[](https://pypi.org/project/estim8/)
[](https://github.com/JuBiotech/estim8/actions)
[](https://app.codecov.io/gh/JuBiotech/estim8)
[](https://estim8.readthedocs.io/en/latest)
# ``estim8``
`estim8` is a open source Python toolbox for parameter estimation of dynamic (bio)process models compliant to the _Functional Mockup Interface_ ([FMI](https://fmi-standard.org/)) standard.
It provides a high-level API for simulation and analysis of FMU models, employing ODE or DAE systems written and compiled from third-party software like e.g. the open source modeling environment of [OpenModelica](https://openmodelica.org/). `estim8` offers special functionality with respect to biotechnological applications, for example the modeling of experimental replicates or measurement noise.
For now, it relies on global meta-heuristic optimization algorithms from [`scipy`](https://scipy.org/) and the highly scalable approaches provided by [`pygmo`](https://esa.github.io/pygmo2/) to solve parameter estimation problems, and provides methods for uncertainty quantification.
`estim8` is build using a highly modular object-oriented architecture, making it easily extensible for custom flavoured implementations.
## Installation:
It is highly recommended to use a [conda](https://docs.conda.io/projects/conda/en/latest/user-guide/install/index.html) or preferably a [mamba](https://github.com/mamba-org/mamba) environment manager.
### 1. Installation from PyPI
It is advised to create a fresh virtual environent using ``mamba`` (or ``conda`` alternatively):
```bash
mamba create --name estim8 python==3.10
mamba activate estim8
```
**_NOTE:_** Not all dependencies are packaged with the PyPI version. In order to use ``pygmo`` optimizers, the package needs to be installed manually. When using federated setups on Windows, additionally install ``m2w64-toolchain``. These packages need to be installed **before** installing ``estim8``!
```bash
mamba install -c conda-forge pygmo m2w64-toolchain
```
``estim8`` can then easily be installed using ``pip``:
```bash
pip install estim8
```
### 2 Development Installation
Download the [source code repository](https://github.com/JuBiotech/estim8) to your computer, best by using [`git`](https://git-scm.com/):
1. navigate to the directory of your computer where you want the repository to be located
2. open a terminal and run `git clone https://github.com/JuBiotech/estim8.git`
3. change into the dowloaded directory `cd estim8`
#### Setting up the environment
It is advised to create a fresh virtual environent:
```bash
conda create --name <env_name>
conda activate <env_name>
conda env update --name <env_name> --file environment.yml
```
#### Importing estim8
To get the most recent version, open a terminal in the repository and run:
```bash
git pull
```
In Python, add the following lines ath the top of your code. Don't forget to adjust the path.
```Python
import sys
sys.path.append('path/to/repo')
```
## Documentation
Check out our [documentation](https://estim8.readthedocs.io/en/latest/), where we provide a series of example notebooks.
## Usage and Citing
``estim8`` is licensed under the [GNU Affero General Public License v3.0](https://github.com/JuBiotech/estim8/blob/main/license.md).
A citable publication is coming soon.
Raw data
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"description": "[](https://pypi.org/project/estim8/)\n[](https://github.com/JuBiotech/estim8/actions)\n[](https://app.codecov.io/gh/JuBiotech/estim8)\n[](https://estim8.readthedocs.io/en/latest)\n\n\n# ``estim8``\n`estim8` is a open source Python toolbox for parameter estimation of dynamic (bio)process models compliant to the _Functional Mockup Interface_ ([FMI](https://fmi-standard.org/)) standard.\n\nIt provides a high-level API for simulation and analysis of FMU models, employing ODE or DAE systems written and compiled from third-party software like e.g. the open source modeling environment of [OpenModelica](https://openmodelica.org/). `estim8` offers special functionality with respect to biotechnological applications, for example the modeling of experimental replicates or measurement noise.\n\nFor now, it relies on global meta-heuristic optimization algorithms from [`scipy`](https://scipy.org/) and the highly scalable approaches provided by [`pygmo`](https://esa.github.io/pygmo2/) to solve parameter estimation problems, and provides methods for uncertainty quantification.\n\n`estim8` is build using a highly modular object-oriented architecture, making it easily extensible for custom flavoured implementations.\n\n## Installation:\nIt is highly recommended to use a [conda](https://docs.conda.io/projects/conda/en/latest/user-guide/install/index.html) or preferably a [mamba](https://github.com/mamba-org/mamba) environment manager.\n\n### 1. Installation from PyPI\n\nIt is advised to create a fresh virtual environent using ``mamba`` (or ``conda`` alternatively):\n\n```bash\n mamba create --name estim8 python==3.10\n mamba activate estim8\n```\n\n\n\n**_NOTE:_** Not all dependencies are packaged with the PyPI version. In order to use ``pygmo`` optimizers, the package needs to be installed manually. When using federated setups on Windows, additionally install ``m2w64-toolchain``. These packages need to be installed **before** installing ``estim8``!\n\n```bash\n mamba install -c conda-forge pygmo m2w64-toolchain\n```\n\n``estim8`` can then easily be installed using ``pip``:\n\n```bash\n pip install estim8\n```\n\n\n### 2 Development Installation\nDownload the [source code repository](https://github.com/JuBiotech/estim8) to your computer, best by using [`git`](https://git-scm.com/):\n1. navigate to the directory of your computer where you want the repository to be located\n2. open a terminal and run `git clone https://github.com/JuBiotech/estim8.git`\n3. change into the dowloaded directory `cd estim8`\n\n\n#### Setting up the environment\nIt is advised to create a fresh virtual environent:\n```bash\nconda create --name <env_name>\nconda activate <env_name>\nconda env update --name <env_name> --file environment.yml\n```\n\n#### Importing estim8\nTo get the most recent version, open a terminal in the repository and run:\n```bash\ngit pull\n```\n\nIn Python, add the following lines ath the top of your code. Don't forget to adjust the path.\n ```Python\n import sys\n sys.path.append('path/to/repo')\n ```\n\n\n\n## Documentation\nCheck out our [documentation](https://estim8.readthedocs.io/en/latest/), where we provide a series of example notebooks.\n\n## Usage and Citing\n``estim8`` is licensed under the [GNU Affero General Public License v3.0](https://github.com/JuBiotech/estim8/blob/main/license.md).\n\nA citable publication is coming soon.\n",
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