def __mul__(self, other):
"""Multiply this matrix with another matrix"""
if isinstance(other, (int, float)):
return Matrix(
*[Vector(*i) for i in np.multiply(self._columns, other).T])
elif isinstance(other, (Vector)):
return Vector(*np.dot(self._columns, other))
elif type(self) == type(other):
return Matrix(
*[Vector(*i) for i in self._columns.dot(other.to_array()).T])
def inverse(self):
"""Returns a new matrix that is the inverse of the given matrix"""
# Take the inverse of the matrix and then turn it back into a Matrix
try:
return Matrix(
*[Vector(*i) for i in np.linalg.inv(self._columns).T])
except np.linalg.linalg.LinAlgError as e:
raise ValueError("Matrix is not invertible") from e
def __pow__(self, p):
"""Returns a matrix to the power p"""
return Matrix(
*[Vector(*i) for i in np.linalg.matrix_power(self._columns, p).T])
def transpose(self):
"""Returns the transpose of the matrix"""
return Matrix(*[Vector(*i) for i in self._columns])
def __sub__(self, other):
"""Subtract this matrix with another matrix"""
return Matrix(
*[Vector(*i) for i in (self._columns - other.to_array()).T])
def __add__(self, other):
"""Add this matrix with another matrix"""
return Matrix(
*[Vector(*i) for i in (self._columns + other.to_array()).T])
def __iter__(self):
"""Iterate over the vectors of the matrix"""
for i in self._columns.T:
yield Vector(*i)
def __getitem__(self, val):
"""Access individual vector of matrix"""
return Vector(*self._columns[:, val])
def __sub__(self, p):
"""Subtract two points to obtain a Vector"""
if len(self) != len(p):
raise ValueError('Dimension mismatch')
return Vector(*[x - y for x, y in zip(self, p)])