def setUpClass(cls):
for forbidden_feature in cls.blacklist_features:
setattr(cls, forbidden_feature, getattr(MockRankProcessor, forbidden_feature))
setattr(MockRankProcessor, forbidden_feature, None)
frame = NumericFeaturesFrame(
lambda content: content[cls.identifier_key],
MockRankProcessor.get_features(),
lambda: cls.test_content
)
frame.to_disk(cls.frame_path)
class TestNumericFeaturesFrame(TestCase):
fixtures = ["test-organisms"]
def setUp(self):
super().setUp()
self.test_fixture = Collective.objects.get(id=2)
self.test_records = [
{
"is_dutch": 1.0,
"is_english": 0.0,
"value_number": 1.0
},
{
"is_dutch": 1.0,
"is_english": 0.0,
"value_number": 2.0
},
{
"is_dutch": 1.0,
"is_english": 0.0,
"value_number": 1.0
},
{
"is_dutch": 0.0,
"is_english": 1.0,
"value_number": 1.0
},
{
"is_dutch": 0.0,
"is_english": 1.0,
"value_number": 2.0
}
]
test_frame = pd.DataFrame.from_records(self.test_records, index=[4, 5, 6, 7, 8])
test_frame = (test_frame - test_frame.min()) / (test_frame.max() - test_frame.min())
self.test_frame = test_frame.fillna(0)
self.test_records_extra = [
{
"is_dutch": 0.0,
"is_english": 0.0,
"value_number": 1.0
},
{
"is_dutch": 0.0,
"is_english": 0.0,
"value_number": 2.0
}
]
test_frame_extra = pd.DataFrame.from_records(self.test_records + self.test_records_extra,
index=[4, 5, 6, 7, 8, 9, 10])
test_frame_extra = (test_frame_extra - test_frame_extra.min()) / \
(test_frame_extra.max() - test_frame_extra.min())
self.test_frame_extra = test_frame_extra.fillna(0)
self.features = [
TestNumericFeaturesFrame.is_dutch,
TestNumericFeaturesFrame.is_english,
TestNumericFeaturesFrame.value_number
]
self.frame = NumericFeaturesFrame(
TestNumericFeaturesFrame.get_identifier,
self.features,
self.get_iterator
)
self.extra_individuals = [
Individual.objects.create(
id=9,
properties={
'country': 'FR',
'language': 'fr',
'value': '1',
'word': 'pension'
},
community=self.test_fixture.community,
collective=self.test_fixture
),
Individual.objects.create(
id=10,
properties={
'country': 'FR',
'language': 'fr',
'value': '2',
'word': 'pension'
},
community=self.test_fixture.community,
collective=self.test_fixture
)
]
@staticmethod
def get_identifier(test):
return test.id
def get_iterator(self):
"""
Returns content that is already in fixtures
"""
return self.test_fixture.individual_set.filter(id__lt=9).iterator()
def get_extra_iterator(self):
"""
Returns content that is created in setUp
"""
return iter(self.extra_individuals)
@staticmethod
def is_dutch(test):
return float(test["language"] == "nl")
@staticmethod
def is_english(test):
return int(test["language"] == "en") # NB: features should return floats, but ints are allowed
@staticmethod
def value_number(test):
return test["value"]
@staticmethod
def invalid_arguments():
return 0.0
@staticmethod
def invalid_return(test):
return "invalid"
@staticmethod
def set_language_to_fr(test):
test["language"] = "fr"
return 0.0
def test_init(self):
sorted_feature_names = ["is_dutch", "is_english", "value_number"]
self.assertEquals(
sorted(self.frame.features.keys()),
sorted_feature_names
)
self.assertTrue(callable(self.frame.content))
assert_frame_equal(self.frame.data, self.test_frame, check_like=True)
def test_init_invalid_features(self):
features = [
TestNumericFeaturesFrame.invalid_arguments
]
try:
NumericFeaturesFrame(
TestNumericFeaturesFrame.get_identifier,
features,
self.get_iterator
)
self.fail("NumericFeaturesFrame did not raise with invalid feature")
except Exception as exc:
self.assertEqual(
str(exc),
"invalid_arguments feature: TypeError: invalid_arguments() takes 0 positional arguments but 1 was given"
)
features = [
