# pyTRT
[](https://badge.fury.io/py/pyTRT)
[](https://github.com/wouterpeere/pyTRT/actions/workflows/test.yml)
[](https://codecov.io/gh/wouterpeere/pyTRT)
[](https://pepy.tech/project/pyTRT)
[](https://pepy.tech/project/pyTRT)
[](https://pyTRT.readthedocs.io/en/latest/)
pyTRT is a python package with different methods for the interpretation of thermal response tests. The goal of this
package is to
bundle all available methodologies for TRT analysis so the user can easily compare one to another.
Currently, the following methods are implemented:
- Traditional ILS, based on the work of (Gehlin, S., 2002)
## Requirements
This code is tested with Python 3.10, 3.11, 3.12 and 3.13 and requires the following libraries (the versions mentioned
are the ones with which the code is tested)
- numpy >= 1.26.4
- pandas >= 1.4.3
For the tests
- pytest >= 7.1.2
## Getting started
In order to use `pyTrt`, one should first import the TRT measurement data. After that, any method inside `pyTRT` can be
used for the analysis.
```python
from pyTRT import TRTData, ILS
# import load
linz = TRTData('examples/data/Linz.csv', 't [s]', 'Tf [degC]', col_power='P [W]',
decimal=',', undisturbed_ground=11.7)
# analyse the measurement data
result = ILS(linz, 150, 0.133 / 2, 2.3e6)
print(f'Thermal conductivity {result.thermal_conductivity}')
print(f'Effective borehole thermal resistance {result.borehole_resistance}')
````
## Citation
If you use this python package, please cite it using the citation below.
Next to that, please cite the work of the author from which you used the methodology.
**Traditional ILS**
Gehlin, S., 2002. Thermal Response Test. Method, Development and Evaluation (Ph. D. dissertation). Department of
Environmental Engineering, University of Lulea, Sweden.
## Collaborate
There are many different methods for the analysis of TRT measurement data. If you have developed a method of your own
and you want to include it in this package, you are encouraged to share this. Please follow the [contribution workflow](CONTRIBUTING.md).
BSD 3-Clause License
Copyright (c) 2025, Wouter Peere
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
1. Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
3. Neither the name of the copyright holder nor the names of its
contributors may be used to endorse or promote products derived from
this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
# pyTRT's Changelog and future developments
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/).
## [0.0.1] - 2025-07-18
### Added
- First release of `pyTRT` with ILS method.
[0.0.1]: https://github.com/wouterpeere/pyTRT/releases/tag/v1.0.1
Raw data
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"description": "# pyTRT\n\n[](https://badge.fury.io/py/pyTRT)\n[](https://github.com/wouterpeere/pyTRT/actions/workflows/test.yml)\n[](https://codecov.io/gh/wouterpeere/pyTRT)\n[](https://pepy.tech/project/pyTRT)\n[](https://pepy.tech/project/pyTRT)\n[](https://pyTRT.readthedocs.io/en/latest/)\n\npyTRT is a python package with different methods for the interpretation of thermal response tests. The goal of this\npackage is to\nbundle all available methodologies for TRT analysis so the user can easily compare one to another.\n\nCurrently, the following methods are implemented:\n\n- Traditional ILS, based on the work of (Gehlin, S., 2002)\n\n## Requirements\n\nThis code is tested with Python 3.10, 3.11, 3.12 and 3.13 and requires the following libraries (the versions mentioned\nare the ones with which the code is tested)\n\n- numpy >= 1.26.4\n- pandas >= 1.4.3\n\nFor the tests\n\n- pytest >= 7.1.2\n\n## Getting started\n\nIn order to use `pyTrt`, one should first import the TRT measurement data. After that, any method inside `pyTRT` can be\nused for the analysis.\n\n```python\nfrom pyTRT import TRTData, ILS\n\n# import load\nlinz = TRTData('examples/data/Linz.csv', 't [s]', 'Tf [degC]', col_power='P [W]',\n decimal=',', undisturbed_ground=11.7)\n\n# analyse the measurement data\nresult = ILS(linz, 150, 0.133 / 2, 2.3e6)\n\nprint(f'Thermal conductivity {result.thermal_conductivity}')\nprint(f'Effective borehole thermal resistance {result.borehole_resistance}')\n````\n\n## Citation\n\nIf you use this python package, please cite it using the citation below.\n\nNext to that, please cite the work of the author from which you used the methodology.\n\n**Traditional ILS**\n\nGehlin, S., 2002. Thermal Response Test. Method, Development and Evaluation (Ph. D. dissertation). Department of\nEnvironmental Engineering, University of Lulea, Sweden.\n\n## Collaborate\n\nThere are many different methods for the analysis of TRT measurement data. If you have developed a method of your own\nand you want to include it in this package, you are encouraged to share this. Please follow the [contribution workflow](CONTRIBUTING.md).\n\nBSD 3-Clause License\n\nCopyright (c) 2025, Wouter Peere\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are met:\n\n1. Redistributions of source code must retain the above copyright notice, this\n list of conditions and the following disclaimer.\n\n2. Redistributions in binary form must reproduce the above copyright notice,\n this list of conditions and the following disclaimer in the documentation\n and/or other materials provided with the distribution.\n\n3. Neither the name of the copyright holder nor the names of its\n contributors may be used to endorse or promote products derived from\n this software without specific prior written permission.\n\nTHIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\"\nAND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\nIMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE\nDISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE\nFOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL\nDAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR\nSERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER\nCAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,\nOR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\n\n# pyTRT's Changelog and future developments\n\nThe format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/).\n\n## [0.0.1] - 2025-07-18\n\n### Added\n\n- First release of `pyTRT` with ILS method.\n\n[0.0.1]: https://github.com/wouterpeere/pyTRT/releases/tag/v1.0.1\n",
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