File size: 1,806 Bytes
e8edb9d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 | """Utility functions for layer resolution, validation, and parameter logging."""
from __future__ import annotations
import logging
from typing import Optional
import numpy as np
from anndata import AnnData
from scipy.sparse import issparse
from . import _constants as C
logger = logging.getLogger("scptr")
def get_layer(adata: AnnData, layer: str) -> np.ndarray:
"""Return a dense numpy array for the given layer."""
mat = adata.layers[layer]
if issparse(mat):
return np.asarray(mat.todense())
return np.asarray(mat)
def require_layers(adata: AnnData, *layers: str) -> None:
"""Raise KeyError if any of the specified layers are missing."""
missing = [l for l in layers if l not in adata.layers]
if missing:
raise KeyError(f"Missing required layers: {missing}")
def require_obs(adata: AnnData, *keys: str) -> None:
"""Raise KeyError if any of the specified obs columns are missing."""
missing = [k for k in keys if k not in adata.obs.columns]
if missing:
raise KeyError(f"Missing required obs columns: {missing}")
def require_var(adata: AnnData, *keys: str) -> None:
"""Raise KeyError if any of the specified var columns are missing."""
missing = [k for k in keys if k not in adata.var.columns]
if missing:
raise KeyError(f"Missing required var columns: {missing}")
def log_params(adata: AnnData, step: str, params: dict) -> None:
"""Record run parameters in adata.uns['scptr']."""
if C.UNS_KEY not in adata.uns:
adata.uns[C.UNS_KEY] = {}
adata.uns[C.UNS_KEY][step] = params
def to_dense_float32(mat) -> np.ndarray:
"""Convert a matrix (sparse or dense) to dense float32."""
if issparse(mat):
mat = np.asarray(mat.todense())
return np.asarray(mat, dtype=np.float32)
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