# HG changeset patch
# User bimib
# Date 1574678430 18000
# Node ID 7b1971251c63f60003e873785935ba71af4e7b44
# Parent  1a97d153762330d0f622fe4b5b19e0a7b98e8c83
Uploaded

diff -r 1a97d1537623 -r 7b1971251c63 Marea/marea.py
--- a/Marea/marea.py	Sat Oct 26 07:49:31 2019 -0400
+++ b/Marea/marea.py	Mon Nov 25 05:40:30 2019 -0500
@@ -5,7 +5,6 @@
 import scipy.stats as st
 import collections
 import lxml.etree as ET
-import shutil
 import pickle as pk
 import math
 import os
@@ -201,6 +200,7 @@
         l = l[1:]
     return (tmp, err)
 
+
 def replace_gene(l, d):
     if l =='and' or l == 'or':
         return l
@@ -577,7 +577,7 @@
 ############################ gene #############################################
 
 def data_gene(gene, type_gene, name, gene_custom):
-    args = process_args(sys.argv)
+    args = process_args(sys.argv)    
     for i in range(len(gene)):
         tmp = gene.iloc[i, 0]
         if tmp.startswith(' ') or tmp.endswith(' '):
@@ -586,6 +586,7 @@
                collections.Counter(gene[gene.columns[0]]).items() if count > 1]
     pat_dup = [item for item, count in 
                collections.Counter(list(gene.columns)).items() if count > 1]
+
     if gene_dup:
         if gene_custom == None:
             if args.rules_selector == 'HMRcore':
@@ -607,12 +608,14 @@
     if pat_dup:
         warning('Warning: duplicated label\n' + str(pat_dup) + 'in ' + name + 
                 '\n')
+        
     return (gene.set_index(gene.columns[0])).to_dict()
 
 ############################ resolve ##########################################
 
 def resolve(genes, rules, ids, resolve_none, name):
     resolve_rules = {}
+    names_array = []
     not_found = []
     flag = False
     for key, value in genes.items():
@@ -630,7 +633,7 @@
                     tmp_resolve.append(ris)
                     flag = True
             else:
-                tmp_resolve.append(None)        
+                tmp_resolve.append(None)    
         resolve_rules[key] = tmp_resolve
     if flag is False:
         warning('Warning: no computable score (due to missing gene values)' +
@@ -662,7 +665,7 @@
 
 ############################ create_ras #######################################
 
-def create_ras (resolve_rules, dataset_name, single_ras):
+def create_ras (resolve_rules, dataset_name, single_ras, rules, ids):
 
     if resolve_rules == None:
         warning("Couldn't generate RAS for current dataset: " + dataset_name)
@@ -673,6 +676,8 @@
                 geni[i] = 'None'
                 
     output_ras = pd.DataFrame.from_dict(resolve_rules)
+    
+    output_ras.insert(0, 'Reactions', ids)
     output_to_csv = pd.DataFrame.to_csv(output_ras, sep = '\t', index = False)
     
     if (single_ras):
@@ -741,7 +746,7 @@
     create_svg = check_bool(args.generate_svg)
     create_pdf = check_bool(args.generate_pdf)
     generate_ras = check_bool(args.generate_ras)
-    
+
     os.makedirs('result')
 
     if generate_ras:
@@ -771,10 +776,10 @@
             ids, rules = load_id_rules(recon.get(type_gene))
         elif args.rules_selector == 'Custom':
             genes = data_gene(dataset, type_gene, name, gene_in_rule)
-                
+        
         resolve_rules, err = resolve(genes, rules, ids, resolve_none, name)
 
-        create_ras(resolve_rules, name, True)
+        create_ras(resolve_rules, name, True, rules, ids)
           
         if err != None and err:
             warning('Warning: gene\n' + str(err) + '\nnot found in class '
@@ -802,10 +807,11 @@
             elif args.rules_selector == 'Custom':
                 genes = data_gene(dataset, type_gene, name, gene_in_rule)
                 
+                
             resolve_rules, err = resolve(genes, rules, ids, resolve_none, name)
 
             if generate_ras:
-                create_ras(resolve_rules, name, False)
+                create_ras(resolve_rules, name, False, rules, ids)
             
             if err != None and err:
                 warning('Warning: gene\n' + str(err) + '\nnot found in class '
@@ -837,7 +843,7 @@
         if resolve_rules != None:
             class_pat = split_class(classes, resolve_rules)
             if generate_ras:
-                create_ras(resolve_rules, name, False)
+                create_ras(resolve_rules, name, False, rules, ids)
     
     	
     if args.rules_selector == 'Custom':
diff -r 1a97d1537623 -r 7b1971251c63 Marea/marea.xml
--- a/Marea/marea.xml	Sat Oct 26 07:49:31 2019 -0400
+++ b/Marea/marea.xml	Mon Nov 25 05:40:30 2019 -0500
@@ -1,4 +1,4 @@
-<tool id="MaREA" name="Metabolic Reaction Enrichment Analysis" version="1.0.5">
+<tool id="MaREA" name="Metabolic Reaction Enrichment Analysis" version="1.0.6">
     <description></description>
     <macros>
         <import>marea_macros.xml</import>