7965

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Build # 7965

Build Type

Pull #3086

travis-ci

Committed by

web-flow

Commit Message

Merge branch 'master' into release_3.4.2

Pull Request Pull Request #3086: Release 3.5

Run Details

1 of 1 new or added line in 1 file covered. (100.0%)

17647 of 19785 relevant lines covered (89.19%)

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64.94

/pymc3/plots/pairplot.py

import warnings

try:
    import matplotlib.pyplot as plt
    from matplotlib import gridspec
except ImportError:  # mpl is optional
    pass
from ..util import get_default_varnames, is_transformed_name, get_untransformed_name
from .artists import get_trace_dict, scale_text


def pairplot(trace, varnames=None, figsize=None, text_size=None,
             gs=None, ax=None, hexbin=False, plot_transformed=False,
             divergences=False, kwargs_divergence=None,
             sub_varnames=None, **kwargs):
    """
    Plot a scatter or hexbin matrix of the sampled parameters.

    Parameters
    ----------

    trace : result of MCMC run
    varnames : list of variable names
        Variables to be plotted, if None all variable are plotted
    figsize : figure size tuple
        If None, size is (8 + numvars, 8 + numvars)
    text_size: int
        Text size for labels
    gs : Grid spec
        Matplotlib Grid spec.
    ax: axes
        Matplotlib axes
    hexbin : Boolean
        If True draws an hexbin plot
    plot_transformed : bool
        Flag for plotting automatically transformed variables in addition to
        original variables (defaults to False). Applies when varnames = None.
        When a list of varnames is passed, transformed variables can be passed
        using their names.
    divergences : Boolean
        If True divergences will be plotted in a diferent color
    kwargs_divergence : dicts, optional
        Aditional keywords passed to ax.scatter for divergences
    sub_varnames : list
        Aditional varnames passed for plotting subsets of multidimensional
        variables
    Returns
    -------

    ax : matplotlib axes
    gs : matplotlib gridspec

    """
    if varnames is None:
        if plot_transformed:

            varnames_copy = list(trace.varnames)
            remove = [get_untransformed_name(var) for var in trace.varnames
                      if is_transformed_name(var)]

            try:
                [varnames_copy.remove(i) for i in remove]
                varnames = varnames_copy
            except ValueError:
                varnames = varnames_copy

            trace_dict = get_trace_dict(
                trace, get_default_varnames(
                    varnames, plot_transformed))

        else:
            trace_dict = get_trace_dict(
                trace, get_default_varnames(
                    trace.varnames, plot_transformed))

        if sub_varnames is None:
            varnames = list(trace_dict.keys())

        else:
            trace_dict = get_trace_dict(
                trace, get_default_varnames(
                    trace.varnames, True))
            varnames = sub_varnames

    else:
        trace_dict = get_trace_dict(trace, varnames)
        varnames = list(trace_dict.keys())

    if text_size is None:
        text_size = scale_text(figsize, text_size=text_size)

    if kwargs_divergence is None:
        kwargs_divergence = {}

    numvars = len(varnames)

    if figsize is None:
        figsize = (8 + numvars, 8 + numvars)

    if numvars < 2:
        raise Exception(
            'Number of variables to be plotted must be 2 or greater.')

    if numvars == 2 and ax is not None:
        if hexbin:
            ax.hexbin(trace_dict[varnames[0]],
                      trace_dict[varnames[1]], mincnt=1, **kwargs)
        else:
            ax.scatter(trace_dict[varnames[0]],
                       trace_dict[varnames[1]], **kwargs)

        if divergences:
            try:
                divergent = trace['diverging']
            except KeyError:
                warnings.warn('No divergences were found.')

            diverge = (divergent == 1)
            ax.scatter(trace_dict[varnames[0]][diverge],
                       trace_dict[varnames[1]][diverge], **kwargs_divergence)
        ax.set_xlabel('{}'.format(varnames[0]),
                      fontsize=text_size)
        ax.set_ylabel('{}'.format(
            varnames[1]), fontsize=text_size)
        ax.tick_params(labelsize=text_size)

    if gs is None and ax is None:
        plt.figure(figsize=figsize)
        gs = gridspec.GridSpec(numvars - 1, numvars - 1)

        for i in range(0, numvars - 1):
            var1 = trace_dict[varnames[i]]

            for j in range(i, numvars - 1):
                var2 = trace_dict[varnames[j + 1]]

                ax = plt.subplot(gs[j, i])

                if hexbin:
                    ax.hexbin(var1, var2, mincnt=1, **kwargs)
                else:
                    ax.scatter(var1, var2, **kwargs)

                if divergences:
                    try:
                        divergent = trace['diverging']
                    except KeyError:
                        warnings.warn('No divergences were found.')
                        return ax

                    diverge = (divergent == 1)
                    ax.scatter(var1[diverge],
                               var2[diverge],
                               **kwargs_divergence)

                if j + 1 != numvars - 1:
                    ax.set_xticks([])
                else:
                    ax.set_xlabel('{}'.format(varnames[i]),
                                  fontsize=text_size)
                if i != 0:
                    ax.set_yticks([])
                else:
                    ax.set_ylabel('{}'.format(
                        varnames[j + 1]), fontsize=text_size)

                ax.tick_params(labelsize=text_size)

