' fb$^{-1}$, 13 TeV,' + f' {year}', fontsize=self.style.fontsize, ax=self.ax)
+            else:
+                hep.cms.lumitext(text=f'{year}', fontsize=self.style.fontsize, ax=self.ax)
 
     def format_figure(self, ratio=True):
         '''Formats the figure's axes, labels, ticks, xlim and ylim.'''
@@ -329,7 +332,7 @@ class Shape:
         self.stack_mc_nominal.plot(ax=self.ax, color=self.colors, density=self.density, **self.style.opts_mc)
         self.format_figure(ratio=False)
 
-    def plot_data(self, year=None, ax=None):
+    def plot_data(self, ax=None):
         '''Plots the data histogram as an errorbar plot.'''
         if ax:
             self.ax = ax
@@ -342,7 +345,7 @@ class Shape:
         self.ax.errorbar(self.xcenters, y, yerr=yerr, **self.style.opts_data)
         self.format_figure(ratio=False)
 
-    def plot_datamc_ratio(self, year=None, ax=None):
+    def plot_datamc_ratio(self, ax=None):
         '''Plots the Data/MC ratio as an errorbar plot.'''
         self.get_datamc_ratio()
         if ax:
-- 
GitLab


From 7f2b6ce6f9368ab08322fdd352ddb702c904853f Mon Sep 17 00:00:00 2001
From: mmarchegiani <matmarcheg@gmail.com>
Date: Wed, 29 Mar 2023 16:52:29 +0200
Subject: [PATCH 22/24] Fix CMS label

---
 pocket_coffea/utils/plot_utils.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/pocket_coffea/utils/plot_utils.py b/pocket_coffea/utils/plot_utils.py
index 809b3caf..de39bc9c 100644
--- a/pocket_coffea/utils/plot_utils.py
+++ b/pocket_coffea/utils/plot_utils.py
@@ -270,7 +270,8 @@ class Shape:
             self.fig.subplots_adjust(hspace=0.06)
         else:
             self.fig, self.ax  = plt.subplots(1, 1, **self.style.opts_figure["datamc"])
-        hep.cms.text("Preliminary", fontsize=self.style.fontsize, loc=0, ax=self.ax)
+        if self.is_mc_only:
+            hep.cms.text("Simulation Preliminary", fontsize=self.style.fontsize, loc=0, ax=self.ax)
         if year:
             if not self.is_mc_only:
                 hep.cms.lumitext(text=f'{self.lumi[year]}' + r' fb$^{-1}$, 13 TeV,' + f' {year}', fontsize=self.style.fontsize, ax=self.ax)
-- 
GitLab


From 25bd845eacd683d195587b7cadbd774d9270de7c Mon Sep 17 00:00:00 2001
From: mmarchegiani <matmarcheg@gmail.com>
Date: Wed, 29 Mar 2023 22:59:19 +0200
Subject: [PATCH 23/24] Update notebook for tests

---
 notebooks/plotting/test_DataMC.ipynb | 514 +++------------------------
 1 file changed, 53 insertions(+), 461 deletions(-)

diff --git a/notebooks/plotting/test_DataMC.ipynb b/notebooks/plotting/test_DataMC.ipynb
index b9ea0f6b..25af1f07 100644
--- a/notebooks/plotting/test_DataMC.ipynb
+++ b/notebooks/plotting/test_DataMC.ipynb
@@ -21,7 +21,7 @@
     {
      "data": {
       "text/plain": [
-       "<pocket_coffea.utils.plot_utils.Shape at 0x7f61abd440d0>"
+       "<pocket_coffea.utils.plot_utils.Shape at 0x7f81d4a64a00>"
       ]
      },
      "execution_count": 2,
@@ -48,19 +48,21 @@
      "data": {
       "text/plain": [
        "['_categorical_axes',\n",
+       " '_stack_sum',\n",
        " 'build_stacks',\n",
        " 'categorical_axes_data',\n",
        " 'categorical_axes_mc',\n",
        " 'categories',\n",
        " 'data_key',\n",
        " 'define_figure',\n",
-       " 'define_samples',\n",
        " 'dense_axes',\n",
        " 'dense_dim',\n",
+       " 'density',\n",
        " 'format_figure',\n",
        " 'get_axis_items',\n",
        " 'get_datamc_ratio',\n",
        " 'get_systematic_uncertainty',\n",
+       " 'group_samples',\n",
        " 'h_dict',\n",
        " 'is_data_only',\n",
        " 'is_mc_only',\n",
@@ -79,7 +81,6 @@
        " 'samples',\n",
        " 'samples_data',\n",
        " 'samples_mc',\n",
-       " 'stack_sum',\n",
        " 'stack_sum_data',\n",
        " 'stack_sum_mc_nominal',\n",
        " 'style',\n",
@@ -252,7 +253,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "id": "23a8834c",
    "metadata": {},
    "outputs": [
@@ -260,19 +261,19 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:207: RuntimeWarning: invalid value encountered in true_divide\n",
+      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:253: RuntimeWarning: invalid value encountered in true_divide\n",
       "  self.ratio = num / den\n",
-      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:210: RuntimeWarning: invalid value encountered in true_divide\n",
+      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:256: RuntimeWarning: invalid value encountered in true_divide\n",
       "  self.ratio_unc = np.sqrt(num) / den\n",
-      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:449: RuntimeWarning: invalid value encountered in true_divide\n",
+      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:526: RuntimeWarning: invalid value encountered in true_divide\n",
       "  return np.where(self.nominal != 0, self.up / self.nominal, 1)\n",
-      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:453: RuntimeWarning: invalid value encountered in true_divide\n",
+      "/work/mmarcheg/PocketCoffea/pocket_coffea/utils/plot_utils.py:530: RuntimeWarning: invalid value encountered in true_divide\n",
       "  return np.where(self.nominal != 0, self.down / self.nominal, 1)\n"
      ]
     },
     {
      "data": {
-      "image/png": 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0aVMRgFirVi2F+6Ojo6X+vr6+CseOHz8uHbt165bYrVs3teeeMWOGmJmZKf7yyy9q16k2atRITE9PV4rN1dVVBCB6enoq3B8fHy/13bZtm+jr66uy/pDsa8WKFWp/BosXLxbNzMw0Pn+WlpYqawTJP0dHjhwRvb29Ffp16NBBzMzMlKaLuru7q41DFEWxX79+IgDRzMxMfP78uca2RET0eRo+fLgIQGzcuLHOfWW14kqXLq2x3Z07d6T/VXv27NF6/BcvXkj9NC3PWLZsmc4zCtS975N/7/fxTJfnz5+LEyZMECtUqCCamJiINjY2YosWLcQ1a9aonY1y4cIFcdOmTRq/bt++rbJvfs10iYuL0/i+RNOMBfk6iepqKYqiqFA7MTo6Otcx52amy6tXr8Qff/xRrFOnjlisWDHRwsJCrFmzpjh27Fjx3r17avtlZGSI5cqVEwGIJUqU0PhzuX79uhTf5MmTdYovO6dPn5bGVldKQUY2U6RevXrSfWfOnJH6//bbb2r7zps3T2p34cIFpeO5ed3k5e92fioConyg7tMKXT8p0ZePZ7pkZGTg+vXr8PDwkO77uBJ3mTJlUK5cOZ3OM3/+fAQHB2tdvTw5ORnXrl3DtWvXsHbtWgBZlb07duyIcePGwd7eXqfzA4o7F2kz0yU4OBiLFi0CAJiamkq7Sj148AAfPnwAAGzcuBFXrlyBIAho1aoVatasidatW0tjBAUFoWXLllJV/6pVq8LDwwPOzs6IiIjArl27EBcXh6CgIPTr1w9nzpxR+NQrPT1dqqT+ccyybDeguI30x8eGDh2KGzduwM3NDV5eXjA2Noa/v7+0ZfmSJUvw5MkTbNmyBSVKlEDHjh1RtWpVBAYGYs+ePQCyXgNHjhxB586dpXHfv3+Pe/fuqTy/fPX3pUuX4vr16zA2Nkb79u3h5uaGtLQ0/Pnnn9IWe99//z2GDx+utA362rVr8d133wHIqoTfvXt3VKtWDUZGRggODsb+/fuRlJSEd+/eYeTIkbh9+7ba52HWrFm4cuUKjI2N8dVXX6F69ero2rUrBEGAk5MTQkJCEBUVBXUCAwPh7+8PAJgyZQpKly6tti0REX2+ZDNdKlWqBCBrFvPDhw8RExOD0qVLo3LlyjAwUD2JXvZ+wMHBQeM55D/F1jSb82MlSpRAkSJFkJ6erjRLWZ78sbz6f3br1i20bt0ar1+/lu5LSUnB+fPncf78eWzYsAFHjhxR2nGoWbNmaNasWZ7EpC9WVlZ49+6dwn1z587FvHnzsu3r4uIitdP03MveIxkaGsLGxiYX0ebOsWPH0K9fP6VdTIODgxEcHIxVq1bht99+w5QpU5Rm7RgYGKBv375YsGABYmNjcebMGYX3yfLycteiV69eSbezu4axt7fHixcvFHYSkr1nBoC2bduq7du+fXv88MMPALKuFz5+HefmdVOYfrdzpaCzPvRlkN/tRf5LX+s1VdE00yUzM1MsU6aMwv1z585V6N+pUyeF47169RJFUf0nHqpmuohiVkXyGTNmKBSqyslX0aJFxdWrV+tUlTstLU0sWrSoCGQVnsrO4cOHxbJly0rn/Omnn6RjW7duVYinZs2a4tWrV5XGeP36tVRAzMLCQtyyZYvSbJFXr16J1atXV/tp1u3bt6Vja9asUTgmv3PRx7MuevbsKR0zNDRUer7ev38vVqpUSeFx9OzZU3z9+rXCOJMmTZKO//rrrwrH5F/LO3bsUDi2YMEChbHd3NzEO3fuKLSJjY1VeI4/Lhb45s0baT2zs7Oz+OjRI6XnODQ0VCqODBWfEMg/RwDEFi1aqPxEpkOHDtJzpWpGjyiKYuvWrUUAYsmSJcWEhASVbYiI6PMn+981cuRIccSIEVJ9DtmXvb29+Msvv4iJiYlKfdu1aycCWQX9NZGf6fL999/rFJ9sViYA8Z9//lE6HhgYKP1/bdSokdbjhoWFKeyCU7JkSalgsKrdi5ycnEQAYpMmTcRff/1V3LZtmzh+/HjRzs5OatOkSRO1/3dzoiB3L5J/X6zNLjSa3L17V3q/3LVrV73Hp+1Ml//++0+aBW1paSl+99134ubNm8UtW7aI48aNU5iJLJsR/rEbN25IbUaMGKH2XLKal+XKldP7zjsPHjyQZkm9fftWbbuEhATpMck/7/I7Br1580Zt/9jYWLXXU+ro8rrJq9/t/MSkC+UL+Yr38l/yU9j0TVPSRRRFsXfv3gr3d+zYUeqbmZkp2traKhz//fffRVHUPekiI6vy3a9fP6WxdflatGiR1s/BrVu3pH6urq7i8uXLlb4WL14sjhkzRmzYsKHCedq2bavwz3vixInSsdKlS4sxMTEqzzly5EgpSXT+/Hm1sckvBfp4uqD8FNSAgACFY7IlQ2XKlFEa09nZWeq3dOlSlecdO3asQjJCVTG/s2fPSm3Wrl2rcGzJkiXSsQcPHigck/+nUL58ebX/4KZPny61u3btmsKxdevWScdUFSyTadu2rfQm92Pyy6pq1aql9p+ZfHE0VUvZ5JfYrV69Wm0sRET0eUtMTNT6fUr9+vWV3iP873//U/t/XZ78Rd7XX3+tU4yvXr0SK1euLAJZBUGHDh0qbt68Wdy+fbs4fvx4acvckiVLKv3/1oa2hXSBrI0XPk6qREREiLVq1ZLa/PnnnzrHoM6nmnS5e/euuH37dnHZsmVi//79pQ8Ky5QpI4aHh+s9Pm2SLhkZGdIy8ho1aogvX75UavP06VOp+GzRokVV7tqTmZkpVqlSRQTULzGS36lT30uLdDFjxgwpjuXLl0v3f/PNNyKQVYQ3IyNDbf/09HSp5IC6zUk+psvrJq9/t/MDky6UL9TVdKlUqVKenTO7pMvixYsV7rexsZH+oISHhyv1k60PzGnSRV5GRoZ448YNce3ateLo0aPFRo0aZVu/Q/ZVpEgRMSIiQqvzbNiwIUeJnZEjR4opKSkKYzVv3lw6fuzYMZXne/bsmbQd94wZMzTGJr++c+DAgQrHRo8eLQIQjY2NleJwdHQUAeWdDWJiYqTxatasqfbTAvntCj+ehSKzf/9+qc2///6rcOzrr78Wgaxt8z7+ByT7hwBAvHz5strH/uOPP0rtYmNjFY6FhoaKZ86cEc+dO6fxEw/ZP/JOnTopHZM9R4aGhmJwcLDaMX799Ve1yZ+MjAyxfv36IgDRxcWlQN7IERFR4RAcHKzwPmHAgAHi7du3xcTERDEsLEzcunWrwixO+Q+yRFFx9yJ3d3eVn5qfPn1a+rQagNi6dWud43zz5o341VdfqX1/U69ePTEyMjJHz4G2SZfKlSurncUi/zx6eHjkKA5VPtWky9SpU5V+Ru3atRNfvHiRJ/Fpk3Q5evSo1F5T3Rb5D5RlH8x+TD6Z8fH7SVEUxd9++03pOiM/ZWZmiqtXr5ZiKFmypEKNS9kMcmtr62zHsra2FgGIffv21ercur5u8vJ3Oz+wpgvlixIlSqi8/8mTJ0hNTYWxsXE+R6Rc1+XNmzd48OABqlatqlTPxcTEBHXr1tXbuQ0MDFCvXj3Uq1dPui89PR1BQUE4d+4cDhw4gAsXLqjsm56ejo0bN2LWrFnZnke+nosmRYsWhYODA7y8vDBs2DDUr19f4XhmZiZu3rwJIGstd5s2bVSOs3HjRmk3nyJFimDFihVqz5mSkiLddnJyUhl3nTp1FF4br1+/ltZ4fxyjfD2VIUOGqKyKD2SttQay6rFUr15dZRv5Ginq6sa4ubkprF1/+/attPbVzc0NjRs3Vjm2fAwVK1ZUWq9ctWpVVK1aVW3flJQU+Pv7SztMNWzYUOG4/HPUsmVL1KhRQ+1Y8s97VFSUQv2cPXv2SDtI/fbbbyhShP8uiIi+VI8fP5bqj/3vf//DrFmzpP+zlSpVQqVKldC5c2c0atQI9+7dwz///IPz58+jRYsWAIDGjRvjm2++wapVq3Dt2jXUqFEDI0eOhKurK2JjY3H+/Hn4+/vD0NAQRkZGSEtLU7sDpDoZGRlYtmwZLl68qLbNrVu3sGjRIsydOxempqY5fDY0mzRpEgwNDVUeq1GjBrp27YoDBw4gODhYb+fUtnbgp+D48eOYMGEC1qxZA2tr63w//9GjRwFk1VR0cXFR26527dooX748Hj9+jPPnz0u1+OT169dPer++a9cupbousnou+t61SBuPHz/GpEmTpJ2TTExMsGfPHpiZmUltEhISAGRdJ2RH9vuky65j2iosv9u5wXfRlC9k2/CGhoYq3J+Wloa7d+8WyLbRderUQdGiRZGUlCTdd/nyZZVJlwYNGuR5YqhIkSKoX78+6tevj8mTJ+PatWvo0aOHyiKnly5d0mpM2UWzIAh4+/YtLC0tcxTbgwcPpO2Te/bsqTahIStACwAzZszQenz5i/+UlBQp6ZHTIrqqtrQDgA8fPiAkJARAVkJCHVnS5+OkyIcPH9QW0ZUlpQCgb9++ascWRVEaX1Nh48TERNy/fx8PHz7Ew4cPER4ejjt37iAwMBCpqalSu4//Scs/Dz179lQ7PqCcdJFJS0vDTz/9BABo3ry50tbcRET0ZencubNCgU1VrKyssHjxYrRv3x5A1kWmLOkCZCXw379/jz///BPPnz+Hr6+vQn9jY2Ns2bIFI0aMQFpaGiwsLLSOTxRFDB06FH/++ScAoE2bNvj+++9Ro0YNGBkZITQ0FMuXL8fOnTuxePFihIaGYv/+/UqF7PUhu4vnhg0b4sCBA3jz5g3i4uIKJLFQWPz666+YN28eXr9+jfv372PZsmXYs2cPdu3ahfv37+Pq1at58jPSRPZ+7tatW2rf737s5cuXKu93dXVF7dq1cevWLezbtw+rVq2SkokvXryQrjd69+6t9blyKyEhAfPmzcPixYulD0BtbGywbds2NG/eXKGtra0tACgVE1YlLi5OGkufCtPvdm6oLjFOlAc+/kWWOXz4sM5jDRgwALa2tgpfH8+WyI6RkZHSLAHZvvH//fefwv2aZi2oc/HiRaUv2QwHbbi7uyskMeSp++MuTz55UbVq1RwnXADFC/kOHTqobPP69WuNVcU1kf/Z3b59G2lpaQCUZ7Nok3QpWrSo2hksN2/elGbiqEt4yCdFPj5/UFCQ1F9T0kddhXoAiIyMRHR0tNoYbt++jTFjxqBkyZKoV68eevfujWnTpmHv3r0wMDDApEmT0K5dO6m9pudI3c9KRr6SvXzSZePGjdKsnQULFuTbGwEiIvq0tWnTRvqUWf7/EQBYWFhgy5YtOHLkCPr164dq1arBxMQEZcqUweDBgxEUFIQuXbpIH/J8vLuPJgcPHpQuyoYPH47jx4/jq6++QqlSpWBjY4OmTZvC398fv/zyC4CsnWnWr1+vj4esxNnZWeNx2e5PAPDw4cM8ieFTIggCSpYsiebNm2P37t0YN24cgKykx19//ZXv8cTExOjcRzYjRJV+/foBgLSLkcyBAwek23369NH5nDlx4sQJ1KhRA7/++quUcOncuTPu3LkjJUvlyXZN/fDhg8IHfh9LSkqSkrJlypTRa8yF6Xc7NzjThfJNq1atsG7dOqX7t2zZgmnTpmm9fCE9PR3//POP0h+4nHxS0LRpU4UpmZcvX0ZiYqJScqRJkyY6j925c2dpi0SZkiVL4uXLl1pfxLq7u8PCwkJ6A6KLW7duScmLjxMEupK9cRIEQWFJlLygoCDp9tatWzFo0KAcnUvTFteyOMqUKaO0fbbsWL169dS+luTHVvdJVFRUlJTUyslMG1NTU7VJn49jkB9fFEXMnTsXP//8M0RRhKurK3r37o3GjRujXr16sLOzk143sk8OK1eurPSJgiyOkiVLwtHRUW0cQNaWerJp3LKky4cPH+Dn5wcg603Ax4lJIiIidQwMDFC5cmUEBwcjNjZWZZv27durvMADgIiICOm2pqW2H9u4cSOArG2GFy9erLbdDz/8gFWrVuHFixfYuHEjvv32W63PoS11S4tkMjIypNv8UEPZzz//jOXLlwMAzp8/jyFDhuTr+dPT0wFkvUfTZik/oHn5Td++faXtlHfv3i0t0ZctLXJyctI481kfUlJSMHHiRKxZs0a6r3bt2li4cCG8vLzU9pN/rx0XF4dSpUqpbCeb5QLof7vmwvS7nRtMulC+6datG+zt7ZVmaYSHh2PlypWYMGGCVuP8+++/KjPKVapU0Tmmj5MpoaGhOHnypPQHVyYnM13KlCmjlHR59eoVwsLCtI713bt3SExMVLrfwcEh276ypUWA8mwIXcku5F1dXdVO933x4oV0u3jx4jk+lyxuc3NzpTdcsjg+fjxv3rzB48ePAWhesnPt2jUA0DgzSpukj5WVFSpWrKjyWL169TSuQ5eNL6vrI7Nx40ZpSc/SpUsxduxYlW/cMjIypKmvqhJH8s9Rdm/mDAwM4OjoiEePHiEyMhIAsGTJErx8+RJGRkaYO3euxv5EREQfk72HKlasmM595T/AqVmzptb9wsPDAWh+nwJkXbi5ubnh8OHD0oxOfXv8+LHGZfPys1tkyze+BFOmTEFkZCTq1auH77//Xm07Ozs72NjY4M2bN3j+/Hk+RphF9mFWUlKSwszinCpfvjwaNWqEK1eu4O+//8aqVauQmJgozXrJ66VFmZmZGDx4MHbt2gUga8bZokWLMGzYsGwThPJJl+DgYLVJF9nSfUD/SZfC9LudG1xeRPnGxMREmjL4salTp+L06dPZjvH8+XMMHTpU5bHu3bvrHJOqZMqSJUsUvq9YsaLaPzKayK9jljdo0CB8+PBBqzG2bNkiLWeRp01RX/nkQW5musgX0dWUvJGfXfL06VONYwYGBsLX1xe+vr5S0VcZWdz16tVT+GcQExMjjfvx45EvoqtpLbVsbHd3d7X/4GRtBEFQep7lEyvyRXQTEhKkwrbZfVohG79atWowNzcHkFVD5eeffwaQlZwcP3682n+EBw4ckGY+ffxY5Z8jbRNtsuRTVFQUYmJiMH/+fADAN998o5RYIiKiL1P79u1Ro0YNfPPNNxrbpaenSxdJ8stobt26Jf3fV1WrTmbHjh0Asj7c0GWWsax+w7t377JtK/vgLq9q9cl/6KWKbCl7iRIlFJb5fu5CQkKwc+dO+Pv7a2yXmJgozZywsrLKj9AUyGYrP3z4UOOSGlEUcfz4cRw7dkx6zasjW2L05s0bnDlzBv/88480G7137956ily16dOnSwmXmjVrIjg4GCNHjsw24QIoXm/8888/atsdOXJEuq3vOp2F6Xc7N5h0oXw1btw4hX/CMikpKejQoQPmzp2rMiGRmZmJnTt3wsPDQ6qHIc/a2ho9evTQOR5ra2ulpSDy6y2BnC0tAoD+/furvP/69eto1aoVDh8+rDKhAmRdPM+ZMwcTJ05UeVxToVb58wBZsxly8wcwLCxM+kOn6UK+du3a0u0TJ06obZeQkIA+ffrAz88PW7duVciIf/jwAXfv3gWQ8yK66pIeb968kT5d0pQYkT1vrq6uCnVwEhMTpULQmoroaho7MzNTZRHde/fuqV3SJC8yMhLTpk2TvtdURDcnSZe5c+ciISEBxYoVk2bdEBERubq6IiQkBBs2bNBYV27btm3SxaT8LIGiRYvCz88Pfn5+2LZtm8q+b968waFDhwBkfZCmy+5FtWrVApC1K+b9+/fVtouJiZH+V8r66NuiRYvUvr8LDAyULlDbtWv3RS0vkr3/Dw0NVfleXubUqVMQRRFA9h9k5YWvvvoKQNZMl7Vr16ptd+zYMbRr1w7t27dXWBanSp8+faSf9a5du6Qdg/J6aVFcXJz0YXKVKlVw9uzZbGsOyatRo4aUGDx48KDC0jiZjIwM6fe2fPnyGpfY50Rh+t3ODSZdKF9ZWlrC399f5T/SlJQU/PjjjyhZsiQ6deqEb775BmPGjEG7du3g7OyMfv36qc0k//rrrzmulv3x1tEfy2nSpXnz5ujatavKY9euXUPnzp3h7OyMNm3aYOjQoZg4cSIGDhwIT09PlClTBj/99JP0T0der1691NZVkXn//r2UIMhuOl52tL2Qd3Fxkf4w79+/H9u3b1dq8+TJE7Rs2VJKfnxcy0dToVttki7W1tZqZ2fIf/KkqYiurN3HbeSL6GoqXqvpn2dYWJiUhZdvJ78jxNWrV5V+7hkZGdi/fz8aNWqkMGWyWrVqauPQdnaTLOny/v17aYvv6dOnf1FTnomISDPZhz1paWno37+/yp2Mbt68KS0bKV26tPTpPpB1wSdbWv3rr78qXaSmpKTAx8cHSUlJMDAwwPTp03WKz9vbW7o9cOBAlfVk3r9/D29vb+nDvcGDB+t0Dm3du3cPkyZNUrpAffz4Mb7++mvp+8JWcyKvyT4oSk5OxqRJk6TknLynT59Kz4uxsbFWHzLqW48ePaQZ7r6+vgozx2VevnyJ8ePHA8h6rWvaEVPWxtPTE0BWLRfZttR5vbRo27ZtUsHcxYsX63ytJAiCVP7h0aNH0mxoefPnz5fe10+YMEHvj6cw/W7nBmu6UL5zc3ODv78/BgwYIP0hkJeYmKhxCtvHRo8ejeHDh+c4niZNmqgs8Ct/PCcEQcCqVasQEhKiNln07NkzpeU1mlSoUEEqLqaJfPJCX0V0DQ0NFWazfKxIkSJYu3atVBxv0KBB2Lx5Mxo2bAhTU1Pcvn0b+/btk9Z6T5w4UennJv+PTV1iw8HBQW0R3QYNGqj9Yy+r5yJrp0p4eLhUhycnOydZWVmpnMklo65eTPXq1VGkSBGkp6fj4MGD8PDwgJeXF4yMjBAeHo5z585J/9DMzMykOj+jR4/GoEGDpF2K5AsNa1s9Xr62TVpaGhwdHaU3EkREREDWNsfffPMNVq1ahbNnz6Jq1aoYNWoUKleujJiYGAQEBGDz5s3IyMiAIAjYtGmTtIuRzLJly9CuXTvEx8ejXr16mDhxImrUqIHnz59j3bp1CA4OBgDMmjULlStXVorB19dXKvQ+c+ZMhS2nW7VqhUGDBmHbtm24ceMGKleujBEjRqBmzZoQBAGhoaHYuHGjNEvH09NT4WJOXxwcHBAXF4elS5fixo0b6NKlCxwcHHDt2jVs27ZNumAcNWoUGjVqpPfza6Lp+csPffr0waxZsxAeHo6//voLt27dwqBBg1CxYkW8e/cOt27dwvr165GUlAQA8PPzK5DlV6ampli9ejV69OiBN2/eoEmTJhg6dCjc3d1haWmJ4OBgrF27Fq9fv4aBgQH++OMPrZbq9OvXD2fOnMGbN2+k+7TZtSg3P7eLFy8CyHoPn5GRgWPHjmXbx8bGRmEm9ejRo7FhwwaEhoZi+vTpuHPnDjp37ozMzEwcOHBAWrpUvXp1jBw5UuvYtFVYfrdzTSQqIBcvXhRLliwpAsjRl6Ghofjjjz+KGRkZKsf38PBQ2e/MmTMK7cLCwtSew9LSUkxPT1doP3PmTJVtZ86cqTKOFy9eiA0bNszx45R9ubm5iVFRUVo9t4sWLZL6LVu2TKs+6siex1q1amnVfunSpaKpqanax2Fubi7OmjVLzMzMVOrbv39/EYBobW2tdNzJyUkEIHbp0kXh/jdv3khj//jjj2rj6tKliwhAdHJyUttm+/bt0lhXrlxROObt7S0CEK2srJRic3FxEQGIX331ldqxRVEUx48fLwIQjY2NxZSUFIVjc+fO1fjzt7OzEw8dOiR27txZ4f4ZM2Zk+xxpcurUKYXxtmzZonVfIiL6cqSkpCj9D1L1vunvv/9WO8acOXNEAwMDtf2nTJmi8v2BKCq+/1L1nislJUWcPHmyaGRkpHZ8QRDEIUOGiPHx8To/ftn5Vb2P2LRpkwhAbNq0qXjgwAGxaNGiamPo37+/mJqaqvP5cyu7508f4yYlJWlse/fuXem9irovAwMD8ZdfflH7OshNfB9fA2iyYcMGja8lc3NzccOGDVqPFxMTIxYpUkTq7+TkpNVjzM3PzdPTU+frDQ8PD6VxHjx4IFaoUEFtn8qVK4uPHj3SKTZdXjd5/budH7i8iApM06ZNERYWhhkzZkgFRbVhYGCADh064Pr165g9e7ZCQdOcqFixIkqWLKnyWKNGjbTKXmtib2+Py5cvY926dTkqTOrk5IRVq1bh6tWrWs9ekF9Kk9siurIitdqOM378eAQFBWHkyJFo0KABzM3N4ejoiFatWmHmzJmIiIjAzz//rHJGiizuj3feiY2NxZMnT1TGIV9EV5taLZrayM5fpEgRpVk98kV05WN79+6dzkV0a9eurVTka9q0adi9ezeaNWsGOzs7GBoawsbGBi1btsTSpUvx6NEjdOrUCZMnT4aLiwuMjIxQuXJlabqqpudIE/lPkWrXro2BAwdq3ZeIiL4cxsbGOHjwIE6dOoWuXbvC1dUVRYsWRbFixVC3bl389NNPCA8P17ixwfTp03Ht2jX06tULlStXhomJCcqVK4f+/fvjwoULWLBgQY6XJxgbG2PhwoW4c+cOxowZg+bNm8POzg7FixdHo0aNMHToUFy7dg1//PFHnhZo7dKlCwIDAzF06FA4OjrCyMhIWjp/4MABbN++Xad6NZ8TV1dX3Lp1CwsWLEDHjh1RtWpVFC1aFE5OTmjbti2mTJmC0NBQ/PTTTwVe72bYsGG4d+8exo8fj6pVq8Lc3Fx6LU2YMAFhYWEYNmyY1uOVKFFC2i4ayPulRUDWrqn6ULlyZdy8eROzZs1CzZo1YWFhAQsLC9SuXRtz5sxBYGAgypcvr5dzqVJYfrdzQxBFFUUjiPLZu3fvcOrUKRw5cgSBgYF4/fq19IeiePHisLW1Rd26deHu7o6uXbvC0dEx2zE9PT1x7tw5pfvPnDkjXajK9OjRA/v27VNqO2PGDGlKn4z8ND952kz5E0URV65cwfHjx3Hz5k3cvXsX8fHxSEhIgCiKKFasGIoXLw5XV1fUrVsXbdq0QZMmTXKdWCJS59KlS2jWrBkA4Pjx4wpvCIiIiOjz0rx5c7Rv317nujlUsPhz+7Qx6UJE9IXKyMiAu7s7AgMD0aZNGxw/frygQyIiIqI8VL16dUybNk2hqC8Vfvy5fdpYSJeI6Au1fv16BAYGQhAElRXpiYiI6POQlpaGU6dO4enTpwrbeVPhxp/b54FJFyKiL9CtW7cwefJkAMDQoUM17kxFREREn7b58+dj165d+Pvvv2FnZ1fQ4ZCW+HP7PHB5ERHRF+L06dMICAhAVFQUdu7ciejoaJQpUwZ37tyBtbV1QYdHRERERPTZ4UwXIqIvxPr16+Hv7y99X6JECRw4cIAJFyIiIiKiPMItUYiIvhDp6ekwMzNDuXLlMHz4cAQEBKB+/foFHRYRERER0WeLy4uIiIiIiIiIiPIAZ7oQEREREREREeUB1nShPGNubo7k5GQYGhqiZMmSBR0OERERERERfeZevXqFjIwMmJqa4sOHDwUdDpcXUd4xNDREZmZmQYdBREREREREXxgDAwNkZGQUdBic6UJ5R5Z0MTAwQOnSpQs6HAXR0dEoVapUQYehgDFpp7DFJIoinj9/jjJlykAQhIIOR0Fhe64AxqStwhYTX+e6YUzaKWwx8XWuG8akncIWE1/numFM2ilsMb148QKZmZkwNDQs6FAAcKYL5SEHBwfpj3pUVFRBh6OgWrVquHv3bkGHoYAxaaewxZSQkAArKyu8ffsWxYoVK+hwFBS25wpgTNoqbDHxda4bxqSdwhYTX+e6YUzaKWwx8XWuG8akncIWU2G7DmUhXSIiIiIiIiKiPJBvy4sOHTqEy5cvw9DQEE2aNEGrVq1gamqaX6cnIiIiIiIiIspXeku6nDlzBps3b8bdu3dx/fp16X5RFNGvXz/s2bNHob2bmxsOHjwIe3t7fYVARERERERERFRo6CXp4ufnh1mzZgGAUrGaP/74A7t371bqExAQgHbt2iEoKEgfIRARERERERERFSq5rukSFBQEPz8/AFmzWlxcXBSOL168GABgb2+PK1eu4PHjx/Dx8QEABAcH4/Dhw7kNgYiIiIiIiIio0Ml10mXBggUAsma4nDx5EsHBwdKx0NBQ3L17F4IgYMyYMXB3d4eTkxM2bNgAJycnAMCmTZtyGwKRzsaOHVvQIShhTNopjDEVVoXxuWJM2imMMRVWhfG5YkzaKYwxFVaF8bliTNopjDEVVoXxuWJM2imMMRUmud4yuk6dOggODkbfvn3x119/KRxbtmwZJk6cCEEQ8OzZM5QpU0Y6NnHiRCxbtgy1a9fGzZs3cxMCFVKFbasuorxQmLdeJNIXvs7pS8DXOX0J+DqnL0Fhuw7N9UyXR48eAQBq1aqldOzChQsAABcXF4WECwCULVsWABAREZHbEIiIiIiIiIiICp1cJ12KFi0KAEhLS1O4Py0tDWfPnoUgCGjRooVSv9TUVABAZmZmbkMgIiIiIiIiIip0cp10qVSpEgAgMDBQ4f5Dhw4hNjYWANC+fXulfvfv3wcAlCtXLrchEBEREREREREVOrlOutSvXx+iKOLw4cO4ePEigKzZK8uWLQMAmJqaok2bNgp97t+/j71790IQBDg7O+c2BCIiIiIiIiKiQifXSZfJkyfDyMgImZmZ8PLywldffYVatWrh/PnzEAQB/fr1k5YghYeHY8qUKWjSpAkSExMBAEOHDs1tCEREREREREREhU6uky7lypXD/PnzAWTVaTl79ixCQ0MBANbW1vj111+ltqdOncLvv/+O+Ph4AICbmxu6d++e2xCIiIiIiIiIiAqdIvoYZMKECahatSqWL1+Oa9euwdDQEO7u7liyZAns7OyU2hsYGKBbt25YtWqVPk5PhdyrV69QrVo1lcfGjh3Lfd2JiIiIiIhIaytXrsTKlStVHnv16lU+R6OZXpIuANC2bVu0bdtWY5sOHTrgzp07qFy5MoyMjPR1aiqkBEEAAJQqVQp3794t4GiI8oaJiQlmzpwJExOTgg6FKM/wdU5fAr7O6UvA1zl9LjR9eF+2bFlERUVJ16MFTRBFUSzoIOjzJHuxOzg4IDIysqDDISIiIiIios9cYbsOzXVNlwoVKqBixYrYunWrTv327NmDChUqqNxOmoiIiIiIiIjoU5fr5UUREREQBAHv3r3TqV9ycjIiIiKQkJCQ2xCIiIiIiIiIiAodnZIuT58+RUREhMpjYWFhOH/+vFbjxMTEYO3atQCAlJQUXUIgIiIiIiIiIvok6JR02bRpE2bNmqVwn6w4zbJly7Bs2TKdTi4IAmrWrKlTHyIiIiIiIiKiT4HOy4v0WXfXysoK8+fP19t4RERERERERESFhU5JFx8fH3h6ekrfi6KIVq1aQRAEjB8/Ht26ddN6LFNTU1SrVg2Wlpa6hEBERERERERE9EnQKeni5OQEJycnlccqV64MDw8PvQRFRERERERERPSpy/XuRTNnzgQAuLu75zoYIiIiIiIiIqLPhd6SLkRERERERERE9H8MCjoAIiIiIiIiIqLPkV6SLhkZGZg1axYaNGgAU1NTGBoaav1VpEiuJ9sQERERERERERU6uc54ZGRkoFWrVrh48SIA/W4pTURERERERET6tW/fPkRFRak9XrVqVXh5eeVjRJ+vXCdd/vjjD1y4cAGCIEAURXh5eaFu3bowMzPTR3xERERE9AnhG3ki0hX/buS/pUuX4ty5c2qPe3t78znXk1wnXbZv3y7d3rdvH7p27ZrbIYmIiIjoE8U38kSkK/7doM9ZrpMu9+/fhyAI6NKlCxMuRERERERERIXc2bNnCzqEL0auky7v378HADRo0CDXwRARERHRp41v5IlIV/y7QZ+zXO9e5OzsDAB49epVbociIiIiIiIiIvps5Drp0rdvX4iiiDNnznDnIiIiIiIiIiKi/y/XSZfx48ejatWquHPnDnx9ffUQEhERERHRl83Z2RmCIMDHx6egQyEqFHx9fSEIAgRBwObNm7Xud/bsWanfp/j7tHnzZin+iIiIAhuDci7XNV2KFSuGY8eOoXv37pg9ezbu3r2LmTNnokaNGvqIj4iIiIgKmaCgIOzfvx8AMHHiRBQvXlyn45QlIiIC5cuXl77nrHH6nPHvBn2pcp10mTRpEgCgUaNGuH//Pv7++2/8/fffsLCwQMWKFbP9ZREEAadOncptGERERET6caRFQUeQMx3O59upgoKC4OfnBwDw8fFRefGk6TjRZ+dcQEFHkDMe9fPtVPy7QV+qXCddlixZAkEQAChm59+9e4egoCC1/QRBgCiKUl8iIiIiIiIios9JrpMuLVq0YOKEiIiIiEhHzs7OXFJERPSZy3XShXuqExEREREREREpy/XuRURERET0ZfDx8YEgCBgyZIh0X/ny5SEIAjw9PbM9rquUlBSsXr0abdu2RaVKlVC0aFFUqFABrVu3xh9//IH09HSN/TMzM+Hv748uXbrAwcEBJiYmcHZ2RuvWrbFt2zakpqaq7SvbPWjFihUAgEuXLqFbt26wt7eHqakpKlasiO+//x7v3r2T+ty6dQsDBgxAmTJlYGJigipVqmDAgAF49OiR2vN4enrm+PnJ6eOT7WRia2sLAEhNTcWKFSvQsGFDFC9eHBYWFqhRowamTp2KFy9e6BwXkbz8/rvxuUtLS8PSpUvh7u4Oa2trmJmZwcXFBd9++y0ePHiQb2OQ9nI904WIiIiISN/u37+PNm3a4OnTpwr3P378GI8fP8bJkyexZMkSXLx4EcWKFVPq/+rVK3Tv3h2XL19WuP/Jkyd48uQJTp48iVmzZuHIkSOoVKmSxljWrl2Lb775BpmZmdJ9jx49woIFC3Dq1ClcvHgRBw4cgLe3t0KiIywsDGFhYdi3bx8CAgJQvXr1nDwVKunr8b169QpdunTB1atXFe4PCQlBSEgI1qxZA39/f7Rv315vsRN9aRISEvDy5UtUqVIlV+O8ffsW/fv3x5UrVxTuf/DgAR48eIB169Zh2bJlGD16dJ6OQbph0oWIiIiItDJo0CDUr18fV65cwfbt2wEAvr6+KFGiBBwcHGBpaanxuLbevXuHrl27SgkXV1dXdOzYESVLlsTz58+xc+dOvHjxAsHBwfj222/x559/KvRPTExEq1atEBISAgDS7I8KFSrg4cOHOHnyJCIiIhAWFobGjRsjICAATk5OKmM5deoUDh48CHNzc3Tr1g2urq64c+cO/P39kZmZicDAQPTq1QsnTpxAWloaOnTogEaNGuHVq1fYunUr3r59i+TkZEyePBnHjh3T+TlXRV+PLyMjA3379sXVq1dhbm4OLy8v1K9fH2FhYTh9+jQiIyORkJCAbt264fLly3Bzc9NL/PRlya+/G4XV/fv30bFjRwiCgMDAQFhaWuZ4rGHDhuHGjRswNzfHV199hQYNGiA8PBxnzpzB06dPkZaWhjFjxsDGxgZ9+vTJszFIN7lOulSoUCFX/QVBwMOHD3MbBhVi0dHRqFatmspjY8eOxdixY/M5IiIiIsoJLy8veHl5wcLCQro48vb2hrOzs0IbTce1cezYMdy/fx8AMHr0aKxcuRIGBv+3Kv6XX36Bu7s7QkND8ddff2HdunUwNTWVjs+YMUNKSEydOhW+vr4Kx5OTk/Hzzz9j4cKFiImJweTJk7Fnzx6Vsezfvx+VKlXCP//8o/Apda9evdCjRw8AwJEjR2BiYoIDBw6gS5cuUpvJkyejZs2aeP/+PS5cuKC3nTv19fji4+Nx9uxZODo64tixYwrv196/f4/Bgwdj3759SE1NxejRo3Ht2jVuoEE6y6+/G4WVvb09MjMz8fjxY4wdO1YpSayLGzduoFy5cjhy5IjCzLnk5GQMHz5cev7Gjh2LTp06wczMLE/GKAxWrlyJlStXqjwWHR2dz9FoluuaLhEREVp/PXnyROX99HkrVaoU7t69q/KLCRciIiL62LVr16Tb06ZNU0i4AICFhQW8vb1haGgIAAgNDZWOxcfHY/Xq1QCAnj17Yt68eQoJCQAwNTXF/Pnz0b17dwDA3r17NX4IuHHjRqVlAd27d0eNGjWk73/44QeFhAuQNQPF29sbQNbslJcvX2p+4FrIi8d36NAhpQ/ILCwssGfPHtSsWRMAEBAQoLQcgaigDBkyBIIgaPXVsmXLAo3VysoKO3bsQJEiRbB161Zs3bo1V+MdOnRIaamiqakptm7dCg8PDwBATEwM/P3983SMgjZ27Fi115ilSpUq6PAU5Drp4u3tne1X9+7dUatWLekfgiAIGD58ONavX49169bl+kEQERER0edDlkwBgKioKJVtpk6divT0dKSnp6Nu3brS/UePHkViYiIAYMqUKWpnZgiCgEmTJknfX7hwQWW7qlWrokWLFiqPubq6SrdHjRqlso18MiMlJUVlG13o+/G1b98etWvXVnnMwMAAP/74o/T9wYMHcxo20RetYcOGmDNnDgBgzJgxOS5W26lTJ9SqVUvlMUEQMHPmTOl7dcsZ9TEG6SbXy4s2bdqkddt3795hyZIlWLBgAbZu3YqOHTuia9euuQ2BiIiIiD4j7u7u0u0ePXpgwoQJ8PHxQenSpbPt+99//0m3r1y5goCAALVtZckLAAgODlbZRlPxW9m0+xIlSsDe3l5jG33R9+OTLZFSR/69uqZzEeWngQMHolGjRlq1DQsLw7Jly/I4ouxNmTIFJ06cwMmTJ9GvXz/8999/MDEx0WmMbt26aTzu6ekJa2trxMXF4caNG3k2BukmXwvpWlpa4ueff4abmxs6d+6Mr7/+Gjdu3EDlypXzMwwiIiIiKsS6d++Orl274sCBA4iOjsb06dPx888/o3HjxmjevDk8PDzQsmVLGBsbK/WNjIyUbn/33XdanzMhIUHl/RYWFtn21aaNvuj78ZUvX15jP1NTU5QpUwbPnz/H8+fPtT4fUV7y8vKCj4+PVm3Pnj1bKJIuBgYG+PPPP1G7dm3cvHkT06ZNw+LFi3UaI7vfV0EQULFiRQQEBOD169d5NgbpJtfLi3KiQ4cO6NevH96/f6/zC42IiIiIPm+CIGDv3r1YvXo1HB0dAWTttHPx4kXMmzcP7dq1Q6lSpTB69GjExMQo9FWXXMhOTvvlN30/vjJlymTbt2zZsgCytpol+tJUrVpV6/ox2X2VKVNGSmQsWbIE//zzj06xaDPbT9YmKSkpz8Yg3RRI0gUAmjdvDoDrxIiIiIhImaGhIUaPHo0nT54gICAAM2bMgIeHhzQdPz4+HmvXroWrqyseP34s9ZMt5zExMUFGRgZEUdTqa+fOnQXyOHWl78cXGxub7TllBYDzc0YP0ZcgPj5ep/avXr3Kto2sDpa1tXWejUG6ydflRfKKFi0KAHqp4k5EREREnydBEODm5gY3NzcAWdua7t+/HytWrMClS5cQExODSZMmYd++fQAg7VqRkpKCyMhIlCtXrsBizwv6fnwRERFo1qyZ2uMpKSl49uwZAKBkyZK5OhfRp+jChQvIyMjQy1jx8fFo0aIFXr9+DW9vbwwcOFCn/o8fP5Z2F1JFFEWEh4cDgNq/DfoYg3RTYEkXWQV1W1vbggqBiIiIiAqhLVu2ICkpCWXLlkWnTp0UjpmamqJfv37o3bs3ateujZCQEFy+fFk67u7ujg0bNgAAbty4ofGi4d69e9KWqF9//TUqVqyYB49Gv/T9+E6dOoVBgwapHePo0aMQRREA0KBBg9yETvRJsrOz08s4oihi/PjxeP36NSpXrowVK1boPMahQ4c01rI5ceKEtJRQXaFhfYxBuimQ5UV///03Nm3aBEEQ4OLiUhAhEBEREVEhtWLFCowZMwY+Pj5qP2E2NDSUPryT32K6Xbt2MDDIeos7c+ZMpKenqz3Pzz//DD8/PyxcuFDt7kOFjb4f37Zt2xAREaHyWGZmJvz8/KTvO3bsmPPAib5wGzZswO7du2FsbIydO3fmaLne33//jZCQEJXHMjMz4evrK33fp0+fPBuDdJPrmS5Dhw7Vum1KSgpCQ0Nx69YtiKIIQRAwevTo3IZARERERAUkJiYGzs7OOT6uiqurKwICAhAbG4uFCxdi6tSpSm3+/fdfXLp0CQDQpEkT6X5HR0f06dMH/v7+CA4OxogRI7B8+XKFCxxRFPH7779