icenet.process package

icenet.process package#

Submodules#

icenet.process.azure module#

icenet.process.azure.upload()[source]#
icenet.process.azure.upload_parse_args()[source]#
Returns:

icenet.process.forecasts module#

icenet.process.forecasts.broadcast_args() → Namespace[source]#

CLI arguments for broadcasting several forecasts linearly through time

icenet.process.forecasts.broadcast_main()[source]#

CLI entry point for icenet_output_broadcast

icenet.process.forecasts.create_geotiff_output()[source]#

CLI entry point for icenet_output_geotiff

icenet.process.forecasts.geotiff_args() → Namespace[source]#

CLI args for creating geotiffs

icenet.process.forecasts.reproject_args() → Namespace[source]#

CLI args for reprojecting against another file

icenet.process.forecasts.reproject_main()[source]#

CLI entry point for icenet_output_reproject

icenet.process.forecasts.reproject_output(forecast_file: object, proj_file: object, save_file: object) → object[source]#
Parameters:

  • forecast_file

  • proj_file

  • save_file

icenet.process.local module#

icenet.process.local.upload()[source]#
icenet.process.local.upload_parse_args()[source]#
Returns:

icenet.process.predict module#

icenet.process.predict.create_cf_output()[source]#
icenet.process.predict.date_arg(string: str) → object[source]#
Parameters:

string

Returns:

icenet.process.predict.get_args()[source]#
Returns:

icenet.process.predict.get_prediction_data(root: str, name: str, date: <module 'datetime' from '/home/runner/micromamba/lib/python3.11/datetime.py'>, return_ensemble_data: bool = False) → tuple[source]#

Get prediction data from ensemble numpy files for specified date.

Parameters:

  • root – Root directory path to pipeline results.

  • name – Name of the prediction.

  • date – Forecast date to get prediction data for.

  • return_ensemble_data (optional) – Whether to also return full ensemble data array, or just the mean. Defaults to False.

Returns:

  • If return_ensemble_data is True: Returns (data_mean, full_data_ensemble, number_of_ensemble_members)

  • If return_ensemble_data is False: Returns (data_mean, number_of_ensemble_members)

Return type:

tuple

icenet.process.predict.get_refcube(north: bool = True, south: bool = False) → object[source]#
Parameters:

  • north

  • south

Returns:

icenet.process.predict.get_refsic(north: bool = True, south: bool = False) → object[source]#
Parameters:

  • north

  • south

Returns:

icenet.process.train module#

icenet.process.utils module#

icenet.process.utils.date_arg(string: str) → object[source]#
Parameters:

string

Returns:

icenet.process.utils.destination_filename(destination: object, filename: str, date: object) → object[source]#
Parameters:

  • destination

  • filename

  • date

Returns:

Module contents#