finished unit testing

Author: mdhumphries

UnitTestData.csv

@@ -0,0 +1,14 @@
+Choice,CuePosition,Reward,go_left,go_right,go_cued,go_uncued,sticky,alternate,win_stay_spatial,win_stay_cued,lose_shift_spatial,lose_shift_cued
+left,left,yes,success,failure,success,failure,null,null,null,null,null,null
+left,right,yes,success,failure,failure,success,success,failure,success,failure,null,null
+left,left,no,success,failure,success,failure,success,failure,success,failure,null,null
+left,right,no,success,failure,failure,success,success,failure,null,null,failure,success
+right,left,yes,failure,success,failure,success,failure,success,null,null,success,failure
+right,right,yes,failure,success,success,failure,success,failure,success,failure,null,null
+right,left,no,failure,success,failure,success,success,failure,success,failure,null,null
+right,right,no,failure,success,success,failure,success,failure,null,null,failure,success
+right,right,yes,failure,success,success,failure,success,failure,null,null,failure,failure
+left,right,yes,success,failure,failure,success,failure,success,failure,failure,null,null
+right,left,yes,failure,success,failure,success,failure,success,failure,success,null,null
+right,left,no,failure,success,failure,success,success,failure,success,success,null,null
+left,left,no,success,failure,success,failure,failure,success,null,null,success,success

__pycache__/strategymodels.cpython-39.pyc

@@ -84,10 +84,13 @@ def alternate(rows):
     # checks if the subject made a different choice on this trial from the previous obe
     nTrials = len(rows)
      # "at" selects the value at the row/column location in the dataframe
-    if nTrials > 1 and rows.at[nTrials-1,'Choice'] != rows.at[nTrials-2,'Choice']:      # check the current trial's choice
+    if nTrials == 1:
+        trial_type = "null" # undefined on first trial
+    elif nTrials > 1 and rows.at[nTrials-1,'Choice'] != rows.at[nTrials-2,'Choice']:      # check the current trial's choice
         trial_type = "success"
-    else:
+    else: 
         trial_type = "failure"
+        
     return trial_type
 
 
@@ -134,7 +137,9 @@ def sticky(rows):
     # checks if the subject made the same choice on this trial as the previous one
     nTrials = len(rows)
      # "at" selects the value at the row/column location in the dataframe
-    if nTrials > 1 and rows.at[nTrials-1,'Choice'] == rows.at[nTrials-2,'Choice']:      # check the current trial's choice
+    if nTrials == 1:
+         trial_type = "null" # undefined on first trial
+    elif nTrials > 1 and rows.at[nTrials-1,'Choice'] == rows.at[nTrials-2,'Choice']:      # check the current trial's choice
         trial_type = "success"
     else:
         trial_type = "failure"
@@ -143,7 +148,7 @@ def sticky(rows):
 
 
 def win_stay_cued(rows):
-    # checks if the subject made the same cued choice on this trial after being rewarded on the previous one
+    # checks if the subject made the same cue-driven choice on this trial after being rewarded on the previous one
     trial_type = "null"   # default is that this trial does not meet criterion for win-stay
 
     nTrials = len(rows)

strategymodels.py

@@ -11,59 +11,69 @@
 import pandas as pd
 import strategymodels
 
-# make test dataframe
-test_data_for_rules = {'Choice' : ['left','left','left','left','right','right','right','right'],
-        'CuePosition': ['left','right','left','right','left','right','left','right'],
-        'Reward': ['yes','yes','no','no','yes','yes','no','no']}
-TestData = pd.DataFrame(test_data_for_rules)
+# load test dataframe
+# set na_filter = False to load "null" as strings
+UnitTestData = pd.read_csv('UnitTestData.csv',na_filter=False)
 
-# target results for rules
-
-go_left_target = ['success','success','success','success','failure','failure','failure','failure']
-go_right_target = ['failure','failure','failure','failure','success','success','success','success']
-go_cued_target = ['success','failure','success','failure','failure','success','failure','success']
-go_uncued_target = ['failure','success','failure','success','success','failure','success','failure']
+TestResults = pd.DataFrame();
 
 #%% run rule strategy models
 trial_type_left = []; trial_type_right = []; trial_type_cued = []; trial_type_uncued = [];
-for trial in range(len(TestData)):
-    rows_of_data = TestData.iloc[0:trial+1]     # select all rows of data up to the curren trial; is trial+1 as dataframe includes column row as row 0????
+for trial in range(len(UnitTestData)):
+    rows_of_data = UnitTestData.iloc[0:trial+1]     # select all rows of data up to the curren trial; is trial+1 as dataframe includes column row as row 0????
     trial_type_left.append(strategymodels.go_left(rows_of_data))         # test whether go-left was used       
     trial_type_right.append(strategymodels.go_right(rows_of_data))
     trial_type_cued.append(strategymodels.go_cued(rows_of_data))  
     trial_type_uncued.append(strategymodels.go_uncued(rows_of_data))  
 
