Add support for `np.ndarray` class of ArviZ package to show plots

[Haleshot]

📝 Summary

This PR addresses issue #1033 by implementing an ArviZ formatter that can handle various plot types returned by ArviZ functions, including numpy arrays, matplotlib axes, and bokeh figures.

🔍 Description of Changes

• Created a new NpndarrayFormatter class that extends FormatterFactory
• Implemented a _show_npndarray_plot function that handles the return types which causes the issue from ArviZ plots:
  • numpy arrays (more specifically np.ndarrays).

📋 Checklist

• [x] I have read the contributor guidelines.
• [ ] For large changes, or changes that affect the public API: this change was discussed or approved through an issue, on Discord, or the community discussions (Please provide a link if applicable).
• [ ] I have added tests for the changes made.
• [x] I have run the code and verified that it works as expected.

📜 Reviewers

@akshayka OR @mscolnick

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[Haleshot]

For my reference:

Detailed preview of all arviz functions compatibility

ArviZ Plot Functions Overview

Function	Input	Return	Behavior	Issues
plot_autocorr	-	Axes or bokeh_figures	Causes typical issue error	Displays complex Axes structure
plot_bf	-	Dictionary, then plot	Plots without plt.show()	Returns text dictionary before plot
plot_bpv	-	2D ndarray of Axes or Bokeh Figure	Plots without plt.show()	-
plot_compare	-	Axes or Bokeh Figure, pandas DataFrame	Issues warning	Not InferenceData
plot_density	-	2D ndarray of Axes or Bokeh Figure	Causes typical issue error	Displays complex Axes structure
plot_dist	Array-like	Axes or Bokeh Figure	Plots without any issue	-
plot_dist_comparison	InferenceData	2D ndarray of Axes	-	-
plot_dot	Array-like	Axes or Bokeh Figure	Plots without any issue	-
plot_ecdf	Array-like	Axes or Bokeh Figure	Plots without any issue	-
plot_elpd	Mapping of {str:ELPDData or InferenceData}	Axes or Bokeh Figure	-	-
plot_energy	obj	Axes or Bokeh Figure	Plots without any issue	-
plot_ess	InferenceData	Axes or Bokeh Figure	Causes typical issue error	-
plot_forest	InferenceData	1D ndarray of Axes or Bokeh Figure	Plots without any issue	-
plot_hdi	Array-like	Axes or Bokeh Figure	Plots without any issue	-
plot_kde	Array-like	Axes or Bokeh Figure, optional glyphs list	Plots without any issue	-
plot_khat	ELPData or Array-like	Axes or Bokeh Figure	Plots without any issue	-
plot_loo_pit	InferenceData	Axes or Bokeh Figure	Plots without any issue	-
plot_lm	str or DataArray or ndarray	Axes or Bokeh Figure	Causes typical issue error	Issues with Bokeh backend
plot_mcse	InferenceData	Axes or Bokeh Figure	Causes typical issue error	Bokeh: Only axes, no data points
plot_pair	InferenceData	Axes or Bokeh Figure	Causes typical issue error	Works well with Bokeh
plot_parallel	InferenceData	Axes or Bokeh Figure	Plots without any issue	Bokeh: No controls in Marimo
plot_posterior	InferenceData	Axes or Bokeh Figure	Causes typical issue error	Bokeh: Incorrect rendering
plot_ppc	InferenceData	Axes or Bokeh Figure, optional Animation	Plots without any issue*	Bokeh doesn't work properly
plot_rank	InferenceData	Axes or Bokeh Figure	Causes typical issue error (sometimes)	-
plot_separation	InferenceData	Axes or Bokeh Figure	Plots without any issue	Trouble with Bokeh
plot_trace	InferenceData	Axes or Bokeh Figure	Causes typical issue error	Works well with Bokeh
plot_ts	InferenceData	Axes or Bokeh Figure	Causes typical issue error	No Bokeh support
plot_violin	InferenceData	Axes or Bokeh Figure	-	Works well with Bokeh

Common Issues and Observations

1. Typical Issue Error: Many functions require plt.show() at the end of the cell block to display the plot.

2. Bokeh Backend Issues:

   • Often opens a random new file in the temp folder
   • Controls for Bokeh don't always work correctly
   • Some functions work well with Bokeh, opening in a new window with proper controls
   • Others have rendering issues or don't display data correctly

3. Plot Display:

   • Some functions plot without requiring plt.show()
   • Others cause the "typical issue error" where plt.show() is needed

4. Return Types:

   • Most functions return matplotlib Axes or Bokeh Figures
   • Some return additional data structures (e.g., pandas DataFrames, dictionaries)

5. Input Types:

   • Many functions accept InferenceData objects
   • Some work with array-like inputs or specific data types (e.g., ELPDData)

6. Specific Function Notes:

   • plot_autocorr and plot_density return complex Axes structures
   • plot_bf returns a dictionary before displaying the plot
   • plot_ppc works fine for single plots but has issues with multiple plots using coords or flatten
   • plot_parallel may have text overlap issues with too much information

[Haleshot]

Completed via #2311