diff --git a/dhi/plots/likelihoods.py b/dhi/plots/likelihoods.py
index 28ebf6dc356da83f566c9b63aa98f37142f1eeab..b06db3acdffa2e024bd6f41397929cb3b66f1edf 100644
--- a/dhi/plots/likelihoods.py
+++ b/dhi/plots/likelihoods.py
@@ -1194,13 +1194,15 @@ def plot_likelihood_scans_2d(
for i, d in enumerate(data):
# join values for contour calculation
smoothContour_temp = smoothContour[0] if len(smoothContour) == 1 else smoothContour[i]
- print(smoothContour_temp, "!!!!!", d["name"])
+ if smoothContour_temp == None :
+ smoothContour_temp = ('None',)
+ print(smoothContour_temp, "!!!!!", d["name"], smoothContour, len(smoothContour))
contours.append(
get_contours(
d["values"][poi1],
d["values"][poi2],
d["values"]["dnll2"],
- levels=[chi2_levels[2][1], chi2_levels[2][2]],
+ levels=[chi2_levels[2][1], chi2_levels[2][2], chi2_levels[2][3], chi2_levels[2][4], chi2_levels[2][5]],
frame_kwargs=[{"mode": "edge"}],
interpolation=interpolation_method,
smooth=smoothContour_temp,
@@ -1242,7 +1244,7 @@ def plot_likelihood_scans_2d(
_color_sequence = [br_hh_colors.root[d["name"]] for d in data]
# loop through data entries
- for d, (cont1, cont2), col in zip(data, contours, _color_sequence[:len(data)]):
+ for d, (cont1, cont2, cont3, cont4, cont5), col in zip(data, contours, _color_sequence[:len(data)]):
# evaluate the scan
scan = evaluate_likelihood_scan_2d(
d["values"][poi1],
@@ -1255,7 +1257,7 @@ def plot_likelihood_scans_2d(
warn("2D likelihood evaluation failed for entry '{}'".format(d["name"]))
# plot selected contours
- g1, g2 = None, None
+ g1, g2, g3, g5 = None, None, None, None
for g1 in cont1:
r.setup_graph(g1, props={"LineWidth": 2, "LineStyle": 1, "LineColor": colors[col]})
if 1 in show_significances:
@@ -1266,6 +1268,18 @@ def plot_likelihood_scans_2d(
r.setup_graph(g2, props={"LineWidth": 2, "LineStyle": 1, "LineColor": colors[col]})
if 2 in show_significances:
draw_objs.append((g2, "SAME,L"))
+ for g3 in cont3:
+ r.setup_graph(g3, props={"LineWidth": 2, "LineStyle": 3, "LineColor": colors[col]})
+ if 3 in show_significances:
+ draw_objs.append((g3, "SAME,L"))
+ for g4 in cont4:
+ r.setup_graph(g4, props={"LineWidth": 2, "LineStyle": 3, "LineColor": colors[col]})
+ if 4 in show_significances:
+ draw_objs.append((g4, "SAME,L"))
+ for g5 in cont5:
+ r.setup_graph(g5, props={"LineWidth": 2, "LineStyle": 4, "LineColor": colors[col]})
+ if 5 in show_significances:
+ draw_objs.append((g5, "SAME,L"))
name = expand_hh_channel_label(d["name"])
if g1:
legend_entries.append((g1, name, "L"))
@@ -1294,6 +1308,24 @@ def plot_likelihood_scans_2d(
legend_entries.append((g2_style, "#pm 2 #sigma", "L"))
else:
warn("no secondary contour found, no line will be visible")
+ if g4 and 4 in show_significances:
+ g4_style = g4.Clone()
+ r.apply_properties(g4_style, {"LineColor": colors.black})
+ legend_entries.append((g4_style, "#pm 3 #sigma", "L"))
+ else:
+ warn("no 4 contour found, no line will be visible")
+ if g3 and 3 in show_significances:
+ g3_style = g3.Clone()
+ r.apply_properties(g3_style, {"LineColor": colors.black})
+ legend_entries.append((g3_style, "#pm 3 #sigma", "L"))
+ else:
+ warn("no 3 contour found, no line will be visible")
+ if g5 and 5 in show_significances:
+ g5_style = g5.Clone()
+ r.apply_properties(g5_style, {"LineColor": colors.black})
+ legend_entries.append((g5_style, "#pm 5 #sigma", "L"))
+ else:
+ warn("no 5 contour found, no line will be visible")
# campaign label
if campaign:
diff --git a/dhi/tasks/limits.py b/dhi/tasks/limits.py
index e26b9e59f25e05bdd6439e09288c5d68482e8a47..7297625a63a670d55c7bc4126978cf6fdf083793 100644
--- a/dhi/tasks/limits.py
+++ b/dhi/tasks/limits.py
@@ -10,6 +10,8 @@ import re
import law
import luigi
+import hashlib
+
from dhi.tasks.base import BoxPlotTask, ModelParameters, view_output_plots
from dhi.tasks.remote import HTCondorWorkflow
from dhi.tasks.combine import (
@@ -352,6 +354,34 @@ class MergeUpperLimitsGrid(UpperLimitsScanBase):
name = self.join_postfix(["limitgrid", self.get_output_postfix()]) + ".root"
return self.target(name)
+ # generate unique id for intermediate outputs
+ def generate_unique_id_from_inputs(self, inputs):
+ hasher = hashlib.md5()
+ for inp in inputs:
+ hasher.update(inp.path.encode("utf-8"))
+ return hasher.hexdigest()[:8]
+
+ # merge 100 files to the intermediate outputs
+ def batch_hadd(self, inputs, output, batch_size=100):
+ intermediate_outputs = []
+
+ unique_id = self.generate_unique_id_from_inputs(inputs)
+
+ for i in range(0, len(inputs), batch_size):
+ batch = inputs[i:i + batch_size]
+ intermediate_output_path = os.path.join(output.parent.path, f"intermediate_{unique_id}_{i}.root")
+ intermediate_output = law.LocalFileTarget(intermediate_output_path)
+
+ intermediate_dir = intermediate_output.parent
+ if not intermediate_dir.exists():
+ intermediate_dir.touch()
+
+ intermediate_outputs.append(intermediate_output)
+
+ law.root.hadd_task(self, batch, intermediate_output, local=True)
+
+ law.root.hadd_task(self, intermediate_outputs, output, local=True)
+
@law.decorator.log
@law.decorator.safe_output
def run(self):
@@ -374,8 +404,14 @@ class MergeUpperLimitsGrid(UpperLimitsScanBase):
input_paths.append(target.path)
inputs.append(target)
- # hadd using a helper
- law.root.hadd_task(self, inputs, output, local=True)
+ # hadd using batch for files > 100
+# law.root.hadd_task(self, inputs, output, local=True)
+ if len(inputs) > 100:
+ self.logger.info(f"More than 100 input files ({len(inputs)}), using batch processing.")
+ self.batch_hadd(inputs, output, batch_size=100)
+ else:
+ self.logger.info(f"Less than or equal to 100 input files ({len(inputs)}), merging directly.")
+ law.root.hadd_task(self, inputs, output, local=True)
class PlotUpperLimits(UpperLimitsScanBase, POIPlotTask):