mathflow alternatives and similar packages
Based on the "Math" category.
Alternatively, view mathflow alternatives based on common mentions on social networks and blogs.
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vector
An efficient implementation of Int-indexed arrays (both mutable and immutable), with a powerful loop optimisation framework . -
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hgeometry
HGeometry is a library for computing with geometric objects in Haskell. It defines basic geometric types and primitives, and it implements some geometric data structures and algorithms. The main two focusses are: (1) Strong type safety, and (2) implementations of geometric algorithms and data structures that have good asymptotic running time guarantees. -
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dimensional
Dimensional library variant built on Data Kinds, Closed Type Families, TypeNats (GHC 7.8+). -
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numhask
A haskell numeric prelude, providing a clean structure for numbers and operations that combine them. -
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poly
Fast polynomial arithmetic in Haskell (dense and sparse, univariate and multivariate, usual and Laurent) -
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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.
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README
mathflow(Dependently typed tensorflow modeler)
This package provides a model of tensor-operations. The model is independent from tensorflow-binding of python and haskell, though this package generates python-code. tensor's dimensions and constraints are described by dependent types. The tensor-operations are based on tensorflow-api. Currently the model can be translated into python-code. 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 python3-pip
> 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]) value-type output-type.
dimensionsare tensor-dimensions.value-typeis a value type like Integer or Float of tensorflow-data-types.output-typeis a type of code which this package generates. PyString-type is used for generating python-code.
This package makes tensorflow-graph from the mode. The model's endpoint is always a tensor-type.
At first write graph by using arithmetic operators like (+,-,,/), % (which is matrix multiply) and tensorflow-functions. Mathflow.{TF,TF.NN,TF.Train} packages define Tensorflow-functions.
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 tensorflow-model.
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 python-code and excecute the code by python.
main = do
(retcode,stdout,stderr) <- run testMatMul
print stdout