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ema-workbench-2.4.0
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تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
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تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشترتوضیحات
Exploratory modelling in Python
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | ema-workbench-2.4.0 |
| نام | ema-workbench |
| نسخه کتابخانه | 2.4.0 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | - |
| ایمیل نویسنده | Jan Kwakkel <j.h.kwakkel@tudelft.nl> |
| آدرس صفحه اصلی | - |
| آدرس اینترنتی | https://pypi.org/project/ema-workbench/ |
| مجوز | Copyright (c) 2010-2016, Delft University of Technology All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * 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. * Neither the name of the Delft University of Technology 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. |
[](https://github.com/quaquel/EMAworkbench/actions)
[](https://coveralls.io/github/quaquel/EMAworkbench?branch=master)
[](http://emaworkbench.readthedocs.org/en/latest/?badge=master)
[](https://pypi.python.org/pypi/ema_workbench)
[](https://pypi.python.org/pypi/ema_workbench)
# Exploratory Modeling workbench
Exploratory Modeling and Analysis (EMA) is a research methodology that uses computational experiments to analyze complex and uncertain systems ([Bankes, 1993](http://www.jstor.org/stable/10.2307/171847)). That is, exploratory modeling aims at offering computational decision support for decision making under [deep uncertainty](http://inderscience.metapress.com/content/y77p3q512x475523/) and [robust decision making](http://en.wikipedia.org/wiki/Robust_decision_making).
The EMA workbench aims at providing support for performing exploratory modeling with models developed in various modelling packages and environments. Currently, the workbench offers connectors to [Vensim](https://vensim.com/), [Netlogo](https://ccl.northwestern.edu/netlogo/), [Simio](https://www.simio.com/), [Vadere](https://www.vadere.org/) and Excel.
The EMA workbench offers support for designing experiments, performing the experiments - including support for parallel processing on both a single machine as well as on clusters-, and analysing the results. To get started, take a look at the high level overview, the tutorial, or dive straight into the details of the API.
The EMA workbench currently under development at Delft University of Technology. If you would like to collaborate, open an issue/discussion or contact [Jan Kwakkel](https://www.tudelft.nl/en/tpm/our-faculty/departments/multi-actor-systems/people/professors/prof-drir-jh-jan-kwakkel).
## Documentation
Documentation for the workbench is availabe at [Read the Docs](https://emaworkbench.readthedocs.io/en/latest/index.html), including an introduction on Exploratory Modeling, tutorials and documentation on all the modules and functions.
There are also a lot of example models available at [ema_workbench/examples](ema_workbench/examples), both for pure Python models and some using the different connectors. A release notes for each new version are available at [CHANGELOG.md](CHANGELOG.md).
## Installation
The workbench is available from [PyPI](https://pypi.org/project/ema-workbench/), and currently requires Python 3.8 or newer. It can be installed with:
```
pip install -U ema_workbench
```
To also install some recommended packages for plotting, testing and Jupyter support, use the `recommended` extra:
```
pip install -U ema_workbench[recommended]
```
There are way more options installing the workbench, including installing connector packages, edible installs for development, installs of custom forks and branches and more. See [Installing the workbench](https://emaworkbench.readthedocs.io/en/latest/getting_started/installation.html) in the docs for all options.
## Contributing
We greatly appreciate contributions to the EMA workbench! Reporting [Issues](https://github.com/quaquel/EMAworkbench/issues) such as bugs or unclairties in the documentation, opening a [Pull requests](https://github.com/quaquel/EMAworkbench/pulls) with code or documentation improvements or opening a [Discussion](https://github.com/quaquel/EMAworkbench/discussions) with a question, suggestions or comment helps us a lot.
Please check [CONTRIBUTING.md](CONTRIBUTING.md) for more information.
## License
This repository is licensed under BSD 3-Clause License. See [LICENSE.md](LICENSE.md).
نیازمندی
| مقدار | نام |
|---|---|
| - | numpy |
| - | pandas |
| - | scikit-learn |
| >=1.4.6 | salib |
| - | platypus-opt |
| - | matplotlib |
| - | statsmodels |
| - | seaborn |
| - | tqdm |
| - | ema-workbench[cov,dev,docs,graph,jupyter,parallel] |
| - | pytest-cov |
| - | coverage |
| - | coveralls |
| - | pytest |
| - | pytest-mock |
| - | jupyter-client |
| - | ipyparallel |
| - | sphinx |
| - | nbsphinx |
| - | myst |
| - | pyscaffold |
| - | myst-parser |
| - | altair |
| - | pydot |
| - | graphviz |
| - | jupyter |
| - | jupyter-client |
| - | ipython |
| - | ipykernel |
| - | jpype-1 |
| - | pynetlogo |
| - | ipyparallel |
| - | traitlets |
| - | pysd |
| - | ema-workbench[dev,graph,jupyter] |
| - | pythonnet |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.8 | Python |
نحوه نصب
نصب پکیج whl ema-workbench-2.4.0:
pip install ema-workbench-2.4.0.whl
نصب پکیج tar.gz ema-workbench-2.4.0:
pip install ema-workbench-2.4.0.tar.gz