Mapping and X-Ray Fluorescence Analysis

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for vasole from gravatar.com vasole

Unverified details

These details have not been verified by PyPI
Project links
Meta
Classifiers

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

Verified details

These details have been verified by PyPI
Maintainers
Avatar for vasole from gravatar.com vasole

Unverified details

These details have not been verified by PyPI
Project links
Meta
Classifiers

Release history Release notifications | RSS feed

5.9.3

5.9.2

5.9.1

5.9.0

5.8.9

5.8.8

5.8.7

5.8.6

This version

5.8.5

5.8.4

5.8.3

5.8.2

5.8.1

5.8.0

5.7.6

5.7.5

5.7.4

5.7.3

5.7.2

5.7.1

5.7.0

5.6.7

5.6.6

5.6.5

5.6.3

5.6.2

5.6.0

5.5.5

5.5.4

5.5.3

5.5.2

5.5.1

5.5.0

5.4.3

5.4.2

5.4.1

5.4.0

5.3.2

5.3.1

5.3.0

5.2.2

5.2.1

5.2.0

5.1.4

5.1.3

5.1.2

Download files

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

Source Distribution

PyMca5-5.8.5.tar.gz (15.9 MB view details)

Uploaded Source

Built Distributions

PyMca5-5.8.5-cp311-cp311-win_amd64.whl (9.5 MB view details)

Uploaded CPython 3.11 Windows x86-64

PyMca5-5.8.5-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (11.6 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ ppc64le

PyMca5-5.8.5-cp311-cp311-macosx_10_9_universal2.whl (10.0 MB view details)

Uploaded CPython 3.11 macOS 10.9+ universal2 (ARM64, x86-64)

PyMca5-5.8.5-cp310-cp310-win_amd64.whl (9.5 MB view details)

Uploaded CPython 3.10 Windows x86-64

PyMca5-5.8.5-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (11.5 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ppc64le

PyMca5-5.8.5-cp310-cp310-macosx_10_9_universal2.whl (10.0 MB view details)

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

PyMca5-5.8.5-cp39-cp39-win_amd64.whl (9.6 MB view details)

Uploaded CPython 3.9 Windows x86-64

PyMca5-5.8.5-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (11.5 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ppc64le

PyMca5-5.8.5-cp39-cp39-macosx_10_9_x86_64.whl (9.6 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

PyMca5-5.8.5-cp39-cp39-macosx_10_9_universal2.whl (10.0 MB view details)

Uploaded CPython 3.9 macOS 10.9+ universal2 (ARM64, x86-64)

PyMca5-5.8.5-cp38-cp38-win_amd64.whl (9.6 MB view details)

Uploaded CPython 3.8 Windows x86-64

PyMca5-5.8.5-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (11.5 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ppc64le

PyMca5-5.8.5-cp38-cp38-macosx_11_0_universal2.whl (10.0 MB view details)

Uploaded CPython 3.8 macOS 11.0+ universal2 (ARM64, x86-64)

PyMca5-5.8.5-cp38-cp38-macosx_10_9_x86_64.whl (9.6 MB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

PyMca5-5.8.5-cp37-cp37m-win_amd64.whl (9.6 MB view details)

Uploaded CPython 3.7m Windows x86-64

PyMca5-5.8.5-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (11.4 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ ppc64le

PyMca5-5.8.5-cp37-cp37m-macosx_10_9_x86_64.whl (9.6 MB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

File details

Details for the file PyMca5-5.8.5.tar.gz.

File metadata

  • Download URL: PyMca5-5.8.5.tar.gz
  • Upload date:
  • Size: 15.9 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.10

File hashes

Hashes for PyMca5-5.8.5.tar.gz
Algorithm Hash digest
SHA256 b1c9a973face13640a920fd0cf9bf4bf2f8bb23c126b34c901ae48b2cd8ffa06
MD5 7404519eb35251aec4d39143b10f8b26
BLAKE2b-256 db79c5d1a44abdc2f4dcd92ede2169ce770fee4b679641e5ee824f94f15cabec

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.5-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: PyMca5-5.8.5-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 9.5 MB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.10

File hashes

Hashes for PyMca5-5.8.5-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 7f7d3403e39d6839a4adbd09265976c8206382b0f4a5a2c81e0c4c80a92a4f83
MD5 ccdd22ab4594911c097ed46f893423e3
BLAKE2b-256 c80a71f9909a0c4bd4b8ece56f7d2673acde8977af8e0e54dec76815f7e90d48

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.5-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for PyMca5-5.8.5-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 e88e1b8a8423c8f34fd73ab8bbb13f600c6dc6e1014d679d83176fe89182b6ac
MD5 626eeeeaf7940499c0a0533fcc7a7d2e
BLAKE2b-256 aed3d9e3e043b72cee091e5d14ea1ca42002220e3b5fe9a2c25eeba5820ac93e

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.5-cp311-cp311-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for PyMca5-5.8.5-cp311-cp311-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 a6031287bbd02cd1c98ef3bd20da341bfd7eaebf2d3c532680ab51e39019c81b
MD5 f8f1906c09e4114cd6fc44b1d4105c49
BLAKE2b-256 ef06a08815a91252b401487c08401989a3cd04a8542452569e71ef291a41cbb4

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.5-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: PyMca5-5.8.5-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 9.5 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.10

