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mock eq method
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@quillcraftsman
quillcraftsman committed Nov 7, 2023
1 parent 4e01253 commit ce79b97
Showing 1 changed file with 93 additions and 88 deletions.
181 changes: 93 additions & 88 deletions core/tests/tests_core_functions.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,11 @@
from django.test import SimpleTestCase
from find_similar import TokenText

def eq(self, other):
return self.text == other.text

TokenText.__eq__ = eq

from core.core_functions import (
to_matrix,
str_to_token_text,
Expand Down Expand Up @@ -115,94 +120,94 @@ def test_find_similar_vector(self):
self.assertEqual(new[0, 0][0].text, old[0, 0])
self.assertEqual(new.shape, old.shape)

# def test_reshape_results(self):
# params = [
# # {
# # 'data': self.one_one,
# # 'expected': np.matrix(
# # ['one two']
# # ),
# # },
# {
# 'data': self.one_two,
# 'expected': np.matrix(
# [['one two', 'one']]
# ),
# },
# {
# 'data': self.two_two,
# 'expected': np.matrix(
# [
# ['one 1984', '1984'],
# ['two 50', '50'],
# ]
# ),
# },
# ]
# for param in params:
# old = to_matrix(param['data'])
# texts = matrix_to_list(old)
# new = find_similar_vector(text_to_check=old, texts=texts, count=len(texts))
# # first
# results = new[0, 0]
# matrix = reshape_results(results, old.shape)
# self.assertIsInstance(matrix, np.matrix)
# self.assertEqual(matrix.shape, old.shape)
# expected_matrix = tokenize_vector(param['expected'])
# self.assertTrue(np.array_equal(matrix, expected_matrix))
#
# # second
# results = new[0, 1]
# matrix = reshape_results(results, old.shape)
# self.assertIsInstance(matrix, np.matrix)
# self.assertEqual(matrix.shape, old.shape)
# expected_matrix = tokenize_vector(param['expected'])
# self.assertFalse(np.array_equal(matrix, expected_matrix))
#
# def test_reshape_results_vector(self):
# params = [
# # {
# # 'data': self.one_one,
# # 'expected': np.matrix(
# # ['one two']
# # ),
# # },
# {
# 'data': self.one_two,
# 'expected': np.matrix(
# [['one two', 'one']]
# ),
# },
# {
# 'data': self.two_two,
# 'expected': np.matrix(
# [
# ['one 1984', '1984'],
# ['two 50', '50'],
# ]
# ),
# },
# ]
# for param in params:
# old = to_matrix(param['data'])
# texts = matrix_to_list(old)
# new = find_similar_vector(text_to_check=old, texts=texts, count=len(texts))
# new = reshape_results_vector(results=new, shape=new.shape)
# # first
# matrix = new[0, 0]
# # matrix = reshape_results(results, old.shape)
# self.assertIsInstance(matrix, np.matrix)
# self.assertEqual(matrix.shape, old.shape)
# expected_matrix = tokenize_vector(param['expected'])
# self.assertTrue(np.array_equal(matrix, expected_matrix))
#
# # second
# matrix = new[0, 1]
# # matrix = reshape_results(results, old.shape)
# self.assertIsInstance(matrix, np.matrix)
# self.assertEqual(matrix.shape, old.shape)
# expected_matrix = tokenize_vector(param['expected'])
# self.assertFalse(np.array_equal(matrix, expected_matrix))
def test_reshape_results(self):
params = [
# {
# 'data': self.one_one,
# 'expected': np.matrix(
# ['one two']
# ),
# },
{
'data': self.one_two,
'expected': np.matrix(
[['one two', 'one']]
),
},
{
'data': self.two_two,
'expected': np.matrix(
[
['one 1984', '1984'],
['two 50', '50'],
]
),
},
]
for param in params:
old = to_matrix(param['data'])
texts = matrix_to_list(old)
new = find_similar_vector(text_to_check=old, texts=texts, count=len(texts))
# first
results = new[0, 0]
matrix = reshape_results(results, old.shape)
self.assertIsInstance(matrix, np.matrix)
self.assertEqual(matrix.shape, old.shape)
expected_matrix = tokenize_vector(param['expected'])
self.assertTrue(np.array_equal(matrix, expected_matrix))

# second
results = new[0, 1]
matrix = reshape_results(results, old.shape)
self.assertIsInstance(matrix, np.matrix)
self.assertEqual(matrix.shape, old.shape)
expected_matrix = tokenize_vector(param['expected'])
self.assertFalse(np.array_equal(matrix, expected_matrix))

def test_reshape_results_vector(self):
params = [
# {
# 'data': self.one_one,
# 'expected': np.matrix(
# ['one two']
# ),
# },
{
'data': self.one_two,
'expected': np.matrix(
[['one two', 'one']]
),
},
{
'data': self.two_two,
'expected': np.matrix(
[
['one 1984', '1984'],
['two 50', '50'],
]
),
},
]
for param in params:
old = to_matrix(param['data'])
texts = matrix_to_list(old)
new = find_similar_vector(text_to_check=old, texts=texts, count=len(texts))
new = reshape_results_vector(results=new, shape=new.shape)
# first
matrix = new[0, 0]
# matrix = reshape_results(results, old.shape)
self.assertIsInstance(matrix, np.matrix)
self.assertEqual(matrix.shape, old.shape)
expected_matrix = tokenize_vector(param['expected'])
self.assertTrue(np.array_equal(matrix, expected_matrix))

# second
matrix = new[0, 1]
# matrix = reshape_results(results, old.shape)
self.assertIsInstance(matrix, np.matrix)
self.assertEqual(matrix.shape, old.shape)
expected_matrix = tokenize_vector(param['expected'])
self.assertFalse(np.array_equal(matrix, expected_matrix))

def test_get_matrix_head(self):
lines = 1
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