Skip to main content

No project description provided

Project description

cleedpy

Python port of the CLEED code written by Georg Held.

Installation

The easiest way to install the package is via pip:

pip install cleedpy

Usage

The cleedpy package provides a command line interface (CLI) to run LEED calculations. Those include: rfactor, search and leed sub-programs. Each program can be called with the cleedpy- prefix, e.g. cleedpy-leed:

cleedpy-leed -i input.yml -e experiment.txt -o search.out -p PHASE

To learn more about the options of each program, use the -h flag:

cleedpy-leed --help

For example runs please see the examples folder.

Documentation

The documentation is available at the Wiki page of the repository.

License

MIT

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

cleedpy-0.1.6.tar.gz (762.1 kB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

cleedpy-0.1.6-cp314-cp314t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (12.3 MB view details)

Uploaded CPython 3.14tmanylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

cleedpy-0.1.6-cp314-cp314t-macosx_11_0_arm64.whl (284.8 kB view details)

Uploaded CPython 3.14tmacOS 11.0+ ARM64

cleedpy-0.1.6-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (12.3 MB view details)

Uploaded CPython 3.14manylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

cleedpy-0.1.6-cp314-cp314-macosx_11_0_arm64.whl (284.8 kB view details)

Uploaded CPython 3.14macOS 11.0+ ARM64

cleedpy-0.1.6-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (12.3 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

cleedpy-0.1.6-cp313-cp313-macosx_11_0_arm64.whl (284.8 kB view details)

Uploaded CPython 3.13macOS 11.0+ ARM64

cleedpy-0.1.6-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (12.3 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

cleedpy-0.1.6-cp312-cp312-macosx_11_0_arm64.whl (284.8 kB view details)

Uploaded CPython 3.12macOS 11.0+ ARM64

cleedpy-0.1.6-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (12.3 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

cleedpy-0.1.6-cp311-cp311-macosx_11_0_arm64.whl (284.8 kB view details)

Uploaded CPython 3.11macOS 11.0+ ARM64

cleedpy-0.1.6-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (12.3 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

cleedpy-0.1.6-cp310-cp310-macosx_11_0_arm64.whl (284.8 kB view details)

Uploaded CPython 3.10macOS 11.0+ ARM64

File details

Details for the file cleedpy-0.1.6.tar.gz.

File metadata

  • Download URL: cleedpy-0.1.6.tar.gz
  • Upload date:
  • Size: 762.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for cleedpy-0.1.6.tar.gz
Algorithm Hash digest
SHA256 7339fed1504d6444a1d28e5c33de7e5c835da5867267099091d8d9ecb8eb24f9
MD5 3e6195556e79b162c10b1e2ce3a656f6
BLAKE2b-256 b904cfda7f85085dc16f316a40c9ecdf27969906e68de5395edc92c3f0505278

See more details on using hashes here.

File details

Details for the file cleedpy-0.1.6-cp314-cp314t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for cleedpy-0.1.6-cp314-cp314t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 c7e1478606f9a312948758b0c69eaef0d4d4363edcf46283bedc068d03167f94
MD5 60255b49de15cae6933a3c8349b84500
BLAKE2b-256 46de6200c79dbf69026f9e29cbf77a5dfa1db924fac895d25c1f46f19eda04fb

See more details on using hashes here.

File details

Details for the file cleedpy-0.1.6-cp314-cp314t-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for cleedpy-0.1.6-cp314-cp314t-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 041c00d33318a0e689b9701885f83858c933c35bd97db7e489cbd9d62115ea18
MD5 3994b4991d1d6a8b5ca05de3d8ede338
BLAKE2b-256 af14a4fbdedb1fd3e1bb847fbf61c013fe3987f7d65aed97afe1153539fbccb2

See more details on using hashes here.

File details

Details for the file cleedpy-0.1.6-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for cleedpy-0.1.6-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 39c82cc21f4aab4d5cc0db8de9a67c895feeea1dc65c032dc3da93958a89fc1c
MD5 cb173a0b472270963954c67ae05b7a24
BLAKE2b-256 566461f3f28c1358e97f03552e457dc6df8af6905697bfde8bf7850b499dc821

See more details on using hashes here.

