class TestZoteroLibrary(unittest.TestCase):
def setUp(self):
self.test_library = ZoteroLibrary()
self.test_data = 'tests/test_data/test_zotero_library.csv'
def test_read_library(self):
self.test_library.read_library(self.test_data)
self.assertIsNotNone(self.test_library.library_df)
def test_get_library(self):
self.test_library.read_library(self.test_data)
out_library = self.test_library.get_library()
col_names = ['Title', 'Abstract']
for name in col_names:
self.assertTrue(name in list(out_library))
def setUp(self):
test_data = 'tests/test_data/test_zotero_library.csv'
self.zotero_library = ZoteroLibrary()
self.zotero_library.read_library(test_data)
self.test_library = self.zotero_library.get_library()
self.training_data = TrainingData(self.test_library)
class TestTrainingData(unittest.TestCase):
def setUp(self):
test_data = 'tests/test_data/test_zotero_library.csv'
self.zotero_library = ZoteroLibrary()
self.zotero_library.read_library(test_data)
self.test_library = self.zotero_library.get_library()
self.training_data = TrainingData(self.test_library)
def test_init(self):
self.assertIsNotNone(self.training_data.library)
def test_row_to_words(self):
words_row_0 = set(
['quantifying', 'magnetic', 'nature', 'light', 'emission'])
words_row_1 = set((
'external reflection infrared spectroscopy anisotropic adsorbate '
+
'layers dielectric substratesmonolayers octadecylsiloxane formed '
+
'native silicon si sio glass surfaces adsorption dilute solutions '
+
'oc tadecyltrichlorosilane investigated polarization angle dependent '
+
'external reflection infrared spectroscopy contrast metal substrates '
+
'parallel perpendicular vibrational components adsorbate detected '
+
'dielectric surfaces monolayer reflection spectra show significant '
+
'changes function light incidence angle polarization infrared radiation '
+
'contain detailed information surface orientation film molecules '
+
'spectral simulations based classical electromagnetic theory yield '
+
'average tilt angle hydrocarbon chains respect surface normal silicon '
+
'glass surfaces despite apparent structural identity monolayer films '
+
'silicon glass significant differences observed monolayer reflection '
+ 'spectra resulting purely optical effects substrate').split())
row_0 = self.training_data.library.iloc[0, :]
row_1 = self.training_data.library.iloc[1, :]
self.assertEqual(set(self.training_data.row_to_words(row_0).split()),
words_row_0)
self.assertEqual(set(self.training_data.row_to_words(row_1).split()),
words_row_1)
def test_clean_library(self):
self.training_data.clean_library()
