def hadamard(A, B):
"""Calculate the Hadamard product of two matrices."""
if not all(isinstance(M, IntegerMatrix) for M in (A, B)):
raise TypeError("can only Hadamard two matrices")
if type(A) is not type(B):
raise TypeError("matrices must be the same type")
if A.m != B.m or A.n != B.n:
raise exc.ComformabilityError(
"matrices must have the same dimensions")
data = [[A[i, j] * B[i, j] for j in range(A.n)] for i in range(A.m)]
return A.__class__(A.m, B.m, data)
def __mul__(self, obj):
"""Multiply this matrix by a valid object and return the result.
Doesn't modify the current matrix. Valid objects include other matrices
vectors, and numeric scalars. In the case where the other object is a
matrix, multiplication occurs with the current matrix on the left-hand
side.
"""
if isinstance(obj, Matrix):
if self.n != obj.m:
raise exc.ComformabilityError(
"inner matrix dimensions must match")
if type(self) is not type(obj):
raise TypeError("matrices must be the same type")
data = [[
sum([self[i, k] * obj[k, j] for k in range(self.n)])
for j in range(obj.n)
] for i in range(self.m)]
return self.__class__(self.m, obj.n, data)
elif isinstance(obj, vec.Vector):
raise NotImplementedError("vector type system not implemented")
if self.n != obj.m:
raise exc.ComformabilityError(
"number of matrix columns much match vector length")
data = [
sum([self[i, k] * obj[k] for k in range(self.n)])
for i in range(self.m)
]
return vec.Vector(self.m, data)
elif Matrix.is_numeric(obj):
self._validate_scalar(obj)
data = [[self[i, j] * obj for j in range(self.n)]
for i in range(self.m)]
return self.__class__(self.m, self.n, data)
else:
raise TypeError("cannot add object of type " + type(obj).__name__ +
" to matrix")
def elem_equal(self, obj):
"""Element-wise equality."""
if type(obj) == self.__class__:
if self.m != obj.m or self.n != obj.n:
raise exc.ComformabilityError(
"matrices must have the same dimensions")
if type(self) is not type(obj):
raise TypeError("matrices must be the same type")
data = [[self[i, j] == obj[i, j] for j in range(self.n)]
for i in range(self.m)]
elif type(obj) == self._type:
data = [[self[i, j] == obj for j in range(self.n)]
for i in range(self.m)]
else:
raise TypeError("cannot add object of type " + type(obj).__name__ +
" to matrix")
return BooleanMatrix(self.m, self.n, data)
def __neq__(self, obj):
"""Elementwise equality."""
if isinstance(obj, Matrix):
if self.m != obj.m or self.n != obj.n:
raise exc.ComformabilityError(
"matrices must have the same dimensions")
if type(self) is not type(obj):
raise TypeError("matrices must be the same type")
data = [[self[i, j] != obj[i, j] for j in range(self.n)]
for i in range(self.m)]
elif Matrix.is_numeric(obj):
self._validate_scalar(obj)
data = [[self[i, j] != obj for j in range(self.n)]
for i in range(self.m)]
else:
raise TypeError("cannot add object of type " + type(obj).__name__ +
" to matrix")
return BooleanMatrix(self.m, self.n, data)
def _boolean_operation(self, obj, op):
"""Perform a generic Boolean operation."""
if isinstance(obj, Matrix):
if self.m != obj.m or self.n != obj.n:
raise exc.ComformabilityError(
"matrices must have the same dimensions")
if not isinstance(obj, BooleanMatrix):
raise TypeError("operation only exists for Boolean matrices")
data = [[op(self[i, j], obj[i, j]) for j in range(self.n)]
for i in range(self.m)]
elif isinstance(obj, bool):
data = [[op(self[i, j], obj) for j in range(self.n)]
for i in range(self.m)]
else:
raise TypeError(
"operation can't be performed with object of type " +
type(obj).__name__)
return self.__class__(self.m, self.n, data)
def __sub__(self, obj):
"""Subtract a valid object from this matrix and return the result.
Doesn't modify the current matrix. Valid objects include other matrices
and numeric scalars
"""
if isinstance(obj, Matrix):
if self.m != obj.m or self.n != obj.n:
raise exc.ComformabilityError(
"matrices must have the same dimensions")
if type(self) is not type(obj):
raise TypeError("matrices must be the same type")
data = [[self[i, j] - obj[i, j] for j in range(self.n)]
for i in range(self.m)]
elif Matrix.is_numeric(obj):
self._validate_scalar(obj)
data = [[self[i, j] - obj for j in range(self.n)]
for i in range(self.m)]
else:
raise TypeError("cannot subtract object of type " +
type(obj).__name__ + " to matrix")
return self.__class__(self.m, self.n, data)
