No more numpy kwarg in pybigwig values().

PRO-seq/PRO-seq.snakefile

@@ -1194,7 +1194,7 @@ rule merge_bigwig_reps:
                         warn(f"The bigwig files without {chrom} will be skipped.\n")
                     to_use = [bw for bw in bws if chrom in bw.chroms()]
                     if to_use:
-                        means = np.nanmean(np.vstack([bw.values(chrom, 0, chrom_len, numpy=True) for bw in to_use]), axis=0)
+                        means = np.nanmean(np.vstack([bw.values(chrom, 0, chrom_len) for bw in to_use]), axis=0)
                     else:
                         means = np.zeros(chrom_len)
                     # bin size is 10

RNA_Seq_Cecere/RNA-seq.snakefile

@@ -1510,7 +1510,7 @@ rule merge_bigwig_reps:
                         warn(f"The bigwig files without {chrom} will be skipped.\n")
                     to_use = [bw for bw in bws if chrom in bw.chroms()]
                     if to_use:
-                        means = np.nanmean(np.vstack([bw.values(chrom, 0, chrom_len, numpy=True) for bw in to_use]), axis=0)
+                        means = np.nanmean(np.vstack([bw.values(chrom, 0, chrom_len) for bw in to_use]), axis=0)
                     else:
                         means = np.zeros(chrom_len)
                     # bin size is 10

Ribo-seq/Ribo-seq.snakefile

@@ -1868,7 +1868,7 @@ rule merge_bigwig_reps:
                         warn(f"The bigwig files without {chrom} will be skipped.\n")
                     to_use = [bw for bw in bws if chrom in bw.chroms()]
                     if to_use:
-                        means = np.nanmean(np.vstack([bw.values(chrom, 0, chrom_len, numpy=True) for bw in to_use]), axis=0)
+                        means = np.nanmean(np.vstack([bw.values(chrom, 0, chrom_len) for bw in to_use]), axis=0)
                     else:
                         means = np.zeros(chrom_len)
                     # bin size is 10
@@ -1905,8 +1905,8 @@ rule make_bigwig_ratios:
                 bw_out.addHeader(list(chrom_sizes.items()))
                 for (chrom, chrom_len) in bw_out.chroms().items():
                     assert cond_bw.chroms()[chrom] == chrom_len
-                    #ratios = np.divide(cond_bw.values(chrom, 0, chrom_len, numpy=True), ref_bw.values(chrom, 0, chrom_len, numpy=True))
-                    ratios = np.log2(np.divide(cond_bw.values(chrom, 0, chrom_len, numpy=True), ref_bw.values(chrom, 0, chrom_len, numpy=True)))
+                    #ratios = np.divide(cond_bw.values(chrom, 0, chrom_len), ref_bw.values(chrom, 0, chrom_len))
+                    ratios = np.log2(np.divide(cond_bw.values(chrom, 0, chrom_len), ref_bw.values(chrom, 0, chrom_len)))
                     # bin size is 10
                     bw_out.addEntries(chrom, 0, values=np.nan_to_num(ratios[0::10]), span=10, step=10)
                 bw_out.close()

small_RNA-seq/small_RNA-seq.snakefile

@@ -2841,7 +2841,7 @@ rule merge_bigwig_reps:
                         raise
                     to_use = [bw for bw in bws if chrom in bw.chroms()]
                     if to_use:
-                        means = np.nanmean(np.vstack([bw.values(chrom, 0, chrom_len, numpy=True) for bw in to_use]), axis=0)
+                        means = np.nanmean(np.vstack([bw.values(chrom, 0, chrom_len) for bw in to_use]), axis=0)
                     else:
                         means = np.zeros(chrom_len)
                     # bin size is 10
@@ -2881,8 +2881,8 @@ rule make_bigwig_ratios:
                 bw_out.addHeader(list(chrom_sizes.items()))
                 for (chrom, chrom_len) in bw_out.chroms().items():
                     assert cond_bw.chroms()[chrom] == chrom_len
-                    #ratios = np.divide(cond_bw.values(chrom, 0, chrom_len, numpy=True), ref_bw.values(chrom, 0, chrom_len, numpy=True))
-                    ratios = np.log2(np.divide(cond_bw.values(chrom, 0, chrom_len, numpy=True), ref_bw.values(chrom, 0, chrom_len, numpy=True)))
+                    #ratios = np.divide(cond_bw.values(chrom, 0, chrom_len), ref_bw.values(chrom, 0, chrom_len))
+                    ratios = np.log2(np.divide(cond_bw.values(chrom, 0, chrom_len), ref_bw.values(chrom, 0, chrom_len)))
                     # bin size is 10
                     bw_out.addEntries(chrom, 0, values=np.nan_to_num(ratios[0::10]), span=10, step=10)
                 bw_out.close()