pymatrix is a Python library that offers easily usable matrix arithmetics.
Just do an import matrix to use it.
Note: Matrix instances are immutable and all operations will return a new instance
To create a 2x3 matrix you can use one of the following (not the only options):
matrix.Matrix([1, 2, 3], [4, 5, 6])
matrix.Matrix([[1, 2, 3], [4, 5, 6]])
matrix.Matrix(1, 2, 3, 4, 5, 6).reshape(2, 3)
The Vector function is a shorthand for creating Nx1 matrices:
matrix.Vector(1, 2, 3) is equal to matrix.Matrix([1], [2], [3])
Identities and matrices filled with ones or zeros can easily be created using:
matrix.identity(size=3)
matrix.ones(height=3, width=4)
matrix.zeros(height=3, width=4)
Matrix addition and multiplication work like expected:
matrix1 * matrix2 - matrix3 + 2 * matrix4
The cross-product between two vectors (3x1 matrices) can be computed as:
vector1 ^ vector2
The T property returns the transposed matrix:
matrix1.T
The norm function returns the computed norm:
matrix1.norm() and matrix.norm(2) return the Eucledian norm (only implemented for vectors)
matrix1.norm(1) returns the Manhattan norm
matrix1.norm('inf') returns the Uniform norm
matrix1.norm('fro') returns the Frobenius norm
The det property returns the determinant of the matrix:
matrix1.det
The adj property returns the adjugate matrix:
matrix1.adj
The inv property returns the inverse matrix:
matrix1.inv
The trace property returns the trace of a square matrix:
matrix1.trace
The diag property returns the diagonal of a matrix as a vector:
matrix1.diag
You can also stack matrices horizontally or vertically using the stackh and stackv functions:
matrix.stackh(matrix1, matrix2, ...)
matrix.stackv(matrix1, matrix2, ...)
The cut function cuts out a rectangular piece of a matrix:
matrix1.cut(left=1, right=3, top=2, bottom=4) (including left and top, excluding right and bottom)
The dimensions of a matrix can be changed by calling the reshape function:
matrix1.reshape(height=3, width=2)