本文整理汇总了Python中scipy.stats.circmean方法的典型用法代码示例。如果您正苦于以下问题：Python stats.circmean方法的具体用法？Python stats.circmean怎么用？Python stats.circmean使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类scipy.stats的用法示例。
在下文中一共展示了stats.circmean方法的15个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_circmean
# 需要导入模块: from scipy import stats [as 别名]
# 或者: from scipy.stats import circmean [as 别名]
def test_circmean(self):
""" Test custom circular mean."""
ref_mean = scistats.circmean(self.test_angles, **self.circ_kwargs)
test_mean = pystats.nan_circmean(self.test_angles, **self.circ_kwargs)
assert ref_mean == test_mean 示例2: test_circmean_nan
# 需要导入模块: from scipy import stats [as 别名]
# 或者: from scipy.stats import circmean [as 别名]
def test_circmean_nan(self):
""" Test custom circular mean with NaN."""
ref_mean = scistats.circmean(self.test_angles, **self.circ_kwargs)
ref_nan = scistats.circmean(self.test_nan, **self.circ_kwargs)
test_nan = pystats.nan_circmean(self.test_nan, **self.circ_kwargs)
assert np.isnan(ref_nan)
assert ref_mean == test_nan 示例3: test_deprecation_warning_circmean
# 需要导入模块: from scipy import stats [as 别名]
# 或者: from scipy.stats import circmean [as 别名]
def test_deprecation_warning_circmean(self):
"""Test if circmean in stats is deprecated"""
with warnings.catch_warnings(record=True) as war:
try:
pystats.nan_circmean(None)
except TypeError:
# Setting input to None should produce a TypeError after
# warning is generated
pass
assert len(war) >= 1
assert war[0].category == DeprecationWarning 示例4: test_circfuncs
# 需要导入模块: from scipy import stats [as 别名]
# 或者: from scipy.stats import circmean [as 别名]
def test_circfuncs(self):
x = np.array([355,5,2,359,10,350])
M = stats.circmean(x, high=360)
Mval = 0.167690146
assert_allclose(M, Mval, rtol=1e-7)
V = stats.circvar(x, high=360)
Vval = 42.51955609
assert_allclose(V, Vval, rtol=1e-7)
S = stats.circstd(x, high=360)
Sval = 6.520702116
assert_allclose(S, Sval, rtol=1e-7) 示例5: test_circfuncs_small
# 需要导入模块: from scipy import stats [as 别名]
# 或者: from scipy.stats import circmean [as 别名]
def test_circfuncs_small(self):
x = np.array([20,21,22,18,19,20.5,19.2])
M1 = x.mean()
M2 = stats.circmean(x, high=360)
assert_allclose(M2, M1, rtol=1e-5)
V1 = x.var()
V2 = stats.circvar(x, high=360)
assert_allclose(V2, V1, rtol=1e-4)
S1 = x.std()
S2 = stats.circstd(x, high=360)
assert_allclose(S2, S1, rtol=1e-4) 示例6: test_circmean_axis
# 需要导入模块: from scipy import stats [as 别名]
# 或者: from scipy.stats import circmean [as 别名]
def test_circmean_axis(self):
x = np.array([[355,5,2,359,10,350],
[351,7,4,352,9,349],
[357,9,8,358,4,356]])
M1 = stats.circmean(x, high=360)
M2 = stats.circmean(x.ravel(), high=360)
assert_allclose(M1, M2, rtol=1e-14)
M1 = stats.circmean(x, high=360, axis=1)
M2 = [stats.circmean(x[i], high=360) for i in range(x.shape[0])]
assert_allclose(M1, M2, rtol=1e-14)
M1 = stats.circmean(x, high=360, axis=0)
M2 = [stats.circmean(x[:,i], high=360) for i in range(x.shape[1])]
assert_allclose(M1, M2, rtol=1e-14) 示例7: test_circfuncs_array_like
# 需要导入模块: from scipy import stats [as 别名]
# 或者: from scipy.stats import circmean [as 别名]
def test_circfuncs_array_like(self):
x = [355,5,2,359,10,350]
assert_allclose(stats.circmean(x, high=360), 0.167690146, rtol=1e-7)
assert_allclose(stats.circvar(x, high=360), 42.51955609, rtol=1e-7)
assert_allclose(stats.circstd(x, high=360), 6.520702116, rtol=1e-7) 示例8: test_empty
