NMatrix¶ ↑

Fast Numerical Linear Algebra Library for Ruby

• sciruby.com

• Google+

• Installation guide

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.

NMatrix was inspired by and based heavily upon NArray, by Masahiro Tanaka.

Installation¶ ↑

To install the latest stable version:

gem install nmatrix

However, you will need to install ATLAS with CBLAS (C interface to BLAS) first. Those directions can be found here. The requirements for NMatrix are:

• ATLAS

• LAPACK, probably

• a version of GCC or clang which supports C++0x or C++11

• Ruby 1.9 or 2.x

• packable 1.3.5 (used for I/O)

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

git clone https://github.com/SciRuby/nmatrix.git
cd nmatrix/
rake compile
rake repackage
gem install pkg/nmatrix-0.0.4.gem

If you get errors about clapack.h or cblas.h, determine where your ATLAS headers are using:

locate clapack.h

If you’re a Mac user, we recommend you search for cblas.h instead.

Then, tell your system:

export C_INCLUDE_PATH=/usr/local/atlas/include
export CPLUS_INCLUDE_PATH=/usr/local/atlas/include

Finally, try compiling again.

Documentation¶ ↑

Carlos Agarie (@agarie) is currently working to improve the documentation. The best way to get help is by posting issues or sending e-mails to our mailing list. You may also email @agarie, or look for ‘agarie` on #sciruby at chat.freenode.net if you want to ask questions or offer suggestions.

You can find the complete API documentation on our website.

EXAMPLES¶ ↑

Create a new NMatrix from a ruby array:

>> NMatrix.new([2, 3], [0, 1, 2, 3, 4, 5], :int64).pp
  [0, 1, 2]
  [3, 4, 5]
=> nil

Create a new NMatrix using the N shortcut:

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

If you want to learn more about how to create a matrix, read the guide in our wiki.

Again, you can find the complete API documentation on our website.

Developers¶ ↑

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

Features¶ ↑

The following features exist in the current version of NMatrix (0.0.3):

• Matrix storage containers: dense, yale, list (more to come)

• Data types: uint8, int8, int16, int32, int64, float32, float64, complex64, complex128, rational64, rational128 (incomplete)

• Conversion between storage and data types (except from-complex, and from-float-to-rational)

• Element-wise operations and comparisons for dense and yale

• Matrix-matrix multiplication for dense (using ATLAS) and yale

• Matrix-vector multiplication for dense (using ATLAS)

• Dense and list matrix slicing and referencing

• Native reading and writing of dense and yale matrices

  • Optional compression for dense matrices with symmetry or triangularity: symmetric, skew, hermitian, upper, lower

• Matlab .MAT v5 file input

• C and C++ API

• BLAS internal implementations (no library) and ATLAS (with library) access:

  • Level 1: xROT, xROTG (BLAS dtypes only)

  • Level 2: xGEMV

  • Level 3: xGEMM, xTRSM

• LAPACK ATLAS access:

  • xGETRF, xGETRI, xGETRS, xGESV (Gaussian elimination)

  • xPOTRF, xPOTRI, xPOTRS, xPOSV (Cholesky factorization)

  • xLASWP, xSCAL, xLAUUM

• LAPACK-less internal implementations (no LAPACK needed and working on non-BLAS dtypes):

  • xGETRF

  • xLASWP, xSCAL

  • xLAUUM (no LAPACK needed, but BLAS dtypes only)

• LU decomposition

• Matrix inversions (requires LAPACK; BLAS dtypes only)

• Determinant calculation for BLAS dtypes

Planned Features (Short-to-Medium Term)¶ ↑

These are features planned for NMatrix 0.1.0, our first beta.

• calculation of determinant (LAPACK-free), trace, and eigenvalues (characteristic polynomial) (0.1.0)

• exponentials and square roots

• matrix inversions (LAPACK-free)

• matrix decomposition/factorization

• calculation of norms

• tensor products

• principal component analysis (PCA)

• improved file I/O

  • compression of yale symmetries in I/O

• operation scheduling

• parallelization of some types of operations

• optimization of non-BLAS data types on BLAS-like operations (e.g., matrix multiplication for rational numbers)

• Ruby/GSL interoperability

Warning¶ ↑

Please be aware that SciRuby and NMatrix are alpha status. If you’re thinking of using SciRuby/NMatrix to write mission-critical code, such as for driving a car or flying a space shuttle, you may wish to choose other software for now.

You should also be aware that NMatrix and NArray are incompatible with one another; you should not try to require both at the same time. Unfortunately, that causes problems with Ruby/GSL, which currently depends upon NArray. As such, we are working on a patch for Ruby/GSL. You can find the most recent version in the work branch of Masaomi’s fork (not currently compiling as of this writing).

License¶ ↑

Copyright © 2012–13, The Ruby Science Foundation.

All rights reserved.

NMatrix, along with SciRuby, is licensed under the BSD 2-clause license. See LICENSE.txt for details.

Donations¶ ↑

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