Cpm And Pert Programming Python

import os # , sys import sys import pandas import numpy from copy import deepcopy # Write functions to check if two answers are close enough together. # Check if two numbers are close. def match_number(n1,n2,allowed_error=0.01):         if n1!=0:         return abs((n1-n2)/n1)<allowed_error     else:         return abs(n1-n2)<allowed_error # Check if two lists of numbers are close. # Note the lists should consist of numbers. def match_list(list1,list2,allowed_error=0.01):         # Lists must be of the same length.     if len(list1)!=len(list2):         return False         for i in range(len(list1)):         l1 = list1[i]         l2 = list2[i]                 # Check if the dictionary we are comparing to has the correct data structure.         if not (isinstance(l2, int) or isinstance(l2, float)                 or isinstance(l2, numpy.float64)):             return False                 # If the items are not close enough together return False.         if not match_number(l1,l2):             return False             return True # Check if two lists of strings are close. # Note the lists should consist of strings def match_list_string(list1, list2, allowed_error=0.01):     # Lists must be of the same length.     if len(list1) != len(list2):         return False     for i in range(len(list1)):         l1 = list1[i]         l2 = list2[i]         # # Check if the dictionary we are comparing to has the correct data structure.         # if not (isinstance(l2, int) or isinstance(l2, float) or isinstance(l2, numpy.float64)):         #     print('not the correct data structure')         #     return False         # If the items are not similar return False.         if not l1==l2:             print('items are not similar')             return False     return True # Checks if two lists partially match. # It returns the fraction of positions at which the lists match. def partial_match_list(list1,list2,allowed_error=0.01):         # Lists must be of the same length.     if len(list1)!=len(list2):         return 0         matches = 0 # Check how many elements in the lists match.         for i in range(len(list1)):         l1 = list1[i]         l2 = list2[i]                 # Check if the dictionary we are comparing to has the correct data structure.         if not (isinstance(l2, int) or isinstance(l2, float)                 or isinstance(l2, numpy.float64)):             continue                 # If the items are not close enough together return False.         if not match_number(l1,l2,allowed_error):             continue                 matches+=1         return matches/len(list1) # Check if two dictionaries of numbers are close. # Note the dictionaries should consist of numbers. def match_dict(dict1,dict2,allowed_error=0.01):         # Lists must be of the same length.     if dict1.keys()!=dict1.keys():         return False         for k in dict1.keys():         d1 = dict1[k]         d2 = dict2[k]                 # Check if the dictionary we are comparing to has the correct data structure.         if type(1)!=type(d2) and type(0.9)!=type(d2):             return False                 # If the items are not close enough together return False.         if not match_number(d1,d2):             return False             return True # Add the folder submission to the path of files where our scipt looks. # This allows us to call the students' script as student(.py). # The students' code should be in the Submissions. sys.path.insert(0, 'Submissions/') # Generate a list of all the submissions by students. files = [] for file in os.listdir(r"Submissions"):     if file.endswith(".py"):         files.append(os.path.splitext(file)[0]) # The following dictionary will have as keys the different questions and # for each question it will have a list of lists corresponding to test cases. # So test_cases_dict[1][1] is the first test case of the first problem. # test_cases_dict[1][1] is a list of two lists. The first list is the input and # the second list is the output. test_cases_original = dict() # test_cases should be in the same folder as the auto grader. f = open("test_cases.txt", "r") lines = f.readlines() question = 0 reading = 0 # 0 for input, 1 for output for l in lines:     test_case = -1     # Set the current question being read in.     if l[0]=="Q":         # Q indicates that the next question         question = l.strip("\n")         test_cases_original[question]=[]     elif l[0:5]=="Input":         reading = 0         test_case +=1         # Add a list to store input         # One could argue that the list containing the answers is unnecessary.         