Skip to main content

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

Or the development version directly from GitHub

pip install https://github.com/dtscalibration/python-dts-calibration/zipball/master --upgrade

Learn by examples

Interactively run the example notebooks online by clicking the launch-binder button.

Documentation

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

Changelog

0.7.0 (2019-11-07)

  • Ensure order of dimension upon initialization of DataStore. Resamplingwould lead to issues

  • Bug in section definition (reported by Robert Law)

  • Rewritten calibration solvers to align with article of this package

  • Removed old calibration solvers

  • New possibilities of saving and loading large DataStores saved to multiplenetCDF files

0.6.7 (2019-11-01)

  • Use twine to check if the compiled package meets all the requirements of Pypi

0.6.6 (2019-11-01)

  • Use twine to check if the compiled package meets all the requirements of Pypi

0.6.5 (2019-11-01)

  • Major bug fix version.

  • More flexibility in defining the time and space dimensions

  • Fixed unsave yaml loading

  • Added support for Silixa 7 files

  • Start using __slots__ as it is something new

  • xarray doesn’t have the attribute ._initialized anymore. Rewritten teststo make more sense by checking the sum of the Stokes instead.

  • Support for double ended Sensornet files and tests

  • Bug fixing

0.6.4 (2019-04-09)

  • More flexibility in defining the time dimension

  • Cleanup of some plotting functions

0.6.3 (2019-04-03)

  • Added reading support for zipped silixa files. Still rarely fails due to upstream bug.

  • pretty __repr__

  • Reworked double ended calibration procedure. Integrated differential attenuation outside of reference sections is now calculated seperately.

  • New approach for estimation of Stokes variance. Not restricted to a decaying exponential

  • Bug in averaging TMPF and TMPB to TMPW

  • Modified residuals plot, especially useful for long fibers (Great work Bart!)

  • Example notebooks updatred accordingly

  • Bug in to_netcdf when passing encodings

  • Better support for sections that are not related to a timeseries.

0.6.2 (2019-02-26)

  • Double-ended weighted calibration procedure is rewritten so that the integrated differential attenuation outside of the reference sections is calculated seperately. Better memory usage and faster

  • Other calibration routines cleaned up

  • Official support for Python 3.7

  • Coverage figures are now trustworthy

  • String representation improved

  • Include test for aligning double ended measurements

  • Example for aligning double ended measurements

0.6.1 (2019-01-04)

  • Many examples were shown in the documentation

  • Fixed verbose settings of solvers

  • Revised example notebooks

  • Moved to 80 characters per line (PEP)

  • More Python formatting using YAPF

  • Use example of plot_residuals_reference_sections function in Stokes variance example notebook

  • Support Python 3.7

0.6.0 (2018-12-08)

  • Reworked the double-ended calibration routine and the routine for confidence intervals. The integrated differential attenuation is not zero at x=0 anymore.

  • Verbose commands carpentry

  • Bug fixed that would make the read_silixa routine crash if there are copies of the same file in the same folder

  • Routine to read sensornet files. Only single-ended configurations supported for now. Anyone has double-ended measurements?

  • Lazy calculation of the confidence intervals

  • Bug solved. The x-coordinates where not calculated correctly. The bug only appeared for measurements along long cables.

  • Example notebook of importing a timeseries. For example, importing measurments from an external temperature sensor for calibration.

  • Updated documentation

0.5.3 (2018-10-26)

  • No changes

0.5.2 (2018-10-26)

  • New resample_datastore method (see basic usage notebook)

  • New notebook on basic usage of DataStore

  • Support for Silixa v4 (Windows xp based system) and Silixa v6 (Windows 7) measurement files

  • The representation string now includes the sections

  • Reorganized the IO related files

  • 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)

  • Rewritten the routine that reads Silixa measurement files

  • 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


Download files

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

Source Distribution

dtscalibration-0.7.1.tar.gz (5.7 MB view hashes)

Uploaded Source

Built Distribution

dtscalibration-0.7.1-py2.py3-none-any.whl (47.4 kB view hashes)

Uploaded Python 2 Python 3

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