self.assertEqual(len(self.training_data.cleaned_library), 243)
def test_train_vectorizer(self):
self.training_data.train_vectorizer()
correct_weights = [
7, 6, 6, 104, 33, 10, 6, 8, 12, 7, 12, 11, 6, 9, 8, 9, 8, 6, 10, 8,
6, 6, 5, 11, 5, 9, 48, 12, 8, 7, 6, 14, 5, 21, 7, 40, 7, 41, 9, 30,
31, 16, 11, 30, 16, 13, 9, 5, 7, 9, 9, 14, 9, 5, 6, 6, 6, 6, 14,
13, 8, 30, 8, 8, 70, 5, 11, 5, 5, 6, 6, 5, 5, 6, 6, 24, 13, 5, 14,
13, 10, 9, 12, 30, 5, 6, 15, 5, 13, 26, 22, 11, 7, 5, 26, 62, 7,
18, 6, 9, 27, 32, 5, 14, 21, 9, 10, 12, 9, 9, 150, 7, 11, 22, 8, 6,
7, 5, 8, 28, 16, 12, 9, 11, 9, 11, 8, 5, 15, 8, 5, 20, 6, 16, 5, 5,
5, 5, 5, 7, 5, 10, 8, 7, 9, 7, 6, 6, 5, 63, 5, 7, 12, 7, 14, 10, 8,
5, 5, 9, 10, 5, 28, 12, 8, 9, 32, 5, 8, 6, 14, 6, 6, 12, 10, 11,
30, 11, 31, 27, 11, 28, 17, 23, 14, 32, 14, 6, 11, 8, 13, 31, 7,
16, 7, 27, 18, 17, 10, 9, 9, 6, 22, 6, 13, 6, 9, 12, 17, 5, 5, 16,
6, 42, 65, 5, 7, 31, 8, 19, 7, 6, 64, 17, 21, 10, 10, 36, 5, 6, 10,
13, 6, 11, 15, 6, 7, 19, 9, 19, 22, 11, 6, 5, 8, 9, 8, 15, 14, 40,
6, 7, 5, 26, 5, 8, 5, 24, 24, 5, 45, 13, 22, 14, 68, 16, 6, 8, 11,
17, 5, 6, 11, 96, 78, 14, 19, 7, 15, 5, 43, 9, 19, 7, 7, 6, 6, 111,
5, 11, 13, 5, 6, 5, 5, 6, 6, 5, 5, 21, 12, 5, 7, 8, 8, 33, 22, 11,
5, 104, 12, 63, 13, 6, 6, 5, 26, 13, 16, 5, 8, 5, 11, 5, 6, 9, 11,
17, 6, 8, 11, 16, 5, 10, 5, 86, 24, 5, 83, 136, 9, 27, 7, 20, 28,
10, 7, 23, 8, 10, 10, 8, 28, 28, 12, 6, 23, 7, 15, 6, 7, 11, 5, 7,
29, 8, 14, 9, 11, 18, 13, 5, 6, 22, 5, 13, 6, 11, 5, 8, 31, 5, 9,
6, 6, 8, 12, 7, 7, 6, 10, 16, 5, 5, 5, 18, 6, 15, 101, 20, 5, 28,
28, 9, 7, 10, 28, 24, 10, 6, 7, 5, 13, 12, 12, 6, 9, 26, 12, 12, 9,
6, 17, 18, 13, 10, 10, 5, 15, 13, 7, 6, 5, 12, 22, 11, 27, 15, 7,
6, 14, 6, 5, 17, 10, 18, 19, 5, 16, 11, 5, 16, 11, 5, 6, 7, 13, 6,
6, 6, 10, 7, 6, 7, 10, 5, 5, 13, 14, 7, 11, 5, 5, 23, 6, 16, 6, 8,
32, 9, 26, 8, 14, 7, 16, 12, 14, 13, 7, 105, 11, 8, 8, 10, 7, 12,
10, 7, 29, 9, 8, 41, 19, 10, 5, 7, 7, 12, 50, 15, 6, 7, 5, 6, 12,
6, 8, 33, 86, 5, 12, 8, 10, 10, 7, 6, 19, 8, 47, 7, 11, 5, 6, 5,
11, 5, 8, 5, 5, 35, 12, 6, 10, 8, 6, 27, 20, 6, 12, 10, 5, 5, 6,
16, 42, 11, 40, 5, 20, 7, 116, 32, 64, 6, 7, 12, 10, 6, 7, 5, 21,
6, 13, 14, 7, 11, 5, 9, 5, 6, 16, 5, 16, 15, 39, 23, 6, 9, 30, 23,
17, 23, 15, 7, 10, 8, 6, 11, 13, 9, 24, 14, 46, 7, 25, 10, 10, 33,
6, 7, 32, 7, 14, 137, 6, 13, 51, 19, 12, 196, 82, 13, 36, 6, 6, 6,
8, 13, 6, 13, 7, 19, 15, 9, 9, 15, 7, 6, 7, 9, 6, 6, 10, 10, 7, 31,
10, 16, 7, 31, 8, 9, 7, 6, 8, 7, 9, 5, 10, 11, 5, 26, 18, 7, 10, 5,
5, 47, 9, 32, 6, 19, 16, 12, 6, 7, 48, 5, 15, 5, 8, 6, 6, 7, 16, 9,
