Fix zero division

Author: FarrasArias

bottle_air/db.py

@@ -232,7 +232,7 @@ def load_csvs(file_list):
         ceil = float(max(column))
         norms[header] = (floor, ceil)
         if ceil == floor:
-	  data[header] = 0
+	  data[header] = [0] * len(column)
         else:
           data[header] = [(x-floor)/(ceil - floor) for x in column] #NEQP (Si es buena idea normalizar SIEMPRE entre -1 y 1? Tambien he visto normalizaciones mas grandes o pequenias, creo, dependiendo de la naturaleza de los datos)
 

bottle_air/model.py

@@ -199,9 +199,9 @@ def init_model(self):
       model.compile(loss='mse',
             optimizer=optimizer,
             metrics=['accuracy'])
-      nb_epoch = 30
+      nb_epoch = 100
       if persist:
-        nb_epoch = 200
+        nb_epoch = 300
 
       model_name = str(hp).replace('{', '').replace('}', '')
       if persist:
@@ -289,13 +289,17 @@ def normalize_float(self, val, header, reverse=False):
     """
     if reverse:
       return val * (self.norms[header][1] - self.norms[header][0]) + self.norms[header][0]
+    
+    # Avoid division by zero for zeroed out columns.
+    if self.norms[header][1] == self.norms[header][0]:
+      return val
     return (val-self.norms[header][0])/(self.norms[header][1] - self.norms[header][0])
 
   def normalize_values(self, values):
     """ Normalizes all non-string features in 'values'. """
     for header, column in values.iteritems():
       if self.types[header] != 'str':
-        values[header] = [self.normalize_float(float(x), header) for x in column]
+	values[header] = [self.normalize_float(float(x) if x else 0.0, header) for x in column]
 
   def intergerize_string(self, data):
     """ Transforms all string features into integer arrays. """

bottle_air/server.py

@@ -162,8 +162,8 @@ def infer():
 
   if 'values' not in args:
     return json.dumps({'status': 'ERROR', 'why': 'No values specified'})
-  print(args['handle'])
-  print(args['values'])
+  print args['handle']
+  print args['values']
   outputs = model.infer(json.loads(args['values']))
   return json.dumps({'status': 'OK', 'result': outputs})
 
@@ -176,4 +176,4 @@ def infer():
 args = parser.parse_args()
 
 config.tf_server = tf.train.Server.create_local_server()
-run(app, reloader=True, host='localhost', port=8012, server='cherrypy')
+run(app, reloader=True, host='0.0.0.0', port=8012, server='cherrypy')

reqs.txt

@@ -7,7 +7,7 @@ certifi==2017.4.17
 cffi==1.10.0
 cheroot==5.4.0
 CherryPy==8.9.0
-cryptography==1.8.1
+cryptography==2.2.2
 decorator==4.0.11
 enum34==1.1.6
 funcsigs==1.0.2

start.sh

@@ -14,6 +14,8 @@ virtualenv --distribute .
 
 source bin/activate
 
+easy_install distribute
+
 pip install --upgrade pip
 
 pip install -r reqs.txt