A Python package to load raw DTS files, perform a calibration, and plot the result
Project description
A Python package to load raw DTS files, perform a calibration, and plot the result
Free software: BSD 3-Clause License
Installation
pip install dtscalibration
Learn by examples
Interactively run the example notebooks online by clicking the launch-binder button.
Documentation
Development
To run the all tests run:
tox
To bump version and docs:
git status # to make sure no unversioned modifications are in the repository
tox # Performes tests and creates documentation and runs notebooks
git status # Only notebook related files should be shown
git add --all # Add all notebook related files to local version
git commit -m "Updated notebook examples to reflect recent changes"
# update CHANGELOG.rst with the recent commits
# update AUTHORS.rst
bumpversion patch # (major, minor, patch)
git push
rm -rf build # Clean local folders (not synced) used for pip wheel
rm -rf src/*.egg-info
rm -rf dist/*
python setup.py clean --all sdist bdist_wheel
twine upload --repository-url https://upload.pypi.org/legacy/ dist/dtscalibration*
On GitHub draft a new release
# GitHub > Code > Releases > Draft a new release
# Tag: v1.2.3
# Title: v1.2.3
# Describtion: Copy-paste the new part of CHANGELOG.rst
Changelog
Master
CI: Add appveyor to continuesly test on Windows platform
Auto load Silixa files to memory option, if size is small
0.5.1 (2018-10-19)
dts-calibration is now citable
Refractored the MC confidence interval routine
MC confidence interval routine speed up, with full dask support
Link to mybinder.org to try the example notebooks online
Added a few missing dependencies
The routine to read the Silixa files is completely refractored. Faster, smarter. Supports both the path to a directory and a list of file paths.
Changed imports from dtscalibration to be relative
0.4.0 (2018-09-06)
Single ended calibration
Confidence intervals for single ended calibration
Example notebooks have figures embedded
Several bugs squashed
Reorganized DataStore functions
0.2.0 (2018-08-16)
Double ended calibration
Confidence intervals for double ended calibration
0.1.0 (2018-08-01)
First release on PyPI.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for dtscalibration-0.5.2-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | fad29b7eb7f94d1a2e60142cc2839e9f9f4a70d1682b5f6a3e29e10ea07e700a |
|
MD5 | 39e10a04abc9550e297a69756f80c890 |
|
BLAKE2b-256 | 0f5965d3f2716707306d562d8ff1bc426bf03ee3e96e532e60ee663dbbf11b07 |