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…into niche_definitions
for more information, see https://pre-commit.ci
…into niche_definitions
for more information, see https://pre-commit.ci
for more information, see https://pre-commit.ci
This was referenced Jun 12, 2024
for more information, see https://pre-commit.ci
for more information, see https://pre-commit.ci
LLehner
commented
Mar 13, 2025
| inplace, | ||
| ) | ||
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| if resolutions is None: |
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Why not set this as default right away?
| if resolutions is None: | ||
| resolutions = [0.5] | ||
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| if distance is None: |
| elif libraries is not None and len(libraries) > 0: | ||
| return [f"{base_column}_{lib}" for lib in libraries] | ||
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| # For neighborhood and utag, we need to handle resolutions |
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Would do this with if-else block maybe
src/squidpy/gr/_niche.py
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| groups: str | None, | ||
| n_neighbors: int | None, | ||
| resolutions: float | list[float], | ||
| subset_groups: list[str] | None, |
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why remove this completely? It serves a different purpose than masking. This was also described in the original tutorial. E.g. a mask allows to restrict niche calculation to specific cell types but they can have neighbors outside the masked region. Subsetting means only observations within that subset are considered as neighbors.
src/squidpy/gr/_niche.py
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| def _get_utag_niches( | ||
| adata: AnnData, | ||
| subset_groups: list[str] | None, |
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Here subsetting serves the same purpose as before.
| if library_key not in data.tables[table_key].obs.columns: | ||
| raise ValueError(f"'library_key' must be a column in 'adata.obs', got {library_key}") | ||
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| if n_neighbors is not None and not isinstance(n_neighbors, int): |
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Why check these separately?
| for param_name in param_specs["unused"]: | ||
| param_value = param_dict.get(param_name) | ||
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| # Special handling for boolean parameters with default values |
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Description
Adds a function that calculates niches using different strategies. The initial function calculates niches based on neighborhood profiles similar to here.
This PR will get updated with methods discussed in #789.