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Improve moments and spectrum_moments docstrings in particulator.py #1947

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Improve moments and spectrum_moments docstrings in particulator.py #1947

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Improve `moments` and `spectrum_moments` docstrings in particulator.py
slayoo Sep 11, 2026
72917a3
clarify the difference between filering attribute and the attribute f…
slayoo Sep 11, 2026
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27 changes: 25 additions & 2 deletions PySDM/particulator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -333,10 +333,27 @@ def moments(
weighting_rank=0,
skip_division_by_m0=False,
):
"""
Writes to `moment_0` and `moment` the zero-th and the k-th statistical moments
r"""
Writes to `moment_0` and `moments` the zero-th and the k-th statistical moments
of particle attributes computed filtering by value of the attribute `attr_name`
to fall within `attr_range`. The moment ranks are defined by `specs`.
By default, the moments are multiplicity-weighted, and any other weighting
(e.g., mass-weighting) can be specified using `weighting_attribute` and
`weighting_rank` parameters. All calculations are done per-cell, hence the
dimensionality of `moment_0` and `moments` matches the environment grid.

Mathematically, the computations correspond to:
$$
M_k = \frac{

@Bodzio-2 Bodzio-2 Sep 11, 2026

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Missing a couple of } s and escaping the _ in attr_range

Corrected (checked in markdown and latex):
M_k = \frac{\left.\sum_i\right|_{\text{attr\_range[0]} < x_i < \text{attr\_range[1]} a_i^k m_i w_i^l}}{\left.\sum_i\right|_{\text{attr\_range[0]} < x_i < \text{attr\_range[1]} m_i w_i^l}}

\left.\sum_i\right|_{\text{attr_range[0]} < x_i < \text{attr_range[1]} a_i^k m_i w_i^l
}{
\left.\sum_i\right|_{\text{attr_range[0]} < x_i < \text{attr_range[1]} m_i w_i^l
}
$$
where $k$ is the rank (e.g., 1 for an ordinary mean), $x$ is the attribute used for filtering
(e.g., radius), $a$ is the attribute of which the moment is calculated (specified via the `specs`
parameter), $m$ is the multiplicity, $w$ is the weighting attribute (e.g., mass) and $l$ is the
weighting rank (by default 0 translating to plain multiplicity weighting).

Parameters:
specs: e.g., `specs={'volume': (1,2,3), 'kappa': (1)}` computes three moments
Expand Down Expand Up @@ -389,6 +406,12 @@ def spectrum_moments(
weighting_rank=0,
skip_division_by_m0=False,
):
"""
Performns calculation of statistical moments as in `moments()`, but with the attribute-value
filtering applied to a series of ranges (bins), instead of just a single range. Typical usage
is to create a binned spectrum representation in one call, rather than executing `moments()`
separately for each spectrum bin.
"""
attr_data = self.attributes[attr]
self.backend.spectrum_moments(
moment_0=moment_0,
Expand Down
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