Note: tensorflow/swift and apple/swift-numerics/issues/6 have or will have more complete support for NumPy-like ndarrays and autodiff. Fast AI has a good overview: https://www.fast.ai/2019/01/10/swift-numerics/
An alternate and much mature library is https://github.com/AlexanderTar/LASwift
Apple's Swift is a high level language that's asking for some numerical library to perform computation fast or at the very least easily. This is a bare-bones wrapper for that library.
A way to have iOS run high-level code similar to Python or Matlab is something I've been waiting for, and am incredibly excited to see the results. This will make porting complex signal processing algorithms to C much easier. Porting from Python/MATLAB to C was (and is) a pain in the butt, and this library aims to make the conversion between a Python/Matlab algorithm and a mobile app simple.
In most cases, this library calls Accelerate or OpenCV. If you want to speed up some function or add add another feature in those libraries, feel free to file an issue or submit a pull request (preferred!).
Currently, this library gives you
- operators and various functions (sin, etc) that operate on entire arrays
- helper function (reshape, reverse, delete, repeat, etc)
- easy initializers for 1D and 2D arrays
- complex math (dot product, matrix inversion, eigenvalues, etc)
- machine learning algorithms (SVM, kNN, SVD/PCA, more to come)
- one dimensional Fourier transforms
- speed optimization using Accelerate and OpenCV
When I was crafting this library, I primarily followed the footsteps and example set by NumPy. For the more complex mathematical functions (e.g., SVD) I tested it against NumPy. Matlab, at least for the SVD, returns slightly different output.
Additionally, I followed NumPy's syntax whenever possible. For example, NumPy
and Matlab differ in their initializer called ones by ones((M,N)) and
ones(M, N) respectively. If in doubt or getting weird compiler bugs, look at
NumPy for Matlab users or the section on possible swix bugs that may pop
up during the Install or other Bugs you may find.
Details on how to install can be found in Install. The swix documentation includes details on each individual function and possible bugs.
- Accelerate
- OpenCV
- ...and I used some of SwiftAccelerate to avoid some BLAS/LAPACK agony.
- EERegression -- General purpose multivaritate and quadratic Regression library for Swift 2.1. This can be used to fit a polynomial of different degrees to points you draw with your finger! (and slick gif on readme!)
- Click - The Artificial Intelligence Game
Why does this library exist?
Not only should you be able to do simple math in arrays like in Surge, Swift makes it possible to call high level mathematical functions just like in Python/Matlab.
How does this library compare to Python/Matlab?
Complete speed results can be found in Speed