src.spyice.postprocess.analysis#

class src.spyice.postprocess.analysis.Analysis[source]#

Bases: object

Represents an analysis object that performs error analysis on temperature differences.

Parameters:

  • t_k_diff (float) – The temperature difference in Kelvin.

  • t_stefan_diff (float) – The temperature difference in Stefan-Boltzmann units.

__init__(t_k_diff, t_stefan_diff)[source]#
Parameters:

  • t_k_diff (float) – The temperature difference in Kelvin.

  • t_stefan_diff (float) – The temperature difference in Stefan-Boltzmann units.

calculate_errors(field_array, error_norms_object)[source]#

Calculates the errors of a given field array using the provided error norms object.

Parameters:

  • field_array (numpy.ndarray) – The field array to calculate the errors for.

  • error_norms_object (ErrorNorms) – The error norms object used to calculate the errors.

Returns:

A tuple containing the one-norm error, infinity-norm error, and two-norm error.

Return type:

tuple

error_analytical_numerical()[source]#

Calculates the errors of Numerical and Analytical using error norms one, two and infinity.

Parameters:

None

Returns:

A tuple containing the errors calculated using different error norms:

  • T_k_Stefan_diff_L1norm (float): L1 norm of the difference between T_k_list and T_Stefan_list.

  • T_k_Stefan_diff_infnorm (float): Infinity norm of the difference between T_k_list and T_Stefan_list.

  • T_k_Stefan_diff_L2norm (float): L2 norm of the difference between T_k_list and T_Stefan_list.

  • T_Stefan_diff_L1norm (float): L1 norm of the difference between consecutive T_Stefan values.

  • T_Stefan_diff_infnorm (float): Infinity norm of the difference between consecutive T_Stefan values.

  • T_Stefan_diff_L2norm (float): L2 norm of the difference between consecutive T_Stefan values.

  • T_k_diff_infnorm (float): Infinity norm of the difference between consecutive T_k values.

  • T_k_diff_L2norm (float): L2 norm of the difference between consecutive T_k values.

  • T_k_diff_L1norm (float): L1 norm of the difference between consecutive T_k values.

Return type:

tuple

export_residuals(residuals, temperature_mushy, phi_mushy, salinity_mushy, output_dir)[source]#

Exports the residuals to a file.

Parameters:

  • residuals (np.array) – The residuals to export.

  • output_dir (str) – The output directory to save the residuals to.

Returns:

None

classmethod get_error_results(t_k_diff, t_stefan_diff, residual, temperature_mushy, phi_mushy, salinity_mushy, output_dir)[source]#

Runs error analysis on the given temperature differences.

Parameters:

  • cls – The class object.

  • t_k_diff (ndarray) – The temperature difference for k.

  • t_stefan_diff (ndarray) – The temperature difference for Stefan.

  • residual (ndarray)

  • temperature_mushy (ndarray)

  • phi_mushy (ndarray)

  • salinity_mushy (ndarray)

  • output_dir (Path | str)

Returns:

An instance of the AnalysisData class containing the error analysis results.

Return type:

AnalysisData

set_analysis()[source]#

Sets up the analysis for the current object.

This method initializes the error_norms_object attribute with an instance of the ErrorNorms class, passing the t_k_diff and t_stefan_diff attributes as arguments. It then calculates the numerical analytical difference using the numerical_analytical_diff method of the error_norms_object.

Parameters:

None

Returns:

None

static set_dataclass(data_to_be_converted, dataclass)[source]#

Sets the values of a dataclass object using a dictionary.

Parameters:

  • data_to_be_converted (dict) – A dictionary containing the values to be set.

  • dataclass (dataclass) – The dataclass object to be updated.

Returns:

The updated dataclass object.

Return type:

dataclass

store_field_errors(T_k_Stefan_diff_L1norm, T_k_Stefan_diff_infnorm, T_k_Stefan_diff_L2norm, T_Stefan_diff_infnorm, T_Stefan_diff_L2norm, T_Stefan_diff_L1norm, T_k_diff_infnorm, T_k_diff_L2norm, T_k_diff_L1norm)[source]#

Stores the field errors.

Parameters:

  • T_k_Stefan_diff_L1norm (float) – The L1 norm of the temperature and concentration difference.

  • T_k_Stefan_diff_infnorm (float) – The infinity norm of the temperature and concentration difference.

  • T_k_Stefan_diff_L2norm (float) – The L2 norm of the temperature and concentration difference.

  • T_Stefan_diff_infnorm (float) – The infinity norm of the temperature difference.

  • T_Stefan_diff_L2norm (float) – The L2 norm of the temperature difference.

  • T_Stefan_diff_L1norm (float) – The L1 norm of the temperature difference.

  • T_k_diff_infnorm (float) – The infinity norm of the temperature and concentration difference.

  • T_k_diff_L2norm (float) – The L2 norm of the temperature and concentration difference.

  • T_k_diff_L1norm (float) – The L1 norm of the temperature and concentration difference.

class src.spyice.postprocess.analysis.AnalysisData[source]#

Bases: object

Represents the analysis data.

Variables:

all_variables (dict) – A dictionary containing all the variables.

__init__(all_variables)#
Parameters:

all_variables (dict)

Return type:

None

all_variables: dict#