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removed materns

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This commit is contained in:
James Hensman 2014-02-21 17:06:06 +00:00
parent 365bc42140
commit 78ceef01c3
7 changed files with 246 additions and 430 deletions
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40
GPy/util/diag.py
View file

@ -11,14 +11,14 @@ import numpy as np
def view(A, offset=0):
"""
Get a view on the diagonal elements of a 2D array.
This is actually a view (!) on the diagonal of the array, so you can
This is actually a view (!) on the diagonal of the array, so you can
in-place adjust the view.
:param :class:`ndarray` A: 2 dimensional numpy array
:param int offset: view offset to give back (negative entries allowed)
:rtype: :class:`ndarray` view of diag(A)
>>> import numpy as np
>>> X = np.arange(9).reshape(3,3)
>>> view(X)
@ -36,7 +36,7 @@ def view(A, offset=0):
"""
from numpy.lib.stride_tricks import as_strided
assert A.ndim == 2, "only implemented for 2 dimensions"
assert A.shape[0] == A.shape[1], "attempting to get the view of non-square matrix?!"
assert A.shape[0] == A.shape[1], "attempting to get the view of non-square matrix?!"
if offset > 0:
return as_strided(A[0, offset:], shape=(A.shape[0] - offset, ), strides=((A.shape[0]+1)*A.itemsize, ))
elif offset < 0:
@ -44,6 +44,12 @@ def view(A, offset=0):
else:
return as_strided(A, shape=(A.shape[0], ), strides=((A.shape[0]+1)*A.itemsize, ))
def offdiag_view(A, offset=0):
from numpy.lib.stride_tricks import as_strided
assert A.ndim == 2, "only implemented for 2 dimensions"
Af = as_strided(A, shape=(A.size,), strides=(A.itemsize,))
return as_strided(Af[(1+offset):], shape=(A.shape[0]-1, A.shape[1]), strides=(A.strides[0] + A.itemsize, A.strides[1]))
def _diag_ufunc(A,b,offset,func):
dA = view(A, offset); func(dA,b,dA)
return A
@ -51,11 +57,11 @@ def _diag_ufunc(A,b,offset,func):
def times(A, b, offset=0):
"""
Times the view of A with b in place (!).
Returns modified A
Returns modified A
Broadcasting is allowed, thus b can be scalar.
if offset is not zero, make sure b is of right shape!
:param ndarray A: 2 dimensional array
:param ndarray-like b: either one dimensional or scalar
:param int offset: same as in view.
@ -67,11 +73,11 @@ multiply = times
def divide(A, b, offset=0):
"""
Divide the view of A by b in place (!).
Returns modified A
Returns modified A
Broadcasting is allowed, thus b can be scalar.
if offset is not zero, make sure b is of right shape!
:param ndarray A: 2 dimensional array
:param ndarray-like b: either one dimensional or scalar
:param int offset: same as in view.
@ -84,9 +90,9 @@ def add(A, b, offset=0):
Add b to the view of A in place (!).
Returns modified A.
Broadcasting is allowed, thus b can be scalar.
if offset is not zero, make sure b is of right shape!
:param ndarray A: 2 dimensional array
:param ndarray-like b: either one dimensional or scalar
:param int offset: same as in view.
@ -99,16 +105,16 @@ def subtract(A, b, offset=0):
Subtract b from the view of A in place (!).
Returns modified A.
Broadcasting is allowed, thus b can be scalar.
if offset is not zero, make sure b is of right shape!
:param ndarray A: 2 dimensional array
:param ndarray-like b: either one dimensional or scalar
:param int offset: same as in view.
:rtype: view of A, which is adjusted inplace
"""
return _diag_ufunc(A, b, offset, np.subtract)
if __name__ == '__main__':
import doctest
doctest.testmod()
doctest.testmod()