Fixing typo and tweaking version

AlexanderLabWHOI · Apr 4, 2022 · 1475a5e · 1475a5e
1 parent 2a77709
commit 1475a5e
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Showing 3 changed files with 15 additions and 5 deletions.
diff --git a/VERSION b/VERSION
@@ -1 +1 @@
-2.0.1
+2.0.2
diff --git a/src/EUKulele/manage_steps.py b/src/EUKulele/manage_steps.py
@@ -578,9 +578,16 @@ def manageTaxEstimation(output_dir, mets_or_mags, tax_tab, cutoff_file, consensu
             sys.stderr = open(os.path.join(output_dir, "log", "tax_est_" +
                                            alignment_res[t].split("/")[-1].split(".")[0] +\
                                            ".err"), "w")
+            err_file=os.path.join(output_dir, "log", "tax_est_" +
+                                           alignment_res[t].split("/")[-1].split(".")[0] +\
+                                           ".err")
+            out_file=os.path.join(output_dir, "log", "tax_est_" +
+                                           alignment_res[t].split("/")[-1].split(".")[0] +\
+                                           ".out")
             curr_out = place_taxonomy(tax_tab, cutoff_file, consensus_cutoff, consensus_proportion,\
                                                     prot_tab, use_salmon_counts, names_to_reads,\
-                                                    alignment_res[t], outfiles[t], rerun_rules)
+                                                    alignment_res[t], outfiles[t], rerun_rules,
+                                      err_file,out_file)
         except:
             print("Taxonomic estimation did not complete successfully.",
                   "Check log file for details.")

diff --git a/src/EUKulele/tax_placement.py b/src/EUKulele/tax_placement.py
@@ -212,6 +212,7 @@ def apply_parallel(grouped_data, match_maker, consensus_cutoff, consensus_propor
                                                                tax_cutoffs,
                                                                classes)
                                           for name, group in grouped_data)
+    sys.stdout.flush()
     return pd.concat(resultdf)
 
 def classify_taxonomy_parallel(df, tax_dict, namestoreads, pdict,
@@ -255,17 +256,19 @@ def classify_taxonomy_parallel(df, tax_dict, namestoreads, pdict,
         else:
             # run apply parallel on current chunk
             candidate_df = apply_parallel(chunk.groupby('qseqid'),
-                                          match_maker, consensus_cutoff, tax_dict,
+                                          match_maker, consensus_cutoff, consensus_proportion, tax_dict,
                                           use_counts, tax_cutoffs, classes)
             # account for if better maximum percent identity previously achieved
             outdf = pd.concat([outdf, candidate_df], axis = 0)
         counter = counter + 1
     return outdf
 
 def place_taxonomy(tax_file,cutoff_file,consensus_cutoff,consensus_proportion,prot_map_file,
-                   use_counts,names_to_reads,diamond_file,outfile,rerun):
+                   use_counts,names_to_reads,diamond_file,outfile,rerun,err_file="tax_assign.err",
+                   out_file="tax_assign.out"):
     ''' Find predicted taxonomy using alignment matches. '''
-
+    sys.stdout = open(out_file,"w")
+    sys.stderr = open(err_file,"w") 
     if (os.path.isfile(outfile)) & (not rerun):
         print("Taxonomic placement already complete at", outfile + "; will not re-run step.")
         return pd.read_csv(outfile, sep = "\t")