Changed loglinear regression into Y = b * X^t.

ace.py

@@ -23,7 +23,7 @@
                        "firm_info_10_10_10.csv", "firm_info_100_100_100.csv", "firm_info_10000_1000_100_10.csv", "firm_info_200000.csv"]
 
 regressions = ['loglinear','bayes', 'linear']
-regression_types = ["total", "average"]
+regression_types = ["average", "total"]
 
 distribute_subsidies = [True, False]
 disturb_results = [True, False]

firm.py

@@ -17,7 +17,7 @@ def __init__(self, i, workers, clf, history, disturb_result, regression):
     def step(self, subsidies):
         print("Firm step " + str(time.time()))
         if self.regression == 'loglinear':
-            self.sales = self.clf.predict([[self.workers * subsidies]])
+            self.sales = math.exp(self.clf.predict([[math.log(self.workers * subsidies)]]))
         else:
             self.sales = self.clf.predict([[self.workers, subsidies]])
         if self.disturb_result:

mape.py

@@ -2,4 +2,6 @@ def mape(y_pred, y_true):
     res = 0
     for i in range(len(y_true)):
         res += abs((y_pred[i] - y_true[i])/y_true[i])
-    return res[0]/len(y_true) * 100
+    if isinstance(res, list):
+        return res[0]/len(y_true) * 100
+    return res / len(y_true) * 100

world.py

@@ -28,8 +28,10 @@ def __init__(self, employees, firm_info, history, distribute_subsidies, disturb_
             self.clf.fit(self.history[['workers', 'subsidies']], self.history['sales'])
         elif regression == 'loglinear':
             self.history['product'] = self.history.workers.mul(self.history.subsidies)
-            self.clf = linear_model.LinearRegression(fit_intercept=False, normalize=False)
-            self.clf.fit(self.history[['product']], self.history[['sales']])
+            self.history['log_product'] = self.history['product'].apply(math.log)
+            self.history['log_sales'] = self.history['sales'].apply(math.log)
+            self.clf = linear_model.LinearRegression(fit_intercept=True)
+            self.clf.fit(self.history[['log_product']], self.history[['log_sales']])
         self.create_firms(firm_info, self.history, self.clf, employees, disturb_result, disturb_coefficients, regression)
         self.employees = employees
         self.sales = []