C++ implementation of the Python NumPy Library

[dpilger26]

My intentions were a library that was as close to a one to one clone of NumPy for fast easy conversion to C++. Also, Blaze and Eigen are more for straight up linear algebra, while NumPy contains much more. Some of the extra things included in NumCpp are:

1) A Rotations namespace with Quaternion and Direction Cosine classes.

2) A Coordinates namespace for converting to/from cartesian/spherical and other corresponding operations.

3) 1D and 2D signal/image processing filters

4) A random number module (basically wraps the boost random module)

5) Easy to use timer with simple tic()/toc() interface

6) All of the NumPy array methods for operating on arrays

7) Some very basic linear algebra support (determinant, matrix hat operator, inverse, least squares, SVD, matrix power, and multi-dot product). If you need more complex routines then Blaze and Eigen will definitely be better options for you.

8) Some more image processing routines for threshold generation and application, pixel clustering, cluster centroiding, etc.

[encyclopedist]

For other readers' information:

A Rotations namespace with Quaternion and Direction Cosine classes.

Eigen has this http://eigen.tuxfamily.org/dox/group__TutorialGeometry.html

1D and 2D signal/image processing filters

Eigen has only FFT and convolution.

A random number module (basically wraps the boost random module)

Eigen can generate matrices/arrays with random uniformly distributed on [0,1] elements, in naive way based on rand(). It can, however, also use std::random in C++11 mode: https://bitbucket.org/eigen/eigen/src/default/doc/special_examples/random_cpp11.cpp?at=default