jz549AIDevXvD3NxcpxgLir4fX3p6Orp06YJDhw7ByclJuv/Dhw/w9vZGUFAQAKBWrVpo2bJl3j0w+qLkxd+Nwuzu3buYMGECAGD+/PmoW7dujsfq1KkTjhw5AldXV+m+xMREDBkyRNpSvkGDBlIN1bwag7SX66TL5s2bIQiCTn1kUxT79OmDnj175jYEIiIiIspHpqam0m0/Pz8MGDAAVlZW6NChg1bHs9OnTx9s3boVADBt2jQcOnQILVu2hLW1Nd68eYMrV67g1KlTAAAjIyPpYkZmyZIlOHv2LF6+fInNmzfj1KlT8PLygouLC+Li4nD06FHcvn0bAFCpUiUsXLgw509GAdDn47O1tUVwcDDq1KmDtm3bombNmggLC8Pp06elWi5GRkbYsGGD0nv+zZs3Y8iQIQAADw8PnD17Nm8eMH0W8vrvRmGVnJyMfv36ISkpCZ06dcL48eNzNI6NjQ1KlSqF0NBQuLu7w8vLC25ubnj48CFOnTol/b6amZmp/H3V1xiku1wnXcqVK6fTD8PY2BjVq1dH586dpT/SRERERPTpaNCgAYoUKYL09HQcPnwYhw8fhoeHh3RxlN3x7HTs2BHTp0/Hr7/+iszMTFy6dEma1SLPwsICa9euVfo0tlSpUjh37hw6deqEsLAwPHv2DJs2bVLqX6tWLezatQslSpTIwbNQcPT5+Pbs2YMRI0YgLCwMO3fuVNrlqFixYvD392c9F8q1vP67UViFhYUhOjoaZcqUkUps5ETRokVx4MABtG/fHg8fPsT+/fuxf/9+hTa2trbYs2cPatWqlWdjkO5ynXRRtwaUiIiIiD5PFStWxM6dO+Hr64uwsDBYWFigQoUKWh/PjiAImDNnDgYPHoyFCxfi1q1bePr0KeLj4+Hg4AAnJye0atUKY8eOVbulaZUqVRAcHIxNmzZh9+7dCA4Oxtu3b1GuXDm4uLigT58+GDhwoEI9mE+Jvh6fk5MTgoKCsGTJEuzcuROPHj1CRkYGnJ2d0alTJ0yaNOmTqXdDhVte/90orGrWrIlbt24hMjIy15vIVK5cGYGBgViyZAl2796Nx48fQxAEVKhQAd26dcP48eOzTSLrYwzSjSDK1voQ6VnZsmURFRUFBwcHREZGFnQ4RERERATFZUGPHz/+rGpnEBEVtuvQAtm9iIiIiIiIiIjoc5fr5UUfe/nyJY4fP46AgAC8fPkSb9++hYWFBUqWLIkGDRqgbdu2KFu2rL5PS0RERERERERUqOgt6fLq1St899132L17NzIyMlS2Wb9+PQwMDNC7d28sWbIEJUuW1NfpiYiIiIiIiIgKFb0sL7p37x5q1qwJf39/pKenQxRF6cvS0lLh+4yMDOzcuRO1a9dGWFiYPk5PRERERERERFTo5DrpkpKSgk6dOuH169cQRREODg5YtGgRQkJC8P79e8THxyMpKQmhoaFYunQpypYtC1EUER0djU6dOiE1NVUfj0Mvjhw5gi5duqBs2bIwMTGBk5MT+vfvj4sXL3KMHI5BRERERERE9MUSc2nlypWiIAiigYGB2KFDBzE1NVVj+5SUFLFdu3ZSn1WrVuU2BLUyMzPFPn36iADEvn37qm2Xnp4ujhgxQgSg9mvGjBkaz8UxlDk4OIgARAcHh2zbEhEREVH+2LRpk/Se7vHjxwUdDhGRXhW269Bcbxnt5eWF06dPw8HBAXfv3oWlpWW2fd6+fYtq1arh5cuX8PT0xKlTp3ITglobN27E8OHDAQB9+/aFv7+/ynY///wzZs+eDQAoVqwYBg0aBCcnJ9y9exf+/v5ISUkBAKxbtw4jRozgGFqMARS+rbqIiIiIiIjo81borkNzm7Wxt7cXDQwMxK+//lqnfl9//bUoCIJYqlSp3Iag0r1790QzMzMpi69upkt4eLhoYGAgAhDLlSunlO0PCAgQLS0tRQBisWLFxPj4eI6RzRgyhS3DSERERERERJ+3wnYdmuuaLm/evAEAVKtWTad+rq6uAIC4uLjchqAkJSUF/fr1Q2JiYrZtFy9ejMzMTADAihUr4OzsrHDczc0Nv/zyCwAgISEBGzZs4BjZjEFEREREREREeiika21tDQC4e/euTv3u3bun0F+fpk2bhqCgIBQvXlxjO1EUsX//fgBA8eLF0b59e5Xt+vfvL90+ePAgx9AwBhERERERERFlyXXSpXr16hBFEadPn0ZCQoJWfRISEnD69GkIgqDzDJnsHD16FEuWLAEArF+/XmPbBw8eICoqCgDQpk0bFClSRGW7kiVLokGDBgCAy5cv48OHDxxDzRhERERERERElCXXSZcePXoAAF68eIH+/fsjLS1NY/v09HQMHDhQuriX9deHly9fwtvbGwAwfPhw9OrVS2P7p0+fSrdbtmypsa3seHp6OsLDwzmGmjGIiIiIiIiIKEuuky7Dhw9HhQoVAADHjh1DpUqVsGLFCoSFhUm73KSkpCAsLAwrVqxApUqVcOTIEQCAs7Ozxt1vdJGZmQlvb2+8fv0aVapUkWa7aBIdHS3dLlWqlMa2JUuWlG7LJxk4Bph0ISIiIiIiIlJB9foRHZiYmODw4cNo0aIFYmJiEBkZiQkTJkjHrays8PbtW4U+oijC1tYWhw8fhomJSW5DAAD8/vvv+Pfff2FkZIQdO3bA3Nw82z7ySYbsasvY2NhIt1+9esUx1IxBRERERERERFlynXQBgKpVqyI4OBgTJ07Enj17kJGRIR2Lj49XaGtgYICePXti6dKlKF26tD5Ojxs3bmD69OkAgHnz5qFevXpa9ZNPMmRXdFc+CSG/KxLHQLa7RImiqHW9H1VMTEz0lpwjIiIiIiKiwislJUVaNZMToijqMZrc00vSBchajrJjxw4sXLgQx44dw/Xr1xEdHY3379/DwsJCKr7arl07lC1bVl+nxbt376RaMq1bt8Z3332ndV/ZdtcAsp0ZI39cPsnAMbJPujx//hxWVlYa22gyc+ZM+Pr65rg/ERERERERfRrmzZsHPz+/gg5Db/SWdJFxcHDAsGHDMGzYMH0PrdK4ceMQFhYGW1tbbNmyBQYG2pepMTY2lm6/f/9eY1v5JVLysy44BrKdhVKmTBmEhoZqbKMJZ7kQERERERF9GX744QdMmjQpx/1dXV3x/PlzPUaUO7lOukRGRsLe3l7t9sJnzpzBrl27ULt2bbRr1w7Ozs65PaVkx44d2LJlCwBg06ZNOi9XMjMzk27HxcVpbCt/XH6WB8fIflaMIAgoVqyYxjZEREREREREuS0vIQiCHqPJvRztXhQZGYl58+bB3d0dzs7OGut1PH/+HGvXrsXYsWNRsWJFNG3aFCdPnsxxwDJxcXEYPXo0AGDs2LHo1KmTzmPY2toqjKeJfG0a+SKyHENxDCIiIiIiIiLKonPSZfny5ahatSp++uknBAQEaF2kRhRFiKKIK1euoG3bthg5ciTS09N1Dljm7du3UrJn5cqVEARB5ZfMzp07pftks20qV64sHX/x4oXG8718+VK6XaVKFek2x1Acg4iIiIiIiIiy6JR0+fHHHzFx4kQkJSVJyZZ69eppnPrTpk0brFq1Cr1790aJEiWk5MvGjRsxdOjQ3EWfS9WqVZNunzlzRmPb06dPA8jafUk+ycAxDJh0ISIiIiIiIlJBELWcqnLixAm0bdtW+n7MmDGYMmUKypcvr/XJkpKSMHv2bCxcuBBpaWkQBAH+/v7o3bu3zoEnJCTgzz//zLbduHHjAAB169aVkjyWlpbw9vaGKIpwdHREVFQUihUrhpiYGBgZGSmNER0dDXt7ewBA06ZNcfHiRekYx1AcQ17ZsmURFRUFBwcHREZGqmxDREREREREpC+F7TpU65kusi17BUHA9u3bsXLlSp0SLgBQtGhRzJkzB0eOHJHumzt3rk5jyBQrVgzffvtttl8yVapUke7z9vaWHkvXrl0BZCVx/vnnH5Xn8vf3l25369ZN4RjH6KayDREREREREdGXTquZLk+ePEH58uUhCAK6d++OPXv25PrEY8aMwdq1ayEIAh49egQnJ6dcj6mKrK5L3759FZIFMg8fPkSVKlWQmZmJcuXK4cKFCyhXrpx0PDAwEC1btkRCQgKKFy+OJ0+eKO3EwzFU70xU2DKMRERERET5IS0tDUeOHEFcXBw6dOiAkiVLKrUJDAxEQEAA6tevj3r16ikdf/XqFY4cOQJra2t06NBBaQa6Ps5Bmu3fvx9BQUEoXrw4Jk6cWNDhkJYK23WoVltGX7lyRbqdm/2y5Q0ZMgRr166Vxs+rpEt2KlasiOnTp2P27Nl4+vQpateujcGDB6Ns2bIICQmBv78/UlJSAACLFy9WmWDgGERERERZ9u3bh6ioKLXHq1atCi8vr3yMiCh/fSoJl1evXqnsR/9n//792LJlC5ycnJh0oZwTtbB48WJREATRwMBAjI2N1aZLtuLj46Uxly5dqpcxVQEgAhD79u2rtk16ero4dOhQqe3HX4IgiHPmzNF4Ho6hzMHBQQQgOjg4ZNuWiIiIPg8eHh5q30MAEL29vQs6RKI8k5qaKu7fv1/ctGmTGB0drbLNjRs3xLVr14o3btxQeTw6OlrctGmTuH//fjE1NTVPz0GaeXt7iwBEJyengg6FdFDYrkO1qumSnJwMIKsmi42NTQ5SO8qsrKxgbm4OAPjw4YNexswpQ0NDbNy4EYcPH0anTp1QunRpGBsbw9HREf3798elS5cwffp0jqHDGEREREREX5JPaYaL7BxElPe0Wl5UpkwZAFm7D6WmpsLY2DjXJ05KSsKHDx8gCALs7OxyPZ46onabMwEAOnbsiI4dO+bqfByDiIiIvmRnz54t6BCI8t2nmHDp0KFDLh4xEWlLq5ku8oVUAwIC9HLi//77T7rt4OCglzGJiIiIiIjy26eYcPn4HHktJSUFq1evRtu2bVGpUiUULVoUFSpUQOvWrfHHH38gPT1doX1iYiLMzMwgCALatWunceznz5/DwMAAgiCgX79+SsdDQkIwbNgwNGjQADY2NrC2tkb9+vUxfPhwhIeHK7V3dnaGIAjYsmULgKyNZQRBgCAI0q6++iI7l4+Pj8Z2Pj4+EAQBzs7OSsc8PT0hCIJUd+bt27eYPXs2atSoAQsLC9jb28PDwwPr1q1Tep4/lpiYiN9//x1NmzaFra0tzM3NUadOHQwcOBBBQUE5e5BfOK1mujRp0gRWVlZISEjAmjVr0KRJk1yfeP369QAAY2NjNGvWLNfjERERERERFQQmXDS7f/8+2rRpg6dPnyrc//jxYzx+/BgnT57EkiVLcPHiRWmjDjMzM7Rt2xb79+/H6dOnkZCQoHYTj71790orHPr3769w7Pvvv8fChQuVVkDcuHEDN27cwJYtW7Bq1SqMGDFCXw+3QD158gTt27dHaGiodN+HDx8QHR2N8+fPY+vWrTh9+rTK18CdO3fQuXNnREREKNx/69Yt3Lp1Czt27MB3332HhQsXSrsEU/a0mulibGyMXr16QRRFbN++HYcOHcrVSY8cOYKdO3dKWUtLS8tcjUdEREREXyZfX1/pE2hdaPvpMpE2mHBR7927d+jatauUcHF1dcWUKVMwf/58TJw4EaVLlwYABAcH49tvv1Xo2717dwBZz8OxY8fUnmP37t0AsuqGys+K2bBhAxYsWABRFGFsbIx+/fph9uzZ8PPzQ6dOnQAA6enpGDduHEJCQqR+fn5+WL58Odzd3QEA1tbWWL58OZYvX16ol2Wlpqaie/fuCA0NRY0aNTBu3Dj88ssv6NKli9Tm4sWLmDNnjlLfyMhIeHp6SgkXV1dXjBkzBnPmzEG/fv1gaGgIURTx+++/488//8yvh/R50LbiblRUlFi8eHHRwMBANDExEbdu3Zqjyr0HDx4UzczMREEQRCMjI/H27ds5GocKv8JWNZqIiIj04+bNm+LMmTPFmTNninFxcTof16eZM2dKOyPJe/z4scKuSR9zcnIq9Lsp5efzSPpXmHYpUneO/LBr1y7p93D06NFiRkaGwvF3796Jrq6uIgDR0NBQTEpKko7FxsaKhoaGIgBxwIABKsePiooSBUEQAYhDhw5VOFatWjURgFi8eHExJCREqe8ff/whxfbTTz8pHc+P3Yu0/VukKRbZrnFmZmYiAPHHH38U09PTFdrs27dPeqz16tVTGqNLly7S8W+//Vapf1BQkGhpaSkCEC0sLMTk5GSdH2t+KWzXoVrNdAGyiumuXLkSQFam0dvbG15eXjhx4gQyMzOz7X/jxg0MGDAA3bp1Q1JSEgRBwPTp01GzZk1tQyAiIiKiQiAoKAh+fn7w8/NDfHy8zsdJO3weP12fwgyXtLS0XD5K7Vy7dk26PW3aNBgYKF6CWlhYwNvbG4aGhgCgsCzGxsYGnp6eALJWS6iKWd3Sonfv3kljdevWDdWqVVPqO3jwYFhaWsLQ0BB37tzJ4SMsPBITE9G9e3fMnj1bej5lunXrBi8vLwBZs4rk3b9/HwcPHgQAtGjRAsuWLVPqX7t2bfzyyy8AgPfv3+ut1uuXQKuaLjIDBgxAZmYmhgwZgoyMDJw5cwZnzpxBiRIl0LBhQ9SqVQt2dnawtLRESkoK4uPjERoaiitXruDRo0cA/m83oYkTJ+q9CBERERFRbv1yLfs2hdHP7gUdAREBn07C5ciRI+jatWsuH2325C/eo6Ki4OTkpNRm6tSpmDp1qsr+3bt3x6lTpxAfH4/z58/jq6++Uji+a9cuAEDJkiWlBI3svLJrz6ioKIiiqLQM0dDQEAkJCTl6XIWVpmvsunXr4uTJk0rJq7///lu6PXnyZLXLNXv06IEFCxYAyErcNG3aNPcBfwF0SroAwKBBg1C9enWMHj0a169fBwDExMTgyJEjOHLkiNp+she8ra0tli9fjr59++YwZCIiIiIizZydnZUKZxLltU8p4RIXF5fLR6sdWV0UIOuifcKECfDx8ZFquWSnW7duUq2XAwcOKCRdoqKicOnSJQBAnz59UKTI/13empmZoWbNmggODsaJEyfQrVs3jB07Fl5eXkqzbT4XFhYWGleSmJmZqbz/ypUr0u02bdqo7e/o6IjIyMicB/iFytGrrW7durhy5QqOHTuGPn36wNzcHKIoavyqU6cOli9fjvDwcCZciIiIiIjos/KpJVzyqyBs9+7dpRk10dHRmD59OhwdHdG8eXNMnz4dx48fR2pqqtr+Dg4OUuLm4MGDCslUTbsWAcDatWthYmIi9W3bti0cHR0xaNAgrF69WmmXnk9dxYoVc7SrkCyRYmdnB1NTU32H9cXLcYpPEAS0adMG/v7+ePv2LW7fvo3t27dj+fLl+OWXXzB//nysX78ex48fR1xcHAIDAzF27Fi123wRERERUeHm4+MDQRAwZMgQ6b7y5ctDEAR4enpmezwnzp07hwEDBsDR0REmJiYoXbo0OnfujH/++Sfbvp6enrk6d2ZmJvz9/dGlSxc4ODjAxMQEzs7OaN26NbZt26b2QnHz5s0QBAG2trYAsnYUWbFiBRo2bIjixYvDwsICNWrUwNSpU/HixQul/ro+jwkJCfj111/RpEkT2NrawtjYGA4ODujcuTP+/PNPZGRkqH2Msl2clixZAgB48eIFpk6dChcXF5iZmcHR0RGtW7dWuLglZZ9iwkXVOfKCIAjYu3cvVq9eDUdHRwBARkYGLl68iHnz5qFdu3YoVaoURo8ejZiYGJVjyHYxevLkCW7duiXdL9u1yMnJCY0bN1bq17hxY4SEhKBbt27SLJjnz59j+/bt+Oabb1C+fHm4u7tj3759en3MBaV48eI56vf27VsAWXVcSf90Xl6kioGBAWrUqIEaNWroYzgiIiIi+sJlZmZi/Pjx0kYOMi9fvsThw4dx+PBhjB49Os8uHF+9eoXu3bvj8uXLCvc/efIET548wcmTJzFr1iwcOXIElSpV0jhOly5dcPXqVYX7Q0JCEBISgjVr1sDf3x/t27fPUZwXL15Ez5498erVK4X7nz9/jufPn+Pw4cNYtmwZDh48mO0FVVBQEDp06KCQCIqMjERkZCROnjyJvn37YseOHTn6JP1zx4SLZoaGhhg9ejRGjRqFwMBAHDx4EOfOncOVK1ekWqBr167F3r17ce3aNZQvX16hf/fu3fHDDz8AyFpiVKdOHYWlRf369VP7uqxYsSL27duHuLg4HDlyBP/++y/Onz8vzXK5fv06evTogcmTJ2PhwoV59yTkUl7WnpEtO3rz5k2eneNLppekCxERERF9/gYNGoT69evjypUr2L59O4Csoo0lSpSAg4MDLC0tNR7XxbRp0xQSLo0aNUKzZs0gCALOnz+Pq1evYs2aNTqPq43ExES0atUKISEhACDNbqlQoQIePnyIkydPIiIiAmFhYWjcuDECAgJUFgfNyMhA3759cfXqVZibm8PLywv169dHWFgYTp8+jcjISCQkJKBbt264fPky3NzcAGT/PMuEhISgTZs2SEpKAgBUqFABnp6eqFChAoKCgnD69Gm8efMGN27cQMuWLXHz5k21NR3i4uLQuXNnvHjxAg0bNkTz5s1hbm6OCxcu4PTp0wCAnTt3ol27dvDx8dHbc/25YMJFO4IgwM3NTXqtJycnY//+/VixYgUuXbqEmJgYTJo0SWnmiYuLC1xdXREaGooDBw5g5syZCrOv+vXrl+25ra2tMXDgQAwcOBAA8ODBA6xbtw7r169HQkICFi1ahIEDB6Ju3bp6ftT68fDhwzwbW/aaiIqKQlpamtJriHKHSRciIiIi0oqXlxe8vLxgYWEhJQO8vb3h7Oys0EbTcW0EBQVJnzgbGRlh9erVGDZsmEKblStXYvz48YiKisr5A1JjxowZUsJl6tSp8PX1VahzkJycjJ9//hkLFy5ETEwMJk+ejD179iiNEx8fj7Nnz8LR0RHHjh1T2LL2/fv3GDx4MPbt24fU1FSMHj0a165dgyAIWj3Poihi+PDhUsLF29tboX4FkHUB1a1bNwQEBODBgwf45ZdfMG/ePJWPeeHChdIyqG+++UaaNSCKIpYuXYrvvvsOAHDo0CEmXVRgwkW9LVu2ICkpCWXLlkWnTp0UjpmamqJfv37o3bs3ateujZCQEKXZZTLdu3dHaGgobt68iSdPnkhLi6pWrYratWsrtQ8JCcGFCxcAZBXjtbe3VzhepUoVLFy4EA0aNJCSNleuXCmwpEtKSoraYwkJCQgLC8uzczdo0ACnTp1CZmYmLl26pHZJZmpqKuzs7JCQkIDBgwdjy5YteRbT5+TzLNtMRERERJ+s5cuXS59gz5o1SynhAgBjx47FlClT9H7u+Ph4rF69GgDQs2dPzJs3T6mwpKmpKebPny/Vmdi7d6/GT6EPHTqkkHABsnYZ2bNnj7TTSEBAgMIOItm5evWq1N7d3R2bNm1SSLgAWQVIjx49iqJFiwIA1q1bJyVpPpaYmIhx48Zh7NixCss0BEHAhAkTULlyZQBZ28RS9phw+T8rVqzAmDFj4OPjo7a+kKGhoVQDSX6LaXmy3zcAWLNmDS5evAggq4CuqqVFERERGDNmDMaMGSNtK61KqVKlFOLIb8bGxgCA0NBQtW2WLl2q9ndXHzp27Cjdnjt3rtp2J06ckJY5eXh45Fk8nxsmXYiIiIio0BBFUSqSa2Njg7Fjx6ptO2HCBOmCRV+OHj2KxMREAMCUKVPU1okQBAGTJk2Svpd9ov6x9u3bq/wUHsiqi/jjjz9K3x88eFDrOA8fPizdnj59uto4bW1tMXz4cABZ9RrUJXaMjY0xbdo0lccEQUCdOnUAQOMuM5TlU0m4BAYG5vKRasfV1RUAEBsbq7Zmyr///ivVZ2nSpInKNm5ublIhXvlx1C0tkp0XAH7//Xe8fPlSqU1SUpLC7C91546Li9NYkDo3qlevDgC4deuWyhlzR44cwfz58/Pk3DJNmzZF/fr1AWQlVqZMmaL0eF+8eCH9PTYxMUHr1q3zNKbPCZcXEREREVGhERUVhejoaABAq1atYGlpqbZtmTJl4O7uLn3irQ///fefdPvKlSsICAhQ21aWnAHUzwDp0aOHxvPJttIFoPFcH7t+/bp0u02bNhrbtmvXDsuXL5fO0bJlS6U2VapU0TgTQl0tGFL0KSVcAgICVI6vb3369MHWrVsBZNVqOnToEFq2bAlra2spEXjq1CkAWcsJJ0yYoHIcQRDQrVs3LF++HOnp6QCylnVVqVJFZfvy5cujfv36CAgIwJMnT1CtWjX06tULFSpUgCAIiIiIwN9//y0Voe7YsaPSjDTZLLeEhAR8//33aNiwISpWrCjVpImIiFAo+puTHb46d+6M/fv3S8/VkCFD0Lx5cyQlJeHixYvYsWMHjIyMMGzYMGzcuFHn8bUhCAI2btyIhg0bIjk5GYsWLcKxY8fQokULlCtXDg8fPsSOHTvw4cMHAMCCBQukBJiMs7Mznjx5AgA4c+ZMjneN+xwx6UJEREREhYYs4QJkFYbNjrOzs16TLpGRkdJtWR0TbajbWeTjXVg+ZmpqijJlyki7DWlL9jzZ29tLy4fUkS/yq+rTfiBrhxfKnU8t4SKb2ZDXOnbsiOnTp+PXX3+VaobIZrXIs7CwwNq1a9G8eXO1Y3Xv3l1KIAJZS4vUEQQBf/31F9q1a4dHjx4hLi4O69evV9nWw8MDO3bsgIGB4kKQpk2bYu3atQCyZssAwMyZM6Wkiz4MGTIEx48fx65duyCKIv744w/88ccf0nEzMzNs3boVb968ybOkCwDUqlULx44dQ8+ePREbGyvtsCbP0NAQEyZMwLfffptncXyOmHShPBcdHa2UNZYZO3asxmnDRERE9GWRr1tQunTpbNtntw2yrnK6Lau6ftrEV7ZsWTx//hxv377V+nzv378HoFiPQh35GNSdo3jx4lqfm5R9igmX/JjlAmQlP+bMmYPBgwdj4cKFuHXrFp4+fYr4+Hg4ODjAyckJrVq1wtixY2Ftba1xrObNm6NEiRKIjY0FAPTt21dj+8qVK+PevXv4888/4e/vj6dPnyIyMhKmpqZwcnJClSpVMHr0aHh4eKhcojdo0CA8fvwYGzduxMuXL2FnZ6dUkDe3BEGAv78/evXqhTVr1uD+/fuIiYmBvb092rZti0mTJsHFxQUbNmzQ63lV8fDwQFhYGJYvX44DBw7g4cOHyMjIgIuLC2rUqIFJkyahVq1aeR6HNlauXKmww508+eR9YcCkC+W5UqVK4e7duwUdBhEREX0C5JcTvXjxItv2+n5zLVtGY2JigsTERKVPvnUluzjURDb7xMLCQutxZW21efyy5RO6noO0V7JkSY27OhkZGSksJVOlXr16GhMh+XGOvOTi4qJ2pom2BEGQ6jg1b95caYmLKrKlOaoKcmtzvhkzZmDGjBkqjzs7O+doSZGq8/Tu3Ru9e/dW22b48OFSfaaPnT17Vqvz+Pr6wtfXV2Mba2trjY9ZnYiICJ3a55amD+/Lli2bJzvb5RQL6RIRERFRoSE/K+PRo0fZttf3G33ZzJGUlBSFpUY5lV18KSkpePbsGQDotLuMrO3Lly+RnJysse3jx4+V+hF9ik6dOiUlYzUtLSIqTJh0ISIiIqJCw87OTqpBcvr0abx7905t25iYGIWCsvrg7u4u3b5x44bGtvfu3ZM+OVa3ZbSsQKg6R48elT4pb9CggdZxyrf9999/NbY9ceKEyn5En5rNmzcDyKot0qtXr4INhkhLTLoQERERUaHSuXNnAFlbHK9YsUJtu2XLlinsIKQP7dq1k5YUzZw5U9olRZWff/4Zfn5+WLhwodo6D9u2bVM72yUzMxN+fn7S9x07dtQ6Tvm2c+fOVbvE4fXr11izZg0AwMrKSu2WuESFXWBgIHbu3Akg6/fUzs6ugCMi0g6TLkRERESUYzExMbk6rsqYMWNgaGgIICvxoWrHjk2bNmHevHk6j50dR0dH9OnTB0DWNtAjRoyQitbKiKKIRYsWYc+ePQCA3r17w9zcXOV46enp6NKli7SVqsyHDx/Qp08fBAUFAcjaOUTVVs4yHz+PjRs3lnafuXr1KoYNG4aUlBSFNpGRkWjfvr2UmBo1apTaOIkKoxcvXqBnz57o2bMnPD09kZmZCQCYOnVqAUdGpD0W0iUiIiIinZiamkq3/fz8MGDAAFhZWaFDhw5aHc9OtWrV8MMPP2D27NlIS0vD8OHDsWHDBjRt2hTGxsa4ePEiLly4AABo3749jh49qsdHByxZsgRnz57Fy5cvsXnzZpw6dQpeXl5wcXFBXFwcjh49itu3bwMAKlWqhIULF6ody9bWFsHBwahTpw7atm2LmjVrIiwsDKdPn5ZquRgZGWHDhg1Ku6doeh4FQcDGjRvRsGFDJCcnY9OmTTh//jxatmwJZ2dn3L59GydOnEBcXBwAoGrVqpg5c6ZenyeivJaSkoK///5b4b7Ro0dr3FaaqLBh0oWIiIiIdNKgQQMUKVIE6enpOHz4MA4fPgwPDw8pqZLdcW34+fkhISEBy5YtAwBcuXIFV65cUWgzevRoDBgwQO9Jl1KlSuHcuXPo1KkTwsLC8OzZM2zatEmpXa1atbBr1y6UKFFC7Vh79uzBiBEjEBYWhp07d0rLI2SKFSsGf39/lbVWsnsea9WqhWPHjqFnz56IjY3Fw4cPVdaWcXNzw6FDh6SdmYg+FRYWFvD09ERAQADs7e0xevRoTJgwoaDDItIJlxcRERERkU4qVqyInTt3ombNmjA1NYWtrS0qVKig9XFtGBgYYOnSpbhw4QIGDBiAsmXLwsjICLa2tvDy8sK+ffuwevVqpdkh+lKlShUEBwdj9erVaNWqFezs7GBsbIxKlSqhY8eO2LJlCwIDA+Hi4qJxHCcnJwQFBWHOnDmoVasWLCwsULRoUbi6uuJ///sf7t+/j/bt26vsq83z6OHhgfDwcMyZMwcNGzaEjY0NihQpAnt7e3To0AFbtmzB1atXUbp0ab09N0T5xdbWFmfOnMG7d+8QFhaGyZMno0gRzhugT4sg6mNjcSIVZPujOzg46GXLRSIiovzwy7WCjiBnfnbPvg3lj82bN2PIkCEAsrZrdnZ2LtiAiIi+IIXtOpRpQiIiIiI5TF4QERGRvnB5ERERERERERFRHmDShYiIiIiIiIgoDzDpQkRERERERESUB5h0ISIiIiIiIiLKA0y6EBERERERERHlASZdiIiIiIj0yMfHB6IoQhRFbhdNRPSFY9KFiIiIiIiIiCgPMOlCRERERERERJQHmHQhIiIiIiIiIsoDTLoQEREREREVQi9evICvry9evHhR0KEQUQ4x6UJERERERFQIvXjxAn5+fky6EH3CmHQhIiIiIiIiIsoDTLoQERERERFRnjp79iwEQdD4ZWxsDCcnJ7Rp0wZr167F27dvCzpsolxj0oWIiIiIiIgKXFpaGp4+fYoTJ05g9OjRqFq1Kvbt25en5wwKCoKvry98fX0RHx+fp+eiL1ORgg6AiIiIiIiIvhzu7u74+uuvFe4TRRHx8fEIDw/HP//8g9jYWLx8+RI9evTAunXrMGLEiDyJJSgoCH5+fgAAHx8fFC9ePE/OQ18uJl2IiIiIiIgo37i6uuLbb79VezwlJQVz5szBL7/8AgAYOXIkqlWrhqZNm+ZXiER6w+VFREREREREVGiYmJhg1qxZWLp0qXTfqFGjkJGRUYBREeUMky5ERERERERU6IwbNw7NmzcHAISEhOD48eMFHBGR7ph0ISIiIiIiokJHEAT873//k77ftGmTynb37t3DqFGj0KBBA9jb28PU1BTly5dH8+bN8dtvv+HNmzdKfXx8fCAIAoYMGSLdV758eQiCAE9PT6X2qamp2LRpE1q3bg0XFxeYmZnB1tYWtWvXRr9+/XDu3DmIopj7B02fHdZ0oTwXHR2NatWqqTw2duxYjB07Np8jIiIiIiKiT0GbNm1gZmaGxMREnD17FqIoQhAEAFnFd6dMmYLFixcrJTwiIiIQERGBixcvYvbs2Th37hzq1auXoxhCQkLQvn17PHv2TOH+pKQkxMbG4vbt29i5cycGDRqEP//8U4qP8s7KlSuxcuVKlceio6PzORrNmHShPFeqVCncvXu3oMMgIiIiIqJPjImJCZydnXH37l3ExMTgyZMncHZ2BgDs3LkTv//+u9S2ffv2cHNzQ7FixfDixQscPHgQDx8+xPv379GlSxc8fvwYRkZGAIBBgwahfv36uHLlCrZv3w4A8PX1RYkSJeDg4CCNmZGRgT59+kgJF3t7e/Tq1QuOjo5ITExEcHAwDh48iPT0dGzbtg1NmjTBmDFj8unZ+XJp+vC+bNmyiIqKyueI1GPShYiIiIiIiAqtsmXLSh/iyidd9uzZAwAwMDDAoUOH0KFDB4V+CxcuxKBBg7Bjxw5ERUXhzp07qFu3LgDAy8sLXl5esLCwkJIu3t7e0tgyoaGh0rk9PDxw7NgxmJqaKrQJDAxEs2bNkJSUhGPHjjHpQgpY04WIiIiIiKiQiY6Oxrhx4wBkFZQtbEsm8lPZsmWl23FxcdLt27dvAwBat26tlHABspIxkyZNkr6/c+eOzueWnQMAfv31V6WECwDUq1cPrVq1yvE56PPGmS5ERERElGOZmZkICQnBjRs38Pr1a2RkZMDa2hrVqlWDm5sbzMzMCjpEok+Sj48Prl69CgC4evUqfHx8cPTo0QKOqmDY2dlJt9+/fy/d3rBhAzIzMxWSMh+ztLSUbudky+lmzZrhzJkzAID69etnex5ua00fY9KFiIiIiHSWkZGBlStXYtGiRXj69KnKNkWLFsXAgQPh5+eHMmXK5HOE+uPj44MtW7bAyckJERERBR0OfSGuXbsmXcBnZGTg+vXrBRxRwYmJiZFuyydRWrRoobFfVFQUFi9enKtzlytXDuXKlVN7PC0tDRcuXMCJEydydR76fDHpQkRERCRv1KiCjiBn1q7Nt1O9f/8enTt3xtmzZxXuL1Ik661leno6gKydPTZs2IA9e/bgwIEDKi+QPD09ce7cOQBZ28H6+PjkaeyfqiVLliA+Ph516tRBt27dCjocygfu7u44ceIEMjIyYGhoiAYNGhR0SAUmMjJSul28eHGl46Io4vbt2wgODkZYWBjCwsIQFBSE0NBQvcYRHx+P//77TzrH/fv38d9//ynMviH6GJMuRERERKSTwYMHSwmXYsWKYerUqejZsycqVKgAAwMDREZG4vr165g9ezZu3bqF+Ph4dOnSBcHBwXB0dCzY4D9RS5YswZMnT+Dt7c2kyxdi8+bN6NGjBy5fvoyGDRti8+bNBR1SgZFPusgXuk1NTcWKFSuwaNEiPH/+XKmfoaEh6tevLy3Tyqng4GBMmzYNx48fV7l8qGzZsjAwMFA764++bEy6EBEREZHWzpw5g3379gEAbGxsEBAQgPLlyyu0cXJygpOTE3r06IGRI0di48aNePv2LXx9fbFx48aCCJvok1OqVCksX74cbm5uWL58OUqVKlXQIRWI1NRUaVmfnZ2dtNRHtpXzgQMHAABGRkZo1qwZ3NzcUKNGDbi6usLV1RWxsbFKf6N0ceHCBbRp0wbJyckAspI+TZs2RZ06daRzODs7Y+jQodiyZUvuHix9lph0ISIiIiKt7dixQ7r9+++/a7yYMTAwwLJly3Dq1ClERERg7969WLNmDYyMjKQ2Hy9RIiKS9++//+LDhw8AsrZsFgQBAKRliwDQsWNHrF+/HqVLl1bqL18PRleZmZkYNWoUkpOTYWJigu3bt6N79+4wMFDeBFgUxRyfhz5v3DKaiIiIiLR28+ZN6fZXX32VbXszMzO0bNkSAPD27Vs8fvw4z2Ijos+LKIqYP3++9P2QIUOk24cOHZJub926VWXCBQDu37+f4/M/evRIqgszZswY9OzZU2XCJbfnoc8bky5EREREpLWEhATptomJiVZ9evfujWHDhmHYsGEwNDRUOLZ582YIggBBEJR2BvL09IQgCJg4cSKArKTN7NmzUaNGDVhYWMDe3h4eHh5Yt26dVLxXnZcvX2Lq1KmoVq0azMzMYGtrizZt2uDgwYMAsmbcyOK4d++eVo9LXmZmJvz9/dGlSxc4ODjAxMQEzs7OaN26NbZt24bU1FSdx4yIiJBievLkCQBgy5Yt0n2cJUSfuxUrVuDChQsAgOrVq6Nt27bSsbi4OACAqakpihUrprK/KIr4888/c3x+2TkAoGTJkmrb3b1794veXYo0Y9KFiIiIiLQmv3Xqtm3btOrTvn17bNiwARs2bEDFihVzdN4nT56gcePG+PnnnxESEoIPHz4gOjoa58+fx6hRo9CyZUukpaWp7Hvs2DG4urpi/vz5CA0NRVJSEmJjY3HixAl07doV48aNy9XSgFevXqF58+bo378/Dh06hOfPnyM1NRVPnjzByZMn8fXXX6NGjRoIDw/P8TmIviQpKSnw9fXFhAkTAACCIGDdunUKSVtXV1cAQHJyMvbv3680RkJCAiZOnKiwJPLly5caz/vxUiQXFxfp9t69e5GSkqLU5/Lly2jdujUyMzMBZCVqVLWjLxdruhARERGR1ho1aoSTJ08CAL7//nvExcVh8uTJsLKyyrNzpqamonv37ggNDUWNGjXQsmVLlCxZEtevX5dmqly8eBFz5syBr6+vQt+AgAB069ZNugiqW7cuWrRoAQsLC1y+fBlnzpzBihUr8PDhwxzFlpiYiFatWiEkJAQApNktFSpUwMOHD3Hy5ElEREQgLCwMjRs3RkBAAJycnLQa28bGBsuXLwcAzJgxA3FxcXB3d8fXX38NAKhcuXKOYiYqaKGhoVixYoXCfaIoIiEhAeHh4Th8+LBCAmTt2rVo0qSJQvtOnTph0aJFAIB+/fqhe/fuqFOnDjIzMxEWFoaDBw8iPj4e9vb2eP36NTIyMrB48WK8e/cO3t7eqFKlCoCsmTIyfn5+GDBgAKysrNChQwcUK1YMLVu2xJkzZ3Djxg1Ur14dPXr0QMmSJfH8+XNcu3YNly5dApC1g1FkZCQSEhLQs2dP9O7dG97e3nny/NGnRRBZ8YfySNmyZREVFQUHBweFbd6IiIgKtVGjCjqCnFm7Nl9O8+bNG1SsWBHx8fHSfcbGxmjfvj06duyINm3aaJ1UALKWF8nqNDx+/FhhO1hPT0+cO3cOZmZmSExMxI8//gg/Pz+FT7v379+P7t27AwDq1auHGzduSMcyMzNRr1493Lp1CwAwe/ZsTJ8+XSrECQC7d+/GoEGDFJb/hIaGomrVqtL3Pj4+2LJlC5ycnJSWQE2ZMkW68Js6dSp8fX0VLuKSk5Px888/Y+HChQCAnj17Ys+ePVo/PzLOzs7SltFf8tbBX5rAwEC4ubnhxo0bqFevXkGHkytnz56V6jtpy97eHitWrEDPnj1VHp8+fTrmzZuntr+bmxv27NmDSZMmSbuuAcC+ffukrdcfPnyIqlWrKixR9PDwkJbvPX36FO7u7oiOjlZ5DhMTE8yePRutWrVCgwYNpBkvtWvXRlBQkA6PlvSlsF2HcnkREREREWnNxsYGZ86cQdmyZaX7UlNTceDAAYwcORLOzs6oWrUqJkyYgCNHjiAxMTHX50xMTET37t0xe/ZspZow3bp1g5eXFwAgODhY4dipU6ekhMugQYPw448/KiRcgKx6M35+fjmKKz4+HqtXrwaQlUyZN2+eQsIFyPoUff78+VJiaO/evTmeVUP0uStSpAjKli2Lr776CitXrkRoaKjahAsAzJ07F2fPnkWnTp1QsWJFGBsbw97eHp07d8aOHTtw7do1ODs7Y+3atejSpQvMzc3h6uqqUJ+lYsWK2LlzJ2rWrAlTU1PY2tqiQoUK0vFy5crh/v37+PHHH9GgQQNYW1vD3Nwc1atXx/fff4/79+9jypQpqFevHv788084OjrCxsYGdevWzdPnij4dXF5ERERERDqpU6cO7ty5g+3bt2Pjxo0IDAxUOH7//n3cv38fy5Ytg5WVFYYMGYJJkybB0dExx+f8eNmQvLp16+LkyZNKNV327t0r3f7+++/V9h85ciR++eUXnRNER48elfpMmTJFKaEjIwiCwiftFy5cyHFtG6JPlaenZ55sq+zh4QEPDw+Nbezs7KTtpVXp0aMHevToofa4lZUVZs+ejdmzZ2s8z8CBAzFw4EDNAdMXh0kXIiIiItKZlZUVvvnmG3zzzTd4+fIlTpw4gX///RcnTpxQmIb/9u1bLFmyBNu3b8eBAwfQuHFjnc9lYWGBmjVrqj1uZmam8v4rV64AAEqXLq2xv42NDdzd3XXeDei///5TOFdAQIDatvIJnY9n5BAR0eeLSRciIiIiyhV7e3t8/fXX+Prrr5GZmYng4GDs27cP27Ztk5bSvH79Gm3btsXDhw9hZ2en0/gVK1ZUO4tEk2fPngGAVjVm5Hdl0pZ8rYDvvvtO637y224TEdHnjTVdiIiIiEhvDAwMULt2bfj6+uLBgwdYs2aNNBPl3bt3mDNnjs5jFi9ePEexvH37FgBQqlSpbNuWLl1a5/Fzmjxh0oWI6MvBmS5EREREpJUbN27g+vXrAIBevXrB1tZWY3sDAwOMGjUKpqam8PHxAQCdl/DkhpmZGd69e4dXr15l2/b169c5Gh/I2r0kMTERBgb8PJOIiBTxPwMRERERaeXy5csYM2YMxowZg0uXLmndr3///jA2NgYAPHjwIK/CU2Jvbw8ga8vX7Dx58kTn8WUzaFJSUgrFtqT0+SldujRmzpyZo5lYRFQ4MOlCRERERFqR331IthWzNgwMDFCkSNYEa3Nzc73HpY67uzsAICoqCnfv3lXb7v3797hx40aOxweQbf979+7B19cXvr6+3DKatFa6dGn4+voy6UL0CWPShYiIiIi04unpCUNDQwDAypUrtV6SExwcLO3eU6tWrTyL72Ndu3aVbs+fP19tuw0bNiA+Pl7n8du1ayctKZo5cybS09PVtv3555/h5+eHhQsXSjNwiIjo88ekCxERERFppXjx4ujfvz8A4NWrV/Dx8UFcXJzGPomJiRg+fLj0/aBBg/I0RnndunVD+fLlAQBbtmzBb7/9BlEUFdocOnQIP/30U47Gd3R0RJ8+fQBkJZZGjBiB9+/fK7QRRRGLFi3Cnj17AAC9e/fO1WyfmJiYHPclIqL8x0K6RERERKS1uXPn4vjx43j9+jWOHDmCypUr48cff4SHhwcqVqwIKysrJCYmIioqCkePHsWSJUvw+PFjAEDjxo0xePDgfIvVyMgIGzZsQOvWrZGZmYlp06Zh9+7daN68OSwtLXH16lWcPHkSmZmZGD58ODZs2AAAMDU11focS5YswdmzZ/Hy5Uts3rwZp06dgpeXF1xcXBAXF4ejR4/i9u3bAIBKlSph4cKFOXosspjOnTuHxYsXw97eHi1atICDg0OOxiMiovzBpAsRERERac3R0REnTpxA586d8ezZM8TGxmLSpEnScXNzc3z48EGpX5MmTXDo0CFpeVJ+adWqFbZv344hQ4YgOTkZN27cUKi/YmxsjFWrVsHBwUFKupQsWVLr8UuVKoVz586hU6dOCAsLw7Nnz7Bp0yaldrVq1cKuXbtQokSJHD2Opk2b4v79+3j//r30fJ85c4ZJFyKiQo7Li4iIiIhIJ7Vr10ZwcDCmTp2qtG30xwmX6tWrY/Xq1Th//jxsbGzyM0xJv379cOfOHYwePRpOTk4wNjaGvb09+vXrh6tXr2LYsGF4/vw5AMDCwkLaClpbVapUQXBwMFavXo1WrVrBzs4OxsbGqFSpEjp27IgtW7YgMDAQLi4uOX4MCxYswNdffw07OzuYmpqiQoUKsLS0zPF4RESUPwTx44WtRHpStmxZREVFwcHBgdsoEhERfabS0tJw584dBAUFITY2FsnJybCyskLp0qVRv359ODk5QRCEgg4zW7NmzcLMmTNRsWJFhIeHF3Q4RESUQ4XtOpTLi4iIiIgox4yMjFC3bl3UrVu3oENRcvfuXVy7dg0A0KVLF40zbQIDAwFkLRciIiLSFyZdKM9FR0ejWrVqKo+NHTsWY8eOzeeIiIiI6Evw4sULDBkyBACwfv16hV2U5IWFheHgwYMAgGbNmuVbfERElDMrV67EypUrVR6Ljo7O52g04/IiyjOFbVoXERERfVmSkpJgY2OD5ORkVKpUCVeuXFEqZBsXF4c+ffrg5MmTAIDr16+jfv36BREuERHpQWG7DuVMFyIiIiL6LBUtWhQLFizAuHHjEB4ejnr16mH8+PGoXbs2UlNTERwcjLVr10pbWvfu3ZsJFyIi0ismXYiIiIjoszV27Fg8fPgQS5cuxdOnTzFlyhSV7Zo3by5tGU1ERKQv3DKaiIiIiD5bgiBg8eLFuH37Nry9veHm5gYrKyuYmJigTJky6Ny5M7Zu3YozZ86gWLFiBR0uERF9ZjjThYiIiIg+ezVq1MDmzZsLOgwiIvrCcKYLEREREREREVEeYNKFiIiIiIiIiCgPMOlCRERERERERJQHmHQhIiIiIiIiIsoDTLoQEREREREREeUBJl2IiIiIiIiIiPIAky5ERERERERERHmASRciIiIiIiIiojzApAsRERERERERUR5g0oWIiIiIiIiIKA8w6UJERERERERElAeYdCEiIiIiIiIiygNMuhARERERERER5QEmXYiIiIiIiIiI8gCTLkRERESklevXr0MQBAiCgGLFiiEjI0Nj+wcPHkjtBUHArVu3NLYXRRGlSpWS2p84cUKf4RMREeU7Jl2IiIiISCt169aFpaUlAODdu3cICQnR2P7kyZMK32eXRImIiMCrV68AAEWKFEGTJk1yEa2is2fPSskcZ2dnvY0rb/PmzfD19cXmzZvzZHwiIvr0FCnoAIiIiIgKkxvrCjqCnHEbmffnKFKkCJo1a4ajR48CAP777z/UqlVLbXtVSZcpU6aobX/lyhXpdv369WFubp7LiPPX5s2bce7cOXh4eMDHx6egwyEiokKAM12IiIiISGuenp7S7cuXL6ttl5GRgdOnTyvcd/78eSQnJ6vtI5908fDwyHmQREREhQSTLkRERESkNfmky3///ae23Y0bN/D27VsAQMOGDQEAycnJuHjxoto+eZl08fT0hCiKEEUREREReh2biIhIHSZdiIiIiEhr9erVg4WFBQAgLCwMr1+/VtlOfmnRr7/+Kt3+999/VbZPTk7GzZs3AQAGBgZo2rSpvkImIiIqMEy6EBEREZHWZHVdZORnp8iTJV2qVKkCT09PlC9fHoD6Yro3b95EWloagKzETrFixfQZNgDA2dkZgiBorLcSExMDPz8/NGjQADY2NjA3N0fNmjUxZMgQBAYGquwjK9B77tw5AMC5c+ek+z4uqpuRkQF/f3907NgRVatWRdGiRVGuXDm0bNkSixYtQlJSkr4eLhERFQJMuhARERGRTrJbYpSYmIhLly4BAL766isAQJs2bQAAQUFB0g5F8uTHKah6LocPH0aVKlXg6+uLgIAAxMXFITExEXfu3MHmzZvh5uaGkSNHIj09PUfjv3r1CnXr1kX//v1x5MgR3L9/H8nJyXj27BnOnj2LKVOmoEqVKnj69KmeHxkRERUU7l5ERERERDqRT4qoKqZ78eJFpKamAgC8vLwAAK1bt8batWsBZM2CGTBggEIfXeu5nD17Fi1btoSTk5NearScOnUK3bp1Q0ZGBgCgZcuWqF+/PiwsLBAUFIQjR44gJSUF69evx9u3b7Fz506p7/LlywEAS5cuRXh4OCpVqoQJEyYA+L96Nunp6ejduzeCg4MBAOXKlUP37t3h4OCA169fY9++fQgPD0dkZCQGDx6M06dPw8CAn48SEX3qmHQhIiIiIp24ubnB3NwcHz58wPXr15GWlgYjIyPpuGxpkSAI0qyYVq1awcDAAJmZmThx4oTapIsgCArLl/JDYmIifHx8kJGRARsbG+zcuVNKFsk8ePAA/fv3R2BgIHbt2oWvv/4anTp1AgB8++23AIA9e/YgPDwcDg4O0n0yN2/exPnz5wEAHTt2xL59+xSes7lz56JNmzY4c+YMzp07h8ePH6NixYp5+bCJiCgfMH1OeS46OhrVqlVT+bVy5cqCDo+IiIh0ZGRkJCVGEhMTcfv2bYXjsqSLm5sbbGxsAADW1tZo0KABgKxiuqIoSu2fP3+OZ8+eAQBq164Na2vrPH8M8v766y9ERkYCALZs2aKUcAGyatP8/fffsLKyAgDMnz9fp3Ncu3ZNuv2///1PIeECZNXKGTVqFAwNDWFoaCjNiCEiImUrV65Ue40ZHR1d0OEp4EwXynOlSpXC3bt3CzoMIiIi0iMPDw8cP34cQFY9Fjc3NwBZhWhluxDJ6rnItG7dGlevXsXz588RGhqKatWqAcjbraK1sXv3bgCAi4uLNHtFFScnJ/Tq1QsbN27E1atXkZycDFNTU63OYWhoKN2OiopS2aZv377o27evDpETEX2Zxo4di7Fjx6o8VrZsWbV/ZwsCky5EREREpLOPi+nKltOcOXNGuv/jGSNt2rTB7NmzAWTtYlQYki6iKErnt7S0xIoVKzS2j4uLAwCkpqYiLCwMNWvW1Oo8slk+ADB69GiEhIRg2LBhqFChQg4jJyKiTwGTLkRERESks/r168PMzAyJiYkKxXRlS4tMTEzQtGlThT6NGjWChYUF3r9/j3///VcqNiufdGnevLnSuVQlQsLCwgAACQkJKo87ODige/fu2T6Od+/eISEhAQAQEBCAgICAbPvIyPppw83NDRMmTMDSpUvx7t07zJ07F3PnzkX9+vXRvHlztGjRAq1bt4a5ubnWYxIRUeHHpAsRERER6czIyAhNmzbFiRMnEBERgRcvXqB06dJS0qVp06YoWrSoUh9PT08cPnwY586dQ0pKCgwMDKRER40aNWBra6t0rnHjxqmNIy4uTuVxDw8PrZIuuiROctt38eLFaNq0KWbMmIF79+4B+L9Ez+LFi1G0aFF069YN8+bNg5OTU47jIiKiwoOFdImIiIgoRz5eYvT48WM8evQIgHI9F5k2bdoAAD58+ID//vsPt2/fRlJSEoCCqediZmYm3R4xYgREUdT6q3379jqdSxAE9O7dG3fv3sXdu3cxb948tGnTBhYWFgCApKQk7NixA9WrV1eY/UNERJ8uJl2IiIiIKEc+TrrIZrkAyvVcZFq3bi3dPnHihFb1XFQlPGS1Y5ycnFQeP3v2rFaPwcrKCsbGxgCA8PBwrfrkliAIcHV1xbRp03D8+HHExcXh8OHD6NChA4CshNSYMWPyJRYiIspbXF5ERERERDlSv359FC1aFElJSbh8+TKePn0KICuRUa9ePZV9XFxc4OjoiGfPnuHEiRNwcXGRjrVo0SJf4pZnaGiI+vXr4/Lly7hz5w5SUlJgYmKitr2/vz/u3bsHS0tLTJ48Wevz/P3333j16hWsrKzQv39/hWNFihRBx44d0bFjR7Rv3x7Hjh1DUFAQPnz4wBovRESfOM50ISIiIqIcMTY2lorl3rhxQ5rp0rJlSxQpovqzPUEQpNkuAQEBUp+qVauiVKlS+RC1Mtk20a9fv8ayZcvUtnv9+jWGDh0KPz8/3LlzR6dz7NixA2PGjMGgQYPw5s0bte1kz4H8FtNERPTpYtKFiIiIiHJMtsQoJSVFSiaoq+ciI0u6iKKIly9fAiiYei4yw4cPh6WlJQDAz88P/v7+Sm3evn2L7t27S/VnvL291Y4XExOjdJ+rqysAIDMzEz/99BNEUVRqc/PmTezfvx8AUKdOHc5yISL6DHB5ERERERHlmKpkibp6LjJfffUVBEFQSDwUZNLFzs4OK1asgLe3Nz58+ID+/ftj1apVcHd3h52dHR49eoSdO3fi7du3AIBJkyYp1LORMTU1BQCEhIRg7ty5qFixIurUqQMXFxf06tULs2fPhiiKWL16NS5duoQOHTrA1tYWCQkJCAoKwj///IOMjAwAwP/+9798e/xERJR3mHQhIiIiohxr0KCBVNcFAMqUKaNQp0UVOzs71K1bF4GBgdJ9BZl0AYDBgwcjKSkJEyZMQEpKCi5cuIALFy4otBEEASNHjsT8+fNVjtG0aVMcP34cAPDjjz8CADZt2gQXFxfUqlULK1aswHfffYfU1FTcvn0bt2/fVhrD2NgYc+fORd++ffX8CImIqCBweRERERER5ZiJiQmaNGkifS+bxZId2dbRAFCpUiWUKVNGp/N6enpCFEVERETo1E+TUaNG4d69e5g8eTKqV68OS0tLWFpaws3NDT4+Prh16xbWrFmjtt7K999/j/Hjx6NMmTIwNjZGuXLlYGNjIx3/5ptv8OjRI0yYMAGNGjWCg4OD1K558+b4/vvv8fjxY50K9BIRUeEmiKoWlBLpQdmyZREVFQUHBwdERkYWdDhERET0hXN2dsaTJ0/g7e2NzZs3F3Q4RESUBwrbdShnuhARERERERER5QEmXYiIiIjoi5CamlrQIRAR0ReGSRciIiIi+uy9efMGr169ApBVrJaIiCg/cPciIiIiIvpshYSE4O7du1izZo20HXP16tULOCoiIvpSMOlCRERERJ+tBQsWYMuWLdL3ZcuWxcCBAwswIqL/x96dx0dV3f8ff09CCGsgZFMSY9xQAwiEgFIVSBU0oxWtC27VtFUsjdrautUWxa36rVq3plSsNbYV+am1gjgIUQE3qiQRJCBuFSJBZhISCGsYkvn9Qec6k8xMQnJnfz0fDx8OuXfO+dx7J3dm3jn3XADxJGYuL9qwYYOuv/56DR8+XCkpKRowYIAKCgp06aWX6vXXX+9SGzabTeedd55ycnKUnJysI488Updddpnee++9LtdBGwAAAJGjb9++6tOnj4477jhdd911eu+995Senh7usgAA8cIVAx5//HFXQkKCS5Lf/84++2zXli1bfD7/wIEDrmuvvTbg8++8886ANdBGR9nZ2S5Jruzs7E7XBQAAAACgpyLte6jF5XK5ghPnhMaCBQt0/vnnG/8uKipSYWGhBg8erA0bNuhf//qX9uzZI0kqLCzUypUr1auX91VVs2bN0n333SdJSklJ0ZVXXqkjjzxS69ev1/z589XS0iJJmjt3rq699lqfddBGR5F2f3QAAAAAQGyLtO+hUR26tLW1KT8/X5999pkk6YUXXtCll17qtc6mTZs0depUff7555KkefPm6bLLLjOWf/XVVxo2bJja2tqUm5urFStWKC8vz1heVVWloqIi7dy5UykpKaqtrdWgQYO8+qAN7zbcIu3FDgAAAACIbZH2PTSq53T5/PPPjcDl4osv7hC4SNKRRx6psrIy49/t5yN59NFH1dbWJkn605/+5BUwSNLYsWN17733SpKam5v117/+tUMftAEAAAAAANqL6tDlyy+/NB5fcsklftebOHGicUnRJ598Yvzc5XLp1VdflSQNHjxYxcXFPp/vOTJm4cKFXstoY6HPdQAAAAAAiHcxE7oceeSRftfr3bu3UlJSJElNTU3Gzz///HPV1dVJkqZOndphrhe3zMxMjRs3TpL0wQcfaPfu3bThpw0AAAAAAHBQVIcuF198sVatWqVVq1Zp5MiRftez2+1qbGyUJB177LHGz2tra43HRUVFAftyLz9w4IBX2EMb3m0AAAAAAICDojp0yc7OVmFhoQoLC9WnTx+f6+zatcvrDjs//vGPjcd2u914nJWVFbCvzMxM47FnyEAbInQBAAAAAMAH39ePRLHNmzfrH//4hxobG7Vp0ya9/vrrxi2jb7zxRp133nnGup4hQ2pqasB2hwwZYjx2OBy04acNAAAAAABwUMyFLl9++aXuuOMOr58lJCTo2Wef1Y9+9CNZLBbj554hw+DBgwO26xlCuEMc2ujYhi8ul0vNzc0B1wkkOTlZycnJ3X4+AAAAACA6tLS0qKWlpdvPd7lcJlbTczEXuvjS1tam66+/Xlu3btUtt9xiBC/ueV4kqX///gHb8FzuGTLQRuehy5YtWzRo0KCA6wRy1113afbs2d1+PgAAAAAgOjzwwAO6++67w12GaWIudJk8ebJcLpd2796tr776SkuXLtX999+v7du367bbbtO+fft05513Sjp4VyO3Xbt2BWx3x44dxmPPURe0oU5HoQwdOlSffvppwHUCYZQLAAAAAMSH3/zmN/rVr37V7eefeOKJ2rJli4kV9UzMhS5u/fv310knnaSTTjpJ559/vkaNGqU9e/bogQce0M9//nOlp6erX79+xvqet5L2xXO55ygP2uh8VIzFYjFu2Q0AAAAAgD89nV7Cc0qRSBDVdy/qqmOPPValpaWSpH379umtt96SJKWnpxvrdBYybN++3XjsOYksbXi3AQAAAAAADorqkS7vvPOO9uzZo5SUFH3ve98LuO7YsWONx998840k6bjjjjN+9u233wZ8/tatW43Hw4YNMx7ThncbAAAAAADgoKge6XL77beruLhYl19+eafrJiR8t6nu4Ub5+fnGz5YtWxbw+W+//bbRjmfIQBsJhC4AAAAAAPgQ1aHLMcccI+ngyJX9+/cHXHf9+vXG4yOOOEKSdMIJJyg7O1uS9Oabb8rpdPp8rt1u1+rVqyVJEyZM0MCBA41ltOHdBgAAAAAAOCgmQpe2tjb9/e9/97ve7t279eyzz0o6ODKjqKhI0sERL9OmTZMkNTc36/XXX/f5/Pnz5xuPzz//fK9ltHG+z3UAAAAAAIh3FpfL5Qp3Ed1VWVmpcePGSZKysrK0YMECnXzyyV7rNDU16brrrtNLL70kSbrqqqv03HPPGcu/+uorDRs2TG1tbcrNzdW7776r3NxcY3l1dbWKiorU3NyswYMHa9OmTR3uxEMbvu9MlJOTo7q6OmVnZ2vz5s0+1wEAAAAAwCyR9j00qkMXSbr44ov18ssvSzo4iuXcc8/V8OHDNWDAAG3YsEFvvPGG6uvrJUm5ubn66KOPlJWV5dXGrFmzdN9990mSBg8erKuuuko5OTlat26d5s+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qAQAAAABwxSPpEoCys7M1YsQI9e7dWx9//LEyMjJ04cIF7d27V7Nnz1bnzp2VmJhY7P3/+9//lsvl8ulRv3596w4MAAAAAIAypJy/K4CiS0pK0ltvvSVJCg8P18CBA1WvXj1t3bpVs2fP1vnz5zVhwgRFR0dr+PDhRd7/zp07ra4yAAAAAABXHHq6BJiffvpJf/3rXyVJdevW1YYNG5SSkqKnn35a06dP17fffqurrrpKkjRmzBidPHmyyDHcSZdatWopOTm5wMf48eOtO7hSlJKS4u8q5EGdfOPEOjmVE88VdfKNE+vkVE48V9TJN06sk1M58VxRJ984sU5O5cRzRZ1848Q6OYqBgJKQkGBIMiQZCxYs8Fpm6tSpZpkpU6YUOUabNm0MSUbv3r1LVNdatWoZkoxatWqVaD92aN68ub+rkAd18o3T6nTy5ElDknHy5El/VyUPp50rw6BOvnJanWjnRUOdfOO0OtHOi4Y6+cZpdaKdFw118o3T6uS076H0dAkghmHoo48+kiRVqVJFvXr18louPj7eXF6wYEGRY7h7ujRt2rR4FQUAAAAAANxeFEh+/PFHZWRkSJK6d++ucuW8D8lTo0YNtW/fXpK0fPlynT171ucYmZmZZvkmTZqUsMYAAAAAAFy5SLoEkL1795rLXbt2LbCse31WVlaRBsbNXZakCwAAAAAAxUfSJYBkZmaay5GRkQWWrVGjhrlclKTLjh07zOXatWtr0qRJ6tixoyIiIlS5cmU1b95co0aN0vbt24tQcwAAAAAArjxMGR1AciddrrnmmgLLVq1a1Vw+fPiwzzFyJ2i6dOmSZ9tt27Zp27ZtmjZtml588UX96U9/ksvl8nn/AAAAAABcKUi6BJDcSZcqVaoUWDZ3UubXX3/1OUbupMvhw4fVrFkz3XnnnapWrZp27NihZcuW6YcfflBOTo6ee+45lStXTk8//bTXfR05ckSSdOjQIdWuXdvnOlzOjqROZmamoqOjLd9vSVAn3zitToZhSJKaN2/uuASk086VRJ185bQ60c6Lhjr5xml1op0XDXXyjdPqRDsvGurkGzvq5G6rxXHo0CFJ//d91O/8OHMSiujBBx80p4L+8ccfCyz7+eefm2UnTJjgc4x27dqZ2z333HNGVlaWx/qLFy8akyZNMsuUK1fO2LVrl9d9BQUFmeV48ODBgwcPHjx48ODBgweP0noEBQX5/D3YTvR0CSChoaHm8pkzZwose/LkSXM5LCzM5xhDhw7VgAEDVLt2bQ0aNCjP+nLlyumZZ57Rjz/+qNTUVGVlZSklJUWTJ0/OU7Z8+fI6d+6cgoODVb16dZ/rcDmnZeEBAAAAAPYxStDT5ciRI8rOzlb58uUtrFHxkXQJIBUrVjSXT5w4UWDZ3OsrVarkc4zRo0f7VG7ChAlKTU2VJC1atMhrmaJMVQ0AAAAAQFnD7EUBpFq1auZyYUmXX375xVzOPaiuVaKjoxURESFJ2r17t+X7BwAAAAAg0JF0CSBNmjQxlw8ePFhgWffgQZLUtGlTW+rToEEDSdJvv/1my/4BAAAAAAhkJF0CSIsWLczlJUuWFFj2yy+/lCQFBQX5nHQ5duyYdu/erd27dysrK6vQ8gcOHJCkEo3XAgAAAABAWUXSJYA0a9bMnHp58eLFunjxotdymZmZWr9+vSTppptu0lVXXeXT/j/88EM1aNBADRo00IIFCwose/z4cTPp0q5dOx+PAAAAAACAKwdJlwDicrnUt29fSdKpU6f0ySefeC03e/Zsc7lfv34+779///4KDg6WJE2dOlXZ2dn5lp04caK5fMcdd/gcAwAAAACAKwVJlwDz5JNPKijo0tP2+OOPa+/evR7r165dqxdeeEGSVKVKFY0YMcLnfVerVk29e/eWJH3zzTd66qmndOHCBY8yOTk5mjZtml577TVJUp06dfJMLf3pp5/qzjvvVHR0tMLCwlSvXj3Fx8dr2bJlRTtYwIFycnI0c+ZMdevWTTVr1lT58uXVqFEjDR8+XBs3biy1fQCFycnJ0ZYtWzRnzhy98cYbmj17tjZs2ODzFIxWXMt5P4Cdtm3bplGjRikmJkbh4eGqXLmy2rVrp3vvvTffH6YuRzvHlYK2jrLO0W3cQMD585//bEgyJBlVqlQxHnvsMePll182hgwZYoSFhZnrUlNT82ybmppqrv/d736XZ31GRoYRFRVllmnUqJHx2GOPGS+99JLxyCOPGG3atDHXhYSEGN988425bVZWljF8+HBzvbfHCy+8YOOZAYruzTffNCQZ48aNK7Ts2bNnjT59+uTbvkNCQow33njD9n0ABcnJyTFSU1ONevXqeW1j9evXN9555x0jJyfH6/ZWXMt5P4DdXnvtNSMoKKjANtazZ0/jwIEDXrennSPQ5eTkGPfcc48hyYiLi8u3HG0dTtepU6cC21buR2JiYp7tA6GNk3QJQFlZWcYDDzyQb4NwuVzGxIkTvW5bWNLFMAzju+++M+rWrVtgo4uMjDSWLFnisV3uZFB4eLjx6KOPGi+99FKeZNCbb75p8RkBiq9Lly4+JV1ycnKMgQMHerwGnnzySeNvf/ubMWDAAPPDv8vlMtLT023bB1CYp556yqcPLvfff7+RnZ2dZ3srruW8H8BOH330kUdb7tq1qzF27Fhj4sSJxqBBg4yKFSua62JjY42LFy/m2QftHIHu7bffNttYQUkX2jqcrmbNmiVKugRCGyfpEsD+97//GX369DGioqKM0NBQo06dOkZ8fLyxfPnyfLfxJeliGIZx7tw54x//+Idx2223GQ0bNjRCQ0ONiIgIo1OnTsaUKVOM06dPe5TfuXOn+YWxbt26xq5duzzWr1692rjqqqvMhvzLL7+U5NABS3z88cfm66GwpMvSpUvNstddd51x7Ngxj/Xp6elGcHCwIV3qIebtQ74V+wAKkrtNh4SEGBMnTjQ2btxonD592li3bp2RmJhohIaGmmUmTJjgsb0V13LeD2Cn7Oxs49prrzXb8KxZs/KU2b17t9G0aVOzzMyZMz3W084R6LZt2+aRXMwv6UJbh9OdPn3abMd33XWXkZycXODj+++/99g+UNo4SRdYIiEhwXzBLFiwwGuZqVOnmmWmTJlSyjUE/s+xY8eMl19+2QgPD/c56dK7d2+z7IYNG7yW+eMf/2iWSUtLs2UfQEE6duxotp9PP/3Ua5nvv//eKFeunCHJqFChgnH48GFznRXXct4PYKcffvjBbDsDBgzIt9yiRYvMco8++qjHOto5Atm5c+eMtm3bevz6n1/ShbYOp1u3bp3Zdj744IMibx8obZykC0osJyfHqF27tiFdGmMmv1/nMzMzzcZ6yy23lHItAcO45557jAYNGnjtrlhQ0uX06dNm74BWrVrlW27VqlXm/gYPHmz5PoCCHD161Gw7N998c75jthiGYYwdO9Ys+8477xiGYc21nPcD2C13b66CPqCfP3/eTC526tTJ/D/tHIHO/eNMlSpVCky60NYRCD744INCf5DMTyC1cWYvQon9+OOPysjIkCR1795d5cqV81quRo0aat++vSRp+fLlOnv2bKnVEZCkzz77TLt27Srydt9++605k1evXr3yLdeuXTvVqFFDkrRo0SLL9wEUZO3ateZynz595HK58i3brVs3c3nz5s2SrLmW834Au+3cudNcrlevXr7lQkNDFR4eLkk6ceKE+X/aOQJZenq6pk6dKkl66623CixLW0cgyH1Nb9y4cZG2DaQ2TtIFJZZ72uquXbsWWNa9Pisry+NFBpSGGTNm6IMPPjAfKSkpPm3naxsPCgpSly5dJEkHDx7UL7/8Yuk+gIIcOXLEXK5Tp06BZSMjI83lc+fOSbLmWs77Aew2YMAArVq1SqtWrVKrVq3yLZeZmanjx49L8vwgTztHoDp06JCGDBkiSXrooYf0hz/8ocDytHUEAndbqV27tipWrFikbQOpjZN0QYllZmaay7k/yHvj/gVfEhdklLq+ffvqD3/4g/m4/fbbfdquuG38p59+snQfQEFatmypyZMna/Lkybr55psLLLthwwZzuVGjRpKsuZbzfgC71a5dW7GxsYqNjVX58uW9ljlz5oyGDx9u/j1s2DBzmXaOQJSTk6MhQ4boyJEjatq0qdnbpSC0dQSCHTt2SJKaNGmibdu2afDgwYqJiVGFChVUvXp1/e53v9PUqVP166+/5tk2kNq49/4zQBHkbqzXXHNNgWWrVq1qLh8+fNi2OgFWsqKN8zqB3Vq3bq3WrVsXWu7ixYv6+9//bv7dsWNHSbRzBK79+/fr3Xff1fHjx7Vnzx598skn5gf0xx57THfeeadZlnaOQPT3v/9dn3/+uUJCQjRr1ixVqlSp0G1o6wgE7uTFxo0bFRMTo5ycHHPduXPn9PXXX+vrr7/WK6+8onnz5ik2NtZcH0htnKQLSix3Y61SpUqBZXM3Zm8ZS8CJrGjjvE7gBFlZWRo+fLjWr18vSbrlllt04403SqKdI3Dt3LlTzz77rMf/goKClJqaqkGDBnmMb0Q7R6BZs2aN2b4nTZqkdu3a+bQdbR1Od/bsWR04cECSdPz4cQUFBalPnz7q0KGDcnJytGnTJn3++ec6deqU9u/fr9tuu02rV69WkyZNJAVWGyfpghJz3zMtqdDMe+71XJARKKxo47xO4G/bt2/XsGHDtGLFCknSVVddpX/84x/meto5ypKcnByNGjVKhw4d0tixY83EC+0cgeT06dOKj4/XxYsX1a1bNz3xxBM+b0tbh9P9/PPP5nJERITmz5+f5/bo/fv3a/DgwVqyZIlOnTqlRx991JxoIpDaOGO6oMRCQ0PN5TNnzhRY9uTJk+ZyWFiYbXUCrGRFG+d1An/55Zdf9OSTT6ply5ZmwqV8+fL68MMP1aZNG7Mc7RyBqkuXLjIMQ2fOnNGGDRs0efJkValSRadPn9a4ceP04osvmmVp5wgko0eP1o4dO1StWjXNmDFDQUG+f3WjrcPpKlWqpEmTJmnSpElavHix1/HooqOjlZaWZt7as3jxYm3ZskVSYLVxki4osdwjTeeeltGb3Ot9uR8VcAIr2jivE5Q2wzA0a9YsNWnSRK+++qqysrIkXZqWfO3atR7TRku0cwS+SpUqqXXr1hozZoxWrVpltsdJkybp6NGjkmjnCByzZs3SjBkzJEmpqamKiooq0va0dThdw4YN9cwzz+iZZ55R27Zt8y1XtWpVj15e7p4ugdTGSbqgxKpVq2YuF9ZYc09/m3swIsDJrGjjvE5Qmo4ePap77rlH9913n/ll8+qrr9aUKVO0YsUKNW/ePM82tHOUJY0bN1ZCQoKkS4MxfvHFF5Jo5wgMJ06c0MMPPyxJSkhIUJ8+fYq8D9o6ypLcSZndu3dLCqw2TtIFJeYezEiSDh48WGDZQ4cOmctNmza1rU6Alaxo47xOUFp27typVq1aKS0tTZIUHBysUaNGaefOnXrqqac8utLmRjtHIPj666+1cOFCLV++vNCy119/vbm8b98+SbRzBIaTJ0/q1KlTkqSUlBS5XC6vD7f333/f/F/9+vUl0dZRtjRo0MBc/u233yQFVhsn6YISa9Gihbm8ZMmSAst++eWXki7NKsAFGYHC1zaenZ2tpUuXSpJq1KihiIgIS/cBFObIkSPq1auX+cGgWbNmWrFihZKTkz1+zfHGims57wew2zPPPKNevXrpvvvuK7Rs7vEv3F9Qaee4UtDW4XR79uzR7t27PZIZ+XHPciRJ1atXlxRYbZzZi1BizZo1U+3atZWRkaHFixfr4sWLCgkJyVMuMzPTnKb0pptu0lVXXVXKNQWKp3PnzgoNDdWFCxe0cOFCvfLKK17LrVmzxhwF/fLxMqzYB1CYBx54QDt37pR0qf3MmzfP5/uOrbiW834AuzVq1EgrVqzQvn37dOHChXx7bknS1q1bzeU6depIop0jMFStWlXJycmFlhs9erQk6brrrtMDDzwgSWY7o63D6eLj47VixQpFREQoIyOjwMFpN2/ebC67p00PpDZOTxeUmMvlUt++fSVJp06d0ieffOK13OzZs83lfv36lUbVAEtUrlxZv//97yVd+hC/bt06r+VmzZplLl/exq3YB1CQvXv3mtff5s2ba8GCBUUa6M2KaznvB7Bbo0aNJF2aEvo///lPvuXOnj2r1NRUSZd+lezatask2jkCQ3h4uEaNGlXow61p06bm/4YMGSKJtg7ni4uLkyQdO3ZM7777br7lzp49q1dffVXSpYFvb731VkkB1sYNwAI7d+40goKCDElG3bp1jT179nisX7NmjREeHm5IMqpUqWKcPHnSTzUF/s+uXbsMSYYkY9y4cQWWXbp0qVm2bdu2xvHjxz3WL1y40AgODjYkGU2aNDGysrJs2QeQnwkTJpjtKy0trVj7sOJazvsB7LRq1SqznUdGRhrfffddnjLHjx83BgwYYJYbPHiwx3raOcoKdxuPi4vzup62DifLyMgwwsLCDElGhQoVjCVLluQpc/jwYaNv375mW3/66ac91gdKG3cZhmEUPVUD5PX888/rL3/5iySpSpUqGjx4sKKjo7VlyxbNnj1b58+fl3Rp2ruhQ4f6sabAJbt37zYH5ho3bpz+9re/5VvWMAwNHjxY7733niQpKipKgwYNUkREhFavXq25c+cqOztbQUFB+uyzz8xeLVbvA8hPXFyc5syZI0maOHGiwsPDfdrutttu85jNyIprOe8HsNOAAQPMgaKDgoLUp08fxcTEqHLlytq2bZsWLlyoI0eOSJLq1q2rlStXKjIy0mMftHOUBe6xiuLi4jx+ic+Ntg4nmz59uoYNG2b+3bNnT8XGxiosLExbt27VZ599Zt52365dOy1btkwVKlTw2EdAtPEip2mAfGRlZRkPPPCAmYm8/OFyuYyJEyf6u5qAqSg9XQzDMM6ePWvcfvvt+bbxsLAwIzU11fZ9AN506dIl33ZV0OPy9mbFtZz3A9jp5MmTRvfu3Qtt27GxscbPP//sdR+0c5QF7raWX08Xw6Ctw/nGjx9vhISEFHg979mzZ54e4m6B0MZJusBy//vf/4w+ffoYUVFRRmhoqFGnTh0jPj7eWL58ub+rBngoatLFMAwjOzvbePfdd42uXbsa1atXN0JDQ4369esbw4cPNzZv3lxq+wAu16JFC0uSLm5WXMt5P4BdsrKyjLlz5xoDBw40OnToYFStWtUICwsz6tSpYwwYMMBIS0vz6RZN2jkCmS9JFzfaOpxs165dxiOPPGJ06NDB/GwcHR1txMXFGZ9++qmRk5NT6D6c3Ma5vQgAAAAAAMAGzF4EAAAAAABgA5IuAAAAAAAANiDpAgAAAAAAYAOSLgAAAAAAADYg6QIAAAAAAGADki4AAAAAAAA2IOkCAAAAAABgA5IuAAAAAAAANiDpAgAAAAAAYAOSLgAAAAAAADYg6QIAAAAAAGADki4AAAAAAAA2IOkCAAAAAABgg3L+rgAAAAAAAGVJenq6pk2bpjVr1ui3335TmzZt9Pjjj6tfv35+qY9hGNq4caO2b9+uAwcO6Ny5c4qIiFDz5s0VGxur8uXL+6VeVwJ6ugAAAAAAYJGkpCTdfvvt+vTTT1W9enXVrFlTS5cu1V133aU///nPxd6vy+XK8ygsiXP27FmNHz9ejRo1Utu2bRUXF6cnnnhCf/rTnzRixAh17txZVatW1YgRI7Rr165i160w2dnZqlWrllnvnTt3Fmn7SZMmmduOGzdOkrR06VKv52T69Ok2HEHxkXQBAAAAAMACq1ev1vjx49WsWTNt3rxZ69ev19atW/Xtt98qMjJSEydO1LJly0qlLl9++aVatGihpKQkj4RKuXLlFBISYv7922+/6a233lKrVq00Y8YMW+oSHBysuLg48+8PPvigSNvPnTvXXL7nnnssq1dpIOkCAAAAAIAFkpKSJEn//e9/1axZM/P/HTt21GuvvSZJev3110sUo1evXkpOTlZycrKGDx/utcz//vc/9erVS3v37pUkNW3aVP/85z+1Z88enTt3Tr/++qu2b9+u//znP2ratKmkS71ihg4dqtTU1BLVLz/x8fHm8pw5c3zebt++fVq9erUkqWHDhmrXrp0kqUmTJuZ5cJ93J3IZhmH4uxIAAAAAAAS6mjVrqmLFivr555/zrDtz5ozCw8PVsGHDIt9eI126vUiSEhMTC0wybN26Ve3atdP58+clSU8++aT++te/KiwszGv5ixcvKjExUZMmTZIklS9fXuvWrfNIGlnBMAw1btzYPDfbt283Ez4FSU5O1mOPPSZJeuaZZ8x65rZ79241aNBAkpSamqqhQ4daV/ESoqcLAAAAAAAldPr0aWVmZmrXrl1exxq56qqrZBiGjh49alsdsrOzNWzYMDPhMmbMGE2ZMiXfhIskhYSEaOLEiWai4ty5cxo/frzldXO5XB69XXy9xWjevHnmcqDdWiTR0wUAAAAAgBI7ceKEqlatqipVqqhDhw75lgsODtYnn3xS5P370tPlo48+0l133SVJatu2rVauXOkxfktBTpw4oaioKJ0/f17BwcHKzMxUREREketZkC1btqhly5aSpNatW2vDhg0Flj927JgiIyOVnZ2txo0b68cffzTPQ270dAEAAAAAwMGmT58ul8ulatWqSZIuXLigf/7zn+rQoYOqVKmiypUrq2XLlho3bpwOHjyYZ/trrrlGVatWVbVq1bRw4cJ8H8VJuPgqJSXFXJ44caLPCRfpUv379+8v6VKPmaVLl3otl5OTo9mzZ+vOO+9U7dq1FRYWpvr166tbt2567733dOHChXxjxMTEqFWrVpKkjRs3atu2bQXW6eOPP1Z2drakS71cvCVcnI6kCwAAAAAAuRw+fFi33HKLRo8erZUrV+rkyZM6e/astmzZopdfflnNmjVTenp6nu1atWqln3/+WT/99FOedVu2bFG/fv00depUW+p88uRJffHFF5KkunXrqkePHkXex8yZM2UYhgzD0N13351n/eHDh9W5c2fFx8fr448/1oEDB3ThwgXt2bNHixcv1qBBg9SyZcsCx6wpyi1GgTxrkRtJFwAAAAAA/r/s7GzFxcXp+++/V6VKldS3b1+9+OKLGjx4sKKjoyVJp06dUr9+/bRmzRqPbZ999lnl5ORo0KBB2rdvn/n/w4cP64EHHtD8+fPVsGFDW+q9YsUKuUcPufXWWxUcHGzp/n/99VfdeuutWr58uSSpfv36Gj58uCZNmqSHHnpI9evXlyTt2LFDN910k/bs2eN1P/fee6+5XNAsRmfOnNHnn38u6dLsS61bt7boSEpXOX9XAAAAAAAAp/jll1+0dOlS1alTRwsXLlSLFi3MdWfOnNHgwYM1b948XbhwQQ8//LBWrlxp3vbSvXt3jRw5Um+88YaaNGmimJgYhYaGat26dTp//rxGjBihO+64w5Z65x4fpX379pbv/4UXXtCWLVskSePGjVNSUpLKly9vrj937pyef/55TZkyRUePHtVTTz2ltLS0PPtp0KCBbrzxRn333XfavHmztm7d6nGO3RYuXGgOCByotxZJ9HQBAAAAACCPjz/+OE8yoHLlykpLSzPHJVm9erW+++47jzL/+te/NGvWLN1yyy3at2+ffvzxR8XGxmrWrFmaNm2abcmDY8eOmcuRkZGW7vuXX37RtGnTJEl33323Jk2a5JFwkS5NNf3yyy+bA/l++OGHXm+zkny7xSjQZy1yI+kCAAAAAEAuvXr1Ups2bbyuCwoK0nPPPWf+vWDBgjxl7r33Xn3++ec6fPiwjh07pmXLlunee+9VUJB9X8FPnDhhLoeHhxdYdsyYMV6ntc796NKli1k+PT1dv/76q8e23rhcLj355JPm3998843Xcvfcc495Lt5//31dPqnyhQsXzAGHr732WnPGo0DE7UUAAAAAAOTinsUnP3379jWXV69ebXd1fFKhQgVz2Z0gscqKFSvM5e+++67AY84de9OmTV7L1KxZU127dtUXX3yhH374wWMqaUlasmSJTp48KSmwby2SSLoAAAAAAOChQYMGBa4vX768atWqpQMHDujAgQOlVKuCRUREmMtHjx4tsGy/fv3MgW8v99prr+WZfWj//v3m8hNPPOFznU6dOpXvuvj4eHO2pTlz5ngkXcrCrEVuJF0AAAAAAMilVq1ahZaJjo7WgQMHzB4Z/lavXj1zef369QWW7dSpkzp16uR13YwZM/L8r6DkSUEK2q5///565JFHdPHiRc2ZM0fjx4+Xy+VSTk6O5s+fL0lq3ry5YmJiihXbKRjTBQAAAACAXHIPSpufQ4cOSbo0uK4kJSUlFTpOSn5jplihc+fO5vLSpUvzjJPiC8MwPHq1uFWsWFGSFBYWpuzsbBmG4dPj/fffzzfWNddco169ekmStm/fbt6KtGLFCmVmZkoK/FuLJHq6AAAAAADgYffu3fn2BJGk8+fPa9++fZKkGjVqSJIaN26sHj16eJTLyMjQ5s2bVatWLXPGI7fWrVtbWueGDRuqQYMG2rVrlzZv3qzVq1cXeero7du3m8mk3NyzIZ0/f1779+9X3bp1LalzfHy8ORDxnDlz1Lp1a49ZiwYMGGBJHH+ipwsAAAAAALm4xxrJT3p6utmTxJ3YGDhwoBYuXOjxeOqppyRJ3bp1y7Pu5ZdftrTOLpdLCQkJ5t8vvPBCkXu7JCcne/3/DTfcYC6vWbOmwH1s27ZNSUlJSkpKynfKaLc77rjD7EUzZ84cGYZhJl1iYmIC/tYiiaQLAAAAAAAe3nvvPe3evdvrupycHI0fP978u3fv3qVUq8I99NBD5oC6CxcuzDeJ4s0333yjN9980+u6nj17mlM8JyYmKisrK9/9PP/88xo/frymTJmimjVrFhizUqVK5kxQO3bs0Lvvvquff/5ZUuAPoOtG0gUAAAAAgFyysrJ05513as+ePR7/P3v2rO655x5zoNrWrVura9eufqihd1dffbXefvtt8+/HH39cL730krKzswvcbvHixerbt2++yZQ6deqYSZBNmzZp+PDhOnPmjEcZwzD0yiuvKC0tTdKlW4MqVapUaJ3j4+PN5T/+8Y/mclm4tUhiTBcAAAAAADxUq1ZNmzZtUtu2bdWjRw+1atVKO3bs0JdffmmO5RISEqK3337bcQO99uvXz7y9R5KeeeYZzZo1S48++qhuv/12RUVFKTg4WL/++quWLVumf//735ozZ44kqXv37qpYsaI++uijPPudOnWqli5dqkOHDmn69On64osv9Pvf/17XXnutTpw4ofT0dG3cuFHSpfFtpkyZ4lN9e/TooWuuuUYnTpzQiRMnJEmtWrVS8+bNS34yHICkCwAAAAAAuaSlpWn48OHasWOH3n///Tyz8ISHh2v27NlFHqi2tCQmJioiIkJjxozR+fPntWHDBo0cOVKSFBwcrAoVKuTpqTJs2DD961//0jvvvOM16RIZGamvvvpKffr00Y4dO7Rv3z6lpqbmKde6dWvNmTPHvM2pMKGhobr77rs9euiUlVuLJG4vAgAAAADAQ7169bR+/XpNnDhRrVu3VuXKlVWhQgU1b95cY8eO1fbt283pjp1q1KhR+uGHH3T//febg9VKUnZ2tplwcblcuuWWW/TVV1/pnXfeUWhoqMfU05dr2rSpNm3apGnTpunWW29V9erVFRoaqsaNG6t3796aMWOG1q5dq2uvvbZIdb3vvvs8/i4rtxZJ9HQBAAAAACCPihUr6tlnn9Wzzz7r76oUW4MGDfTee+/pt99+09dff629e/fqyJEjCg8PV1RUlDp37mxOee0WExNT4KxHYWFhevjhh/Xwww9bVs+uXbsWeaalQEHSBQAAAACAMqxChQrq0aOHv6txReL2IgAAAAAAABuQdAEAAAAAALABtxcBAAAAABAgVq5cqX/+85+SLo3Z0rt3bz/XyD8yMjI0b948SdKxY8f8XJv8kXQBAAAAACBApKenKz09XZLUt2/fKzbpsmPHDo0ePdrf1SgUtxcBAAAAAADYgJ4uAAAAAIAr3tChQzV06FB/VyNfZXVK5eLq0qVLQJwTlxEItQQAAAAAAAgw3F4EAAAAAABgA5IuAAAAAAAANiDpAgAAAAAAYAOSLgAAAAAAADYg6QIAAAAAAGADki4AAAAAAAA2IOkCAAAAAABgA5IuAAAAAAAANiDpAgAAAAAAYAOSLgAAAAAAADYg6QIAAAAAAGADki4AAAAAAAA2+H9zN5pjK5D1DQAAAABJRU5ErkJggg==\n",
       "text/plain": [
        "<Figure size 1200x1200 with 2 Axes>"
       ]
@@ -282,15 +283,16 @@
     }
    ],
    "source": [
+    "#datamc.define_figure(year)\n",
+    "#datamc.plot_datamc()\n",
+    "#datamc.plot_datamc_ratio(ax=datamc.rax)\n",
     "datamc.define_figure(year)\n",
-    "datamc.plot_datamc()\n",
-    "datamc.plot_datamc_ratio()\n",
-    "#datamc.plot_datamc_ratio()"
+    "datamc.plot_datamc()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "id": "105ce019",
    "metadata": {},
    "outputs": [],
@@ -300,23 +302,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "id": "70efe610-3668-43e2-8bc4-d0eaaaac5d2d",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<pocket_coffea.utils.plot_utils.PlotManager at 0x7f60d4cda3a0>"
-      ]
-     },
-     "execution_count": 13,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "from pocket_coffea.utils.plot_utils import PlotManager\n",
     "\n",
@@ -326,23 +317,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": null,
    "id": "c922cbf7-0bdd-45fc-843d-5667c9e6a968",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<pocket_coffea.utils.plot_utils.SystManager at 0x7f60d4cda040>"
-      ]
-     },
-     "execution_count": 14,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "from pocket_coffea.utils.plot_utils import SystUnc, SystManager\n",
     "\n",
@@ -352,95 +332,34 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": null,
    "id": "8d712bd2-e9be-4410-aa27-f06b6b057460",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['datamc',\n",
-       " 'get_syst',\n",
-       " 'mcstat',\n",
-       " 'syst_dict',\n",
-       " 'systematics',\n",
-       " 'total',\n",
-       " 'variations_down',\n",
-       " 'variations_up']"
-      ]
-     },
-     "execution_count": 15,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "[d for d in dir(syst_manager) if not d.startswith(\"__\")]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": null,
    "id": "5f139750-b13f-45fa-9ae3-18f01726cd2d",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "{'JER': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4cc0d00>,\n",
-       " 'JES_Total': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4cc09d0>,\n",
-       " 'pileup': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4cc0bb0>,\n",
-       " 'sf_btag_cferr1': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4ccf6d0>,\n",
-       " 'sf_btag_cferr2': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4c8afd0>,\n",
-       " 'sf_btag_hf': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4ccffd0>,\n",
-       " 'sf_btag_hfstats1': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4c8caf0>,\n",
-       " 'sf_btag_hfstats2': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4c8c160>,\n",
-       " 'sf_btag_lf': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4c8dbe0>,\n",
-       " 'sf_btag_lfstats1': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4c8dcd0>,\n",
-       " 'sf_btag_lfstats2': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4a92df0>,\n",
-       " 'sf_ele_id': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4a92d00>,\n",
-       " 'sf_ele_reco': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4a95e50>,\n",
-       " 'sf_ele_trigger_era': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4a954c0>,\n",
-       " 'sf_ele_trigger_ht': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4a97f70>,\n",
-       " 'sf_ele_trigger_pileup': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4a97f40>,\n",
-       " 'sf_ele_trigger_stat': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4a98e20>,\n",
-       " 'sf_jet_puId': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4a98f40>,\n",
-       " 'sf_mu_id': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4a9af40>,\n",
-       " 'sf_mu_iso': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4a9dfa0>,\n",
-       " 'sf_mu_trigger': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4a9da30>,\n",
-       " 'mcstat': <pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d60507f0>}"
-      ]
-     },
-     "execution_count": 16,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "syst_manager.syst_dict"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": null,
    "id": "9760a85f-9ae9-43b5-b8f7-9df57e2ac350",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4cc0bb0>"
-      ]
-     },
-     "execution_count": 17,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "pileup = syst_manager.get_syst(\"pileup\")\n",
     "JES_Total = syst_manager.get_syst(\"JES_Total\")\n",
@@ -449,161 +368,60 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": null,
    "id": "bdfabb2c-8023-4921-bb21-6cfd64c0395e",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['_get_err2',\n",
-       " '_get_err2_from_syst',\n",
-       " '_is_empty',\n",
-       " '_n_empty',\n",
-       " 'datamc',\n",
-       " 'down',\n",
-       " 'err2_down',\n",
-       " 'err2_up',\n",
-       " 'h_mc_nominal',\n",
-       " 'is_mcstat',\n",
-       " 'name',\n",
-       " 'nominal',\n",
-       " 'nsyst',\n",
-       " 'plot',\n",
-       " 'ratio_down',\n",
-       " 'ratio_up',\n",
-       " 'style',\n",
-       " 'syst_list',\n",
-       " 'up',\n",
-       " 'xbinwidth',\n",
-       " 'xcenters',\n",
-       " 'xedges',\n",
-       " 'xlabel']"
-      ]
-     },
-     "execution_count": 18,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "[d for d in dir(pileup) if not d.startswith(\"__\")]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": null,
    "id": "61768a25-1746-43d7-9c04-e3c41f00f8ea",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 8.51337422e+07,\n",
-       "       8.90241147e+07, 6.64709598e+07, 4.59969080e+07, 2.82356043e+07,\n",
-       "       1.78276167e+07, 1.00355040e+07, 6.55987354e+06, 3.78138649e+06,\n",
-       "       2.23447858e+06, 1.30466117e+06, 8.02222623e+05, 4.72369448e+05,\n",
-       "       2.87164680e+05, 1.77262956e+05, 1.06025114e+05, 6.91775404e+04,\n",
-       "       4.31903425e+04, 2.70651251e+04, 1.81530320e+04, 1.08317567e+04,\n",
-       "       7.50194295e+03, 4.49418414e+03, 3.24486251e+03, 2.19998961e+03,\n",
-       "       1.12964046e+03, 8.97573917e+02, 7.08310409e+02, 5.53588187e+02,\n",
-       "       3.30488474e+02, 2.01758672e+02, 1.44288738e+02, 1.02800902e+02,\n",
-       "       8.86509731e+01, 7.86310281e+01, 4.85163362e+01, 4.51786076e+01,\n",
-       "       3.98595327e+01, 2.01625029e+01, 1.37058162e+01, 2.92223969e+01,\n",
-       "       1.37124958e+01, 6.93892325e+00, 5.89023492e+00, 4.93240838e+00,\n",
-       "       3.26040344e+00, 6.62067888e+00])"
-      ]
-     },
-     "execution_count": 19,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "pileup.err2_up"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": null,
    "id": "51d6a9d3-558d-456e-acd8-0eafd709465b",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 2.02656822e+07,\n",
-       "       2.17308697e+07, 1.66442304e+07, 1.18335686e+07, 7.37476730e+06,\n",
-       "       4.73021724e+06, 2.64759568e+06, 1.78458721e+06, 1.02357480e+06,\n",
-       "       6.09997298e+05, 3.51991067e+05, 2.19712149e+05, 1.29681615e+05,\n",
-       "       7.78051990e+04, 5.01615061e+04, 2.86600587e+04, 1.90775747e+04,\n",
-       "       1.20582843e+04, 7.20273063e+03, 4.89034759e+03, 3.16110538e+03,\n",
-       "       2.02555795e+03, 1.22943144e+03, 8.96961366e+02, 6.17372767e+02,\n",
