200 time step, with anova

data_analysis.py

@@ -3,7 +3,7 @@ import pandas as pd
 import matplotlib.pyplot as plt
 from datetime import datetime
 
-num_time_step = 501
+num_time_step = 201
 num_iter = 10
 
 env_data = pd.DataFrame(pd.read_excel('env_data.xlsx', engine='openpyxl', sheet_name=0))

env.py

@@ -90,7 +90,7 @@ class Env(ap.Model):
         # self.picture_out()
         self.update()
 
-        if self.t >= 500:
+        if self.t >= 200:
             self.running = False
             self.stop()
         else:

experiment.py

@@ -6,7 +6,7 @@ import datetime
 
 idx_start = 1  # first index is 1 !
 
-n_sample = 30
+n_sample = 50
 
 df_xv = pd.read_csv("xv.csv", header=None, index_col=None).transpose()
 lst_xv_keys = [

result/experiment_result_25.csv

@@ -1,26 +1,26 @@
 ,alpha,percent_search,is_RH_ratio,is_FH_ratio,4,5,out_w_avg_salary,out_w_gini_salary,out_f_avg_profit,out_f_avg_yield,out_f_gini_profit,out_w_percent_hired
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