本文整理汇总了Python中numpy.core.umath_tests.euclidean_pdist方法的典型用法代码示例。如果您正苦于以下问题：Python umath_tests.euclidean_pdist方法的具体用法？Python umath_tests.euclidean_pdist怎么用？Python umath_tests.euclidean_pdist使用的例子？那么恭喜您, 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numpy.core.umath_tests的用法示例。
在下文中一共展示了umath_tests.euclidean_pdist方法的3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_euclidean_pdist
# 需要导入模块: from numpy.core import umath_tests [as 别名]
# 或者: from numpy.core.umath_tests import euclidean_pdist [as 别名]
def test_euclidean_pdist(self):
a = np.arange(12, dtype=np.float).reshape(4, 3)
out = np.empty((a.shape[0] * (a.shape[0] - 1) // 2,), dtype=a.dtype)
umt.euclidean_pdist(a, out)
b = np.sqrt(np.sum((a[:, None] - a)**2, axis=-1))
b = b[~np.tri(a.shape[0], dtype=bool)]
assert_almost_equal(out, b)
# An output array is required to determine p with signature (n,d)->(p)
assert_raises(ValueError, umt.euclidean_pdist, a) 示例2: test_euclidean_pdist
# 需要导入模块: from numpy.core import umath_tests [as 别名]
# 或者: from numpy.core.umath_tests import euclidean_pdist [as 别名]
def test_euclidean_pdist(self):
a = np.arange(12, dtype=float).reshape(4, 3)
out = np.empty((a.shape[0] * (a.shape[0] - 1) // 2,), dtype=a.dtype)
umt.euclidean_pdist(a, out)
b = np.sqrt(np.sum((a[:, None] - a)**2, axis=-1))
b = b[~np.tri(a.shape[0], dtype=bool)]
assert_almost_equal(out, b)
# An output array is required to determine p with signature (n,d)->(p)
assert_raises(ValueError, umt.euclidean_pdist, a) 示例3: test_unary_gufunc_fuzz
# 需要导入模块: from numpy.core import umath_tests [as 别名]
# 或者: from numpy.core.umath_tests import euclidean_pdist [as 别名]
def test_unary_gufunc_fuzz(self):
shapes = [7, 13, 8, 21, 29, 32]
gufunc = umath_tests.euclidean_pdist
rng = np.random.RandomState(1234)
for ndim in range(2, 6):
x = rng.rand(*shapes[:ndim])
it = iter_random_view_pairs(x, same_steps=False, equal_size=True)
min_count = 500 // (ndim + 1)**2
overlapping = 0
while overlapping < min_count:
a, b = next(it)
if min(a.shape[-2:]) < 2 or min(b.shape[-2:]) < 2 or a.shape[-1] < 2:
continue
# Ensure the shapes are so that euclidean_pdist is happy
if b.shape[-1] > b.shape[-2]:
b = b[...,0,:]
else:
b = b[...,:,0]
n = a.shape[-2]
p = n * (n - 1) // 2
if p <= b.shape[-1] and p > 0:
b = b[...,:p]
else:
n = max(2, int(np.sqrt(b.shape[-1]))//2)
p = n * (n - 1) // 2
a = a[...,:n,:]
b = b[...,:p]
# Call
if np.shares_memory(a, b):
overlapping += 1
with np.errstate(over='ignore', invalid='ignore'):
assert_copy_equivalent(gufunc, [a], out=b)