23, 30, 12, 6, 10, 61, 7, 6, 136, 12, 7, 70, 8, 7, 8, 15, 12, 6,
23, 10, 5, 6, 15, 20, 10, 7, 16, 5, 5, 5, 39, 33, 16, 6, 5, 10, 9,
11, 68, 5, 6, 14, 6, 8, 10, 5, 5, 8, 7, 5, 5, 6, 11, 72, 8, 6, 12,
6, 21, 5, 38, 5, 21, 6, 8, 28, 5, 6, 5, 18, 13, 36, 6, 7, 10, 21,
13, 5, 7, 5, 16, 7, 9, 5, 15, 10, 30, 5, 13, 15, 10, 7, 8, 24, 12,
5, 6, 9, 14, 7, 17, 9, 65, 12, 8, 21, 6, 5, 24, 19, 5, 8, 5, 6, 15,
5, 18, 6, 5, 8, 7, 8, 6, 16, 12, 26, 32, 27, 16, 6, 32, 9, 23, 14,
6, 11, 7, 62, 14, 9, 6, 9, 8, 14, 6, 7, 20, 7, 14, 12, 10, 8, 5, 6,
75, 43, 7, 8, 15, 90, 19, 6, 20, 9, 7, 5, 7, 8, 12, 8, 45, 34, 23,
9, 55, 21, 93, 15, 6, 5, 8, 5, 7, 11, 67, 53, 5, 8, 5, 6, 16, 19,
31, 63, 24, 20, 21, 38, 7, 5, 29, 24, 5, 5, 6, 74, 12, 5, 8, 21,
32, 6, 5, 5, 5, 5, 7, 19, 11, 9, 39, 7, 7, 8, 16, 9, 5, 21, 22, 7,
11, 14, 8, 13, 94, 11, 29, 6, 6, 5, 43, 13, 10, 9, 5, 10, 6, 9, 5,
43, 5, 9, 13, 27, 24, 16, 21, 5, 55, 7, 6, 57, 78, 13, 9, 6, 5, 5,
17, 9, 13, 11, 10, 9, 16, 6, 20, 43, 66, 9, 12, 6, 6, 7, 6, 11, 5,
17, 6, 18, 15, 7, 12, 14, 8, 16, 21, 7, 11, 14, 9, 8, 33, 10, 12,
26, 6, 7, 7, 9, 6, 6, 6, 10
]
# Check element-wise equality
all_elem_equal = (self.training_data.weights == correct_weights).all()
self.assertTrue(all_elem_equal)
def test_score_article(self):
self.training_data.train_vectorizer()
test_article = ' '.join(
self.training_data.vectorizer.get_feature_names())
score = self.training_data.score_article(test_article)
self.assertEqual(
score,
self.training_data.weights.sum() /
float(len(self.training_data.weights) + 1))
def setUp(self):
test_data = 'tests/test_data/test_zotero_library.csv'
self.zotero_library = ZoteroLibrary()
self.zotero_library.read_library(test_data)
self.test_library = self.zotero_library.get_library()
self.training_data = TrainingData(self.test_library)
class TestTrainingData(unittest.TestCase):
def setUp(self):
test_data = 'tests/test_data/test_zotero_library.csv'
self.zotero_library = ZoteroLibrary()
self.zotero_library.read_library(test_data)
self.test_library = self.zotero_library.get_library()
self.training_data = TrainingData(self.test_library)
def test_init(self):
self.assertIsNotNone(self.training_data.library)
def test_row_to_words(self):
words_row_0 = set(['quantifying', 'magnetic', 'nature', 'light', 'emission'])
words_row_1 = set(('external reflection infrared spectroscopy anisotropic adsorbate '+
'layers dielectric substratesmonolayers octadecylsiloxane formed '+
'native silicon si sio glass surfaces adsorption dilute solutions '+
'oc tadecyltrichlorosilane investigated polarization angle dependent '+
'external reflection infrared spectroscopy contrast metal substrates '+
