MIN Better error messages

Also refactoring to simplify internal interfaces and avoid code duplications
BigDataBiology · Oct 18, 2023 · d5cfeaf · psj1997 · Nov 5, 2023 · luispedro
1 parent bdc1087
commit d5cfeaf
Show file tree

Hide file tree

Showing 2 changed files with 23 additions and 25 deletions.
diff --git a/SemiBin/generate_coverage.py b/SemiBin/generate_coverage.py
@@ -71,7 +71,7 @@ def calculate_coverage(depth_stream, bam_file, must_link_threshold, edge=75, is_
         return pd.DataFrame({
             '{0}_mean'.format(bam_file): mean_coverage,
             '{0}_var'.format(bam_file): var,
-            }, index=contigs)
+            }, index=contigs), None
 
 
 def generate_cov(bam_file, bam_index, out, threshold,
@@ -97,39 +97,36 @@ def generate_cov(bam_file, bam_index, out, threshold,
         universal_newlines=True,
         stdout=subprocess.PIPE)
 
+    contig_cov, must_link_contig_cov = calculate_coverage(
+                                    bed_p.stdout,
+                                    bam_file,
+                                    threshold,
+                                    is_combined=is_combined,
+                                    sep=sep,
+                                    contig_threshold=(contig_threshold if sep is None else 1000),
+                                    contig_threshold_dict=(contig_threshold if sep is not None else None))
+
+    if bed_p.wait() != 0:
+        raise OSError(f"Failure in running bedtools ({bam_file})")
+    elif len(contig_cov) == 0:
+        logger.critical(f"Running `bedtools genomecov` did not return an error, but the result is an empty file (processing {bam_file}). "
+                        "Please check your input files: SemiBin expects that they are sorted BAM files.")
+        raise OSError(f"Running bedtools returned an empty file ({bam_file})")
+
+    contig_cov += 1e-5
+    with atomic_write(os.path.join(out, '{}_data_cov.csv'.format(bam_name)), overwrite=True) as ofile:
+        contig_cov.to_csv(ofile)
+
     if is_combined:
-        contig_cov, must_link_contig_cov = calculate_coverage(bed_p.stdout, bam_file, threshold, is_combined = is_combined, sep = sep, contig_threshold = contig_threshold if sep is None else 1000, contig_threshold_dict =  contig_threshold if sep is not None else None)
-        if bed_p.wait() != 0:
-            logger.critical(f"Running `bedtools genomecov` failed ({bam_file}). Please check your input files: SemiBin expects that they are sorted BAM files.")
-            raise OSError(f"Failure running `bedtools genomecov` ({bam_file})")
-        elif len(contig_cov) == 0:
-            logger.critical("Running `bedtools genomecov` did not return an error, but the result is an empty file. Please check your input files: SemiBin expects that they are sorted BAM files.")
-            raise OSError("Running bedtools returned an empty file")
-
-        contig_cov = contig_cov.apply(lambda x: x + 1e-5)
         must_link_contig_cov = must_link_contig_cov.apply(lambda x: x + 1e-5)
         if sep is None:
             abun_scale = (contig_cov.mean() / 100).apply(np.ceil) * 100
             abun_split_scale = (must_link_contig_cov.mean() / 100).apply(np.ceil) * 100
             contig_cov = contig_cov.div(abun_scale)
             must_link_contig_cov = must_link_contig_cov.div(abun_split_scale)
 
-        with atomic_write(os.path.join(out, '{}_data_cov.csv'.format(bam_name)), overwrite=True) as ofile:
-            contig_cov.to_csv(ofile)
-
         with atomic_write(os.path.join(out, '{}_data_split_cov.csv'.format(bam_name)), overwrite=True) as ofile:
             must_link_contig_cov.to_csv(ofile)
-    else:
-        contig_cov = calculate_coverage(bed_p.stdout, bam_file, threshold, is_combined=is_combined, sep = sep,
-                                        contig_threshold = contig_threshold if sep is None else 1000,
-                                        contig_threshold_dict =  contig_threshold if sep is not None else None)
-        if bed_p.wait() != 0:
-            raise OSError("Failure in running bedtools")
-
-        contig_cov = contig_cov.apply(lambda x: x + 1e-5)
-
-        with atomic_write(os.path.join(out, '{}_data_cov.csv'.format(bam_name)), overwrite=True) as ofile:
-            contig_cov.to_csv(ofile)
 
     return bam_file
 

diff --git a/test/test_cov.py b/test/test_cov.py
@@ -40,12 +40,13 @@ def test_cov():
     assert_frame_equal(cov_split, pd.DataFrame([2.609756, 2.554217, 2.682243, 2.574074], index=[
                        'k141_63080_1', 'k141_63080_2', 'k141_0_1', 'k141_0_2'], columns=['cov']))
 
-    cov = calculate_coverage(
+    cov, split = calculate_coverage(
         test_data,
         'test_data',
         must_link_threshold=0,
         is_combined=False,
         contig_threshold=0)
+    assert split is None
     cov.columns = ['mean', 'var']
     assert_frame_equal(cov, pd.DataFrame([[2.581818, 0.606942], [
                        2.627907, 0.252244]], index=['k141_63080', 'k141_0'], columns=['mean', 'var']))