small fixes abundance estimation

inference/diff_abundance_kmers.py

@@ -3,6 +3,7 @@ import argparse, subprocess, re
 from os.path import basename, splitext
 from tempfile import TemporaryDirectory
 
+import numpy as np
 import pandas as pd
 
 COMPLEMENT_DICT = {'A': 'T', 'T': 'A', 'C': 'G', 'G': 'C'}
@@ -52,7 +53,7 @@ kmer_list = []
 count_df = pd.concat([target_df] + bg_df_list, axis=1)
 for bg_fn in bg_fn_list:
     count_df.loc[:, f'ratio_{bg_fn}'] = count_df.target / count_df.loc[:, bg_fn]
-    ratio_series = count_df.loc[:, f'ratio_{bg_fn}'].sort_values()
+    ratio_series = count_df.loc[~np.in1d(count_df.index, kmer_list), f'ratio_{bg_fn}'].sort_values()
     kmer_list.extend(ratio_series.iloc[-kmers_per_bg:].index)
     kmer_list.extend(ratio_series.iloc[:kmers_per_bg].index)
 

inference/run_inference.py

@@ -60,8 +60,9 @@ def main(args):
         read_manager_process.join()
         print(f'rutime was {run_time.seconds} s')
         if abundance_mode:
-            abundance_array = abundance_array / max(abundance_array.sum(), 1)
-            abundance_txt = 'kmer,frequency\n' + '\n'.join([f'{km},{ab}' for km, ab in zip(kmer_list, abundance_array)])
+            freq_array = abundance_array / max(abundance_array.sum(), 1)
+            abundance_txt = 'kmer,abundance,frequency\n' + \
+                            '\n'.join([f'{km},{ab}' for km, ab in zip(kmer_list, abundance_array, freq_array)])
             with open(f'{args.out_dir}abundance_estimation.csv', 'w') as fh:
                 fh.write(abundance_txt)