kd script with command line args and as function

meta_data_analysis/kd_df.py

@@ -70,6 +70,9 @@ print('Output filename:', out_filename
       , '\n=============================================================')
 #%% end of variable assignment for input and output files
 #=======================================================================
+#===================
+#calculate KD values: same as the expasy server
+#===================
 #%%specify window size for hydropathy profile computation
 # https://web.expasy.org/protscale/pscale/protscale_help.html
 my_window = 3
@@ -104,6 +107,9 @@ else:
           ,'\nExpected length:', expected_length
           ,'\nActual length:', len(kd_values)
           , '\n=========================================================')
+#===================
+# creating two dfs
+#===================
 #%% make 2 dfs; 1) aa sequence and 2) kd_values. Then reset index for each df 
 # which will allow easy merging of the two dfs.
 
@@ -153,7 +159,9 @@ else:
     print('Checking dtype for after conversion:\n'
           , '\ndtype is:', kd_df.index.dtype
           , '\n=========================================================')
-#%% write file
+#===============
+# writing file
+#===============
 print('Writing file:', out_filename
       , '\nFilename:', out_filename
       , '\nPath:',  outdir
@@ -166,7 +174,9 @@ print('Finished writing:', out_filename
       , '\nNo. of cols:', len(kd_df.columns)
       , '\n=============================================================')
 
-#%% plot
+#===============
+# plot: optional!
+#===============#%% plot
 # http://www.dalkescientific.com/writings/NBN/plotting.html
 
 # FIXME: save fig