Multidimensional data analysis toolbox

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for ericpre from gravatar.com ericpre Avatar for francisco_dlpm from gravatar.com francisco_dlpm Avatar for t.ostasevicius from gravatar.com t.ostasevicius

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: GNU General Public License v3 (GPLv3) (GPL v3)
  • Author: The HyperSpy developers
  • Maintainer: Francisco de la Peña
  • Tags EDX, EELS, EFTEM, EMSA, FEI, ICA, PCA, PES, STEM, TEM, curve fitting, data analysis, dm3, electron energy loss spectroscopy, electron microscopy, emi, energy dispersive x-rays, hyperspectral, hyperspectrum, multidimensional, hyperspy, machine learning, microscopy, model, msa, numpy, python, quantification, scipy, ser, spectroscopy, spectrum image
Classifiers

Project description

Travis AppVeyor Coveralls rtd pypi_version python_version gitter saythanks

HyperSpy is an open source Python library which provides tools to facilitate the interactive data analysis of multidimensional datasets that can be described as multidimensional arrays of a given signal (e.g. a 2D array of spectra a.k.a spectrum image).

HyperSpy aims at making it easy and natural to apply analytical procedures that operate on an individual signal to multidimensional arrays, as well as providing easy access to analytical tools that exploit the multidimensionality of the dataset.

Its modular structure makes it easy to add features to analyze different kinds of signals.

HyperSpy is released under the GPL v3 license.

Since version 0.8.4 HyperSpy only supports Python 3. If you need to install HyperSpy in Python 2.7 install HyperSpy 0.8.3.

Contributing

Everyone is welcome to contribute. Please read our contributing guidelines and get started!

Cite

DOI

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for ericpre from gravatar.com ericpre Avatar for francisco_dlpm from gravatar.com francisco_dlpm Avatar for t.ostasevicius from gravatar.com t.ostasevicius

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: GNU General Public License v3 (GPLv3) (GPL v3)
  • Author: The HyperSpy developers
  • Maintainer: Francisco de la Peña
  • Tags EDX, EELS, EFTEM, EMSA, FEI, ICA, PCA, PES, STEM, TEM, curve fitting, data analysis, dm3, electron energy loss spectroscopy, electron microscopy, emi, energy dispersive x-rays, hyperspectral, hyperspectrum, multidimensional, hyperspy, machine learning, microscopy, model, msa, numpy, python, quantification, scipy, ser, spectroscopy, spectrum image
Classifiers

Release history Release notifications | RSS feed

2.2.0

2.1.1

2.1.0

2.0.1

2.0

2.0rc0 pre-release

1.7.6

1.7.5

1.7.4

1.7.3

1.7.2

1.7.1

1.7.0

1.6.5

1.6.4

1.6.3

1.6.2

1.6.1

1.6.0

1.5.2

1.5.1

This version

1.5

1.4.2

1.4.1

1.4

1.3.2

1.3.1

1.3

1.2

1.1.2

1.1.1

1.1

1.0.1

1.0

0.8.5

0.8.4

0.8.3

0.8.2

0.8.1

0.8

0.7.3

0.7.2

0.7.1

0.7

0.6

0.5.1

0.5

0.4.1

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

hyperspy-1.5.tar.gz (26.3 MB view details)

Uploaded Source

Built Distributions

hyperspy-1.5-cp37-cp37m-win_amd64.whl (27.3 MB view details)

Uploaded CPython 3.7m Windows x86-64

hyperspy-1.5-cp37-cp37m-win32.whl (27.3 MB view details)

Uploaded CPython 3.7m Windows x86

hyperspy-1.5-cp37-cp37m-macosx_10_7_x86_64.whl (27.3 MB view details)

Uploaded CPython 3.7m macOS 10.7+ x86-64

hyperspy-1.5-cp36-cp36m-win_amd64.whl (27.3 MB view details)

Uploaded CPython 3.6m Windows x86-64

hyperspy-1.5-cp36-cp36m-macosx_10_7_x86_64.whl (27.3 MB view details)

Uploaded CPython 3.6m macOS 10.7+ x86-64

File details

Details for the file hyperspy-1.5.tar.gz.

