dtscalibration 0.5.2

A Python package to load raw DTS files, perform a calibration, and plot the result

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

https://python-dts-calibration.readthedocs.io/

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.