def test_pickle_features(es):
dfs_obj = DeepFeatureSynthesis(target_entity_id='sessions',
entityset=es,
filters=[],
agg_primitives=[Last, Mean],
trans_primitives=[],
max_features=20)
features_no_pickle = dfs_obj.build_features()
dir_path = os.path.dirname(os.path.realpath(__file__))
filepath = os.path.join(dir_path, 'test_feature')
es_filepath = os.path.join(dir_path, 'test_entityset')
# pickle entityset
save_obj_pickle(features_no_pickle[0].entityset, es_filepath)
ft.save_features(features_no_pickle, filepath)
features_pickle = ft.load_features(filepath, es)
for feat_1, feat_2 in zip(features_no_pickle, features_pickle):
assert feat_1.hash() == feat_2.hash()
assert feat_1.entityset == feat_2.entityset
# file is smaller than entityset in memory
assert os.path.getsize(filepath) < getsize(feat_1.entityset)
# file is smaller than entityset pickled
assert os.path.getsize(filepath) < os.path.getsize(es_filepath)
os.remove(filepath)
os.remove(es_filepath)
def test_pickle_features_with_custom_primitive(es):
NewMean = make_agg_primitive(
np.nanmean,
name="NewMean",
input_types=[Numeric],
return_type=Numeric,
description="Calculate means ignoring nan values")
dfs_obj = DeepFeatureSynthesis(target_entity_id='sessions',
entityset=es,
agg_primitives=[Last, Mean, NewMean],
trans_primitives=[],
max_features=20)
features_no_pickle = dfs_obj.build_features()
assert any([isinstance(feat, NewMean) for feat in features_no_pickle])
dir_path = os.path.dirname(os.path.realpath(__file__))
filepath = os.path.join(dir_path, 'test_feature')
es_filepath = os.path.join(dir_path, 'test_entityset')
# pickle entityset
save_obj_pickle(es, es_filepath)
ft.save_features(features_no_pickle, filepath)
features_pickle = ft.load_features(filepath)
for feat_1, feat_2 in zip(features_no_pickle, features_pickle):
assert feat_1.hash() == feat_2.hash()
assert feat_1.entityset == feat_2.entityset
# file is smaller than entityset in memory
assert os.path.getsize(filepath) < getsize(es)
# file is smaller than entityset pickled
assert os.path.getsize(filepath) < os.path.getsize(es_filepath)
os.remove(filepath)
os.remove(es_filepath)
def test_pickle_features_with_custom_primitive(es):
NewMean = make_agg_primitive(
np.nanmean,
name="NewMean",
input_types=[Numeric],
return_type=Numeric,
description="Calculate means ignoring nan values")
dfs_obj = DeepFeatureSynthesis(target_entity_id='sessions',
entityset=es,
agg_primitives=[Last, Mean, NewMean],
trans_primitives=[],
max_features=20)
features_no_pickle = dfs_obj.build_features()
assert any([isinstance(feat, NewMean) for feat in features_no_pickle])
dir_path = os.path.dirname(os.path.realpath(__file__))
filepath = os.path.join(dir_path, 'test_feature')
es_filepath = os.path.join(dir_path, 'test_entityset')
# pickle entityset
save_obj_pickle(es, es_filepath)
ft.save_features(features_no_pickle, filepath)
features_pickle = ft.load_features(filepath)
for feat_1, feat_2 in zip(features_no_pickle, features_pickle):
assert feat_1.hash() == feat_2.hash()
assert feat_1.entityset == feat_2.entityset
# file is smaller than entityset in memory
assert os.path.getsize(filepath) < asizeof(es)
# file is smaller than entityset pickled
assert os.path.getsize(filepath) < os.path.getsize(es_filepath)
os.remove(filepath)
os.remove(es_filepath)
def test_pickle_features(es):
dfs_obj = DeepFeatureSynthesis(target_entity_id='sessions',
entityset=es,
agg_primitives=[Last, Mean],
trans_primitives=[],
max_features=20)
features_no_pickle = dfs_obj.build_features()
dir_path = os.path.dirname(os.path.realpath(__file__))
filepath = os.path.join(dir_path, 'test_feature')
es_filepath = os.path.join(dir_path, 'test_entityset')
# pickle entityset
save_obj_pickle(es, es_filepath)
ft.save_features(features_no_pickle, filepath)
features_pickle = ft.load_features(filepath)
for feat_1, feat_2 in zip(features_no_pickle, features_pickle):
assert feat_1.hash() == feat_2.hash()
assert feat_1.entityset == feat_2.entityset
# file is smaller than entityset in memory
assert os.path.getsize(filepath) < asizeof(es)
# file is smaller than entityset pickled
assert os.path.getsize(filepath) < os.path.getsize(es_filepath)
os.remove(filepath)
os.remove(es_filepath)
def test_pickle_features_with_custom_primitive(es):
NewMax = make_agg_primitive(
lambda x: max(x),
name="NewMax",
input_types=[Numeric],
return_type=Numeric,
description="Calculate means ignoring nan values")
features_no_pickle = ft.dfs(target_entity='sessions',
entityset=es,
agg_primitives=["Last", "Mean", NewMax],
features_only=True)
assert any(
[isinstance(feat.primitive, NewMax) for feat in features_no_pickle])
dir_path = os.path.dirname(os.path.realpath(__file__))
filepath = os.path.join(dir_path, 'test_feature')
es_filepath = os.path.join(dir_path, 'test_entityset')
# pickle entityset
save_obj_pickle(es, es_filepath)
ft.save_features(features_no_pickle, filepath)
features_pickle = ft.load_features(filepath)
for feat_1, feat_2 in zip(features_no_pickle, features_pickle):
assert feat_1.hash() == feat_2.hash()
assert feat_1.entityset == feat_2.entityset
# file is smaller than entityset in memory
assert os.path.getsize(filepath) < asizeof(es)
# file is smaller than entityset pickled
assert os.path.getsize(filepath) < os.path.getsize(es_filepath)
os.remove(filepath)
os.remove(es_filepath)
def test_pickle_features(es):
features_no_pickle = ft.dfs(target_entity='sessions',
entityset=es,
features_only=True)
dir_path = os.path.dirname(os.path.realpath(__file__))
filepath = os.path.join(dir_path, 'test_feature')
es_filepath = os.path.join(dir_path, 'test_entityset')
# pickle entityset
save_obj_pickle(es, es_filepath)
ft.save_features(features_no_pickle, filepath)
features_pickle = ft.load_features(filepath)
for feat_1, feat_2 in zip(features_no_pickle, features_pickle):
assert feat_1.hash() == feat_2.hash()
assert feat_1.entityset == feat_2.entityset
# file is smaller than entityset in memory
assert os.path.getsize(filepath) < asizeof(es)
# file is smaller than entityset pickled
assert os.path.getsize(filepath) < os.path.getsize(es_filepath)
os.remove(filepath)
os.remove(es_filepath)
