def test_asmatrix(self):
a = [[1, 2, 3]]
b = np.array(a)
assert isinstance(sputils.asmatrix(a), np.matrix)
assert isinstance(sputils.asmatrix(b), np.matrix)
c = sputils.asmatrix(b)
c[:, :] = 123
assert_equal(b, [[123, 123, 123]])
def rmatvec(self, x):
"""Adjoint matrix-vector multiplication.
Performs the operation y = A^H * x where A is an MxN linear
operator and x is a column vector or 1-d array.
Parameters
----------
x : {matrix, ndarray}
An array with shape (M,) or (M,1).
Returns
-------
y : {matrix, ndarray}
A matrix or ndarray with shape (N,) or (N,1) depending
on the type and shape of the x argument.
Notes
-----
This rmatvec wraps the user-specified rmatvec routine or overridden
_rmatvec method to ensure that y has the correct shape and type.
"""
x = np.asanyarray(x)
M, N = self.shape
if x.shape != (M, ) and x.shape != (M, 1):
raise ValueError('dimension mismatch')
y = self._rmatvec(x)
if isinstance(x, np.matrix):
y = asmatrix(y)
else:
y = np.asarray(y)
if x.ndim == 1:
y = y.reshape(N)
elif x.ndim == 2:
y = y.reshape(N, 1)
else:
raise ValueError(
'invalid shape returned by user-defined rmatvec()')
return y
def matmat(self, X):
"""Matrix-matrix multiplication.
Performs the operation y=A*X where A is an MxN linear
operator and X dense N*K matrix or ndarray.
Parameters
----------
X : {matrix, ndarray}
An array with shape (N,K).
Returns
-------
Y : {matrix, ndarray}
A matrix or ndarray with shape (M,K) depending on
the type of the X argument.
Notes
-----
This matmat wraps any user-specified matmat routine or overridden
_matmat method to ensure that y has the correct type.
"""
X = np.asanyarray(X)
if X.ndim != 2:
raise ValueError('expected 2-d ndarray or matrix, not %d-d' %
X.ndim)
if X.shape[0] != self.shape[1]:
raise ValueError('dimension mismatch: %r, %r' %
(self.shape, X.shape))
Y = self._matmat(X)
if isinstance(Y, np.matrix):
Y = asmatrix(Y)
return Y
def rmatmat(self, X):
"""Adjoint matrix-matrix multiplication.
Performs the operation y = A^H * x where A is an MxN linear
operator and x is a column vector or 1-d array, or 2-d array.
The default implementation defers to the adjoint.
Parameters
----------
X : {matrix, ndarray}
A matrix or 2D array.
Returns
-------
Y : {matrix, ndarray}
A matrix or 2D array depending on the type of the input.
Notes
-----
This rmatmat wraps the user-specified rmatmat routine.
"""
X = np.asanyarray(X)
if X.ndim != 2:
raise ValueError('expected 2-d ndarray or matrix, not %d-d' %
X.ndim)
if X.shape[0] != self.shape[0]:
raise ValueError('dimension mismatch: %r, %r' %
(self.shape, X.shape))
Y = self._rmatmat(X)
if isinstance(Y, np.matrix):
Y = asmatrix(Y)
return Y
def postprocess(x):
if isinstance(b, matrix):
x = asmatrix(x)
return x.reshape(b.shape)