 #%% did they pass the tests?    
-print('Go left passed?')    
-print(trial_type_left == go_left_target)
+TestResults['go_left_result'] = UnitTestData['go_left'].eq(trial_type_left)
+TestResults['go_right_result'] = UnitTestData['go_right'].eq(trial_type_right)
+TestResults['go_cued_result'] = UnitTestData['go_cued'].eq(trial_type_cued)
+TestResults['go_uncued_result'] = UnitTestData['go_uncued'].eq(trial_type_uncued)
 
-print('Go right passed?')    
-print(trial_type_right == go_right_target)
+# print to screen
+print('Go left passed? ' + str(TestResults['go_left_result'].all()))
 
-print('Go cued passed?')    
-print(trial_type_cued == go_cued_target)
-    
-print('Go uncued passed?')    
-print(trial_type_uncued == go_uncued_target)
+print('Go right passed? ' + str(TestResults['go_right_result'].all()))    
+
+print('Go cued passed? ' + str((TestResults['go_cued_result'].all())))
+
+print('Go uncued passed? ' + str(TestResults['go_uncued_result'].all()))    
 
 #%%
 #  test Explore strategy models
 # 
 
-# extend test data to include all win-stay and lose-shift test cases
-test_data_for_rules['Choice'].append('right','left','right','right','left')
-test_data_for_rules['CuePosition'].append('right','right','left','left','left')
-test_data_for_rules['Reward'].append('yes','yes','yes','no','no')
-
-TestData = pd.DataFrame(test_data_for_rules)  # overwrite dataframe
+trial_type_alternate = []; trial_type_sticky = []; trial_type_win_stay_spatial= []; 
+trial_type_win_stay_cued = []; trial_type_lose_shift_spatial= []; trial_type_lose_shift_cued= []; 
+
+for trial in range(len(UnitTestData)):
+    rows_of_data = UnitTestData.iloc[0:trial+1]     # select all rows of data up to the curren trial; is trial+1 as dataframe includes column row as row 0????  
+    trial_type_alternate.append(strategymodels.alternate(rows_of_data)) 
+    trial_type_sticky.append(strategymodels.sticky(rows_of_data)) 
+    trial_type_win_stay_spatial.append(strategymodels.win_stay_spatial(rows_of_data)) 
+    trial_type_win_stay_cued.append(strategymodels.win_stay_cued(rows_of_data)) 
+    trial_type_lose_shift_spatial.append(strategymodels.lose_shift_spatial(rows_of_data)) 
+    trial_type_lose_shift_cued.append(strategymodels.lose_shift_cued(rows_of_data)) 
+    
+# did they pass test?    
+TestResults['alternate_result'] = UnitTestData['alternate'].eq(trial_type_alternate)
+TestResults['sticky_result'] = UnitTestData['sticky'].eq(trial_type_sticky)
+TestResults['win_stay_spatial_result'] = UnitTestData['win_stay_spatial'].eq(trial_type_win_stay_spatial)
+TestResults['win_stay_cued_result'] = UnitTestData['win_stay_cued'].eq(trial_type_win_stay_cued)
+TestResults['lose_shift_spatial_result'] = UnitTestData['lose_shift_spatial'].eq(trial_type_lose_shift_spatial)
+TestResults['lose_shift_cued_result'] = UnitTestData['lose_shift_cued'].eq(trial_type_lose_shift_cued)
 
-# define target results for exploration rules (null, success, failure)
+# print to screen
+print('Alternate passed? ' + str(TestResults['alternate_result'].all()))
 
+print('Sticky passed? ' + str(TestResults['sticky_result'].all()))    
 
-# run explore strategy models
-trial_type_alternate = []; trial_type_sticky = []; trial_type_win_stay_spatial= []; 
-trial_type_win_stay_cue = []; trial_type_lose_shift_spatial= []; trial_type_lose_shift_cue = []; 
+print('Win-stay-spatial passed? ' + str(TestResults['win_stay_spatial_result'].all()))    
+    
+print('Win-stay-cued passed? ' + str(TestResults['win_stay_cued_result'].all()))    
 
-for trial in range(len(TestData)):
-    rows_of_data = TestData.iloc[0:trial+1]     # select all rows of data up to the curren trial; is trial+1 as dataframe includes column row as row 0????  
-    
+print('Lose-shift-spatial passed? ' + str(TestResults['lose_shift_spatial_result'].all()))    
+    
+print('Lose-shift-cued passed? ' + str(TestResults['lose_shift_cued_result'].all()))