8412

Committed 28 Nov 2018 - 15:42 coverage decreased (-0.7%) to 88.7%

Build # 8412

Build Type

Pull #3275

travis-ci

Committed by

web-flow

Commit Message

Fix link to be relative

Pull Request Pull Request #3275: Documentation rewrite

Run Details

17630 of 19876 relevant lines covered (88.7%)

4.43 hits per line

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85.71

/pymc3/plots/energyplot.py

import warnings

import numpy as np
try:
    import matplotlib.pyplot as plt
except ImportError:  # mpl is optional
    pass
from .kdeplot import kdeplot


def energyplot(trace, kind='kde', figsize=None, ax=None, legend=True, shade=0.35, bw=4.5,
               frame=True, kwargs_shade=None, **kwargs):
    """Plot energy transition distribution and marginal energy distribution in
    order to diagnose poor exploration by HMC algorithms.

    Parameters
    ----------

    trace : result of MCMC run
    kind : str
        Type of plot to display (kde or histogram)
    figsize : figure size tuple
        If None, size is (8 x 6)
    ax : axes
        Matplotlib axes.
    legend : bool
        Flag for plotting legend (defaults to True)
    shade : float
        Alpha blending value for the shaded area under the curve, between 0
        (no shade) and 1 (opaque). Defaults to 0.35
    bw : float
        Bandwidth scaling factor for the KDE. Should be larger than 0. The higher this number the
        smoother the KDE will be. Defaults to 4.5 which is essentially the same as the Scott's rule
        of thumb (the default rule used by SciPy). Only works if `kind='kde'`.
    frame : bool
        Flag for plotting frame around figure.
    kwargs_shade : dicts, optional
        Additional keywords passed to `fill_between` (to control the shade)
    Returns
    -------

    ax : matplotlib axes
    """

    if ax is None:
        _, ax = plt.subplots(figsize=figsize)

    try:
        energy = trace['energy']
    except KeyError:
        warnings.warn('There is no energy information in the passed trace.')
        return ax

    series = [('Marginal energy distribution', energy - energy.mean()),
              ('Energy transition distribution', np.diff(energy))]

    if figsize is None:
        figsize = (8, 6)

    if kwargs_shade is None:
        kwargs_shade = {}

    if kind == 'kde':
        for label, value in series:
            kdeplot(value, label=label, shade=shade, bw=bw, ax=ax, kwargs_shade=kwargs_shade,
                    **kwargs)

    elif kind == 'hist':
        for label, value in series:
            ax.hist(value, alpha=shade, label=label, **kwargs)

    else:
        raise ValueError('Plot type {} not recognized.'.format(kind))

    ax.set_xticks([])
    ax.set_yticks([])

    if not frame:
        for spine in ax.spines.values():
            spine.set_visible(False)

    if legend:
        ax.legend()

    return ax

1	import warnings	10×
2
3	import numpy as np	10×
4	try:	10×
5	import matplotlib.pyplot as plt	10×
6	except ImportError: # mpl is optional	!
7	pass	!
8	from .kdeplot import kdeplot	10×
9
10
11	def energyplot(trace, kind='kde', figsize=None, ax=None, legend=True, shade=0.35, bw=4.5,	10×
12	frame=True, kwargs_shade=None, **kwargs):
13	"""Plot energy transition distribution and marginal energy distribution in
14	order to diagnose poor exploration by HMC algorithms.
15
16	Parameters
17	----------
18
19	trace : result of MCMC run
20	kind : str
21	Type of plot to display (kde or histogram)
22	figsize : figure size tuple
23	If None, size is (8 x 6)
24	ax : axes
25	Matplotlib axes.
26	legend : bool
27	Flag for plotting legend (defaults to True)
28	shade : float
29	Alpha blending value for the shaded area under the curve, between 0
30	(no shade) and 1 (opaque). Defaults to 0.35
31	bw : float
32	Bandwidth scaling factor for the KDE. Should be larger than 0. The higher this number the
33	smoother the KDE will be. Defaults to 4.5 which is essentially the same as the Scott's rule
34	of thumb (the default rule used by SciPy). Only works if `kind='kde'`.
35	frame : bool
36	Flag for plotting frame around figure.
37	kwargs_shade : dicts, optional
38	Additional keywords passed to `fill_between` (to control the shade)
39	Returns
40	-------
41
42	ax : matplotlib axes
43	"""
44
UNCOV 45	if ax is None:	3×
UNCOV 46	_, ax = plt.subplots(figsize=figsize)	3×
47
UNCOV 48	try:	3×
UNCOV 49	energy = trace['energy']	3×
UNCOV 50	except KeyError:	3×
UNCOV 51	warnings.warn('There is no energy information in the passed trace.')	3×
UNCOV 52	return ax	3×
53
UNCOV 54	series = [('Marginal energy distribution', energy - energy.mean()),	3×
55	('Energy transition distribution', np.diff(energy))]
56
UNCOV 57	if figsize is None:	3×
UNCOV 58	figsize = (8, 6)	3×
59
UNCOV 60	if kwargs_shade is None:	3×
UNCOV 61	kwargs_shade = {}	3×
62
UNCOV 63	if kind == 'kde':	3×
UNCOV 64	for label, value in series:	3×
UNCOV 65	kdeplot(value, label=label, shade=shade, bw=bw, ax=ax, kwargs_shade=kwargs_shade,	3×
66	**kwargs)
67
UNCOV 68	elif kind == 'hist':	3×
UNCOV 69	for label, value in series:	3×
UNCOV 70	ax.hist(value, alpha=shade, label=label, **kwargs)	3×
71
72	else:
73	raise ValueError('Plot type {} not recognized.'.format(kind))	!
74
UNCOV 75	ax.set_xticks([])	3×
UNCOV 76	ax.set_yticks([])	3×
77
UNCOV 78	if not frame:	3×
79	for spine in ax.spines.values():	!
80	spine.set_visible(False)	!
81
UNCOV 82	if legend:	3×
UNCOV 83	ax.legend()	3×
84
UNCOV 85	return ax	3×

pymc-devs / pymc3 / 8412

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