Single kernel call for volume and intensity

[jellybean2004]

Description

Removes hard-coded/duplicated volume math and ensures intensities/volumes come from the model kernel.

Replaces the previous per-bin DirectModel/analytic volume approach with a kernel-based single call.
Builds the sasmodels kernel (from model info) and calls call_Fq for each bin to retrieve Fsq and volume. Compute intensity per bin as intensity = (scale/volume) * Fsq + background and store per-bin volumes in self._volumes.

Fixes #3418

How Has This Been Tested?

Tested functionality -- same as before.

Review Checklist:

Documentation

• There is nothing that needs documenting
• Documentation changes are in this PR
• There is an issue open for the documentation (link?)

Installers

• There is a chance this will affect the installers, if so
  • Windows installer (GH artifact) has been tested (installed and worked)
  • MacOSX installer (GH artifact) has been tested (installed and worked)
  • Wheels installer (GH artifact) has been tested (installed and worked)

Licensing

• The introduced changes comply with SasView license (BSD 3-Clause)

[Copilot]

Pull request overview

This PR updates the size distribution model-matrix generation so that both per-bin intensity and volume are obtained via a single sasmodels kernel call, removing the prior duplicated/hard-coded volume math path.

Changes:

• Replaces load_model/DirectModel usage with load_model_info + build_model and call_Fq in generate_model_matrix.
• Computes per-bin intensity from returned kernel outputs and stores per-bin volumes on the class for later use.

Comments suppressed due to low confidence (1)

src/sas/sascalc/size_distribution/SizeDistribution.py:193

• self._volumes is initialized twice in __init__ (once untyped, then again with a type annotation). This duplication is redundant and can confuse readers/type checkers; remove the earlier self._volumes = None assignment and keep the single typed initialization.

        self.model_matrix: np.ndarray | None = None
        self._volumes = None

        # Advanced parameters for MaxEnt
        self._iterMax: int = 5000
        self._skyBackground: float = 1e-6
        self._weightType: str = "dI"
        self._weightFactor: float = 1.0
        self._weightPercent: float = 1.0
        self._weights: np.ndarray | None = np.array(data.dy)

        self._bin_edges: np.ndarray = np.array([])
        self._binDiff: np.ndarray = np.array([])
        self._volumes: np.ndarray | None = None

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[pkienzle]

This is duplicating code from within sasmodels.kernel.Kernel.Iq. This isn't avoidable in the current implementation, but we should consider this use case when addressing sasmodels #182.

The idea is to return intermediate and derived values from the calculation back to the caller. The current hack to get $P(Q)$ and $S(Q)$ from P@S is that sasmodels.product sets up a kernel.results() function that returns a dictionary with keys P(Q), S(Q), volume, volume_ratio and radius_effective after calling kernel.Iq(). We could extend this to the base Kernel class in sasmodels. Then using call_kernel instead of call_Fq we can get the volume and volume ratio from calculator.results().

[jellybean2004]

Hey @pkienzle! Thanks for your review! I have addressed your comments in my recent commit.

[pkienzle]

_volumes is never used. Is this preparation for a future change?

[jellybean2004]

_volumes is never used. Is this preparation for a future change?

I somehow managed to miss one commit. The goal in the issue was to replace ellsipse_volume with self._volumes, and I have now done that.