mathflow alternatives and similar packages
Based on the "Math" category.
Alternatively, view mathflow alternatives based on common mentions on social networks and blogs.

vector
An efficient implementation of Intindexed arrays (both mutable and immutable), with a powerful loop optimisation framework . 
statistics
A fast, high quality library for computing with statistics in Haskell. 
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GHC plugin that improves Haskell code's numerical stability 
dimensional
Dimensional library variant built on Data Kinds, Closed Type Families, TypeNats (GHC 7.8+). 
computationalalgebra
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mwcrandom
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numhask
A haskell numeric prelude, providing a clean structure for numbers and operations that combine them. 
cf
"Exact" real arithmetic for Haskell using continued fractions (Not formally proven correct) 
optimization
Some numerical optimization methods implemented in Haskell 
poly
Fast polynomial arithmetic in Haskell (dense and sparse, univariate and multivariate, usual and Laurent) 
safedecimal
Safe and very efficient arithmetic operations on fixed decimal point numbers 
equationalreasoning
Agdastyle equational reasoning in Haskell 
sbvPlugin
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eigen
Haskel binding for Eigen library. Eigen is a C++ template library for linear algebra: matrices, vectors, numerical solvers, and related algorithms. 
polynomial
Haskell library for manipulating and evaluating polynomials 
monoidsubclasses
Subclasses of Monoid with a solid theoretical foundation and practical purposes 
diagramssolve
Miscellaneous solver code for diagrams (lowdegree polynomials, tridiagonal matrices)
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README
mathflow(Dependently typed tensorflow modeler)
This package provides a model of tensoroperations. The model is independent from tensorflowbinding of python and haskell, though this package generates pythoncode. tensor's dimensions and constraints are described by dependent types. The tensoroperations are based on tensorflowapi. Currently the model can be translated into pythoncode. To write this package, I refer to this neural network document and singletons.
Install
Install tensorflow of python and this package.
> sudo apt install python3 python3pip
> pip3 install U pip
> pip3 install tensorflow
> git clone [email protected]:junjihashimoto/mathflow.git
> cd mathflow
> stack install
Usage
About model
Model has a type of Tensor (dimensions:[Nat]) valuetype outputtype
.
dimensions
are tensordimensions.valuetype
is a value type like Integer or Float of tensorflowdatatypes.outputtype
is a type of code which this package generates. PyStringtype is used for generating pythoncode.
This package makes tensorflowgraph from the mode. The model's endpoint is always a tensortype.
At first write graph by using arithmetic operators like (+,,,/), % (which is matrix multiply) and tensorflowfunctions. Mathflow.{TF,TF.NN,TF.Train} packages define Tensorflowfunctions.
A example is below.
testMatMul :: Tensor '[2,1] Int PyString
testMatMul =
let n1 = (Tensor "tf.constant([[2],[3]])") :: Tensor '[2,1] Int PyString
n2 = (Tensor "tf.constant([[2,0],[0,1]])") :: Tensor '[2,2] Int PyString
y = (n2 %* n1) :: Tensor '[2,1] Int PyString
in y
Create model and run it
Write tensorflowmodel.
testMatMul :: Tensor '[2,1] Int PyString
testMatMul =
let n1 = (Tensor "tf.constant([[2],[3]])") :: Tensor '[2,1] Int PyString
n2 = (Tensor "tf.constant([[2,0],[0,1]])") :: Tensor '[2,2] Int PyString
y = n2 %* n1 :: Tensor '[2,1] Int PyString
in y
Run the model. This run
function generates pythoncode and excecute the code by python.
main = do
(retcode,stdout,stderr) < run testMatMul
print stdout