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= NMatrix

{}[https://gitter.im/SciRuby/nmatrix?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge]

Fast Numerical Linear Algebra Library for Ruby

• {sciruby.com}[http://sciruby.com]
• {Google+}[https://plus.google.com/109304769076178160953/posts]
• {Google Group - Mailing List}[https://groups.google.com/forum/#!forum/sciruby-dev]
• {NMatrix Installation wiki}[https://github.com/SciRuby/nmatrix/wiki/Installation]
• {SciRuby Installation guide}[http://sciruby.com/docs#installation]

{}[https://travis-ci.org/SciRuby/nmatrix]

{}[https://codeclimate.com/github/SciRuby/nmatrix]

== Description

NMatrix is a fast numerical linear algebra library for Ruby, with dense and sparse matrices, written mostly in C and C++. It is part of the SciRuby project.

Three gems are provided in this repository. The +nmatrix+ gem provides all core matrix functionality, and requires minimal external dependencies, making it easy to install. The +nmatrix-atlas+ and +nmatrix-lapacke+ gems are optional extensions of the main +nmatrix+ gem that rely on external linear algebra libraries to provide advanced features for dense matrices (singular value decomposition, eigenvalue/eigenvector finding, Cholesky factorization), as well as providing faster implementations of common operations like multiplication, inverses, and determinants. +nmatrix-atlas+ requires the {ATLAS library}[http://math-atlas.sourceforge.net/], while +nmatrix-lapacke+ is designed to work with various LAPACK implementations (including ATLAS). The +nmatrix-atlas+ and +nmatrix-lapacke+ gems both provide similar interfaces for using these advanced features.

NMatrix was inspired by {NArray}[http://narray.rubyforge.org], by Masahiro Tanaka.

== Installation

To install the latest stable version:

gem install nmatrix

The requirements for NMatrix are:

• GCC 4.3 or later (clang support is experimental)
• Ruby 1.9.3 or later

To install +nmatrix-atlas+ or +nmatrix-lapacke+, an additional requirement is a compatible LAPACK library. Detailed directions for this step can be found {here}[https://github.com/SciRuby/nmatrix/wiki/Installation].

If you want to obtain the latest (development) code, you should generally do:

git clone https://github.com/SciRuby/nmatrix.git
cd nmatrix/
gem install bundler
bundle install
bundle exec rake compile
bundle exec rake spec

If you want to try out the code without installing:

bundle exec rake pry

To install:

bundle exec rake install

=== JRuby

First, you need to download Apache Commons Math 3.6.1 (the JAR, which you can find in the binary package). For example, in the NMatrix directory, do:

wget https://www.apache.org/dist/commons/math/binaries/commons-math3-3.6.1-bin.tar.gz
tar zxvf commons-math3-3.6.1-bin.tar.gz
mkdir ext/nmatrix_java/vendor/
cp commons-math3-3.6.1/commons-math3-3.6.1.jar ext/nmatrix_java/vendor/

Next, create build directories:

mkdir -p ext/nmatrix_java/build/class
mkdir ext/nmatrix_java/target

Finally, compile and package as jar.

rake jruby

=== Plugins

The commands above build and install only the core +nmatrix+ gem. If you want to build one or more of the plugin gems (+nmatrix-atlas+, +nmatrix-lapacke+) in addition to the core nmatrix gem, use the nmatrix_plugins= option, e.g. rake compile nmatrix_plugins=all, rake install nmatrix_plugins=atlas, rake clean nmatrix_plugins=atlas,lapacke. Each of these commands apply to the +nmatrix+ gem and any additional plugin gems specified. For example, rake spec nmatrix_plugins=atlas will test both the core +nmatrix+ gem and the +nmatrix-atlas+ gem.

== Upgrading from NMatrix 0.1.0

If your code requires features provided by ATLAS (Cholesky decomposition, singular value decomposition, eigenvalues/eigenvectors, inverses of matrices bigger than 3-by-3), your code now depends on the +nmatrix-atlas+ gem. You will need to add this a dependency of your project and require 'nmatrix/atlas' in addition to require 'nmatrix'. In most cases, no further changes should be necessary, however there have been a few {API changes}[https://github.com/SciRuby/nmatrix/wiki/API-Changes], please check to see if these affect you.

== Documentation

If you have a suggestion or want to add documentation for any class or method in NMatrix, please open an issue or send a pull request with the changes.

You can find the complete API documentation {on our website}[http://sciruby.com/nmatrix/docs/].

