def test_robust_kurtosis_dg(self):
# Test custom delta, gamma in kr4
x = self.kurtosis_x
delta, gamma = (10.0, 45.0)
kurtosis = robust_kurtosis(self.kurtosis_x, dg=(delta,gamma), excess=False)
q = np.percentile(x,[delta, 100.0-delta, gamma, 100.0-gamma])
assert_almost_equal(kurtosis[3], (q[1] - q[0]) / (q[3] - q[2]))
def test_robust_kurtosis_dg(self):
# Test custom delta, gamma in kr4
x = self.kurtosis_x
delta, gamma = (10.0, 45.0)
kurtosis = robust_kurtosis(self.kurtosis_x, dg=(delta,gamma), excess=False)
q = np.percentile(x,[delta, 100.0-delta, gamma, 100.0-gamma])
assert_almost_equal(kurtosis[3], (q[1] - q[0]) / (q[3] - q[2]))
def test_robust_kurtosis_ab(self):
# Test custom alpha, beta in kr3
x = self.kurtosis_x
alpha, beta = (10.0, 45.0)
kurtosis = robust_kurtosis(self.kurtosis_x, ab=(alpha,beta), excess=False)
num = np.mean(x[x>np.percentile(x,100.0 - alpha)]) - np.mean(x[x<np.percentile(x,alpha)])
denom = np.mean(x[x>np.percentile(x,100.0 - beta)]) - np.mean(x[x<np.percentile(x,beta)])
assert_almost_equal(kurtosis[2], num/denom)
def test_robust_kurtosis_ab(self):
# Test custom alpha, beta in kr3
x = self.kurtosis_x
alpha, beta = (10.0, 45.0)
kurtosis = robust_kurtosis(self.kurtosis_x, ab=(alpha,beta), excess=False)
num = np.mean(x[x>np.percentile(x,100.0 - alpha)]) - np.mean(x[x<np.percentile(x,alpha)])
denom = np.mean(x[x>np.percentile(x,100.0 - beta)]) - np.mean(x[x<np.percentile(x,beta)])
assert_almost_equal(kurtosis[2], num/denom)
def test_robust_kurtosis_excess_false(self):
x = self.kurtosis_x
expected = self.expected_kurtosis + self.kurtosis_constants
kurtosis = np.array(robust_kurtosis(x, excess=False))
assert_almost_equal(expected, kurtosis)
def test_robust_kurtosis_3d(self):
x = np.tile(self.kurtosis_x, (10, 10, 1))
kurtosis = np.array(robust_kurtosis(x, axis=2))
for i, r in enumerate(self.expected_kurtosis):
assert_almost_equal(r * np.ones((10, 10)), kurtosis[i])
def test_robust_kurtosis(self):
x = self.kurtosis_x
assert_almost_equal(np.array(robust_kurtosis(x)), self.expected_kurtosis)
def test_robust_kurtosis_1d_2d(self, reset_randomstate):
x = np.random.randn(100)
y = x[:, None]
kr_x = np.array(robust_kurtosis(x))
kr_y = np.array(robust_kurtosis(y, axis=None))
assert_almost_equal(kr_x, kr_y)
def test_robust_kurtosis_excess_false(self):
x = self.kurtosis_x
expected = self.expected_kurtosis + self.kurtosis_constants
kurtosis = np.array(robust_kurtosis(x, excess=False))
assert_almost_equal(expected, kurtosis)
def test_robust_kurtosis_3d(self):
x = np.tile(self.kurtosis_x, (10, 10, 1))
kurtosis = np.array(robust_kurtosis(x, axis=2))
for i, r in enumerate(self.expected_kurtosis):
assert_almost_equal(r * np.ones((10, 10)), kurtosis[i])
def test_robust_kurtosis(self):
x = self.kurtosis_x
assert_almost_equal(np.array(robust_kurtosis(x)), self.expected_kurtosis)
def test_robust_kurtosis_1d_2d(self):
x = np.random.randn(100)
y = x[:, None]
kr_x = np.array(robust_kurtosis(x))
kr_y = np.array(robust_kurtosis(y, axis=None))
assert_almost_equal(kr_x, kr_y)