File metadata

  • Download URL: hyperspy-1.5.tar.gz
  • Upload date:
  • Size: 26.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.2 CPython/3.7.3

File hashes

Hashes for hyperspy-1.5.tar.gz
Algorithm Hash digest
SHA256 cd2ff4efc6bdafa4e18d60312ad099a8a91ac2725a137345cd7906c8dc9510ac
MD5 f3f0fc99962602d7574261112a6fbf5c
BLAKE2b-256 c7fa614b425fe4816cce2459c5ce279fbbf8799b9ef1c7421aa7cc8cd0a79277

See more details on using hashes here.

Provenance

File details

Details for the file hyperspy-1.5-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: hyperspy-1.5-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 27.3 MB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.2 CPython/3.7.3

File hashes

Hashes for hyperspy-1.5-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 9dbbd433e32f1527ebcc76d72075f38dcf897907b86e6e40393646f34a6ec9d7
MD5 b4b3937ae23e3c4d97d1e2b79c664c1a
BLAKE2b-256 1483aa12560ff451020e1ea6a0799f86d5180b81ea2ff104d6e2e55dd65032f1

See more details on using hashes here.

Provenance

File details

Details for the file hyperspy-1.5-cp37-cp37m-win32.whl.

File metadata

  • Download URL: hyperspy-1.5-cp37-cp37m-win32.whl
  • Upload date:
  • Size: 27.3 MB
  • Tags: CPython 3.7m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.2 CPython/3.7.3

File hashes

Hashes for hyperspy-1.5-cp37-cp37m-win32.whl
Algorithm Hash digest
SHA256 b7041b521dfc8c2ef7c13faeb2133ba2bd9ffa8d7f1669f5f2b709364b64db77
MD5 182541bad46cfe0bd464a2b07e800639
BLAKE2b-256 945c27be870c4d4ea50f7bd82897f7a8fbad76a8f8d4f986808360537d44ce5e

See more details on using hashes here.

Provenance

File details

Details for the file hyperspy-1.5-cp37-cp37m-macosx_10_7_x86_64.whl.

File metadata

  • Download URL: hyperspy-1.5-cp37-cp37m-macosx_10_7_x86_64.whl
  • Upload date:
  • Size: 27.3 MB
  • Tags: CPython 3.7m, macOS 10.7+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.2 CPython/3.7.3

File hashes

Hashes for hyperspy-1.5-cp37-cp37m-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 fd7c7cb8a020b20a34aa41714a829fa37140af2069442f277402caad646578c7
MD5 ef016f18588a37e8d1d4d5d3144395b1
BLAKE2b-256 46e7b059b45b96e3ff1ec9c47b63a435fe267bda4a162040cc2fce4fbc8660fe

See more details on using hashes here.

Provenance

File details

Details for the file hyperspy-1.5-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: hyperspy-1.5-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 27.3 MB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.2 CPython/3.7.3

File hashes

Hashes for hyperspy-1.5-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 c04fdaf3249b5d85b2f620f612215c55edb87f3c5af67f107654c05ab1fc5a72
MD5 9e27e202f308b7192a86053c44dfe6eb
BLAKE2b-256 fdca3008a62bb8e0ea7fd09421dae5c149d7856ad7a8210938de953d876754ef

See more details on using hashes here.

Provenance

File details

Details for the file hyperspy-1.5-cp36-cp36m-macosx_10_7_x86_64.whl.

File metadata

  • Download URL: hyperspy-1.5-cp36-cp36m-macosx_10_7_x86_64.whl
  • Upload date:
  • Size: 27.3 MB
  • Tags: CPython 3.6m, macOS 10.7+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.2 CPython/3.7.3

File hashes

Hashes for hyperspy-1.5-cp36-cp36m-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 596a136a33e4a86658565020857b379256978ac85d07dcb7a3811000405a0037
MD5 488d905676e840075dd921fd3e9a63f5
BLAKE2b-256 855144ed70fbfc1abca9afb01553e5456e5b838128dc6e69ee96012594305a13

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page