-       "       2.87447372e+02, 2.37476197e+02, 2.03730107e+02, 1.60001047e+02,\n",
-       "       9.68389643e+01, 5.77194977e+01, 3.83799760e+01, 2.96710093e+01,\n",
-       "       2.65471836e+01, 2.55496134e+01, 1.25101752e+01, 1.42294449e+01,\n",
-       "       1.21007688e+01, 6.18274467e+00, 3.59160479e+00, 8.12502747e+00,\n",
-       "       5.20526733e+00, 1.85857319e+00, 1.80768379e+00, 1.74494923e+00,\n",
-       "       8.60198034e-01, 1.92928490e+00])"
-      ]
-     },
-     "execution_count": 20,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "pileup.err2_down"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": null,
    "id": "7752ee8b-0dbd-4ded-bb88-06725af4267b",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0"
-      ]
-     },
-     "execution_count": 21,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "pileup._n_empty"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": null,
    "id": "a62e6c6b-e08e-4387-af71-81eb1ea902c5",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<pocket_coffea.utils.plot_utils.SystUnc at 0x7f60d4803460>"
-      ]
-     },
-     "execution_count": 22,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "s_sum = pileup + JES_Total\n",
     "s_sum"
@@ -611,221 +429,72 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": null,
    "id": "a1e65a02-632d-44e3-a9b3-b1062ae2d2e2",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'pileup_JES_Total'"
-      ]
-     },
-     "execution_count": 23,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "s_sum.name"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": null,
    "id": "0f39e4ac-627a-4a54-813f-e769c2c5b371",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 2.25806757e+05,\n",
-       "       2.26535243e+05, 1.91588041e+05, 1.55574641e+05, 1.21627448e+05,\n",
-       "       9.49689294e+04, 7.21009542e+04, 5.72741375e+04, 4.40003891e+04,\n",
-       "       3.39193336e+04, 2.63300267e+04, 2.05633756e+04, 1.60511352e+04,\n",
-       "       1.25832364e+04, 9.88849950e+03, 7.87600155e+03, 6.33039723e+03,\n",
-       "       5.06530613e+03, 4.09517215e+03, 3.31261179e+03, 2.69942393e+03,\n",
-       "       2.19986359e+03, 1.79598653e+03, 1.48753835e+03, 1.21714564e+03,\n",
-       "       1.00826226e+03, 8.57665994e+02, 7.29275142e+02, 5.99958888e+02,\n",
-       "       4.91218753e+02, 4.36476528e+02, 3.63295001e+02, 3.03137107e+02,\n",
-       "       2.68162037e+02, 2.27362756e+02, 2.02136569e+02, 1.71023651e+02,\n",
-       "       1.47058240e+02, 1.27441950e+02, 1.13981028e+02, 1.00391585e+02,\n",
-       "       8.24555328e+01, 7.42288373e+01, 6.25570875e+01, 5.99941083e+01,\n",
-       "       5.30236269e+01, 4.70497157e+01])"
-      ]
-     },
-     "execution_count": 24,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "s_sum.up"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": null,
    "id": "3b2968aa-3aac-4af0-b534-2178dc5d277c",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 2.00040019e+05,\n",
-       "       2.00292883e+05, 1.69206880e+05, 1.37290504e+05, 1.07452081e+05,\n",
-       "       8.39788368e+04, 6.38926637e+04, 5.07792096e+04, 3.91324276e+04,\n",
-       "       3.02213645e+04, 2.35475409e+04, 1.84126443e+04, 1.44164748e+04,\n",
-       "       1.13255818e+04, 8.90637700e+03, 7.12786574e+03, 5.73028191e+03,\n",
-       "       4.59309349e+03, 3.72802385e+03, 3.01496591e+03, 2.46662245e+03,\n",
-       "       2.00622518e+03, 1.64674215e+03, 1.36381887e+03, 1.11278133e+03,\n",
-       "       9.32363899e+02, 7.91049485e+02, 6.71703028e+02, 5.48385797e+02,\n",
-       "       4.50671356e+02, 4.05438259e+02, 3.36839810e+02, 2.78314290e+02,\n",
-       "       2.47076839e+02, 2.08073739e+02, 1.87189350e+02, 1.56247476e+02,\n",
-       "       1.33770381e+02, 1.17515282e+02, 1.06020823e+02, 8.92708660e+01,\n",
-       "       7.47261394e+01, 6.82490816e+01, 5.71709897e+01, 5.52665686e+01,\n",
-       "       4.91861115e+01, 4.18536275e+01])"
-      ]
-     },
-     "execution_count": 25,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "s_sum.down"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": null,
    "id": "e4cca839-62b8-404a-8c30-b977dc422fab",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['pileup', 'JES_Total']"
-      ]
-     },
-     "execution_count": 26,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "[s.name for s in s_sum.syst_list]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": null,
    "id": "881d8932-6df6-4596-baa6-f0ad6e05bffc",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(<Figure size 1200x900 with 1 Axes>,\n",
-       " <AxesSubplot: xlabel='$p_{T}^{e}$ [GeV]', ylabel='Counts'>)"
-      ]
-     },
-     "execution_count": 27,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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NFz5Hyp+VTCYT3bp1E7NmzRJ79uwRQgjRt29fqV5OTo7Wa+LevXvC2tpaLQFERERE9LwwmUFFOnnypNYb9fbt2z+zfepLZsjlcuHh4aH2+eLFi9Xa9+vXT6188ODBQghRrGSGEELk5uaKzz77TO83qIY8rK2txerVqzVufovy22+/aWzL3Nxc9OrVSyxfvlxERkYavK2NGzdK2zhz5oxa2XvvvadxPnJzc6Xy/Px80aFDB7U6nTp10uiZsGzZMql8ypQpamVnzpwx6AY8LS1NmJiYCABizpw5amXJycnSNubNm6dWlp+fL9zd3aXEz8WLFzW2HRcXJ7y9vaVt3LhxQ61cLpeLypUrCwBi6NChWuOrVauWACB69eql9vmDBw9E1apVBaDoLfTtt99q3EhGRUWp3cgfPXpUYxuq59jOzk789ttvateNXC4X06dPl+oUlRjSRXnjbG5uLrKzs/XWPXPmjNTzAoAYPXq0WnnhfyO8vb3F/v37NbaTnZ0tbcfMzEx8++23GvtOS0sT3bp1k7b1zTffqJXruwaMfY2r9mJbsmSJWtmff/6ptu3atWuLU6dOqdXJysoSzZs3l+rs3LlTrbwsrnHVcwRANGrUSGsya9q0aVIdbT2QhBBi0qRJAoCwtLQUMTExWusQERERPSucM4OKpGtiwKysrOcciYJMJtOYN+O///6TXgshNCb/LM58GarMzc0REBCAmJgYrF27FsOHD4erq2uxt5OVlYWpU6fi+++/L1a7CRMm4KOPPlL7LC8vDwcPHsQ777yDmjVrokGDBvjggw8QHBysd1vKlU1MTU3RpEkTrWUA8O6772LBggVqc4aYmppiwIAB0vu6deti165dapONAsD//d//Sa+dnJzUylSX39W3CklwcLA0X0CLFi10xll4G0ePHsX9+/cBKJYRLdwWAKpWrYrevXsDUFxHhed9uHPnjjQXgrbJP5OTk3H79m2tsb3//vvS8sW//fYb5syZA1NTU7U6Pj4++OKLL6T3hed7Kbz6zNatWzFx4kTIZDLpM5lMhlmzZknvDVkFSNtxKOcicXJywq+//ooVK1aoPZYtW4bZs2ejS5cuaNeuHcLCwgAoVgVatWqVzrhtbW1x+PBh6Tyr+u677xAWFgYTExNs3rwZc+bMgaWlpVodOzs7aU4LQP85KnwNGPsaV92HvmvXyckJR48e1fh3zMrKSm2528I/27K4xlXjqFq1KgIDA7Ve66rHHRsbq1EeHh6OtWvXAgBmz56N6tWra9QhIiIiepa4mgkVycXFRevnqampzzmSp9q1a4c///xTen/mzBnI5XKYmJggMjISSUlJGvVLw9nZGePHj8f48eMhl8tx+fJlXLx4EZcuXcLly5dx5coVZGZmFrmdDz/8EG+88YbGDZIuMpkMixcvxogRI7Bq1Srs3r1b48YiNDQUoaGh+Prrr9GzZ0/873//Q5UqVTS2pbyJqV+/vtoqJ3K5XEqEuLi4YMmSJVpjUa7wAQDffvstHB0dNeokJydLr2vUqKFWppy00cHBAXXq1NF5zKqTOxa+WVNNiBSe+LFOnToIDAwEoP/nHRUVBQBo0KABbGxs1MrOnz8vvdZ2g6eaMFKN7fr169iwYQMAxSSP+lae6dKli/S68CS1qjeakydPlibTLEw1uVG7dm2d+9JFdT+JiYl45513DGr3+uuvY/369RoJTtXtffvtt1p/vpmZmfjqq68AKJZPHTp0qM791KlTB46OjkhJSUFCQoJamb5rwNjXuOp5KDxxpmrZqlWrNJIMSvp+tmVxjavGsW7dOp3/vheVzJg/fz4KCgrg4uKCefPm6YyFiIiI6FlhMoOKpOuP3ZiYGOTm5sLCwuI5R6S5osmjR48QEREBX19fjV4ZlpaWaNasWZnt28TEBM2bN1e7WcnPz8fly5dx/Phx/PPPPzqXss3Pz8eaNWuwcOHCYu2zUaNGWL16NVatWoWQkBDs3bsXe/fuxblz59RWPTh06BA6dOiAoKAgODg4SJ/L5XJcunQJgOa32bdv35YSU6NGjdL4plxJuRqFm5sbevXqpbXOlStXpNeF96O8CW3ZsiVMTHR3ClPWs7e317gpVpa5ublp3Az6+PjoXFIXUJz7f//9V7oZbN26tc59K3/GhenqFfDLL79Ir+fPn68zBgCoXLmy9Lpwzw3V7StXmtBGdWWQkixNqpoQ0MfCwgJVq1ZFp06dMG7cOHTr1k1rPWXcdnZ20kodhf35559SssDZ2RkrVqzQu2/lqimFE3+6roHycI0rz0ONGjXU/t0UQkhlbm5uGDx4sNZtq8ZgZWWFhg0bqpWV9hpXPUe1a9fWu/qIvmTGuXPn8NdffwEAPv30U1SqVEnndoiIiIieFSYzqEjW1taoV6+e1M1cKS8vD6GhoUZZnrVp06awtrZWG+py+vRprckMPz+/Z55wMTMzQ8uWLdGyZUu89957OH/+PAYNGqT1G03VITHFJZPJ0LRpUzRt2hTz58/HgwcPsGXLFvzwww+Ijo4GANy6dQvffPONWsIkIiJCWsZTX/d3XTerQgjpJrJTp04wM9P+T4eyjqWlpdqNWFpamrRUZFE338qeGc2aNdNIeijL/Pz81L7BVpWTk4ObN2/i1q1buH37Nm7fvo3Q0FBcuHBBrfeMtp4XyvgbNmwIW1tbjXLluXJ1dVW7kVYu0ern54dOnTrpPT7lzwnQTBSq9iwofCOrLU4TE5MSJepUe79cv34d9evXL/Y2lDIyMqSfbd++fWFlZaW13vbt26XXP/zwg8HbL5zM0HUNGPsaV01YFN5/TEwMHj16BAAYPHiwzm2rbr9p06Y6l4cu6TWueo7eeOMNnb9DgO5khhBC6olRs2ZNTJ06Vec2iIiIiJ4lJjPIIB07dtRIZgDAnj17ip3MGDlyJA4dOqT2ma2tLWJiYgzehrm5OVq3bo1jx45Jn50+fRoTJkzAmTNn1Oq2bdu2WPEBwKlTpzQ+s7e31xiHr0urVq2wfft2rftWjnkvC5UrV8asWbPw1ltvYciQIdi/fz8AYN++fWrJDEPH8utKNMTGxkpx60tG6LoRCw4OhhACgP75Mh4/foxbt25pjfPBgwfSNaJtG5GRkfjpp5+wdu1aPHz4UPrczs4Ovr6+mDRpEpKSkrB582YAmjd6BQUF0rnQlugAoHazqrwRvHv3Lu7du1fksSndvHlTeq3a8+Thw4fS8fXo0UPvNpTnuUGDBlqTLkVRtre1tUXdunWL3V7V5cuXpd5Br732mtY6+fn5OHHiRIm2r3pTre8aMPY1HhcXJw2J0bd/fT/bvLw8XL58WWcMpb3GVePQ9bNSqlKlCiwsLJCbm6uWzDh48KD07+6SJUuM0jOPiIiICGAygwzUrVs3ta70Shs2bMC8efP0ftOoKj8/H3v37tWYb6PwRHqGaN++vUYyIzMzU60LPlCy+TL69++vNjYeUHQPv3//vt5vM1W1atUKdnZ20jehhtqzZ490XB999JHOYT6qbG1tsWzZMunmWDkRpZIhEyN6enrCw8ND6/ZVhyXoutHXdyOm2hNA342isns8ULz5MtatW4cpU6YgNzcX1apVw1tvvYW2bduiRYsW8PT0lH5mb775JgBFb6MGDRqobSM8PBxpaWk6jzElJUVrokV13gt9c4EoqQ5T6Nixo/TakBtuQDFUQLV3QnElJibizp07ABS9XwoPdSkuQ+KOioqSfuc///xzfPLJJyXalyHzZRjrGi9tMgUArl69ipycHK31yuIaV8Yhk8m0DqNSZWJigmrVquH27dtSMkMul0u9Mlq1aoUhQ4bo3QYRERHRs8RkBhnk9ddfh7u7u0avglu3bmHlypVqqyvoc+jQIa0Th77yyivFjqlwkiIsLAz//vuvNNZeqSQ9Mzw8PDSSGYmJibh586bBsaalpWmdFNTT01Nvuy1btmDr1q0AUKybPtVx67Vq1VIrU97ENGjQQG1iRCGENDGivpss5cSYMplM6woKgOKmPjs7W+u2lDeKlStX1rvqwe+//y69Lrwf1YSI6rfyhw4dwsSJEyGEwAcffIDPP/9c57fFyvPQvHlzjS78Rd3Mqk7+qbp/1W/IC08IWVh2dra0Eki1atXUhimo3vDqupkGFD07lL9DJUlm6DqPJaU6X4au3w3V5Fpp5lfQF7uxr3FDkhkeHh56f/91JWvK6hpXltWrVw92dnY641Dy9vbG7du3pZ5HW7dulZLF33zzjcGJXSIiIqJngUuzkkEsLS11rnjw4Ycf4ujRo0VuIy4uDhMmTNBaNnDgwGLHpC1JUXgsfq1atbSu7FEUXfMejB49GhkZGQZtY8OGDWqTcyoVNceB8sYBgMZKDvocOXJEev36669Lr1Un/St8k3X79m1pUkZ9N9DKm6x69erpXKpX39KrqvNg6LoBio+Px549ewBovzFWbr9atWpqP9OPP/4YQgg0a9YMX375pd6bvNDQUAD658vQ9o22sr2S6nlUfpMOKIbJ6LNu3TrExcUBAKZNm6bWK0K5/UqVKuldoURf7wRDqLbXddNeHKo3z7p6eaj23FL2CtElMjISCxYswIIFC3D16lW1Ml3XQHm4xlUn/3R2dpY+V51Lo6ifl3L7Dg4Oatd/WVzj+iZI1UU5xCc2NhY5OTn49NNPAQADBgxQ61VEREREZAxMZpDB3nnnHa03WTk5OXjttdewePFirTf6crkcv//+Ozp37qz15tzJyQmDBg0qdjxOTk4aN52qwxSAki/JOmLECK2fX7hwAd26dcOePXu0JioAICkpCYsWLcLs2bO1lg8bNkzvvlWHlajeQOuTlJQkzZFRqVIlqas5oPgmXzl8oiTd3w0d1qC8EbOzs1ObhyE1NRW3b98GAJ3zOwghMH78eKknS+HJP1UnZ1SNITU1VTqGli1b6kyUJCcnqyXj9CUzWrRooXXYlK7JP1Unz9Q3L4TyJh1QfEM/ZcoUrdvXdxzA0x4EFhYWaNSokc56uui7IS+uzMxMaS4dfdtSjfPIkSM6f3fy8vIwZswYBAQE4Pvvv1frxaPrGgCMf42r7qfw/u/cuSP13ikqmaH82bZo0UK6/svqGlc9R8VNZuTk5GDJkiWIioqCqakpvvzyS4PaExERET1LTGaQwezt7bFt2zatM+zn5ORg/vz5cHNzQ79+/TBt2jRMnToVvXv3ho+PD4YPHy7NN1DYl19+qfZNZnEUXqK1sJImMzp27IgBAwZoLTt//jz69+8PHx8f9OzZExMmTMDs2bMxatQodOnSBR4eHvjkk0+kCS9VDR48uMix6p07d5Zef/jhh9IqCLqEhoaid+/e0jeyX331FVxdXaVyXcuJFlWmdOvWLembbUNu9Fq0aKH2Db1q/KdOndI4nszMTLz99ts4ePCg9FnhG8LY2FgpEaYag2qviKCgIOTl5am1E0IgMDAQ7du3V5sYtvDqHQUFBdJcCLpWEdF1Q9moUSPpm/INGzaoHYfS6dOn0bVrVyQmJgIAfv75Z7XhFg8fPpRWOTH02/umTZsWe/JFIYR0065vWIihVCf/1HeDbG9vL/0uBgcH48svv9T4/UhKSkK/fv1w+vRpAIqlaR0dHaVyXdcAYPxrPC4uThqCp2//+radkZGB69eva9Qrq2vckPNQmOrkq4sXLwYATJo0Cb6+vga1JyIiInqWOGcGFUuLFi2wbds2jBw5Uu2PbKXMzEzs3bvX4O1NmTIFb731VonjadeundaJSVXLS0Imk2HVqlW4fv26ziTM3bt3cffuXYO3WbNmTSxfvrzIem+++Sa++OILPHz4EPfu3YOvry/ee+89dOrUCdWqVYOJiQmioqJw+/Zt/PXXX9i1a5fUdurUqZg0aZLa9lQnRmzcuLHWsldeeUXnXAbKb4sB3d30MzMzpYkwC98oeXl5ScvoPnjwAO3bt8esWbPg5uaGS5cu4ffff8fNmzfh4uIifYOtb/JP1e1XrlwZHh4eiIuLQ3BwMPz8/DBgwADY2NggMjISZ86ckYYq2NraSj2HPvzwQ7z55ptSD5y0tDTk5uYCAHbu3CnNmaJcrSElJUVahaRwbHZ2dggICMBHH30EIQR69+6NQYMGoXnz5sjJycHJkyfVJqr9+eef0a9fP7VtqM7Hoe+Gt6jVLopy7949KSHQvHlzjaVvi6s4N8irV69GixYtkJ+fj/nz52PXrl3o3LkzKlWqhBs3bmD79u1Sz5zBgwdLvViUDBniYaxr3NDJP/Wdo0uXLkmJIdWfbVld4/omSNVFNZmRl5cHW1tb+Pv7G9SWiIiI6JkTRCVw6tQp4ebmJgCU6GFqairmz58vCgoKtG6/c+fOWtsFBgaq1bt586bOfdjb24v8/Hy1+v7+/lrr+vv7a40jPj5etG7dusTHqXy0aNFCxMbGGnx+jx49KmxsbIp1Pr/++mshl8t1nsvGjRurfS6Xy0WlSpUEADFq1CidscycOVMAEObm5iI7O1trnf/++0+KZdu2bRrlAQEBeuPv2bOn2LVrl/Q+NDRUrf1HH30klT1+/FitbMuWLXq3bWtrK9asWSPeeecdtc/ffPNNtXPh7e2tVl6zZk2pPDAwUPp8x44dGseXl5cnhg8frjcOLy8vsWfPHq3nb8mSJVK9u3fv6vxZBAcHS/XWr1+vs54uf/31l9R+zpw5xW5f2NixYwUA4ejoqPN3WdW2bduka07bw9zcXMyYMUPk5uZqtNV3DRj7Glf9d+Xhw4dqZb169RIARK1atfSdGvHdd99J24iOjlYrK4trXNc50uf27dtq2wsICDC4LREREdGzxmEmVCLt27fHzZs38dlnn+mcB0EbExMTvPbaa7hw4QK++OKLUn8zXKtWLbi5uWkta9OmTamXnXR3d8fp06fxyy+/aKwQYghvb2+sWrUK586d07kkpDZdu3bFzZs3MW3aNK3DepQcHR0xZcoUhIWF4f3339cYTy+Xy6Vv/Qt/YxwZGSmt2GJI1/omTZrA0tJSa52ill795JNPsGHDBrRu3RpOTk6wsrKCt7c3Ro0ahQMHDuDAgQPSEAxbW1uN4Q/K7depU0fj2/URI0bg33//RY8ePeDh4QFTU1M4ODigXbt2+OKLLxAdHY0JEyZgypQpaNq0KczNzeHt7Y3evXtL25DJZPjzzz/RqlUrWFlZoWrVqmqTqOr75h1QTHC5detW7Nu3DwMGDEDt2rVhaWmJ6tWro1evXlizZg3CwsLQt29fredPuX13d/cSrXZhKNWfU1lP/mnI7/KwYcNw/fp1zJo1C+3bt4eDgwOqVq2Kjh07Ys6cObh9+zaWL1+u9ZrXdQ2Uh2u8LCf/1LbiT2mvcX3nSB8vLy/p3xR3d3fMmTPH4LZEREREz5pMCC0D+4mKIS0tDUeOHMG+ffsQHByMBw8eSDemlSpVgqurK5o1a4ZWrVphwIABapMn6tKlSxccP35c4/PAwEB06dJF7bNBgwZh586dGnU/++wzBAQEqH22YMECjc8AwN/fX6Nbe2FCCJw9exYHDx7EpUuXEBoaiuTkZKSmpkIIAQcHB1SqVAn16tVDs2bN0LNnT7Rr167UCZuHDx8iPDwckZGRuHv3LqytreHs7IxGjRqhcePGpU7YEBFpEx0djTp16iA/Px+//PKLxhA2IiIiImNiMoOIiIg0DBw4EH///Tfq1auHK1euaF3lh4iIiMhYOMyEiIiI1Bw4cAB///03AGDp0qVMZBAREVG5w54ZREREJLl37x5atmyJhIQEdO/eHYcPH9aYj4eIiIjI2JjMICIiesldunQJBw4cwOPHj7F9+3ZERUXB1tYWV65cQc2aNY0dHhEREZEG9hslIiJ6yf3xxx/48ssvpfdWVlb4888/mcggIiKicotzZhAREb3ksrOzYW9vj6pVq2LYsGG4cOEC+vTpY+ywiIiIiHTiMBMiIiIiIiIieqGwZwYRERERERERvVA4ZwZpZWtri+zsbJiamsLNzc3Y4RAREREREVEFl5iYiIKCAlhZWSEjI0NvXQ4zIa1MTU0hl8uNHQYRERERERG9ZExMTFBQUKC3DntmkFbKZIaJiQmqVq1qtDiEEIiLi4OHhwdkMpnR4gCAhIQEVKlSxagxKJWXWMpLHED5iKU8Xa9A+Tgn5SkOgLEUxmu2fMcBlJ9Yyksc5emaLS/nBCg/sZSXOIDyEUt5ul6B8nFOylMcQPmJpbzEUR6u2fj4eMjlcpiamhZZlz0zSCsvLy/ExsbC09MT9+7dM1ocqampcHR0REpKChwcHIwWBwDUr18foaGhRo1BqbzEUl7iAMpHLOXpegXKxzkpT3EAjKUwXrPlOw6g/MRSXuIoT9dseTknQPmJpbzEAZSPWMrT9QqUj3NSnuIAyk8s5SWO8nDNFuc+lBOAEhEREREREdEL5bkNM9m9ezdOnz4NU1NTtGvXDt26dYOVldXz2j0RERERERERVRBllswIDAzE+vXrERoaigsXLkifCyEwfPhwbN++Xa1+ixYtsGvXLri7u5dVCERERERERET0EiiTZEZAQAAWLlwIABoTdaxduxZ//vmnRpuLFy+id+/euHz5clmEQEREREREREQviVLPmXH58mUEBAQAUPTCqFu3rlr5999/DwBwd3fH2bNnERUVhXHjxgEArl69ij179pQ2BCIiIiIiIiJ6iZS6Z8bXX38NQNEj48CBA+jWrZtUFhYWhtDQUMhkMkydOhWtWrUCAPz2228IDAzEnTt3sG7dOvTr16+0YdAzkpCQgPr162stmz59OqZPn/6cIzKe8nSs5SWW8hIHUL5iKS/KyzkpL3EAjKW8Ky/npLzEAZSfWMpLHOVJeTon5SWW8hIHUL5iKS/KyzkpL3EA5SeW8hLH87Jy5UqsXLlSa1lCQoLB2yn10qxNmzbF1atXMWzYMGzZskWtbNmyZZg9ezZkMhnu3r0LDw8PqWz27NlYtmwZmjRpgkuXLpUmBHoGuDQrUfHxeqUXDa9ZetHwmqUXCa9XetGUh2v2uS7NGhkZCQBo3LixRtnJkycBAHXr1lVLZCiDBIDo6OjShkBEREREREREL5FSJzOsra0BAHl5eWqf5+Xl4dixY5DJZOjUqZNGu9zcXACAXC4vbQhERERERERE9BIpdTKjdu3aAIDg4GC1z3fv3o2HDx8CAPr06aPRLjw8HABQvXr10oZARERERERERC+RUiczWrZsCSEE9uzZg1OnTgFQ9LZYtmwZAMDKygo9e/ZUaxMeHo6//voLMpkMPj4+pQ2BiIiIiIiIiF4ipU5mvPfeezA3N4dcLserr76K7t27o3Hjxjhx4gRkMhmGDx8uDUW5desW3n//fbRr1w6ZmZkAgAkTJpQ2BCIiIiIiIiJ6iZQ6mVG9enUsXboUgGIejGPHjiEsLAwA4OTkhC+//FKqe+TIEXz33XdITk4GALRo0QIDBw4sbQhERERERERE9BIpdTIDAGbNmoV9+/bhtddeg4uLC9zc3NC/f39cuHABlStX1typiQneeOMN7N27tyx2T0REREREREQvEbOy2lCvXr3Qq1cvvXVee+01XLt2DXXq1IG5uXlZ7ZoqMEtLS/j7+8PS0tLYoRAVidcrvWh4zdKLhtcsvUh4vdKL5kW7ZmVCCGHsIKj88fLyQmxsLDw9PXHv3j1jh0NEREREREQVXHHuQ0s9zKRmzZqoVasWNm7cWKx227dvR82aNbUu20pEREREREREpEuph5lER0dDJpMhLS2tWO2ys7MRHR2N1NTU0oZARERERERERC+RYiUz7ty5g+joaK1lN2/exIkTJwzaTlJSEn7++WcAQE5OTnFCICIiIiIiIqKXXLGSGevWrcPChQvVPpPJZACAZcuWYdmyZcXauUwmQ6NGjYrVhoiIiIiIiIhebsUeZlKW84U6Ojpi6dKlZbY9IiIiIiIiIqr4ipXMGDduHLp06SK9F0KgW7dukMlkmDlzJl5//XWDt2VlZYX69evD3t6+OCEQERERERER0UuuWMkMb29veHt7ay2rU6cOOnfuXCZBEREREREZ2507d5CUlGTsMDS4urqievXqxg6j3ImNjUX37t0BADNmzMCMGTOMFouPjw9iYmIQGBio9mUwEZWdUq9m4u/vDwBo1apVqYMhIiIiIioP7ty5g3r16iEzM9PYoWiwsbFBWFgYExqF5OXlITw8HADKZRKKiMpWmSUziIiIiIgqiqSkJGRmZmLTpk2oV6+escORhIWFYfTo0UhKSmIyg4heaqVOZlDFlpCQgPr162stmz59OqZPn/6cIyIiIiJ6furVq4fmzZsbOwwygI+PT5kuVkBEz8bKlSuxcuVKrWUJCQkGb6dMkhkFBQVYtGgRdu/ejatXryIvL8/gtjKZDPn5+WURBj0DVapUQWhoqLHDICIiIiIiogpA35fiXl5eiI2NNWg7JqUNpKCgAN26dUNAQACCg4ORm5sLIUSxHkREREREZFzHjh2DTCZD7969AQCnTp1Cnz594OLiAgcHB/j5+eG3335DQUGBRtvk5GQsXLgQvXv3RtWqVWFra4sGDRrgww8/xIMHD7TuTyaTwc7OTtpXz549UalSJdjZ2aFjx444duwYACA/Px9fffUVfH19YWVlBR8fH4wbNw7x8fEa2/Tx8YFMJpPalva4AMXEonPnzkXTpk3h4uICGxsb1KlTBwMHDsThw4d5P0NkJKXumbF27VqcPHkSMpkMQgi8+uqraNasGWxsbMoiPiIiIiIies7++OMPjBo1Sq0H9cWLF3Hx4kVcvnwZK1askD4PDw9Hjx49cPfuXbVthIaGIjQ0FGvXrsX+/fvRsmVLrfv666+/MGzYMLVkwqlTp9CjRw8cPXoUS5cuxZ49e6SymJgYbNiwARcvXsSlS5dgbm7+TI4LAG7evImWLVsiNTVV7fNbt27h1q1b+Pvvv/Htt99izpw5BsdARGWj1MmMzZs3S6937tyJAQMGlHaTRGRsd+4AhWcBb9gQsLAAIiOB5GT1Mg8PwN1d8XlkpHqZlRWgnHfl8mVALlcv9/UFbGy079PNDfDyAtLTgYgI9TIzM6BxY8Xr69eBnBz18tq1AQcHID5e8VDl5ATUqAFkZwPahlEpx0aHhwMZGeplPj6AszPw4AFQ6I822NsDdeoABQVASIh6masrwInaiIjoBRATE4MJEyagc+fOWLhwIRo1aoSbN29izpw5OH78OFauXIn33nsPNWrUQE5ODgYNGoS7d+/C3t4e33//PXr06AFzc3OcOHECM2fORGJiIgYOHIhr167B0dFRbV/Z2dkYO3Ys+vfvj4ULF8Lb2xuHDx/GhAkTkJqaildffRV5eXnw9/fHxIkTYWZmhsWLF2PFihW4fv06Dh48iH79+pX5cSlNmTIFqampqFWrFpYtW4Y2bdrA0tISN27cQEBAAHbv3o0PP/wQU6dOhbW1dZn+HIioCKKU3N3dhYmJiXj99ddLuykqRzw9PQUA4enpaexQ6HmLiREC0HzcvasoHzxYs2zxYkXZP/9oltWv/3Tb9vaa5UFBirJp0zTL3n1XUXb6tGaZq+vT7daqpVl+4ICizN9fs2zUKEXZzZvaj1WpTRvNso0bFWUrVmiW9eypKEtJ0b7dmJgy+zEREdGzFRQUJACIIOX/U+XEs4wrMDBQABAARKdOnUReXp5aeVJSkrCxsREAxPbt24UQQqxfv14AEDKZTFy8eFFjm1FRUcLKykoAEN98841amXJfHTt2FHK5XK0sICBAKv/000/VyvLz80Xt2rUFAPH111+rlXl7ewsAIjAwsFTHJYQQBQUFwtbWVgAQp0+f1ji2rKws6djOnTtXZBxEVLTi3IeWumdGeno6AMDPz6+0myKi8sDLS9Hj4P59wERlWh03N8XzV18BH32k3sbDQ/HcqRMQFKReZmX19PWJE9p7ZgDAhx8CEyeqlyn32aiR5nbNVP75+ucf7T0zAGDyZOD//k+9zMlJ8ezlpbldVevXa++ZAQBDhwJt26qX2dsrnm1t1bebl6coq1pV976IiIjKkYCAAJiZqd8quLi4oEGDBrhw4QLS0tIAAPv37wcADBo0CC1atNDYjo+PDyZMmIBVq1Zh7969eO+99zTqzJkzBzKZTO0z1SEp7777rlqZqakpmjVrhlu3bkn3ImV9XACQl5eH9evXAwBat26tsS0rKytUqlQJ9+/fR2ZmZrHiIKLSK3Uyw8fHB6GhoUhMTCyLeIjI2ExMFDf5Xl7ay2vW1N22UqWnQzS0adpUd1n16rqHYdjZ6d9ugwa6y6pW1Z1EsLLSv926dXWXVa6seGhjaqp/u0REROWYTCZDmzZttJYVnhfv1q1bAIAePXro3N6rr76KVatWIbLwUNQn6tWrp3M/7u7ucFJ+CaEnDkMU57gAwNLSEoMHD9b4XC6XIyQkBH/99Rfu379f7DiIqGyUejWTYcOGQQiBwMBAzuRLVBFERABdumjOUUEld/u2onfI7dvGjoSIiKhI7u7usFLtWanH7Sf/t3l7e+usoyy7e/cucnNzNcotLS11ttVXVlzFOS5V4eHhWLRoEV5//XU0bNgQNjY2aN68ORYtWlRmsRFR8ZU6mTFz5kz4+vri2rVrWLBgQRmERERGlZ4OHD+ueKaykZIC7N6teCYiIirnLCwsynR7Jk+GrcrlcrVVRJ634h6XEAIff/wx6tevj08++QS7du1CQUEBXnvtNXz44YfYvXs3PD09n1G0RFSUUg8zcXBwwIEDBzBw4EB88cUXCA0Nhb+/Pxo2bFgW8RERERERUTlVq1YtBAUFISYmRmedqKgoAICnp2eJhocYy59//oklS5bAzMwM3333HcaNG6exGkvh+TeI6Pkp9W+fck3lNm3aIDw8HDt27MCOHTtgZ2eHWrVqoVKlSnrby2QyHDlypLRhEBERERHRc6ZMZvz777+YPHmy1jrKv/Xr1KnzPEMrte3btwMA3nrrLcyaNUujPCMjA/GFl38nouem1MmMH374QZp9WHXOjLS0NFy+fFlnO5lMBiGExszFRERERET0YujTpw/++OMP/PXXXwgODkbzQhNg3759G7/99hsAYOjQocYIscRynqyUpmt4yg8//CDNAcK5A4mev1InMzp16sSEBFFFUr068OuvulcWoeLz9AS+/VbxTEREVIEMHz4cX331FW7cuIEuXbrgxx9/xKuvvgozMzMcO3YMM2fORE5ODnx9fTFp0iRjh1sszZs3x65du7B27Vp07NgRPXr0gEwmQ2hoKFatWoWNGzdKdQ8dOoQ2bdrA2traiBETvVxKncw4duxYGYRBROWGqyvw1lvGjqJiqVIFeDIkj4iIqCKxsrLCzp070aNHD9y7dw8TJkzQqOPq6opNmza9cPNLzJw5E+vWrUNMTAyGDBmiUT5mzBgUFBRgy5Yt+PLLL7F//369PdOJqGy9WP+iENGzl5QE/P038PrrisQGld7jx8C//wKvvgo4ORk7GiIiKoawsDBjh6CmvMUDAL6+vrhy5QqWL1+O//77D1euXEF+fj4aN26MNm3aYNasWXBzczN2mMXm5OSEc+fOYdGiRTh06BCio6Nhb2+P9u3bY+rUqejVqxcSExMRHx+Py5cvo2vXrsYOmeilIhMc4EVaeHl5ITY2Fp6enrh3756xw6HnKTgYaNECCAoCCo17pRLiOSUieuHcuXMH9erVQ2ZmprFD0WBjY4OwsDBU55BQIqpginMfyp4ZRERERESFVK9eHWFhYUhKSjJ2KBpcXV2ZyCCil16pkxk1a9YsVXuZTIbbt2+XNgwiIiIiojJVvXp1Jg2IiMqpUiczoqOjDa6rXI618GdERERERERERIYqdTJj7NixRdZJTU3F7du3cfPmTWRlZUEmk2HixIlo3bp1aXdPRGXNzg7o3FnxTGXD2hpo1kzxTEREREREpfZcJwBNS0vDDz/8gK+//hp5eXnYtm0bBgwY8Lx2T8WgnHjFzMwMderU0Vpn+vTpmD59+nOOjIiIiIiIiF5UK1euxMqVK7WW3bx5E/n5+QZNAGqU1Uz27duH/v37w9bWFkFBQTpvlsl4uJrJS0wuB/LyAHNzwMTE2NEQEREREdFLojj3oUa5U3nttdcwfPhwpKen4/vvvzdGCESky+XLgJWV4pnKxqVLgKWl4pmIiIiIiErNaF+7duzYEQBw4MABY4VARPR8CAHk5iqeiYiIiIio1IyWzLB+MhHe/fv3jRUCEREREREREb2AjJbMOHnyJADA1dXVWCEQERERERER0QvIKMmMHTt2YN26dZDJZKhbt64xQiAiIiIiIiKiF5RZaTcwYcIEg+vm5OQgLCwMISEhEEJAJpNhypQppQ2BiMpSw4bA3buAm5uxI6k46tUDrl0DatY0diRERERERBVCqZMZ69evh0wmK1Yb5WqwQ4cOxRtvvFHaEIioLFlYAF5exo6iYrG2Bho0MHYUREREREQVRqmTGdWrVy9WMsPCwgINGjRA//79MX78+NLunojKWmQk8OGHwFdfsSdBWYmJAT7/HPj0U8Db29jREBERERG98EqdzIiOji6DMIio3EhOBrZvBz76yNiRVBwPHwJr1gDTpjGZQURERERUBoy2mgkRERERERERUUlUmGTGjRs38NZbb6F69eqwtrZGw4YN8c477+Dhw4da6wshsHbtWrRp0wYODg5wcHBAmzZtsHbtWmlOD13+/vtvdOvWDc7OzrC1tUXTpk3x7bffIi8vT2+748ePo3///nBzc4O1tTV8fX3x2WefIT09XW+7kJAQjBgxAlWrVoWlpSVq1qyJ2bNn48GDB3rbRUVFYdKkSahWrRosLS1RrVo1vPXWW4iMjNTbjoiIiIiIiKg8k4mi7tyL6f79+zh48CAuXryI+/fvIyUlBXZ2dnBzc4Ofnx969eoFrzKeXHDXrl0YMWIEMjMzNcoqV66MM2fOoFatWtJnQgiMGTMGmzdv1rq9kSNHYtOmTVrnApk/fz4WL16stV3nzp1x8OBBWFpaapT99NNPmDZtmtZESf369XHy5Ek4OztrlO3evRtDhgxBTk6ORpmHhwdOnjyJmlrmNbhw4QJ69OiBlJQUjTIHBwccPnwYrVq10nocAODl5YXY2Fh4enri3r17OutRBRQcDLRoAQQFAc2bGzuaioHnlIiIiIioSMW6DxVlJCEhQYwcOVKYm5sLExMTnQ8zMzMxYsQIkZCQUCb7vXHjhrC1tRUAxNChQ8WJEydESkqKOHz4sHjllVcEANG6dWtRUFAgtVm5cqUAIAAIf39/ERERISIiIoS/v7/0+YoVKzT2tXfvXql82rRpIiQkRNy5c0csW7ZMmJqaCgDi/fff12h3+fJlYWZmJgCIIUOGiLNnz4r79++LDRs2CHt7ewFADB48WKNdXFycVN61a1cRGBgoHjx4ILZv3y48PT0FANGyZUshl8vV2mVmZorq1asLAKJx48Zi7969IikpSezdu1c0atRIABBeXl4iMzNT53lVbt/T07M4Pw6qCOLjhVi8WPFMZePePSHmzVM8ExHRiyU4WIigIPWH8m+o6GjNMuW/9ampmmVXrjzd7pUrmuWpqYqye/c0y6KjFWWZmULExDy/4y/Cjh07RN26dUXdunXFuXPnpM+Vf1ePHTvWeMGVM8pz4u3trVGmvMcw9KFtG0qhoaFi0qRJon379sLNzU3Y2dmJxo0bi9dff11s2LBB5Ofnl/kxleRRHgUGBhZ5funZKs59aJlcRWFhYcLNzU2YmJgImUym9nB0dNT4zMTERLi7u4uIiIhS73vIkCECgHj99dc1fjFv3rwpLCwsBADpH9ecnBzh4eEhAIgPPvhAY3tz584VAISHh4fIzc1VK2vZsqUAIIYNG6aRQFAmSKytrcWDBw/UygYPHiwAiA4dOoicnBy1sj179ki/0NeuXVMre//99wUAUadOHfH48WO1sqCgIGFpaSkAiL1796qVrVixQgAQrq6uIqbQf3bR0dHC1dVVABArV67UOH4lJjOIiIiIhBAWFkIA6g/l32wTJ2qWzZunKAsM1CxT/bvK01OzPDBQUTZvnmbZxInq2y0nCY1169ZJf8sGKuMXTGZo86yTGQUFBWLq1KnCxMREb1tfX19x5syZMj0mYyQzoqKihL+/v/j+++9LfyBPMJlhfMW5Dy31nBk5OTno168fHjx4ACEEPD098e233+L69etIT09HcnIysrKyEBYWhh9//BFeXl4QQiAhIQH9+vVDbm5uifedmJiI7du3AwCWLl0KU1NTtfLatWtj4sSJaNKkCa5evQoAOHXqFOLi4mBiYoIPP/xQY5sffvghTExMEBcXh9OnT0ufR0ZG4uLFiwCAjz/+WGMIyuTJk+Hs7IysrCzs3btX+jwjIwO7d+8GAMydOxcWFhZq7fr27YumTZsCgHQsgGIozO+//w4AmDFjBipVqqTWrnnz5ujTpw8A4M8//1QrU7YbM2YMqlevrlbm7e2N0aNHa21HBECxmsmuXYpnKhtpacCxY4pnIiJ6sZw9qxgmqPpQDvH99FPNshkzFGXK4YWqj/37n253/37N8hYtFGUzZmiWffqposzcXPGclPR8jp+eq3Xr1kEovnDW+9C2ouTixYuxevVqyOVyDBw4EMeOHUNiYiKSk5MREhKCr776Cm5ubrhx4wZ69+6N2NjYUse7YMECrfGtW7dOqqPrGEorOjoaAQEB+OGHH0q9LXoxlTqZsWbNGkRGRkImk6FPnz6IjIzEu+++i3r16sHGxgYAYGlpibp16+Kdd97BrVu30KtXLwDArVu3sGbNmhLv+8CBAxBCwM/PD3Xq1NFaZ9WqVbh8+TImTpwIQDEJJwC0a9dO6xwVLi4uaNu2rVpd1ddeXl5o1KiRRjtTU1MpuaDa7vz588jJyYGlpSW6d++uNca+fftqtIuOjsbdu3fVyg1pl5ubKyVhimr333//FTlpKb2EIiOBAQMUz1Q2bt4EunZVPBMR0YshLEwxz5GVleJZ9WFtrajj7a1Z5umpKLO31yxT/RuyUSPNcnt7RZmnp2aZcmlv5b7LiXHjxkk3p126dDF2OC+t+Ph4+Pv7A1B8gbpjxw507twZlStXhqOjIxo3bowPPvgA586dg4uLC1JSUrBs2TIjR01UOqVOZuzYsQOAYjLKbdu2wVyZLdbBwsIC27ZtQ9WqVQGo90YortDQUACQkg+GUGYgW7durbOOcmJM1WylajttE4MW1a5hw4awtbUtdjsXFxe1yUt1tVNmNxMTE1FQUKD3GJXt8vLykMSsPhEREZGmrCzg0iXFM1E5d+HCBcjlcpiYmOCTTz7RWc/HxwczZ86U2hC9yEqdzLh+/TpkMhm6du0Ke2U2uQiOjo7o3r07hBC4fv16ifd9//59AECVKlVw+/ZtjB07Fh4eHrCxsUGLFi0wbdo0qY5SQkICAGjtlaHk4uICQJEYeBHa5ebmIjU1Va2dubm5zuSJvb09zMzMNPZJREREROWcTAZYWCiey9C4ceMgk8mwfft2pKamYt68eahVqxYsLS3h4eGBUaNGScO2VUVHR0Mmk+n8sk+X48ePY/DgwXB3d4eVlRXq1q2Lt956Czdu3NBa38fHBzKZDMeOHdNavn79eshkMo3eITKZDHZ2dgAUN++vv/46KleuDGtrazRs2BABAQFIT08vVuzlkfK82dvbF3lP1rt3bwwbNgyvvPLK8wjNIEII/PXXXxg5ciQaNGggXXdDhgzBqVOnNOor7z8BICYmRroGVYffCCFw7NgxDBw4EHXq1IG1tTVcXV3RpEkTzJ07FzExMWUSu/J3Z8GCBVrLdf2OdOnSBTKZDBcvXkR8fDymTZuGatWqwdLSEt7e3nj77bfLLMaKyqy0G3j06BEAxfKixVGvXj0AwOPHj0u87/j4eACK+SyaNGmCjIwMqSw4OBjBwcH4/fffsXXrVvTs2RPA05t9JycnndtVJhCUdZ9Xu+TkZGlISnHaKffj6Oio1k7XfyoymQzOzs5ITExUi1UbIYSUKCkJS0tLrUvVEhEREVEJNGsG5OQ8s80nJSXBz88PERER0mfx8fHYsmUL/vjjD2zZsgVDhgwp8faFEJg/fz6WLFmi9nlERAQiIiKwYcMGbN68GUOHDi3xPrT566+/MGLECLUh1tevX8f169exbds2HD16VOo5/iLy8vICAKSkpODPP//Ue/5atWqFbdu2Pa/QipSfn49x48Zh8+bNap/Hx8dj+/bt2L59O/z9/XUmC3T55ptv8MEHH6h9lp2djYcPH+LKlStYu3Ytzp49q3O6gufl5s2b6Nevn9p92Z07d/Drr79i69at2LdvHzp27GjECIsnJycHOaX4N6o486mUOpnh5OSEBw8eSEM+DKXMHuq7WS+KstfFmjVrYG9vjx9//BH9+vWDk5MTLl68iPfeew9Xr17FmDFjcOPGDTg5OUnJE2WGVhtlmeoQjOfRDgAePnwIDw8Pg9pZWVnBxMQEcrkcSUlJeOWVVwxqpyxPTEwscphJXFwcHB0d9dbRpyT/8JCRWVkht04d3IqMRLaxY6kgrG7exCvu7jArYhgeERGRsc2bNw8pKSmYPXs23nrrLbi5ueG///7DrFmzcOfOHUyYMAHdunWTeggX1969e6VExoQJEzBjxgzUrFkTISEhmD9/Pk6dOoURI0agdu3aaN68eZkcU3Z2NsaOHQt7e3usWLEC3bt3x6NHj/D7778jICAAN27cwHvvvYctW7aUyf6M4bXXXoOLiwsePnyIYcOGYdeuXRg1ahS6du0KKysrY4en15dffiklMiZOnIipU6eiTp06uHbtGhYtWoR9+/YhICAATZo0wcCBAwE87XXRtWtXeHt7a0yIGhUVhXnz5gEARo0ahY8++gg1a9ZEeno6Tpw4gRkzZuD+/fsICAjApk2bnuvxFjZ16lSkpaVh0aJFGDZsGKytrXHkyBHMmjULjx8/xpgxYxAREaGxkER5tWTJEgQEBDyfnZV26ZRu3boJmUwmPD09RUpKikFtUlJShJeXlzAxMRFdu3Yt8b7r1q0rLe1z8uRJjfLU1FTh5uYmAIiPPvpICCGEn59fkcuSLl++XAAQLVu2lD5TLgE7d+5cne12794tLYmqpFzqdciQITrbXb16VTqOtLQ0IcTTpV79/Px0tktLS9NY1nXv3r0CgKhcubLOdkII4eLiIgCIPXv2aC1XLonj4eEhUlJSSvzIzs7WGweVPzExMcLGxqbEy2zxof1hY2OjsVQyERGVY48eCfHHH4rn8iQ0VIhmzRTPZWjs2LHS/1nz58/XKL9//75wdXVV+7taCMXymMp2qrQtzZqXlyfq1asnAIj3339fYx95eXmiS5cuAoB49dVX1cq8vb0FoL78qyrlErGdO3dW+1wZm5mZmbh+/bpGu7Vr1woAQiaTidAyPqeFleXSrNqWIz1y5IhwdnZWq2dpaSm6desmFi1aJM6cOSPy8vKe6TEqqS7Zq09qaqqwt7cXAMTMmTOFXC5XK8/Pzxd9+/YVAETDhg3VyvUto/r7778LQLEMbX5+vkb5hg0bBABRr149tc9LsjSr8nfH399fa7mu35HOnTtLn//6668a7cLCwoS5ubkAIH7++WeD4zG27OzsUt0/enh4CMCwpVlL3TNj0KBBCAwMRHx8PEaMGIG///5b7ySg+fn5GDVqFGJjYyGTyTBo0KAS79vd3R3h4eHo1asXOnTooFFub2+PadOmYcGCBTh37pzUBtA/vEVZpqz7vNrZ2dlJPSqK0061vmo7IYTWoSZCCCQ/WXZTNVZtZDIZHBwc9NahiiUpKQmZmZnYtGmTNByMSicsLAyjR49GUlKSxnLJRERUTjk5AaUYTvHMPOOJSR0cHDB37lyNz6tUqYI5c+bg448/xoYNG7B48eJib/u///5DWFgY7O3ttX5za2Zmhm+++QYtW7ZEYGAg0tPTi+xtbKjRo0drHRb/5ptvYunSpbhx4wY2bdqERYsWlcn+jKFbt24ICwvD//73P/zxxx8ICgpCTk4Ojh49iqNHjwIAKlWqhNGjR2PWrFmoXbu2kSNWXBNpaWmwsrLC/PnzNe5dTE1N4e/vj7179+LatWu4e/euQX9LNWnSBH/++SeqV68OU1NTjfIqVaoAADIzM8vmQEqhVq1aGD9+vMbnvr6+GD9+PH755Rds2LABb7/9thGiK77STjNQnPl3Sp3MeOutt/D9998jKioKBw4cQO3atTF37lz06tUL1atXh6WlJXJycnDnzh0cPHgQ33zzjbTkqI+PDyZNmlTifStvxJs0aaKzToMGDQAA165dA/D0wn348KHONsp5QFTHzZXndubm5tL8Gcp2+fn5SEtL05qISE1NlVY8eZHHBtKzYR0ejhQAsSYmqFdG3TtfdlY3b+IugNSbNxXL6xERUfmXkABs3gyMGgU8+fvqZdCxY0edQ4z79u2Ljz/+GHFxccjMzISNjU2xth0eHg5AsRKhrrZNmzaFtbU1srKycPnyZa1fWJZE3759tX5uamqKPn364MaNG7h9+3aZ7Ks01q1bh3HjxpW4vZubG95//328//77SElJwYkTJ6RkxpUrV5CcnIwVK1Zg/fr12LZtm87z8rzcunULgOLn7ubmprWOn58fHBwckJqaisjISIOSGXXr1kXdunU1Pk9LS8OJEyfw9ddfly7wMtS7d2+tCRdAcd3+8ssv5eLaLI9KvZqJpaUl9uzZAxcXFwghcO/ePcyaNQu+vr6wsbGBs7MzbGxs4Ovri1mzZuHu3bsQQsDV1RV79uwpVdZGmczQl1GTy+UAFFlIAPB8svb32bNndbZR9uLw8PCQPlO2O3funM5JSfS1u3btGtLS0ord7vHjx2oTMOlqp8xgubm5SSuV6DpGZTtTU1NUrlxZax16icnlcHjyTGVDlp8PryfPRET0goiNBd57T/H8EqlRo4ZBZYXnKDDEzZs3AQCHDh2SVnco/DAzM0PWk14npVkooDB9x1WzZk0AikUFKhJHR0f0798f33//PUJCQhAZGYmPPvoIFhYWSE9Px6hRo4pcDOBZU96ke3t7662nLC/OTb1cLse+ffswY8YMdOvWDdWrV4eDgwP69euH48ePlzzoMmbItZmQkKC22AUplDqZASi6wFy9ehXDhg2DiYkJhBDSIzk5We29TCbD4MGDERISUuou7H5+fgCA8+fP60wwBAcHAwAaNWoEAOjcuTMAxY2+tl4PDx8+lG72lcv9AECnTp0AKCbEDAkJ0WhXUFCAgwcParRr1aoVLC0tkZeXhyNHjmiNcf/+/RrtvL29pazjvn37DG5nbm6Odu3aGdSuY8eOeocEEREREdHLRd8kg8ovzADFpJrFlZubW6z6ur4I1EZ1lRJtDDmukhyTqrNnz+KHH37A2rVrtZbrul8pC3v27MGePXv09uquUaMGFi9ejH379kEmkyElJQVbt259ZjGVJRMTxW2rodfQ/fv30apVK/Tt2xcrV67EuXPn4OXlhbFjx+LLL7/EypUrn2W4asri2gRQqhVCKqoySWYAiuENW7duRXR0NH799Ve8/fbbGDBgALp3744BAwZg0qRJ+OWXXxAdHY0//vijTIY39OnTB9bW1jh//jx27NihUR4XF4dVq1YBAHr16gUAaN++PTw8PCCE0FgSCgCWLl0KuVwOT09PKSkAKLJiyuTJokWLNP4x+uWXX/Do0SPY2NigX79+0uc2Njb4v//7P2nbhX8B9+3bh8uXLwOA2jJXMpkMw4YNAwCsWLFCmuNCKTg4WEpKKOspKd9v3LhRY23iO3fuSDP2Fm5HREREROVcjRrAH38onp8BfT0uVHsu1KpVq9jbVs7RMGjQILUvO3U9Ro4cafC2C//NW5i+41J+21/aOSQOHDiAd999F/7+/lrLU1JSABRvTgBDjRkzBv3799f5Zaaq7t27S18qK4d5GIvyOtL38xNCICoqCgAMXkZ1woQJCAoKQoMGDXD06FGkpqbi9OnTWL9+PT788EOt86c8K2VxbTo5OUnTCtBTZZbMUPL09MTEiRPx008/YefOnTh8+DB27tyJn3/+GW+99Za0BnJZcHZ2xuzZswEAI0aMwNKlSxEZGYmkpCTs2LEDbdq0QVpaGvz8/DBhwgQAiszXp59+CgD49ttvsXDhQkRGRiIiIgIBAQFYunQpAOCzzz7T6LWgnKho+/btmDlzJq5fv447d+5gxYoVmDlzJgBg1qxZGktVffLJJzAzM8OZM2cwZswYXLx4Effv38fGjRsxfPhwKf7Cv1Rz5syBg4MDbt++jTfeeAMnTpyQjm3AgAHIyclBu3btpESN0vjx4+Ht7Y1Hjx5hwIABOHjwIB49eoQDBw6gX79+SEpKgo+PT6nG4xERERGRESgnJnVyeiabP3PmjM4eCgcOHAAAVK5cWee8Gvoob0SvXbums5dCXl4eLl68iIsXL0pzvKnSFdvFixf17vvYsWNaP5fL5Th06BCA0iczlDebCQkJWmO/d+8egKKHVJSEMjnx77//FllXCCEN4XnllVfKPJbiUCYzQkJC8ODBA611goKCkJqaCsCwZEZGRob0pe+aNWvQtWtXjTkpnkUSpzTXpq7fB+XvXHmYrLVcKu3SK3fv3tW7xM/Ro0fFlClTxOrVq0VUVFRpd6chJydH9OzZU+eyRY0bNxbh4eFqbeRyuRg1apTONuPGjdNYFkjp448/1tmuR48eIicnR2u7n376SchkMq3tmjRpIpKTk7W22717t7CwsNDarlq1ajqXejx//rxwdHTU2s7JyUkEBwfrPa/KpVkNWRKHKpbgU6dEM0AEnzpl7FAqjEsnTojOgLh04oSxQyEiIkPduiVE//6K5/Lk/n0hvv1W8VyGVJdm/e677zTKExMThZubmwAg3nnnHenz4izNqroM5+bNm7XG8eOPP0p/w6v+Pd6gQQMBQCxcuFCjzYULF6QYdC3NamNjI+7evavR9n//+59U58KFC1pjMtS///4rbWvv3r1qZSkpKdKxT5s2TaOtst26detKtG/leQMgduzYobfu5s2bpbrnz58v0f6KYujSrCkpKcLOzk4AELNmzdIoz8/PF7169RIAROvWrbUuzVq9enW1No8ePZL2re2eJzU1VTRr1kxr25IszTp9+nQBQHTr1k2jLC0tTbi7uxe5NKu2n1lERISwtLQUAMS3335rcDwvuuLch5YomXH37l2xePFi4efnJ0xNTcXDhw911t20aZOQyWTCxMREmJiYiHbt2onDhw+XZLc65efni1WrVonWrVsLBwcH4ezsLK2nnJ2drbWNXC4Xv/32m2jVqpWws7MTdnZ2onXr1mL9+vU6ExlKO3fuFJ07dxaOjo7C2tpaNGnSRPzwww9Frtt87Ngx8dprrwkXFxdhaWkp6tatKxYsWCAyMjL0trt8+bIYOnSocHNzExYWFsLHx0e8++67es+7EEJERkaKCRMmCA8PD2Fubi48PT3FpEmTdCZAVDGZ8fIKCgoSAERQUJCxQ6kweE6JiKjMBAUJASiey5BqMkMmk4nPPvtMhIeHiwcPHoi///5beHt7CwDC1tZW3FdJpBQnmSGEEIsWLRIAhJWVlViwYIEIDw8XWVlZIioqSixcuFCYmpoKAGLDhg1q7caMGSMACDs7O/HPP/+I/Px8kZWVJXbt2iVcXV2lG0ZdyQzl37U7d+4UDx48EDdu3BCff/65MDExEQDEkCFDSn0OMzIyRI0aNQQA4eHhIf755x+RmJgoLl++LHr06CEACDMzMxESEqLRtrTJjOzsbNG4cWNpO0OHDhWHDx8WkZGRIisrS8TGxoqTJ0+Kt99+W5ibmwsAon///kXe95SUockMIYQICAiQ6k6aNEkEBweLlJQUcfr0abUvrU+ePKnWTpl4MDU1FXFxcUIIIR2Pj4+PACA6deokLl++LLKyssS9e/fE1q1bRcOGDaVtmpqaiuDgYJGfn6+2zeIkM9asWSNt74svvhBZWVmioKBAXLp0STRv3lw4OjpKSQlVqskMCwsL8eOPP4ro6GgRFxcnNm7cKJydnQUA4eXlJbKysgyO50X3TJMZy5YtE7a2tsLExERKUhiSzFA+lEmNSZMmFXnzT8bDZMbL68qePWIFIK7s2WPsUCqMK/v3i8WAuLJ/v7FDISIiQ+XmCpGYqHguT55xMmPMmDHS34GFH6ampmLr1q1q7YqbzMjPz1dLnGh7zJ8/XyO+mzdvSt/gK5Mhyptyb29vsX//fr3JjHnz5unc3yuvvCLu3btXJufx6NGjwsbGRut+ZDKZWLp0qdZ2+s6HrsfOnTvVtpGQkCC6dOlSZDsTExMxduzYIr9QLY3iJDPy8vLE8OHD9cYcEBCg0S46Olrt3Nra2kojAXbs2KFzWzY2NmL9+vVq19P3338vhChZMiM7O1s0bdpU7fza2toKAMLa2locOnRIuLi46ExmTJs2TTg4OGiN1dbWVgQGBhocS0VQnPvQYs2ZMX/+fMyePRtZWVnSuJ7mzZvrXV61Z8+eWLVqFYYMGSIt3yqEwJo1a6R5LIio/DBLTsb0J89UNswePsRHT56JiOgFcfUq4OYGbNgABAc/fTyZiBDZ2eqfKx9K4eGaZY8eKcoePNAse7JsKQoKtG9XuSJCfPwzPeyaNWvi0qVLmD59Ory8vGBpaYkmTZpg4sSJCAoKkuZ7KylTU1OsW7cOO3fuxMiRI1G/fn1YW1ujTp06GDx4MM6dO4cvvvhCo13t2rURHByM4cOHw9vbG3K5HFWrVsXMmTMRHBxc5Lx8kydPxrFjx9CrVy84OjrC0dER3bp1w8KFC3Hx4kV4enqW6riUunbtirCwMIwfPx4NGzaEtbU1atWqhQEDBuDMmTOYO3dumexHGzc3Nxw5cgR79uzB2LFj0a5dO3h4eMDS0hK1atVCt27dMHPmTERERGD9+vWwsbF5ZrEUh5mZGbZs2YI//vgDw4cPR7169WBjY4NmzZph7NixOHHiBD777DONdt7e3li1ahWqVasGc3NzODs7S3MeDhw4EMePH0evXr3g4eEBCwsL1K5dG7NmzUJ4eDjGjh2LLVu2wMvLC3Xq1CnVKpuWlpYIDAzE3Llz4evrC3Nzc9jY2GDIkCE4d+4cevToobe9n58fLl++jDfffBNVqlSBlZUV/Pz8MGPGDFy9ehVdunQpcWwVnqEZkkOHDqn1sJg2bZqIjIwsVpYlMzNTfPzxx8LCwkLqpfHHH38Uaxv0fLBnxssrdNMmIQDFM5UJnlMiohdQXJyiB0Thx6hRivKbN7WXK7Vpo1m2caOibMUKzbKePRVlKSnat5uYqCjv318IGxshDBg2XBzK3hL+/v5lul1jw5NvuJ/F3H1EpaHsmVHSoUUVVXHuQ830JTpULViwAIBiKaFNmzZhxIgRxU6cWFtbY9GiRejWrZuUoVq8eLHakqREREREREZXtSoQF6fZE0K5ioiXFxAUpLv9+vVARob6Zz4+iuehQ4G2bdXL7O0Vz7a22rdbqZLi+fvvAXNzoHp1Aw6CiKjiMiiZERMTgzNnzkAmk2HgwIElSmSo6t69OyZPnoyff/4ZV65cQUxMzDNZooiIiIiIqMSqVlU8tLGyApo31922bl3dZZUrKx7amJrq3+6TpSyJiF52Bs2ZcfbsWen1nDlzymTH48eP17p9IjKufGdnfPfkmcpGQaVK+O3JMxEREZVf3bt3h5mZWYkeCxcuNHb4JfIyHjNVDAb1zIhX6V7n6+tbJjuuq5KtTkhIKJNtElHp5VWpgvcABFWpYuxQKozcqlUxCUCQrm/3iIiIqFz47bffkFF4eJCB3Nzcyjia5+NlPGaqGAxKZmRnZwNQzHnhXEbf1jo6OsLW1haZmZkl/uUhorJnkpmJNk+eqWzIsrNR/8kzERERlV81atQwdgjP3ct4zFQxGJTM8PDwAABkZWUhNzcXFhYWpd5xVlYWMjIyIJPJUFnXmEEieu4sY2JwBkBYTAzQoYOxw6kQrKKicB1AWFQU0K6dscMhIiLSsH79eqxfv97YYZQ5IYSxQyDS6tixY8YO4YVn0JwZ1VVmS7548WKZ7PjMmTPS67Ja15mIiIiIiIiIKj6Dkhnt2rWDo6MjAOCnn34qkx3/+uuvAAALCwt04Le/RERERERERGQgg4aZWFhYYPDgwVizZg02b96MIUOGoH///iXe6b59+/D7779DJpOhd+/esFeuq03lTkJCAurXr6+1bPr06Zg+ffpzjoiIiIiIiIheVCtXrsTKlSu1lhVncRCDkhkAEBAQgO3btyM1NRVDhgzBb7/9htGjRxu8I6Xdu3dj+PDhAABTU1Mu51POValSBaGhocYOg54nMzM8ePJMZUQmQ86TZyIiIiKil5m+L8W9vLwQGxtr0HYMGmYCKCYBVWZP8vLyMHbsWLz66qs4fPgw5HJ5ke2DgoIwcuRIvP7668jKyoJMJsPHH3+MRo0aGRoCET0HWXXqwO3JM5WNLF9fWD15JiIiIiKi0ivWV68jR46EXC7H+PHjUVBQgMDAQAQGBsLFxQWtW7dG48aNUblyZdjb2yMnJwfJyckICwvD2bNnERkZCeDpjMKzZ8/GggULyvyAiIiIiIiIiKhiK3Y/8tGjR6NBgwaYMmUKLly4AABISkrCvn37sG/fPp3tlEkMV1dXLF++HMOGDSthyET0LFndvo2bAHJv3waaNzd2OBWCVVQUgp4885wSEREREZWewcNMVDVr1gxnz57FgQMHMHToUNja2kIIoffRtGlTLF++HLdu3WIig6gck+XmovaTZyobsuxsNH/yTEREREREpVfiGf5kMhl69uyJnj17Qi6XIzQ0FFevXsWjR4+QnJwMS0tLODk5oXr16mjVqpW0tCsRERERERERUWmUyXIFJiYmaNiwIRo2bFgWmyMiIiIiIiIi0qlEw0yIiIiIiIiIiIyFyQwiUpNTrRp6PXmmspHr6YkhT56JiIiIiKj0mMwgIjVyOzscevJMZaPAwQHbnzwTEdGL5coVID5e8To9HQgOBrKyFO/v3QOuX39a9/p1IDZW8TorS1E3I0PxPj4euHr1ad3QUODuXcXr7GxF3bQ0xfuEBCAk5Gnd8HAgJkbxOi8PuHOnbI+xNHbu3AlfX1/4+vri/Pnz0ucLFiyATCbDuHHjjBdcOaM8Jz4+PhplMpmsWA9t21AKCwvD22+/jQ4dOqBKlSqwt7dHkyZNMHDgQPzvf/9DQUFBmR9TSR7l0bFjx4o8vyXh4+MDmUyGY8eOlel2X3ZMZhCRGrMHD+D/5JnKhtnDh3j3yTMREb1YevUC1qxRvL56FWjRAoiMVLz/8Udg0KCndQcMAFasULy+eVNRNzRU8f7nn4E+fZ7WHT4c+Pprxet79xR1g4IU7//3P6Br16d1x40DPv9c8TosDPD2Lj8JjZSUFISHhyM8PByZmZnGDuelJpfLMW3aNDRs2BC//vor/vvvPyQmJiI9PR1XrlzB33//jbFjx6Jhw4Y4e/asscMttejoaCxYsAA//PCDsUMhI2Eyg4jUmCclYcGTZyob5omJ+O7JMxERvVgOHgQmTlS8btRIkXCoWVPxftYsYMeOp3X/+QeYMUPxuk4dRd369RXvJ08G9u9/WnfbNmDuXMVrLy9F3RYtFO/ffBMIDHxad/164NNPFa89PIB16wAuFFgxrVu3DkKIIh/R0dEabRcvXozVq1dDLpdj4MCBOHbsGBITE5GcnIyQkBB89dVXcHNzw40bN9C7d2/EKrsRlcKCBQu0xrdu3Tqpjq5jKK3o6GgEBAQwmfESYzKDiIiIiKiQsDCgeXPA3ByoWlXxmZ2d4jNra8V7Ly+gQYOnbRo0AJTTI1lbK+ra2ireV62qSIYo1a8PKKensrJS1LW3V7yvUgVo0uRp3bp1Fb0xAMDVVdFTo7wkM8aNGyfdnHbp0sXY4by04uPj4e/vDwCYO3cuduzYgc6dO6Ny5cpwdHRE48aN8cEHH+DcuXNwcXFBSkoKli1bZuSoiUqHyQwiIiIiokJsbYG2bZ8mI8qLBw+AlSsVz0RKFy5cgFwuh4mJCT755BOd9Xx8fDBz5kypDdGLjMkMIiIiIqJCqldXJA2qVzd2JOru3QPmzFE8l6Vx48ZBJpNh+/btSE1Nxbx581CrVi1YWlrCw8MDo0aNwlXVGUyfiI6OLtGEjsePH8fgwYPh7u4OKysr1K1bF2+99RZu3LihtX5REyiuX78eMplMo3eITCaD3ZNJzS9cuIDXX38dlStXhrW1NRo2bIiAgACkp6cXK/bySHne7O3tYa/s4qND7969MWzYMLzyyivPIzSDCCHw119/YeTIkWjQoIF03Q0ZMgSnTp3SqC+TydD1ycQyMTEx0jWoOvxGCIFjx45h4MCBqFOnDqytreHq6oomTZpg7ty5iFHOqlsG5HI51q9fjw4dOsDR0RF2dnZo3bo11q5dW+SQmuDgYLz99tto1aoVbG1t4erqiu7du+N///sf5HK5Wt0GDRpAJpNhwYIFGttZvHixdB42b96sUa78HVf9HZHJZLCysgKgOI8TJ06Eh4cHrK2t0aBBA8ybNw8pKSnFPyHPiZmxAyCi8qXAwQGbADTlyhtlpsDODrsA1OQKMUREL4ycHMUKJFWrApaWxo7mqWbNFLE9K0lJSfDz80NERIT0WXx8PLZs2YI//vgDW7ZswZAhQ0q8fSEE5s+fjyVLlqh9HhERgYiICGzYsAGbN2/G0KFDS7wPbf766y+MGDECeXl50mfXr1/H9evXsW3bNhw9ehRVleOJXkBeXl4AFBOy/vnnn3rPX6tWrbBt27bnFVqR8vPzMW7cOI0b8Pj4eGzfvh3bt2+Hv7+/1ht4fb755ht88MEHap9lZ2fj4cOHuHLlCtauXYuzZ8+iTp06pYo/Ly8Pw4cPxw7VCXQAnD9/HufPn8epU6d0JjRWrVqFGTNmqJVnZmbi6NGjOHr0KLZt24bt27fDxsYGANCzZ0+Ehobi+PHjGttSTfqcPHkSo0aNUis/ceIEAEUyq7CwsDB06dIFiSrzu4WGhiI0NBSHDx/GmTNnYGFhUdSpeO7YM4OI1OR6emLMk+eoKEDlbxlcvgwo/41LTVUsI5ebq3h/5w6g+mXKlSvA/fuK18ql7LKzFe/v3Xs6uzsAXLsGxMUpXmdmKuoqJ0SPi1OUK4WGPv02SrmUnfILlfv3FftVunHj6WzvubmKuqmpiveJiYrjUYqIAKKiFK/z8xV1Hz9WvE9KUrxXunXr6Uz2crmi7NEjxftHjxTvlaueRUYCt0RtDACQqxwcTURE5d7160CNGupLr74M5s2bh4iICMyePRvXrl1DYmIidu7cierVqyM/Px8TJkzAw1KszrV3714pkTFhwgQEBwcjOTkZx48fR4cOHZCfn48RI0YgWPU/3lLKzs7G2LFjYW9vjy1btiAhIQFhYWHSsqI3btzAe++9V2b7M4bXXnsNLi4uAIBhw4Zh9OjR2L9/P7KVf3yVY19++aWUyJg4cSIuXryIlJQU/Pfff3jttdcAAAEBAdi5c6fURgiBwCez5Hp7e0vztiiXVI2KisK8efMAAKNGjcK1a9eQmZmJxMREbN++He7u7nj06BECAgJKHf+vv/4qJTJGjBiBc+fO4fHjx/j333/RrFkzrFu3Dne0LD904sQJKZHRpk0bHD16FI8fP8aVK1cw98nswPv375eOAwB69eoFADhz5ozaz7agoACnT5+W3p88eVJtX3fv3kXUkz90CyczCgoKMHz4cFhbW+Off/5BUlISoqKiMG3aNACKniNbtmwp8fl5pgSRFp6engKA8PT0NHYo9JydP3Fa+MBJnD9xWowaJUTnzk/LbGyE+PFHxesDB4QAhLh7V/H+7beFaNnyaV1XVyEWL1a8PnlSUffGDcX7d98Von79p3W9vYWYP1/xOihIUTcoSPF+/nxFuVL9+or2Qii2Byi2L4Rif66uT+u2bKmISwhFnIAibiEUx2Fj87Ru585CjBqleP3woaLuX38p3v/6q+K90muvCTFwoOJ1draibONGxfstWxTv09MV7wcPFqJN68fCFRBBZ88KIiJ6MaSkCHH4sOK5PImIEKJ7d8VzWRo7dqwAIACI+cr/lFXcv39fuLq6CgDio48+kj6PioqS2qny9/cXAMTYsWOlz/Ly8kS9evUEAPH+++9r7CMvL0906dJFABCvvvqqWpm3t7cAIAIDA7XGv27dOgFAdFb9w0UIKTYzMzNx/fp1jXZr164VAIRMJhOhoaFat11WlOfEW/UPm0JxGvr4/vvvNbZx5MgR4ezsrFbP0tJSdOvWTSxatEicOXNG5OXlPdNjVFL+PIq63UxNTRX29vYCgJg5c6aQy+Vq5fn5+aJv374CgGjYsKFaeWBgoM7z+fvvvwsAwtfXV+Tn52uUb9iwQQAQ9erVU/tc3za1SU9PF1WqVBEAxPjx4zXiT01Nla75wtev8lr38/MT2dnZGtv+6quvpGs3Pj5eCCFERkaGsLS0FADEsWPHpLohISHStszMzAQAkZSUJJVv2rRJABBVqlQRBQUF0ufKuCpVqiQSEhLU9i+Xy0WbNm0EADFjxgyDzkdZKM59KHtmEJGaO8cfIxqPcOf4Y3z+OfDLL0/L/vsPGD5c8bptW8Uycm5uivfz5wMbNz6te+QIMH684nXTpoq6ypnY58wB/vzzad09e4AnyV/4+irq+voq3k+bpihX+vNPRXtAsb2gIMX2AcX+jhx5WnfjRkVcgCLOoCBF3IDiOP7772ndX34BPv9c8drBQVH3yVBMvP664r3Sjz8C33yjeG1urih78sUBevVSvH8y/BBffQV8NuQEHgCwvnULRET0YnBwAF59VfFcnpiZAZUrK56fBQcHB+lbYVVVqlTBnCf/AW/YsKFE2/7vv/8QFhYGe3t7rd+Im5mZ4Zsn/8EGBgaW6VwWo0ePRn3lOrkq3nzzTfj6+kIIgU2bNpXZ/oyhW7duCAsLw9dffw0/Pz+YmJggJycHR48exfz589G2bVtUrlwZ77zzDm6Vk79J/vvvP6SlpcHKygrz58/XmHvF1NRUWqXl2rVruHv3rkHbbdKkCf78809s2LABpqamGuVVqlQBoBjSURrHjh1DQkICLCwssHDhQo347e3t1XpWKGVmZkrzv3z22Wew1DKWbcaMGXB1dUV+fj4OHToEALCxsUHHjh2lfSsph5j07t0bLZ6s8aw67EQ5xKRXr14wMdFMAcyaNQtuyj/qn5DJZNK+0tLSdJ8EI2Iyg/RKSEhA/fr1tT5Wrlxp7PDoGfB0y8BfGARPtwzUqAGozg3VtOnT5IWDg2IZOeXwuerVnyYgAKBxY8DdXfFauZSd8gbfy0uxJJ1Sw4aAh4fitY2Nou6ToYHw8FCUK9Wvr2gPPF3KTjkVhbu7Yr9Kvr5PJ26zsFDUVf5R6ub2NAkCKI6zRg3FazMzRV0nJ8V7V1fFe6XatYGaNRWvTUwUZc7OivfOzor3yv83a9YEMrPMYIY8hEY5gYiIXgwJCcB33ymey5MaNYCtW5/+n1XWOnbsCEcd67727dsXABAXF1eim8Dw8HAAQNu2baU5AApr2rQprK2tUVBQgMuq40FLSRl7YaampujTpw8A4Pbt22W2v5Jat26dNGRC32P27Nla27u5ueH999/H+fPn8ejRI+zatQuzZ89G4yd/ICUnJ2PFihVo1qwZ9u7d+xyPTDtlUqVp06YaN9NKfn5+cHjyB1ykcpxvEerWrYvBgwejVatWap+npaWpDXUqLWX8TZo0keYtKUzbtad6HN27d9fazsbGBu3atdOo37NnTwDqyYz/nnxD16FDB3Tu3BnA0wQGAGmODW3zZQBA+/btdcbwLKxcuVLnPWZCMf7R5QSgpFeVKlUQqjq5AVV4jra5aIOdCLN9w9ihVBjuLplYielwd+lh7FCIiMhA8fHAggVAt27Aky9xy4WCAiAjQ7FkrJYvnEuthp4siWpZdHS01p4O+ty8eRMAcOjQIYNWP3msnLyqDOg7rppPvqEw9Eb5ReHo6Ij+/fujf//+ABTzSPz666/49ttvkZ6ejlGjRiE8PFzqpWAMygSSt7L7rg7e3t64evUqbt++rbFijS5yuRwHDhzAvn37EBoailu3bhncs8NQymSGvuvL2dkZdnZ2aj2NlMddpUoVWFtb62yrPC+qibZevXrhgw8+wNmzZ5GdnQ0rKyucOnUKJiYmaNOmDfLy8rB06VJp3oyEhASEh4dDJpOhRw/tf4sWdf7L2vTp0zF9+nStZV5eXoiNjTVoO0xmEJGax2mW+A0TUT+tHE3d/oJzdsjBZPyCMIdOxg6FiIgM1LTp00mjy5OQEKBFC8WQRtVeg2VF34oFZipjW0oysWSuctZwAxWna7vqKiXaGHJcpZ0s8+zZszh79iwcHBwwYcIEjXJRxBKdpbHnyZjctm3bShOBFlajRg0sXrwY3bt3R48ePZCSkoKtW7fq7OVRniiHRhh6Dd2/fx/9+vVD0JNxwjY2NmjSpAm6deuGevXqwd7eXufNdHEolzXVRyaTaR3qYghtx92oUSO4u7vj/v37OH/+PGrUqIE7d+6gWbNmcHBwQIcOHWBiYoLg4GCkp6dLSY2WLVvC1dVV637K40olhuAwEyJSE59kg0n4DfFJz6Zb2csoNcMcu9AfqRnmxg6FiIhecDVqAH/88eyGmURHR+ssU+25UKtWrWJvu3bt2gCAQYMGGTSUYuTIkQZvOyYmRm+5vuNSfuutjK+kDhw4gHfffVea46GwlJQUADCoV0pxjRkzBv3798e+ffuKrNu9e3fUq1cPAIw+d4byOtL38xNCSCtxGLqM6oQJExAUFIQGDRrg6NGjSE1NxenTp7F+/Xp8+OGHxe5VpIuyV48yPm0eP34s/eyVlMedkJCArKwsnW21HbdMJlMbaqKcG6NDhw4AFD1ymjZtioKCApw9e7bIISYvMiYziEhNjdfcAciePFNZuGXdAAOwC7esGxg7FCIiMlB4ONChg+K5PHFyAoYMeTqvU1krvOSjqgMHDgAAKleurHNeDX2UN2TXrl3T2UshLy8PFy9exMWLF1GgXOdcha7YLl68qHffqvMLqJLL5dLkiqVNZjg/mUArISFBa+z3nqwt/yy69CuTE//++2+RdYUQ0hCeV1QnRzMC5U19SEgIHjx4oLVOUFAQUp90kzIkmZGRkYH9+/cDANasWYOuXbtq9IwoqySOMpkREhIi/XwLO6I6O32hdgBw9OhRre0yMzNx5swZAJrHrVyiVVsyAwA6dVL0Bj5x4oQ0dwaTGUREVGy1X8kBUPnJMxERvQgsLRUTPmtZZMCoHj4E1q9XPD8L8fHxWL16tcbnDx48wNKlSwEAw5VLmxVT+/btYW9vj4iICGzdulVrndWrV8PPzw8TJ05UW3XB7sls3xcuXNBoc/HiRRw8eFDvvn/66SetN5ubN2/GlStXAABDhw41+Fi0adBA8aVFXl6eRjypqalS0kRZrywpfyb/+9//sHPnTr11t27divj4eACKYSnG1L59e9jZ2SErKwuLFi3SKC8oKMAnn3wCAGjdujWqK2d2V1E4MaY6JEPb8Im0tDSsWrVKa9vi6tKlC6pVq4bc3Fx89tlnGtvLzs7Welw2NjbSRJ0LFy5ETo7m34jff/89Hjx4ADs7O41ExKuvvgpAkXxUJkNUJ/FUbnvXrl24evUqHB0dNSZDrQiYzCAiNQlnHqAt9iDhjPbsOBWfXfwdHEAS7OLvGDsUIiIykI+PImng42PkQAqJiVEsRV7EqIpSee+99+Dv74+IiAgkJSXhn3/+gZ+fHxITE2Fra4v5ynXPi0l1mcqJEyciICAAERERyM7ORnR0ND7//HNp+df33ntPbThG8ycThCxduhS7du1CQUEBsrOzsXv3bvTp0wfu7vp7lGZmZqJNmzb4+++/kZSUhPDwcHzxxRcYN24cAGDIkCFo2bJliY5LqW3bttJEkJMmTcKuXbvw4MEDhISEYPDgwUhLS4OZmRkmT55cqv1oM3nyZGnFkkGDBmHYsGH4999/ERUVhezsbMTFxeHUqVOYPHmydMz9+/cv9TGXlupSwD/++CPefvttXLp0CampqThz5gxee+01KTH0zTffaB2iExsbKyVnhBBwcnKCz5Nf3NmzZyMkJATZ2dmIjY3Ftm3b0K5dO1y6dElqe+nSJa09aQxhaWmJTz/9FIBiJZqRI0fiwoULSElJwcmTJ9GtWzdcvnxZSsapWrBgAQDg/Pnz6NatG44fP46UlBRcu3YN77//vpTEmTdvnsYkrW5ubmjevDmys7Nx48YN1KhRA56enlK5cknVkJAQCCHQo0cPtTlvKgxBpIWnp6cAIDw9PY0dCj1nB7/7WwzEX+Lgd38bO5QK4/D3O8VYrBOHv99p7FCIiMhAublCJCYqnssTuVyIvDzFc1kaO3asACDGjBkj/R1Y+GFqaiq2bt2q1i4qKkoqV+Xv7y8AiLFjx6p9np+fL+1L12P+/Pka8d28eVPY2dlJdaysrIS5ubkAILy9vcX+/fsFANG5c2e1dsr68+bN07m/V155Rdy7d69MzuPRo0eFjY2N1v3IZDKxdOlSre30nQ9dj507d6ptIyEhQXTp0qXIdiYmJmLs2LEiIyOjTI5Zm3Xr1mm9LrTJy8sTw4cP1xtzQECARrvo6Gi1c2trayuioqKEEELs2LFD57ZsbGzE+vXr1a6n77//XgghRGBgoHRNGSovL0+88cYbOvc3ZswYMXLkSAFABAYGqrVdvny53uPu06ePyMzM1Lpf1Wt6zJgxGuUNGzaUyn/77Tet21CWK89bYbp+j5+l4tyHsmcGEamp5paOHXgD1dzSi65MBsnNM8Et1EZuHv/JJSJ6UVy9Cri5AVu2PP0sNBRQruyYnQ0EBwPKBTcSEhQrjSiFhz/tPZGXp6irnAPwwQPgyRfDAICbNwHl/IEFBYq6ylVJHz5UvFf2Xo+MVJQ9gzkkASjG8l+6dAnTp0+Hl5cXLC0t0aRJE0ycOBFBQUElHmKiZGpqinXr1mHnzp0YOXIk6tevD2tra9SpUweDBw/GuXPn8MUXX2i0q127NoKDgzF8+HB4e3tDLpejatWqmDlzJoKDg+Hl5aV3v5MnT8axY8fQq1cvODo6wtHREd26dcPChQtx8eJFtW+1S6Nr164ICwvD+PHj0bBhQ1hbW6NWrVoYMGAAzpw5I/VCeBbc3Nxw5MgR7NmzB2PHjkW7du3g4eEBS0tL1KpVC926dcPMmTMRERGB9evXw8amfEz2bmZmhi1btuCPP/7A8OHDUa9ePdjY2KBZs2YYO3YsTpw4gc8++0yjnbe3N1atWoVq1arB3Nwczs7OMDdXTLY+cOBAHD9+HL169YKHhwcsLCxQu3ZtzJo1C+Hh4Rg7diy2bNkCLy8v1KlTR5pzpKTx//HHH1i/fr00lMra2hpNmzbF6tWrsWHDBp2Tvs6YMQMXLlzAW2+9BT8/P9ja2kq/Cxs2bMDu3bt1Lt2qnDcDUJ8vQ0k51ASANGFoRSMT4hmuEUQvLOX6vp6enjons6GK6frGzaj95gTc+t9aNBgzytjhVAhhmzej3ujRCNu0CfVG8ZwSEb0IkpOBbt2AiAgg/Ul+v3FjoEsXYNky4NYtoE4dIDBQ8dnXXwNLlgCPHinqtm0LNGgA/PYbEB8PeHgAe/YAffsCK1cCc+YAymHyr74KVK4MbN2qWA7W0VGxYsmQIYqhLuPHKxIiZmZAnz6AuTmwcaOiXlkZN24cNmzYAH9/f6n7e0WgvImMioqShh4QUflVnPvQCjhwhohK40aMExoiB9tj9oFrbxAR0cuqUiVg714gKenpZ9u2Afb2itdeXkBQkCKhAQBvvgmofvm5fj1gZaV47eqqqKtczXToUKBdu6d1V69WJCoAwNZWUVe59Gr//or3ysUYVqxQJDPKMpFBRPQiYjKDiNRUbmSPdhiNyo3KfnKql9XV9NpoghRsSg9DyTsxEhHR81a1quKhVL/+09dWVsCTOSkBAFWqKB5Kdes+fW1url63cmXFQ0l11UVTU/W6Li6Kh5IyIUJE9LLjAG4iUmNXzRansRl21WyNHUqF4VTTGnlYAKea2sc8EhERUfnQvXt3mJmZleixcOFCY4dfIi/jMVPFwJ4ZRKQmIyYNPTAcGTFpQPOi61PR3MweYhS+h5tZf2OHQkRERHr89ttvyMjIKFFbNze3Mo7m+XgZj5kqBiYziEhN4vUMHMZWTL6+Dxho7GgqhtxbiRiH7si9lQh0NXY0REREpEsN5WQlL5GX8ZipYuAwEyJSU9c7GemwRV3vZGOHUmHcSbBHD/yLOwn2xg6FiIhIq/Xr10MIUaFWMgEAIQSEEFzJhKgCYjKDiNSYmgjYIhOmJly1uazU9kpBFHxQ2yvF2KEQEREREVUITGYQkZq7iXYYgj9wN9HO2KFUGBbmcvggBhbmcmOHQkRERERUITCZQURq8i1tEAkH5FvaGDuUCiM23RlvYAVi052NHQoRERERUYXAZAYRqXFv44Jg9IZ7G5eiK5NBUly9sQNtkeLqbexQiIiIiIgqBCYziEhdQQHsnzxT2ahRIxtAiyfPRERERERUWlyalfRKSEhA/fr1tZZNnz4d06dPf84R0bMWdfABMpGHqIOH0NzP2NFUDNZhYRAAwsLCgObNjR0OEREREZHRrFy5EitXrtRalpCQYPB2mMwgvapUqYLQ0FBjh0HPkbtLJlZiOtxdehg7lAoj/E4ldEMcVt8JRj1jB0NEREREZET6vhT38vJCbGysQdvhMBMiUuPskIPJ+AXODjnGDqXCcLbPxnSshLM9h5kQEREREZUFJjOISE1qhjl2oT9SM8yNHUqFUdkpG59gESo7MZlBRERERFQWmMwgIjX3Eu0wALtwL9HO2KFUGBnZZjiDNsjI5sg+IiIiIqKywGQGEanx6uoKZ1SGV1dXY4dSYUSY1kM7nEGEKWfMICIiIiIqC0xmEJEac2szPEISzK3Zi6Cs+LxSAKDBk2ciIiIiIiotJjOISM2Di0nohnV4cDHJ2KFUGA4P72EjQuHw8J6xQyEiIiIiqhCYzCAiNQUp2chBbRSkcLLKsvIgKg8hWIoHUXnGDoWIiIiIqEJgMoOI1NTwSMMpdEQNjzRjh1JhpGVZYBf+D2lZFsYOhYiIiIioQmAyg4joGavjlYJw+KKOV4qxQyEiIiIiqhCYzCAiNWExTnBACsJinIwdChERERERkVZMZhCRGqfatmiGBXCqbWvsUCqMsHRvOOMmwtK9jR0KEREREVGFwGQGEalxrG2PE/gejrXtjR1KhWHj7YjH+BM23o7GDoWIiIiIqEJgMoOI1GTFZ6AjuiMrPsPYoVQY7jaP0RMfw93msbFDISIiIiKqEJjMICI19y+l4ST+xf1LXM2krIjbcfgajSBuxxk7FCIiIiKiCoHJDCJSU9srBVHwQW2uvFFmImMd0ARXEBnrYOxQiIiIiIgqBCYziEiNhbkcPoiBhbnc2KFUGD5VU3EefvCpmmrsUIiIiIiIKgQmM4hITVySDaZjBeKSbIwdSoVhY1UAP1yEjVWBsUMhIiIiIqoQmMwgIjWZsMURtEUmuDRrWUnMcMBM+CMxg8NMiIiIiIjKgpmxAyCi8sWzoyvC0QKeHYOMHUqFcd+xFpajGdo7cpgJEREREVFZYDKD9EpISED9+vW1lk2fPh3Tp09/zhERvXjq1MkG0AB16jBBREREREQvt5UrV2LlypVayxISEgzeDpMZpFeVKlUQGhpq7DDoObpz6D7cEYc7hy6heXNjR1MxWN+8iUQASTdvgieViIiIiF5m+r4U9/LyQmxsrEHb4ZwZRKTG2S4L07ESznZZxg6lwrgVY4PuCMGtGE6qSkRERERUFpjMICI1lZ2y8QkWobJTtrFDqTBsrfLRBcdga5Vv7FCIiIiIiCoEJjOISE1GthnOoA0ysjkKraxUdcnEMsxCVZdMY4dCRERERFQhMJlBRGpi4u3RDmcQE29v7FAqjJxcE9xCLeTk8p9cIiIiIqKywL+siUiNR3tn1EQDeLR3NnYoFUaY3Bd1cAthcl9jh0JEREREVCEwmUFEaiwdLRCJUFg6Whg7lArD6xUZgC5PnomIiIiIqLSYzCAiNY+uPkZPLMWjq4+NHUqFUSk9Ht/iOCqlxxs7FCIiIiKiCoHJDCJSk3k/C9H4P2Te59KsZSU5KhMFeB/JUZwAlIiIiIioLDCZQURq6nilIBy+qOOVYuxQKoykZCsswUdISrYydihERERERBUCkxlERM+Yr3cyHsEFvt7Jxg6FiIiIiKhCeKmTGUIIrF27Fm3atIGDgwMcHBzQpk0brF27FkIIvW3//vtvdOvWDc7OzrC1tUXTpk3x7bffIi8vT2+748ePo3///nBzc4O1tTV8fX3x2WefIT09XW+7kJAQjBgxAlWrVoWlpSVq1qyJ2bNn48GDB3rbRUVFYdKkSahWrRosLS1RrVo1vPXWW4iMjNTbjl5eN+85ojZu4uY9R2OHQkREREREpJVMFHXX/gI4cOAA+vTpU2S9tLQ02NnZAVAkMsaMGYPNmzdrrTty5Ehs2rQJMpnm6gPz58/H4sWLtbbr3LkzDh48CEtLS42yn376CdOmTdOaKKlfvz5OnjwJZ2fN5TB3796NIUOGICcnR6PMw8MDJ0+eRM2aNTXKLly4gB49eiAlRXO4gIODAw4fPoxWrVppPQ4vLy/ExsbC09MT9+7d01qHKqZ/NwXiizFn8cnGNnh1dFdjh1Mh7Pr5GGZNscSPP+Xg/yZ3MXY4RERERETlUnHuQytEz4wbN24Uu83q1aulRIa/vz8iIiIQEREBf39/AMCWLVuwatUqjXb79u2TEhnTpk1DSEgI7ty5g2XLlsHU1BTHjx/HJ598otEuJCQE77zzDoQQGDJkCM6ePYv79+9jw4YNsLe3R2hoKCZPnqzRLj4+HqNGjUJOTg66du2KwMBAPHjwANu3b4enpyfi4uIwbNgwjQRJVlYWBg8ejJSUFDRu3Bh79+5FUlIS9u7di0aNGiE1NRVvvPEGsrI4ySOpc67viOP4GM712TOjrJh6uSIa12Hq5WrsUIiIiIiIKgZRAUyZMkUAEJ9++qlB9XNycoSHh4cAID744AON8rlz5woAwsPDQ+Tm5qqVtWzZUgAQw4YNE3K5XK1s5cqVAoCwtrYWDx48UCsbPHiwACA6dOggcnJy1Mr27NkjAAgA4tq1a2pl77//vgAg6tSpIx4/fqxWFhQUJCwtLQUAsXfvXrWyFStWCADC1dVVxMTEqJVFR0cLV1dXAUCsXLlS6zny9PQUAISnp6fWcqq4zhw+JVqgkThz+JSxQ6kwgk+dEs0AEXyK55SIiIiISJfi3IdWqJ4ZDRs2NKj+qVOnEBcXBxMTE3z44Yca5R9++CFMTEwQFxeH06dPS59HRkbi4sWLAICPP/5YYwjK5MmT4ezsjKysLOzdu1f6PCMjA7t37wYAzJ07FxYWFmrt+vbti6ZNmwIAtm/fLn0uhMDvv/8OAJgxYwYqVaqk1q558+bS8Jo///xTrUzZbsyYMahevbpambe3N0aPHq21HVHs2RQE4Qpiz3I1k7JieisGe+EO01sxxg6FiIiIiKhCqBDJjPDwcACGJzOOHz8OAGjXrp3WOSpcXFzQtm1btbqqr728vNCoUSONdqamplJyQbXd+fPnkZOTA0tLS3Tv3l1rTH379tVoFx0djbt376qVG9IuNzdXSsIU1e6///4rctJSern4VE3FefjBp2qqsUOpMG7erQQPxOPm3UrGDoWIiIiIqEJ44ZMZqampiI+Ph7m5OZKSktC/f394eXnByckJXbp0wWeffYbMzEy1NrGxsQCA1q1b69yucmJMZd3C7bRNDFpUu4YNG8LW1rbY7VxcXFCrVq0i24kn82YkJiaioKBA7zEq2+Xl5SEpKUlrHXo52VgVwA8XYWNVYOxQKoxqVdKxB31RrYr+VYuIiIiIiMgwL3wyQ9krIz8/H507d8aePXsQGxuL5ORkHD9+HJ9//jmaNWuGq1evSm0SEhIAQGuvDCUXFxcAisTAi9AuNzcXqampau3Mzc11Jk/s7e1hZmamsU+iB4+tsAD+ePDYytihVBj2Nnnoi32wt2EvKCIiIiKismBm7ABKS5nMEEKgYcOGWLx4Mdq0aYO0tDQcOnQIH3zwASIiIjBq1CgEBwfDzMxMutl3cnLSuV1lAkFZV/X1s2yXnJwsDUkpTjvlfhwdHdXa6epBIpPJ4OzsjMTERLVYCxNCSEmSkrC0tNS6TC2VX4+ybPEz3kLTrGvGDqXCeJRujW8xDW3SrY0dChERERHRM5OTk4OcnJwStxeFVunU54VPZqSmpqJBgwaoXr06Nm3aJN3cV65cGVOmTEGbNm3QokULXL16Fb/88gumTZuGx48fAwDs7Ox0bldZpjoE43m0A4CHDx/Cw8PDoHZWVlYwMTGBXC5HUlISXnnlFYPaKcsTExP1DjOJi4uDo2PJl+j09/fHggULStyenr/q3d1wH9VQvXuQsUOpMGLs6+F99MVm+0i0N3YwRERERETPyJIlSxAQEPBc9vXCJzOmTZuGadOm6Sxv2rQpRo4ciU2bNuHff//FtGnTpJ4OaWlpOtulpChWclC9kX8e7QDAwcHB4HYZGRmQy+Vq+zSkna5YC/Pw8EBYWJje7ejDXhlEgK9vFgAr+PoyQUREREREFddHH32EOXPmlLh9vXr1EBcXZ1DdFz6ZYYh27dph06ZNCA0NBQC4u7sDeNpjQhtlmbLu82pnZ2cn9agoTjvV+qrthBBah5oIIZCcnKwRa2EymUxKrtDL4V5gAnwRgnuBsWje3NjRVAxWkZG4BkAWGQmeVCIiIiKqqEo7zYCuaRK0eeEnADWEt7c3AMXwDQCoUqWK2nttHj16BACoWrWq9Fl5bmdubi4NsVG2y8/P19k7IzU1VVrxRHWfRHbm2eiBY7AzzzZ2KBVGTIwFZuEwYmIsjB0KEREREVGF8EInM/Ly8nDgwAEcOHBA75CK+Ph4AICvry8AwNPTEwBw9uxZnW3OnTsHQDHMQknZ7ty5czonJtHX7tq1azrj1Nfu8ePHiIiIKLKdMovl5uYmrVSi6xiV7UxNTVG5cmWtdejlVNUlE8swC1VdMouuTAYxM5GjMh7AzERu7FCIiIiIiCqEFzqZYWZmhhkzZqBPnz7YsmWLznoXL14EANSvXx8A0LlzZwCKG31tvR4ePnwo3ex37dpV+rxTp04AFJNihoSEaLQrKCjAwYMHNdq1atUKlpaWyMvLw5EjR7TGuH//fo123t7eqF69OgBg3759BrczNzdHu3btDGrXsWNHmJuba61DL6ecXBPcQi3k5L7Q/zyUK15uGdiKkfByyzB2KEREREREFcILfbcik8kwaNAgAMA333yjdQnRmzdvYs2aNQCAMWPGAADat28PDw8PCCGwZMkSjTZLly6FXC6Hp6enlBQAgJo1a8LPzw8AsGjRIo3eGb/88gsePXoEGxsb9OvXT/rcxsYG//d//ydtOzc3V63dvn37cPnyZQDAkCFD1I5v2LBhAIAVK1ZIc1woBQcHS0kJZT0l5fuNGzciJiZGrezOnTvYtGmT1nZEt2MdUQe3cDu25KvYkLoCuQypsEeB3PAxgEREREREpNsLncwAgOnTp8PJyQm3bt1Cjx49cPz4caSmpiImJgbr169H27ZtkZeXhzFjxqBDhw4AAAsLC3z66acAgG+//RYLFy5EZGQkIiIiEBAQgKVLlwIAPvvsM41eC8plZrZv346ZM2fi+vXruHPnDlasWIGZM2cCAGbNmgUXFxe1dp988gnMzMxw5swZjBkzBhcvXsT9+/exceNGDB8+HAAwYsQIqfeI0pw5c+Dg4IDbt2/