https://github.com/copasi/python-petab-importer
PEtab --> COPASI importer
Science Score: 36.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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✓Committers with academic emails
1 of 2 committers (50.0%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (15.2%) to scientific vocabulary
Keywords
Repository
PEtab --> COPASI importer
Basic Info
- Host: GitHub
- Owner: copasi
- License: artistic-2.0
- Language: Python
- Default Branch: master
- Size: 4.35 MB
Statistics
- Stars: 3
- Watchers: 6
- Forks: 1
- Open Issues: 1
- Releases: 10
Topics
Metadata Files
README.md
PEtab Importer
This project holds the code to import the parameter estimation benchmark problems into COPASI. The test cases it ought to be able to deal with are from this project:
These models are encoded in the PEtab format with this documentation. The format specifies:
- an SBML file with the model definition
- a measurement file with the experimental data
- a condition file that specifies different initial conditions
So this converter 1. reads the SBML file and converts it to the COPASI format, then converts the experimental data so we can use it in COPASI, and provides the mapping to the observables. Once the converter is done, and you run the parameter estimation you will get the current solution displayed.
The benchmarks are also added as submodule to this repo. So if you do want to use those, be sure to check it out as well, running:
git submodule init
git submodule update
Run PEtab the easy way
This project is used direclty from basico, where we directly implement a PetabSimulator. So if you are interested in just running PEtab problems with COPASI, I recommend to
pip install copasi-basico[petab]
and then follow the basico petab example. Otherwise, this project can of course be used on its own as described below.
Setup
Create a new virtual environment, and then run pip install -r requirements.txt. This will install all the dependencies, these are:
- numpy
- pandas
- python-copasi
- python-libsbml
- PyQt5
- pyyaml
You can also directly install the importer in one line directly from git (including the dependencies) using:
pip install git+https://github.com/copasi/python-petab-importer.git
and you can run directly:
copasi_petab_import [<petab_dir>] <model_name> <output_dir>
Usage
Once installed, you can use the graphical user interface, specify the benchmark directory, select the test and the model, and you ought to be able to open the generated COPASI file directly. You do this by running:
python PEtab.py

Alternatively you cold convert the benchmark models directly by invoking the converter:
python convert_petab.py <benchmark_dir> <model_name> <output_dir>
where:
benchmark_diris a directory to a pe tab dir, like./hackathon_contributions_new_data_format/Becker_Science2010.model_nameis one of the model names in the directory likeBecker_Science2010__BaF3_Exp. The program assumes, that the measurement data and condition data files are in the directory containing the model name (otherwise any measurement / condition file will be greedily taken)output_diris the directory into which the output will be written. For example '/out'. In this case at the end of the run the filesBecker_Science2010__BaF3_Exp.cpsandBecker_Science2010__BaF3_Exp.txtwould be generated.
Also added a bulk converter:
python convert_all_petab.py <base_dir> <output_dir>
where:
base_diris the pe tab root dir, as in./hackathon_contributions_new_data_format/output_dirthe directory in which the files will be saved in
License
Just as COPASI, the packages available on this page are provided under the Artistic License 2.0, which is an OSI approved license. This license allows non-commercial and commercial use free of charge.
Owner
- Name: COPASI
- Login: copasi
- Kind: organization
- Website: http://www.copasi.org
- Repositories: 22
- Profile: https://github.com/copasi
GitHub Events
Total
- Create event: 2
- Release event: 2
- Issues event: 2
- Delete event: 1
- Issue comment event: 2
- Push event: 6
- Fork event: 1
Last Year
- Create event: 2
- Release event: 2
- Issues event: 2
- Delete event: 1
- Issue comment event: 2
- Push event: 6
- Fork event: 1
Committers
Last synced: almost 3 years ago
All Time
- Total Commits: 81
- Total Committers: 2
- Avg Commits per committer: 40.5
- Development Distribution Score (DDS): 0.012
Top Committers
| Name | Commits | |
|---|---|---|
| Frank T. Bergmann | f****n@c****u | 80 |
| Stefan Hoops | s****s@c****g | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 7 months ago
All Time
- Total issues: 3
- Total pull requests: 0
- Average time to close issues: 4 months
- Average time to close pull requests: N/A
- Total issue authors: 2
- Total pull request authors: 0
- Average comments per issue: 3.67
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 1
- Pull requests: 0
- Average time to close issues: about 4 hours
- Average time to close pull requests: N/A
- Issue authors: 1
- Pull request authors: 0
- Average comments per issue: 5.0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- dweindl (2)
- pmendes (1)
Pull Request Authors
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
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Total downloads:
- pypi 175 last-month
- Total dependent packages: 1
- Total dependent repositories: 1
- Total versions: 10
- Total maintainers: 1
pypi.org: copasi-petab-importer
COPASI PEtab Importer
- Homepage: https://github.com/copasi/python-petab-importer
- Documentation: https://copasi-petab-importer.readthedocs.io/
- License: Artistic-2.0
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Latest release: 1.0.9
published 7 months ago
Rankings
Maintainers (1)
Dependencies
- PyQt5 *
- numpy *
- pandas *
- python-copasi *
- python-libsbml *
- pyyaml *
- numpy *
- pandas *
- python-copasi *
- python-libsbml *
- pyyaml *