test_cases_original[question].append([[],[]])     elif l[0:6]=="Output":         reading = 1     # Skip over white lines.     elif l[0]=="\n":         continue     else:         # The eval function evaluates text and interprets it as a variable.         test_cases_original[question][test_case][reading].append(eval(l))     # If the line start with a "{" it is a dictionary # Create a data frame to store the results in. df = pandas.DataFrame(files,columns=["File name"]) # Records the points awarded for each test case. # If you're not interesting in this you can remove this (and related) code. test_case_points = dict() test_case_points['Q1']=[len(files)]*len(test_cases_original['Q1']) test_case_points['Q2']=[len(files)]*len(test_cases_original['Q2']) test_case_points['Q3']=[len(files)]*len(test_cases_original['Q3']) for i in range(len(files)):         student = __import__(files[i])         # The students total score. You can modify this at the end to reflect a grade.     total_points = 0         # Sometimes students modify the input. This ensures our test cases are not modified.     test_cases = deepcopy(test_cases_original)         # Helps in debugging when students make errors.     print(i, files[i])         # Write the student information to the file.     df.at[i,'student 1 name']=student.student1_name     df.at[i,'student 1 surname']=student.student1_surname     df.at[i,'student 2 name']=student.student2_name     df.at[i,'student 2 surname']=student.student2_surname     # QUESTION 1     total_points_Q1 = 2     number_of_test_cases_Q1 = len(test_cases['Q1'])     df.at[i, 'Q1'] = total_points_Q1         for j in range(len(test_cases['Q1'])):         current_test_case = test_cases['Q1'][j]         try:             activities = current_test_case[0][0]             CP,duration = student.Q1(activities)             result = duration             if not match_number(current_test_case[1][0],result):                 df.at[i, 'Q1'] -= total_points_Q1/number_of_test_cases_Q1                 test_case_points['Q1'][j]-=1                 print('Q1-pd incorrect')             result = CP             for list in result:                 if list not in current_test_case[1][1]:                 # if not match_list_string(current_test_case[1][1], result):                     df.at[i, 'Q1'] -= total_points_Q1 / number_of_test_cases_Q1                     test_case_points['Q1'][j] -= 1                     print('Q1-cp incorrect')                         except Exception as e:             print(e)             df.at[i, 'Q1'] -= total_points_Q1/number_of_test_cases_Q1             df.at[i, 'E1'] = str(e)             test_case_points['Q1'][j]-=1     total_points += df.at[i, 'Q1']     # QUESTION 2     total_points_Q2 = 1     number_of_test_cases_Q2 = len(test_cases['Q2'])     df.at[i, 'Q2'] = total_points_Q2         for j in range(len(test_cases['Q2'])):         current_test_case = test_cases['Q2'][j]         try:             prob, activities =current_test_case[0][0]             result = student.Q2(activities, prob)                         if not match_number(current_test_case[1][0],result):                 df.at[i, 'Q2'] -= total_points_Q2/number_of_test_cases_Q2                 test_case_points['Q2'][j]-=1                 print('Q2 incorrect')         except Exception as e:             df.at[i, 'Q2'] -= total_points_Q2/number_of_test_cases_Q2             df.at[i, 'E2'] = str(e)             test_case_points['Q2'][j]-=1     total_points += df.at[i, 