VerboseDistribution Class Reference

Inheritance diagram for VerboseDistribution:

Public Member Functions
def	__init__ (self, figure=None, axis=None, normed=False, range_in_std=None)
def	add (self, data, column, mask=None, weight_column=None, label=None)
def	finish (self)

Public Attributes
	normed
	Normalize histograms before drawing them.
	range_in_std
	Show only a certain range in terms of standard deviations of the data.
	box_axes
	create empty list for box axes
	distribution
	The distribution plot.

Static Public Attributes
None	box_axes = None
	Axes for the boxplots.

Detailed Description

Plots distribution of a quantity including boxplots

Definition at line 989 of file plotting.py.

Constructor & Destructor Documentation

__init__()

def __init__	(		self,
			figure = None,
			axis = None,
			normed = False,
			range_in_std = None
	)

Creates a new figure and axis if None is given, sets the default plot parameters
@param figure default draw figure which is used
@param axis default draw axis which is used
@param normed true if the histograms should be normed before drawing
@param range_in_std show only the data in a windows around +- range_in_std * standard_deviation around the mean

Reimplemented from Plotter.

Definition at line 997 of file plotting.py.

    def __init__(self, figure=None, axis=None, normed=False, range_in_std=None):
        """
        Creates a new figure and axis if None is given, sets the default plot parameters
        @param figure default draw figure which is used
        @param axis default draw axis which is used
        @param normed true if the histograms should be normed before drawing
        @param range_in_std show only the data in a windows around +- range_in_std * standard_deviation around the mean
        """
        super().__init__(figure, axis)
        
        self.normed = normed
        
        self.range_in_std = range_in_std
        
        self.box_axes = []
        
        self.distribution = Distribution(self.figure, self.axis, normed_to_all_entries=self.normed, range_in_std=self.range_in_std)
 

Member Function Documentation

add()

def add	(		self,
			data,
			column,
			mask = None,
			weight_column = None,
			label = None
	)

Add a new distribution plot, with additional information like a boxplot compared to
the ordinary Distribution plot.
@param data pandas.DataFrame containing all data
@param column which is used to calculate distribution histogram
@param mask boolean numpy.array defining which events are used for the distribution histogram
@param weight_column column in data containing the weights for each event

Reimplemented from Plotter.

Definition at line 1015 of file plotting.py.

    def add(self, data, column, mask=None, weight_column=None, label=None):
        """
        Add a new distribution plot, with additional information like a boxplot compared to
        the ordinary Distribution plot.
        @param data pandas.DataFrame containing all data
        @param column which is used to calculate distribution histogram
        @param mask boolean numpy.array defining which events are used for the distribution histogram
        @param weight_column column in data containing the weights for each event
        """
        self.distribution.set_plot_options(self.plot_kwargs)
        self.distribution.set_errorbar_options(self.errorbar_kwargs)
        self.distribution.set_errorband_options(self.errorband_kwargs)
        self.distribution.add(data, column, mask, weight_column, label=label)
 
        n = len(self.box_axes) + 1
        gs = matplotlib.gridspec.GridSpec(4 * n, 1)
        gridspecs = [gs[:3 * n, :]] + [gs[3 * n + i, :] for i in range(n)]
        box_axis = self.add_subplot(gridspecs)
 
        if self.range_in_std is not None:
            mean, std = histogram.weighted_mean_and_std(data[column], None if weight_column is None else data[weight_column])
            # Everything outside mean +- range_in_std * std is considered not inside the mask
            mask = mask & (data[column] > (mean - self.range_in_std * std)) & (data[column] < (mean + self.range_in_std * std))
        box = Box(self.figure, box_axis)
        box.add(data, column, mask, weight_column)
        if len(box.plots) > 0:
            box.plots[0]['boxes'][0].set_facecolor(self.distribution.plots[-1][0][0].get_color())
        box.finish()
 
        self.box_axes.append(box_axis)
        return self
 

finish()

def finish

(

self

)

Sets limits, title, axis-labels and legend of the plot

Reimplemented from Plotter.

Definition at line 1047 of file plotting.py.

    def finish(self):
        """
        Sets limits, title, axis-labels and legend of the plot
        """
        self.distribution.finish()
        matplotlib.artist.setp(self.axis.get_xticklabels(), visible=False)
        self.axis.get_xaxis().set_label_text('')
        for box_axis in self.box_axes[:-1]:
            matplotlib.artist.setp(box_axis.get_xticklabels(), visible=False)
            box_axis.set_title("")
            box_axis.get_xaxis().set_label_text('')
        self.box_axes[-1].set_title("")
        self.axis.set_title("Distribution Plot")
        self.axis.legend([x[0] for x in self.distribution.plots], self.distribution.labels,
                         loc='best', fancybox=True, framealpha=0.5)
        return self
 
 

Member Data Documentation

box_axes [1/2]

None box_axes = None

static

Axes for the boxplots.

Definition at line 995 of file plotting.py.

box_axes [2/2]

box_axes

create empty list for box axes

Definition at line 1011 of file plotting.py.

distribution

distribution

The distribution plot.

Definition at line 1013 of file plotting.py.

normed

normed

Normalize histograms before drawing them.

Definition at line 1007 of file plotting.py.

range_in_std

range_in_std

Show only a certain range in terms of standard deviations of the data.

Definition at line 1009 of file plotting.py.

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The documentation for this class was generated from the following file:

• mva/scripts/basf2_mva_evaluation/plotting.py