# 需要导入模块: from scipy import stats [as 别名]
# 或者: from scipy.stats import circmean [as 别名]
def test_empty(self):
assert_(np.isnan(stats.circmean([])))
assert_(np.isnan(stats.circstd([])))
assert_(np.isnan(stats.circvar([]))) 示例9: test_circfuncs
# 需要导入模块: from scipy import stats [as 别名]
# 或者: from scipy.stats import circmean [as 别名]
def test_circfuncs(self):
x = np.array([355, 5, 2, 359, 10, 350])
M = stats.circmean(x, high=360)
Mval = 0.167690146
assert_allclose(M, Mval, rtol=1e-7)
V = stats.circvar(x, high=360)
Vval = 42.51955609
assert_allclose(V, Vval, rtol=1e-7)
S = stats.circstd(x, high=360)
Sval = 6.520702116
assert_allclose(S, Sval, rtol=1e-7) 示例10: test_circfuncs_small
# 需要导入模块: from scipy import stats [as 别名]
# 或者: from scipy.stats import circmean [as 别名]
def test_circfuncs_small(self):
x = np.array([20, 21, 22, 18, 19, 20.5, 19.2])
M1 = x.mean()
M2 = stats.circmean(x, high=360)
assert_allclose(M2, M1, rtol=1e-5)
V1 = x.var()
V2 = stats.circvar(x, high=360)
assert_allclose(V2, V1, rtol=1e-4)
S1 = x.std()
S2 = stats.circstd(x, high=360)
assert_allclose(S2, S1, rtol=1e-4) 示例11: test_circmean_axis
# 需要导入模块: from scipy import stats [as 别名]
# 或者: from scipy.stats import circmean [as 别名]
def test_circmean_axis(self):
x = np.array([[355, 5, 2, 359, 10, 350],
[351, 7, 4, 352, 9, 349],
[357, 9, 8, 358, 4, 356]])
M1 = stats.circmean(x, high=360)
M2 = stats.circmean(x.ravel(), high=360)
assert_allclose(M1, M2, rtol=1e-14)
M1 = stats.circmean(x, high=360, axis=1)
M2 = [stats.circmean(x[i], high=360) for i in range(x.shape[0])]
assert_allclose(M1, M2, rtol=1e-14)
M1 = stats.circmean(x, high=360, axis=0)
M2 = [stats.circmean(x[:, i], high=360) for i in range(x.shape[1])]
assert_allclose(M1, M2, rtol=1e-14) 示例12: test_circfuncs_array_like
# 需要导入模块: from scipy import stats [as 别名]
# 或者: from scipy.stats import circmean [as 别名]
def test_circfuncs_array_like(self):
x = [355, 5, 2, 359, 10, 350]
assert_allclose(stats.circmean(x, high=360), 0.167690146, rtol=1e-7)
assert_allclose(stats.circvar(x, high=360), 42.51955609, rtol=1e-7)
assert_allclose(stats.circstd(x, high=360), 6.520702116, rtol=1e-7) 示例13: test_circmean_range
# 需要导入模块: from scipy import stats [as 别名]
# 或者: from scipy.stats import circmean [as 别名]
def test_circmean_range(self):
# regression test for gh-6420: circmean(..., high, low) must be
# between `high` and `low`
m = stats.circmean(np.arange(0, 2, 0.1), np.pi, -np.pi)
assert_(m < np.pi)
assert_(m > -np.pi) 示例14: test_circfuncs_unit8
# 需要导入模块: from scipy import stats [as 别名]
# 或者: from scipy.stats import circmean [as 别名]
def test_circfuncs_unit8(self):
# regression test for gh-7255: overflow when working with
# numpy uint8 data type
x = np.array([150, 10], dtype='uint8')
assert_equal(stats.circmean(x, high=180), 170.0)
assert_allclose(stats.circvar(x, high=180), 437.45871686, rtol=1e-7)
assert_allclose(stats.circstd(x, high=180), 20.91551378, rtol=1e-7) 示例15: test_can_predict_from_data
# 需要导入模块: from scipy import stats [as 别名]
# 或者: from scipy.stats import circmean [as 别名]
def test_can_predict_from_data():
Invt_model = InvertedEncoding()
Invt_model.fit(X, y)
m_reconstruct = []
for j in np.arange(dim):
preds = Invt_model.predict(X2[n_*j:n_*(j+1), :])
tmp = circmean(np.deg2rad(preds))
m_reconstruct.append(np.rad2deg(tmp))
logger.info('Reconstructed angles: ' + str(m_reconstruct))
# Show that prediction is invalid when input data is wrong size