WARNING: This package is under development. The public API should not be considered stable.
- What is MetPyRad?
- Main features of MetPyRad
- How to install MetPyRad?
- Quick user guide
- Future developments
- How to get support?
- Documentation
- Contributors
- License
- Contributing to MetPyRad
MetPyRad is a Python package that provides a collection of tools for radionuclide metrology. It is an open source, GPLv3-licensed library for the Python programming language. It is compatible with Python 3. MetPyRad provides tools for processing measurements for a given radionuclide using a Hidex 300 SL automatic liquid scintillation counter. It is designed to facilitate the handling, analysis, and summarization of measurement data.
MetPyRad provides five main features for processing measurements for a given radionuclide using a Hidex TDCR system:
- Data Parsing and Processing: It includes tools to parse measurement data from CSV files, process different types of measurements (background, sample, net), and compile the results into comprehensive data structures.
- Measurement Summarization: It includes tools to generate detailed summaries of the measurements, including statistical analysis and cycle information.
- Visualization: It includes plotting tools to visualize various quantities of the measurements, such as count rates, dead times, and uncertainties, making it easier to interpret the data.
- Exporting Results: It includes tools to export the processed data and visualizations to CSV and PNG files, for further analysis or reporting.
- Comprehensive Analysis: It supports end-to-end analysis workflows, from parsing raw data to generating summaries and visualizations, and saving the results.
MetPyRad can be installed from the Python Package Index (PyPI) by running the following command from a terminal:
pip install metpyradConsider that we made a measurement of the radionuclide Lu-177 starting on November 2023 using a Hidex 300 SL automatic liquid scintillation counter. The measurement consists on a series cicles of measurements, each one with a number of repetitions. Each repetition consists on measuring the background and the sample of Lu-177 consecutively in periods of 100 seconds. For each cicle of measurements, Hidex TDCR system provides a CSV file with the readings.
We want to process the reading files provided by the Hidex 300 SL automatic liquid scintillation counter, and get some quantities of interest that characterizes the activity of the radionuclide in terms of time. The tool that MetPyRad provides to do this is the HidexTDCR class. It allows performing a comprehensive analysis of the measurements, including parsing the files, processing, summarizing and visualizing the measurements, and exporting the results.
Here is a code snippet to process the readings of a set in CSV files the Hidex 300 SL stored in the folder input_file,
exporting the different types of measurements (background, sample and net) to CSV files and
plots of these measurements to PNG files.
from metpyrad import Hidex300
processor = Hidex300(radionuclide='Lu-177', year=2023, month=11)
processor.analyze_readings(input_folder='input_files', time_unit='s', save=True, output_folder='output')
print(processor.sample)Output:
Processing readings from input_files.
Found 2 CSV files in folder input_files
Measurements summary:
Measurements of Lu-177 on November 2023
Summary
Number of cycles: 2
Repetitions per cycle: 2
Time per repetition: 100 s
Total number of measurements: 4
Total measurement time: 400 s
Cycles summary
Cycle Repetitions Real time (s) Date
0 1 2 100 2023-11-30 08:44:20
1 2 2 100 2023-12-01 12:46:16
Saving measurement files to folder output/Lu-177_2023_11.
Saving CSV files
Readings measurements CSV saved to "output/Lu-177_2023_11" folder.
Background measurements CSV saved to "output/Lu-177_2023_11" folder.
Sample measurements CSV saved to "output/Lu-177_2023_11" folder.
Net measurements CSV saved to "output/Lu-177_2023_11" folder.
All measurements CSV saved to "output/Lu-177_2023_11" folder.
Summary saved to output/Lu-177_2023_11/summary.txt
Saving figures
Background measurements PNG saved to "output/Lu-177_2023_11" folder.
Sample measurements PNG saved to "output/Lu-177_2023_11" folder.
Net measurements PNG saved to "output/Lu-177_2023_11" folder.
Example of exported table for the sample measurements:
Sample measurements
Cycle Sample Repetitions Count rate (cpm) Counts (reading) Dead time Real time (s) End time Live time (s) Elapsed time Elapsed time (s) Counts Counts uncertainty Counts uncertainty (%)
1 2 1 252623.23 374237 1.125 100 2023-11-30 08:47:44 88.888889 0 days 00:00:00 0.0 374256.637037 611.765181 0.163461
1 2 2 251953.09 373593 1.124 100 2023-11-30 08:54:28 88.967972 0 days 00:06:44 404.0 373595.922301 611.224936 0.163606
2 2 1 223744.10 335987 1.110 100 2023-12-01 12:49:40 90.090090 1 days 04:01:56 100916.0 335952.102102 579.613753 0.172529
2 2 2 223689.40 335843 1.110 100 2023-12-01 12:56:24 90.090090 1 days 04:08:40 101320.0 335869.969970 579.542897 0.172550
Example of exported plot for the sample measurements:
- Add support to compute the half-live of the radionuclide from time measurements of the activity.
- Add support to process output files for other measuring instruments.
If you need support, please check the MetPyRad documentation at GitHub (README).
If you need further support, please send an e-mail to Xandra Campo.
The official documentation of MetPyRad is hosted on GitHub Pages.
MetPyRad is developed and maintained by Xandra Campo, with the support of Nuria Navarro and Virginia Peyres. It is one of the projects of the Ionizing Radiation Metrology Laboratory (LMRI), which is the Spanish National Metrology Institute for ionizing radiation.
MetPyRad is distributed under the GNU GPLv3 License.
All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome. Please check the MetPyRad issues page if you want to contribute.