File details

Details for the file cleedpy-0.1.6-cp314-cp314-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for cleedpy-0.1.6-cp314-cp314-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 1b08b7c3a3cdf81743284833967748ecbd6ef9216cd9133629bc67abbfeaa607
MD5 fe0ec8ff43a9a5aad76823d26ebf0a63
BLAKE2b-256 988225e0f1ca13bff9e56b04cfcdc9ba0d504f4520328fd97fee7dff9659c115

See more details on using hashes here.

File details

Details for the file cleedpy-0.1.6-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for cleedpy-0.1.6-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 008f4688edc771009c0c925bbb4754373e034b32849d59a0b8dc11936b0335d9
MD5 863a0edb917a1a9fceebb7d853eaa567
BLAKE2b-256 433e91facad710535abe41a5684b900d7fdef83d3bc49e6f341515f86cd7b532

See more details on using hashes here.

File details

Details for the file cleedpy-0.1.6-cp313-cp313-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for cleedpy-0.1.6-cp313-cp313-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 55a4f6843dc9d6db1b7d7f7af703ad2a05909fb71a5e16a89dcf04ea1cfd9625
MD5 0a5e0c9a2b923c4436dce07d74125903
BLAKE2b-256 3eabbad024092398d0634557d793b42488ae814d7f572c6276e78bf29bc4d13d

See more details on using hashes here.

File details

Details for the file cleedpy-0.1.6-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for cleedpy-0.1.6-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 75b3e18453c3363c5779eadda5ff17f379f29dd75b1d2b64fa92dcaed8e2a522
MD5 17aa28624065b353724965dea5e2dd96
BLAKE2b-256 cee9533a5f57a44554d85937a534c45c337991b4234c5128fe86d6ff037c24b2

See more details on using hashes here.

File details

Details for the file cleedpy-0.1.6-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for cleedpy-0.1.6-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 25e7982fd46a465a0071fbd0e7b8621fafb37cf16ee5dfb199a9a767f7450a9f
MD5 663ebf6ebdd44b71052ac50320e4aba2
BLAKE2b-256 a6b917a380cf873e841ca4686dc467f164080f39f261a3f6e98e3dcfc779ce68

See more details on using hashes here.

File details

Details for the file cleedpy-0.1.6-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for cleedpy-0.1.6-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 f8d9ce9df94b86e5492693b54d73d8bfd47039cf7c59b81191ac6a582754f973
MD5 7511c5c0c2d1bed3f31b2beab1e0aa06
BLAKE2b-256 f270d7132e2651f88b5c330ce7301fa18c1b095a76dd4f151ced9ff2a66807ee

See more details on using hashes here.

File details

Details for the file cleedpy-0.1.6-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for cleedpy-0.1.6-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 f0551981476541ec54580c43926358ac28be04e6ffd0784ac49168b32af3ca17
MD5 4ca9ca24842ed17e90178508026eea6b
BLAKE2b-256 026678d453dcbd7875448579a1b320c917226cab6f4e854a95cc3cc01b218f67

See more details on using hashes here.

File details

Details for the file cleedpy-0.1.6-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for cleedpy-0.1.6-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 5015dae000ec39a103c8648ae0c11dfb0fe993bed150991544f2e2ce26829b87
MD5 19ad604a961e2a8fad663ea15f284c43
BLAKE2b-256 4fd1e3a51b4d33ffe1d6cf1d68d9aefc6cb1f83e6ef063262eee5aa27945791e

See more details on using hashes here.

File details

Details for the file cleedpy-0.1.6-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for cleedpy-0.1.6-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 782f266371c5ff72f1664f495b65d82150706fb91edc843ebeef4c9da21eb7e5
MD5 25ef8ddd8382152e149139bce7ca6f39
BLAKE2b-256 2f1ef649b9075f87346b13ac9859aecdc41d571e94d6a4863cc9e41305d018cb

See more details on using hashes here.

Supported by

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