Skip to main content

Python library for analyzing and visualizing SSLS SUV Beamline data.

Project description

SUV Tools

Python tests status Deploy gh-pages status Deploy gh-pages status Latest Release

Visit the project homepage https://pranabdas.github.io/suvtools/

Quick start

Install latest stable release:

pip3 install --upgrade suvtools

Import suvtools into your project:

import suvtools as suv

Modules:

  • suv.load("datafile.txt", scan=None): It will return a two dimensional array with columns for various parameters. If the second argument, i.e., the scan number is not specified, the code will read the last scan from the file.

  • suv.fit_gauss(x, y, a=None, x0=None, sigma=None, xmin=None, xmax=None, num=1000): returns x, Gaussian fitted y values, and prints out relevant parameters. xmin and xmax determines the range to fit. If xmin and xmax are not provided, whole range is used. num determines the number of points returned in x_fit and y_fit.

  • suv.fit_lorentz(x, y, a=None, x0=None, gamma=None, xmin=None, xmax=None, num=1000): returns x, Lorentzian fitted y values, and prints out relevant parameters. xmin and xmax determines the range to fit. If xmin and xmax are not provided, whole range is used. num determines the number of points returned in x_fit and y_fit.

  • suv.save_csv("datafile.txt", csvname=None, scan=None): saves scan to a csv file. The file will be saved in the save directory as datafile with name datafile.csv unless csvname is specified. Like the load module, if the scan number is not specified, it will read the last scan from the file.

  • suv.norm_bg(energy, intensity, x1, x2, x_norm_loc=None): Removes linear background, and normalizes the data. x1, x2 are energy values that determines the slope of the background. By default the normalization done at the tail point of the spectra. It can be changed to other point, enter the corresponding energy value. The intention is to normalize at an energy value away from the peaks/features of interest.

  • suv.lock_peak(data, refdata, x1=None, x2=None, E_col=0, I_col=9, I0_col=4): Locks peak position with respect to the reference data. It locks the maximum of intensity to the same energy; the range of peak search can be specified by input x1 and x2. If no bounds are given, it will find the maximum in the whole data range.

  • suv.calc_area(y, x, x_start=None, x_end=None): Calculates area under the curve for given x and y values. x_start and x_end can be specified to set the limit of integration region, if not provided whole range is integrated.

See the notebook and documentation for example usage.

Documentation development

# install npm packages
npm install

# serve locally
npm start

# build
npm run build

Python tests

python3 -m unittest discover tests

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

suvtools-1.0.2.tar.gz (6.7 kB view details)

Uploaded Source

Built Distribution

suvtools-1.0.2-py3-none-any.whl (8.8 kB view details)

Uploaded Python 3

File details

Details for the file suvtools-1.0.2.tar.gz.

File metadata

  • Download URL: suvtools-1.0.2.tar.gz
  • Upload date:
  • Size: 6.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for suvtools-1.0.2.tar.gz
Algorithm Hash digest
SHA256 3acd38748371a8ba9d96ad34411815cda2d64ca01191cf7438065a57db2ea816
MD5 95e3a0fc9dd5491c936300b4ee0fd71e
BLAKE2b-256 b8b3c250b8487d8ab674a905a411c925ed43a4f72dad15a6be7385acb77fa653

See more details on using hashes here.

File details

Details for the file suvtools-1.0.2-py3-none-any.whl.

File metadata

  • Download URL: suvtools-1.0.2-py3-none-any.whl
  • Upload date:
  • Size: 8.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for suvtools-1.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 713c48bd20e9f0818522b22d229fca6d446e38823580766accdbdaacee36de58
MD5 c4102cffe7a14aa83978c0ce01ffa54f
BLAKE2b-256 b10c5dd778d351172626472865767eb23c8a640ef80b416bedae8f8adfa86fdc

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