numpycpp

A c++ header library for matrix operation inspired Numpy, Scipy and MATLAB only using Eigen.

This library has some APIs which Numpy, Scipy, MATLAB has, but Eigen doesn't.

You can use it with only Eigen, and only include it.

Requrements

• Eigen

How to use

Just add a compile option to add the Eigen path, and include numpycpp.h in your code.

APIs

The test code: numpycppTest.cpp helps to understand APIs.

reshape

Gives a new shape to an array without changing its data.

This function is based on numpy.reshape

see: https://docs.scipy.org/doc/numpy/reference/generated/numpy.reshape.html

Eigen::MatrixXf x(6,1);
x<<1.0,2.0,3.0,4.0,5.0,6.0;
PRINT(x);

Eigen::MatrixXf rx = reshape(x,2,3);
PRINT(rx);
//rx:
//1 3 5
//2 4 6

Eigen::MatrixXf rx2 = reshape(x,3,2);
PRINT(rx2);
//rx2:
//1 4
//2 5
//3 6

isdiag

Detemine if matrix is diagonal

If matrix is not square, return false

It is inspired by MATLAB isdiag function.

see: https://www.mathworks.com/help/matlab/ref/isdiag.html

Eigen::MatrixXf x(3,1);
x<<5.0,6.0,7.0;
bool flag = isdiag(x);//return false

Eigen::MatrixXf x2(2,2);
x2<<5.0,6.0,7.0,1.0;
bool flag2 = isdiag(x2);//return false

Eigen::MatrixXf x3(3,3);
x3<<1.0,0.0,0.0,
    0.0,1.0,0.0,
    0.0,0.0,1.0;
bool flag3 = isdiag(x3);//return true

vstack

Stack matrix in sequence vertically

imspired by numpy.vstack

see :https://docs.scipy.org/doc/numpy/reference/generated/numpy.vstack.html

Eigen::MatrixXf x(3,1);
x<<5.0,
   6.0,
   7.0;

Eigen::MatrixXf y(3,1);
y<<1.0,
   10.0,
   100.0;

Eigen::MatrixXf a = vstack(x,y);
//ans<<5,
//     6,
//     7,
//     1,
//     10,
//     100;

hstack

Stack matrix in sequence horizontally

imspired by numpy.hstack

see: https://docs.scipy.org/doc/numpy/reference/generated/numpy.hstack.html

Eigen::MatrixXf x(3,1);
x<<5.0,
   6.0,
   7.0;

Eigen::MatrixXf y(3,1);
y<<1.0,
   10.0,
   100.0;

Eigen::MatrixXf a = hstack(x,y);
//a=
//5   1
//6  10
//7 100

kron

Compute the Kronecker product

A composite array made of blocks of the second array scaled by the first.

Inspired numpy.kron.

see: https://docs.scipy.org/doc/numpy/reference/generated/numpy.kron.html

Eigen::MatrixXf x(1,3);
x<<1.0,10.0,100.0;

Eigen::MatrixXf y(1,3);
y<<5.0,6.0,7.0;

Eigen::MatrixXf a = kron(x,y);
// a = [5 50 500  6 60 600  7  70 700]

block_diag

Create a block diagonal matrix from provided matrices

inspired scipy.linalg.block_diag

see: https://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.linalg.block_diag.html

Eigen::MatrixXf x(3,1);
x<<5.0,
   6.0,
   7.0;

Eigen::MatrixXf y(1,3);
y<<1.0,10.0,100.0;

Eigen::MatrixXf a = block_diag(x,y);
//a=  5,  0,  0,  0,
//    6,  0,  0,  0,
//    7,  0,  0,  0,
//    0,  1, 10,100;

License

MIT

Author

Atsushi Sakai (@Atsushi_twi)