A Python package to load raw DTS files, perform a calibration, and plot the result
A Python package to load Distributed Temperature Sensing files, perform a calibration, and plot the result. A detailed description of the calibration procedure can be found at https://doi.org/10.3390/s20082235 .
- Free software: BSD 3-Clause License
pip install dtscalibration
Or the development version directly from GitHub
pip install https://github.com/dtscalibration/python-dts-calibration/zipball/master --upgrade
- Advanced calibration routine
- Both single- and double-ended setups
- Confidence intervals of calibrated temperature
- Time integration of calibration parameters
- Weighted least-squares calibration
- Fixing parameters to a previously determined value
- (Asymmetric) step loss correction
- Matching temperature sections
- Dynamic reference section definition
- Tools for merging and aligning double-ended setups
- Data formats of most manufacturers are supported
Devices currently supported
- Silixa Ltd.: Ultima & XT-DTS .xml files (up to version 7.0)
- Sensornet Ltd.: Oryx & Halo .ddf files
- AP Sensing: CP320 .xml files (single ended only)
- SensorTran: SensorTran 5100 .dat binary files (single ended only)
Learn by examples
Interactively run the example notebooks online by clicking here.
How to cite
The following article explains and discusses the calibration procedure:
des Tombe, B., Schilperoort, B., & Bakker, M. (2020). Estimation of Temperature and Associated Uncertainty from Fiber-Optic Raman-Spectrum Distributed Temperature Sensing. Sensors, 20(8), 2235. https://doi.org/10.3390/s20082235
Cite the specific implementation / repository via Zenodo:
Check the version of dtscalibration that is used in your Python console with:
>>> import dtscalibration >>> dtscalibration.__version__ '1.0.0'
Go to Zenodo and follow the link to the version of interest.
The citation is found on the bottom right of the page.
- Same as v1.0.1
- st_var can now be array-like. The array-like can vary in x or time, or both.
- When converting from a xr.Dataset to a DataStore object, the attributes arenow transfered over
- Added ‘verbose’ kwarg to shift_double_ended utility function to silence theconsole output
- If the ‘_sections’ attribute is missing from a DataStore object it is automagically re-added.
- Assert that stokes variances are passed when running a double-ended WLS calibration
- Added check for NaN/inf values in wls_sparse solver to avoid unclear error messages
- Before calibration, the values of the used reference temperatures are checked if they are valid (float dtype, no NaN/inf values, correct time dimension)
- European Geosciences Union conference 2020 presentation added
- Updated documentation with content article
- Use YAPF formatting of the Python files
- Travis-CI.org integration in GitHub restored.
- First major release
- Reduced flexibility in defining names under which the Stokes are stored
- 4 Averaging functions implemented, with uncertainty estimation. Seenotebook 16 for the various options
- Notebook about transient attenuation caused by for example connectors
- Bug in singel ended transient attenuation
- Check for consistent number of measurement locations across read files
- Reduced flexibility in defining Stokes labels
- Same as 0.9.2
- Increased precision of least squares solver, as this was limiting theprecision of the parameter estimation
- The variance of the noise in the Stokes can change linear with the intensity
- Improved residuals plot function
- Reduced the number of equations for double ended calibration
- Support for transient attenuation due to connectors along fibers
- Matching sections
- Valentine edition
- Added example for fixing parameters
- Bug fixed in routine for reading Sensornet files (Bor van der Scheer)
- Official support for Python 3.8
- When the datastore is printed to the screen, the mean and std of thereference temperature is plotted
- Integrated differential attenuation is reformulated. Starts integrating atthe first reference section location.
- Estimation of the variance of the Stokes that is linear dependent on theintensity (Poisson)
- Removed __slots__ attribute
- Update automated zenodo reference requires to draft a new release
- Solved xlim in subplots of plot_residuals_reference_sections funciton
- Solved YAML deprecation related problems
- Introduced new approach for double ended calibration, with a different Cfor the forward and backward channel
- First code added for time variant asymmetric attenuation, such as connectors.
- First code added for matching sections
- Set alpha and or gamma to known value, with corresponding variance.
- Bug in computation of the weights for single and double-ended calibration
- Added notebook about merging two single ended measurements
- Added example notebook on how to create a custom datastore
- Added notebook examples for loading in data from the different manufa..
- Loading AP Sensing files and tests
- Loading Sensortran files
- 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
- Use twine to check if the compiled package meets all the requirements of Pypi
- Use twine to check if the compiled package meets all the requirements of Pypi
- 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
- More flexibility in defining the time dimension
- Cleanup of some plotting functions
- 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.
- 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
- 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
- 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
- No changes
- 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
- 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
- Single ended calibration
- Confidence intervals for single ended calibration
- Example notebooks have figures embedded
- Several bugs squashed
- Reorganized DataStore functions
- Double ended calibration
- Confidence intervals for double ended calibration
- First release on PyPI.
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