Distribution Class Reference

Inheritance diagram for Distribution:

Collaboration diagram for Distribution:

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

Public Attributes
	normed_to_all_entries
	Normalize histograms before drawing them.
	normed_to_bin_width
	Normalize histograms before drawing them.
	range_in_std
	Show only a certain range in terms of standard deviations of the data.
	ymin
	size in x/y
	ymax
	size in x/y
	xmin
	size in x/y
	xmax
	size in x/y
	keep_first_binning
	Keep first binning if user wants so.
	first_binning
	first binning
	x_axis_label
	x axis label

Detailed Description

Plots distribution of a quantity

Definition at line 585 of file plotting.py.

Constructor & Destructor Documentation

__init__()

def __init__	(		self,
			figure = None,
			axis = None,
			normed_to_all_entries = False,
			normed_to_bin_width = False,
			keep_first_binning = 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 histograms should be normed before drawing
@param keep_first_binning use the binning of the first distribution for further plots
@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 590 of file plotting.py.

                 keep_first_binning=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 histograms should be normed before drawing
        @param keep_first_binning use the binning of the first distribution for further plots
        @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_to_all_entries = normed_to_all_entries
        
        self.normed_to_bin_width = normed_to_bin_width
        
        self.range_in_std = range_in_std
        # if self.normed_to_all_entries or self.normed_to_bin_width:
        
        self.ymin = float(0)
        
        self.ymax = float('-inf')
        
        self.xmin = float('inf')
        
        self.xmax = float('-inf')
        
        self.keep_first_binning = keep_first_binning
        
        self.first_binning = None
        
        self.x_axis_label = ''
 

Member Function Documentation

add()

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

Add a new distribution to the plots
@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 histogram
@param weight_column column in data containing the weights for each event

Reimplemented from Plotter.

Definition at line 623 of file plotting.py.

    def add(self, data, column, mask=None, weight_column=None, label=None):
        """
        Add a new distribution to the plots
        @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 histogram
        @param weight_column column in data containing the weights for each event
        """
        if mask is None:
            mask = numpy.ones(len(data)).astype('bool')
 
        bins = 100
        if self.keep_first_binning and self.first_binning is not None:
            bins = self.first_binning
        hists = histogram.Histograms(data, column, {'Total': mask}, weight_column=weight_column,
                                     bins=bins, equal_frequency=False, range_in_std=self.range_in_std)
        if self.keep_first_binning and self.first_binning is None:
            self.first_binning = hists.bins
        hist, hist_error = hists.get_hist('Total')
 
        if self.normed_to_all_entries:
            normalization = float(numpy.sum(hist))
            hist = hist / normalization
            hist_error = hist_error / normalization
 
        if self.normed_to_bin_width:
            hist = hist / hists.bin_widths
            hist_error = hist_error / hists.bin_widths
 
        self.xmin, self.xmax = min(hists.bin_centers.min(), self.xmin), max(hists.bin_centers.max(), self.xmax)
        self.ymin = numpy.nanmin([hist.min(), self.ymin])
        self.ymax = numpy.nanmax([(hist + hist_error).max(), self.ymax])
 
        p = self._plot_datapoints(self.axis, hists.bin_centers, hist, xerr=hists.bin_widths / 2, yerr=hist_error)
        self.plots.append(p)
        self.x_axis_label = column
 
        appendix = ''
        if self.ymax <= self.ymin or self.xmax <= self.xmin:
            appendix = ' No data to plot!'
 
        if label is None:
            self.labels.append(column + appendix)
        else:
            self.labels.append(label + appendix)
        return self
 

finish()

def finish

(

self

)

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

Reimplemented from Plotter.

Definition at line 670 of file plotting.py.

    def finish(self):
        """
        Sets limits, title, axis-labels and legend of the plot
        """
        self.axis.set_title("Distribution Plot")
        self.axis.get_xaxis().set_label_text(self.x_axis_label)
 
        self.axis.legend([x[0] for x in self.plots], self.labels, loc='best', fancybox=True, framealpha=0.5)
 
        if self.ymax <= self.ymin or self.xmax <= self.xmin:
            self.axis.set_xlim((0., 1.))
            self.axis.set_ylim((0., 1.))
            self.axis.text(0.36, 0.5, 'No data to plot', fontsize=60, color='black')
            return self
 
        self.scale_limits()
 
        self.axis.set_xlim((self.xmin, self.xmax))
        self.axis.set_ylim((self.ymin, self.ymax))
 
        if self.normed_to_all_entries and self.normed_to_bin_width:
            self.axis.get_yaxis().set_label_text('# Entries per Bin / (# Entries * Bin Width)')
        elif self.normed_to_all_entries:
            self.axis.get_yaxis().set_label_text('# Entries per Bin / # Entries')
        elif self.normed_to_bin_width:
            self.axis.get_yaxis().set_label_text('# Entries per Bin / Bin Width')
        else:
            self.axis.get_yaxis().set_label_text('# Entries per Bin')
 
        return self
 
 

Member Data Documentation

first_binning

first_binning

first binning

Definition at line 619 of file plotting.py.

keep_first_binning

keep_first_binning

Keep first binning if user wants so.

Definition at line 617 of file plotting.py.

normed_to_all_entries

normed_to_all_entries

Normalize histograms before drawing them.

Definition at line 602 of file plotting.py.

normed_to_bin_width

normed_to_bin_width

Normalize histograms before drawing them.

Definition at line 604 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 606 of file plotting.py.

x_axis_label

x_axis_label

x axis label

Definition at line 621 of file plotting.py.

xmax

xmax

size in x/y

Definition at line 615 of file plotting.py.

xmin

xmin

size in x/y

Definition at line 613 of file plotting.py.

ymax

ymax

size in x/y

Definition at line 611 of file plotting.py.

ymin

ymin

size in x/y

Definition at line 609 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