'parallel perpendicular vibrational components adsorbate detected '+
'dielectric surfaces monolayer reflection spectra show significant '+
'changes function light incidence angle polarization infrared radiation '+
'contain detailed information surface orientation film molecules '+
'spectral simulations based classical electromagnetic theory yield '+
'average tilt angle hydrocarbon chains respect surface normal silicon '+
'glass surfaces despite apparent structural identity monolayer films '+
'silicon glass significant differences observed monolayer reflection '+
'spectra resulting purely optical effects substrate').split())
row_0 = self.training_data.library.iloc[0,:]
row_1 = self.training_data.library.iloc[1,:]
self.assertEqual(set(self.training_data.row_to_words(row_0).split()), words_row_0)
self.assertEqual(set(self.training_data.row_to_words(row_1).split()), words_row_1)
def test_clean_library(self):
self.training_data.clean_library()
self.assertEqual(len(self.training_data.cleaned_library), 243)
def test_train_vectorizer(self):
self.training_data.train_vectorizer()
correct_weights = [7, 6, 6, 104, 33, 10, 6, 8, 12, 7, 12, 11, 6, 9, 8, 9, 8, 6, 10, 8, 6, 6,
5, 11, 5, 9, 48, 12, 8, 7, 6, 14, 5, 21, 7, 40, 7, 41, 9, 30, 31, 16, 11,
30, 16, 13, 9, 5, 7, 9, 9, 14, 9, 5, 6, 6, 6, 6, 14, 13, 8, 30, 8, 8, 70,
5, 11, 5, 5, 6, 6, 5, 5, 6, 6, 24, 13, 5, 14, 13, 10, 9, 12, 30, 5, 6,
15, 5, 13, 26, 22, 11, 7, 5, 26, 62, 7, 18, 6, 9, 27, 32, 5, 14, 21, 9,
10, 12, 9, 9, 150, 7, 11, 22, 8, 6, 7, 5, 8, 28, 16, 12, 9, 11, 9, 11, 8,
5, 15, 8, 5, 20, 6, 16, 5, 5, 5, 5, 5, 7, 5, 10, 8, 7, 9, 7, 6, 6, 5, 63,
5, 7, 12, 7, 14, 10, 8, 5, 5, 9, 10, 5, 28, 12, 8, 9, 32, 5, 8, 6, 14, 6,
6, 12, 10, 11, 30, 11, 31, 27, 11, 28, 17, 23, 14, 32, 14, 6, 11, 8, 13,
31, 7, 16, 7, 27, 18, 17, 10, 9, 9, 6, 22, 6, 13, 6, 9, 12, 17, 5, 5, 16,
6, 42, 65, 5, 7, 31, 8, 19, 7, 6, 64, 17, 21, 10, 10, 36, 5, 6, 10, 13,
6, 11, 15, 6, 7, 19, 9, 19, 22, 11, 6, 5, 8, 9, 8, 15, 14, 40, 6, 7, 5,
26, 5, 8, 5, 24, 24, 5, 45, 13, 22, 14, 68, 16, 6, 8, 11, 17, 5, 6, 11,
96, 78, 14, 19, 7, 15, 5, 43, 9, 19, 7, 7, 6, 6, 111, 5, 11, 13, 5, 6, 5,
5, 6, 6, 5, 5, 21, 12, 5, 7, 8, 8, 33, 22, 11, 5, 104, 12, 63, 13, 6, 6,
5, 26, 13, 16, 5, 8, 5, 11, 5, 6, 9, 11, 17, 6, 8, 11, 16, 5, 10, 5, 86,
24, 5, 83, 136, 9, 27, 7, 20, 28, 10, 7, 23, 8, 10, 10, 8, 28, 28, 12, 6,
23, 7, 15, 6, 7, 11, 5, 7, 29, 8, 14, 9, 11, 18, 13, 5, 6, 22, 5, 13, 6,
11, 5, 8, 31, 5, 9, 6, 6, 8, 12, 7, 7, 6, 10, 16, 5, 5, 5, 18, 6, 15,
101, 20, 5, 28, 28, 9, 7, 10, 28, 24, 10, 6, 7, 5, 13, 12, 12, 6, 9, 26,
