pyROX.cross_sections

pyROX.cross_sections#

Classes#

CrossSections

Base class for handling cross-sections.

Functions#

load_data_object(config, **kwargs)

Load the data object based on the given configuration.

Module Contents#

pyROX.cross_sections.load_data_object(config, **kwargs)#

Load the data object based on the given configuration.

Parameters:

  • config (object) – Configuration object containing database information.

  • **kwargs – Additional arguments to pass to the data object.

Returns:

An instance of the appropriate data object based on the database type.

Return type:

object

Raises:

NotImplementedError – If the specified database is not implemented.

class pyROX.cross_sections.CrossSections(config, download=False)#

Base class for handling cross-sections.

static _mask_arrays(arrays, mask, **kwargs)#

Apply a mask to the given arrays.

Parameters:

  • arrays (list) – List of arrays to mask.

  • mask (array-like) – Boolean mask to apply.

  • **kwargs – Additional arguments for numpy.compress.

Returns:

List of masked arrays.

Return type:

list

database#
abstractmethod download_data(*args, **kwargs)#

Download data required for cross-section calculations.

Raises:

NotImplementedError – This method should be implemented in a subclass.

abstractmethod calculate_temporary_outputs(*args, **kwargs)#

Calculate temporary outputs for cross-sections.

Raises:

NotImplementedError – This method should be implemented in a subclass.

abstractmethod plot_combined_outputs(*args, **kwargs)#

Plot merged outputs for cross-sections.

Raises:

NotImplementedError – This method should be implemented in a subclass.

save_combined_outputs(keys_to_merge, progress_bar=False, overwrite=False, **kwargs)#

Combine temporary files and save the final output.

Parameters:

  • keys_to_merge (list) – List of keys to combine.

  • progress_bar (bool, optional) – Whether to show a progress bar. Defaults to False.

  • overwrite (bool, optional) – Whether to overwrite the final output file if it exists. Defaults to False.

  • **kwargs – Additional arguments for merging.

combine_temporary_outputs(keys_to_merge, progress_bar=False, **kwargs)#

Combine temporary output-files into a single dataset.

Parameters:

  • keys_to_merge (list) – List of keys to read from the temporary files.

  • progress_bar (bool, optional) – Whether to show a progress bar. Defaults to False.

  • **kwargs – Additional arguments for merging.

Raises:

  • FileNotFoundError – If no temporary cross-section files are found.

  • ValueError – If the temperature grid is not found in a temporary file.

_combine_PT_grids(tmp_files, sum_outputs)#

Combine the PT-grids of the temporary files.

Parameters:

  • tmp_files (list) – List of temporary files to combine.

  • sum_outputs (bool) – Whether to sum the outputs.

Returns:

A tuple containing the main wavelength grid, pressure grid, temperature grid, and a list of booleans indicating if the wavelength axis was flipped.

Return type:

tuple

Raises:

ValueError – If the PT grid is not rectangular or grids are incompatible.

_check_if_sum_outputs()#

Check if the cross-sections should be summed.

Returns:

True if the outputs should be summed, False otherwise.

Return type:

bool

_check_existing_output_files(input_files=[''], overwrite_all=False, final_output_file=None)#

Check if the output files already exist.

Parameters:

  • input_files (list) – List of input file paths.

  • overwrite_all (bool) – Whether to overwrite all existing files.

  • final_output_file (str) – Expected output file name.

Returns:

List of output file paths.

Return type:

list

_read_configuration_parameters(config)#

Read parameters from the configuration object.

Parameters:

config (object) – Configuration object containing parameters.

Raises:

ValueError – If no input-data files are specified in the configuration.

_setup_nu_grid()#

Configure the wavenumber grid based on the configuration parameters.

_setup_coarse_nu_grid(adaptive_delta_nu)#

Configure a coarse wavenumber grid for adaptive calculations.

Parameters:

adaptive_delta_nu (float) – Desired resolution for the coarse grid.

Returns:

Coarse wavenumber grid.

Return type:

numpy.ndarray