def __init__(self, college_codes, branch_codes, semester):
"""
:type branch_codes: list containing branch codes
of branches selected by user
:type college_codes: list containing college codes
of colleges selected by user
:type semester: integer lies between 0 and 8
"""
ExcelGenerator.__init__(self, college_codes, branch_codes, semester)
def graph_selector(self):
"""
Selects which graph to plot on the basis of fields selected and returns data in
the form such that google charts can plot graph
:return: a list containing data which is to be passed to google charts
"""
# this dictionary maps branch codes to their abbreviations
branch_dict = {
"00": "CE",
"10": "CSE",
"13": "IT",
"20": "EE",
"21": "EN",
"22": "ICE",
"30": "ELE",
"31": "ECE",
"32": "EIE",
"35": "AEI",
"40": "ME",
"41": "MT",
"45": "IPE",
"51": "CHE",
"54": "BT",
}
# this dictionary maps college codes to their abbreviations
college_dict = {
"027": "AKGEC",
"029": "KIET",
"032": "ABES",
"033": "RKGIT",
"054": "BBDNITM",
"063": "GLAITM",
"068": "MIET",
"077": "KNMIET",
"091": "JSSATE",
"097": "GALGOTIAS",
"110": "IERT",
"122": "RAMSWAROOP",
"128": "BHARAT",
"143": "IMS",
"161": "KEC",
"164": "PSIT",
"193": "UNITED",
"520": "INDRAPRASTHA",
}
# this if plots marks for subjects of one college, one branch and one semester
if len(self.colleges) == 1 and len(self.branches) == 1 and len(self.semester) == 1:
# the dictionary to be returned
return_dict = {}
data = [["Subject Codes", "Maximum Obtained", "Average Marks", "Minimum Obtained"]]
return_dict["title"] = (
"Subject-wise analysis: College: "
+ college_dict[self.colleges[0].code]
+ " - Branch: "
+ branch_dict[self.branches[0].code]
+ " - Semester: "
+ str(self.semester[0])
)
# getting results in list of dictionary form by calling result_dict method
results = ExcelGenerator.result_dict(self.colleges[0], self.branches[0], self.semester[0])
if not results:
return_dict["error"] = "Selected branch and semester doesn't exist for this college"
return return_dict
data_list = [[str(sub_code), 0, 0, 300] for sub_code in results[1]]
num_students = 0
maximum_marks = [] # stores maximum marks of each subject
for i in range(len(results[0])):
sub_code_keys = results[0][i]["marks"].keys()
if sub_code_keys == results[1]: # checking if student is normal or not
num_students += 1
if not maximum_marks:
for r in range(len(sub_code_keys)):
maximum_marks.append(GraphGenerator.max_of_subject(results[0][i]["marks"].values()[r][-1]))
for j in range(len(sub_code_keys)):
sub_marks = sum(results[0][i]["marks"][sub_code_keys[j]][1:-1])
data_list[j][2] += sub_marks
if data_list[j][1] < sub_marks:
data_list[j][1] = int(sub_marks)
if data_list[j][3] > sub_marks:
data_list[j][3] = int(sub_marks)
for k in range(len(results[1])):
data_list[k][2] = int(data_list[k][2] / float(num_students))
data_list[k][1] = int(data_list[k][1] / float(maximum_marks[k]) * 100)
data_list[k][2] = int(data_list[k][2] / float(maximum_marks[k]) * 100)
data_list[k][3] = int(data_list[k][3] / float(maximum_marks[k]) * 100)
return_dict["data"] = data + data_list
return return_dict
# this if plots average, max and min marks of each semester for selected college and branch
elif len(self.colleges) == 1 and len(self.branches) == 1 and len(self.semester) != 1:
# dictionary to be returned
return_dict = {}
data = [["Semesters", "Maximum Marks", "Average Marks", "Minimum Marks"]]
return_dict["title"] = (
"Semester-wise analysis: College: "
+ college_dict[self.colleges[0].code]
+ " - Branch: "
+ branch_dict[self.branches[0].code]
)
for sem in self.semester:
# querying marks of each semester
sem_marks = AverageMarks.objects.filter(
college=self.colleges[0], branch=self.branches[0], semester=sem
).first()
if sem_marks:
data.append([str(sem), int(sem_marks.maximum), int(sem_marks.average), int(sem_marks.minimum)])
if len(data) == 1:
return_dict["error"] = "Selected branch doesn't exist for this college"
return return_dict
return_dict["data"] = data
return return_dict
