Metadata-Version: 2.1
Name: dtscalibration
Version: 0.6.3
Summary: A Python package to load raw DTS files, perform a calibration, and plot the result
Home-page: https://github.com/bdestombe/python-dts-calibration
Author: Bas des Tombe
Author-email: bdestombe@gmail.com
License: BSD 3-Clause License
Keywords: DTS,Calibration
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: Unix
Classifier: Operating System :: POSIX
Classifier: Operating System :: Microsoft :: Windows
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Utilities
Requires-Python: >= 3.6
Requires-Dist: numpy
Requires-Dist: xarray
Requires-Dist: pyyaml
Requires-Dist: xmltodict
Requires-Dist: scipy
Requires-Dist: patsy
Requires-Dist: statsmodels
Requires-Dist: nbsphinx
Requires-Dist: dask
Requires-Dist: toolz
Requires-Dist: matplotlib
Requires-Dist: netCDF4
Requires-Dist: pandas (>=0.24.1)

========
Overview
========



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
=========
0.6.3 (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.