    plt.tight_layout()
    return ax, gs

1	import warnings	10✔
2
3	try:	10✔
4	import matplotlib.pyplot as plt	10✔
5	from matplotlib import gridspec	10✔
6	except ImportError: # mpl is optional	×
7	pass	×
8	from ..util import get_default_varnames, is_transformed_name, get_untransformed_name	10✔
9	from .artists import get_trace_dict, scale_text	10✔
10
11
12	def pairplot(trace, varnames=None, figsize=None, text_size=None,	10✔
13	gs=None, ax=None, hexbin=False, plot_transformed=False,
14	divergences=False, kwargs_divergence=None,
15	sub_varnames=None, **kwargs):
16	"""
17	Plot a scatter or hexbin matrix of the sampled parameters.
18
19	Parameters
20	----------
21
22	trace : result of MCMC run
23	varnames : list of variable names
24	Variables to be plotted, if None all variable are plotted
25	figsize : figure size tuple
26	If None, size is (8 + numvars, 8 + numvars)
27	text_size: int
28	Text size for labels
29	gs : Grid spec
30	Matplotlib Grid spec.
31	ax: axes
32	Matplotlib axes
33	hexbin : Boolean
34	If True draws an hexbin plot
35	plot_transformed : bool
36	Flag for plotting automatically transformed variables in addition to
37	original variables (defaults to False). Applies when varnames = None.
38	When a list of varnames is passed, transformed variables can be passed
39	using their names.
40	divergences : Boolean
41	If True divergences will be plotted in a diferent color
42	kwargs_divergence : dicts, optional
43	Aditional keywords passed to ax.scatter for divergences
44	sub_varnames : list
45	Aditional varnames passed for plotting subsets of multidimensional
46	variables
47	Returns
48	-------
49
50	ax : matplotlib axes
51	gs : matplotlib gridspec
52
53	"""
54	if varnames is None:	3✔
55	if plot_transformed:	3✔
56
57	varnames_copy = list(trace.varnames)	3✔
58	remove = [get_untransformed_name(var) for var in trace.varnames	3✔
59	if is_transformed_name(var)]
60
61	try:	3✔
62	[varnames_copy.remove(i) for i in remove]	3✔
63	varnames = varnames_copy	3✔
64	except ValueError:	×
65	varnames = varnames_copy	×
66
67	trace_dict = get_trace_dict(	3✔
68	trace, get_default_varnames(
69	varnames, plot_transformed))
70
71	else:
72	trace_dict = get_trace_dict(	3✔
73	trace, get_default_varnames(
74	trace.varnames, plot_transformed))
75
76	if sub_varnames is None:	3✔
77	varnames = list(trace_dict.keys())	3✔
78
79	else:
80	trace_dict = get_trace_dict(	3✔
81	trace, get_default_varnames(
82	trace.varnames, True))
83	varnames = sub_varnames	3✔
84
85	else:
86	trace_dict = get_trace_dict(trace, varnames)	×
87	varnames = list(trace_dict.keys())	×
88
89	if text_size is None:	3✔
90	text_size = scale_text(figsize, text_size=text_size)	3✔
91
92	if kwargs_divergence is None:	3✔
93	kwargs_divergence = {}	3✔
94
95	numvars = len(varnames)	3✔
96
97	if figsize is None:	3✔
98	figsize = (8 + numvars, 8 + numvars)	3✔
99
100	if numvars < 2:	3✔
101	raise Exception(	×
102	'Number of variables to be plotted must be 2 or greater.')
103
104	if numvars == 2 and ax is not None:	3✔
105	if hexbin:	×
106	ax.hexbin(trace_dict[varnames[0]],	×
107	trace_dict[varnames[1]], mincnt=1, **kwargs)
108	else:
109	ax.scatter(trace_dict[varnames[0]],	×
110	trace_dict[varnames[1]], **kwargs)
111
112	if divergences:	×
113	try:	×
114	divergent = trace['diverging']	×
115	except KeyError:	×
116	warnings.warn('No divergences were found.')	×
117
118	diverge = (divergent == 1)	×
119	ax.scatter(trace_dict[varnames[0]][diverge],	×
120	trace_dict[varnames[1]][diverge], **kwargs_divergence)
121	ax.set_xlabel('{}'.format(varnames[0]),	×
122	fontsize=text_size)
123	ax.set_ylabel('{}'.format(	×
124	varnames[1]), fontsize=text_size)
125	ax.tick_params(labelsize=text_size)	×
126
127	if gs is None and ax is None:	3✔
128	plt.figure(figsize=figsize)	3✔
129	gs = gridspec.GridSpec(numvars - 1, numvars - 1)	3✔
130
131	for i in range(0, numvars - 1):	3✔
132	var1 = trace_dict[varnames[i]]	3✔
133
134	for j in range(i, numvars - 1):	3✔
135	var2 = trace_dict[varnames[j + 1]]	3✔
136
137	ax = plt.subplot(gs[j, i])	3✔
138
139	if hexbin:	3✔
140	ax.hexbin(var1, var2, mincnt=1, **kwargs)	3✔
141	else:
142	ax.scatter(var1, var2, **kwargs)	3✔
143
144	if divergences:	3✔
145	try:	×
146	divergent = trace['diverging']	×
147	except KeyError:	×
148	warnings.warn('No divergences were found.')	×
149	return ax	×
150
151	diverge = (divergent == 1)	×
152	ax.scatter(var1[diverge],	×
153	var2[diverge],
154	**kwargs_divergence)
155
156	if j + 1 != numvars - 1:	3✔
157	ax.set_xticks([])	3✔
158	else:
159	ax.set_xlabel('{}'.format(varnames[i]),	3✔
160	fontsize=text_size)
161	if i != 0:	3✔
162	ax.set_yticks([])	3✔
163	else:
164	ax.set_ylabel('{}'.format(	3✔
165	varnames[j + 1]), fontsize=text_size)
166
167	ax.tick_params(labelsize=text_size)	3✔
168
169	plt.tight_layout()	3✔
170	return ax, gs	3✔

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