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Optimize the calculation speed and logic of InterRDF_s to ensure that the results are consistent with InterRDF #5073

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Optimize the calculation speed and logic of InterRDF_s to ensure that the results are consistent with InterRDF #5073

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8965375
Refactored bin index calculation in the _single_frame function of Int…
gitzhangch Jun 29, 2025
2760210
Adjust the code to ensure the test passes.
gitzhangch Jul 1, 2025
375ecc9
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gitzhangch Jul 3, 2025
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gitzhangch Jul 3, 2025
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19 changes: 17 additions & 2 deletions package/MDAnalysis/analysis/rdf.py
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Original file line number Diff line number Diff line change
Expand Up @@ -645,9 +645,24 @@ def _single_frame(self):
backend=self.backend,
)

# Different people write code for different purposes. For my needs, the following two lines are sufficient:
# count, _ = np.histogram(dist, **self.rdf_settings)
# self.results.count[i][0, 0, :] += count

# The following is an optimized version based on the old logic.
bins = self.rdf_settings["bins"]
minv, maxv = (
self.rdf_settings["range"][0],
self.rdf_settings["range"][1],
)
# Calculate bin indices for each value in dist, similar to np.histogram's bin assignment.
bin_indices = (dist - minv) * bins / (maxv - minv)
bin_indices = bin_indices.astype(np.int64)

for j, (idx1, idx2) in enumerate(pairs):
count, _ = np.histogram(dist[j], **self.rdf_settings)
self.results.count[i][idx1, idx2, :] += count
if 0 <= bin_indices[j] < bins:
self.results.count[i][idx1, idx2, bin_indices[j]] += 1
# self.results.count[i][0, 0, bin_indices[j]] += 1 # this is necessary to calc rdf

if self.norm == "rdf":
self.volume_cum += self._ts.volume
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