TestNumericFeaturesFrame.invalid_return
]
try:
NumericFeaturesFrame(
TestNumericFeaturesFrame.get_identifier,
features,
self.get_iterator
)
self.fail("NumericFeaturesFrame did not raise with invalid feature return value")
except ValueError as exc:
self.assertEqual(
str(exc),
"invalid_return feature did not return float but <class 'str'>"
)
def test_init_immutable_content(self):
content = list(self.get_iterator())
features = [
TestNumericFeaturesFrame.set_language_to_fr
]
try:
NumericFeaturesFrame(
self.get_identifier,
features,
lambda: content
)
self.fail("NumericFeaturesFrame did not raise when features modified content")
except ValueError:
pass
def test_init_file(self):
with patch("core.utils.data.numeric_features.NumericFeaturesFrame.from_disk", return_value=self.test_frame) as \
from_disk_patch:
frame = NumericFeaturesFrame(
self.get_identifier,
self.features,
file_path="test/path/to/frame.pkl"
)
sorted_feature_names = ["is_dutch", "is_english", "value_number"]
self.assertEquals(
sorted(frame.features.keys()),
sorted_feature_names
)
from_disk_patch.assert_called_once_with("test/path/to/frame.pkl")
def test_to_disk(self):
self.frame.data.to_pickle = Mock()
self.frame.to_disk("test/path/to/frame.pkl")
self.frame.data.to_pickle.assert_called_once_with('test/path/to/frame.pkl')
def test_from_disk(self):
with patch("core.utils.data.numeric_features.pd.read_pickle", return_value=self.test_frame) as pandas_patch:
self.frame.from_disk("test/path/to/frame.pkl")
pandas_patch.assert_called_once_with("test/path/to/frame.pkl")
assert_frame_equal(self.frame.data, self.test_frame, check_like=True)
def test_from_disk_invalid(self):
self.test_frame["extra"] = self.test_frame["is_dutch"]
with patch("core.utils.data.numeric_features.pd.read_pickle", return_value=self.test_frame) as pandas_patch:
try:
self.frame.from_disk("test/path/to/frame.pkl")
self.fail("NumericFeatureFrame.from_disk did not raise an assertion when loading too much data")
except DSFileLoadError as exc:
pass
pandas_patch.assert_called_once_with("test/path/to/frame.pkl")
self.test_frame.drop("is_dutch", axis=1)
with patch("core.utils.data.numeric_features.pd.read_pickle", return_value=self.test_frame) as pandas_patch:
try:
self.frame.from_disk("test/path/to/frame.pkl")
self.fail("NumericFeatureFrame.from_disk did not raise an assertion when loading wrong data")
except DSFileLoadError:
pass
pandas_patch.assert_called_once_with("test/path/to/frame.pkl")
self.test_frame.drop("extra", axis=1)
with patch("core.utils.data.numeric_features.pd.read_pickle", return_value=self.test_frame) as pandas_patch:
try:
self.frame.from_disk("test/path/to/frame.pkl")
self.fail("NumericFeatureFrame.from_disk did not raise an assertion when loading too little data")
except DSFileLoadError:
pass
pandas_patch.assert_called_once_with("test/path/to/frame.pkl")
def test_adding_features(self):
features = [
TestNumericFeaturesFrame.is_dutch
]
frame = NumericFeaturesFrame(
TestNumericFeaturesFrame.get_identifier,
features,
self.get_iterator
)
frame.load_features([
TestNumericFeaturesFrame.value_number,
TestNumericFeaturesFrame.is_english
])
assert_frame_equal(frame.data, self.test_frame, check_like=True)
sorted_feature_names = ["is_dutch", "is_english", "value_number"]
self.assertEquals(
sorted(self.frame.features.keys()),
sorted_feature_names
)
def test_adding_content(self):
self.frame.load_content(self.get_extra_iterator)
assert_frame_equal(self.frame.data, self.test_frame_extra, check_like=True)
def test_adding_content_mixed(self):
self.skipTest("Bug: GH-109")
old = list(self.get_iterator())[-2:]
def update(ind):
ind.properties["value"] = int(ind.properties["value"]) * 5
