Skip to main content

A Midas module for weather datasets.

Project description

Midas Weather

Description

This package contains a midas module providing a simulator for weather data.

Although this package is intendet to be used with midas, it can be use it in any mosaik simulation scenario.

Installation

This package will usually be installed automatically together with midas-mosaik if you opt-in for the base extra. It is available on pypi, you can install it manually with

pip install midas-weather

Usage

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

Inside of midas

To use the weather data inside of midas, add weather to your modules

my_scenario:
  modules:
    - weather
    - ...

and configure it with

  weather_params:
    my_weather_scope:
      weather_mapping:
        WeatherCurrent:
          - interpolate: true
            randomize: true

If a store module is enabled, the weather module will automatically send all outputs to the store.

Any mosaik scenario

If you don't use midas, you can add the weather manually to your mosaik scenario file. First, the entry in the sim_config:

sim_config = {
    "WeatherData": {"python": "midas_weather.simulator:WeatherDataSimulator"},
    # ...
}

Next, you need to define start_date and step_size. The start_date is to be provided as ISO datestring and can anything between 2009 and 2022:

start_date = "2021-06-08 14:00:00+0000"

The step_size can be anything between 1 and 3600. Higher values might be possible, but this is untested.

Now, the simulator can be started:

weather_sim = world.start("WeatherData", step_size=900, start_date=start_date)

Next, a weather data model can be started:

weather_model = weather_sim.WeatherCurrent(interpolate=True, randomize=True)

Finally, the model needs to be connected to other models:

world.connect(weather_model, other_entity, "t_air_deg_celsius", "wind_v_m_per_s")

License

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

midas_weather-2.0.0.tar.gz (23.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

midas_weather-2.0.0-py3-none-any.whl (22.1 kB view details)

Uploaded Python 3

File details

Details for the file midas_weather-2.0.0.tar.gz.

File metadata

  • Download URL: midas_weather-2.0.0.tar.gz
  • Upload date:
  • Size: 23.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.12.7

File hashes

Hashes for midas_weather-2.0.0.tar.gz
Algorithm Hash digest
SHA256 4d06ea3c790df93dca4836e4fd9c93824364e2f09eed4854eccd98abdfe0b68f
MD5 755db22e20f9605a76ff685cf4b14647
BLAKE2b-256 000b9fcfe30ac24af46492983a1be3d9652f3dd8868fdeaf73701bbf28c3eb5d

See more details on using hashes here.

File details

Details for the file midas_weather-2.0.0-py3-none-any.whl.

File metadata

  • Download URL: midas_weather-2.0.0-py3-none-any.whl
  • Upload date:
  • Size: 22.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.12.7

File hashes

Hashes for midas_weather-2.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 e51c42d3812ca316ba78e50bfe86183f68031cc6329013528ae2cc7514cb362f
MD5 e66ef76f1693d85c5d44cbd5447d2405
BLAKE2b-256 4c2c85cea400b26c167c1edda48bdfb0acb632f0bccefd594c586c6bd0eec5f7

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page