def test_add_total_score(self):
ep.ExcelOutput.write_excel(self.excel,1)
ep.ExcelOutput.add_total_score(self.excel)
ep.ExcelOutput.close_workbook(self.excel)
array = fi.readfile(self.file_name)
array = fi.transpose(array)
self.assertTrue(array[1][5] == 4)
def test_add_correlation(self):
ep.ExcelOutput.write_excel(self.excel,0)
ep.ExcelOutput.add_total_score(self.excel)
ep.ExcelOutput.add_correlation(self.excel, [5,5,5,5], 'row')
ep.ExcelOutput.close_workbook(self.excel)
array = fi.readfile(self.file_name)
array = fi.transpose(array)
self.assertTrue(array[1][6] == 5)
def test_transpose_matrix(self):
self.assertTrue(
ad.transpose_matrix(self.data_shoudlbe) == fi.transpose(
self.data_shoudlbe))
def setUp(self) -> None:
# The path should be configured as the full path of the test data file. TODO: I don't really understand why the relative path not working.
path = "/Users/Apple/Documents/Google-Sync/SWEN90014 Master Project/Project/swen90014-2019-rv-quoll" \
"/testdata/SampleAssessmentResult.xlsx"
self.data = fi.readfile(path)
self.data = fi.transpose(self.data)
fi.sort_2d_array_mark(self.data)
# After reading from excel_importing module, the data read transformed as original_data.
# Here only performing unit test for guttman-analysis module and aussmes that the data imported are correct.
self.original_data = [[
'', 'etc…', 'Recognises steps in the teaching and learning cycle.',
'Defines 21st century competencies', 'etc…', 'etc…', 'etc…',
'etc…', 'Distinguishes between competence and content.',
'Identifies levels of competence.', 'etc…',
'Interprets learning progressions describing increasing competence.',
'Describes methods for assessment of competence.',
'Connects teaching and learning cycle to classroom practice.',
'Distinguishes between evidence and inference.',
'Lists methods of evidence collection.', 'etc…',
'Explains plan for meeting student needs.',
'Uses teaching and learning cycle to plan instruction.', 'etc…',
'etc…', 'etc…', 'etc…'
],
[
'student_id', '2.1.1', '1.3.1', '1.1.1',
'3.1.1', '2.1.2', '3.1.2', '3.1.3', '1.2.1',
'1.1.2', '4.1.1', '1.1.3', '1.2.2', '1.3.2',
'1.4.1', '1.4.2', '4.1.2', '1.2.3', '1.3.3',
'2.1.3', '2.1.4', '3.1.4', '4.1.3'
],
[
'664', 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1,
1, 1, 1, 0, 0, 0, 0, 0, 0
],
[
'674', 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1,
1, 1, 1, 0, 0, 0, 0, 0, 0
],
[
'686', 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1,
1, 1, 1, 0, 0, 0, 0, 0, 0
],
[
'671', 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0,
1, 1, 1, 0, 0, 0, 0, 0, 0
],
[
'670', 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1,
0, 0, 1, 0, 0, 0, 0, 0, 0
],
[
'679', 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'682', 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0
],
[
'683', 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 1, 0, 1,
1, 1, 0, 0, 0, 0, 0, 0, 0
],
[
'656', 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'662', 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'681', 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'663', 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'654', 1, 0, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0,
1, 1, 0, 0, 0, 0, 0, 0, 0
],
[
'676', 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'677', 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'657', 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'680', 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'653', 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'666', 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'675', 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'669', 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'690', 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'652', 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'684', 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'678', 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'687', 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'658', 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'655', 1, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'659', 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'685', 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'673', 1, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'651', 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'661', 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'688', 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'667', 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'660', 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'668', 1, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'672', 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'689', 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
],
[
'665', 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0
]]
# Data after cleaning. The data that is supposed to be parsed to Guttman Analysis module to process with.
self.data_shoudlbe = [
[1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 0, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
]
self.data_first_row_one = ad.clean_input(self.original_data)
# Manipulate the data so that the first element in the list has zero standard deviation.
self.data_first_row_one[0] = [
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1
]
# transposed data
self.transposed_data = ad.transpose_matrix(self.data_shoudlbe)
def test_transpose(self):
array = self.array
array = fi.transpose(array)
self.assertTrue(array[1][2] == 3)