'Q2']     # QUESTION 3     total_points_Q3 = 1     number_of_test_cases_Q3 = len(test_cases['Q3'])     df.at[i, 'Q3'] = total_points_Q3     for j in range(len(test_cases['Q3'])):         current_test_case = test_cases['Q3'][j]         try:             duedate, activities= current_test_case[0][0]             cost = student.Q3(activities, duedate)             result = cost             if not match_number(current_test_case[1][0], result):                 df.at[i, 'Q3'] -= total_points_Q3 / number_of_test_cases_Q3                 test_case_points['Q3'][j] -= 1                 print('Q3-cp incorrect')         except Exception as e:             print(e)             df.at[i, 'Q3'] -= total_points_Q3 / number_of_test_cases_Q3             df.at[i, 'E3'] = str(e)             test_case_points['Q3'][j] -= 1     total_points += df.at[i, 'Q3']     df.at[i, 'Total'] = total_points df.to_excel("results.xlsx") # Some code to check how the students performed. print("\nAverage points per test case\n") n_students = len(files) print("Question 1") for i in range(len(test_case_points['Q1'])):     print("Test case {}: {}".format(i,str(test_case_points['Q1'][i]/n_students))) print("\nQuestion 2") for i in range(len(test_case_points['Q2'])):     print("Test case {}: {}".format(i,str(test_case_points['Q2'][i]/n_students))) print("\nQuestion 3") for i in range(len(test_case_points['Q3'])):     print("Test case {}: {}".format(i,str(test_case_points['Q3'][i]/n_students))) import sys # Please fill out the information below student1_name = "" student1_surname = "" student2_name = "" student2_surname = "" print("check") # Fill in your personal information before continuing. if ( student1_name == "" or student1_surname == "" or student2_name == "" or student2_surname == ""): print("Please enter your personal information before continuing.") sys.exit() def Q1(activities): """ calculation of the critical path and its duration :param: activities: dictionary :return: CP: a list of lists of the activities of the critical path, in order from start to end. duration: project duration (integer) """ CP = [] duration = 0 # YOUR CODE GOES HERE. return CP, duration def Q2(activities, prob): """ PERT calculation of the project duration based on a probability of finishing if the company wants to promise a duration with a certain probability, based on the probability, what duration can they promise? :param: activities: dictionary prob: probability of finishing (float between 0 and 1) :return: duration: duration of the project for that probability (integer) """ duration = 0 # YOUR CODE GOES HERE. return duration def Q3(activities, duedate): """ Crashing calculation of the project duration when activities are cost partial crashing is allowed backtracking is not needed the new project duration should become lower than or equal to the duedate :param: activities: dictionary duedate: aimed project duration (integer) :return: cost: total costs of crashing (integer) """ cost = 0 # YOUR CODE GOES HERE. return cost Q1 Input { 'A' : [[], 14],'B' : [[], 10],'C' : [['A', 'B'], 3], 'D' : [['B'], 7], 'E' : [['C', 'D'], 4],'F' : [['E'], 10]} Output 31 [['A', 'C', 'E', 'F'], ['B', 'D', 'E', 'F']] Input { 'A': [[], 110], 'B': [[], 260], 'C': [[], 180], 'D': [['A', 'B', 'C'], 30], 'E': [['D'], 60], 'F': [['A', 'B', 'C'], 140], 'G': [['D'], 150], 'H': [['G'], 270], 'I': [['D', 'F'], 100], 'J': [['G'], 330], 'K': [['E'], 240], 'L': [['K'], 300], 'M': [['K', 'H'], 190], 'N': [['H', 'J'], 60]} Output 900 [['B', 'D', 'G', 'H', 'M']] Q2 Input 0.014, { 'A':[[], 6.5,7.5,14.5], 'B':[[],8.5,10.5,12.5], 'C':[['A'],2.5,3.5,4.5], 'D': [['A'],6.5,7.5,8.5], 'E':[['B', 'C'],5.5,5.5,9.5], 'F':[['B','C'],5.5,7.5,9.5], 'G':[['D', 'E'],4.5,6.5,8.5], 'H':[['F'],2.5,3.5,3.5]} Output 21 Q3 Input 16, { 'A' : [[], 3, 3, 30, 30], 'B' : [[], 6, 6, 60, 60], 'C' : [[], 8, 7, 80, 120], 'D' : [['A'], 7, 7, 70, 70], 'E' : [['B'], 5, 5, 50, 50], 'F' : [['C'], 10, 6, 100, 180], 'G' : [['C'], 4, 4, 40, 40], 'H' : [['D', 'E', 'F'], 5, 2, 50, 80], 'I' : [['G'], 6, 3, 60, 150]} Output 700