plotting functions for d2 and scattering cross section

[jtgasparik]

This pull request introduces a new visualization function for statistical distance analysis and updates test cases for plotting functions to use more accurate parameter conversions. The main highlights are the addition of the plot_d2 function to visualize Moteki & Kondo statistical distance, and the corresponding test to ensure its correctness. Additionally, all test cases now use FWTM-to-sigma conversions for relevant parameters, improving consistency and accuracy.

New plotting functionality:

• Added plot_d2 function to pysp2/util/normalized_derivative_method.py for visualizing Moteki & Kondo statistical distance $d^2(k)$, including options for log-scaling, threshold lines, and highlighting the optimal $k$ value.

Testing improvements:

• Added test_plot_d2 in tests/test_vis.py to validate the new plot_d2 function using pytest's image comparison, ensuring visual correctness of the plot.
• Imported plot_d2 in tests/test_vis.py to enable testing of the new plotting function.

Parameter conversion consistency:

• Updated all test cases (test_ndm_moteki_kondo, test_plot_incident_irradiance, test_plot_scattering_cross_section, and test_plot_d2) to convert FWTM values to sigma by dividing by 2.335, ensuring parameter consistency with the model's requirements. [1] [2] [3] [4]

[Copilot]

🟡 Changes recommended

The new plot_d2 currently drops the DataArray’s k coordinate (misaligning the x-axis/best-k marker), and the updated tests use an inconsistent FWHM→σ conversion constant.

Once you've addressed the issues Copilot identified, you can request another Copilot review.

Pull request overview

This PR adds a new visualization helper to plot Moteki & Kondo statistical distance (d^2(k)) and updates the existing NDM/plotting tests to apply width-to-sigma conversions more consistently.

Changes:

• Added plot_d2 to visualize (d^2(k)) with optional log scaling, threshold line, and best-(k) highlighting.
• Added test_plot_d2 (mpl image comparison) and imported plot_d2 into the plotting test suite.
• Updated NDM and plotting tests to convert width-like inputs to (\sigma) before constructing MLEConfig.

File summaries

File	Description
pysp2/util/normalized_derivative_method.py	Adds plot_d2 plotting function for Moteki & Kondo (d^2(k)).
tests/test_vis.py	Imports plot_d2, adds image-based test for it, and updates width conversion constants in plotting-related tests.
tests/test_ndm.py	Updates width conversion constants in Moteki & Kondo NDM test configuration.

Review details

Suppressed comments (2)

tests/test_vis.py:119

• Same conversion issue as above: 2.335 is not the standard Gaussian FWHM→σ factor used elsewhere in this repo (2.35482). Keeping a single factor avoids subtle mismatches across plotting tests.

    sigma_bar= (18.5/2.335)*0.4,  # example; use your measured average width
    delta_sigma=(1.2/2.335)*0.4, # example; use your measured width std dev

tests/test_vis.py:183

• Same conversion issue as the other plotting tests: 2.335 should be 2.35482 (Gaussian FWHM→σ), consistent with other modules (e.g., plot_wave / leo_fit).

    sigma_bar= (18.5/2.335)*0.4,  # example; use your measured average width
    delta_sigma=(1.2/2.335)*0.4, # example; use your measured width std dev

• Files reviewed: 3/5 changed files
• Comments generated: 4
• Review effort level: Lite

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