def test_haversine(es):
log_latlong_feat = es['log']['latlong']
log_latlong_feat2 = es['log']['latlong2']
haversine = ft.Feature([log_latlong_feat, log_latlong_feat2],
primitive=Haversine)
features = [haversine]
df = ft.calculate_feature_matrix(entityset=es, features=features,
instance_ids=range(15))
values = df[haversine.get_name()].values
real = [0, 525.318462, 1045.32190304, 1554.56176802, 2047.3294327, 0,
138.16578931, 276.20524822, 413.99185444, 0, 0, 525.318462, 0,
741.57941183, 1467.52760175]
assert len(values) == 15
assert np.allclose(values, real, atol=0.0001)
haversine = ft.Feature([log_latlong_feat, log_latlong_feat2],
primitive=Haversine(unit='kilometers'))
features = [haversine]
df = ft.calculate_feature_matrix(entityset=es, features=features,
instance_ids=range(15))
values = df[haversine.get_name()].values
real_km = [0, 845.41812212, 1682.2825471, 2501.82467535, 3294.85736668,
0, 222.35628593, 444.50926278, 666.25531268, 0, 0,
845.41812212, 0, 1193.45638714, 2361.75676089]
assert len(values) == 15
assert np.allclose(values, real_km, atol=0.0001)
error_text = "Invalid unit inches provided. Must be one of"
with pytest.raises(ValueError, match=error_text):
Haversine(unit='inches')
def test_haversine(es):
log_latlong_feat = es['log']['latlong']
log_latlong_feat2 = es['log']['latlong2']
haversine = Haversine(log_latlong_feat, log_latlong_feat2)
features = [haversine]
pandas_backend = PandasBackend(es, features)
df = pandas_backend.calculate_all_features(instance_ids=range(15),
time_last=None)
values = df[haversine.get_name()].values
real = [0., 524.15585776, 1043.00845747, 1551.12130243,
2042.79840241, 0., 137.86000883, 275.59396684,
413.07563177, 0., 0., 524.15585776,
0., 739.93819145, 1464.27975511]
assert len(values) == 15
for i, v in enumerate(real):
assert v - values[i] < .0001
def test_haversine(es):
log_latlong_feat = es['log']['latlong']
log_latlong_feat2 = es['log']['latlong2']
haversine = Haversine(log_latlong_feat, log_latlong_feat2)
features = [haversine]
pandas_backend = PandasBackend(es, features)
df = pandas_backend.calculate_all_features(instance_ids=range(15),
time_last=None)
values = df[haversine.get_name()].values
real = [
0., 524.15585776, 1043.00845747, 1551.12130243, 2042.79840241, 0.,
137.86000883, 275.59396684, 413.07563177, 0., 0., 524.15585776, 0.,
739.93819145, 1464.27975511
]
assert len(values) == 15
for i, v in enumerate(real):
assert v - values[i] < .0001
def test_call_multiple_args():
primitive = Haversine()
data1 = [(42.4, -71.1), (40.0, -122.4)]
data2 = [(40.0, -122.4), (41.2, -96.75)]
answer = [2631.231, 1343.289]
for _ in range(2):
assert np.round(primitive(data1, data2), 3).tolist() == answer
class DaskCompatibleHaversine(DaskCompatibleTransformPrimitive):
stub = Haversine(unit='kilometers')
name = f'{stub.name}_'
input_types = stub.input_types
return_type = stub.return_type
def fn_pd(self, x1, *args):
return self.stub.get_function()(x1, args[0])
def generate_name(self, base_feature_names):
return self.stub.generate_name(base_feature_names)
def test_haversine(es):
log_latlong_feat = es['log']['latlong']
log_latlong_feat2 = es['log']['latlong2']
haversine = ft.Feature([log_latlong_feat, log_latlong_feat2],
primitive=Haversine)
features = [haversine]
df = ft.calculate_feature_matrix(entityset=es,
features=features,
instance_ids=range(15))
values = df[haversine.get_name()].values
real = [
0., 524.15585776, 1043.00845747, 1551.12130243, 2042.79840241, 0.,
137.86000883, 275.59396684, 413.07563177, 0., 0., 524.15585776, 0.,
739.93819145, 1464.27975511
]
assert len(values) == 15
assert np.allclose(values, real, atol=0.0001)
haversine = ft.Feature([log_latlong_feat, log_latlong_feat2],
primitive=Haversine(unit='kilometers'))
features = [haversine]
df = ft.calculate_feature_matrix(entityset=es,
features=features,
instance_ids=range(15))
values = df[haversine.get_name()].values
real_km = [
0, 845.68234976, 1682.80832898, 2502.60659757, 3295.88714394, 0,
222.42578133, 444.64819005, 666.46354463, 0, 0, 845.68234976, 0,
1193.82939092, 2362.49490616
]
assert len(values) == 15
assert np.allclose(values, real_km, atol=0.0001)
error_text = "Invalid unit inches provided. Must be one of"
with pytest.raises(ValueError, match=error_text):
Haversine(unit='inches')