data0.load_input

Functions

get_npy_from_netcdf(netcdf, year, input_config[, ...])

Extract a numpy array for a specific year (and variable if requested) from a netcdf file.

apply_config(input_netcdf, input_config)

Apply the conditions in the config to the netcdf.

apply_mask(xr_dataset, var, config_dict, year)

Apply specified mask to the given variable.

Module Contents

data0.load_input.get_npy_from_netcdf(netcdf, year, input_config, x_or_y=None, var=None)

Extract a numpy array for a specific year (and variable if requested) from a netcdf file.

Parameters:

  • netcdf (str or xr.Dataset) – Path to the netcdf file or an xarray Dataset.

  • year (int) – The year for which to extract the data.

  • input_config (str or dict) – Path to the input configuration JSON file or a dictionary containing the configuration.

  • x_or_y (str, optional) – If ‘x’, return the stage 1 x variables, if ‘x2’, return the stage 2 x variables, if ‘y’, return the y variables. If None, return all variables.

  • var (str, optional) – The variable to extract from the netcdf file. Overrides the x_or_y argument. If None, all variables are returned.

Returns:

  • data_array (numpy.ndarray) – The extracted data as a numpy array.

  • lats (numpy.ndarray) – The latitude values of the arrays to restrict.

  • lons (numpy.ndarray) – The longitude values of the arrays to restrict.

Examples

>>> input_set = 'my_inputs'
>>> arr, lats, lons = get_npy_from_netcdf(f'inputfiles/{input_set}/{input_set}.nc', 2019, 'x')
>>> type(arr)
<class 'numpy.ndarray'>
>>> arr.shape
(364, 56, 120, 9)
data0.load_input.apply_config(input_netcdf, input_config)

Apply the conditions in the config to the netcdf.

Based on the parameters in the input configuration, modify the xarray in the input netcdf and return the resulting xarray dataset.

Parameters:

  • input_netcdf (str or xr.Dataset) – Path to the netcdf file or an xarray Dataset.

  • input_config (str or dict) – Path to the input configuration JSON file or a dictionary containing the configuration.

Returns:

prepped_dataset – The dataset from the input netcdf with the configuration rules applied.

Return type:

xr.Dataset

data0.load_input.apply_mask(xr_dataset, var, config_dict, year)

Apply specified mask to the given variable.

Determine the mask to apply based on the configuration dictionary and apply it to the specified variable in the xarray dataset.

Parameters:

  • xr_dataset (xr.Dataset) – The xarray dataset containing the variable to be masked.

  • var (str) – The variable to which the mask will be applied.

  • config_dict (dict) – Configuration dictionary specifying mask details.

  • year (int) – The year for which the data is being processed.

Returns:

The masked variable as an xarray DataArray.

Return type:

xr.DataArray