def testEuclideanDistanceSquare(self):
assertion.eq(0.0, metric.euclidean_distance_square([0], [0]))
assertion.eq(1.0,
metric.euclidean_distance_square([0.0, 1.0], [0.0, 0.0]))
assertion.eq(4.0,
metric.euclidean_distance_square([2.0, 2.0], [4.0, 2.0]))
assertion.eq(
4.0, metric.euclidean_distance_square([-2.0, 2.0], [-4.0, 2.0]))
def testCommonAndNumPyMetricsTwoDimension(self):
a = [1.2, 3.4]
b = [5.4, -7.1]
npa = numpy.array(a)
npb = numpy.array(b)
assertion.eq(metric.euclidean_distance(a, b),
metric.euclidean_distance_numpy(npa, npb))
assertion.eq(metric.euclidean_distance_square(a, b),
metric.euclidean_distance_square_numpy(npa, npb))
assertion.eq(metric.manhattan_distance(a, b),
metric.manhattan_distance_numpy(npa, npb))
assertion.eq(metric.chebyshev_distance(a, b),
metric.chebyshev_distance_numpy(npa, npb))
assertion.eq(metric.minkowski_distance(a, b, 2),
metric.minkowski_distance_numpy(npa, npb, 2))
assertion.eq(metric.minkowski_distance(a, b, 4),
metric.minkowski_distance_numpy(npa, npb, 4))
assertion.eq(metric.canberra_distance(a, b),
metric.canberra_distance_numpy(npa, npb))
assertion.eq(metric.chi_square_distance(a, b),
metric.chi_square_distance_numpy(npa, npb))
assertion.eq(metric.chi_square_distance(a, b),
metric.chi_square_distance_numpy(npa, npb))
gower = metric.distance_metric(metric.type_metric.GOWER,
data=[a, b],
numpy_usage=False)
gower_numpy = metric.distance_metric(metric.type_metric.GOWER,
data=[a, b],
numpy_usage=True)
assertion.eq(gower(a, b), gower_numpy(npa, npb))
def compute_distance(self, x, y) -> float:
return euclidean_distance_square(x, y)
def testEuclideanDistanceSquare(self):
assertion.eq(0.0, metric.euclidean_distance_square([0], [0]))
assertion.eq(1.0, metric.euclidean_distance_square([0.0, 1.0], [0.0, 0.0]))
assertion.eq(4.0, metric.euclidean_distance_square([2.0, 2.0], [4.0, 2.0]))
assertion.eq(4.0, metric.euclidean_distance_square([-2.0, 2.0], [-4.0, 2.0]))