jjTfewIkTJ5CUlIQdO3ZgwIAByMnJQbt27dCrVy+1duPHj4e3tzcePXqEAQMG4ODBg3j06BEOHDiAfv36ISkpCT4+Phg3blwZ/BSoInH3q4Qm6AJ3v0rGDqXCuJZdF45IxbXsusYOhYiIiIioQpAJXZM/vED27duHQYMGIScnR2t5mzZtsGfPHrUEgxACY8aMwebNm7W2GTduHNauXat1NtX58+dj8eLFWtv16NEDe/bsgYWF5kR/P//8M6ZOnap1vo0mTZrg+PHjWpdJ3bNnD9544w2NHh0AUK1aNZw6dUoajqLqwoUL6NGjh9qyr0pOTk44cuQImjVrpvU4vLy8EBsbC09PT9y7d09rHaqYgoOD0aJFCwQFBaE5V94oE8eOhaBr1y8QGPgJunRpYuxwiIiIiIjKpeLch77wPTMA4LXXXkNERAQmTZqEhg0bwtbWFj4+Phg4cCB+/vlnnDhxQqOnhEwmw8aNG/Hbb7+hVatW0pKorVu3xvr163UmMgDFEJOdO3eic+fOcHR0hLW1NZo0aYIffvgB+/bt05rIAIDJkycjMDAQr732GlxcXGBpaYm6detiwYIFOH36tNZEBgD069cP58+fx9ChQ+Hm5gYLCwv4+Pjg3XffxeXLl7UmMgDAz88Ply5dwoQJE+Dh4QFzc3N4enpi0qRJuHz5ss5EBr3cUsOT0RvvIzU82dihVBjOuQmYh+1wzk0wdihERERERBVCheiZQWWPPTNeXjsX78XE+W2xZtEZDPy4r7HDqRDO/PQnwqfuRd3VfdF2ypCiGxARERERvYReup4ZRFR2fL2T8Qgu8PVONnYoFUZcki3GYz3ikmyNHQoRERERUYXAZAYR0TNWz+cx8mCGej6PjR0KEREREVGFwGQGEamJirNHW5xGVJy9sUOpMGQywAwF0DENDxERERERFROTGUSkxszVDma4DjNXO2OHUmFEp1dBS/yD6PQqxg6FiIiIiKhCYDKDiNS4NqmEU5gE1yaVjB1KhZHr7o6gJ89ERERERFR6TGYQkZr89BzUgTvy03OMHUqFUd09A54YgOruGcYOhYiIiIioQmAyg4jU3D3xGDcRj7snOFllWbG8eQvRMIXlzVvGDoWIiIiIqEJgMoOI1FSrko496ItqVf6fvTuPj7K89///Dlkm+77vRNYgsijgjlapiihVRLHiqbZaTo3W6k+/PW4tnh71dNHaHtJqT3vUI9ZWOGpVUOqCuCCCICiEnSxkT8gesuf+/TGZwJhJDBJy5R5ez8cjj2tmrutzz5vUKvOZ+76vJtNRvMbOgij5q1M7C6JMRwEAAAC8As0MAG7Cgjt0uVYrLLjDdBSvkRzbrGd0k5JjucwEAAAAGAp+pgNgZKuoqFB2drbHuZycHOXk5AxzIpxoNQ0O5eo2TW1wmI7iNSLD2nWTntPOsDmmowAAAABG5ebmKjc31+NcRUXFoI9DMwMDSkhIUF5enukYGEbltSG6W0/or7XvmY7iNeqbA7RC1yitOcB0FAAAAMCogb4UT01NVUlJyaCOw2UmANyMvjRB7QrU6EsTTEfxGvuDJ+lardD+4EmmowAAAABegWYGAJxg48a3SgrvGQEAAAAcL5oZANxUrK/STL2tivVVpqN4jeDiQq1Vo4KLC01HAQAAALwCzQwAbvw6WpSlKvl1tJiO4jVKC3z0tP6q0gIf01EAAAAAr0AzA4Cb1PhmvajvKjWebUSHSmf3KFUpTp3d/CsXAAAAGAr8zRqAm65uHzUoTF3dnEUwVDITG/WO5igzsdF0FAAAAMAr0MwA4GZ3YaQi1KDdhZGmowAAAACARzQzALiJnxKuM7VQ8VPCTUfxGl80jpGvWvVF4xjTUQAAAACvQDMDgJuQlGBt0EqFpASbjuI1YscGqVt3K3ZskOkoAAAAgFegmQHATVN+g76t76kpv8F0FK8Rqyr9QH9QrNjuFgAAABgKNDMAuKnaeVj/1LOq2nnYdBSv0XbgkK7SXLUdOGQ6CgAAAOAVaGYAcDMxs1Yd8tPEzFrTUbzGwYpQzdMqHawINR0FAAAA8Ao0MwC48fGR/NQlH3ZmHTJj0+pUqiSNTaszHQUAAADwCjQzALgpqgjVlfqHijiLYMj4+1lKUrn8/SzTUQAAAACvQDMDgJvu4GCV94wYGsVNMbpc/63iphjTUQAAAACvQDMDgJuEmTHapPlKmMkH76HSGJem1Zqkxrg001EAAAAAr0AzA4Abq71DMfKV1d5hOorXyExvUYDOVmZ6i+koAAAAgFegmQHATcE7h3RInSp4h21Eh0rQ7t1q6xkBAAAAHD+aGQDcJMc26xndpOTYZtNRvMauwkhF65B2FUaajgIAAAB4BT/TATCyVVRUKDs72+NcTk6OcnJyhjkRTrTIsHbdpOe0M2yO6SheIzayVffpMcVGnmk6CgAAAGBUbm6ucnNzPc5VVFQM+jg0MzCghIQE5eXlmY6BYVTfHKAVukZpzQGmo3iN2IhW3avfaGfEctNRAAAAAKMG+lI8NTVVJSUlgzoOl5kAcFNSGaJrtUIllSGmo3iN5hY/va/Zam6hfwwAAAAMBZoZANykXxynUIUr/eI401G8xh7/bF2o97XH3/MlWwAAAACODc0MAG58A3zVpEb5BviajuI1Ro/rlDSmZwQAAABwvGhmAHBTtalas/VXVW2qNh3Fa4RVHdRL2q+wqoOmowAAAABegQu4AbjpbmqVn+LU3XTYdBSvUVnQpQ/1O8UUdJmOAgAAAHgFmhnwHtXVUlGR+2uhodK4cVJ3t7R1a9+aU0+VAgKkAwekujr3ueRkKTHR+fqBA+5zgYGSa8varVudxz/ahAlScLAzT/VXznCIj5dSU6WmJmnPHvc5Pz/ptNOcj3fskNra3OfHjJHCw6WyMufP0aKipNGjpdZWydMONNOnO8fdu6XmZve5zEwpOlqqqtKEli/0jh7SzkR23hgqza1+el8XaE5roekoAAAAgFegmQHv8eqr0q23ur82e7b0/vtSR4d0+ul9aw4edDYWfvpTaeVK97lHH5Xuu0/64ANp/nz3uexsZ7NBks4/X2psdJ/fvNnZPPjlL6U//MF97q67pCeekL78Ujr7bPe52Fipqsr5eP58af9+9/m33pIuuUR6+mnp4Yfd5264QVq+XCou9vxntSzneNNN0oYN7nPPPy8tXiy99JJGP/SQmiV1Rkb2PQa+kTEpDfpCU7QzhQYRAAAAMBRoZsD+qqudjYxzz3U2EY4WGuoc/f37zknOsyQkZ9Phvvvc55KTneP55/etDQw88viDDzyfmSE5myQ/+IHn95w8ue9x/Y76v+Q//uH5zAxJWrJEuvJK97moKOeYmur5z+ry7LOez8yQpGuv1f/VjdY1D16kF+oPaHL/RwEAAAAAY2hmwP6KipxnZLjOhvBk1Kj+5yQpK6v/ucjIgWunTu1/Lj3d+eNJaOjAx500qf+5pCTnjyeBgQMfd/z4/ufi4hR5Zqqku5WQsKT/dTgmeU2jNUsH9UxTkSaaDgMAAAB4AXYzAeAmKqpT0h96RgyF0MxQNerPCs0MNR0FAAAA8Ao0MwC4aWwcJWluz4ihkBhYqyv0sBIDa01HAQAAALwCn1YAuCkudkha1TNiKHTuK9NDOkOd+8q+fjEAAACAr0UzA/YXGurctSSUU/iHwpgxLZKSekYMhYKycM3UJhWUhZuOAgAAAHgFmhmwv3HjnNuvjhtnOolX8PeXpPKeEUMhK6VB23SaslIaTEcBAAAAvALNDNhfd7dzC9Ovbo+Kb6SsLEDSf/eMGAqBAV06TV8qMKDLdBQAAADAK9DMgP1t3ercjnTrVtNJvEJbm4+kST0jhkJ5U4Ru0aMqb4owHQUAAADwCjQzALjJzGyTdHbPiKFQHZ2lv2ihqqOzTEcBAAAAvALNDAA4wU45pVXS2J4RAAAAwPGimQHAzZ49QZIO9YwYCkG7d6u+ZwQAAABw/PxMB8DIVlFRoezsbI9zOTk5ysnJGeZEONFiYjokPaaYmBtNR/Eae4vC9B3t0q+L9mqi6TAAAACAQbm5ucrNzfU4V1FRMejj0MzAgBISEpSXl2c6xsBOPVU6eFCKjzedxCvExHRK+o1iYq43HcVrhAW160q9prCgU0xHAQAAAIwa6Evx1NRUlZSUDOo4XGYC+wsIkFJTnSOOW3PzKEmze0YMhcSYFv1a/0+JMS2mowAAAABegU8rsL8DB6SFC50jjltRkUPS+z0jhkJru692KFut7b6mowAAAABegWYG7K+uTlq50jniuGVltUoa0zNiKOy0JuhU7dBOa4LpKAAAAIBXoJkBwI3DYUna3zNiKKSPk6SzekYAAAAAx4tmBgA35eX+kn7XM2IoRNSXaJk2KKJ+cDczAgAAADAwmhkA3Bw+7Cvpgp4RQ6E2v1W1ekC1+Vy6AwAAAAwFmhmwv+Rk6dFHnSOOm/NeGVO4Z8YQqmkMVK5yVNMYaDoKAAAA4BVoZsD+EhOl++5zjsAIND69TmVK1vj0OtNRAAAAAK9AMwP2V1cnvfYau5kMkb17AyUd7BkBAAAAYOShmQH7O3BAmj/fOeK4RUZ2Svpzz4ihsKcpTanarD1NaaajAAAAAF6BZgYAN3FxnZIe7hkxFPxSo1SiT+SXGmU6CgAAAOAV/EwHAIbKzp071WI6hBf4/PM9ks5QSwu9zqGSElGvM3W7UiI+NB0FAAAA8Ao0M2B7ZWVlSpJ0w+LF+tx0GK8wTdIW1dWVmQ7iNXz2HdSLylD9voPSuabTAAAAAPZHMwO2V9vSohpJD//yl0q5+GLTcWyvtdVHjY1lOv/8JNNRvMa+4ghdowKtLF6tKabDAAAAAF6AZgZsrzUrS6dL2nzxxZo+fbrpOEAf6QmNelsXKyLhVtNRAAAAAK/ARfEA3JSUSPfd5xwxNEKDO3Wx3lVoMDdVBQAAAIYCzQzYXtDu3arvGXH86uqkFSucI4ZGdVOI/l13qbopxHQUAAAAwCtwmQnsr7tb4ZJKurtNJ/EKkyZJ+/aZTuFdisPH6+f6lsaGc7oLAAAAMBQ4MwMATrDx41skRfSMAAAAAI4XZ2ZgQBUVFcrOzvY4l5OTo5ycnGFOhBNtxw7p6qull192nqWB4xe4f7/2Smrfv1/iJrUAAAA4ieXm5io3N9fjXEVFxaCPQzMDA0pISFBeXp7pGBhGERHSlVc6RwyNggKHHtWHur+gRp5bgwAAAMDJYaAvxVNTU1UyyJ0IuMwEtteamanpPSOOX2qq9OtfO0cMjQD/bo3RPgX4c18XAAAAYCjQzIDtWUFB+rxnxPFraXFeatLC7R2GTEpcs57VzUqJazYdBQAAAPAKNDNge/5lZVrWM+L47dwpnXqqc8TQ6Oj0UZVi1dHpYzoKAAAA4BVoZsD2/OrqlNMz4viNGyetX+8cMTR2dExQvKq0o2OC6SgAAACAV6CZAcBNaKh01lnOEUMjeayvpCt7RgAAAADHi2YGADdlZdJ//IdzxNCIai3Xz/W6olrLTUcBAAAAvALNDABuqqqk3FzniKHReKBRSfqhGg80mo4CAAAAeAWaGbC9zuhoPdEz4viddprzrIzTTjOdxHuUHwpWjnJVfijYdBQAAADAK9DMgO11JCTo/+sZgZEoe3StOuWv7NG1pqMAAAAAXuGkbmasW7dOV1xxheLj4xUUFKQJEyboZz/7mZqamgas27Ztm66//nolJSXJ4XAoKytLP/nJT1T1Nefl5+fn69Zbb1VaWpocDofS0tJ0yy236MCBAwPWVVVV6a677lJWVpYcDoeSkpK0aNEibd26dcC65uZm/fznP9fEiRMVFBSk+Ph4zZs3T+vWrRuwzm5GHT6sM3tGHL+dO6Xp09maFQAAAMDI5bXNjKefflo+Pj7613/9V4/zTz31lC688EK98cYbqqqqUmtrq3bv3q1f/OIXmjVrlmpqajzWvf7665o1a5b+9re/qby8XO3t7crPz9fvfvc7TZ06td/GxKZNmzRt2jT9+c9/VnFxsdrb21VcXKy//OUvmjZtmjZu3OixLj8/X9OmTdOTTz6p/Px8tbe3q7y8XH//+981a9Ysvfbaax7ramtrNWvWLP37v/+7du3apdbWVlVVVWnVqlW68MIL9cc//nEQv0V7cBQW6pOeEccvJMS5m0lIiOkk3uNAU5JO01s60JRkOgoAAADgFbyymbFnzx7dfffd/c5v27ZNd9xxhyzL0sKFC7VhwwaVl5frueeeU1hYmPLy8rRkyZI+dWVlZbrhhhvU1tamCy+8UGvXrlVVVZVWrlyplJQUlZaW6rrrrpNlWW51LS0tuuaaa1RfX6/TTjtNq1atUnV1tVatWqXJkyeroaFBCxYsUEtLi1udZVlatGiRSkpKlJqaqpUrV6qqqkrvvfeeLrjgArW3t2vx4sUqLS3tk3XJkiXasWOHwsLC9Nxzz6m8vFyffPKJrrnmGlmWpTvuuONrz+zAySk93XkD0PR000m8R1dSvL5Ug7qS4k1HAQAAALyC1zUzOjo6dMMNN+jwAJcc/Md//Ic6Ozt17rnnavny5Zo1a5YSEhL0L//yL3rxxRclSStXrtSOHTvc6p544gk1NjZq7Nixevnll3XBBRcoNjZWCxYs0GuvvSaHw6HPPvtMb775plvd//zP/6ioqEixsbF6/fXXNXfuXMXExGju3Ll6/fXXFRsbq+LiYj3zzDNudatXr9bGjRvlcDj0j3/8QwsWLFBsbKwuvPBCvfLKKxo7dqwaGxv15JNPutVt375dK1askCT97W9/07/8y78oISFBZ555pl544QWdc8456urq0qOPPvpNf83wYm1tUkGBc8TQSItr1Cm6Vmlx7GYCAAAADAWva2Y8/PDD+uyzz/qdb25u1uuvvy5JuvfeexUQEOA2f/nll2vq1KmSnA0NF8uy9Pe//12SdPvttysyMtKtbvr06brsssskqbeR4OKqu/HGG5X+la+7MzIytHjx4gHr5s6dq+nTp7vNRUZGKicnp7fu6LNBXnrpJUnStGnTNHfuXLe6gIAA3XvvvZKcl8x89WwQYMcOafRo54ih4b8vX9sULP99+aajAAAAAF7Bq5oZH330kR577DElJyfriiuu8Lhm48aNamtrk8Ph0EUXXeRxzeWXXy5JbjfKLCgo0MGDB93mB1PX3t6u9evXD6ru448/VkdHR+/rruN8Xd3R2QZTd9FFFykgIECtra3atGmTxzW24uenqp4Rx2/MGOntt50jhsbuwkiFqlm7CyNNRwEAAAC8gtc0MxoaGnTjjTequ7tbzz77rKKjoz2uKykpkSSdeuqpCunnDoczZ850W3v045iYGJ1yyilfW+c6U6KyslJdXV2SpFmzZg1Y19HRoerqaklSd3d3770w+qsbM2aMoqKi+s3aX11oaKgmTZrUp86uWsaOVXzPiOMXHi5dfLFzxNBIjmvWX3W9kuOaTUcBAAAAvILXNDPuuOMOFRQU6M4779ScOXP6XVdRUSFJ/TY7JGfDQnI2Ir5JXXt7uxoaGtzq/P39+22ehIWFya/nrALXe9bW1qqzs/OEZz26DpCkigrpiSecI4ZGZGi7rtffFBnabjoKAAAA4BW8opnx0ksv6X//93+VnZ2txx57bMC1rg/6rjMaPHE1Aerq6tTWcxfEY6k7ev3RdT4+Ph7rfHx8emu/WjfY93StP3z4sJqamo65rj+WZamhoeEb/7QNw10kA/fv1zqlqfSDI42ZL76Qysudj5uapC1bpNZW5/PiYikv70j99u2Sa0OYw4eda133jy0tdc675OU56yXn8bZscR5fcr7fF18cWbtrl1RU5Hzc3u5c29PjUmWldPRmMnv2SPk9t1Po7HSura11Pq+udj532bdPcu0A3N3tnHPtJFxT43zeczKQDhyQ9u49Urtli1RV5XxcV+d87rqyqaBA2r1bKiuTli51jhgadU0BWq4bVNcU8PWLAQAAAJtqa2s7rs+PX90ZdCC2b2YUFxdryZIl8vf31/LlyxUUFDTg+tqeT4ihoaH9rjl67tChQ4OuCwwM1KhRzl+p63KRwdQdPf/VulGjRikwMPCY677uPb9a15/S0lJFRER845+vay4NhdbGLr2gB3Tf72f0vnbRRZJrc5itW6XTT5cKC53Pn3hCWrjwSP28edIf/uB8vGuXc+2uXc7nf/iDc95l4UJnveQ83umnH2lKPPOM831dbrxReuQR5+PKSufaTz5xPv/b36Rzzjmy9oc/lB56yPm4ocG5du1a5/NXX3U+d7nzTumee5yPOzqcc6tXO5+vWeN87mrc/PSn0u23H6mdOVN6+WXn4w8+cK6tq3M+X7pU+sEPpKlTnRl67oOLIXAg9FTdqOU6EHqq6SgAAADACfPYY48d1+dH160WBsPWd0zs7u7W9773PdXV1ek///M/NW3atK+tcZ2t0NjY/xaJ9fX1vY/De24cMJi65uZmdXd3S5IiIiIGXXf0e361rru7Wy0tLQoODj6muq97z6/W9Sc5OVk7d+4ccM1AHA7HN64drCBHl/5DD2rjj5IlOW/8+u67Uny8c37qVGnzZikjw/n87rulW245Uv/GG5LrpJoJE5xrJ0xwPr/tNmnRoiNrV6w4ci+JjAzn2nHjnM9vvlk6+p6rzz8vuf5ni493rnXdVHPRIun884+s/dOfJH9/5+PwcOfa0aOdz7/zHenozWx+9zupp2cmf3/n2sxM5/NLLnE+d/W/fvnLI2dpSNLGjVJamvPx+ec717o25lm6lO1YT5Tx41skOTR+/CemowAAAAAnzH333ae77777G9dPnDhx0A0NWzczfvvb3+q9997Teeedp3tcX1V/jcTEREnuZzB81dFnU7jOYDiWuqPXH11nWZbHS00sy1Jdz9fjX61z1fbXzHC9p2t9cHCwwsLC1NjYOKisR7+PJz4+Pr0NnZGqvXOU2uRQanxT72unnXZkPjTUvRmQmupef+pRX5YHB7uvTU52/rhkZx95HBjovjYx0fnj4mqISFJAgPva+PgjzRbpSENEcm7KcvTa2Fjnj8vRu4yMGuW+Njr6SGNGkrKy5ObotZGR7s9dDREMvaCiAq1Xu4KKCqQzpn/tegAAAMCOHA7HcX2h3d+tGTyx7WUm+/fv1/3336+wsDD97//+r3x9fQdVl5CQIOnI5SOe1PTcgCApKekb1fn7+/fek8JV19nZ2e+ZEg0NDb07nrjeMyoqSv49X9X3956WZR131qPr7GrfwQilqVj7Dg58lglgSkmhr36t/1NJ4eD+PQUAAABgYLZtZhw8eFDt7e1qbGzU6NGj5ePj4/bz3HPPSZKefvrp3tdeffVVpaSkSJK2b9/eb3Ph008/leS8xMLFVVdbW6s9e/Z8bZ2roxQfH9+7U8mGDRsGrPP19VVcXJwkZ0fK9f791e3du7f3jA5PWfura2xs1I4dO/rU2VXC6RGarkuUcDrNDIxM3d1SmxzquQoNAAAAwHGybTPjm5o5c6YcDoc6Ojr07rvvelzz5ptvSpIuvPDC3tcyMjKUnp4uSVrtutviIOr8/f119tlnD6ruvPPO6z0bQ5Jmz549qLrMzExluG4IMYi69957Tx0dHQoMDNTMmTM9rrGT4IQgbdE/FZww8M1fAVMyEpu0SvOUkdj09YsBAAAAfC3bNjMuuOACWZbV78/3vvc9SdKSJUt6X/vOd76j4OBgXXnllZKkX/3qV2pvb3c77urVq7W1Z3uKhUdteeHj46PrrrtOkrRs2bLeMyJctmzZ0ttccK1zcT1//vnnVejaUqNHUVGRli9fPmDdm2++qc2bN7vN1dXVKTc3t3fd0dcWuXJv27ZNb7zxhltde3u7fvOb30iS5s+f3++9OOykfm+9LtUdqt9b//WLAQAAAAC2Z9tmxvF48MEH5efnp08++UQ33nijPvvsM5WXl+v555/Xop6tK66//nplH323R0l33323wsPDtX//fi1YsEAffPCBqqur9fLLL2v+/Plqa2vT2WefrUsuucSt7uabb1ZGRoZqamo0f/58rVmzRjU1NXrrrbc0b948VVdXKzMzUzfddJNb3WWXXaZZs2apvb1dV111lV599VUdOnRI77//vq6++mrt3btXERERfe4We+qpp/Y2Qm644QYtX75clZWV+vTTT7V48WJ99NFH8vf314MPPjjEv1kzave36AM9ptr9LaajAB5taxonH1na1jTu6xcDAAAA+Fq23s3kmzrttNO0bNky/ehHP9JLL72kl156yW1+ypQp+uMf/9inLjExUS+88IIWLFig9957T++9957bfFpaml588cU+d2ANCgrSihUrNGfOHG3btk2XXnqp23xUVJRefvllBbr20+zh4+OjF198Ueeee64OHjyoq666ym0+MDBQf/vb3xR/9LYYPf74xz9q+/bt2rFjh2688Ua3uVGjRumpp57SqUdv42FjEzNq1axQ7cxYbjoK4FHcmABJtyhuzB2mowAAAABe4aQ8M0NyXn6ydu1azZ07VzExMXI4HBo/fryWLl2q9evXKyLC880k582bp40bN+raa69VfHy8AgIClJmZqbvuuktbt27tva/GV82YMUOff/65vv/97ys5OVn+/v5KSUnRrbfeqq1bt2ratGke60aPHq2tW7fqzjvvVGZmpgICApSQkKBFixZp06ZNfRojLlFRUfr000/10EMPady4cXI4HIqJidG8efP0wQcf6Pvf//43+8UBOGZxqtZt+oviVG06CgAAAOAVfCzLskyHwMiTmpqqkpISpaSkqLi42HScAb35m9f0y3vD9dNfN+iye640HQfoY8OfVqh0yYtKfvp6nfnDhV9fAAAAAJyEjuVz6El7Zga8h09EsDpULJ8I+9/MFN6ppDJEC/SySipDTEcBAAAAvALNDNhe/OnRWq8bFX96tOkogEfj0ut0SNEal15nOgoAAADgFWhmwPa6mtuUqSh1NbeZjgJ45OdrKVq18vPlqj4AAABgKNDMgO0VratVgWpUtK7WdBTAo6KmOH1Lz6uoKc50FAAAAMAr0MyA7aXEN+v/dLVS4ptNRwE8OhyforVK1eH4FNNRAAAAAK9AMwO2FxHSrqv1iiJC2k1HATzKSD2sMF2ojNTDpqMAAAAAXoFmBmyvttGhP+sHqm10mI4CeBS0Z48aekYAAAAAx49mBmyvrDpYt+rPKqtma1aMTDsLoxSiJu0sjDIdBQAAAPAKNDNge6PnJkry6RmBkSc+8rAe032Kj+QyEwAAAGAo0MwAgBMsJqJNP9Z/KSaC7YMBAACAoeBnOgBGtoqKCmVnZ3ucy8nJUU5OzjAn6qvikyqdpTdU8UmVNN10GqCvpsN+WqNvK/ow/8oFAADAyS03N1e5ubke5yoqKgZ9HP5mjQElJCQoLy/PdIwB+ba3KlFd8m3vNB0F8GhPQLYWa42WB3ypGabDAAAAAAYN9KV4amqqSkpKBnUcLjOB7aXFN+llLVBafJPpKIBHYyZ0SkrtGQEAAAAcL5oZsL3ubqlNAeruNp0E8CykvEj/UIlCyotMRwEAAAC8As0M2N6uwigFqk272PYSI1RFQbdW6SlVFNBxAwAAAIYCzQzYXtzkMJ2txYqbHGY6CuBRa7uftmi6Wtu5TREAAAAwFGhmwPZC00K0Xi8oNC3EdBTAo6zkBm3STGUlN5iOAgAAAHgFmhmwvebCRs3RIjUXNpqOAgAAAAAYBjQzYHuVO5r1tl5U5Y5m01EAj3Y0ZSlYldrRlGU6CgAAAOAVaGbA9sZn1KlJIRqfUWc6CuBR+OgQtegJhY/mUigAAABgKNDMgO35jrIUosPyHWWZjgJ4lBBQo2v0n0oIqDEdBQAAAPAKNDNgewcrQ7VQL+lgZajpKIBHHfsrdKfOUcf+CtNRAAAAAK9AMwO21+kI1gGFq9MRbDoK4FFhWZjO00cqLGP7YAAAAGAo0MyA7SWeGaMtulSJZ8aYjgJ4dEpKvXZpvE5JqTcdBQAAAPAKNDNgf11dCusZgZHIEdCt8dojR0C36SgAAACAV6CZAdvLX1Olw+pQ/poq01EAj8qao7RYj6usOcp0FAAAAMAr0MyA7SXGHFaucpQYc9h0FMCjmuhMvaBLVBOdaToKAAAA4BVoZsD2osPbtER/UnR4m+kogEdZWa2STu0ZAQAAABwvmhmwvYZmf72mK9TQ7G86CuBR0K5dau0ZAQAAABw/mhmwveLKUM3XayquDDUdBfBob1G4xitfe4vCTUcBAAAAvALNDNhe6oWxilacUi+MNR0F8CgitF2LtVwRoe2mowAAAABewc90AIxsFRUVys7O9jiXk5OjnJycYU7Ul3+Qn2pULf8g/nHGyBQf1aL/0EPaGbXcdBQAAADAqNzcXOXm5nqcq6ioGPRx+PSHASUkJCgvL890jAFVfVatb+kZVX1WLU03nQboq6XNV1s0TWrzNR0FAAAAMGqgL8VTU1NVUlIyqONwmQlsr6u+VW0ao656dorAyLTLZ6JO1xbt8ploOgoAAADgFWhmwPZGJzfqI52n0cmNpqMAHmWM65Y0vWcEAAAAcLxoZgDACRZRV6r/1ueKqCs1HQUAAADwCjQzYHs7C6MUrnrtLIwyHQXw6FB+mwr0Cx3KbzMdBQAAAPAKNDNge1FjQjRNSxU1JsR0FMCj+qYALddi1TcFmI4CAAAAeAWaGbC9iDFh+kC/VcSYMNNRAI/GptWrQKM1Nq3edBQAAADAK9DMgO21lDXrPF2klrJm01EAAAAAAMOAZgZsr/zzRn2od1T+ObuZYGTa3ZSuBG3X7qZ001EAAAAAr0AzA7Y3JrVe+crUmFRO4cfI5EiPVKXWyJEeaToKAAAA4BVoZsD2Avy7lalCBfh3m44CeJQUWqfZ+v+UFFpnOgoAAADgFWhmwPZKq4OVo2UqrQ42HQXwbF+xntY4aV+x6SQAAACAV6CZAds7rBC9q7N0WGzNipFpf0mEJmi39pdEmI4CAAAAeAWaGbC9lPNitVunK+W8WNNRAI8ykhr1oc5VRhI3qQUAAACGAs0MADjBQgI7da4+Vkhgp+koAAAAgFegmQHbK/pnuRJVqqJ/lpuOAnhU2RSqf9O/qbIp1HQUAAAAwCv4mQ4AHK/o0BblKFfRodNMRwE8Ko8cp1/qbE2LrDYdBQAAAPAKnJkB24uLatWDekRxUa2mowAejR3bIim+ZwQAAABwvGhmwPaaW/30ic5UcysnGmFkCty7Vwd7RgAAAADHj2YGbK+wLExn6xMVloWZjgJ4lF8UrKu0UflFwaajAAAAAF6Br7IxoIqKCmVnZ3ucy8nJUU5OzjAn6iv5nGhlaZKSz/mL6SiAR4EBnZquLQoMiDcdBQAAADAqNzdXubm5HucqKioGfRyaGRhQQkKC8vLyTMcYkCMiQAeUJ0dEgOkogEfJsYf1tP5VO2OXm44CAAAAGDXQl+KpqakqKSkZ1HG4zAS2V/Nlrb6tX6nmy1rTUQCP2jtHqVgpau/kX7kAAADAUOBv1rC9w+UtKtCVOlzOThEYmfI6xitNxcrrGG86CgAAAOAVaGbA9sam1mu3Jmhsar3pKIBHKeNGSbqkZwQAAABwvPibNQCcYFGHy/Wo/qmow+WmowAAAABegWYGbG9vcYTGaK/2FkeYjgJ4VH+gSSG6Q/UHmkxHAQAAALwCzQzYXnBKiFK1QsEpIaajAB5V1gXrPj2myrpg01EAAAAAr0AzA7YXnR2hdbpf0dmcmYGRaWJGrZoVqokZ7LgDAAAADAWaGbC99poWna7Jaq9hNxMAAAAAOBnQzIDtlWyo12Z9oZIN7GaCkWl/c4rGa632N6eYjgIAAAB4BZoZsL3MpAZt1AxlJjWYjgJ4ZCXFao+KZSXFmo4CAAAAeAWaGbC94MAuzdBnCg7sMh0F8Cg1pkHZulGpMTTcAAAAgKFAMwO2V1UbqKX6uapqA01HATzy21egDxUlv30FpqMAAAAAXoFmBmyvpiVET+sW1bSwNStGpj1FkYpRjfYURZqOAgAAAHgFmhmwvfSL4lWuNKVfFG86CuBRSnyz/k9XKyW+2XQUAAAAwCvQzACAEywipF1X6xVFhLSbjgIAAAB4BZoZsL3itRWaoG0qXlthOgrgUW1ToP6oH6i2ifu6AAAAAEOBZgZsL9S/VXP0vkL9W01HATzKD83Wbfqz8kOzTUcBAAAAvALNDNheUsxh/V53KinmsOkogEcTJ7ZI8ukZAQAAABwvP9MBMLJVVFQoO9vzt8k5OTnKyckZ5kR9tbWP0j6dorZ2enMYmQLz87W5Z9T06abjAAAAAMbk5uYqNzfX41xFxeBvHUAzAwNKSEhQXl6e6RgD2l8SoWu0TytLVmuq6TCAB0UFfvovvaE7CjrFhSYAAAA4mQ30pXhqaqpKSkoGdRy+yobtJc6I1BRdoMQZkaajAB6NGiU51KZR/BsXAAAAGBL81Rq2FxQXqG1ap6A4dorAyJQW36SXtUBp8U2mowAAAABegWYGbK9hd50u1T1q2F1nOgrgUXe31KYAdXebTgIAAAB4B5oZsL3a/BZ9qvtUm89OERiZvmwZr0C16cuW8aajAAAAAF6BZgZsb0JGnWoUowkZdaajAB4ljPWXtLhnBAAAAHC8aGYAwAkW01mpu/SCYjorTUcBAAAAvALNDNhefmmYztJ65ZeGmY4CeNR8oE4ztEjNB+pMRwEAAAC8As0M2J5fbKj8tEN+saGmowAelVaF6Lt6UaVVIaajAAAAAF6BZgZsL3ZKpD7SrYqdEmk6CuDR+Iw6NSlE47mvCwAAADAkaGbA9jqb2jRWiepsajMdBfDId5SlEB2W7yjLdBQAAADAK3hFM6Oqqkp33HGHzjzzTEVGRioxMVGzZ8/Wr3/9a7W1DfwB99VXX9W3vvUtRUdHKyQkRFOnTtXjjz+ujo6OAevWrVunK664QvHx8QoKCtKECRP0s5/9TE1NTQPWbdu2Tddff72SkpLkcDiUlZWln/zkJ6qqqhqwLj8/X7feeqvS0tLkcDiUlpamW265RQcOHBiwrqqqSnfddZeysrLkcDiUlJSkRYsWaevWrQPW2cnBD2q1V2U6+EGt6SiARwVN8TpHL6mgKd50FAAAAMAr+FiWZeuvCj/88ENdddVVOnTokMf5sWPH6sMPP1RCQkKfuQceeECPPvqox7rZs2drzZo1cjgcfeaeeuop3XbbbfL0q8vOztaHH36o6OjoPnOvv/66Fi5c6LHBkpycrA8//FBZWVl95jZt2qQ5c+aovr6+z1x4eLjefvttzZw5s89cfn6+zjvvPJWUlPSZCwgI0IoVK3TllVf2mZOk1NRUlZSUKCUlRcXFxR7XjBQb//slVf3wOcX96Xuaeeu1puMAfbz66g5ddVWxXnklVd/5ziTTcQAAAIAR6Vg+h9r6zIyOjg798Ic/1KFDh5Sdna01a9bo0KFDKisr0zPPPKOYmBjt3btXt912W5/a1atX9zYybrvtNm3btk1FRUX6/e9/L19fX61bt04PPvhgn7pt27bpjjvukGVZWrhwoTZs2KDy8nI999xzCgsLU15enpYsWdKnrqysTDfccIPa2tp04YUXau3ataqqqtLKlSuVkpKi0tJSXXfddX0aJC0tLbrmmmtUX1+v0047TatWrVJ1dbVWrVqlyZMnq6GhQQsWLFBLS4tbnWVZWrRokUpKSpSamqqVK1eqqqpK7733ni644AK1t7dr8eLFKi0tPZ7/CUaEsOAOXa7VCgse+GwawJT0pCbF6lKlJw185hYAAACAQbJs7MUXX7QkWQ6HwyouLu4z/9prr1mSLElWeXm529wZZ5xhSbKuu+46q7u7220uNzfXkmQFBQVZVVVVbnPXXHONJck699xzrba2Nre5N954o/f9tm/f7jZ3zz33WJKssWPHWrW1tW5zmzdvthwOhyXJWrVqldvcsmXLLElWbGysVVhY6DZXUFBgxcbGWpKs3Nxcj1kcDoe1efNmt7na2lpr7NixliTr3nvv7fN7syzLSklJsSRZKSkpHudHko/+sMJaptusj/6wwnQUwKO85cstS3KOAAAAADw6ls+htj4zY/v27ZKkyy67TCkpKX3mL7/8cgUHB0uSvvzyy97XDxw4oM8++0ySdP/998vHx8etbsmSJYqOjlZLS4tWrVrV+3pzc7Nef/11SdK9996rgICAPu83depUSdLKlSt7X7csS3//+98lSbfffrsiIyPd6qZPn67LLrtMkrRixQq3OVfdjTfeqPT0dLe5jIwMLV68eMC6uXPnavr06W5zkZGRysnJ6a2z7H2lkcprQ3S3nlB5LdteYmTKy4+SnzqUlx9lOgoAAADgFWzdzNi/f78kKTMz0+P8qFGjFBERIUmqq6vrfX3dunWSnNfjTJ48uU+dr69vb3PBtVaSNm7cqLa2NjkcDl100UUe3/Pyyy/vU1dQUKCDBw+6zQ+mrr29XevXrx9U3ccff+x201LXcb6u7uhsdjX60gS1K1CjL+17XxRgJEiMOaxc5Sgx5rDpKAAAAIBXsHUz48UXX5RlWfrtb3/rcX7//v0qKyuTJE2adOSme64bYs6aNavPWRkurhtqHn3zTNfjU089VSEhns8CGKguJiZGp5xyytfWuc6UqKysVFdXV2/Wgeo6OjpUXV0tSeru7u69F0Z/dWPGjFFUVFSfrACGXnR4m5boT4oOZ/tgAAAAYCjYupnxVZZlqaGhQfn5+Xruuec0d+5cSdKCBQs0ceLE3nUVFRWS5HHHEZeYmBhJzobCcNa1t7eroaHBrc7f37/f5klYWJj8/Pzc3rO2tladnZ3fKKsdVayv0ky9rYr1A29vC5jS0Oyv13SFGpr9TUcBAAAAvIKf6QBD6R//+Ieuuuoqt9duv/12/fKXv3R7zdUkcJ2Z4ImrCeBae6x1dXV1vZekHEud630iIiLc6vo7g8THx0fR0dGqrKzsXX905mP9M36Vq0H0TTkcDo/b2w4lv44WZalFfh1BJ/R9gG9qX9AkLdZrWh60Q57PlQIAAADsr62tTW1t3/xs5GO5n6NXnZnhyQcffKDPP//c7bXa2lpJUmhoaL91rjnXpRvHWidJhw4dGnRdYGCgRo0a5faeg6nzlNVVN2rUKAUGBg66zpPS0lJFRER845/HHntswOxDITW+WS/qu0qNbz7h7wV8E2PGtUmK6xkBAAAA7/TYY48d1+dH1+0SBsOrzsz4zne+o+7ublVVVemLL77Q0qVL9fHHH+vb3/62Pv30U5166qmSjpyt0NjY2O+x6uvrJan3BqLHWidJ4eHhg65rbm5Wd3e323sOps5TVlddd3e3Wlpaend0+bo6T5KTk7Vz584B338gJ/qsDEnq6vZRg8LU1e357BXAtNCyIr2laoWWFUma/rXrAQAAADu67777dPfdd3/j+okTJw66oeFVzQzJedlFfHy8Lr74Yp177rmaPn26du7cqSeffFJ//vOfJUmJiYmSjpzB4IlrzrX2WOtCQ0N7z3w4lrqj1x9dZ1mWx0tNLMvq3anlq3Wu2v6aGZ7+jF/l4+PT25QZqXYXRmqyGrSycLVONR0G8KCsQHpRz2hxgTTp6xYDAAAANnW8txno7/YKnnj1ZSaBgYH67ne/K0naunVr7+sJCc4tPF2XgXhSU1MjSUpKShrWOn9//957WbjqOjs7+z07o6GhoXfHE9d7RkVFyd/ff8D3tCzLY1Y7ip8SrjO1UPFTRnbTBSev9o5R2qcxau/w6n/lAgAAAMPG1n+zTklJUWhoqN55551+17gaAh0dHW51kvTpp5/2e4ORTz/9VJLzMouv1m3fvr3f5sJAdbW1tdqzZ8/X1rm6UfHx8b07lWzYsGHAOl9fX8XFxUlydrNc799f3d69e3vP6Dg6qx2FpARrg1YqJMXzGSiAaaOTG/WRztPo5IEvGQMAAAAwOLZuZiQkJKi5uVl79+7td43rfg+nnXZa72vnn3++JOfNLbdt29anpqurS2vWrJEkXXjhhb2vz5w5Uw6HQx0dHXr33Xc9vt+bb77Zpy4jI0Pp6emSpNWrVw+6zt/fX2efffag6s4777zeszEkafbs2YOqy8zMVEZGhsc1dtGU36Bv63tqyv/mu64AAAAAAOzD1s2MCRMmSJL++Mc/9l5qcbSKigo9++yzkqSzzjqr9/WsrCzNmDFDkvTII4/0OTvjT3/6k2pqahQcHKx58+b1vh4cHKwrr7xSkvSrX/1K7e3tbnWrV6/uvZxl4cKFva/7+PjouuuukyQtW7as94wIly1btvQ2F1zrXFzPn3/+eRUWFrrNFRUVafny5QPWvfnmm9q8ebPbXF1dnXJzc3vXHct1SSNR1c7D+qeeVdXOw6ajAB592TRGAarXl01jTEcBAAAAvIKtmxk//elPNWrUKH355Ze69NJL9cknn6i+vl7l5eV6+eWXdc4556i2tlZTp07VLbfc4lb78MMPS5JWrlypH//4x9qxY4eKioq0bNky/fjHP5Yk3XnnnYqJiXGre/DBB+Xn56dPPvlEN954oz777DOVl5fr+eef16JFiyRJ119/vbKzs93q7r77boWHh2v//v1asGCBPvjgA1VXV+vll1/W/Pnz1dbWprPPPluXXHKJW93NN9+sjIwM1dTUaP78+VqzZo1qamr01ltvad68eaqurlZmZqZuuukmt7rLLrtMs2bNUnt7u6666iq9+uqrOnTokN5//31dffXV2rt3ryIiIo7rTrMjxcTMWnXITxMz+7/BKmBSVFaQOrRUUVlBpqMAAAAA3sGyuX//93+3fHx8LEkefyZNmmTl5eV5rL3//vv7rZszZ47V1tbmse6pp57q9z2nTJli1dXVeax7/fXXrYCAAI91aWlpVmFhoce6jRs3WhERER7roqKirC1btnisO3DggJWcnOyxLjAw0HrzzTf7/b2mpKRYkqyUlJR+14wUecuXW5bkHIERaOt771k3SNbW994zHQUAAAAYsY7lc6itz8yQpIceekiffvqprr76amVnZysoKEjp6em69NJL9eSTT+rzzz/XxIkTPdY+8sgjeuWVVzR79mxFREQoKChIU6ZM0ZNPPqnVq1crICDAY92SJUu0du1azZ07VzExMXI4HBo/fryWLl2q9evXKyIiwmPdvHnztHHjRl177bWKj49XQECAMjMzddddd2nr1q2999X4qhkzZujzzz/X97//fSUnJ8vf318pKSm69dZbtXXrVk2bNs1j3ejRo7V161bdeeedyszMVEBAgBISErRo0SJt2rRJl1566SB+wyNfUUWortQ/VFQRajoK4FH7vkrdpIvUvq/SdBQAAADAK/hYVj/beeCklpqaqpKSEqWkpKi4uNh0nAG9+dTb+vmPWvTwH4N02b/OMR0H6OP//mO1rnlorlb+YrUWPDjXdBwAAABgRDqWz6G2PzMDSJgZo02ar4SZMV+/GDBgTGq98pWpMan1pqMAAAAAXoFmBmzPau9QjHxltXeYjgJ4FODfrUwVKsC/23QUAAAAwCvQzIDtFbxzSIfUqYJ3DpmOAnhU0hStBVqmkqZo01EAAAAAr0AzA7aXHNusZ3STkmObTUcBPKqPzdDLOkv1sRmmowAAAABegWYGbC8yrF036TlFhrWbjgJ4NHp0q6TTe0YAAAAAx4tmBmyvvjlAK3SN6ps9b6ULmBa0c6esnhEAAADA8aOZAdsrqQzRtVqhksoQ01EAj3YXRSpJpdpdFGk6CgAAAOAVaGbA9tIvjlOowpV+cZzpKIBH0WGtylGuosO4zAQAAAAYCjQzYHu+Ab5qUqN8A3xNRwE8iotq1YN6RHFRNDMAAACAoUAzA7ZXtalas/VXVW2qNh0F8Ki51U+f6Ew1t/qZjgIAAAB4Bf5mjQFVVFQoOzvb41xOTo5ycnKGOVFf3U2t8lOcupsOm44CeLTHd6Ju0Cd6wfcLnWE6DAAAAGBQbm6ucnNzPc5VVFQM+jg0MzCghIQE5eXlmY4xoMzERr2j+dqZuNx0FMCjzHFdkiYpcxz/jAIAAODkNtCX4qmpqSopKRnUcbjMBABOsPBDxXpeeQo/VGw6CgAAAOAVaGbA9vIKouRQq/IKokxHATyqyu/QNv1KVfkdpqMAAAAAXoFmBmwvZkKoZuluxUwINR0F8KixJUCv6Uo1tgSYjgIAAAB4BZoZsL3w0aH6UH9Q+GiaGRiZxqbWa7cmaGxqvekoAAAAgFegmQHbO1zSpAs0V4dLmkxHAQAAAAAMA5oZsL2KbU16X6tUsY1mBkamnU0ZitZe7WzKMB0FAAAA8Ao0M2B7Y9PqVKokjU2rMx0F8Cg4I0K1WqHgjAjTUQAAAACvQDMDtufvZylJ5fL3s0xHATxKDK7Vt3W/EoNrTUcBAAAAvALNDNheSXWIbtF/q6Q6xHQUwCNrf6l+rcmy9peajgIAAAB4BZoZsL3WUcHaoElqHRVsOgrg0YGScE3RFzpQEm46CgAAAOAVaGbA9pLPidUOna3kc2JNRwE8ykxq0EbNUGZSg+koAAAAgFegmQEAJ1hwYJdm6DMFB3aZjgIAAAB4BZoZsL3Ct8oUpUMqfKvMdBTAo8rmcP1YP1dlM5eZAAAAAEOBZgZsLzayVffpMcVGtpqOAnhUHnGK/ku3qDziFNNRAAAAAK9AMwO2FxvRqnv1G8VG0MzAyDR2bKuktJ4RAAAAwPGimQHba27x0/uareYWP9NRAI+C9u5VZc8IAAAA4PjRzIDtFZaH6UK9r8LyMNNRAI/2FQbrIm3TvkK2DwYAAACGAs0M2F7KudFK1xilnBttOgrgUUhgpy7Q+woJ7DQdBQAAAPAKNDNgewHhASrSfgWEB5iOAniUFHNYv9edSoo5bDoKAAAA4BW4yQAGVFFRoezsbI9zOTk5ysnJGeZEfdVsPaQ5+p1qth6SpptOA/TV1j5K+3SK2trpHwMAAODklpubq9zcXI9zFRUVgz4OzQwMKCEhQXl5eaZjDKilulXlukAt1YWmowAe7eyeoO9qn/7a/bmmmg4DAAAAGDTQl+KpqakqKSkZ1HH4mhC2NyalQV9oisakNJiOAniUOs5H0gU9IwAAAIDjRTMDAE6wyKYyPa51imwqMx0FAAAA8Ao0M2B7ew5GKlUHtedgpOkogEd1+YfVpXtUl88NQAEAAIChQDMDtheaHqwx+rNC04NNRwE8qq4L1GO6T9V1gaajAAAAAF6BZgZsL2pChNbpYUVNiDAdBfBoQkadahSjCRl1pqMAAAAAXoFmBmyvreqwZukMtVVxCj8AAAAAnAxoZsD2Sjc16FNtUukmdjPByLS3KUWjtV57m1JMRwEAAAC8As0M2F5WSoO26TRlsTUrRijf1FgVaId8U2NNRwEAAAC8As0M2F5gQJdO05cKDOgyHQXwKDmyXtN0q5Ij601HAQAAALwCzQzYXkVNkO7To6qoCTIdBfDId1+hVilRvvsKTUcBAAAAvALNDNheQ0eI/qqFaugIMR0F8GjvwUglq0x7D0aajgIAAAB4BZoZsL3UC+JUpLFKvSDOdBTAo7SEJr2hy5WW0GQ6CgAAAOAVaGYAwAkWFtyhy7VaYcEdpqMAAAAAXoFmBmyv+L0KnaJdKn6vwnQUwKOapiA9rttU08R9XQAAAIChQDMDthcW0KKr9JrCAlpMRwE8KgybqHv0hArDJpqOAgAAAHgFmhmwvcSYFv1a/0+JMTQzMDJNmNAiKbBnBAAAAHC8aGbA9lrbfbVD2Wpt9zUdBfAo8MABbe8ZAQAAABw/mhmwvQMl4TpVO3SgJNx0FMCjwsIA3am3VVgYYDoKAAAA4BX8TAfAyFZRUaHs7GyPczk5OcrJyRnmRH0lzYzUJJ2lpJmPm44CeOQ3qltxqpLfKG4ACgAAgJNbbm6ucnNzPc5VVAx+UweaGRhQQkKC8vLyTMcYUGBsoHZogwJjA01HATxKjW/Wi1qsnfHLTUcBAAAAjBroS/HU1FSVlJQM6jhcZgLbq9tZp0v1gOp21pmOAnjU1e2jBoWpq9vHdBQAAADAK9DMgO01FLVoq3LUUMROERiZtreOV4QatL11vOkoAAAAgFegmQHbG59epzIla3x6nekogEeJY/0kLewZAQAAABwvmhkAcIJFt1fo37RS0e2Dv6ERAAAAgP7RzIDt7S8J13Rt1n62ZsUI1XygXuP1PTUfqDcdBQAAAPAKNDNgewFxwQrVJwqICzYdBfCotDpEN+tZlVaHmI4CAAAAeAWaGbC92ClR+lC3K3ZKlOkogEcTM2vVIT9NzKw1HQUAAADwCjQzYHsd9a3KVoY66ltNRwE88vGR/NQlH3ZmBQAAAIYEzQzYXvHHdcpTgYo/rjMdBfCooClBZ+gfKmhKMB0FAAAA8Ao0M2B76QmNelsXKz2h0XQUwKP2xERt7hkBAAAAHD+aGbC90OBOXax3FRrcaToK4FF6YrNSNF/pic2mowAAAABegWYGbK+6PlBP6C5V1weajgJ45Ni7TwXylWPvPtNRAAAAAK9AMwO2V1UfrKVaqqp6tmbFyLSzIEr+6tTOAnbcAQAAAIYCzQzYXuYlCWpUhDIv4eaKGJmSY5v1jG5SciyXmQAAAABDgWYGAJxgkWHtuknPKTKs3XQUAAAAwCvQzIDtlX1YqWn6UGUfVpqOAnhU3xygFbpG9c0BpqMAAAAAXoFmBmzPYbXqNO2Tw2o1HQXwaH/wJF2rFdofPMl0FAAAAMAr0MyA7aXENetZ3ayUOO5HgJFp3PhWSeE9IwAAAIDjRTMDttfR6aMqxaqj08d0FMCj4OJCrVWjgosLTUcBAAAAvIKf6QAY2SoqKpSdne1xLicnRzk5OcOcqK+9ByM1RVVaeXC1TjMdBvCgtMBH/6O/6vsFPuJCEwAAAJzMcnNzlZub63GuoqJi0MehmYEBJSQkKC8vz3SMAcVPDdcMXan4qf/PdBTAo87uUapSnDq7D5uOAgAAABg10JfiqampKikpGdRxuMwEtheSHKxNel0hycGmowAeZSY26h3NUWZio+koAAAAgFegmQHba9hXr0v0QzXsqzcdBQAAAAAwDGhmwPYO7WnRO8rVoT0tpqMAHn3ROEa+atUXjWNMRwEAAAC8As0M2F726Fp1yl/Zo2tNRwE8ih0bpG7drdixQaajAAAAAF6BZgYAnGCxqtIP9AfFqsp0FAAAAMAr0MyA7RWUh+kSvaWC8jDTUQCP2g4c0lWaq7YDh0xHAQAAALwCzQzYX1iwGtQghbGbCUamgxWhmqdVOlgRajoKAAAA4BVoZsD2Es6I1gZdq4Qzok1HATwam1anUiVpbFqd6SgAAACAV6CZAdvrbu1QkoLV3dphOgrgkb+fpSSVy9/PMh0FAAAA8Ao0M2B7he8dUpmaVfge9yPAyFTcFKPL9d8qbooxHQUAAADwCid