swix alternatives and similar libraries
Based on the "Math" category.
Alternatively, view swix alternatives based on common mentions on social networks and blogs.
DDMathParser7.1 0.0 L2 swix VS DDMathParserString → Number
BigInt6.5 2.6 L4 swix VS BigIntArbitrary-precision arithmetic in pure Swift
SigmaSwiftStatistics6.2 0.0 L5 swix VS SigmaSwiftStatisticsA collection of functions for statistical calculation written in Swift.
Easy-Cal-Swift4.3 0.0 L5 swix VS Easy-Cal-SwiftOverload +-*/ operator for Swift, make it easier to use (and not so strict)
Upsurge3.9 0.0 L5 swix VS UpsurgeMulti-dimensional Swift math
Matft2.3 0.0 swix VS MatftNumpy-like library in swift. (Multi-dimensional Array, ndarray, matrix and vector library)
Arithmosophi2.0 0.0 L5 swix VS ArithmosophiA set of protocols for Arithmetic, Statistics and Logical operations
PlotKit1.7 0.0 L4 swix VS PlotKitOS X plotting framework
Appwrite - The Open Source Firebase alternative introduces iOS support
* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest.
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Swift Matrix and Machine Learning Library
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(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.
Third Party Frameworks/Libraries
- ...and I used some of SwiftAccelerate to avoid some BLAS/LAPACK agony.
To be integrated
- 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