A Landau PDF definition to be used in Python.

These details have not been verified by PyPI

Project links

repository

GitHub Statistics

View statistics for this project via Libraries.io, or by using our public dataset on Google BigQuery

Project description

pylandau

example branch parameter

A simple Landau definition to be used in Python, since no common package (Scipy, Numpy, ...) provides this. Also a fast Landau + Gauss convolution is offered, that is usefull for fitting energy losses of charged particles in matter. The Landau is approximated according to Computer Phys. Comm. 31 (1984) 97-111 and the implementation is from CERN ROOT Mathlibs.

Installation

The project is hosted at PyPI. For installation just type:

pip install pylandau

If you want to change the code or start contributing download it and put it into a directory of your choice. From the project root folder run:

pip install -e .

Usage

import numpy as np
import pylandau

x = np.arange(0, 100, 0.01)
y_landau = pylandau.landau(x)
y_langau = pylandau.langau(x)

Project details

These details have not been verified by PyPI

Project links

repository

GitHub Statistics

View statistics for this project via Libraries.io, or by using our public dataset on Google BigQuery

Release history Release notifications | RSS feed

This version

2.2.1

Apr 26, 2022

2.2.0

Mar 16, 2022

2.1.0

Sep 2, 2016

2.0.1

Jun 30, 2016

2.0.0

Jun 30, 2016

1.1.0

Jan 20, 2016

1.0.0

Aug 25, 2015

Download files

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

Source Distribution

pylandau-2.2.1.tar.gz (108.1 kB view hashes)

Uploaded Apr 26, 2022 Source

Built Distributions

pylandau-2.2.1-cp310-cp310-win_amd64.whl (172.3 kB view hashes)

Uploaded Apr 26, 2022 CPython 3.10 Windows x86-64

pylandau-2.2.1-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (450.4 kB view hashes)

Uploaded Apr 26, 2022 CPython 3.10 manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

pylandau-2.2.1-cp310-cp310-macosx_11_0_arm64.whl (185.3 kB view hashes)

Uploaded Apr 26, 2022 CPython 3.10 macOS 11.0+ ARM64

pylandau-2.2.1-cp310-cp310-macosx_10_9_x86_64.whl (186.4 kB view hashes)

Uploaded Apr 26, 2022 CPython 3.10 macOS 10.9+ x86-64

pylandau-2.2.1-cp39-cp39-win_amd64.whl (164.8 kB view hashes)

Uploaded Apr 26, 2022 CPython 3.9 Windows x86-64

pylandau-2.2.1-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (441.8 kB view hashes)

Uploaded Apr 26, 2022 CPython 3.9 manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

pylandau-2.2.1-cp39-cp39-macosx_11_0_arm64.whl (177.9 kB view hashes)

Uploaded Apr 26, 2022 CPython 3.9 macOS 11.0+ ARM64

pylandau-2.2.1-cp39-cp39-macosx_10_9_x86_64.whl (179.0 kB view hashes)

Uploaded Apr 26, 2022 CPython 3.9 macOS 10.9+ x86-64

pylandau-2.2.1-cp38-cp38-win_amd64.whl (157.2 kB view hashes)

Uploaded Apr 26, 2022 CPython 3.8 Windows x86-64

pylandau-2.2.1-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (440.9 kB view hashes)

Uploaded Apr 26, 2022 CPython 3.8 manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

pylandau-2.2.1-cp38-cp38-macosx_11_0_arm64.whl (168.4 kB view hashes)

Uploaded Apr 26, 2022 CPython 3.8 macOS 11.0+ ARM64

pylandau-2.2.1-cp38-cp38-macosx_10_9_x86_64.whl (169.4 kB view hashes)

Uploaded Apr 26, 2022 CPython 3.8 macOS 10.9+ x86-64

Hashes for pylandau-2.2.1.tar.gz

Hashes for pylandau-2.2.1.tar.gz
Algorithm	Hash digest
SHA256	`5dd1cb2c42fda284fd0c69b61abac6238e1379991ce306358131cf59e5623c57`
MD5	`2b04d2b13891fdd1f083ea696f0d149e`
BLAKE2b-256	`593e12593417ab98b8c5c13fe693fdff27bda0a5f05aab5ec85d434c09b315b1`

Hashes for pylandau-2.2.1-cp310-cp310-win_amd64.whl

Hashes for pylandau-2.2.1-cp310-cp310-win_amd64.whl
Algorithm	Hash digest
SHA256	`98ed78abfc15fb0fd6453ea6d4025c171d853821d7b87ea2681a663866a11def`
MD5	`48bf5aef89e99dfdef2cfe9ae1d97efc`
BLAKE2b-256	`ba6b8b625f884db27a64a82c541cda4ca94809af1d6fe2ed83d08f673866b437`

Hashes for pylandau-2.2.1-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Hashes for pylandau-2.2.1-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`ffb85cb71698812b87458de7011af2c069993c698cfc7eb05b043e31efd21c1b`
MD5	`e13c5fa04512078b34e04688684b502b`
BLAKE2b-256	`a351c0af36350ce899d8f2ac97e4977e6567b526cb94b885ee2d24ed03375680`