File hashes

Hashes for PyMca5-5.8.5-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 aa2aa57f44bc207ab418af94dd483a9965efc6de74e6303cdeba698322f3a190
MD5 039e969dd63a41ff5020c07a10d65f35
BLAKE2b-256 58cb4bc288d43da9fad6dbdcabf37ef8189b67be3741a8ffc652e9a811301fca

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.5-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for PyMca5-5.8.5-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 09970882925f4313a0e068e83676de891cd0938b6662de00fe92381debcd2d5b
MD5 2496a6b8132c490e857a71d8f58e1441
BLAKE2b-256 ec0c59ee87e562b962b839ea875081114949a07a049d2d668f81c92988f5ead7

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.5-cp310-cp310-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for PyMca5-5.8.5-cp310-cp310-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 290a59a5ce036d7ace91183b11b1c080c1ca77e3f7d4dd6a515d8829306e2d5e
MD5 4840380d43cf17039f3496ab39f98463
BLAKE2b-256 2ff774b8d2fe6556da6443f6e865b85fa7d3073cbc4c91797a565e1e531e7cc1

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.5-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: PyMca5-5.8.5-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 9.6 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.10

File hashes

Hashes for PyMca5-5.8.5-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 677f5d198a521f042dd1ad137408e400832e9bbd586e75d337f8a4a5b1faf2f2
MD5 c1fd338c2feaa14306a97a80e013ed60
BLAKE2b-256 74c362a18bbbf2b74957ad0a1022987d2810f5735f3d25b2156a69d5a0e6ebfd

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.5-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for PyMca5-5.8.5-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 46c82d337b200f206c6abbdeb180421045d5553b4b4dc10df8f3c6dd3542a703
MD5 18d6adf7dddf29e64feadc68b02bf14e
BLAKE2b-256 0ced168b629cf47a2711362d5e19183dafedb7c112a4bf9df44961a1db05185c

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.5-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for PyMca5-5.8.5-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 eebe100efaa79ed7c4428a28c803a92dd11fc766053606af17f1ea95186f59a9
MD5 4c14c386acf2a5c7ebdfa3203dfb7d23
BLAKE2b-256 4dd41f6e7e1e891b563d70da52f230cc4cfc72bc22b49db0697cf255a6530b8d

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.5-cp39-cp39-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for PyMca5-5.8.5-cp39-cp39-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 284fefdfc96814f12363914cf2df491005182abfc01fdf621c3bce29d36a9a1f
MD5 872742f2d017b55ee5aaf3d68c14cee0
BLAKE2b-256 1f42ae011fef1a1dd47c940672109f27c7a3117a81a54ad4c31838f6d09e8a2b

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.5-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: PyMca5-5.8.5-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 9.6 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.10

File hashes

Hashes for PyMca5-5.8.5-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 6331da1c0b6bbed2a092407d559d0b80b8ba72dfcf58ab94dd2b4c5c70294a7d
MD5 694b88015cde7119ca784f41d7f08794
BLAKE2b-256 3a8fe48fcb950f9eeb23ae5b6a80af20bf42b5123aafdc33a3082a8997316d36

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.5-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for PyMca5-5.8.5-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 e3a0b16da0be85df1f9ece609e78785e0a4fbb4e4f95e5b760d668215d6b7af0
MD5 a920e33b338a0fcd08a0bfb942b52cde
BLAKE2b-256 b1ee6109d71d787737862fa102a1d98709297093bc2b30a6d6e94b139dfcda09

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.5-cp38-cp38-macosx_11_0_universal2.whl.

File metadata

File hashes

Hashes for PyMca5-5.8.5-cp38-cp38-macosx_11_0_universal2.whl
Algorithm Hash digest
SHA256 987d46147dee297541708245ed6465a6d5de8618d1aa0ab3c8d39fe078ddcfce
MD5 12287925e672a0c7b07c9096b1b72fc4
BLAKE2b-256 2c368a2407c096ab5c27172e9c64871553b8a82036ae6769532e7aad83daae3e

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.5-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for PyMca5-5.8.5-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 25af49b540984965d6f04043cbfb18c6aeb00596bfe883f967dfed5c09cc1335
MD5 277f966838a33c1c5fd23db56fefd9f9
BLAKE2b-256 7798219fa1f365116894b1d916addae447c58a2f9641815efa982b8f54e4690b

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.5-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: PyMca5-5.8.5-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 9.6 MB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.10

File hashes

Hashes for PyMca5-5.8.5-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 e7705c32932fbf67e6f12d88e70f4423246b50597489de7c11878251a89df8ba
MD5 64f91d503a5933de1376e24cea233c65
BLAKE2b-256 0140fc046ddaf649856925c423d4cc979d14f91ae4b829c59168f962fb4650e7

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.5-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for PyMca5-5.8.5-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 a629bac3d5f3d75b87d916a16105cf522f243a621ded321626463731fe027276
MD5 6276b3335f0f08d252b93ce05031a0f0
BLAKE2b-256 0b449e8939d05824b066593981c7ce258ba60e80b0cc28ed4f968994a782f364

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.5-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for PyMca5-5.8.5-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 aad2c0eecaedd45c5e3ce1fac22c90f3153403713c729842dc88ce77e22a49cd
MD5 a19c3b5ddb22b37590479d68c040b0f8
BLAKE2b-256 30329b72df9c9245b7fd79c55882bdf71667b2ac2611e2e56a69b6d84605c47a

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