12, 12, 9, 6, 17, 18, 13, 10, 10, 5, 15, 13, 7, 6, 5, 12, 22, 11, 27, 15,
7, 6, 14, 6, 5, 17, 10, 18, 19, 5, 16, 11, 5, 16, 11, 5, 6, 7, 13, 6, 6,
6, 10, 7, 6, 7, 10, 5, 5, 13, 14, 7, 11, 5, 5, 23, 6, 16, 6, 8, 32, 9,
26, 8, 14, 7, 16, 12, 14, 13, 7, 105, 11, 8, 8, 10, 7, 12, 10, 7, 29, 9,
8, 41, 19, 10, 5, 7, 7, 12, 50, 15, 6, 7, 5, 6, 12, 6, 8, 33, 86, 5, 12,
8, 10, 10, 7, 6, 19, 8, 47, 7, 11, 5, 6, 5, 11, 5, 8, 5, 5, 35, 12, 6,
10, 8, 6, 27, 20, 6, 12, 10, 5, 5, 6, 16, 42, 11, 40, 5, 20, 7, 116, 32,
64, 6, 7, 12, 10, 6, 7, 5, 21, 6, 13, 14, 7, 11, 5, 9, 5, 6, 16, 5, 16,
15, 39, 23, 6, 9, 30, 23, 17, 23, 15, 7, 10, 8, 6, 11, 13, 9, 24, 14, 46,
7, 25, 10, 10, 33, 6, 7, 32, 7, 14, 137, 6, 13, 51, 19, 12, 196, 82, 13,
36, 6, 6, 6, 8, 13, 6, 13, 7, 19, 15, 9, 9, 15, 7, 6, 7, 9, 6, 6, 10, 10,
7, 31, 10, 16, 7, 31, 8, 9, 7, 6, 8, 7, 9, 5, 10, 11, 5, 26, 18, 7, 10,
5, 5, 47, 9, 32, 6, 19, 16, 12, 6, 7, 48, 5, 15, 5, 8, 6, 6, 7, 16, 9,
23, 30, 12, 6, 10, 61, 7, 6, 136, 12, 7, 70, 8, 7, 8, 15, 12, 6, 23, 10,
5, 6, 15, 20, 10, 7, 16, 5, 5, 5, 39, 33, 16, 6, 5, 10, 9, 11, 68, 5, 6,
14, 6, 8, 10, 5, 5, 8, 7, 5, 5, 6, 11, 72, 8, 6, 12, 6, 21, 5, 38, 5, 21,
6, 8, 28, 5, 6, 5, 18, 13, 36, 6, 7, 10, 21, 13, 5, 7, 5, 16, 7, 9, 5,
15, 10, 30, 5, 13, 15, 10, 7, 8, 24, 12, 5, 6, 9, 14, 7, 17, 9, 65, 12,
8, 21, 6, 5, 24, 19, 5, 8, 5, 6, 15, 5, 18, 6, 5, 8, 7, 8, 6, 16, 12, 26,
32, 27, 16, 6, 32, 9, 23, 14, 6, 11, 7, 62, 14, 9, 6, 9, 8, 14, 6, 7, 20,
7, 14, 12, 10, 8, 5, 6, 75, 43, 7, 8, 15, 90, 19, 6, 20, 9, 7, 5, 7, 8,
12, 8, 45, 34, 23, 9, 55, 21, 93, 15, 6, 5, 8, 5, 7, 11, 67, 53, 5, 8, 5,
6, 16, 19, 31, 63, 24, 20, 21, 38, 7, 5, 29, 24, 5, 5, 6, 74, 12, 5, 8,
21, 32, 6, 5, 5, 5, 5, 7, 19, 11, 9, 39, 7, 7, 8, 16, 9, 5, 21, 22, 7,
11, 14, 8, 13, 94, 11, 29, 6, 6, 5, 43, 13, 10, 9, 5, 10, 6, 9, 5, 43, 5,
9, 13, 27, 24, 16, 21, 5, 55, 7, 6, 57, 78, 13, 9, 6, 5, 5, 17, 9, 13,
11, 10, 9, 16, 6, 20, 43, 66, 9, 12, 6, 6, 7, 6, 11, 5, 17, 6, 18, 15, 7,
12, 14, 8, 16, 21, 7, 11, 14, 9, 8, 33, 10, 12, 26, 6, 7, 7, 9, 6, 6, 6,
10]
# Check element-wise equality
all_elem_equal = (self.training_data.weights == correct_weights).all()
self.assertTrue(all_elem_equal)
def test_score_article(self):
self.training_data.train_vectorizer()
test_article = ' '.join(self.training_data.vectorizer.get_feature_names())
score = self.training_data.score_article(test_article)
self.assertEqual(score,
self.training_data.weights.sum()/float(len(self.training_data.weights)+1))
def setUp(self):
self.test_library = ZoteroLibrary()
self.test_data = 'tests/test_data/test_zotero_library.csv'