asterion.plotting#
The plotting module contains functions for plotting inference data.
Module Contents#
- get_labeller(data, group='posterior', var_names=None)[source]#
Get labeller for use with arviz plotting. This automatically searches variable metadata (contained in their attrs dictionary) for its ‘symbol’ and ‘unit’ if available.
- Parameters
data (arviz.InferenceData) – Inference data object.
group (str) – Inference data group for which to map labels.
var_names (list[str], optional) – Variable names for which to map labels.
- Returns
Label map.
- Return type
- plot_corner(data, group='posterior', var_names=None, quantiles=None, labeller='auto', **kwargs)[source]#
A wrapper for
corner.corner()with automatic labelling and custom default arguments specified below.- Parameters
data (arviz.InferenceData) – Inference data object.
group (str) – Inference data group from which to take samples. Defaults to ‘posterior’.
var_names (List[str], optional) – Variable names to plot. Defaults to plotting all available variables.
quantiles (iterable, optional) – Quantiles to plot as dashed lines in the marginals. If None, defaults to the 68% confidence interval. Pass an empty list to plot no confidence intervals.
labeller (str, or MapLabeller) – Labeller which maps variable names to their axis labels. Defaults to ‘auto’.
**kwargs – Keyword arguments to pass to
corner.corner().
- Returns
Figure object.
- Return type
See also
corner.corner(): The function for which this wraps.
- plot_glitch(data, group='posterior', kind='full', x_var='n', quantiles=None, observed='auto', use_alpha=True, ax=None, **kwargs)[source]#
Plot the glitch from either the prior or posterior predictive contained in inference data.
- Parameters
data (arviz.InferenceData) – Inference data object.
group (str) – One of [‘posterior’, ‘prior’].
kind (str) – Kind of glitch to plot. One of [‘full’, ‘helium’, ‘BCZ’].
x_var (str) – Variable name for x-axis. One of [‘n’, ‘nu’]. If ‘nu’, the median value of ‘nu’ in
data['group']is used.quantiles (iterable, optional) – Quantiles to plot as confidence intervals. If None, defaults to the 68% confidence interval. Pass an empty list to plot no confidence intervals.
observed (bool or str) – Whether to plot observed data. Default is “auto” which will plot observed data when group is “posterior”.
use_alpha (bool) – Whether to use alpha channel for transparency. If False, will shade with lightened solid color.
ax (matplotlib.axes.Axes) – Axis on which to plot the glitch.
**kwargs – Keyword arguments to pass to
matplotlib.pyplot.plot().
- Raises
ValueError – If kind is not valid.
- Returns
Axis on which the glitch is plot.
- Return type