Simplified COPASI interface for python
Project description
BasiCO
This project hosts a simplified python interface to COPASI. While all functionality from COPASI is exposed via automatically generated SWIG wrappers, this package aims to add a layer on top of that, to hide most of the complexity away when calling COPASI functions.
Installation
The package works with python 3.7+, provided the following packages are installed:
- python-copasi
- pandas
- numpy
- matplotlib
- PyYAML
that are freely available on pypi, they will be automatically installed when installing via setup.py.
Once done, just have the basico directory
in the PYTHONPATH or sys.path.
Or you could directly install everything you need right from pypi
pip install copasi-basico
from this git repo:
pip install git+https://github.com/copasi/basico.git
Usage
The following modules are available:
model_io: functionality, for creating / loading / saving models.model_info: functionality to getting / setting model elements from pandas dataframestask_timecourse: a wrapper for running time course simulationstask_parameter_estimation: a wrapper for parameter estimationtask_optimization: a wrapper for computing optimizations with arbitrary objective functionstask_steadystate: a wrapper for computing steady statestask_scan: a wrapper for parameter scans / repeatstask_sensitivities: a wrapper for computing sensitivitiescompartment_array_tools: utility for plotting and the like
Documentation is continually updated at: https://basico.readthedocs.org/.
Please use the issue tracker for bug reports and feature requests.
Run the tests
basico comes with a number of unit tests based on pytest. To run them, change to the root directory of this project and run:
python3 -m pytest
that will ensure that basico is in the python path, and the test run as expected. Some
tests require more data, that is not included in the repository, such as tests for PEtab
and petab select, for those, specify the environment variables to the directories where
the files are for example:
PETAB_BENCHMARK_MODELS=/path/to/petab/benchmark/models
PETAB_SELECT_MODELS=/path/to/petab/select/models
for example:
PETAB_BENCHMARK_MODELS=../Benchmark-Models-PEtab/Benchmark-Models PETAB_SELECT_MODELS=../petab_select/test_cases python3 -m pytest
Acknowledgements
This project has been possible thanks to the BMBF funded de.NBI initiative (031L0104A):
License
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.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file copasi_basico-0.69.tar.gz.
File metadata
- Download URL: copasi_basico-0.69.tar.gz
- Upload date:
- Size: 209.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.0 CPython/3.9.19
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | e0196aafa0ef63df0c595629ed68fdf98ce0299342f06b3cafb5504be66b46f1 |
|
| MD5 | f24cb412df57778de85e129669f112a1 |
|
| BLAKE2b-256 | be09c37636182d514eadca2636967fa802260352aa955e4091a08193b2f05057 |
File details
Details for the file copasi_basico-0.69-py3-none-any.whl.
File metadata
- Download URL: copasi_basico-0.69-py3-none-any.whl
- Upload date:
- Size: 183.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.0 CPython/3.9.19
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | cd84bcff530e6b19040ced8f1c93d18c2020b856d42ef2d82c6e618671609f7d |
|
| MD5 | d94ef7558b0990c0a93d8eaa883d70b0 |
|
| BLAKE2b-256 | 7b878438ef21f4c858f24c826adf74358bc3a5c8c8fe65d5dbff154b7858847e |
