data0.load_input
================

.. py:module:: data0.load_input


Functions
---------

.. autoapisummary::

   data0.load_input.get_npy_from_netcdf
   data0.load_input.apply_config
   data0.load_input.apply_mask


Module Contents
---------------

.. py:function:: 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.

   :param netcdf: Path to the netcdf file or an xarray Dataset.
   :type netcdf: `str` or `xr.Dataset`
   :param year: The year for which to extract the data.
   :type year: `int`
   :param input_config: Path to the input configuration JSON file or a dictionary containing the configuration.
   :type input_config: `str` or `dict`
   :param x_or_y: 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.
   :type x_or_y: `str`, optional
   :param var: The variable to extract from the netcdf file. Overrides the `x_or_y` argument.
               If None, all variables are returned.
   :type var: `str`, optional

   :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.

   .. rubric:: 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)


.. py:function:: 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.

   :param input_netcdf: Path to the netcdf file or an xarray Dataset.
   :type input_netcdf: `str` or `xr.Dataset`
   :param input_config: Path to the input configuration JSON file or a dictionary containing the configuration.
   :type input_config: `str` or `dict`

   :returns: **prepped_dataset** -- The dataset from the input netcdf with the configuration rules applied.
   :rtype: `xr.Dataset`


.. py:function:: 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.

   :param xr_dataset: The xarray dataset containing the variable to be masked.
   :type xr_dataset: `xr.Dataset`
   :param var: The variable to which the mask will be applied.
   :type var: `str`
   :param config_dict: Configuration dictionary specifying mask details.
   :type config_dict: `dict`
   :param year: The year for which the data is being processed.
   :type year: `int`

   :returns: The masked variable as an xarray DataArray.
   :rtype: xr.DataArray