return ind
updated = list(map(update, old))
self.frame.load_content(
lambda: iter(list(self.get_extra_iterator()) + updated)
)
self.test_frame_extra["value_number"].loc[[7, 8]] *= 5
assert_frame_equal(self.frame.data, self.test_frame_extra, check_like=True)
def test_resetting_features_and_content(self):
features = [
TestNumericFeaturesFrame.is_dutch
]
frame = NumericFeaturesFrame(
TestNumericFeaturesFrame.get_identifier,
features,
self.get_iterator
)
frame.reset(
features=[
TestNumericFeaturesFrame.value_number,
TestNumericFeaturesFrame.is_english
],
content=self.get_extra_iterator
)
self.test_frame_extra = self.test_frame_extra.drop([4, 5, 6, 7, 8], axis=0)
self.test_frame_extra = self.test_frame_extra.drop(labels="is_dutch", axis=1)
assert_frame_equal(frame.data, self.test_frame_extra, check_like=True)
sorted_feature_names = ["is_english", "value_number"]
self.assertEquals(
sorted(frame.features.keys()),
sorted_feature_names
)
def test_resetting_features(self):
features = [
TestNumericFeaturesFrame.is_dutch
]
frame = NumericFeaturesFrame(
TestNumericFeaturesFrame.get_identifier,
features,
self.get_iterator
)
frame.reset(features=[
TestNumericFeaturesFrame.value_number,
TestNumericFeaturesFrame.is_english
])
self.test_frame = self.test_frame.drop(labels="is_dutch", axis=1)
assert_frame_equal(frame.data, self.test_frame, check_like=True)
sorted_feature_names = ["is_english", "value_number"]
self.assertEquals(
sorted(frame.features.keys()),
sorted_feature_names
)
def test_resetting_features_no_content(self):
features = [
TestNumericFeaturesFrame.is_dutch
]
frame = NumericFeaturesFrame(
TestNumericFeaturesFrame.get_identifier,
features
)
frame.reset(features=[
TestNumericFeaturesFrame.value_number,
TestNumericFeaturesFrame.is_english
])
self.test_frame = self.test_frame.drop(labels="is_dutch", axis=1)
assert_frame_equal(frame.data, self.test_frame[0:0], check_like=True)
sorted_feature_names = ["is_english", "value_number"]
self.assertEquals(
sorted(frame.features.keys()),
sorted_feature_names
)
def test_resetting_content(self):
self.frame.reset(content=self.get_extra_iterator)
self.test_frame_extra = self.test_frame_extra.drop([4, 5, 6, 7, 8], axis=0)
assert_frame_equal(self.frame.data, self.test_frame_extra, check_like=True)
def test_resetting_content_no_features(self):
self.frame.features = None
self.frame.reset(content=self.get_extra_iterator)
self.assertEqual(self.frame.content.__name__, self.get_extra_iterator.__name__) # TODO: better equality test
assert_frame_equal(self.frame.data, pd.DataFrame(dtype=np.float), check_like=True)
def test_clean_params(self):
test_params = {
"is_dutch": "1", # get converted to float
"is_french": 1.0, # gets skipped
"$is_french": 1.0, # gets skipped (without errors)
"value_number": None, # gets skipped a a non-numeric
"is_english": "test", # gets skipped as a non-numeric
"$value_number": 2.0
}
for function in [str, int, float]:
test_params["is_dutch"] = function(test_params["is_dutch"])
cleaned_params = self.frame.clean_params(test_params)
self.assertEquals(cleaned_params, {"is_dutch": 1.0, "value_number": 2.0})
test_error_params = {
"is_dutch": "1",
"$is_dutch": 1.0,
}
try:
self.frame.clean_params(test_error_params)
self.fail("Clean params should have raised for invalid params")
except ValueError:
pass
def test_rank_by_params(self):
ranking = self.frame.rank_by_params({"is_dutch": 1, "value_number": 1})
self.assertEquals(ranking, [5, 8, 6, 4, 7])
ranking = self.frame.rank_by_params({"is_dutch": 0.5, "value_number": -1, "is_english": 2, "is_french": 100})
self.assertEquals(ranking, [7, 8, 6, 4, 5])
