BaseMultivariateSliceDistribution.plot (function)

def plot(self, size=100000.0, unit=None, wrap_at=None, seed=None, samples=None, plot_sample=True, plot_sample_kwargs={'color': 'gray'}, plot_pdf=True, plot_pdf_kwargs={'color': 'red'}, plot_cdf=False, plot_cdf_kwargs={'color': 'green'}, plot_gaussian=False, plot_gaussian_kwargs={'color': 'blue'}, plot_uncertainties=True, plot_uncertainties_kwargs={'color': 'black', 'linestyle': 'dashed'}, label=None, xlabel=None, show=False, **kwargs)

Plot both the analytic distribution function as well as a sampled histogram from the distribution. Requires matplotlib to be installed.

See also:

• BaseMultivariateSliceDistribution.plot_sample
• BaseMultivariateSliceDistribution.plot_pdf
• BaseMultivariateSliceDistribution.plot_cdf
• BaseMultivariateSliceDistribution.plot_gaussian

Arguments

• size (int, optional, default=1e5): number of points to sample for the histogram. See also BaseMultivariateSliceDistribution.sample. Will be ignored if samples is provided.
• unit (astropy.unit, optional, default=None): units to use along the x-axis. Astropy must be installed. If samples is provided, the passed values will be assumed to be in the correct units.
• wrap_at (float, None, or False, optional, default=None): value to use for wrapping. See BaseMultivariateSliceDistribution.wrap. If not provided or None, will use the value from BaseMultivariateSliceDistribution.wrap_at. Note: wrapping is computed before changing units, so wrap_at must be provided according to BaseMultivariateSliceDistribution.unit not unit. Will be ignored if samples is provided.
• seed (int, optional): seed to use when sampling. See also BaseMultivariateSliceDistribution.sample. Will be ignored if samples is provided.
• samples (array, optional, default=None): plot specific sampled values instead of calling BaseMultivariateSliceDistribution.sample internally. Will override size.
• plot_sample (bool, optional, default=True): whether to plot the histogram from sampling. See also BaseMultivariateSliceDistribution.plot_sample.
• plot_sample_kwargs (dict, optional, default={'color': 'gray'}): keyword arguments to send to BaseMultivariateSliceDistribution.plot_sample.
• plot_pdf (bool, optional, default=True): whether to plot the analytic form of the underlying distribution, if applicable. See also BaseMultivariateSliceDistribution.plot_pdf.
• plot_pdf_kwargs (dict, optional, default={'color': 'red'}): keyword arguments to send to BaseMultivariateSliceDistribution.plot_pdf.
• plot_cdf (bool, optional, default=True): whether to plot the analytic form of the cdf, if applicable. See also BaseMultivariateSliceDistribution.plot_cdf.
• plot_cdf_kwargs (dict, optional, default={'color': 'green'}): keyword arguments to send to BaseMultivariateSliceDistribution.plot_cdf.
• plot_gaussian (bool, optional, default=False): whether to plot a guassian distribution fit to the sample. Only supported for distributions that have BaseMultivariateSliceDistribution.to_gaussian methods.
• plot_gaussian_kwargs (dict, optional, default={'color': 'blue'}): keyword arguments to send to BaseMultivariateSliceDistribution.plot_gaussian.
• plot_uncertainties (bool or int, optional, default=True): whether to plot uncertainties (as vertical lines) and include the representation of the uncertainties in the plot title. If an integer, will plot at that sigma. If True, will default to sigma=1. See BaseMultivariateSliceDistribution.uncertainties.
• plot_uncertainties_kwargs (dict, optional, default={'color': 'black', 'linestyle': 'dashed'}): keyword arguments to send to BaseMultivariateSliceDistribution.plot_uncertainties.
• label (string, optional, default=None): override the label on the x-axis. If not provided or None, will use BaseMultivariateSliceDistribution.label. Will only be used if show=True. Unit will automatically be appended. Will be ignored if xlabel is provided.
• xlabel (string, optional, default=None): override the label on the x-axis without appending the unit. Will override label.
• show (bool, optional, default=True): whether to show the resulting matplotlib figure.
• **kwargs: all keyword arguments (except for bins) will be passed on to BaseMultivariateSliceDistribution.plot_pdf and BaseMultivariateSliceDistribution.plot_gaussian and all keyword arguments will be passed on to BaseMultivariateSliceDistribution.plot_sample. Keyword arguments defined in plot_sample_kwargs, plot_pdf_kwargs, and plot_gaussian_kwargs will override the values sent in kwargs.

Returns

• tuple: the return values from BaseMultivariateSliceDistribution.plot_sample (or None if plot_sample=False), BaseMultivariateSliceDistribution.plot_pdf (or None if plot_pdf=False), BaseMultivariateSliceDistribution.plot_cdf (or None if plot_cdf=False), Gaussian.plot_pdf (or None if plot_gaussian=False), and BaseMultivariateSliceDistribution.plot_uncertainties (or None if plot_uncertainties=False).

Raises

• ImportError: if matplotlib dependency is not met.