Refine figures as requested by journal

change_new_fig.py

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+import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+from datetime import datetime
+
+num_time_step = 201
+num_iter = 10
+
+env_data = pd.DataFrame(pd.read_excel('env_data.xlsx', engine='openpyxl', sheet_name=0))
+
+assert env_data.shape[0] == num_iter * (num_time_step + 1), f"{env_data.shape[0]}, {num_iter * (num_time_step + 1)}"
+
+lst_df = []
+for i in range(num_iter):
+    df_tmp = env_data.iloc[i * (num_time_step + 1): (i + 1) * (num_time_step + 1), 1:]
+    lst_df.append(df_tmp)
+
+lst_column = lst_df[0].columns
+# print(lst_column)
+# lst_column = [lst_column[2], lst_column[0]]
+
+dct_y = {
+    'out_w_avg_salary': 'Avg. salary of workers',
+    'out_w_gini_salary': "Gini index of workers' salaries (unit: 1)",
+    'out_f_avg_profit': "Avg. profit of firms",
+    'out_f_avg_yield': "Avg. yield of firms (unit: 1)",
+    'out_f_gini_profit': "Gini index of firms' profit (unit: 1)",
+    'out_w_percent_hired': "% hired workers (unit: %)"
+}
+
+dct_file_name = {
+    'out_w_avg_salary': 'd',
+    'out_w_gini_salary': "e",
+    'out_f_avg_profit': "a",
+    'out_f_avg_yield': "c",
+    'out_f_gini_profit': "b",
+    'out_w_percent_hired': "f"
+}
+
+for str_col in lst_column:
+    x = np.arange(num_time_step+1)
+    for df in lst_df:
+        y = np.array(df[str_col]).flatten()
+        if str_col == 'out_f_avg_profit':
+            y /= 10000000000
+            plt.ylabel(dct_y[str_col] + r' (unit: $1 \times 10^{10}$ CNY)')
+        elif str_col == 'out_w_avg_salary':
+            y /= 1000000000
+            plt.ylabel(dct_y[str_col] + r' (unit: $1 \times 10^{9}$ CNY)')
+        elif str_col == 'out_w_percent_hired':
+            from matplotlib.ticker import PercentFormatter
+            plt.gca().yaxis.set_major_formatter(PercentFormatter(1, decimals=0))
+            plt.ylabel(dct_y[str_col])
+        else:
+            plt.ylabel(dct_y[str_col])
+        plt.xlabel('Time step')
+        plt.plot(x, y)
+    # plt.show()
+    # plt.close()
+    # plt.savefig(f"{str_col}-{datetime.today().strftime('%Y-%m-%d')}.pdf", bbox_inches="tight")
+    plt.savefig(f"Fig3{dct_file_name[str_col]}.pdf", bbox_inches="tight")
+    plt.close()