Add hist styling draft

nnfwtbn/plot.py

@@ -46,9 +46,9 @@ def _type_to_histtype(type):
     type_map = {"fill": "stepfilled", "line": "step"} 
     return type_map[type]
 
-def hist(dataframe, variable, bins, *stacks, data=None, selection=None,
-         range=None, color=None, blind=None, axes=None, figure=None,
-         weight=None):
+def hist(dataframe, variable, bins, *stacks, selection=None,
+         range=None, blind=None, axes=None, figure=None,
+         weight=None, **kwds):
     """
     Creates a histogram of stacked processes. The first argument is the
     dataframe to operate on. The 'variable' argument defines the x-axis. The
@@ -65,15 +65,9 @@ def hist(dataframe, variable, bins, *stacks, data=None, selection=None,
     in a list are stacked. The type attributes of processes are considered
     during plotting.
 
-    The optional color must have the with same structure as the stacked list
-    and defines the color of the process. For a list of stacked processes, the
-    corresponding list of colors can be replaced by a callable which is used
-    repeatedly for each process in the stack. The colors must be valid
-    matplotlib colors.
-
     The optional blind argument controls which process should be blinded. The
-    argument can be a list of processes to blind. By default blinding is
-    applied to data. Use an empty list to disable blinding.
+    argument can be a single process, a list of processes or None. By default,
+    no process is blinded.
 
     If the figure argument is omitted, this method creates a new axes and
     figure. If axes only is omitted, the method creates a new axes from the
@@ -85,6 +79,15 @@ def hist(dataframe, variable, bins, *stacks, data=None, selection=None,
     The weight is used to weight the entries. Entries have unit
     weight if omitted. The argument can be a string name of a column or a
     variable object.
+
+    Any other keyword argument is used to define the style. If the keyword
+    argument is a list, it's length must equal the number of stacks. If the
+    list item is a list, it is cycled for every stack member. If the list
+    member is not a list, this value is used for all members of the stack.
+    If the keyword is not a list,  the property is passed directly to
+    matplotlib. The only exception is 'histtype'. The histtype argument can be
+    'step', 'stepfilled' or 'points'. In the former two cases matplotlibs hist
+    method ist used, in the latter case 'errorbar' is used.
     """
     # Wrap column string by variable
     if isinstance(variable, str):
@@ -119,22 +122,45 @@ def hist(dataframe, variable, bins, *stacks, data=None, selection=None,
         bins = np.linspace(range[0], range[1], bins + 1)
         equidistant_bins = True
 
+    # Check structure of kwds
+    new_kwds = {}
+    for kwd, value in kwds.items():
+        if isinstance(value, list):
+            if len(value) != len(stacks):
+                raise ValueError("Length of %s must equal number of stacks."
+                                 % repr(kwd))
+
+            # Wrap properties for the whole stack in a list
+            new_kwds[kwd] = [(_ if isinstance(_, list) else [_]) for _ in value] 
+
+        else:
+            # Single value for all stacks and all processes
+            new_kwds[kwd] = [[value]]*len(stacks)
+    kwds = new_kwds
+
     # Handle stack
-    for stack in stacks:
+    for i_stack, stack in enumerate(stacks):
         if isinstance(stack, Process):
             # Wrap single process
             stack = [stack]
 
         bottom = np.zeros(len(bins) - 1)
-        for process in stack:
+        for i_process, process in enumerate(stack):
             sel = selection & process.selection
 
+            # Prepare style
+            process_kwds = {}
+            for kwd, props in kwds.items():
+                # Cycle through property stacks
+                stack_props = props[i_stack]
+                process_kwds[kwd] = stack_props[i_process % len(stack_props)]
+
             n, _, _ = axes.hist(variable(dataframe[sel(dataframe)]),
                                 bins=bins, range=range,
                                 bottom=bottom,
                                 label=process.label,
-                                histtype=_type_to_histtype(process.type),
-                                weights=weight(dataframe[sel(dataframe)]))
+                                weights=weight(dataframe[sel(dataframe)]),
+                                **process_kwds)
             bottom += n 
 
     axes.set_xlim((bins.min(), bins.max()))