def test_get_content_hash(self):
self.skipTest("not tested")
def test_get_feature_value(self):
self.skipTest("not tested")
def test_get_feature_series(self):
self.skipTest("not tested")
class TestNumericFeaturesFrame(TestCase):
fixtures = ["test-organisms"]
def setUp(self):
super().setUp()
self.test_fixture = Collective.objects.get(id=2)
self.test_records = [
{
"is_dutch": 1.0,
"is_english": 0.0,
"value_number": 1.0
},
{
"is_dutch": 1.0,
"is_english": 0.0,
"value_number": 2.0
},
{
"is_dutch": 1.0,
"is_english": 0.0,
"value_number": 1.0
},
{
"is_dutch": 0.0,
"is_english": 1.0,
"value_number": 1.0
},
{
"is_dutch": 0.0,
"is_english": 1.0,
"value_number": 2.0
}
]
test_frame = pd.DataFrame.from_records(self.test_records, index=[4, 5, 6, 7, 8])
test_frame = (test_frame - test_frame.min()) / (test_frame.max() - test_frame.min())
self.test_frame = test_frame.fillna(0)
self.test_records_extra = [
{
"is_dutch": 0.0,
"is_english": 0.0,
"value_number": 1.0
},
{
"is_dutch": 0.0,
"is_english": 0.0,
"value_number": 2.0
}
]
test_frame_extra = pd.DataFrame.from_records(self.test_records + self.test_records_extra,
index=[4, 5, 6, 7, 8, 9, 10])
test_frame_extra = (test_frame_extra - test_frame_extra.min()) / \
(test_frame_extra.max() - test_frame_extra.min())
self.test_frame_extra = test_frame_extra.fillna(0)
self.features = [
TestNumericFeaturesFrame.is_dutch,
TestNumericFeaturesFrame.is_english,
TestNumericFeaturesFrame.value_number
]
self.frame = NumericFeaturesFrame(
TestNumericFeaturesFrame.get_identifier,
self.features,
self.get_iterator
)
self.extra_individuals = [
Individual.objects.create(
id=9,
properties={
'country': 'FR',
'language': 'fr',
'value': '1',
'word': 'pension'
},
community=self.test_fixture.community,
collective=self.test_fixture
),
Individual.objects.create(
id=10,
properties={
'country': 'FR',
'language': 'fr',
'value': '2',
'word': 'pension'
},
community=self.test_fixture.community,
collective=self.test_fixture
)
]
@staticmethod
def get_identifier(test):
return test.id
def get_iterator(self):
"""
Returns content that is already in fixtures
"""
return self.test_fixture.individual_set.filter(id__lt=9).iterator()
def get_extra_iterator(self):
"""
Returns content that is created in setUp
"""
return iter(self.extra_individuals)
@staticmethod
def is_dutch(test):
return float(test["language"] == "nl")
@staticmethod
def is_english(test):
return int(test["language"] == "en") # NB: features should return floats, but ints are allowed
@staticmethod
def value_number(test):
return test["value"]
@staticmethod
def invalid_arguments():
return 0.0
@staticmethod
def invalid_return(test):
return "invalid"
@staticmethod
def set_language_to_fr(test):
test["language"] = "fr"
return 0.0
def test_init(self):
sorted_feature_names = ["is_dutch", "is_english", "value_number"]
self.assertEquals(
sorted(self.frame.features.keys()),
sorted_feature_names
)
self.assertTrue(callable(self.frame.content))
assert_frame_equal(self.frame.data, self.test_frame, check_like=True)
def test_init_invalid_features(self):
features = [
TestNumericFeaturesFrame.invalid_arguments
]
try:
NumericFeaturesFrame(
TestNumericFeaturesFrame.get_identifier,
features,
self.get_iterator
)
self.fail("NumericFeaturesFrame did not raise with invalid feature")
except Exception as exc:
self.assertEqual(
str(exc),
"invalid_arguments feature: TypeError: invalid_arguments() takes 0 positional arguments but 1 was given"
)
features = [
TestNumericFeaturesFrame.invalid_return
]
try:
NumericFeaturesFrame(
TestNumericFeaturesFrame.get_identifier,
features,
self.get_iterator
)
self.fail("NumericFeaturesFrame did not raise with invalid feature return value")
