Skip to main content

Mapping and X-Ray Fluorescence Analysis

Project description

Stand-alone application and Python tools for interactive and/or batch processing analysis of X-Ray Fluorescence Spectra. Graphical user interface (GUI) and batch processing capabilities provided

Project details


Download files

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

Source Distribution

PyMca5-5.7.1.tar.gz (15.8 MB view details)

Uploaded Source

Built Distributions

PyMca5-5.7.1-cp310-cp310-win_amd64.whl (9.4 MB view details)

Uploaded CPython 3.10 Windows x86-64

PyMca5-5.7.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (11.4 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ppc64le

PyMca5-5.7.1-cp310-cp310-macosx_10_9_universal2.whl (9.9 MB view details)

Uploaded CPython 3.10 macOS 10.9+ universal2 (ARM64, x86-64)

PyMca5-5.7.1-cp39-cp39-win_amd64.whl (9.5 MB view details)

Uploaded CPython 3.9 Windows x86-64

PyMca5-5.7.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (11.4 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ppc64le

PyMca5-5.7.1-cp38-cp38-win_amd64.whl (9.5 MB view details)

Uploaded CPython 3.8 Windows x86-64

PyMca5-5.7.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (11.5 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ppc64le

PyMca5-5.7.1-cp37-cp37m-win_amd64.whl (9.5 MB view details)

Uploaded CPython 3.7m Windows x86-64

PyMca5-5.7.1-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (11.3 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ ppc64le

PyMca5-5.7.1-cp36-cp36m-win_amd64.whl (9.5 MB view details)

Uploaded CPython 3.6m Windows x86-64

File details

Details for the file PyMca5-5.7.1.tar.gz.

File metadata

  • Download URL: PyMca5-5.7.1.tar.gz
  • Upload date:
  • Size: 15.8 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/54.2.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.8.8

File hashes

Hashes for PyMca5-5.7.1.tar.gz
Algorithm Hash digest
SHA256 62b1d9eaeb4d88bd4d8e13eb80705c8c4274175a7ffc5bb664571f4e9185e298
MD5 3c59f59de566260481a2bc2368a944b0
BLAKE2b-256 794be042763ee1f9ed979ea09f715225434d75789e6f5841292b10375c8ee99d

See more details on using hashes here.

File details

Details for the file PyMca5-5.7.1-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: PyMca5-5.7.1-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 9.4 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/54.2.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.8.8

File hashes

Hashes for PyMca5-5.7.1-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 374ae94f29a8d8408b4270c62dce85b721899b9031984884c784d85dbac7fcc4
MD5 56d60578f41fbe858362924c087afd66
BLAKE2b-256 f472a78b1d922a472a0745e14df8dae515ef47326929cbaaa85261814204b2fa

See more details on using hashes here.

File details

Details for the file PyMca5-5.7.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for PyMca5-5.7.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 84b8b6507a0d4841d1274f1c1bb26e2c6255f303f318cca082d7cabea8adc418
MD5 818ab4d1b4c05b1233f2352821ab9c7f
BLAKE2b-256 60c3606065b289cf924536b73d00f8fe0ec241d2ea5f6e1fd3b24ddab248159c

See more details on using hashes here.

File details

Details for the file PyMca5-5.7.1-cp310-cp310-macosx_10_9_universal2.whl.

File metadata

  • Download URL: PyMca5-5.7.1-cp310-cp310-macosx_10_9_universal2.whl
  • Upload date:
  • Size: 9.9 MB
  • Tags: CPython 3.10, macOS 10.9+ universal2 (ARM64, x86-64)
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/54.2.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.8.8

File hashes

Hashes for PyMca5-5.7.1-cp310-cp310-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 7c70fe508dfb1554c0fab92ce4b2019ad8685b5c27bdf9c8c42b9aee8497a356
MD5 e6f48ce86587bd30a1b907907eb90130
BLAKE2b-256 1fb18f5cbc5b686f67e83b69c0b6d5ee762b30a202a1cbc31883d109ac930bcb

See more details on using hashes here.

File details

Details for the file PyMca5-5.7.1-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: PyMca5-5.7.1-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 9.5 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/54.2.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.8.8

File hashes

Hashes for PyMca5-5.7.1-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 807222b37f1744d54abb10af73c6764413d1160135f1f64813aac440701e3ed6
MD5 94fb38210cdf4c72e623f0c3b8c50ca0
BLAKE2b-256 74e2b8e9e5207aec81a88bf94759232a4cc5003240d8c54820f94488daf76f8e

See more details on using hashes here.

File details

Details for the file PyMca5-5.7.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for PyMca5-5.7.1-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 8f3f2bed0666cd3c17afbbedbe934e2e0cbef6949ca56ffd629d62e52894fc3f
MD5 7aa758642617577bb643d83272ca9934
BLAKE2b-256 d1d3d9ec5a267f4d251a8cf146fca6dc6c14e2db56b83a1551cdf71949b85e3f

See more details on using hashes here.

File details

Details for the file PyMca5-5.7.1-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: PyMca5-5.7.1-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 9.5 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/54.2.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.8.8

File hashes

Hashes for PyMca5-5.7.1-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 46130dfe77b80d01773d26cef18f47263b0042cd41f84d06f6a6b8fc5487e5db
MD5 e7adf45f994ff46caa89d79561db5a07
BLAKE2b-256 a3277b0f12d0cb4cb27c27aec5a9a26e07e9a4a455c310442d7ef8d0c7318a32

See more details on using hashes here.

File details

Details for the file PyMca5-5.7.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for PyMca5-5.7.1-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 1396d05b4fb4b44c27ef645307a3017e69f2e8c4a250368a4b77f5954e996b11
MD5 2ede3da5defc96fb830ae725576b9464
BLAKE2b-256 bb2032e1a60c442b494f63c4637d732d422a0156d21191a7570d9bbb0cd1f99f

See more details on using hashes here.

File details

Details for the file PyMca5-5.7.1-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: PyMca5-5.7.1-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 9.5 MB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/54.2.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.8.8

File hashes

Hashes for PyMca5-5.7.1-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 8f2e8fd12899d4e7b6b0bf42957299140f3309a2565430aadbbef43fc2e574bd
MD5 f5a9131e1acf6c8582f30154114f9778
BLAKE2b-256 134a05cf6ddd4d2e069adfe49f5f34d1063e66ab891bbdca426f6bfaf2165253

See more details on using hashes here.

File details

Details for the file PyMca5-5.7.1-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for PyMca5-5.7.1-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 c02fed6a0fcf75d6f120b98c6cc888b9bdfce10533aa21e0e93696db5c1de119
MD5 fc4995b4201e49b243bc423e78842663
BLAKE2b-256 09f0256db222d28726696ded57d2010c1b85800e33ac01f2c5c73d52c6b1ee6b

See more details on using hashes here.

File details

Details for the file PyMca5-5.7.1-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: PyMca5-5.7.1-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 9.5 MB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/54.2.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.8.8

File hashes

Hashes for PyMca5-5.7.1-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 055ad66c9887588ae1717de07c77461b7746b2bb43374e5a9f70e45453b5c54d
MD5 cbd4edb6616004c2a7e9bac36ae16946
BLAKE2b-256 3de5866a1cc3079c0a96c3fb79038e6907180f8267079c86d5886e3c831bfeac

See more details on using hashes here.

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