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gnu: Add python-opentsne.
* gnu/packages/machine-learning.scm (python-opentsne): New variable. Signed-off-by: Leo Famulari <leo@famulari.name>
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@ -896,6 +896,51 @@ data analysis.")
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for k-neighbor-graph construction and approximate nearest neighbor search.")
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(license license:bsd-2)))
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(define-public python-opentsne
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(package
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(name "python-opentsne")
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(version "0.4.4")
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(source
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(origin
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;; No tests in the PyPI tarball.
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(method git-fetch)
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(uri (git-reference
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(url "https://github.com/pavlin-policar/openTSNE")
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(commit (string-append "v" version))))
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(file-name (string-append name "-" version "-checkout"))
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(sha256
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(base32 "08wamsssmyf6511cbmglm67dp48i6xazs89m1cskdk219v90bc76"))))
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(build-system python-build-system)
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(arguments
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`(#:phases
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(modify-phases %standard-phases
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;; Benchmarks require the 'macosko2015' data files.
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(add-after 'unpack 'delete-benchmark
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(lambda _
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(delete-file-recursively "benchmarks")
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#t))
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;; Numba needs a writable dir to cache functions.
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(add-before 'check 'set-numba-cache-dir
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(lambda _
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(setenv "NUMBA_CACHE_DIR" "/tmp")
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#t)))))
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(native-inputs
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`(("python-cython" ,python-cython)))
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(inputs
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`(("fftw" ,fftw)))
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(propagated-inputs
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`(("python-numpy" ,python-numpy)
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("python-pynndescent" ,python-pynndescent)
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("python-scikit-learn" ,python-scikit-learn)
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("python-scipy" ,python-scipy)))
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(home-page "https://github.com/pavlin-policar/openTSNE")
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(synopsis "Extensible, parallel implementations of t-SNE")
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(description
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"This is a modular Python implementation of t-Distributed Stochastic
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Neighbor Embedding (t-SNE), a popular dimensionality-reduction algorithm for
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visualizing high-dimensional data sets.")
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(license license:bsd-3)))
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(define-public python-scikit-rebate
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(package
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(name "python-scikit-rebate")
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