reworked presentation

contenders.py

@@ -37,6 +37,20 @@ def random_positive_leaner(game_data,player_nr):
     #your cool code ended here
     return choice
 
+def random_negative_leaner(game_data,player_nr):
+    #game_data is the array of games so far, either empty(first round) or formatted like this: player_nr [[False, False],[False, False]] (2 rounds of only defections)
+    #player_nr is this players index, so whether they are the first(0) or the second(1) value in a round
+    opponent_nr=1-player_nr
+    #for ease of use this is index of the opponents value
+    choice=False
+    #this function should return either true(coorperate) or false(defect)
+
+    #your cool code goes here
+    if random.randint(0,10)<4:
+        choice=True
+    #your cool code ended here
+    return choice
+
 def i_hate_certain_numbers(game_data,player_nr):
     opponent_nr=1-player_nr
     hated_numbers=[7,13,17,23]

helper_functions.py

@@ -1,10 +1,10 @@
 import statistics
 
-def analyze_results(game_data):
+def analyze_results(game_data,game_nr):
     defect_str="X "
     coorperate_str="O "
-    spacer_str="___"*len(game_data)
-    lines=["These are the results",spacer_str]
+    spacer_str=""*len(game_data)
+    lines=["Game "+str(game_nr)+":",spacer_str]
     str1="Player 1: "
     str2="Player 2: "
     p_1_points=0

main.py

@@ -19,13 +19,13 @@ nr_of_games=300#int(input("How many games should be played?"))
 #                      Put YOUR functions down below
 #XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
 function1=contenders.random_positive_leaner
-function2=contenders.i_hate_certain_numbers
+function2=contenders.random_negative_leaner
 
 for i in range(nr_of_games):
     helper_functions.play_game( games,function1,function2,nr_of_rounds)
-    scores.append(helper_functions.analyze_results(games))
+    scores.append(helper_functions.analyze_results(games,len(scores)+1))
     games=[]
-    
+
 print("Played "+str(nr_of_games)+ " games with "+str(nr_of_rounds)+" rounds each.")
 print("(A huge disparity of the average and median could hint at special behaviour)")
 helper_functions.analyze_scores(scores)