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Programmation Python
Les fondamentaux
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Module « scipy.linalg »
Signature de la fonction ishermitian
def ishermitian(a, atol=None, rtol=None)
Description
help(scipy.linalg.ishermitian)
ishermitian(a, atol=None, rtol=None)
Check if a square 2D array is Hermitian.
Parameters
----------
a : ndarray
Input array of size (N, N)
atol : float, optional
Absolute error bound
rtol : float, optional
Relative error bound
Returns
-------
her : bool
Returns True if the array Hermitian.
Raises
------
TypeError
If the dtype of the array is not supported, in particular, NumPy
float16, float128 and complex256 dtypes.
See Also
--------
issymmetric : Check if a square 2D array is symmetric
Notes
-----
For square empty arrays the result is returned True by convention.
`numpy.inf` will be treated as a number, that is to say ``[[1, inf],
[inf, 2]]`` will return ``True``. On the other hand `numpy.nan` is never
symmetric, say, ``[[1, nan], [nan, 2]]`` will return ``False``.
When ``atol`` and/or ``rtol`` are set to , then the comparison is performed
by `numpy.allclose` and the tolerance values are passed to it. Otherwise an
exact comparison against zero is performed by internal functions. Hence
performance can improve or degrade depending on the size and dtype of the
array. If one of ``atol`` or ``rtol`` given the other one is automatically
set to zero.
Examples
--------
>>> import numpy as np
>>> from scipy.linalg import ishermitian
>>> A = np.arange(9).reshape(3, 3)
>>> A = A + A.T
>>> ishermitian(A)
True
>>> A = np.array([[1., 2. + 3.j], [2. - 3.j, 4.]])
>>> ishermitian(A)
True
>>> Ac = np.array([[1. + 1.j, 3.j], [3.j, 2.]])
>>> ishermitian(Ac) # not Hermitian but symmetric
False
>>> Af = np.array([[0, 1 + 1j], [1 - (1+1e-12)*1j, 0]])
>>> ishermitian(Af)
False
>>> ishermitian(Af, atol=5e-11) # almost hermitian with atol
True
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