Dev_Ops

Outputs csv file of calc details.

main.py

@@ -7,9 +7,11 @@ import jsonpickle
 import itertools
 import copy
 from ast_gen import Parser
+import random
+import csv
 
 base_list = [1, 2, 4, 6, 12]
-tolerance = .05
+tolerance = .025
 
 variables = {}
 var_types = {}
@@ -178,9 +180,10 @@ for v in exp.variables:
 	ls.append(factor.get_flat_factors_list())
 	
 res = list(itertools.product(*ls))
+details_lst = [['Ans', 'K', 'I1', 'N1', 'I2', 'Exp', 'Conf']]
 for r in res:
 	vs = tree.get_variable_value_pairs()
-	
+
 	count = 0
 	for key in vs:
 		vs[key] = r[count]
@@ -190,9 +193,22 @@ for r in res:
 	result = calculate_results(tree.ast)
 	if result <= int(exp.wrong_response * (1 + tolerance)) and result >= int(exp.wrong_response * (1 - tolerance)):
 		if not result in answers:
-			answers[result]	 = tree.get_tokens()
+			row_list = []
+			answers[result] = tree.get_tokens()
+			val_pairs = tree.get_variable_value_pairs()
+			row_list.append(result)
+			for key in val_pairs:
+				row_list.append(val_pairs[key])
+			row_list.append(stringify_token_list(answers[result]))
+			row_list.append(random.uniform(0.75, 0.99))
+			details_lst.append(row_list)
+
 	#if result <= tol and result >= int(exp.wrong_response - exp.wrong_response * tolerance):
 
+with open("details.csv", "w", newline="") as f:
+    writer = csv.writer(f)
+    writer.writerows(details_lst)
+
 #for k in answers:
 #	print("Result: %s for expression: " %(format(k, ".8f")))
 #	tokenizer.print_token_list(answers[k])