spateo.svg.utils#
Module Contents#
Functions#
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Aggregate cell-based adata by bin size. Cells within a bin would be |
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Shuffle X in anndata object randomly. |
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Filter out cells with positive ratio lower than a setting value. |
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Get genes that have postive ratio higher than a setting value. |
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Calculate positive ratios for all genes, and return to AnnData. |
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Calculate geodesic distance between any pair of genes. |
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Scale the X array in AnnData. |
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Computing Wasserstein distance. |
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- spateo.svg.utils.bin_adata(adata: anndata.AnnData, bin_size: int = 1, layer: str = 'spatial') anndata.AnnData[source]#
Aggregate cell-based adata by bin size. Cells within a bin would be aggregated together as one cell.
- Parameters:
- adata
the input adata.
- bin_size
the size of square to bin adata.
- Returns:
Aggreated adata.
- spateo.svg.utils.shuffle_adata(adata: anndata.AnnData, seed: int = 0, replace: bool = False)[source]#
Shuffle X in anndata object randomly.
- Parameters:
- adata
AnnData object
- seed
seed for randomly shuffling
- Returns:
AnnData object
- Return type:
adata
- spateo.svg.utils.filter_adata_by_pos_ratio(adata, pos_ratio)[source]#
Filter out cells with positive ratio lower than a setting value.
- Parameters:
- adata
AnnData object.
- pos_ratio
Cells with positive ratio lower than this value would be discarded.
- Returns:
AnnData object.
- spateo.svg.utils.get_genes_by_pos_ratio(adata: anndata.AnnData, pos_ratio: float = 0.1) list[source]#
Get genes that have postive ratio higher than a setting value.
- Parameters:
- adata
AnnData object.
- pos_ratio
The threshold of positive ratio.
- Returns:
Gene list. AnnData object.
- spateo.svg.utils.add_pos_ratio_to_adata(adata: anndata.AnnData, layer: str = None, var_name: str = 'raw_pos_rate')[source]#
Calculate positive ratios for all genes, and return to AnnData. We defind positive ratio of a gene as the percent of cells express this gene.
- Parameters:
- adata
AnnData object.
- layer
The layer of AnnData, in which the data are used. If not given, we use data in X.
- var_name
The var name for storing positive ratios.
- Returns:
None
- spateo.svg.utils.cal_geodesic_distance(adata: anndata.AnnData, layer: str = 'spatial', n_neighbors: int = 30, min_dis_cutoff: float = 2.0, max_dis_cutoff: float = 4.0) anndata.AnnData[source]#
Calculate geodesic distance between any pair of genes.
- Parameters:
- adata
AnnData object.
- layer
The layer of AnnData, in which the data are used.
- n_neighbors
The number of neighbor to connect a cell to its nearest neighbors.
- min_dis_cutoff
Remove cells with minimal distance with its neighbors larger than this value. These cells are like islated cells.
- max_dis_cutoff
Remove cells with maximal distance with its neighbors larger than this value. These cells are like sparse cells.
- Returns:
AnnData object.
- spateo.svg.utils.cal_euclidean_distance(adata: anndata.AnnData, layer: str = 'spatial', min_dis_cutoff: float = np.inf, max_dis_cutoff: float = np.inf) anndata.AnnData[source]#
- spateo.svg.utils.scale_to(adata: anndata.AnnData, to_median: bool = True, N: int = 10000) anndata.AnnData[source]#
Scale the X array in AnnData.
- Parameters:
- adata
AnnData object.
- to_median
Whether scale to the median of cell total expressions.
- N
if to_median is False, scale data to this value.
- Returns:
AnnData object.
- spateo.svg.utils.cal_wass_dis(M, a, b=[], numItermax=1000000)[source]#
Computing Wasserstein distance.
- Parameters:
- M
(ns,nt) array-like, float – Loss matrix (c-order array in numpy with type float64)
- a
(ns,) array-like, float – Source histogram (uniform weight if empty list)
- b
(nt,) array-like, float – Target histogram (uniform weight if empty list)
- Returns:
(float, array-like) – Optimal transportation loss for the given parameters
- Return type:
W
- spateo.svg.utils.loess_reg(adata: anndata.AnnData, layers: str = 'X') anndata.AnnData[source]#