9M+PVV1/Vt771LUVHRyskJERTp07V448/ro6Ogb/lX7duna644grFx8crKChIEyZM0M9+9jM1NTUNWLdt2zZdf/31SkpKksPhUFZWln7yk5+oqmrgXQ7y8/N16623Ki0tTQ6HQ2lpabrlllt04MCBAeuqqqp01113KSsrSw6HQ0lJSVq0aJG2bt06YJ2dJMc166+6XslxzaajAB41xqVptSapMS7NdBQAAADAK/hYlmX7854PHTqk3/3ud/roo4+0Z88eNTQ0aNKkSZo1a5buv/9+xcfHe6x74IEH9Oijj3qcmz17ttasWSOHw9Fn7qmnntJtt90mT7+67Oxsffjhh4qO7nv/htdff10LFy5UW1tbn7nk5GR9+OGHysrK6jO3adMmzZkzR/X19X3mwsPD9fbbb2vmzJl95vLz83XeeeeppKSkz1xAQIBWrFihK6+8ss+cJKWmpqqkpEQpKSkqLi72uGak2PnCC5q4eLF2Ll+uiTfcYDoO0MeWzz7TWTNm6JNNmzT9jDNMxwEAAABGpGP5HGr7MzP27t2rqVOn6he/+IXWrl2rkpISNTY2asOGDfrd736n8ePH69VXX+1Tt3r16t5Gxm233aZt27apqKhIv//97+Xr66t169bpwQcf7FO3bds23XHHHbIsSwsXLtSGDRtUXl6u5557TmFhYcrLy9OSJUv61JWVlemGG25QW1ubLrzwQq1du1ZVVVVauXKlUlJSVFpaquuuu65Pg6SlpUXXXHON6uvrddppp2nVqlWqrq7WqlWrNHnyZDU0NGjBggVqaWlxq7MsS4sWLVJJSYlSU1O1cuVKVVVV6b333tMFF1yg9vZ2LV68WKWlpcfx2x8Z6poCtFw3qK4pwHQUwKOg3bvV1jMCAAAAGAKWjXV3d1uzZs2yJFlRUVHWM888Yx08eNA6dOiQtXr1amvKlCmWJCssLMzKz893qz3jjDMsSdZ1111ndXd3u83l5uZakqygoCCrqqrKbe6aa66xJFnnnnuu1dbW5jb3xhtvWJIsSdb27dvd5u655x5LkjV27FirtrbWbW7z5s2Ww+GwJFmrVq1ym1u2bJklyYqNjbUKCwvd5goKCqzY2FhLkpWbm+sxi8PhsDZv3uw2V1tba40dO9aSZN177719f7GWZaWkpFiSrJSUFI/zI8nKX6yyJOcIjEQvP/KGFaVD1suPvGE6CgAAADBiHcvnUFufmbF582Z9+umnkqS///3vuummm5Samqro6Ghddtll+vjjjzV+/Hg1Njbq3//933vrDhw4oM8++0ySdP/998vHx8ftuEuWLFF0dLRaWlq0atWq3tebm5v1+uuvS5LuvfdeBQS4nwlw+eWXa+rUqZKklStX9r5uWZb+/ve/S5Juv/12RUZGutVNnz5dl112mSRpxYoVbnOuuhtvvFHp6elucxkZGVq8ePGAdXPnztX06dPd5iIjI5WTk9NbZ9n8SqOMb8fLXw5lfNvz5USAabGRrbpPjyk2stV0FAAAAMAr2LqZ8eWXX0qSJkyYoIsvvrjPfEhIiO666y5J0saNG3tfX7dunSTn9TiTJ0/uU+fr69vbXHCtdR2jra1NDodDF110kcdMl19+eZ+6goICHTx40G1+MHXt7e1av379oOo+/vhjt5uWuo7zdXVHZ7OrUX6j1KF2jfKz9T/O8GKxEa26V79RbATNDAAAAGAo2PrTn2snj3HjxvU5u8LllFNOkeS8GaaL64aYs2bN6rfOdUPNo2+e6Xp86qmnKiQk5JjrYmJievMMVOc6U6KyslJdXV29WQeq6+joUHV1tSSpu7u7914Y/dWNGTNGUVFRfbLaUeWnVTpP/6fKTwfeEQYwpbnFT+9rtppb/ExHAQAAALyCrf9mfeWVV2rSpEkedwBx2bJliyS5ramoqJAkjzuOuMTExEhyNhSGs669vV0NDQ2KiIjorfP39++3eRIWFiY/Pz91dnaqsrJSSUlJqq2tVWdn56Des7a21i2rLR1uVZgc0mG+9cbItMc/Wzfofb3g/6XYywQAAAA4frZuZsyYMUMzZszod76oqEiPP/64JOnaa6/tfd3VJHCdmeCJqwngWnusdXV1db2XpBxLnet9jm5mREVF9XsGiY+Pj6Kjo1VZWdm7/ujMx/pn/CrLstTQ0NDv/NdxOBwet7cdShmJTVqlxdqZuPyEvg/wTY0e1ylpjEaPW/G1awEAAAC7amtrU1tb2zeuP5b7Odq6mTGQjz76SDfeeKMqKyuVmZmpO+64o3eutrZWkhQaGtpvvWvOdenGsdZJ0qFDh5ScnDyousDAQI0aNUrd3d2qrq7WuHHjBlXnmq+srOzN6qobNWqUAgMDj+nP+FWlpaWKiIgY8P0H8vOf/1xLly79xvWANwirOqiXtF9hVQclTTMdBwAAADghHnvsMT388MPD8l5e18woKCjQAw88oL/+9a+SpOTkZP3zn/9020HEdbZCY2Njv8epr6+XJLcP8sdSJ0nh4eGDrmtublZ3d7fbew6mzlNWV113d7daWloUHBw8qDpPkpOTtXPnzgHffyAn+qwMScrLj1K2LK3MX62JJ/zdgGNXWdClD/U7xRR0mY4CAAAAnDD33Xef7r777m9cP3HixN77P34dr2lmtLe367HHHtOjjz6q9vZ2SdL111+vZcuW9blvRGJioqQjZzB44ppzrT3WutDQ0N4zH46l7uj1R9dZluXxUhPLslRXV+exzlXbXzPD05/xq3x8fHqbMiNVTHaoztUtisn+F9NRAI+aW/30vi7QnNZC01EAAACAE+Z4bzPQ3+0VPLH1biYuW7du1RlnnKGlS5eqvb1dZ599tj788EP99a9/9XgDzISEBEnOy0D6U1NTI0lKSkoa1jp/f//ezK66zs7Ofs/OaGho6N3xxPWeUVFR8vf3H/A9LcvymNWOwjND9ZH+ovDMgS/HAUwZk9KgLzRFY1K++f1nAAAAABxh+2bGF198oQsuuEBffvmlQkJC9Pzzz+ujjz7Sueee229NSkqKJOnTTz/t9wYjn376qSTnZRZfrdu+fXu/zYWB6mpra7Vnz56vrXN1o+Lj4+Xn5zx5ZsOGDQPW+fr6Ki4uTpKzm+V6//7q9u7d23tGx9FZ7ai5qFEX6So1Fw18OQ4AAAAAwDvYupnR2NioSy+9VPX19ZowYYI2btyoxYsXf+2pKeeff74k580tt23b1me+q6tLa9askSRdeOGFva/PnDlTDodDHR0devfddz0e+8033+xTl5GRofT0dEnS6tWrB13n7++vs88+e1B15513Xu/ZGJI0e/bsQdVlZmYqIyPD4xq7qNzerHf1siq3N5uOAniU1zRa4TqovKbRpqMAAAAAXsHWzYwXX3xRZWVlio2N1Ycffqjs7OxB1WVlZfVu6frII4/0OTvjT3/6k2pqahQcHKx58+b1vh4cHKwrr7xSkvSrX/2q994cLqtXr9bWrVslSQsXLux93cfHR9ddd50kadmyZb1nRLhs2bKlt7ngWufiev7888+rsND9evuioiItX758wLo333xTmzdvdpurq6tTbm5u77pjuS5pJBqXXqdDita49DrTUQCPQjND1ag/K5RLoQAAAIAhYetmhmvHku9///uKjY09plrXdjErV67Uj3/8Y+3YsUNFRUVatmyZfvzjH0uS7rzzTsXExLjVPfjgg/Lz89Mnn3yiG2+8UZ999pnKy8v1/PPPa9GiRZKcNx79amPl7rvvVnh4uPbv368FCxbogw8+UHV1tV5++WXNnz9fbW1tOvvss3XJJZe41d18883KyMhQTU2N5s+frzVr1qimpkZvvfWW5s2bp+rqamVmZuqmm25yq7vssss0a9Ystbe366qrrtKrr76qQ4cO6f3339fVV1+tvXv3KiIi4rjuNDtS+Plailat/HwHvycxMJwSA2t1hR5WYmD/NwEGAAAAMHg+Vn83jbCB0aNHq6CgYFBrMzIy+qx94IEH9Oijj3pcP2fOHL3xxhsKCAjoM/f000/rRz/6kcf7bUyZMkXr1q3zuN3pG2+8oQULFvQ5o0OS0tLS9NFHH/VejnK0TZs2ac6cOW7bvrpERUXp3Xff1bRp0/rM5efn69xzz/W4tU1gYKBeeeUVXXrppX3mJCk1NVUlJSVKSUlRcXGxxzUjxdu/fVXP3d2k7z0Rqjl3fcd0HKCPzX/5m7pveVyj/vz/6fQfLDIdBwAAABiRjuVzqK3PzKisrDyu+kceeUSvvPKKZs+erYiICAUFBWnKlCl68skntXr1ao+NDElasmSJ1q5dq7lz5yomJkYOh0Pjx4/X0qVLtX79eo+NDEmaN2+eNm7cqGuvvVbx8fEKCAhQZmam7rrrLm3dutVjI0OSZsyYoc8//1zf//73lZycLH9/f6WkpOjWW2/V1q1bPTYyJGezZ+vWrbrzzjuVmZmpgIAAJSQkaNGiRdq0aVO/jQy7aQ8I0Xalqj0gxHQUwKOCsnDN1CYVlI3sbY4BAAAAu7D1mRk4cex0ZsaWLVt0+umna/PmzZo+fbrpOEAfnz/zN/l+/1F1/c/9mnYzZ2YAAAAAnpw0Z2YAkqTubgX0jMBIFBjQpdP0pQIDukxHAQAAALwCzQzYXsE/K+WnJhX88/guOwJOlPKmCN2iR1Xe5PkSNAAAAADHhmYGbC8+8rAe032KjzxsOgrgUXV0lv6ihaqOzjIdBQAAAPAKNDNgezERbfqx/ksxEW2mowAenXJKq6SxPSMAAACA40UzA7bXdNhPa/RtNR32Mx0F8Cho927V94wAAAAAjh/NDNheUUWYLtUaFVWEmY4CeLS3KEwztEt7i/hnFAAAABgKNDNge2kXxCpRqUq7INZ0FMCjsKB2XanXFBbUbjoKAAAA4BU4Lx+25xfsp3KVyC+Yf5wxMiXGtOjX+n/aHfJn5wtFRVJ1tfui+HgpNVVqapL27HGf8/OTTjvN+XjHDqntK/eHGTNGCg+XysqcP0eLipJGj5ZaW6W8vL7hpk93jrt3S83N7nOZmVJ0tFRVJR086D4XFiaNHSt1dUnbtvU97uTJkr+/tH+/VF/vPpeSIiUkSLW1Un6++1xQkDRxovPx559LluU+P3Gic01zsxQS0vd9AQAAcFLg0x9s79Dnh3SxntKhzw9J002nAfpqCorWDmWru77nzIxf/lL6wx/cF911l/TEE9KXX0pnn+0+FxvrbChI0vz5zgbB0d56S7rkEunpp6WHH3afu+EGaflyqbhYOv30vuFczYKbbpI2bHCfe/55afFi6aWXpNtvd5/79relNWucTQVPx62slOLinH+u1193n3v8cenuu6V33pGuvdZ9bto0acsW5+Mzz5Tav3I2y/btzsbPffdJP/uZlJ7e970BAADg9WhmwPbaa1pVp+lqryk3HQXwaE9LphZrh16I3KrJkvTTn0o/+IH7ovh45zh5srR5s/uc31H/qv7HPzyfmSFJS5ZIV17pPhcV5RxTU/se92jPPuv5zAzJ2XA46yz3ubCe+3+EhHg+bmSkc/ztb6WlS93nUlKc48UX960NCjryeMOGvmdmZGVJO3dKf/mLdNttNDMAAABOUjQzMKCKigplZ2d7nMvJyVFOTs4wJ+orK7lBm3SldiYvNx0F8Cgjo03SWUof90fnC+np/X8IDw09cumHJ5Mm9T+XlOT88SQwcODjjh/f/1xcnPPHE1/fgY97yin9z0VFHWm2eDJtWv9zAAAAsKXc3Fzl5uZ6nKuoqBj0cWhmYEAJCQnK83SdPYBBCw7ulrShZwQAAABOXgN9KZ6amqqSkpJBHYfdTGB7u4siFadK7S6KNB0F8Kiqyk/SAz0jAAAAgONFMwO2Fz46RJP0hMJHs7MBRqa6On9JOT0jjltCgvRv/+YcAQAAcFKimQHbixwXrnX6T0WOCzcdBfBo7NgWSck9I45bSor02GNHbiQKAACAkw7NDNheW0WzztY5aqto/vrFAOyvsVF6/33nCAAAgJMSzQzYXunmRq3XRyrdzAcbjEz5+YGSNveMOG5790oXXugcAQAAcFLibnSwvVNS6rVL49WSstR0FMCjwMAuSZ+ouDhZW7a0mo5je0E7d2qi6RAAAAAwimYGbM8R0K3x2qOdAWx7iZFp8uQIBQf/P/3kJ4dNR/EK0yRtkVRWVqYk02EAAABgBM0M2F75oSD9tx7XFYeC+LYWI1JCQrr++c898vWtVECAZTqO7ZWvXi099JDq6upoZgAAAJykaGbA9hq7QvSaLtEFXcWmowAe7dghnXtuijZvTtH06abT2F/e3r0qlmT58Z8wAACAkxU3AIXtpc6O036dqtTZcaajAB6NGSO9/bZzxPFrHTtWaT0jAAAATk58rQUAJ1h4uHTxxaZTAAAAAN6DMzNge8XvlCtd+Sp+p9x0FMCjigrpiSecI45f4N69OtgzAgAA4OREMwO2FxHcqhu1XBHBbHmJkamsTFq61Dni+Pl0diq1ZwQAAMDJiWYGbC8+qkX/oYcUH9ViOgrg0dSpUkODcwQAAABw/LhnBmyvpc1XWzRNavM1HQUAAAAAMAw4MwO2l18artO1Rfml4aajAB7t3i2dfbZz7OiQtmyR6uqcc1VVzucue/dKBw44H3d1OedqapzPa2qcz7u7nc8PHJD27TtSu2WLVF3tfFxb63zuuhIjP1/as+fI2q1bpcpK5+OGBufa9nbn86IiadeuI2u/+EIq77klTVOTc21rz1VdxcVSXt6Rtdu3S6WlzseHDzvXHj7sfF5a6px3yctz1kvO423Z4jy+5Hy/L744snbXLmcuSWrvHKUipQkAAAAnL5oZsL2ks6I0XtOVdFaU6SiAR0FB0rhxUnS0s4lx+unSBx84515+WZo588ja22+XfvpT5+PWVufaNWucz1evdj7v6HA+v+ce6c47j9Sefrr06qvOx2vXOp83NDifP/SQ9MMfHll7zjnS3/7mfPzJJ861rubGI49IN954ZO1FF0nPPON8vHWrc21hofP5E09ICxceWTtvnvSHPzgf79rlXOtqjPzhD855l4ULnfWS83inn+48vuR8v4suOrL2xhuduSRpZ+d4ZahIBQ62ZgUAADhZcZkJbC8wyqHd+lyBUQ7TUQCP0tOlZcuk0FBnI2LzZikryzl39dXSjBlH1i5bJvn2XDEVGOhcm5npfD53rvO5v7/z+W9+c+QsDck5l57ufHzhhc7n4T0nLP3iF0eaIJL08cdScrLz8VlnOdfGxzufP/DAkbMpJOndd4/MTZ3qXJuR4Xx+993SLbccWfvGG86mjSRNmOBcO2GC8/ltt0mLFh1Zu2LFkXwZGc6148Y5n998s3T55UfWPv+8FBzsfByX6StpsULi7xEAAABOTj6WZVmmQ2DkSU1NVUlJiVJSUlTsOg98hHr3f9/Rr7+3Qfc+d6Yu+peLTccBcIJ9+dZbeuOyyzTvzTc1+dJLTccBAADAEDmWz6GcmYEBVVRUKDs72+NcTk6OcnJyhjlRX82lrdqlxWou3f71iwHYXv2BJoXoDtUfaDIdBQAAAMcoNzdXubm5HucqKioGfRyaGRhQQkKC8o6+u98INDatXgUarZ1py01HATAMKuuCdZ8e0/N160xHAQAAwDEa6Etx15kZg8ENQAEAtjIxo1bNCtXEjFrTUQAAAGAIzQzY3r6ScE3Sdu0rYWtWAAAAADgZ0MyA7QUmhSpWaxSYFGo6CoBhsL85ReO1VvubU0xHAQAAgCE0M2B7MZMi9IH+P8VMijAdBcAwsJJitUfFspJiTUcBAACAITQzYHsdtS2aonHqqG0xHQXAMEiNaVC2blRqTIPpKAAAADCEZgZsr/iTem3TbhV/Um86CoBh4LevQB8qSn77CkxHAQAAgCE0M2B7GUmN+lDnKiOp0XQUAMNgT1GkYlSjPUWRpqMAAADAEJoZsL2QwE6dq48VEthpOgqAYZAS36z/09VKiW82HQUAAACG0MyA7VXVBeox/Zuq6gJNRwEwDCJC2nW1XlFESLvpKAAAADCEZgZsr6Y5RI/rbtU0h5iOAmAY1DYF6o/6gWqbaGACAACcrGhmwPbSL47XIcUr/eJ401EADIP80Gzdpj8rPzTbdBQAAAAYQjMDAGArEye2SPLpGQEAAHAyopkB2yv9oFKTtVGlH1SajgJgGATm52tzzwgAAICTE80M2F6QT4vO0hYF+fAtLXAyKCrw00N6Q0UFfqajAAAAwBCaGbC95NjDelr/quTYw6ajABgGo0ZJDrVpFP8FAwAAOGnxV0HYXnvnKBUrRe2d/OMMnAzS4pv0shYoLb7JdBQAAAAYwqc/2N6+gxFKU7H2HYwwHQXAMOjultoUoO5u00kAAABgCs0M2F7C6RGarkuUcDrNDOBk8GXLeAWqTV+2jDcdBQAAAIZw9zQMqKKiQtnZ2R7ncnJylJOTM8yJ+gpOCNIW/VPBCY+ZjgJgGCSM9Ze0WAlj7zUdBQAAAMcoNzdXubm5HucqKioGfRyaGRhQQkKC8vLyTMcYUP3eel2qO1S/t16abjoNgBMtprNSd+kFxXR+z3QUAAAAHKOBvhRPTU1VSUnJoI7DZSawvdr9LfpAj6l2P1uzAieD5gN1mqFFaj5QZzoKAAAADKGZAdubmFGrZoVqYkat6SgAhkFpVYi+qxdVWhViOgoAAAAMoZkBALCV8Rl1alKIxmfUmY4CAAAAQ2hmwPYKysJ0gdaqoCzMdBQAw8B3lKUQHZbvKMt0FAAAABhCMwO25xMRrA4Vyyci2HQUAMOgoCle5+glFTTFm44CAAAAQ9jNBLYXf3q01muO4k/fbDoKgGHQlpCs9epWW0Ky6SgAAAAwhDMzYHtdzW3KVJS6mttMRwEwDNKTmhSrS5We1GQ6CgAAAAyhmQHbK1pXqwLVqGgdu5kAJ4OgfftU1TMCAADg5EQzA7aXEt+s/9PVSolvNh0FwDDIy4+SnzqUlx9lOgoAAAAMoZkB24sIadfVekURIe2mowAYBokxh5WrHCXGHDYdBQAAAIbQzIDt1TY69Gf9QLWNDtNRAAyD6PA2LdGfFB3OfXIAAABOVjQzYHtl1cG6VX9WWTVbswIng4Zmf72mK9TQ7G86CgAAAAyhmQHbGz03UZJPzwjA2+0LmqT5ek37giaZjgIAAABDaGYAAGxlzLg2SXE9IwAAAE5GNDNgexWfVOksvaGKT6pMRwEwDELLivSWqhVaVmQ6CgAAAAyhmQHb821vVaLa5NveajoKgGFQViC9qGdUVmA6CQAAAEyhmQHbS4tv0staoLT4JtNRAAyD9o5R2qcxau/gP2EAAAAnK/4mCNvr7pbaFKDubtNJAAyH0cmN+kjnaXRyo+koAAAAMIRmBmxvV2GUAtWmXYVRpqMAAAAAAIaBn+kAGNkqKiqUnZ3tcS4nJ0c5OTnDnKivuMlhOluLFTd5iekoAIbBl01jNEX1Wt60UxNNhwEAAMAxyc3NVW5urse5ioqKQR+HZgYGlJCQoLy8PNMxBhSaFqL1ekGhaXebjgJgGERlBalDSxWVdZPpKAAAADhGA30pnpqaqpKSkkEdh8tMYHvNhY2ao0VqLuT6eeBkEO93SDfot4r3O2Q6CgAAAAyhmQHbq9zRrLf1oip3NJuOAmAYtO+r1E26SO37Kk1HAQAAgCE0M2B74zPq1KQQjc+oMx0FwDAoqgjTHL2jooow01EAAABgCM0M2J7vKEshOizfUZbpKACGwZjUeuUrU2NS601HAQAAgCE0M2B7BytDtVAv6WBlqOkoAIZBgH+3MlWoAP9u01EAAABgCM0M2F6nI1gHFK5OR7DpKACGQUlTtBZomUqaok1HAQAAgCE0M2B7iWfGaIsuVeKZMaajABgG9bEZellnqT42w3QUAAAAGEIzA/bX1aWwnhGA9xs9ulXS6T0jAAAATkY0M2B7+WuqdFgdyl9TZToKgGEQtHOnrJ4RAAAAJyeaGbC9xJjDylWOEmMOm44CYBjsLopUkkq1uyjSdBQAAAAYclI3M1599VV961vfUnR0tEJCQjR16lQ9/vjj6ujoGLBu3bp1uuKKKxQfH6+goCBNmDBBP/vZz9TU1DRg3bZt23T99dcrKSlJDodDWVlZ+slPfqKqqoHPKMjPz9ett96qtLQ0ORwOpaWl6ZZbbtGBAwcGrKuqqtJdd92lrKwsORwOJSUladGiRdq6deuAdXYTHd6mJfqTosPbTEcBMAyiw1qVo1xFh3GZCQAAwMnKx7Isy3SIoTZ9+nQdPnxYu3bt6nfNAw88oEcffdTj3OzZs7VmzRo5HI4+c0899ZRuu+02efq1ZWdn68MPP1R0dN877L/++utauHCh2tr6fuBOTk7Whx9+qKysrD5zmzZt0pw5c1RfX99nLjw8XG+//bZmzpzZZy4/P1/nnXeeSkpK+swFBARoxYoVuvLKK/vMuaSmpqqkpEQpKSkqLi7ud91I8OmfXlLFkuVKeHqxZv3wWtNxAJxgO194QRMXL9bO5cs18YYbTMcBAADAEDmWz6Fed2bGtm3b9Pnnnw+4ZvXq1b2NjNtuu03btm1TUVGRfv/738vX11fr1q3Tgw8+6PHYd9xxhyzL0sKFC7VhwwaVl5frueeeU1hYmPLy8rRkyZI+dWVlZbrhhhvU1tamCy+8UGvXrlVVVZVWrlyplJQUlZaW6rrrruvTIGlpadE111yj+vp6nXbaaVq1apWqq6u1atUqTZ48WQ0NDVqwYIFaWlrc6izL0qJFi1RSUqLU1FStXLlSVVVVeu+993TBBReovb1dixcvVmlp6bH+ekek4spQzddrKq4MNR0FwDBobvXTJzpTza1+pqMAAADAFMuLHDhwwJo0aZIlyRo/fny/68444wxLknXddddZ3d3dbnO5ubmWJCsoKMiqqqpym7vmmmssSda5555rtbW1uc298cYbliRLkrV9+3a3uXvuuceSZI0dO9aqra11m9u8ebPlcDgsSdaqVavc5pYtW2ZJsmJjY63CwkK3uYKCAis2NtaSZOXm5nrM4nA4rM2bN7vN1dbWWmPHjrUkWffee2+/v6OUlBRLkpWSktLvmpFiw0efWtGKtTZ89KnpKACGwQvPbLMk5wgAAADvcSyfQ21/Zsb27dt155136lvf+pbGjBmjHTt2DLj+wIED+uyzzyRJ999/v3x8fNzmlyxZoujoaLW0tGjVqlW9rzc3N+v111+XJN17770KCAhwq7v88ss1depUSdLKlSt7X7csS3//+98lSbfffrsiIyPd6qZPn67LLrtMkrRixQq3OVfdjTfeqPT0dLe5jIwMLV68eMC6uXPnavr06W5zkZGRysnJ6a2zvOAqI/8gP9WoWv5BfEsLnAwyx3VJmtQzAgAA4GRk+2bGZ599pt///vdau3aturu7v3b9unXrJDmvxZk8eXKfeV9f397mgmutJG3cuFFtbW1yOBy66KKLPB778ssv71NXUFCggwcPus0Ppq69vV3r168fVN3HH3/sdtNS13G+ru7obHZW9Vm1vqVnVPVZtekoAIZB+KFiPa88hR8a2ffzAQAAwIlj+2bG/Pnz9eWXX/b+/OIXvxhwveuGmLNmzepzVoaL64aaR9880/X41FNPVUhIyDHXxcTE6JRTTvnaOteZEpWVlerq6urNOlBdR0eHqqudH+S7u7t774XRX92YMWMUFRXVJ6tdddW3qk1j1FXPzgbAyaAqv0Pb9CtV5Q+88xQAAAC8l+2bGVFRUTr11FN7f1JTUwdcX1FRIUkedxxxiYmJkeRsKAxnXXt7uxoaGtzq/P39+22ehIWFyc/Pz+09a2tr1dnZ+Y2y2tXo5EZ9pPM0OrnRdBQAw6CxJUCv6Uo1tgR8/WIAAAB4pZPuJgOuJoHrzARPXE0A19pjraurq+u9JOVY6lzvExER4VbX3xkkPj4+io6OVmVlZe/6ozMf65/RE8uyehss34TD4fC4xS0AfFNjU+u1WxO0M3W56SgAAAA4Sltbm9ra2r5x/bHc0/Gka2bU1tZKkkJD+9/G0zXnunTjWOsk6dChQ0pOTh5UXWBgoEaNGqXu7m5VV1dr3Lhxg6pzzVdWVvZmddWNGjVKgYGBx/Rn9KS0tFQREREDrhnIz3/+cy1duvQb1w/GzsIozVK9ni38SBNP6DsBAAAAAPrz2GOP6eGHHx6W9zrpmhmusxUaG/u/JKG+vl6S3D7EH0udJIWHhw+6rrm5uffmpa73HEydp6yuuu7ubrW0tCg4OHhQdf1JTk7Wzp07B1wzkOE4KyNqTIimaamixsw/4e8FwLydTRk6R3v156ZyGpgAAAAjyH333ae77777G9dPnDix9x6QX+eka2YkJiZKOnIGgyeuOdfaY60LDQ3tPfPhWOqOXn90nWVZHi81sSxLdXV1Hutctf01Mzz9GT3x8fHpbcyMVBFjwvSBfquIMYtNRwEwDIIzIlSrFQrOmGc6CgAAAI5yvLcZ6O8WC57Y/gagxyohIUGS8zKQ/tTU1EiSkpKShrXO39+/914WrrrOzs5+z85oaGjo3fHE9Z5RUVHy9/cf8D0ty/KY1a5aypp1ni5SS1mz6SgAhkFicK2+rfuVGNx/kxgAAADe7aRrZqSkpEiSPv30035vLvLpp59Kcl5i8dW67du399tcGKiutrZWe/bs+do6VycqPj6+d6eSDRs2DFjn6+uruLg4Sc5Oluv9+6vbu3dv7xkdR2e1q/LPG/Wh3lH55+xmApwMrP2l+rUmy9o/uFMQAQAA4H1OumbG+eefL8l5Y8tt27b1me/q6tKaNWskSRdeeGHv6zNnzpTD4VBHR4feffddj8d+8803+9RlZGQoPT1dkrR69epB1/n7++vss88eVN15553XezaGJM2ePXtQdZmZmcrIyPC4xk7GpNYrX5kak1r/9YsB2N6BknBN0Rc6UDKyL4EDAADAiXPSNTOysrI0Y8YMSdIjjzzS5+yMP/3pT6qpqVFwcLDmzTtyPXZwcLCuvPJKSdKvfvUrtbe3u9WtXr1aW7dulSQtXLiw93UfHx9dd911kqRly5b1nhHhsmXLlt7mgmudi+v5888/r8LCQre5oqIiLV++fMC6N998U5s3b3abq6urU25ubu+6Y7kmaaQK8O9WpgoV4N9tOgqAYZCZ1KCNmqHMpG++bTQAAADs7aRrZkjq3Spm5cqV+vGPf6wdO3aoqKhIy5Yt049//GNJ0p133qmYmBi3ugcffFB+fn765JNPdOONN+qzzz5TeXm5nn/+eS1atEiSdP311ys7O9ut7u6771Z4eLj279+vBQsW6IMPPlB1dbVefvllzZ8/X21tbTr77LN1ySWXuNXdfPPNysjIUE1NjebPn681a9aopqZGb731lubNm6fq6mplZmbqpptucqu77LLLNGvWLLW3t+uqq67Sq6++qkOHDun999/X1Vdfrb179yoiIuK47jI7kpRWBytHy1Ra7flmpwC8S3Bgl2boMwUHdpmOAgAAAEN8rP5uHGFTzz77rG6++WaNHz9eu3bt6nfdAw88oEcffdTj3Jw5c/TGG28oICCgz9zTTz+tH/3oRx7vtzFlyhStW7fO43anb7zxhhYsWNDnjA5JSktL00cffdR7OcrRNm3apDlz5rht++oSFRWld999V9OmTeszl5+fr3PPPdfjtjaBgYF65ZVXdOmll/aZc0lNTVVJSYlSUlJUXFzc77qR4PXf/VP3/iRWv36yWlfc+W3TcQCcYOv+9Lr+b8lmLXj6dM3+4RWm4wAAAGCIHMvn0JPyzAzJeYnJK6+8otmzZysiIkJBQUGaMmWKnnzySa1evdpjI0OSlixZorVr12ru3LmKiYmRw+HQ+PHjtXTpUq1fv95jI0OS5s2bp40bN+raa69VfHy8AgIClJmZqbvuuktbt2712MiQpBkzZujzzz/X97//fSUnJ8vf318pKSm69dZbtXXrVo+NDEkaPXq0tm7dqjvvvFOZmZkKCAhQQkKCFi1apE2bNg3YyLCblPNitVunK+W8WNNRAAyD8ohT9F+6ReURp5iOAgAAAEO87swMDA07nZmxZcsWnX766dq8ebOmT59uOg6AE4z/zwMAAHgnzszASaXon+VKVKmK/lluOgqAYRC0d68qe0YAAACcnGhmwPaiQ1uUo1xFh7aYjgJgGOwrDNZF2qZ9hdz0FwAA4GRFMwO2FxfVqgf1iOKiWk1HATAMQgI7dYHeV0hgp+koAAAAMIRmBmyvudVPn+hMNbf6mY4CYBgkxRzW73WnkmIOm44CAAAAQ2hmwPYKy8J0tj5RYVmY6SgAhkFb+yjt0ylqa+c/YQAAACcr/iYI20s+J1pZmqTkc6JNRwEwDHZ2T9BY7dPO7gmmowAAAMAQmhmwPUdEgA4oT46IANNRAAyD1HE+ki7oGQEAAHAyopkB26v5slbf1q9U82Wt6SgAhkFkU5ke1zpFNpWZjgIAAABDaGbA9g6Xt6hAV+pwOVuzAieDuvzD6tI9qsvnBqAAAAAnK5oZsL2xqfXarQkam1pvOgqAYVBdF6jHdJ+q6wJNRwEAAIAh7GWJAVVUVCg7O9vjXE5OjnJycoY5EYCT3YSMOtUoRjszlpuOAgAAgGOUm5ur3Nxcj3MVFRWDPg7NDAwoISFBeXl5pmMMaG9xhK7QXj1RvEsTTYcBAAAAAPRroC/FU1NTVVJSMqjjcJkJbC84JUSpWqHglBDTUQAMg71NKRqt9drblGI6CgAAAAyhmQHbi86O0Drdr+jsCNNRAAwD39RYFWiHfFNjTUcBAACAITQzYHvtNS06XZPVXsNuJsDJIDmyXtN0q5IjuekvAADAyYpmBmyvZEO9NusLlWzggw1wMvDdV6hVSpTvvkLTUQAAAGAIzQzYXmZSgzZqhjKTGkxHATAM9h6MVLLKtPdgpOkoAAAAMIRmBmwvOLBLM/SZggO7TEcBMAzSEpr0hi5XWkKT6SgAAAAwhGYGbK+qNlBL9XNV1QaajgJgGIQFd+hyrVZYcIfpKAAAADCEZgZsr6YlRE/rFtW0sDUrcDKoaQrS47pNNU1BpqMAAADAEJoZsL30i+JVrjSlXxRvOgqAYVAYNlH36AkVhk00HQUAAACG0MwAANjKhAktkgJ7RgAAAJyMaGbA9orXVmiCtql4bYXpKACGQeCBA9reMwIAAODkRDMDthfq36o5el+h/q2mowAYBoWFAbpTb6uwMMB0FAAAABhCMwO2lxRzWL/XnUqKOWw6CoBh4DeqW3Gqkt+obtNRAAAAYAjNDNheW/so7dMpamvnH2fgZJAa36wX9V2lxjebjgIAAABD+PQH29tfEqGx2qf9JRGmowAYBl3dPmpQmLq6fUxHAQAAgCE0M2B7iTMiNUUXKHFGpOkoAIbB9tbxilCDtreONx0FAAAAhtDMgO0FxQVqm9YpKC7QdBQAwyBxrJ+khT0jAAAATkY0M2B7DbvrdKnuUcPuOtNRAAyD6PYK/ZtWKrqd7ZgBAABOVnythQFVVFQoOzvb41xOTo5ycnKGOVFftfkt+lT3qTb/E9NRAAyD5gP1Gq/vqflAvekoAAAAOEa5ubnKzc31OFdRMfgvq2hmYEAJCQnKy8szHWNAEzLqVKMY7cxYbjoKgGFQWh2im/WsVlavNh0FAAAAx2igL8VTU1NVUlIyqONwmQkAwFYmZtaqQ36amFlrOgoAAAAMoZkB28svDdNZWq/80jDTUQAMAx8fyU9d8mFnVgAAgJMWzQzYnl9sqPy0Q36xoaajABgGBU0JOkP/UEFTgukoAAAAMIRmBmwvdkqkPtKtip0SaToKgGHQnpiozT0jAAAATk40M2B7nU1tGqtEdTa1mY4CYBikJzYrRfOVnthsOgoAAAAMYTcT2N7BD2q1V2U6+MFqzTzfdBoAJ5pj7z4VyFdF/3xb8vd3vjh1qjRqlLRnj9TU5F6Qni7FxkrV1VJRkftcaKg0bpzU3S1t3dr3zU49VQoIkA4ckOrq3OeSk6XEROfrBw64zwUGSq5trbdudR7/aBMmSMHBzjzV1e5z8fFSaqrzz7Fnj/ucn5902mnOxzt2SG1faeKOGSOFh0tlZc6fo0VFSaNHS62tkqddqqZP7/saAADACEUzA7aXltCkN3S54hK+ZzoKgGHw5aF0TVKnNv9suvSzh5wvtrZKDof0wx9K69a5F/z3f0u33CK9+qp0663uc7NnS++/L3V0SKef3vfNDh50NhZ++lNp5Ur3uUcfle67T/rgA2n+fPe57Gxns0GSzj9famx0n9+82dk8+OUvpT/8wX3urrukJ56QvvxSOvts97nYWKmqyvl4/nxp/373+bfeki65RHr6aenhh93nbrhBWr5cKi72/Ge1rL6vAQAAjFA0M2B7YcEdmqnV2hn8XdNRAAyDuMnhitZNavvjfdLMU5wvus7Q+NOfPJ+ZIUnf+U7fsw9CQ4/Ub97c983i453jL3/pbFwcLTnZOZ5/ft/awMAjjz/4wPOZGZKzSfKDH3h+z8mT+x7X76j/bP/jH57PzJCkJUukK690n4uKco6pqZ7/rAAAADZCMwO2V9PgUK5u09QGh+koAIZBZGSXavScDoTNUe//6z1dIuJSVNT38hKXpiZpy5b+a7dv73+utNT540lr68DH3bWr/7nKSuePJ52dAx93377+52prnT8eOAoKNOaWW+R48UVp/Pj+jwEAADBC0MyA7ZXXhuhuPaG/1r5nOgqAYeDvH6eAgBu0ePHtkupMx/EK0yRtkVS2b5+SaGYAAAAboJkB2xt9aYLaHwjU6Es5bRo4GXR0pKm9fbmWL9+p8PAudXX5KD3debnFrl1BSkjoUFRUpxobR6m42KExY1rk7y+VlQWorc1HmZnOtXv2BCkmpkMxMZ1qbh6loiKHsrJa5XBYKi/31+HDvsrKapUk7d0bqMjITsXFdaqlZZQKChwaPbpVgYGWKiv91djoq1NOca7dvz9QoaFdSkjoUGurj/LzA5WR0abg4G5VVfmprs5fY8e2SJLy8wMVGNilpKQOtbf7aP/+QKWltSk0tFuHDvmputpf48c71xYUOBQQYCk5uV0dHdK+fUFKTW1XWFiXamv9VF7ur4kTnWuLihwaNcpSamq7urqcf9bk5HZFRHSpvt5XpaUBGj++RaNGScXFAapcu0568nbV1dUpaVj/1wQAAPiGLMCDlJQUS5KVkpJiOsrX2rx5syXJ2rx5s+koAIZBZ6dl1dc7x0WLLOuii47MBQRY1rJlzsdvvGFZkmWVljqf/+AHlnXmmUfWRkVZ1q9+5Xy8dq1z7d69zud33GFZkycfWZuSYlk//7nz8caNzrXbtjmf/9u/WdYppxxZO26cZd1zj/Px9u3OtevXO5//4heWlZh4Km8yewAAOhxJREFUZO20aZZ1223Ox/n5zrVvv+18/vjjlhUWdmTtOedY1ve+53xcWelc+49/OJ8/9ZRl+foeWfvtb1vWNdc4Hzc1Odf+9a/O588/73ze2up8ftVVlnX+lGLLkqy85cstAAAAU47lcyhnZsD2KtZXaabeVsX6KomdBQGv5+vr3H1Ucm4o0tl5ZG7DBuf9LSXp3HOd97mMjXU+f+gh560sXNaude6sKjk399i8+UjtvfdK//qvR9a++eaR42RnO9eOHet8fvvt0uLFR9a+/LIUEeF8nJXlXDtunPP5D37gfl/OF16QQkKcj5OSnGtd9/C84QbpW986svYvf3Fu2CJJkZHOtVlZzudXXy3NmHFk7bJlzt+T5LwX6ebNUmam8/ncuc7nrnum/uY30p5XPpO2CQAAwDZoZsD2/DpalKUW+XUEmY4CYJiNHu3+fNq0I48jItw3L8nIcF87ZcqRx2Fh7mvT0tzXTp585HFIiPvalBTnj8ukSUceBwW5r01Kcv64TJx45LHD4b42IcH543L0rSz8/d3XxsU5f1xcjRbJ2dQ4em10tPPHJStL2hiaLB9ZerFpk46KBAAAMGKNMh0AOF6p8c16Ud9Vanyz6SgAYEtxYwIk3dIzAgAAjHw0M2B7Xd0+alCYurp9TEcBAFuKU7Vu018Up2rTUQAAAAaFZgZsb3dhpCLUoN2FkaajAIAtHd5fo4t0lQ7vrzEdBQAAYFBoZsD24qeE60wtVPyUcNNRAMCWSipDtEAvq6QyxHQUAACAQaGZAdsLSQnWBq1USEqw6SgAYEvj0ut0SNEal15nOgoAAMCgsJsJBlRRUaHs7GyPczk5OcrJyRnmRH015Tfo2/qemvIb2JoVAL4BP19L0apVha9lOgoAAPByubm5ys3N9ThXUVEx6OPQzMCAEhISlJeXZzrGgKp2HtY/9ax+uHO16SgAYEtFTXHK0fP6aVMcW7MCAIATaqAvxVNTU1VSUjKo43CZCWxvYmatOuSniZm1pqMAgC0djk/RWqXqcHyK6SgAAACDQjMDtufjI/mpSz7szAoA30hG6mGF6UJlpB42HQUAAGBQaGbA9ooqQnWl/qGiilDTUQDAloL27FFDzwgAAGAHNDNge93BwSrvGQEAx25nYZRC1KSdhVGmowAAAAwKzQzYXsLMGG3SfCXMjDEdBQBsKT7ysB7TfYqP5DITAABgDzQzYHtWe4di5CurvcN0FACwpZiINv1Y/6WYiDbTUQAAAAaFZgZsr+CdQzqkThW8c8h0FACwpabDflqjb6vpMDu2AwAAe6CZAdtLjm3WM7pJybHNpqMAgC3tCcjWpVqjPQHZpqMAAAAMCs0M2F5kWLtu0nOKDGs3HQUAbGnMhE5JqT0jAADAyEczA7ZX3xygFbpG9c0BpqMAgC2FlBfpHypRSHmR6SgAAACDQjMDtldSGaJrtUIllSGmowCALVUUdGuVnlJFQbfpKAAAAINCMwO2l35xnEIVrvSL40xHAQBbam330xZNV2s7NwAFAAD2QDMDtucb4KsmNco3wNd0FACwpazkBm3STGUlN5iOAgAAMCg0M2B7VZuqNVt/VdWmatNRAAAAAADDgGYGbK+7qVV+ilN3U6vpKABgSzuashSsSu1oyjIdBQAAYFBoZsD2MhMb9Y7mKDOx0XQUALCl8NEhatETCh/NjZQBAIA90MwAAOAklxBQo2v0n0oIqDEdBQAAYFBoZsD28gqi5FCr8gqiTEcBAFvq2F+hO3WOOvZXmI4CAAAwKDQzYHsxE0I1S3crZkKo6SgAYEuFZWE6Tx+psCzMdBQAAIBBYUN5DKiiokLZ2dke53JycpSTkzPMifoKHx2qD/UHhY/+gekoAGBLp6TUa5fGqyVlqekoAADAy+Xm5io3N9fjXEXF4M8SpZmBASUkJCgvL890jAEdLmnSBZqrwyVN0nTTaQDAfhwB3RqvPdoZ0G06CgAA8HIDfSmempqqkpKSQR2HZgZsr2Jbk97XKlVsWy1dYToNANhPWXOUHtHjumhHvfTXv0qW5TbfOnq0rMBABZSVybeuzm2uMyZGHfHxGtXcLEdRkduc5een1rFjJUmBe/fKp7PTbb4tPV3dISHyr6yU36FDbnNdkZFqT0qST2urAvPz3QP7+KhlwgTncfPz5dPqvjV3e0qKusLD5XfokPwrK92PGxqq9rQ0qaNDQfv29fldtIwbJ/n6ylFUpFHNzW5zHYmJ6oyKkm99vQJKS93muoOC1JaZKUkK2rlT4VlZSjnrrD7HBwAAQ4NmBmxvbFqdSpWkqrTHTUcBAFvqzpqqv/pk6oXHrtFmjVKiapSsMh1WkHZpgm7QLu1Si36tJF2qaJ2qHZKkPE3UC2rQL1Wi8+TQk8rWOO1RqJpVrgR9qXh9W19KktZqvLJ0WOk6qHb5a7tO1Y+1Tx+rUfcrTguVrKnaJknao7F6VR26XwWaKF8t12karXxFqU7VitE+pessfS5JelWnaLK6laV8dctHWzVVD6tAr6lWP1KUblGmpmibfNWtAxqtf8pXP9I+xUpao2lK00HFqVp1itABZWm2vlSTOvWsMnSmHBqvPZKkrZqi36lMz6pS1ypMP9UYTdIOOdSuIqXpY4Xou9olSdqmyWpVlUrWv0xDAwCAE4QbgGJEa2tr09KlS9XW1tbvGn8/S0kql7+f1e8aYDgM5p9XYCRx/TN73nkxKigI1ebNy3VF7Ab9+/x/aufy5XrzFyt1urboof/5RJs3b9ae69bpktgN2rl8uXYuX64rU9ar9KqPtHnzZt29/COdri36/9u77/iqqnT/45+T3ntIhUAoSeggAqJIGcugg2JDEXBw7qiMyjiOqCMzShiv8htHrjrIoDNeQAQRLg5YKBaUphQJ0iOhJZQkhIQkpLezfn+EHIkpQkg5Cd/363Ve7Jy11j7POTxszn6y9torn/8PiYsW8bexa7nXezsJCQkkJCTwePS3TB2xjsRFi/jmjQ+4ip3c/+o3JCQkUDF5A0Ncd9j2OyF2E98Mr9zvP9d8y1Xs5L0nPiJx0SLm/tenXMNO237/p/8mHhmwnsRFi9g7fzFXsZNB0yr3G/XcBq5iJ7veWUziokX8buDXvNe3su2zrVsZ6LCDOQ9+SuKiRSx+cmVl/J9VxrxixEbu77bJFtN1bt8ROHkTCQkJjPz7Rq5iJ5teW0riokX86YYvebHTFltMIz02sYT/4tzRoy39V9zm6DgrrYnyVVqb1pazFmOMzgClhqprlSIiIjh58mSLxXHu3Dl8fX3Jzc3Fx8en1j5fvrGSD/6QyX2vB3HDE2OaN0CRC1xMvorYk9pydt8+CAiA8HAoLIQffoDYWPDwgNRUOHsWevasHH/gAPj4QGQkFBdX/tytG3h5QXo6ZGRA796VfX/4oXIfHTpAaWnl63TpUjk+I6Ny3337VvZNSgJnZ+jUCcrLYc+eym1/f8jMhOPHof/5NZIOHwYHB4iOBqsVdu2Cjh0r38PZs5CcDH36gKMjHD0KFRVw/soXdu6E9u0hOBhycirbe/WqfO3kZCgpgZiYyr67dkFYGISEwLlzla/bowe4ulbGU1AAcXGVfVfOXMWgab8lZ9GrxI0f35R/hVccHWelNVG+SmtjDzl7KeehusxEWr1iBw+20oMxDnktHYqISKtXVaiAyuJD/wsWVg4Pr3xUufBmV25u1fuGhlY+qpxf4gIAF5fqfdu1q3xU6dbtx20np+p9g4IqH1W6dPlx28Ghet+AgMpHlehoqrmwr59f9Z/PL39hU1VogcoCzIV9O3So3jeyXT7JdMS5WF+zREREmoouM5FWL/zaIPYzhPBrg36+s4iISBNLcoxjCFtIcoxr6VBERETaLBUzRERERBpRx24VQI/zf4qIiEhTUDFDWr2UtWn4k0XK2rSWDkVERASfrJO8xwF8slpuzSkREZG2TsUMafWC/Ip5jpkE+RW3dCgiIiKcOVbGbl7hzLGylg5FRESkzVIxow0zxjBv3jwGDx6Mj48PPj4+DB48mHnz5tGWbmIT5FvM07xKkK+KGSIi0vLyilz4mNvIK3Jp6VBERETaLC2z3UYZY5g4cSKLFy+u9vy2bdvYtm0b69atY9GiRVgslhaKsPEUFDmxnmF4FSmdRUSk5XWNzOUgsSRGLmrpUERERNosnf21UXPnzrUVMqZPn8748/e5X7x4MTNmzOD9999nyJAhPPbYYy0ZZqNISffmbtazPH01A5rwdebMmWM3n5e9xGIvcYB9xWIv7OUzsZc4QLHYO3v5TBojjnLg2LFjlGzciOuJE9XajIsLxZ07A+B+6BCUl1drL4mKwurhgfPp03y9dCk33njjj/v186MsLAxLURFuycnVX9TBgaKYGADcjh7FUlJSrbk0MpIKb2+cMjNxPnOmWluFtzelkZFYyspwO3y4xvtZuGcP99x7L64pKTgUFlbfb2goFf7+OGZn45KeXq3N6uFBSVQUWK24HzxYY7/FXbpgnJ1xOXkSx7zqt1gvCw6mPCgIx7w8XE6exCc6Gu8ePWrso6XYS76C/cRiL3GAfcViL+zlM7GXOMB+YrGXOFodI21OSUmJCQ8PN4B55plnarQ//fTTBjDh4eGmtLS01n1EREQYwERERDR1uPXKzc01gMnNza2zz5avt5gOdDZbvt7SpLHExcU16f4vhb3EYi9xGGMfsVxMvjYne/hMjLGfOIxRLD+lnK3d5caxbtH3JogfjB/dzS9wMwn0M/l4GAMmlVDzKT0NYACziThznEhjwBThahLoZ67GywAmnnZmF72NAWPA/EA381c6GMD0xckk0M/k4GMMmAyCzEb62va7ii7mKB2NAVOOg0mgn7kZPwOYJwgwCfQz1vP7PUy0+QfRld8NwCTQz2QSYAyYs/iZBPoZZxwMYN6no0miiy2mnfQ19xNkADMRH5NAP1OKkzFgkulg3qWbAYwLmF30Num0MwbMObxMAv1MOK4GMP8k0uwnzrbfPfQ0jxNqADMKD5NAP3MGN3Pwiy/sJmftJV+NsZ9Y7CUOY+wjFh1ja2cvcRhjP7HYSxz2kLOXch6qmRlt0ObNm0lNTcXBwYFnn322Rvuzzz7LrFmzSE1N5dtvv2XYsGEtEGXjcfFx4ThHcPHRtckiItLyugzty9hHsrnzniVkHS/jqt9cxdIZa+jV+SxvftiLDzd0IeGLHwAYd0c0V8em8+cHEkhJ92LU1Nv59z/28ta1ZSya48HV80PY/d7qyr7xNxEdXUTCzEwyT5Rz1ZiBzH3qa4b1S+X9L7rxt8X9Sdi2G4DHJkUQ4FnEq49/Q36hEwMfvpdX4vfz8ugSVr3vwlWzerLn3fdxcjQ8NmsYxsmJhLdSqSgq46rrBvHSw1u44/qjrN3WgT/OHkpU+578Z+VC/vJEMP/IdmLec18BMGjSfTz1u8MkTCrgmzUOXPWXvmyY/SHB/sU8/+9BHE4LIGFJMlitXD+8Fw+N3s9//SqR7QfaMenlG1n5f7toH21l1gt+vL7Hn5UzK9/rjVPu4I5b00h4MpfE7+Cqyf3ZTW/KfzobRURErlgqZrRBGzZsAGDIkCEEBATUaA8MDOSaa67hm2++YcOGDa2+mHF2VxY38gZnd2VB/5aORkRErnQdOsD/vOGPq6s/RUWQ0AdiYkbh6Ql/GQmTM6FXr8r/sFasAW9vP9q3j6VTMSSMgK5de+HtDREvw8qv7yBu/AoAlg4ANzeIiupAWS9ISIDOnUfg6wu/vwnufAL69avc78IPwckJOnXqSEUFJFwFnTr1wN8foqLg1vuhZ7/7sVjg34Mr4+7cORRjKvcbFXUNgYHXEHoLDJsE48dD//79mbOw8qqYrl0rL1/d1h0iI2MIDobOneHaUdCr1104O8Os66C4GGJiKr+LbPwGQkP7ExLSn8g86HUXdO/eFzc3+H9zIS8P4rpX7veL3hAU1JmwMIiJgeVnVtP1+UMkNuPfo4iI2DcVM9qgU6dOATBo0KA6+wwcOJBvvvnG1rc1K8osJp3hFGWmtHQoIiIiALi6Vv7p7