Skip to main content

LLWP is a fast, efficient and easy solution for exploring and assigning spectra - relying on Loomis-Wood plots.

Project description

LLWP - Luis' Loomis-Wood Program

LLWP allows you to efficiently and confidently assign (typically rotational or rovibrational) spectra by relying on Loomis-Wood plots.

A quickstart guide is given down below. For more information see LLWP's website.

If you want to acknowledge LLWP, please cite the paper LLWP - A new Loomis-Wood software at the example of Acetone-13C1.

Feel free to contact me in case of any problems or for feature requests.

Quickstart Guide

The preferred way to install LLWP is via Python's package manager pip. Run the following command in a terminal to install LLWP:

pip install llwp

After installing LLWP via pip you can run it from any terminal by simply running

llwp

To see and assign your first series

  1. open your spectrum and prediction files via drag and drop or Files > Add Files
  2. specify the correct reference series in the Reference Series window
  3. choose the fitfunction under Fit > Choose Fit Function
  4. select the area around the experimental peak with the mouse to fit the data

ASAP Mode

To start the ASAP mode of LLWP run

asap

To see and assign your first cross-correlation peaks

  1. open your spectrum, *.egy, and *.cat file via drag and drop or Files > Add Files
  2. specify the correct energy levels in the ASAP Settings window
  3. specify the correct unit conversion factor for the *.cat file in the Units Cat File field (e.g. 3.335641e-05 for *.cat file in MHz and *.egy file in wavenumbers)
  4. press Calculate Cross Correlation
  5. choose the fitfunction under Fit > Choose Fit Function
  6. select the area around the experimental peak with the mouse to fit the data

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

llwp-2.0.25.tar.gz (79.0 kB view details)

Uploaded Source

Built Distribution

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

llwp-2.0.25-py3-none-any.whl (78.9 kB view details)

Uploaded Python 3

File details

Details for the file llwp-2.0.25.tar.gz.

File metadata

  • Download URL: llwp-2.0.25.tar.gz
  • Upload date:
  • Size: 79.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.1

File hashes

Hashes for llwp-2.0.25.tar.gz
Algorithm Hash digest
SHA256 fbb77b8a83051179acd04350dc49930a8f9d5193df0b85c3e7740f6388f1bf51
MD5 6297dfa8aac367afce709f3a3116d3a1
BLAKE2b-256 f282820747d2d297afd1a324cfc0b69197e38b49a45974eae37d99f8f19b0d86

See more details on using hashes here.

File details

Details for the file llwp-2.0.25-py3-none-any.whl.

File metadata

  • Download URL: llwp-2.0.25-py3-none-any.whl
  • Upload date:
  • Size: 78.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.1

File hashes

Hashes for llwp-2.0.25-py3-none-any.whl
Algorithm Hash digest
SHA256 c085a5c9395941d8d268f170f3b90f9b81338b6251955503213eaa2af21814bd
MD5 5c072a2c9f804f003d7b1a659e82e7b7
BLAKE2b-256 ba983010c8e12f62d41097cbe18517d7ebfb747fe7908a0ff4261ec52f107e47

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