# this if plots average, max, min marks of each branch of selected college and semester
elif len(self.colleges) == 1 and len(self.branches) != 1 and len(self.semester) == 1:
# dictionary to be returned
return_dict = {}
data = [["Branches", "Maximum", "Average", "Minimum"]]
return_dict["title"] = (
"Branch-wise analysis: College: "
+ college_dict[self.colleges[0].code]
+ " - Semester: "
+ str(self.semester[0])
)
for branch in self.branches:
# querying marks of each branch
br_marks = AverageMarks.objects.filter(
college=self.colleges[0], branch=branch, semester=self.semester[0]
).first()
if br_marks:
data.append(
[branch_dict[branch.code], int(br_marks.maximum), int(br_marks.average), int(br_marks.minimum)]
)
if len(data) == 1:
return_dict["error"] = "Selected branch and semester doesn't exist for this college"
return return_dict
return_dict["data"] = data
return return_dict
# plots average marks of each branch for each semester of the selected college
elif len(self.colleges) == 1 and len(self.branches) != 1 and len(self.semester) != 1:
# dictionary to be returned
return_dict = {}
data = [["Semesters"]]
return_dict["title"] = "Semester-wise analysis College: " + college_dict[self.colleges[0].code]
# lists contains branches which exist for selected college
existing_branches = []
# the next two loops for adding existing branches to the list
for sem in self.semester:
for branch in self.branches:
sem_marks = AverageMarks.objects.filter(
college=self.colleges[0], branch=branch, semester=sem
).first()
if sem_marks:
if branch not in existing_branches:
existing_branches.append(branch)
data[0].append(branch_dict[branch.code])
for sem in self.semester:
sem_list = [str(sem)] # individual list to be appended to the nested list
for branch in existing_branches:
sem_marks = AverageMarks.objects.filter(
college=self.colleges[0], branch=branch, semester=sem
).first()
if sem_marks:
sem_list.append(int(sem_marks.average))
else:
sem_list.append(0) # adding zero if marks doesn't exit for that semester
data.append(sem_list)
if len(data) == 1:
return_dict["error"] = "Branches doesn't exist for selected college"
return return_dict
return_dict["data"] = data
return return_dict
# plots marks of selected colleges for given branch and semester
elif len(self.colleges) != 1 and len(self.branches) == 1 and len(self.semester) == 1:
# dictionary to be returned
return_dict = {}
data = [["Colleges", "Maximum", "Average", "Minimum"]]
return_dict["title"] = (
"College-wise analysis of Branch: "
+ branch_dict[self.branches[0].code]
+ " - Semester: "
+ str(self.semester[0])
)
for college in self.colleges:
college_marks = AverageMarks.objects.filter(
college=college, branch=self.branches[0], semester=self.semester[0]
).first()
if college_marks:
data.append(
[
college_dict[college.code],
int(college_marks.maximum),
int(college_marks.average),
int(college_marks.minimum),
]
)
if len(data) == 1:
return_dict["error"] = "No colleges for selected branch and semester"
return return_dict
return_dict["data"] = data
return return_dict
# plots semester-wise marks of different colleges for selected branch
elif len(self.colleges) != 1 and len(self.branches) == 1 and len(self.semester) != 1:
# dictionary to be returned
return_dict = {}
data = [["Semesters"]]
return_dict["title"] = "Semester-wise analysis of Branch: " + branch_dict(self.branches[0].code)
existing_colleges = []
# next 2 for loops for selecting which colleges have selected branch
for sem in self.semester:
for college in self.colleges:
college_marks = AverageMarks.objects.filter(
college=college, branch=self.branches[0], semester=sem
).first()
if college_marks: # add college if marks exist
if college not in existing_colleges:
existing_colleges.append(college)
data[0].append(college_dict[college.code])
# for making data list
for sem in self.semester:
sem_list = [str(sem)]
for i in range(len(existing_colleges)):
college_marks = AverageMarks.objects.filter(
college=existing_colleges[i], branch=self.branches[0], semester=sem
).first()
if college_marks:
