[ ソース: debian-science ]
パッケージ: science-datamanagement (1.14.6)
science-datamanagement に関するリンク
Debian の資源:
debian-science ソースパッケージをダウンロード:
メンテナ:
外部の資源:
- ホームページ [wiki.debian.org]
類似のパッケージ:
Debian Science Data Management packages
This metapackage will install packages to assist with data management tasks, such as obtaining data from remote resources, keeping data under version control, etc.
その他の science-datamanagement 関連パッケージ
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- dep: science-config (= 1.14.6)
- Debian Science Project config package
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- dep: science-tasks (= 1.14.6)
- Debian Science tasks for tasksel
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- rec: git-annex
- manage files with git, without checking their contents into git
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- rec: hdf5-filter-plugin
- external filters for HDF5: LZ4, BZip2, Bitshuffle
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- rec: hdf5-filter-plugin-blosc-serial
- blocking, shuffling and lossless compression library
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- rec: hdf5-filter-plugin-zfp-serial
- Compression plugin for the HDF5 library using ZFP compression
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- rec: nexus-tools
- NeXus scientific data file format - applications
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- rec: plfit
- fitting power-law distributions to empirical data -- interfaces
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- rec: python3-jdata
- JData encoder/decoder for python 3
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- rec: python3-mdp
- Modular toolkit for Data Processing
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- rec: python3-nxs
- NeXus scientific data file format - Python 3 binding
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- rec: python3-pyzoltan
- Wrapper for the Zoltan data management library
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- rec: virtuoso-opensource
- 高性能なデータベース
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- rec: visidata
- rapidly explore columnar data in the terminal
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- sug: datalad
- data files management and distribution platform
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- sug: datalad-container
- DataLad extension for working with containerized environments
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- sug: libnexus-dev
- NeXus scientific data file format - development libraries
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- sug: libnexus-java
- NeXus scientific data file format - java libraries
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- sug: libplfit-dev
- fitting power-law distributions to empirical data -- development
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- sug: python3-openpyxl
- Python 3 module to read/write OpenXML xlsx/xlsm files
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- sug: python3-opentsne
- t-Distributed Stochastic Neighbor Embedding algorithm
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- sug: python3-plfit
- fitting power-law distributions to empirical data -- Python