except ValueError as exc:
self.assertEqual(
str(exc),
"invalid_return feature did not return float but <class 'str'>"
)
def test_init_immutable_content(self):
content = list(self.get_iterator())
features = [
TestNumericFeaturesFrame.set_language_to_fr
]
try:
NumericFeaturesFrame(
self.get_identifier,
features,
lambda: content
)
self.fail("NumericFeaturesFrame did not raise when features modified content")
except ValueError:
pass
def test_init_file(self):
with patch("core.utils.data.numeric_features.NumericFeaturesFrame.from_disk", return_value=self.test_frame) as \
from_disk_patch:
frame = NumericFeaturesFrame(
self.get_identifier,
self.features,
file_path="test/path/to/frame.pkl"
)
sorted_feature_names = ["is_dutch", "is_english", "value_number"]
self.assertEquals(
sorted(frame.features.keys()),
sorted_feature_names
)
from_disk_patch.assert_called_once_with("test/path/to/frame.pkl")
def test_to_disk(self):
self.frame.data.to_pickle = Mock()
self.frame.to_disk("test/path/to/frame.pkl")
self.frame.data.to_pickle.assert_called_once_with('test/path/to/frame.pkl')
def test_from_disk(self):
with patch("core.utils.data.numeric_features.pd.read_pickle", return_value=self.test_frame) as pandas_patch:
self.frame.from_disk("test/path/to/frame.pkl")
pandas_patch.assert_called_once_with("test/path/to/frame.pkl")
assert_frame_equal(self.frame.data, self.test_frame, check_like=True)
def test_from_disk_invalid(self):
self.test_frame["extra"] = self.test_frame["is_dutch"]
with patch("core.utils.data.numeric_features.pd.read_pickle", return_value=self.test_frame) as pandas_patch:
try:
self.frame.from_disk("test/path/to/frame.pkl")
self.fail("NumericFeatureFrame.from_disk did not raise an assertion when loading too much data")
except DSFileLoadError as exc:
pass
pandas_patch.assert_called_once_with("test/path/to/frame.pkl")
self.test_frame.drop("is_dutch", axis=1)
with patch("core.utils.data.numeric_features.pd.read_pickle", return_value=self.test_frame) as pandas_patch:
try:
self.frame.from_disk("test/path/to/frame.pkl")
self.fail("NumericFeatureFrame.from_disk did not raise an assertion when loading wrong data")
except DSFileLoadError:
pass
pandas_patch.assert_called_once_with("test/path/to/frame.pkl")
self.test_frame.drop("extra", axis=1)
with patch("core.utils.data.numeric_features.pd.read_pickle", return_value=self.test_frame) as pandas_patch:
try:
self.frame.from_disk("test/path/to/frame.pkl")
self.fail("NumericFeatureFrame.from_disk did not raise an assertion when loading too little data")
except DSFileLoadError:
pass
pandas_patch.assert_called_once_with("test/path/to/frame.pkl")
def test_adding_features(self):
features = [
TestNumericFeaturesFrame.is_dutch
]
frame = NumericFeaturesFrame(
TestNumericFeaturesFrame.get_identifier,
features,
self.get_iterator
)
frame.load_features([
TestNumericFeaturesFrame.value_number,
TestNumericFeaturesFrame.is_english
])
assert_frame_equal(frame.data, self.test_frame, check_like=True)
sorted_feature_names = ["is_dutch", "is_english", "value_number"]
self.assertEquals(
sorted(self.frame.features.keys()),
sorted_feature_names
)
def test_adding_content(self):
self.frame.load_content(self.get_extra_iterator)
assert_frame_equal(self.frame.data, self.test_frame_extra, check_like=True)
def test_adding_content_mixed(self):
self.skipTest("Bug: GH-109")
old = list(self.get_iterator())[-2:]
def update(ind):
ind.properties["value"] = int(ind.properties["value"]) * 5
return ind
updated = list(map(update, old))
self.frame.load_content(
lambda: iter(list(self.get_extra_iterator()) + updated)
)
self.test_frame_extra["value_number"].loc[[7, 8]] *= 5
