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

This version

5.8.8

5.8.7

5.8.6

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

PyMca5-5.8.8.tar.gz (15.9 MB view details)

Uploaded Source

Built Distributions

PyMca5-5.8.8-cp311-cp311-win_amd64.whl (9.6 MB view details)

Uploaded CPython 3.11 Windows x86-64

PyMca5-5.8.8-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (11.8 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ ppc64le

PyMca5-5.8.8-cp311-cp311-macosx_10_9_universal2.whl (10.1 MB view details)

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

PyMca5-5.8.8-cp310-cp310-win_amd64.whl (9.6 MB view details)

Uploaded CPython 3.10 Windows x86-64

PyMca5-5.8.8-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (11.6 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ppc64le

PyMca5-5.8.8-cp310-cp310-macosx_10_9_universal2.whl (10.1 MB view details)

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

PyMca5-5.8.8-cp39-cp39-win_amd64.whl (9.6 MB view details)

Uploaded CPython 3.9 Windows x86-64

PyMca5-5.8.8-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (11.6 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ppc64le

PyMca5-5.8.8-cp39-cp39-macosx_10_9_x86_64.whl (9.7 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

PyMca5-5.8.8-cp39-cp39-macosx_10_9_universal2.whl (10.1 MB view details)

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

PyMca5-5.8.8-cp38-cp38-win_amd64.whl (9.6 MB view details)

Uploaded CPython 3.8 Windows x86-64

PyMca5-5.8.8-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (11.7 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ppc64le

PyMca5-5.8.8-cp38-cp38-macosx_11_0_universal2.whl (10.1 MB view details)

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

PyMca5-5.8.8-cp38-cp38-macosx_10_9_x86_64.whl (9.7 MB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

PyMca5-5.8.8-cp37-cp37m-win_amd64.whl (9.6 MB view details)

Uploaded CPython 3.7m Windows x86-64

PyMca5-5.8.8-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (11.5 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ ppc64le

PyMca5-5.8.8-cp37-cp37m-macosx_10_9_x86_64.whl (9.7 MB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

File details

Details for the file PyMca5-5.8.8.tar.gz.

File metadata

  • Download URL: PyMca5-5.8.8.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 PyMca5-5.8.8.tar.gz
Algorithm Hash digest
SHA256 0972209bac65605730b34dd506cfc5d536058394cdd04de2f0fd84eac1b9d8b6
MD5 e3feae14eed5a6ab2f5cf1e2666be4c9
BLAKE2b-256 ccc1d9b1451a48520b908e225254eab14131b7c7c5b32f611fd4219a1c0038aa

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.8-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: PyMca5-5.8.8-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 9.6 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 PyMca5-5.8.8-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 3f288ed6a36459aabeac61f1bbf1575486bb3e5cf3e6c2ad46f721a3736ac253
MD5 04a636a547daa6b4fa10eae09e89c25c
BLAKE2b-256 049e598398367c80e2be91113ec4844e528d5e67df5fd12fa7d27e304449907a

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.8-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for PyMca5-5.8.8-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 d077101e52e7871d7b9c7637fa9c2db76e95cd702524fbfc9cc21829ce0bbc39
MD5 cd6826ff944a517d5026a5d0a09ff326
BLAKE2b-256 b187fc89e0ac39e42e10c5a674672a394105d3d75a824369886922e543e9fea4

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.8-cp311-cp311-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for PyMca5-5.8.8-cp311-cp311-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 b96cba558c9a249ae047e396efa2a3b333d8e3326276d25e2cc68f0ae88f2443
MD5 af0f64800177836a7609bb7b635082e8
BLAKE2b-256 3d502980b69e595b7fdb300a60d1ad22bc61eb4b320ae319502ee896511c0553

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.8-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: PyMca5-5.8.8-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 9.6 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 PyMca5-5.8.8-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 a3d181fb42ab3eef41a6fe7d8b568dc624d07e47b5e809b9a05f460f73e99653
MD5 f9cf0e308a3b0a933257c4a8dbce6bce
BLAKE2b-256 35ab797e99f09395c4760a2756b949f548effb7b3040656146e455e28bb1c384

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.8-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for PyMca5-5.8.8-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 cd530da954b24cc13b323c8443c018ce08c7aeb4e339267f30baadcd8a7bc5fd
MD5 6c4eadddba68bcec2e950765198f4e27
BLAKE2b-256 d8c6387511c43e77c3155649effd3540b40ba23f6b64dc05ba3e4309e8cc256a

