Reduced iteration count when calculating balances over time.

Also call functions from a main block.

econ-demo.py

@@ -2,17 +2,25 @@
 import pandas as pd
 import matplotlib.pyplot as plt
 
+# it = 0
+
 def compounding_interest(balances, rate=0.05, terms=3):
     if terms <= 0:
         print("Number of terms must be >0!")
         return
-    new_bal = []
-    for balance in balances:
-        b = balance
+    global it 
+    balances_over_time = []
+    current_balances = balances
     for i in range(0, terms):
-            b = b + (b * rate)
+        new_bal = []
+        for balance in current_balances:
+            b = balance + (balance * rate)
             new_bal.append(b)
-    return new_bal
+            # it += 1
+        assert(len(new_bal) == len(balances))
+        balances_over_time.append(new_bal)
+        current_balances = new_bal
+    return balances_over_time
 
 def calc_share_of_wealth(balances):
     total_money = sum(balances)
@@ -23,12 +31,17 @@ def calc_share_of_wealth(balances):
 
 def ubi(balances, dividend=10, terms=3):
     new_bal = []
-    for balance in balances:
-        b = balance
+    balances_over_time = []
+    current_balances = balances
     for i in range(0, terms):
-            b = b + dividend
+        new_bal = []
+        for balance in current_balances:
+            b = balance + dividend
             new_bal.append(b)
-    return new_bal
+        assert(len(new_bal) == len(balances))
+        balances_over_time.append(new_bal)
+        current_balances = new_bal
+    return balances_over_time
 
 def get_balances_over_time(names, balances, func, terms=4, param=0):
     if func is None:
@@ -42,14 +55,15 @@ def get_balances_over_time(names, balances, func, terms=4, param=0):
         'initial' : balances
     }
     df = pd.DataFrame(data)
-    for t in range(1,terms):
-        key = str(t)
+    frame_data = []
     if param == 0:
-            frame = func(balances, terms=t)
+        frame_data = func(balances, terms=terms)
     else:
-            frame = func(balances, terms=t, rate=param)
-        if frame is not None:
-            df[key] = frame
+        frame_data = func(balances, terms=terms, rate=param)
+    assert(len(frame_data) == terms)
+    for i in range(1, terms):
+        key = str(i)
+        df[key] = frame_data[i]
     return df
 
 # -------------
@@ -69,6 +83,7 @@ def illustrate_share_of_wealth():
     df = get_balances_over_time (
         participants, balances, compounding_interest
     )
+    # print(it)
     df["share"] = [val * 100 for val in calc_share_of_wealth(df["3"]) ]
     
     print(df.to_html())
@@ -77,7 +92,7 @@ def illustrate_share_of_wealth():
     print(f"How much money exists after {terms} terms?")
     #### In 222 terms, even C becomes a millionaire.
     nb = compounding_interest(balances, terms=terms)
-    print(nb)
+    print(nb[-1])
     print("\n")
 
     df = get_balances_over_time (
@@ -87,12 +102,12 @@ def illustrate_share_of_wealth():
 
     print("How much money exists after 999 terms?")
     u = ubi(balances, terms=999)
-    print(u)
+    print(u[-1])
 
     print("What is the share of wealth in a UBI economy?")
-    print(calc_share_of_wealth(u))
+    print(calc_share_of_wealth(u[-1]))
+
 
-illustrate_share_of_wealth()
 
 def visualize_ubi(terms=25):
 
@@ -139,8 +154,6 @@ def visualize_ubi(terms=25):
     # plt.show()
     return
 
-visualize_ubi(terms=50)
-
 def calc_total_supply(df):
     total = []
     for key, data in df.items():
@@ -205,4 +218,10 @@ def visualize_inflation(terms=50):
     plt.close()
     # plt.show()
 
+
+
+if __name__ == "__main__":
+
+    illustrate_share_of_wealth()
+    visualize_ubi(terms=50)
     visualize_inflation(terms=75)