Hashes for pylandau-2.2.1-cp310-cp310-macosx_11_0_arm64.whl

Hashes for pylandau-2.2.1-cp310-cp310-macosx_11_0_arm64.whl
Algorithm	Hash digest
SHA256	`84aa66d21eb5662121d313359c968af9b4dfc04dd1c41e11b5161003e0cdd5cd`
MD5	`d3ae8eac6eb3b9e7373510436ac0fc5b`
BLAKE2b-256	`2eebc85a4f8a0b8a7e852236b93e3c806bb5dd566c38d349a6da15b7160aff34`

Hashes for pylandau-2.2.1-cp310-cp310-macosx_10_9_x86_64.whl

Hashes for pylandau-2.2.1-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`d44dc5f1d6a26e660f23fa66aad449b7fed2a8d1169a1304ef9d8e26084fe977`
MD5	`ab480643319d0cab56510df5da10cfb6`
BLAKE2b-256	`f0921520636bc3ebc95b15f1cd61f770bae006c072231dc15255e0656ccc58ab`

Hashes for pylandau-2.2.1-cp39-cp39-win_amd64.whl

Hashes for pylandau-2.2.1-cp39-cp39-win_amd64.whl
Algorithm	Hash digest
SHA256	`0c7e8d46065a5b4e40b13c024b7ea80008d19eb37207845ce73cdb09b55e7e1b`
MD5	`640a420663dc0be919c1c6b62c7aaf15`
BLAKE2b-256	`a014e753281535c8ab8f106c92bfe172a796be942e20414421d7a1831cb8dd52`

Hashes for pylandau-2.2.1-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Hashes for pylandau-2.2.1-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`27ebfba9f0f4a43b04cb3b701b84a0d63e99a6c84f6093b2ddacf9d0d2f9f984`
MD5	`1c4bd566240382c512218b1db3eff9e2`
BLAKE2b-256	`98f70a2694dbd5df056331a261aa1ab3253ad296683eb58ec27757e312cf2f26`

Hashes for pylandau-2.2.1-cp39-cp39-macosx_11_0_arm64.whl

Hashes for pylandau-2.2.1-cp39-cp39-macosx_11_0_arm64.whl
Algorithm	Hash digest
SHA256	`c15eed9fc911fe089cc308c8054522e6f348ea32b41a3565bf6e4697e801c073`
MD5	`b9292b5c238d562ab2569cc67fa945ed`
BLAKE2b-256	`22fc712d056d2442428e170c9d07005625b6e44439341580e694599d4ea36bee`

Hashes for pylandau-2.2.1-cp39-cp39-macosx_10_9_x86_64.whl

Hashes for pylandau-2.2.1-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`2f85dd4ed88bd97fa87312c071cbdefd652da2bd2176d6129d3a67f9c5ef2b4b`
MD5	`984a184fab099a54df723b2dc72672ee`
BLAKE2b-256	`f745b6aee38b51ee778a3926d9da929f9ee83fa7f11aca7a3151671797e8ebe8`

Hashes for pylandau-2.2.1-cp38-cp38-win_amd64.whl

Hashes for pylandau-2.2.1-cp38-cp38-win_amd64.whl
Algorithm	Hash digest
SHA256	`a945777ebc3baff8c941d7b60d0f8a849842efef5019f1a1f25515040e18d667`
MD5	`52f8d77beb4a1b37329e68ec5fa7e484`
BLAKE2b-256	`c9d3515ad7ffc4437eec38be8cacd9cf2b67d958a1a5f4ed236db2e3e8f5c124`

Hashes for pylandau-2.2.1-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Hashes for pylandau-2.2.1-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`e0aa971189519d963906ddd4116a5b612bde43d0d245ad99fb454186e2ca4b39`
MD5	`d891990b945c1218b7a70ddacec4d83b`
BLAKE2b-256	`140d22bd42b439a6ae1a28fa69e8308cbc66aa2073e02c75c6c9cfff0966d60d`

Hashes for pylandau-2.2.1-cp38-cp38-macosx_11_0_arm64.whl

Hashes for pylandau-2.2.1-cp38-cp38-macosx_11_0_arm64.whl
Algorithm	Hash digest
SHA256	`aed88be162cc2454e62bf9582aa7b0b1e7ce7d945b072418a2b861681d1b29ad`
MD5	`7c7e8539647dd663cc0c2a4ea71f72e0`
BLAKE2b-256	`508f7d64e1bfcb0f5eb6ba6c9af7c69c46596dbd77659b0ee5b2063430ac51f5`

Hashes for pylandau-2.2.1-cp38-cp38-macosx_10_9_x86_64.whl

Hashes for pylandau-2.2.1-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`ee2e27a293dd3ccce41084d80d19143383f9b05af66b283bd59fec21efe8b47b`
MD5	`620f82496d8981ea03598cad078a35e5`
BLAKE2b-256	`3ff41a90d48449ade8ca5e79d375d4393b8e9f251fc62afc5921d6e78867246f`