arviz.plot_elpd¶
-
arviz.plot_elpd(compare_dict, color='C0', xlabels=False, figsize=None, textsize=None, coords=None, legend=False, threshold=None, ax=None, ic=None, scale=None, plot_kwargs=None, backend=None, backend_kwargs=None, show=None)[source]¶ Plot pointwise elpd differences between two or more models.
- Parameters
- compare_dictmapping, str -> ELPDData or InferenceData
A dictionary mapping the model name to the object containing inference data or the result of loo/waic functions. Refer to az.convert_to_inference_data for details on possible dict items
- colorstr or array_like, optional
Colors of the scatter plot, if color is a str all dots will have the same color, if it is the size of the observations, each dot will have the specified color, otherwise, it will be interpreted as a list of the dims to be used for the color code
- xlabelsbool, optional
Use coords as xticklabels
- figsizefigure size tuple, optional
If None, size is (8 + numvars, 8 + numvars)
- textsize: int, optional
Text size for labels. If None it will be autoscaled based on figsize.
- coordsmapping, optional
Coordinates of points to plot. All values are used for computation, but only a a subset can be plotted for convenience.
- legendbool, optional
Include a legend to the plot. Only taken into account when color argument is a dim name.
- thresholdfloat
If some elpd difference is larger than threshold * elpd.std(), show its label. If None, no observations will be highlighted.
- icstr, optional
Information Criterion (PSIS-LOO loo, WAIC waic) used to compare models. Defaults to
rcParams["stats.information_criterion"]. Only taken into account when input is InferenceData.- scalestr, optional
scale argument passed to az.loo or az.waic, see their docs for details. Only taken into account when input is InferenceData.
- plot_kwargsdicts, optional
Additional keywords passed to ax.scatter
- ax: axes, optional
Matplotlib axes or bokeh figures.
- backend: str, optional
Select plotting backend {“matplotlib”,”bokeh”}. Default “matplotlib”.
- backend_kwargs: bool, optional
These are kwargs specific to the backend being used. For additional documentation check the plotting method of the backend.
- showbool, optional
Call backend show function.
- Returns
- axesmatplotlib axes or bokeh figures
Examples
Compare pointwise PSIS-LOO for centered and non centered models of the 8-schools problem using matplotlib.
>>> import arviz as az >>> idata1 = az.load_arviz_data("centered_eight") >>> idata2 = az.load_arviz_data("non_centered_eight") >>> az.plot_elpd( >>> {"centered model": idata1, "non centered model": idata2}, >>> xlabels=True >>> )
import arviz as az idata1 = az.load_arviz_data("centered_eight") idata2 = az.load_arviz_data("non_centered_eight") az.plot_elpd( {"centered model": idata1, "non centered model": idata2}, backend="bokeh" )