Project
Reverse Dependencies for narray
The projects listed here declare narray as a runtime or development dependency
0.0
Includes solvers for continuous and discrete multivariate optimisation problems.
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RubyGSL is a Ruby interface to the GNU Scientific Library, for numerical computing with Ruby
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Toolkit for working with DICOM image sequences
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'egor' is a program for calculating environment-specific substitution tables from user providing environmental class definitions and sequence alignments with the annotations of the environment classes.
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Gem version of T. Horinouchi's ruby-fftw3.
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a multi-purpose class to handle Gridded Physical quantities.
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Fast Fourier Transforms by using FFTW Ver.3
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RubyNetCDF is the Ruby interface to the NetCDF library built on the NArray library, which is an efficient multi-dimensional numeric array class for Ruby.
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Comprehensive library for self-descriptive gridded physical data (in NetCDF, GrADS, or on memory) with graphics. This version works with Ruby 2.0.
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This Ruby extension implements conversions from Hornetseye::MultiArray to NArray and vice versa.
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Activity
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This rubygem does not have a description or summary.
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Provides KATCP client library for Ruby. KATCP is the Karoo Array Telescope
Control Protocol.
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LicenseMatcher is rubygem, which uses Fosslim to match various OSS license
with correct SPDX-id or EULA label.
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The MIRIAD-Ruby package...
1. Makes MIRIAD datasets accessible from Ruby by wrapping
the MIRIAD UVIO routines.
2. Makes Ruby usable with MIRIAD datasets by adding convenience,
utility, and astronomy related methods to Ruby classes.
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detects music on wave (.wav) file
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Ruby narray_ffi interface
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NArrayMiss is an additional class with processing of missing value to NArray which is a numeric multi-dimensional array class.
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A pure Ruby API to the NIfTI Neuroimaging Format
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Game of Life with customizable rules on ncurses viewer
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A linear algebra library cooperating with NArray.
This library calls blas and lapack routines for fast computations.
This library has following functionalities.
* xGEMM (multiply two matrices and add other matrix)
* Solve LLS(Least Square Sum) problems
* Computing determinant (using QR decomposition)
* Solve eigenproblems (compute eigenvalues and eigenvectors)
* (Pivoted) LU decompotision
* SVD(Singular value decomposition)
* QR decomposition
* Cholesky decomposition
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Activity