[july] s2/s4 support 24 model's weight

s2.py

@@ -112,7 +112,8 @@ def produce_part3(sum_result, lo_weight):
                 lo_xmodels = lo_xmodels.union(set(sum_result[i]))
         lo_xmodels = sorted(list(lo_xmodels))
         for l in lo_xmodels:
-            lo_sum = [0, 0, 0, 0, 0, 0]
+            ## build container to store sum of all weight
+            lo_sum = [0 for k in xrange(0, 25)]
             if l not in lo_weight:
                 continue
             for i in ii:
@@ -120,7 +121,7 @@ def produce_part3(sum_result, lo_weight):
                     continue
                 lo_sum = [
                     float(x) + float(y) for x, y
-                    in zip(lo_weight[l][i], lo_sum)]
+                    in zip(lo_weight[l][i][9:], lo_sum)]
             rows.append([l] + lo_sum)
 
         _f = '%s-3.csv' % ii
@@ -131,8 +132,8 @@ def main(*argv):
     _r = process_s2_data()
     _lw = process_lo_weight()
     produce_s2_part1(_r['sum'])
-    # produce_s2_part2(_r['rank'])
-    # produce_part3(_r['sum'], _lw)
+    produce_s2_part2(_r['rank'])
+    produce_part3(_r['sum'], _lw)
 
 
 if __name__ == '__main__':

s4.py

@@ -36,7 +36,8 @@ def get_weight(xmodel):
     with open(fpath, 'rb') as f:
         rows = csv.reader(f)
         for r in rows:
-            result[r[0]] = [r[1], r[2], r[3], r[4], r[5], r[6]]
+            # result[r[0]] = [r[1], r[2], r[3], r[4], r[5], r[6]]
+            result[r[0]] = [r[k] for k in xrange(1, 26)]
     return result