openpathsampling.numerics.Histogram

class openpathsampling.numerics.Histogram(n_bins=None, bin_width=None, bin_range=None)[source]

Wrapper for numpy.histogram with additional conveniences.

In addition to the behavior in numpy.histogram, this provides a few additional calculations, as well as behavior that allows for better interactive use (tricks to assist caching by libraries using it, etc.)

__init__(n_bins=None, bin_width=None, bin_range=None)[source]

Creates the parameters for the histogram.

Either n_bins or bin_width must be given. If bin_width is used, then bin_range is required. If n_bins is used, then bin_range is optional. n_bins overrides bin_width.

If no options are given, the default is to use 20 bins and the range generated by np.histogram.

Methods

__init__([n_bins, bin_width, bin_range])

Creates the parameters for the histogram.

add_data_to_histogram(data[, weights])

Adds data to the internal histogram counter.

compare_parameters(other)

Return true if other has the same bin parameters as self.

cumulative([maximum, bin_edge])

Cumulative from the left: number of values less than bin value.

empty_copy()

Returns a new histogram with the same bin shape, but empty

histogram([data, weights])

Build the histogram based on data.

map_to_bins(data)

param data

input data

map_to_float_bins(trajectory)

normalized([raw_probability, bin_edge])

Return normalized version of histogram.

plot_bins([scaling])

Bins used in plotting.

rebinned(scaling)

Redistributes histogram bins of width binwidth*scaling

reverse_cumulative([maximum, bin_edge])

Cumulative from the right: number of values greater than bin value.

sum_histograms(hists)

xvals([bin_edge_type])

Position values for the bin