8000 DOC: Added docstring for eigh · numpy/numpy@43c25bb · GitHub
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DOC: Added docstring for eigh
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‎numpy/core/src/umath/gufuncs_linalg.py

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"""Gufunc'ed versions of linalg.
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"""Linear Algebra functions implemented as gufuncs, so they can be broadcast.
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Notes
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-----
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This modules contains functionality that could be found in the linalg module,
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but in a gufunc-like way. This allows the use of vectorization and broadcasting
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on the operands.
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There are also some extra useful ufuncs.
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Additional functions some fused arithmetic, useful for efficient operation over
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"""
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__all__ = ['inner1d', 'innerwt', 'matrix_multiply', 'det', 'slogdet', 'inv',
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import numpy.core.umath_linalg as _impl
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import numpy as np
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"""
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<Description>
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Parameters
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----------
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<insert parameters + explanations>
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Returns
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-------
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<insert return values>
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Notes
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-----
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<insert any notes that may be interesting, optional>
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See Also
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--------
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<reference related functions>
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Examples
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--------
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<Some example in doctest format>
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"""
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def inner1d(a, b, **kwargs):
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"""
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Compute the inner product, with broadcasting
@@ -827,7 +804,48 @@ def multiply4_add(a, b, c, d, e, **kwargs):
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def eigh(A, UPLO='L', **kw_args):
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"""
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Computes the eigen values and eigenvectors for the square matrices in the inner dimensions of A, being those matrices symmetric/hermitian
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Computes the eigen values and eigenvectors for the square matrices
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in the inner dimensions of A, being those matrices
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symmetric/hermitian.
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Parameters
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----------
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A : (<NDIMS>, M, M) array
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Hermitian/Symmetric matrices whose eigenvalues and
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eigenvectors are to be computed.
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UPLO : {'L', 'U'}, optional
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Specifies whether the calculation is done with the lower
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triangular part of the elements in `A` ('L', default) or
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the upper triangular part ('U').
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Returns
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-------
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w : (<NDIMS>, M) array
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The eigenvalues, not necessarily ordered.
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v : (<NDIMS>, M, M) array
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The inner dimensions contain matrices with the normalized
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eigenvectors as columns. The column-numbers are coherent with
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the associated eigenvalue.
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Notes
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-----
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Numpy broadcasting rules apply.
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The eigenvalues/eigenvectors are computed using LAPACK routines _ssyevd,
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_heevd
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Implemented for single, double, csingle and cdouble. Numpy conversion
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rules apply.
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See Also
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--------
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eigvalsh : eigenvalues of symmetric/hermitian arrays.
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eig : eigenvalues and right eigenvectors for general matrices.
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eigvals : eigenvalues for general matrices.
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Examples
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--------
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<Some example in doctest format>
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"""
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if 'L' == UPLO:
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gufunc = _impl.eigh_lo
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gufunc = _impl.poinv_up
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return gufunc(A, **kw_args);
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""" doc template (23 lines)"""
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"""
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<Description>
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Parameters
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----------
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<insert parameters + explanations>
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Returns
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-------
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<insert return values>
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Notes
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-----
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<insert any notes that may be interesting, optional>
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See Also
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--------
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<reference related functions>
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Examples
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--------
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<Some example in doctest format>
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"""

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