mvpa2.clfs.stats.plot_distribution_matches(data, matches, nbins=31, nbest=5, expand_tails=8, legend=2, plot_cdf=True, p=None, tail='both')

Plot best matching distributions


data : np.ndarray

Data which was used to obtain the matches

matches : list of tuples

Sorted matches as provided by match_distribution

nbins : int

Number of bins in the histogram

nbest : int

Number of top matches to plot

expand_tails : int

How many bins away to add to parametrized distributions plots

legend : int

Either to provide legend and statistics in the legend. 1 – just lists distributions. 2 – adds distance measure 3 – tp/fp/fn in the case if p is provided

plot_cdf : bool

Either to plot cdf for data using non-parametric distribution

p : float or None

If not None, visualize null-hypothesis testing (given p). Bars in the histogram which fall under given p are colored in red. False positives and false negatives are marked as triangle up and down symbols correspondingly

tail : (‘left’, ‘right’, ‘any’, ‘both’)

If p is not None, the choise of tail for null-hypothesis testing



list of lines