sem_list.append(int(college_marks.average))
else:
sem_list.append(0)
data.append(sem_list)
if len(data) == 1:
return_dict["error"] = "Selected branch doesn't exist in selected colleges"
return return_dict
return_dict["data"] = data
return return_dict
# plots branch-wise marks of different colleges(clustered) for selected semester
elif len(self.colleges) != 1 and len(self.branches) != 1 and len(self.semester) == 1:
# dictionary to be returned
return_dict = {}
data = [["Branches"]]
return_dict["title"] = "Branch-wise analysis of Semester: " + str(self.semester[0])
common_branches = []
# selecting common branches
for branch in self.branches:
flag = 1
for college in self.colleges:
college_marks = AverageMarks.objects.filter(
college=college, branch=branch, semester=self.semester[0]
).first()
if not college_marks:
flag = 0
if flag == 1:
common_branches.append(branch)
# making data list if some common branches found
if common_branches:
for branch in common_branches:
branch_list = [branch_dict[branch.code]]
for college in self.colleges:
college_marks = AverageMarks.objects.filter(
college=college, branch=branch, semester=self.semester[0]
).first()
if college_marks:
if college_dict[college.code] not in data[0]:
data[0].append(college_dict[college.code])
branch_list.append(int(college_marks.average))
data.append(branch_list)
return_dict["data"] = data
return return_dict
# checking for common colleges
common_colleges = []
for college in self.colleges:
flag = 1
for branch in self.branches:
branch_marks = AverageMarks.objects.filter(
college=college, branch=branch, semester=self.semester[0]
)
if not branch_marks:
flag = 0
if flag == 1:
common_colleges.append(college)
# making data list if common colleges found
if common_colleges:
for branch in self.branches:
branch_list = [branch_dict[branch.code]]
for college in common_colleges:
college_marks = AverageMarks.objects.filter(
college=college, branch=branch, semester=self.semester[0]
).first()
if college_marks:
if college_dict[college.code] not in data[0]:
data[0].append(college_dict[college.code])
branch_list.append(int(college_marks.average))
data.append(branch_list)
return_dict["data"] = data
return return_dict
# if no common branch or common college found then returning the error message
return_dict["error"] = "Selected branches do not exist in selected colleges"
return return_dict
# plots semester-wise average marks(of all branches) of selected colleges(clustered)
elif len(self.colleges) != 0 and len(self.branches) != 1 and len(self.semester) != 1:
# dictionary to be returned
return_dict = {}
data = [["Semesters"]]
return_dict["title"] = "Semester-wise analysis of different colleges by taking average of all branches"
for sem in self.semester:
sem_list = [str(sem)]
common_branches = []
for branch in self.branches:
flag = 1
for college in self.colleges:
college_marks = AverageMarks.objects.filter(
college=college, branch=branch, semester=sem
).first()
if not college_marks:
flag = 0
if flag == 1:
common_branches.append(branch)
if common_branches:
common_colleges = self.colleges
else:
common_branches = self.branches
common_colleges = []
for college in self.colleges:
flag = 1
for branch in common_branches:
branch_marks = AverageMarks.objects.filter(
college=college, branch=branch, semester=sem
).first()
if not branch_marks:
flag = 0
if flag == 1:
common_colleges.append(college)
for college in common_colleges:
if college_dict[college.code] not in data[0]:
data[0].append(college_dict[college.code])
college_marks = 0
for branch in common_branches:
branch_marks = AverageMarks.objects.filter(college=college, branch=branch, semester=sem).first()
college_marks += branch_marks.average
college_marks = int(college_marks / float(len(common_branches)))
sem_list.append(college_marks)
data.append(sem_list)
if len(data[0]) != 1: # returning data
return_dict["data"] = data
return return_dict
else: # returning error message if no data found
return_dict["error"] = "Selected branches do not exist for selected colleges"
return return_dict