g79Lyi0h4VVPqp07/7jtptb9b4hIeDm9uM6E+eXwwDA2bl63+DgykeVrl1/3HZ0rN43MLDyUeX88h0AWCzV+/r7Vz4sFisAnTpVf5/9+v247etbfWxUVPW+ffr8uO3tXb1v+/bV+/bq9eO2pycEBFv5Da8y/Ic8+gCfvfY5Qf4OhAYWUVzqSKKJpUM38M09RfaxYs7muRHTIQeApPz2OEX6E+Gbi+XwCQ6f9KVDSB5eHuVk5nty0ieGmJgi3I4cITnZFRdnKxHBBZSVW9hfFkt4V0f8i9PJO5pHepYH3TtlA+BxNpCPP95H++A8nA8f42CKH+HBBfh5lZKT78JRr57ExBThfjyZUymOWK0QFZoPwO78bgR3cSGYTAqPnOVUhifdOuTg5Gg4nh9MYbsIoiILcU9KIjHFn3Z+hQT6lpBf6ESSS3e6xJbjmX6c08lWikudiM7JIXHxYvbnR+PTyZMQl7OUHTlNSpo3nSNycXWxklbgz9mAjkRHF+P+ww8U+3Sj36+acrUxEZGmpWJGG3T69GmAWmdlVAk8/y0mIyOjWWJqSl0izrGHPiRGaNV4ERGRtsitdz+WWuL4YNZgcoGr43txGx/zd55hP90Zz37gGt5kK9n8mTk8RhrhANxIAqfYyGAeZwlR3E0yX3ADV7OOv/Ik0xkJ+HIIeJlNdOEwC3iQMwTRhzPAbUznE8J4mMeYQznOAJSylttvT6QzY9mNB70o4H3GMY4PWMR4JnIP4Mq3lPIWH1KCK6uYAEB3DPBbHuV/+QV3cDf/IYsAAsjmMd7ja1zwZgTngAHkM5Pn+D2z+YybmMBnQCQfcYpVvMVO+vMdaTBhAleRQRH/w938P57gWu5mMz8QQwxJvMQsFhMFXMUJgvgVW3hj6mzC44L5wRJHVDcrvjmpZB0rITffha7tcwE4mN8B1w5+hHnlwOGTHDnlS1RYHp5u5WTke5Hu142uXYtwO3SIdplBrHtjBeFBhZSWO3CgLIaIbg74F6aTezSfjBwP4qIqi0FHCiIwYUFEBp7D6XAyScf9iGhXgK9nKdn5bhzz6k5cXBFux45xPNkJBwdo3y4fqxX2FsUQ0tWZwPIMCo7mkHrGk5ioHBwdDMn57SgJCaessJDExYs5cMyf0MBCAnxKOFfgzGH3HnTpVoJX2nHSkqG0zIFO4ZWLz+7N74J/tDvtnLIoPZzB8dPedInMxcXZyqn8AHKDoujUqRj3xEQOHvcjwLuYYP9iCoqdSHKMY8AQf7p1+0llTkSajIoZbVBVMcPf37/OPlWFjqq+IiIiIvbqmmsi+O67kxQUfMj1w4bx3/F7CfLvTGLgIkpLHVlsdtGh21zbzIyeeTtJ7FD5S445+fk4RV5PhO8mcg+fYPnJ1fiGPESix4OMyPekq88pYmISKD1yhGnJZ3Fx9iMxeBFl5RbeL9tJeNcX8S9+jLyjeSzN+pzETpX7dXnqv/noX3NpH/wtxw4fY3nKasKD7yTR61d0zndhkVciMTFbcD+ezOQUR6zWchJDK8cuyf+O4C5TCGYchUfOsjxjNac6vMlpR8Oz+cFMaRdMVOR2EpOSeC9lA+38rifRdxABhU4sctlLl9hP8Ew/zthkK7eVpvOr18L4+9//zsL8w/h0GkeIy82UHTnN8rTVFEXEk+hi5TcF/owJsBAdncCupVu46ZXVDHr1RU7QnvHsBPrzb74nmRdZxASSqZyGM5x9ZPAZw3iKt+nG3RxkE9cxgG94lz/xN4YA7TgBFLCdZX/YydtM5iQR3M9J4GZe5nM8mcJzzKQALwDG8DVJ7KI7E9mEP705y4fcyWBWMJf/4lHuAiwkALP5FFdK+A8TKMGFnpQAE3iSxVzNfdzPEvLxxJNCfssyvsVKECnETZhAL8qYw2M8wr/4mNFM4GMgmLVksoT5HKYLm7kdgD7kUkY843mNSfyCu/mSY3SkIyn8hTf5DyHAVRhgJKk8xhz+wktsYTDj2UKo61XM/fPjOLgE0zUyl6KiIgLpzhdfHKBzcCnmSCpHT/nQMewcHm4VZBT4kO7bma5di3E/dIjDKR54upUTFlhISakDidZYIrtZ8MtPI+dYIZk5bsRG5QBwKD8Cx8ggwv1ycTycwqETfrQPycfbo4yz+e6keMcRG1uE29GjpKS44ORgJTonh33vvc++4hhCuzoRUHqagqO5pGZ6EtcxG4sFkvNDKA0NpUNoAa6HDpOY7E94UAF+3qXkFrhwxKMH3WKK8TiZQmqyhXKrAx1DK4tBe/K6ENTVnSDOUHI0ixOnvejaPgdnJ8PJ/EDygtvTsUMR0Tk5rHh5FUF+xQT5FlNQ5ESSc3c6dSvH+8wJMpIrKCh2okvEOQAO5HfCq6MXoW7ZlB9OIznNh+iIc7i5VJCe70tmQDSdOxfjfvAgh4574+1eetGztvLy/Nm1eXOjzto6mh9GRVi7S5q1VTW7qtFnbYVXfoZVs7ZiY/3o0KFD4x+kW4jFGGNaOghpXF27duXw4cMsXLiQiRMn1trnvffe44EHHqBr164kJSXVaHdxcaGsrAwHBwdCQ0MbHIvFYmnwWABjDKmpqYSHh9e5r+K8YrLPOePvU4abt9tlvV59Tp8+TUhISJPt/1LYSyz2EgfYRywXk6/NyR4+E3uKAxTLTyln7TsOsJ9Y7CUOe8pZe/lMoGGxVJSWYsrLMVgowwknJ7BYK7BWGIzVgpNj5aVF5cYJHC04Ohgor6C8woKTo8GCocI4YHVwwsnJYCkvJzsnHx9vLxwdDAYL5cYJR+fK/ZoKQ4XVgrNtv47g6HB+v+WUV1RuO1gMVmOh3OKMs3PlfssrLFgAR4fKsWXGGQcncMCKKbdScT5ei22/juTkZBLk40NZLft1cjI4WCuoKK+8/Y+Tbb9OODhZcMAK5VbKrXW817IyyisccDi/X4OF0goHLOeyKMOHYtwIofIXhqmEYCjClXP44kQGIbQjA2fKyMGbAjyBdMKAM7TDlRL8yKUcR04TCpzBl1LAi3N4E04aAOkEU0EZzuQQhANphBFIFm4Uk48nufgBpwiB8z2sBHAWg4VUwoGzeFOEEx5k408ElZeeZxBIGeBAFmHAKSLwJxsPCinCnbMEAKkEYSggACsOBJEJ5/tCDh4U4I4bWQQSRhoOWMnCj2KcgTNEAKmE4UMeXuRTgguZBAPpBFBBCb6U4EoIGec/w1AMBbiRhw/OZNCOdpzGmXKy8aEQd+A04UAGIbhRjC+5lOPEaUKAM/hRihVv8vEi7PxnmEY7rJTiQg4BOJJOKEFk4koJeXhxDp/zf4OQTTBOlONPNtbznzdk4U0xjniSg5/tMzxNEOVYceQsIec/7wDO4k4RhbiTTQBwimAgjwDAQiBZF3yG2XhSiCtunCWQMFJxwJCJPyU4YiGTcCCVcHzIxYsCSnAlkyAgjUCsFONHKS60O/8ZniIMyMedPHzbtcPR2bnW40JjHWMvp8SQnp6O1WrF2dmZ0tLSevuqmNEGDRw4kO+++445c+bw6KOP1trnzTffZMqUKQwYMIDvvvuuRrujoyNWq7WpQxURERERERGpxsHBgYqKinr76DKTNqhqJkV2dnadfara6pp14ebmRnFxMY6OjgRfuKLYJWrp35qIiIiIiIhI87mc+RJnzpyhoqICN7efn3GvYkYbVDXNMCsrq84+Z8+eBSDswiXVL1BQUND4gYmIiIiIiIg0AoeWDkAaX0REBABbt26ts8+2bdsACA8Pb5aYRERERERERBqLihlt0LBhw4DKYkZtszOysrJsxYwRI0Y0a2wiIiIiIiIil0vFjDbo2muvJTw8HGMMM2fOrNH+yiuvYLVaiYiIYMiQIS0QoYiIiIiIiEjDac2MNsjFxYXnn3+e3/3ud8yaNQsfHx8mTJhAeXk5S5Ys4ZVXXgHghRdewLmO2/KIiIiIiIiI2CvdmrWNMsYwceJEFi9eXGv7pEmTmDdvnu42IiIiIiIiIq2OLjNpoywWC++99x7vvPMOAwcOxMvLCy8vLwYNGsSCBQvsupBhjGHevHkMHjwYHx8ffHx8GDx4MPPmzbus2/yINJWVK1cycuRIAgIC8PT0pG/fvsyaNYuysrJ6x23YsIHRo0fTrl073N3diY2N5YUXXiA/P7+ZIpcrlXJWmtuZM2eYMmUKgwcPxs/Pj9DQUIYNG8bf//53SkpK6h2rfJXWpqG5t3v3bsaNG0dYWBiurq5ER0fzhz/8gTNnzjRT5HKluZzzroYemxuVEbEjVqvVjB8/3gC1Pu6//35jtVpbOky5QvTr18/ExMTU22fatGl15uuwYcNMcXFxrePmzp1rLBZLreO6d+9usrKymuItSRuSmZlpnn/+eTNixAgTERFhvL29zeDBg80TTzxhTp8+Xec45aw0t40bN5rAwMA6865r164mPT291rHKV7E3b731lgHMI488Umt7Q3Pv448/Nq6urrWOCw8PN0eOHGnKtyWt3Jo1a+o8Vl74yMvLs425nPOuhh6bG5uKGWJX5syZY/uHMH36dJOUlGSSkpLM9OnTbc+/+eabLR2mXAF27dplgHqLGatWrbLl5aOPPmp2795tjh8/bv7xj38YR0dHA5ipU6fWum8nJycDmHvuucds3brVpKenm3fffdd4e3sbwNx9991N+faklUtKSjKRkZF1fpHw8/MzK1asqDFOOSvNrbS01MTGxtpO5D777DOTlZVl0tLSzPz5821FjjvvvLPGWOWr2JuDBw8aDw+POosZDc291NRUW/uIESPM119/bc6cOWOWL19uIiIiDGAGDBigX+hJnV577bVLLmY09LyrocfmpqBihtiNkpISEx4ebgDzzDPP1Gh/+umnbdXp0tLSFohQrhRHjx41PXr0+NlixoABAwxg7r333hpfMKr+g3B3dzdnzpyp1nb33XcbwFx33XWmpKSkWtunn35q+w9i3759jfempM2wWq1m0KBBBjD+/v5m/vz55sSJEyYrK8usXr3a9OnTxwDG29vbHDt2rNpY5aw0tyVLlhjAuLq6mpMnT9Zo//jjj23589PZGcpXsSelpaW2nKyrmNHQ3Js6daptllJ2dna1toSEBNuMjVWrVjX6+5K2YfLkyQYwzz///EX1v5zzroYem5uCihliN9atW2cA4+DgUOsUvMzMTOPg4GAAs379+haIUNqyvXv3mt///vdmxIgRtjyrr5hx5MgRW5/du3fXaC8vLzcBAQEGMAsWLLA9n5+fb/tS8tFHH9W67759+xrAxMfHN86bkzblu+++s+Xe559/XqM9Pz/fxMTEGMA8+OCDtueVs9IS/vznPxvAjBkzptb2iooK22+6v/jiC9vzylexN1W5XFcxo6G5Z7VaTfv27Q1g3njjjVrHjRkzxgBm0qRJjfeGpE0ZPny4AczSpUsvqn9Dz7saemxuKloAVOzGhg0bABgyZAgBAQE12gMDA7nmmmuq9RVpLDt27OAf//gHX3/9NVar9Wf7V+VgZGQkvXr1qtHu6OjIqFGjqvUF2L59OyUlJbi6uvKLX/yi1n3feuutNcaJVNm7dy8AsbGx3HDDDTXaPT09efLJJ4HKfKuinJWWcOTIEQA6duxYa7uDgwO+vr4A5OTk2J5Xvoo92bx5MzNnziQ8PJzRo0fX2qehuZecnMyJEyeqtV/MOJELHTx4EICePXteVP+Gnnc19NjcVFTMELtx6tQpAAYNGlRnn4EDB1brK9JYbr/9dvbu3Wt7vPjii/X2vzBf67ozUG35WrXds2dPPD09L3qcSJWjR48C0K1btzpzr3PnzgAcO3bM9pxyVlrCkiVLMMbw2muv1dp+5MgR0tLSAOjRo4fteeWr2Itz584xceJErFYrCxYsqPXEDxqee1XbgYGBtmN3feOM7uwnP3Hu3DnS0tJwdnYmMzOT0aNHExkZib+/P8OHD+eFF16gsLCw2piGnnc19NjcVJya/BVELtLp06cB6vxPAioP9AAZGRnNEpNcOfz9/fH397f9vGPHjnr7NzRfledyuW677TZ69OhBdHR0nX127twJUK2PclbsgTGGvLw8srKy2LhxIy+//DIAd911F3FxcbZ+ylexF1OmTCE5OZknnniCG2+8kcWLF9farzlytrS0lHPnztlmM4nAj7MyysvLGTZsWLW2DRs2sGHDBpYuXcry5cttsynayjFWMzPEblT947jwhPKnqv7hVPUVaSkNzddLGZeTk0NJScllxypty9VXX819991n+83HTx0/fpxZs2YBMHbsWNvzylmxBx999BG+vr5ER0czadIkkpKSePzxx1m4cGG1fspXsQfLli1j4cKFdO/enZkzZ9bbt6G5dynjLuwvUqWqmGGMoWfPnnz88cdkZGRw5MgR5s6di7e3N0lJSYwfP57y8nKgeY6xzZGrKmaI3cjOzgbAy8urzj5VbZmZmc0Sk0hdGpqvlzIOICsr67LilCvL5s2bGTZsGBkZGXTs2JEpU6bY2pSzYq82btzI999/X+055au0tJMnT/LII4/g7OzMokWLcHd3r7d/Q3PvYsa5ubnh4FB52qbvwPJT586do0ePHowaNYoNGzYwevRogoODiY6OZvLkyWzcuBEHBwf27t3Lv/71L6B5jrHNkasqZojdqKrw5eXl1dknNzcXQNPrpMU1NF8vZRyAj4/PZcUpV4bk5GTGjx/P0KFDSU5OJjw8nM8//xw/Pz9bH+Ws2IMxY8ZgtVo5ffo0X3zxBddeey179uzhpptuYt++fbZ+yldpSVarlV//+tfk5OTw4osv0q9fv58d09Dcu5hxBQUFtsXJ9R1YfurRRx9l3759rF69utbLP/r27cv9998PwJdffgk0zzG2OXJVxQyxG6GhocCPFb/aVLVV9RVpKQ3N10sZ5+XlVW/lW6S0tJQZM2YQExPD+++/D8C4cePYu3cvXbt2rdZXOSv2wmKx0K5dO2644Qa+/PJL4uLiKCws5PXXX7f1Ub5KS3rttdf46quvGDp0KFOnTr2oMQ3NvUsZd2F/kUsxZMgQAA4cOAA0zzG2OXJVxQyxGyEhIUD9Uz7Pnj0LQFhYWLPEJFKXhuar8lway65duxgwYADx8fGUlpYyZMgQNm3axPvvv1/rb2aUs2KP3NzcbL8x3LVrl+155au0lCNHjjBt2jS8vb1ZuHAhjo6OFzWuOXLW2dm53oUXReoSFRUF/JhnbeUYq2KG2I2IiAgAtm7dWmefbdu2ARAeHt4sMYnUpSpft23bVudt0mrL16px+/btq3OKnvJcfs6ePXsYPnw4e/fuxdPTk/fee4/Nmzdz3XXX1TlGOSstISIiAi8vL9vU5tpUfTkuKyurNg6Ur9L8Tpw4QWlpKXl5eXTq1AmLxVLt8e677wLw9ttv255buXJlg3Ovalx2djZJSUk/O66u22HKlamsrIy1a9eydu3aei/9qLoFdmxsLNDw866GHpubiooZYjeqbiW0devWWqt9WVlZtn8cI0aMaNbYRH7q+uuvByA1NZXdu3fXaK+oqOCzzz4DqufrwIEDcXV1paysjHXr1tW67zVr1tQYJ1IlLy+PX/7yl+Tm5hIbG8v27duZMGHCz37BVc5KSwgJCaGgoIBDhw7V2ScxMRGA3r17255Tvkpr09Dci4qKokOHDgCsXr36oseJADg5OfH4448zatQo2+WmtdmxYwcA3bt3Bxp+3tXQY3OTMSJ2oqSkxISHhxvAPPXUUzXan3nmGQOYiIgIU1pa2gIRypVk/vz5BjAxMTF19rn66qsNYO6++25jtVqrtf3zn/80gPHw8DCZmZnV2u655x4DmGuuucaUlJRUa1u1apUBDGD279/feG9I2oy3337bACYoKMicOXPmksYqZ6W5jRs3zgCmV69epry8vEZ7enq68ff3N4CZM2dOtTblq9ijX//61wYwjzzySI22hube008/bQDTuXNnk52dXa0tISHBuLq6GsCsWbOm0d+PtH5V+dOlSxeTm5tboz0pKck4OzsbwGzatMkYc3nnXQ09NjcFFTPErsydO9d2oJ8xY4Y5cuSIOXjwoImPj7c9//bbb7d0mHIFuJhixurVq215+fjjj5t9+/aZlJQUM3v2bOPk5GQA89xzz9UYt3v3blv72LFjzXfffWfS0tLMwoULjbe3twHMuHHjmvLtSSs2bNgwA5hnnnnmkscqZ6W57dq1yzg4OBjA3HDDDebbb781OTk5Ji0tzXz44Yemc+fOBjB9+/atcfKnfBV7VF8xo6G5l5aWZnx8fAxgRo4caTZs2GDOnDljPvzwQxMZGWkAM2TIkBonjiLGGJOcnGwrCg8cONCsX7/e5ObmmuTkZDN//nwTGBhoADNx4sRq4xp63tXQY3NTUDFD7IrVajXjx4+3/QP56WPSpEk6kEuzuJhihjHGTJs2rc58vfHGG2t8Oa/y1ltvGYvFUuu4Pn36mJycnKZ4W9IGdOzYsc6c++kjKiqqxnjlrDS3v/71r3XmDmB69OhhDhw4UOtY5avYm/qKGcY0PPc++eQT4+LiUuu49u3bm5SUlKZ8W9LKrVq1yjaDp7bH4MGDa8yUuJzzroYemxubihlid6xWq3nnnXfMwIEDjZeXl/Hy8jKDBg0yCxYsUCFDms3FFjOMMWbFihVm2LBhxtfX17i7u5s+ffqY119/3ZSVldU7bv369eaWW24xgYGBxtXV1cTExJj4+HhTUFDQWG9D2iAPD4/LKmYYo5yV5rd9+3Zz5513mu7duxt3d3fToUMH88tf/tK8/vrrP3vpqPJV7MnPFTOMaXju7dq1y4wdO9a0a9fOuLi4mI4dO5onn3zSZGVlNfbbkDYoJSXFPPTQQ6Znz57G09PTdOzY0dxxxx3m7bffrvM4eznnXQ09NjcmizF1LEMqIiIiIiIiImKHdDcTEREREREREWlVVMwQERERERERkVZFxQwRERERERERaVVUzBARERERERGRVkXFDBERERERERFpVVTMEBEREREREZFWRcUMEREREREREWlVVMwQERERERERkVZFxQwRERERERERaVVUzBARERERERGRVkXFDBERERERERFpVVTMEBEREREREZFWxamlAxARERERERGxF2vWrGHu3LkkJCRQVFREnz59eOKJJxgzZkyLxGOMYc+ePRw8eJDU1FSKi4sJDAwkLi6OAQMG4Obm1iJxtTTNzBAREREREREB4uPjueWWW1i9ejXBwcGEhoayfv167rjjDv7yl780eL8Wi6XG4+eKIwUFBcyYMYPOnTvTt29f7r33Xp588kmee+45Hn74YYYOHUpAQAAPP/wwx44da3BsP6eiooLw8HBb3IcPH76k8TNnzrSNffbZZwFYv359rZ/JggULLnq/KmaIiIiIiIjIFW/Hjh3MmDGD2NhY9u3bx65duzhw4ADffPMNISEhvPTSS2zevLlZYvnqq6/o3r078fHx1QoVTk5OODs7234uKiri3//+N7169eLdd99tklgcHR259957bT//3//93yWN/89//mPbHjt2bKPFpWKGiIiIiIiIXPHi4+MBWLx4MbGxsbbnhwwZwhtvvAHAP//5z8t6jVGjRjF79mxmz57NQw89VGufTz/9lFGjRnH8+HEAunXrxptvvklKSgrFxcUUFhZy8OBBFi5cSLdu3YDKWRyTJk1i/vz5lxVfXcaNG2fbXrZs2UWPO3HiBDt27AAgOjqa/v37A9C1a1fb51D1uV8qizHGNGikiIiIiIiISBsRGhqKh4cHR48erdGWn5+Pj48P0dHRl3yZBVReZgIwffr0ek/eDxw4QP/+/SkpKQHgj3/8Iy+//DKurq619i8rK2P69OnMnDkTADc3N77//vtqxZjGYIyhS5cuts/m4MGDtkJKfWbPns3vf/97AP70pz/Z4rxQcnIynTp1AmD+/PlMmjTpomLSzAwRERERERG5ouXl5XH69GmOHTtW61oO3t7eGGPIzMxsshgqKip48MEHbYWMqVOn8uqrr9ZZyABwdnbmpZdeshUAiouLmTFjRqPHZrFYqs3OuNhLTVasWGHbbsxLTEAzM0REREREROQKl52dTUBAAH5+fgwaNKjOfo6OjqxateqS938xMzNWrlzJHXfcAUDfvn3Zvn17tfUx6pOdnU1YWBglJSU4Ojpy+vRpAgMDLznO+uzfv5+ePXsC0Lt3b3bv3l1v/6ysLEJCQqioqKBLly4kJSXZPocLaWaGiIiIiIiIXJEWLFiAxWIhKCgIgNLSUt58800GDRqEn58fXl5e9OzZk2effZa0tLQa4/39/QkICCAoKIi1a9fW+WhIIeNizZkzx7b90ksvXXQhAyrjv/POO4HKGR7r16+vtZ/VauWDDz7gtttuIyIiAldXVzp27MiNN97IokWLKC0trfM1evToQa9evQDYs2cPP/zwQ70xffLJJ1RUVACVszJqK2RcDhUzREREREREpM3IyMjg+uuvZ8qUKWzfvp3c3FwKCgrYv38/r7zyCrGxsaxZs6bGuF69enH06FGOHDlSo23//v2MGTOG119/vUlizs3NZd26dQB06NCBm2+++ZL38f7772OMwRjDXXfdVaM9IyODoUOHMm7cOD755BNSU1MpLS0lJSWFL7/8kokTJ9KzZ8961wS5lEtNmuouJlVUzBAREREREZE2oaKignvvvZdt27bh6enJ7bffzosvvsgDDzxAZGQkAOfOnWPMmDEkJCRUGztt2jSsVisTJ07kxIkTtuczMjL4zW9+w0cffUR0dHSTxL1lyxaqVoAYOXIkjo6Ojbr/wsJCRo4cybfffgtAx44deeihh5g5cya//e1v6dixIwCHDh3immuuISUlpdb93Hfffbbt+u5qkp+fz+effw5U3o2ld+/ejfROfuTU6HsUERERERERaQE5OTmsX7+e9u3bs3btWrp3725ry8/P54EHHmDFihWUlpYyefJktm/fbrv84aabbuKRRx7h7bffpmvXrvTo0QMXFxe+//57SkpKePjhhxk9enSTxH3h+hNXX311o+//hRdeYP/+/QA8++yzxMfH4+bmZmsvLi7m+eef59VXXyUzM5OnnnqK5cuX19hPp06dGDx4MFu3bmXfvn0cOHCg2mdcZe3atbaFTJviEhPQzAwRERERERFpYz755JMaJ9leXl4sX77ctu7Djh072Lp1a7U+b731FkuWLOH666/nxIkTJCUlMWDAAJYsWcLcuXOb5KQcKhfLrBISEtKo+87JyWHu3LkA3HXXXcycObNaIQMqb+n6yiuv2BYg/fDDD2u93AYu7lKTpryLSRUVM0RERERERKTNGDVqFH369Km1zcHBgT//+c+2nz/++OMafe677z4+//xzMjIyyMrKYvPmzdx33304ODTd6XN2drZt28fHp96+U6dOrfX2sRc+hg8fbuu/Zs0aCgsLq42tjcVi4Y9//KPt502bNtXab+zYsbbPYunSpfz0BqmlpaW2hVJjYmJsd0BpbLrMRERERERERNqMqrt61OX222+3be/YsaOpw7ko7u7utu2qwkNj2bJli21769at9b7nC1977969tfYJDQ1lxIgRrFu3jsTExGq3bAX4+uuvyc3NBZruEhNQMUNERERERETakE6dOtXb7ubmRnh4OKmpqaSmpjZTVPULDAy0bWdmZtbbd8yYMbYFO3/qjTfeqHE3kpMnT9q2n3zyyYuO6dy5c3W2jRs3znb3lWXLllUrZjT1XUyqqJghIiIiIiIibUZ4ePjP9omMjCQ1NdU2g6ClRUVF2bZ37dpVb9/rrruO6667rta2d999t8Zz9RUl6lPfuDvvvJPf/e53lJWVsWzZMmbMmIHFYsFqtfLRRx8BEBcXR48ePRr02hdDa2aIiIiIiIhIm3HhYpp1SU9PByoXBQWIj4//2XUo6lqTojEMHTrUtr1+/foa61BcDGNMtVkYVTw8PABwdXWloqICY8xFPZYuXVrna/n7+zNq1CgADh48aLskZcuWLZw+fRpo2ktMQDMzREREREREpA1JTk6uc+YCQElJCSdOnACgXbt2AHTp0oWbb765Wr9Tp06xb98+wsPDbXdAqdK7d+9GjTk6OppOnTpx7Ngx9u3bx44dOy75Fq0HDx60FWkuVHV3lJKSEk6ePEmHDh0aJeZx48bZFlBdtmwZvXv3rnYXk3vuuadRXqcumpkhIiIiIiIibUbVWg51WbNmjW3mQ1XBYMKECaxdu7ba46mnngLgxhtvrNH2yiuvNGrMFouFxx57zPbzCy+8cMmzM2bPnl3r8wMHDrRtJyQk1LuPH374gfj4eOLj4+u8NWuV0aNH22Z9LFu2DGOMrZjRo0ePJr3EBFTMEBERERERkTZk0aJFJCcn19pmtVqZMWOG7edbb721maL6eb/97W9tC4GuXbu2zuJEbTZt2sS//vWvWtt++ctf2m6lOn36dMrLy+vcz/PPP8+MGTN49dVXCQ0Nrfc1PT09bXeGOXToEO+99x5Hjx4FmnbhzyoqZoiIiIiIiEibUV5ezm233UZKSkq15wsKChg7dqxtgc3evXszYsSIFoiwdr6+vrzzzju2n5944gn+9re/UVFRUe+4L7/8kttvv73OIkX79u1txYW9e/fy0EMPkZ+fX62PMYZZs2axfPlyoPISEU9Pz5+Nedy4cbbtP/zhD7btpr7EBLRmhoiIiIiIiLQhQUFB7N27l759+3LzzTfTq1cvDh06xFdffWVbK8PZ2Zl33nmnSReobIgxY8bYLvMA+NOf/sSSJUt49NFHueWWWwgLC8PR0ZHCwkI2b97M//7v/7Js2TIAbrrpJjw8PFi5cmWN/b7++uusX7+e9PR0FixYwLp167jhhhuIiYkhOzubNWvWsGfPHqBy/ZBXX331ouK9+eab8ff3Jzs7m+zsbAB69epFXFzc5X8YP0PFDBEREREREWkzli9fzkMPPcShQ4dYunRpjbty+Pj48MEHH1zyApvNZfr06QQGBjJ16lRKSkrYvXs3jzzyCACOjo64u7vXmFnx4IMP8tZbbzFv3rxaixkhISFs2LCBX/3qVxw6dIgTJ04wf/78Gv169+7NsmXLbJe7/BwXFxfuuuuuajNKmuMSE9BlJiIiIiIiItKGREVFsWvXLl566SV69+6Nl5cX7u7uxMXF8fTTT3Pw4EHbbUXt1eOPP05iYiLjx4+3LbIJUFFRYStkWCwWrr/+ejZs2MC8efNwcXGpdovXn+rWrRt79+5l7ty5jBw5kuDgYFxcXOjSpQu33nor7777Ljt37iQmJuaSYr3//vur/dwcl5iAZmaIiIiIiIhIG+Ph4cG0adOYNm1aS4fSYJ06dWLRokUUFRWxceNGjh8/zpkzZ/Dx8SEsLIyhQ4fabi1bpUePHvXeBcXV1ZXJkyczefLkRotzxIgRl3znlcagYoaIiIiIiIiInXJ3d+fmm29u6TDsji4zEREREREREZFWRcUMEREREREREWlVdJmJiIiIiIiISDPYvn07b775JlC5Jsatt97awhG1jFOnTrFixQoAsrKyGrQPFTNEREREREREmsGaNWtYs2YNALfffvsVW8w4dOgQU6ZMuax96DITEREREREREWlVNDNDREREREREWrVJkyYxadKklg6jTi1x61J7Nnz48Mv+TCxGn6qIiIiIiIiItCK6zEREREREREREWhUVM0RERERERESkVVExQ0RERERERERaFRUzRERERERERKRVUTFDRERERERERFoVFTNEREREREREpFVRMUNEREREREREWhUVM0RERERERESkVVExQ0RERERERERaFRUzRERERERERKRVUTFDRERERERERFoVFTNEREREREREpFX5/ykdn8knbKSrAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<Figure size 1200x900 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "s_sum.plot()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": null,
    "id": "3787a08f-a9e9-467c-ac70-545b428c845c",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['__add__',\n",
-       " '__class__',\n",
-       " '__delattr__',\n",
-       " '__dict__',\n",
-       " '__dir__',\n",
-       " '__doc__',\n",
-       " '__eq__',\n",
-       " '__format__',\n",
-       " '__ge__',\n",
-       " '__getattribute__',\n",
-       " '__gt__',\n",
-       " '__hash__',\n",
-       " '__init__',\n",
-       " '__init_subclass__',\n",
-       " '__le__',\n",
-       " '__lt__',\n",
-       " '__module__',\n",
-       " '__ne__',\n",
-       " '__new__',\n",
-       " '__reduce__',\n",
-       " '__reduce_ex__',\n",
-       " '__repr__',\n",
-       " '__setattr__',\n",
-       " '__sizeof__',\n",
-       " '__str__',\n",
-       " '__subclasshook__',\n",
-       " '__weakref__',\n",
-       " '_get_err2',\n",
-       " '_get_err2_from_syst',\n",
-       " '_is_empty',\n",
-       " '_n_empty',\n",
-       " 'datamc',\n",
-       " 'down',\n",
-       " 'err2_down',\n",
-       " 'err2_up',\n",
-       " 'is_mcstat',\n",
-       " 'name',\n",
-       " 'nominal',\n",
-       " 'nsyst',\n",
-       " 'plot',\n",
-       " 'ratio_down',\n",
-       " 'ratio_up',\n",
-       " 'style',\n",
-       " 'syst_list',\n",
-       " 'up',\n",
-       " 'xbinwidth',\n",
-       " 'xcenters',\n",
-       " 'xedges',\n",
-       " 'xlabel']"
-      ]
-     },
-     "execution_count": 28,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "syst_tot = syst_manager.total\n",
     "dir(syst_tot)"
@@ -833,76 +502,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": null,
    "id": "94d67dde-bb55-4df8-b166-648330d54212",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['JER',\n",
-       " 'JES_Total',\n",
-       " 'pileup',\n",
-       " 'sf_btag_cferr1',\n",
-       " 'sf_btag_cferr2',\n",
-       " 'sf_btag_hf',\n",
-       " 'sf_btag_hfstats1',\n",
-       " 'sf_btag_hfstats2',\n",
-       " 'sf_btag_lf',\n",
-       " 'sf_btag_lfstats1',\n",
-       " 'sf_btag_lfstats2',\n",
-       " 'sf_ele_id',\n",
-       " 'sf_ele_reco',\n",
-       " 'sf_ele_trigger_era',\n",
-       " 'sf_ele_trigger_ht',\n",
-       " 'sf_ele_trigger_pileup',\n",
-       " 'sf_ele_trigger_stat',\n",
-       " 'sf_jet_puId',\n",
-       " 'sf_mu_id',\n",
-       " 'sf_mu_iso',\n",
-       " 'sf_mu_trigger',\n",
-       " 'mcstat']"
-      ]
-     },
-     "execution_count": 29,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "[s.name for s in syst_tot.syst_list]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": null,
    "id": "36cfc805-5d95-4546-862d-bfe8287bb492",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(<bound method Artist.get_figure of <AxesSubplot: xlabel='$p_{T}^{e}$ [GeV]', ylabel='Counts'>>,\n",
-       " <AxesSubplot: xlabel='$p_{T}^{e}$ [GeV]', ylabel='Counts'>)"
-      ]
-     },
-     "execution_count": 30,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 1200x900 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "syst_list_btag = [s for s in syst_tot.syst_list if s.name.startswith(\"sf_btag\")]\n",
     "syst_btag = SystUnc(name=\"btag\", syst_list=syst_list_btag)\n",
@@ -912,35 +527,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": null,
    "id": "a3874d45-10d5-43bf-aa82-7479b48a9e71",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 2.38378415e+05,\n",
-       "       2.37628049e+05, 2.00992189e+05, 1.63296976e+05, 1.27664658e+05,\n",
-       "       9.98019590e+04, 7.59419451e+04, 6.01856752e+04, 4.62802357e+04,\n",
-       "       3.56882614e+04, 2.77513957e+04, 2.16801587e+04, 1.69295329e+04,\n",
-       "       1.32757362e+04, 1.04277639e+04, 8.31632294e+03, 6.68277165e+03,\n",
-       "       5.37253263e+03, 4.34722996e+03, 3.51209968e+03, 2.86437024e+03,\n",
-       "       2.33327176e+03, 1.90469949e+03, 1.57580711e+03, 1.28901482e+03,\n",
-       "       1.06841478e+03, 9.08351392e+02, 7.71220244e+02, 6.33041587e+02,\n",
-       "       5.17515526e+02, 4.61499958e+02, 3.83540757e+02, 3.19845397e+02,\n",
-       "       2.83522777e+02, 2.39171695e+02, 2.12657796e+02, 1.80037133e+02,\n",
-       "       1.53940332e+02, 1.34781246e+02, 1.20977158e+02, 1.05021016e+02,\n",
-       "       8.65065829e+01, 7.81180913e+01, 6.60693264e+01, 6.33138114e+01,\n",
-       "       5.62289338e+01, 4.97717261e+01])"
-      ]
-     },
-     "execution_count": 31,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "syst_manager.total.up"
    ]
-- 
GitLab


From 69dc465acf5b18f913f0a3f8d64244add5b63032 Mon Sep 17 00:00:00 2001
From: mmarchegiani <matmarcheg@gmail.com>
Date: Thu, 30 Mar 2023 08:51:33 +0200
Subject: [PATCH 24/24] Notebook to study samples map

---
 notebooks/plotting/test_samples_map.ipynb | 256 ++++++++++++++++++++++
 1 file changed, 256 insertions(+)
 create mode 100644 notebooks/plotting/test_samples_map.ipynb

diff --git a/notebooks/plotting/test_samples_map.ipynb b/notebooks/plotting/test_samples_map.ipynb
new file mode 100644
index 00000000..a1f60b4e
--- /dev/null
+++ b/notebooks/plotting/test_samples_map.ipynb
@@ -0,0 +1,256 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "f5850c4d-67aa-4432-95ae-7cf076f62ef3",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "from coffea.util import load\n",
+    "from pocket_coffea.utils.plot_utils import Shape\n",
+    "from pocket_coffea.parameters.plotting import style_cfg"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "67a77d56-73f1-497c-849c-fce02e1f96d9",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "dict_keys(['ttHTobb', 'TTToSemiLeptonic', 'DATA_SingleEle', 'DATA_SingleMuon', 'WJetsToLNu_HT', 'SingleTop', 'TTTo2L2Nu'])"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "filename = \"/work/mmarcheg/PocketCoffea/output/datamc/ttHbb_ttbar_ST_WJets_datamc_2018_MuonIsoTight_bugfix/output_all.coffea\"\n",
+    "o = load(filename)\n",
+    "histname = \"ElectronGood_pt_1\"\n",
+    "h_dict = o[\"variables\"][histname]\n",
+    "h_dict.keys()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5b9ed326-e783-42e5-b474-be114cb90baf",
+   "metadata": {},
+   "source": [
+    "## Modify the default style config\n",
+    "As a test, we can modify the entries of the style config dictionary in order to:\n",
+    "\n",
+    "- have unstacked plots for MC with a `step` style.\n",
+    "- group the `TTToSemiLeptonic` and `TTTo2L2Nu` in a single sample `ttbar`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "1052f76a-9b55-4194-96f1-d423be7ddd79",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'histtype': 'fill', 'stack': True}"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "style_cfg[\"opts_mc\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "f12d7d6a-0b82-40b8-8e5b-2e73ba58a1d0",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'histtype': 'step', 'stack': False}\n",
+      "{'ttbar': ['TTToSemiLeptonic', 'TTTo2L2Nu']}\n"
+     ]
+    }
+   ],
+   "source": [
+    "style_cfg[\"opts_mc\"][\"histtype\"] = \"step\"\n",
+    "style_cfg[\"opts_mc\"][\"stack\"] = False\n",
+    "style_cfg[\"samples_map\"] = {\"ttbar\" : [\"TTToSemiLeptonic\", \"TTTo2L2Nu\"]}\n",
+    "print(style_cfg[\"opts_mc\"])\n",
+    "print(style_cfg[\"samples_map\"])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5992560f-01b8-4694-a088-ded6950d33ce",
+   "metadata": {},
+   "source": [
+    "## Define Shape object"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "d3ef1a3b-532d-4d2c-a5db-3304e7476381",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<pocket_coffea.utils.plot_utils.Shape at 0x7fe8c9b3f610>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "shape = Shape(h_dict, histname, plot_dir='plots/', style_cfg=style_cfg, density=True)\n",
+    "shape"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "95ef4c9f-5b39-44ca-b898-fb484f4e8616",
+   "metadata": {},
+   "source": [
+    "## Samples after regrouping\n",
+    "The regrouping of the samples is done internally in the Shape object by reading the dictionary `samples_map` in the style config."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "f4eb5461-92d3-43cb-8b75-75a9984f7054",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "dict_keys(['ttbar', 'ttHTobb', 'DATA_SingleEle', 'DATA_SingleMuon', 'WJetsToLNu_HT', 'SingleTop'])"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "shape.h_dict.keys()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "b083b293-ce50-4a9c-9ad7-aedad05020f1",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['ttbar', 'ttHTobb', 'WJetsToLNu_HT', 'SingleTop']"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "shape.samples_mc"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "67444510-60e3-4652-b0c9-efea3d33e238",
+   "metadata": {},
+   "source": [
+    "## Density plot"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "4b3a1212-c6fd-41bc-a0b5-47062e26bded",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1200x900 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "year = \"2018\"\n",
+    "shape.build_stacks(year, 'SingleEle_1b')\n",
+    "shape.plot_data(year)\n",
+    "shape.plot_mc()\n",
+    "plt.show()\n",
+    "plt.close()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "978aed30-052c-4bfe-844e-cbb572338b54",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.15"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
-- 
GitLab