d2a42aaf1fb53a1e3beeaa90bb80767fccf80eaf,scanpy/preprocess/simple.py,,smp_norm,#Any#,181

Before Change

        X = X[:, counts_per_gene >= 1]  // only consider genes with more than one count
        X = X * np.median(counts_per_cell) / (counts_per_cell[:, np.newaxis] + 1e-6)
    else:
        X = X.tocsc()[:, np.flatnonzero(counts_per_gene.A1 >= 1)].tobsr()
        Norm = sp.sparse.diags(np.median(counts_per_cell.A1) / (counts_per_cell.A.ravel() + 1e-6))
        X = Norm.dot(X).tocsr()
    return X

After Change

        gene_filter = counts_per_gene >= 1
        X = X * np.median(counts_per_cell) / (counts_per_cell[:, np.newaxis] + 1e-6)
    else:
        gene_filter = np.flatnonzero(counts_per_gene.A1 >= 1)
        Norm = sp.sparse.diags(np.median(counts_per_cell.A1) / (counts_per_cell.A.ravel() + 1e-6))
        X = Norm.dot(X.tobsr()).tocsr()
    return X, gene_filter


def smp_norm_weinreb16(X, max_fraction=1, mult_with_mean=False):

Instances