== Examples

Create a new NMatrix from a ruby Array:

>> require 'nmatrix'
>> NMatrix.new([2, 3], [0, 1, 2, 3, 4, 5], dtype: :int64)
=> [
    [0, 1, 2],
    [3, 4, 5]
   ]

Create a new NMatrix using the +N+ shortcut:

>> m = N[ [2, 3, 4], [7, 8, 9] ]
=> [
    [2, 3, 4],
    [7, 8, 9]
   ]
>> m.inspect
=> #<NMatrix:0x007f8e121b6cf8shape:[2,3] dtype:int32 stype:dense>

The above output requires that you have a pretty-print-enabled console such as Pry; otherwise, you'll see the output given by +inspect+.

If you want to learn more about how to create a matrix, {read the guide in our wiki}[https://github.com/SciRuby/nmatrix/wiki/How-to-create-an-NMatrix].

Again, you can find the complete API documentation {on our website}[http://sciruby.com/nmatrix/docs/].

=== Using advanced features provided by plugins

Certain features (see the documentation) require either the nmatrix-atlas or the nmatrix-lapacke gem to be installed. These can be accessed by using require 'nmatrix/atlas' or require 'nmatrix/lapacke'. If you don't care which of the two gems is installed, use require 'nmatrix/lapack_plugin', which will require whichever one of the two is available.

Fast fourier transforms can be conducted with the nmatrix-fftw extension, which is an interface to the FFTW C library. Use require 'nmatrix/fftw' for using this plugin.

== Plugin Details

=== FFTW

This is plugin for interfacing with the {FFTW library}[http://www.fftw.org]. It has been tested with FFTW 3.3.4.

It works reliably only with 64 bit numbers (or the NMatrix :float64 or :complex128 data type). See the docs for more details.

== NArray Compatibility

When NArray[http://masa16.github.io/narray/] is installed alongside NMatrix, require 'nmatrix' will inadvertently load NArray's +lib/nmatrix.rb+ file, usually accompanied by the following error:

uninitialized constant NArray (NameError)

To make sure NMatrix is loaded properly in the presence of NArray, use require 'nmatrix/nmatrix' instead of require 'nmatrix' in your code.

== Developers

Read the instructions in +CONTRIBUTING.md+ if you want to help NMatrix.

== Features

The following features exist in the current version of NMatrix (0.1.0.rc1):

• Matrix and vector storage containers: dense, yale, list (more to come)
• Data types: byte (uint8), int8, int16, int32, int64, float32, float64, complex64, complex128, Ruby object
• Interconversion between storage and data types
• Element-wise and right-hand-scalar operations and comparisons for all matrix types
• Matrix-matrix multiplication for dense (with and without ATLAS) and yale
• Matrix-vector multiplication for dense (with and without ATLAS)
• Lots of enumerators (each, each_with_indices, each_row, each_column, each_rank, map, etc.)
• Matrix slicing by copy and reference (for dense, yale, and list)
• Native reading and writing of dense and yale matrices
  • Optional compression for dense matrices with symmetry or triangularity: symmetric, skew, hermitian, upper, lower
• Input/output:
  • Matlab .MAT v5 file input
  • MatrixMarket file input/output
  • Harwell-Boeing and Fortran file input
  • Point Cloud Library PCD file input
• C and C++ API
• BLAS internal implementations (no library) and external (with nmatrix-lapack or nmatrix-atlas) access:
  • Level 1: xROT, xROTG (BLAS dtypes only), xASUM, xNRM2, IxAMAX, xSCAL
  • Level 2: xGEMV
  • Level 3: xGEMM, xTRSM
• LAPACK access (with nmatrix-lapack or nmatrix-atlas plugin):
  • xGETRF, xGETRI, xGETRS, xGESV (Gaussian elimination)
  • xPOTRF, xPOTRI, xPOTRS, xPOSV (Cholesky factorization)
  • xGESVD, xGESDD (singular value decomposition)
  • xGEEV (eigenvalue decomposition of asymmetric square matrices)
• LAPACK-less internal implementations (no plugin or LAPACK needed and working on non-BLAS dtypes):
  • xGETRF, xGETRS
• LU decomposition
• Matrix inversions
• Determinant calculation for BLAS dtypes
• Traces
• Ruby/GSL interoperability (requires {SciRuby's fork of rb-gsl}[http://github.com/SciRuby/rb-gsl])
• slice assignments, e.g., x[1..3,0..4] = some_other_matrix

=== Planned Features (Short-to-Medium Term)

See the issues tracker for a list of planned features or to request new ones.

== License

Copyright (c) 2012--16, John Woods and the Ruby Science Foundation.

All rights reserved.

NMatrix, along with SciRuby, is licensed under the BSD 2-clause license. See {LICENSE.txt}[https://github.com/SciRuby/sciruby/wiki/License] for details.

== Donations

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