assert_frame_equal(self.frame.data, self.test_frame_extra, check_like=True)
def test_resetting_features_and_content(self):
features = [
TestNumericFeaturesFrame.is_dutch
]
frame = NumericFeaturesFrame(
TestNumericFeaturesFrame.get_identifier,
features,
self.get_iterator
)
frame.reset(
features=[
TestNumericFeaturesFrame.value_number,
TestNumericFeaturesFrame.is_english
],
content=self.get_extra_iterator
)
self.test_frame_extra = self.test_frame_extra.drop([4, 5, 6, 7, 8], axis=0)
self.test_frame_extra = self.test_frame_extra.drop(labels="is_dutch", axis=1)
assert_frame_equal(frame.data, self.test_frame_extra, check_like=True)
sorted_feature_names = ["is_english", "value_number"]
self.assertEquals(
sorted(frame.features.keys()),
sorted_feature_names
)
def test_resetting_features(self):
features = [
TestNumericFeaturesFrame.is_dutch
]
frame = NumericFeaturesFrame(
TestNumericFeaturesFrame.get_identifier,
features,
self.get_iterator
)
frame.reset(features=[
TestNumericFeaturesFrame.value_number,
TestNumericFeaturesFrame.is_english
])
self.test_frame = self.test_frame.drop(labels="is_dutch", axis=1)
assert_frame_equal(frame.data, self.test_frame, check_like=True)
sorted_feature_names = ["is_english", "value_number"]
self.assertEquals(
sorted(frame.features.keys()),
sorted_feature_names
)
def test_resetting_features_no_content(self):
features = [
TestNumericFeaturesFrame.is_dutch
]
frame = NumericFeaturesFrame(
TestNumericFeaturesFrame.get_identifier,
features
)
frame.reset(features=[
TestNumericFeaturesFrame.value_number,
TestNumericFeaturesFrame.is_english
])
self.test_frame = self.test_frame.drop(labels="is_dutch", axis=1)
assert_frame_equal(frame.data, self.test_frame[0:0], check_like=True)
sorted_feature_names = ["is_english", "value_number"]
self.assertEquals(
sorted(frame.features.keys()),
sorted_feature_names
)
def test_resetting_content(self):
self.frame.reset(content=self.get_extra_iterator)
self.test_frame_extra = self.test_frame_extra.drop([4, 5, 6, 7, 8], axis=0)
assert_frame_equal(self.frame.data, self.test_frame_extra, check_like=True)
def test_resetting_content_no_features(self):
self.frame.features = None
self.frame.reset(content=self.get_extra_iterator)
self.assertEqual(self.frame.content.__name__, self.get_extra_iterator.__name__) # TODO: better equality test
assert_frame_equal(self.frame.data, pd.DataFrame(dtype=np.float), check_like=True)
def test_clean_params(self):
test_params = {
"is_dutch": "1", # get converted to float
"is_french": 1.0, # gets skipped
"$is_french": 1.0, # gets skipped (without errors)
"value_number": None, # gets skipped a a non-numeric
"is_english": "test", # gets skipped as a non-numeric
"$value_number": 2.0
}
for function in [str, int, float]:
test_params["is_dutch"] = function(test_params["is_dutch"])
cleaned_params = self.frame.clean_params(test_params)
self.assertEquals(cleaned_params, {"is_dutch": 1.0, "value_number": 2.0})
test_error_params = {
"is_dutch": "1",
"$is_dutch": 1.0,
}
try:
self.frame.clean_params(test_error_params)
self.fail("Clean params should have raised for invalid params")
except ValueError:
pass
def test_rank_by_params(self):
ranking = self.frame.rank_by_params({"is_dutch": 1, "value_number": 1})
self.assertEquals(ranking, [5, 8, 6, 4, 7])
ranking = self.frame.rank_by_params({"is_dutch": 0.5, "value_number": -1, "is_english": 2, "is_french": 100})
self.assertEquals(ranking, [7, 8, 6, 4, 5])
def test_get_content_hash(self):
self.skipTest("not tested")
def test_get_feature_value(self):
self.skipTest("not tested")
def test_get_feature_series(self):
self.skipTest("not tested")