def vdot(a, b):
"""Returns the dot product of 2 vectors (or anything that can be made into
a vector). NB: this is not the same as `dot`, as it takes the conjugate
of its first argument if complex and always returns a scalar."""
a, b = _na.ravel(a), _na.ravel(b)
try:
return _dotblas.vdot(a, b)
# in case we get an integer Value
except TypeError:
return _numarray.dot(a, b)
def vdot(a, b):
"""Returns the dot product of 2 vectors (or anything that can be made into
a vector). NB: this is not the same as `dot`, as it takes the conjugate
of its first argument if complex and always returns a scalar."""
a, b = _na.ravel(a), _na.ravel(b)
try:
return _dotblas.vdot(a, b)
# in case we get an integer Value
except TypeError:
return _numarray.dot(a, b)
def tensormultiply(array1, array2):
"""tensormultiply returns the product for any rank >=1 arrays, defined as:
r_{xxx, yyy} = \sum_k array1_{xxx, k} array2_{k, yyyy}
where xxx, yyy denote the rest of the a and b dimensions.
"""
array1, array2 = _na.asarray(array1), _na.asarray(array2)
if array1.shape[-1] != array2.shape[0]:
raise ValueError, "Unmatched dimensions"
shape = array1.shape[:-1] + array2.shape[1:]
return _gen.reshape(dot(_gen.reshape(array1, (-1, array1.shape[-1])),
_gen.reshape(array2, (array2.shape[0], -1))), shape)
def tensormultiply(array1, array2):
"""tensormultiply returns the product for any rank >=1 arrays, defined as:
r_{xxx, yyy} = \sum_k array1_{xxx, k} array2_{k, yyyy}
where xxx, yyy denote the rest of the a and b dimensions.
"""
array1, array2 = _na.asarray(array1), _na.asarray(array2)
if array1.shape[-1] != array2.shape[0]:
raise ValueError, "Unmatched dimensions"
shape = array1.shape[:-1] + array2.shape[1:]
return _gen.reshape(
dot(_gen.reshape(array1, (-1, array1.shape[-1])),
_gen.reshape(array2, (array2.shape[0], -1))), shape)
def dot(a, b):
"""returns matrix-multiplication between a and b.
The product-sum is over the last dimension of a and the
second-to-last dimension of b.
NB: No conjugation of complex arguments is performed.
This version uses the BLAS optimized routines where possible.
"""
try:
return _dotblas.dot(a, b)
except TypeError:
try:
return _numarray.dot(a, b)
except TypeError,detail:
if _na.shape(a) == () or _na.shape(b) == ():
return a*b
else:
raise TypeError, detail or "invalid types for dot"
def dot(a, b):
"""returns matrix-multiplication between a and b.
The product-sum is over the last dimension of a and the
second-to-last dimension of b.
NB: No conjugation of complex arguments is performed.
This version uses the BLAS optimized routines where possible.
"""
try:
return _dotblas.dot(a, b)
except TypeError:
try:
return _numarray.dot(a, b)
except TypeError, detail:
if _na.shape(a) == () or _na.shape(b) == ():
return a * b
else:
raise TypeError, detail or "invalid types for dot"