本文整理汇总了Python中numpy.linalg.eigh方法的典型用法代码示例。如果您正苦于以下问题：Python linalg.eigh方法的具体用法？Python linalg.eigh怎么用？Python linalg.eigh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.linalg的用法示例。
在下文中一共展示了linalg.eigh方法的7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: do
# 需要导入模块: from numpy import linalg [as 别名]
# 或者: from numpy.linalg import eigh [as 别名]
def do(self, a, b, tags):
# note that eigenvalue arrays returned by eig must be sorted since
# their order isn't guaranteed.
ev, evc = linalg.eigh(a)
evalues, evectors = linalg.eig(a)
evalues.sort(axis=-1)
assert_almost_equal(ev, evalues)
assert_allclose(dot_generalized(a, evc),
np.asarray(ev)[..., None, :] * np.asarray(evc),
rtol=get_rtol(ev.dtype))
ev2, evc2 = linalg.eigh(a, 'U')
assert_almost_equal(ev2, evalues)
assert_allclose(dot_generalized(a, evc2),
np.asarray(ev2)[..., None, :] * np.asarray(evc2),
rtol=get_rtol(ev.dtype), err_msg=repr(a)) 示例2: test_UPLO
# 需要导入模块: from numpy import linalg [as 别名]
# 或者: from numpy.linalg import eigh [as 别名]
def test_UPLO(self):
Klo = np.array([[0, 0], [1, 0]], dtype=np.double)
Kup = np.array([[0, 1], [0, 0]], dtype=np.double)
tgt = np.array([-1, 1], dtype=np.double)
rtol = get_rtol(np.double)
# Check default is 'L'
w, v = np.linalg.eigh(Klo)
assert_allclose(w, tgt, rtol=rtol)
# Check 'L'
w, v = np.linalg.eigh(Klo, UPLO='L')
assert_allclose(w, tgt, rtol=rtol)
# Check 'l'
w, v = np.linalg.eigh(Klo, UPLO='l')
assert_allclose(w, tgt, rtol=rtol)
# Check 'U'
w, v = np.linalg.eigh(Kup, UPLO='U')
assert_allclose(w, tgt, rtol=rtol)
# Check 'u'
w, v = np.linalg.eigh(Kup, UPLO='u')
assert_allclose(w, tgt, rtol=rtol) 示例3: test_0_size
# 需要导入模块: from numpy import linalg [as 别名]
# 或者: from numpy.linalg import eigh [as 别名]
def test_0_size(self):
# Check that all kinds of 0-sized arrays work
class ArraySubclass(np.ndarray):
pass
a = np.zeros((0, 1, 1), dtype=np.int_).view(ArraySubclass)
res, res_v = linalg.eigh(a)
assert_(res_v.dtype.type is np.float64)
assert_(res.dtype.type is np.float64)
assert_equal(a.shape, res_v.shape)
assert_equal((0, 1), res.shape)
# This is just for documentation, it might make sense to change:
assert_(isinstance(a, np.ndarray))
a = np.zeros((0, 0), dtype=np.complex64).view(ArraySubclass)
res, res_v = linalg.eigh(a)
assert_(res_v.dtype.type is np.complex64)
assert_(res.dtype.type is np.float32)
assert_equal(a.shape, res_v.shape)
assert_equal((0,), res.shape)
# This is just for documentation, it might make sense to change:
assert_(isinstance(a, np.ndarray)) 示例4: do
# 需要导入模块: from numpy import linalg [as 别名]
# 或者: from numpy.linalg import eigh [as 别名]
def do(self, a, b):
# note that eigenvalue arrays returned by eig must be sorted since
# their order isn't guaranteed.
ev, evc = linalg.eigh(a)
evalues, evectors = linalg.eig(a)
evalues.sort(axis=-1)
assert_almost_equal(ev, evalues)
assert_allclose(dot_generalized(a, evc),
np.asarray(ev)[..., None, :] * np.asarray(evc),
rtol=get_rtol(ev.dtype))
ev2, evc2 = linalg.eigh(a, 'U')
assert_almost_equal(ev2, evalues)
assert_allclose(dot_generalized(a, evc2),
np.asarray(ev2)[..., None, :] * np.asarray(evc2),
rtol=get_rtol(ev.dtype), err_msg=repr(a)) 示例5: do
# 需要导入模块: from numpy import linalg [as 别名]
# 或者: from numpy.linalg import eigh [as 别名]
def do(self, a, b):
# note that eigenvalue arrays must be sorted since
# their order isn't guaranteed.
ev, evc = linalg.eigh(a)
evalues, evectors = linalg.eig(a)
ev.sort(axis=-1)
evalues.sort(axis=-1)
assert_almost_equal(ev, evalues)
assert_allclose(dot_generalized(a, evc),
np.asarray(ev)[...,None,:] * np.asarray(evc),
rtol=get_rtol(ev.dtype))
ev2, evc2 = linalg.eigh(a, 'U')
ev2.sort(axis=-1)
assert_almost_equal(ev2, evalues)
assert_allclose(dot_generalized(a, evc2),
np.asarray(ev2)[...,None,:] * np.asarray(evc2),
rtol=get_rtol(ev.dtype), err_msg=repr(a)) 示例6: test_UPLO
# 需要导入模块: from numpy import linalg [as 别名]
# 或者: from numpy.linalg import eigh [as 别名]
def test_UPLO(self):
Klo = np.array([[0, 0],[1, 0]], dtype=np.double)
Kup = np.array([[0, 1],[0, 0]], dtype=np.double)
tgt = np.array([-1, 1], dtype=np.double)
rtol = get_rtol(np.double)
# Check default is 'L'
w, v = np.linalg.eigh(Klo)
assert_allclose(np.sort(w), tgt, rtol=rtol)
# Check 'L'
w, v = np.linalg.eigh(Klo, UPLO='L')
assert_allclose(np.sort(w), tgt, rtol=rtol)
# Check 'l'
w, v = np.linalg.eigh(Klo, UPLO='l')
assert_allclose(np.sort(w), tgt, rtol=rtol)
# Check 'U'
w, v = np.linalg.eigh(Kup, UPLO='U')
assert_allclose(np.sort(w), tgt, rtol=rtol)
# Check 'u'
w, v = np.linalg.eigh(Kup, UPLO='u')
assert_allclose(np.sort(w), tgt, rtol=rtol) 示例7: spectral_decomposition
# 需要导入模块: from numpy import linalg [as 别名]
# 或者: from numpy.linalg import eigh [as 别名]
def spectral_decomposition(A):
r"""Spectral decomposition of a Hermitian matrix.
Args:
A (array): Hermitian matrix
Returns:
(vector[float], list[array[complex]]): (a, P): eigenvalues and hermitian projectors
such that :math:`A = \sum_k a_k P_k`.
"""
d, v = eigh(A)
P = []
for k in range(d.shape[0]):
temp = v[:, k]
P.append(np.outer(temp, temp.conj()))
return d, P
# ========================================================
# fixed gates/observables
# ========================================================