Metadata-Version: 2.1
Name: midas-sbdata
Version: 1.0.1
Summary: A MIDAS module for Simbench datasets.
Home-page: https://gitlab.com/midas-mosaik/midas-sbdata
Author: Stephan Balduin
Author-email: stephan.balduin@offis.de
License: LGPL
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU Lesser General Public License v2 (LGPLv2)
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: midas-util (>=1.0.1)
Requires-Dist: mosaik-api
Requires-Dist: pandas
Requires-Dist: tables
Requires-Dist: simbench
Provides-Extra: dev
Requires-Dist: flake8 ; extra == 'dev'
Requires-Dist: pytest ; extra == 'dev'
Requires-Dist: coverage ; extra == 'dev'
Requires-Dist: black (==22.3.0) ; extra == 'dev'
Requires-Dist: setuptools ; extra == 'dev'
Requires-Dist: twine ; extra == 'dev'
Requires-Dist: wheel ; extra == 'dev'
Requires-Dist: matplotlib ; extra == 'dev'

# MIDAS Simbench Data Simulator

## Description
This package contains a MIDAS module providing a simulator for Simbench data sets.

Although this package is intended to be used with MIDAS, it does not depend from anything MIDAS-related except for the `midas-util` package. You can use in any mosaik simulation scenario.

## Installation
This package will usually installed automatically together with `midas-mosaik`. It is available on pypi, so you can install it manually with

```bash
pip install midas-sbdata
```

## Usage
The complete documentation is available at https://midas-mosaik.gitlab.io/midas.

### Inside of MIDAS
To use the Simbench data inside of MIDAS, just add `sbdata` to your modules

```yaml
my_scenario:
  modules:
    - sbdata
    - ...
```

and configure it with:

```yaml
  sbdata_params:
    my_grid_scope:
      step_size: 900
      grid_name: my_grid_scope
      start_date: 2020-01-01 00:00:00+0100
      cos_phi: 0.9
      filename: 1-LV-rural3--0-sw.hdf5
      data_path: path/to/hdf-specified-by-filename
      load_scaling: 1.0
      load_mapping: default
      sgen_scaling: 1.0
      sgen_mapping: default
      storage_scaling: 1.0
      storage_mapping: default
      interpolate: False
      randomize_data: False
      noise_factor: 0.2
      randomize_cos_phi: False
      seed: ~
      seed_max: 1_000_000
```

All of the attributes show their default values and can optionally be left out. The *xxx*_mapping attributes can either be `default` or a dictionary with a specific mapping. When `default` is used, the mapping defined in the powergrid profiles is used.

## License
This software is released under the GNU Lesser General Public License (LGPL). See the license file for more information about the details.