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.8-cp310-cp310-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for PyMca5-5.8.8-cp310-cp310-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 189d3df7a5b41742e93447d7e7aabfed2401b963145a7f8448783e735bf3df53
MD5 363e05adba982681b5a71a8f6ed6553b
BLAKE2b-256 092b19ad1412dae63dc70b734a3734c2ed888ed976cd842a563cbd22bd2dc07b

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.8-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: PyMca5-5.8.8-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 PyMca5-5.8.8-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 d89153d9b37ad751e0b9524d781473039ace0c7bbcfd4ac5c6cc307acada0d10
MD5 e168123a53111b2a54d74dc6c745b41d
BLAKE2b-256 500d0b083ecdf4486249daefc604531166921d6f299ebb19676b8455754795a8

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.8-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for PyMca5-5.8.8-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 b8723a60493762922271ac174f06a186b2e96e063dc97a3f46da70e2d448f472
MD5 d50b3984d08cb1ca5d73b79ae14d0af6
BLAKE2b-256 267edc3340d18249e1460da03a3755c2cc4b49cef1635df16d0f7ae2ff50f1fe

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.8-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for PyMca5-5.8.8-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 3bc1a5cdd486144883ad67067c3e6868f02519dbcb3f034c9c57c05d90d1a509
MD5 9dba419314e3242dc30f86b0b0608333
BLAKE2b-256 fc94caae3c442153ba7a2d03c26a9d79982dfdafcacfd63a7c57a5b718c2ed47

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.8-cp39-cp39-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for PyMca5-5.8.8-cp39-cp39-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 3cfbe8acff683f2b9eaab737b2de610f763c275f409ab04fe475991a477f8ca5
MD5 a899cacdced7511254b40107472b0309
BLAKE2b-256 13ed6c2f042d1b934ae8a166102a51abbfa1baf05948ed6a2104a24f8f2b8d01

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.8-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: PyMca5-5.8.8-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 PyMca5-5.8.8-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 fbf5cff4154b6b5f4d55e62fc528b8480196929be4e04096326b1a7e9585b79a
MD5 2250b01ecf0f2791f95437df0e83c6e8
BLAKE2b-256 8997d529124ecd828dd4455fb5101fde9e3644d39a26a9095ea9a2b914921891

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.8-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for PyMca5-5.8.8-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 d2c34d3250da05c12324c5a59c2b9afb3128d0e84b1530fc7ccebdec72f0f27b
MD5 b2f81cc077418c791a2f110c5381a7e2
BLAKE2b-256 2ea98e3a2c7bda021fac57fffbf5487d8b2b382e5800e208b02a36966146d06b

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.8-cp38-cp38-macosx_11_0_universal2.whl.

File metadata

File hashes

Hashes for PyMca5-5.8.8-cp38-cp38-macosx_11_0_universal2.whl
Algorithm Hash digest
SHA256 2ac37a7e80916d6e0257f66036f00ccec84ae164944404f27ec3664af639a771
MD5 7a4f5321a8f88055703a689c39f94354
BLAKE2b-256 dacbf51e697c4375ce080736df1ed757cec6e26c9a3d0daf9fc9ca6f2fd8b41a

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.8-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for PyMca5-5.8.8-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 dda0c1cd438a674095ea0ff87ab9142d9be6db723dccbe1a5f69008945dbae52
MD5 2b660b8df8b56a801df74c3af3f7f31d
BLAKE2b-256 96acdf40bbd358f6bb4e298c3cb780bebf7ad4e2f3071daabd1cf6fb3c0d0338

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.8-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: PyMca5-5.8.8-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 PyMca5-5.8.8-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 688f05d6bf55e10bd95f90c2e8073cfc225c71a3ffe4576cb09c033b4a0ca885
MD5 4b4a38858870171e09979f850a3530f4
BLAKE2b-256 2d182bc44294445f330a099432067b63ee552312894dfde118cb163646563c56

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.8-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for PyMca5-5.8.8-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 f6e82f652e664bf8ddfc7c24766058a23f5aff77399402f75df30ec413587bd4
MD5 965d2bb43032fafc76323fef20fb9979
BLAKE2b-256 76f25ffcb7f0742b2f163e7dc9835f95a74c367529c5d997ef292fa04469ff4a

See more details on using hashes here.

File details

Details for the file PyMca5-5.8.8-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for PyMca5-5.8.8-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 fdd8612a73cb419875beb01cb61b40efc3ad901b0f338fd6ea8b467e97913ed2
MD5 c408f1e3950c7e99e0285c1a8f2f55a5
BLAKE2b-256 8dce931ee5f1bb0499a9cc6431ff62aceee0223c8eca88203448d1715642ed3d

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