arviz.plot_kde#

arviz.plot_kde(values, values2=None, cumulative=False, rug=False, label=None, bw='default', adaptive=False, quantiles=None, rotated=False, contour=True, hdi_probs=None, fill_last=False, figsize=None, textsize=None, plot_kwargs=None, fill_kwargs=None, rug_kwargs=None, contour_kwargs=None, contourf_kwargs=None, pcolormesh_kwargs=None, is_circular=False, ax=None, legend=True, backend=None, backend_kwargs=None, show=None, return_glyph=False, **kwargs)[source]#

1D or 2D KDE plot taking into account boundary conditions.

Parameters:

valuesarray_like: Values to plot
values2array_like, optional: Values to plot. If present, a 2D KDE will be estimated
cumulativebool, dafault False: If True plot the estimated cumulative distribution function. Ignored for 2D KDE.
rugbool, default False: Add a rug plot for a specific subset of values. Ignored for 2D KDE.
labelstr, optional: Text to include as part of the legend.
bwfloat or str, optional: If numeric, indicates the bandwidth and must be positive. If str, indicates the method to estimate the bandwidth and must be one of “scott”, “silverman”, “isj” or “experimental” when is_circular is False and “taylor” (for now) when is_circular is True. Defaults to “default” which means “experimental” when variable is not circular and “taylor” when it is.
adaptivebool, default False: If True, an adaptative bandwidth is used. Only valid for 1D KDE.
quantileslist, optional: Quantiles in ascending order used to segment the KDE. Use [.25, .5, .75] for quartiles.
rotatedbool, default False: Whether to rotate the 1D KDE plot 90 degrees.
contourbool, default True: If True plot the 2D KDE using contours, otherwise plot a smooth 2D KDE.
hdi_probslist, optional: Plots highest density credibility regions for the provided probabilities for a 2D KDE. Defaults to [0.5, 0.8, 0.94].
fill_lastbool, default False: If True fill the last contour of the 2D KDE plot.
figsize(float, float), optional: Figure size. If None it will be defined automatically.
textsizefloat, optional: Text size scaling factor for labels, titles and lines. If None it will be autoscaled based on figsize. Not implemented for bokeh backend.
plot_kwargsdict, optional: Keywords passed to the pdf line of a 1D KDE. See matplotlib.axes.Axes.plot() or bokeh:bokeh.plotting.Figure.line() for a description of accepted values.
fill_kwargsdict, optional: Keywords passed to the fill under the line (use fill_kwargs={'alpha': 0} to disable fill). Ignored for 2D KDE. Passed to bokeh.plotting.Figure.patch().
rug_kwargsdict, optional: Keywords passed to the rug plot. Ignored if rug=False or for 2D KDE Use space keyword (float) to control the position of the rugplot. The larger this number the lower the rugplot. Passed to bokeh:bokeh.models.glyphs.Scatter.
contour_kwargsdict, optional: Keywords passed to matplotlib.axes.Axes.contour() to draw contour lines or bokeh.plotting.Figure.patch(). Ignored for 1D KDE.
contourf_kwargsdict, optional: Keywords passed to matplotlib.axes.Axes.contourf() to draw filled contours. Ignored for 1D KDE.
pcolormesh_kwargsdict, optional: Keywords passed to matplotlib.axes.Axes.pcolormesh() or bokeh.plotting.Figure.image(). Ignored for 1D KDE.
is_circular{False, True, “radians”, “degrees”}. Default False: Select input type {“radians”, “degrees”} for circular histogram or KDE plot. If True, default input type is “radians”. When this argument is present, it interprets values as a circular variable measured in radians and a circular KDE is used. Inputs in “degrees” will undergo an internal conversion to radians.
axaxes, optional: Matplotlib axes or bokeh figures.
legendbool, default True: Add legend to the figure.
backend{“matplotlib”, “bokeh”}, default “matplotlib”: Select plotting backend.
backend_kwargsdict, optional: These are kwargs specific to the backend being used, passed to matplotlib.pyplot.subplots() or bokeh.plotting.figure. For additional documentation check the plotting method of the backend.
showbool, optional: Call backend show function.
return_glyphbool, optional: Internal argument to return glyphs for bokeh.

Returns:

axesmatplotlib.Axes or bokeh.plotting.Figure: Object containing the kde plot
glyphslist, optional: Bokeh glyphs present in plot. Only provided if return_glyph is True.

See also

kde: One dimensional density estimation.
plot_dist: Plot distribution as histogram or kernel density estimates.

Examples

Plot default KDE

>>> import arviz as az
>>> non_centered = az.load_arviz_data('non_centered_eight')
>>> mu_posterior = np.concatenate(non_centered.posterior["mu"].values)
>>> tau_posterior = np.concatenate(non_centered.posterior["tau"].values)
>>> az.plot_kde(mu_posterior)

Plot KDE with rugplot

>>> az.plot_kde(mu_posterior, rug=True)

Plot KDE with adaptive bandwidth

>>> az.plot_kde(mu_posterior, adaptive=True)

Plot KDE with a different bandwidth estimator

>>> az.plot_kde(mu_posterior, bw="scott")

Plot KDE with a bandwidth specified manually

>>> az.plot_kde(mu_posterior, bw=0.4)

Plot KDE for a circular variable

>>> rvs = np.random.vonmises(mu=np.pi, kappa=2, size=500)
>>> az.plot_kde(rvs, is_circular=True)

Plot a cumulative distribution

>>> az.plot_kde(mu_posterior, cumulative=True)

Rotate plot 90 degrees

>>> az.plot_kde(mu_posterior, rotated=True)

Plot 2d contour KDE

>>> az.plot_kde(mu_posterior, values2=tau_posterior)

Plot 2d contour KDE, without filling and contour lines using viridis cmap

>>> az.plot_kde(mu_posterior, values2=tau_posterior,
...             contour_kwargs={"colors":None, "cmap":plt.cm.viridis},
...             contourf_kwargs={"alpha":0});

Plot 2d contour KDE, set the number of levels to 3.

>>> az.plot_kde(
...     mu_posterior, values2=tau_posterior,
...     contour_kwargs={"levels":3}, contourf_kwargs={"levels":3}
... );

Plot 2d contour KDE with 30%, 60% and 90% HDI contours.

>>> az.plot_kde(mu_posterior, values2=tau_posterior, hdi_probs=[0.3, 0.6, 0.9])

Plot 2d smooth KDE

>>> az.plot_kde(mu_posterior, values2=tau_posterior, contour=False)