Material Class

Each material is saved as an instance of the Material class. To make changes to a material or to update it with new data or new fits, it suffices to load the instance of Material class from the corresponding pkl file, and edit the attributes of that instance.

class thermal_conductivity.material_class.Material(name, parent: str = None, fit_type='loglog', force_update: bool = False)

A class to represent a material with thermal conductivity data and fits.

name

Name of the material.

Type:

str

folder

Path to the material’s folder.

Type:

str

data_folder

Path to the folder containing raw data files.

Type:

str

plot_folder

Path to the folder for saving plots.

Type:

str

parent

Name of the parent material, if any.

Type:

str

fit_type

The function type used for fitting the data.

Type:

function

fits

List of Fit objects representing different fits applied to the data.

Type:

list

data_classes

Dictionary of DataSet objects for each data file.

Type:

dict

temp_range

Temperature range covered by the data.

Type:

tuple

raw_fit_params

Parameters from the initial fit to all included data.

Type:

np.ndarray

raw_fit_cov

Covariance matrix from the initial fit to all included data.

Type:

np.ndarray

room_temp_tuple

Tuple containing room temperature and corresponding conductivity, if available.

Type:

tuple

interpolate_function

Interpolation function for thermal conductivity based on fits.

Type:

function

Initialize the Material class.

Parameters:

• name (str) – Name of the material.

• parent (str, optional) – Name of the parent material. Defaults to None.

• fit_type (function, optional) – The fitting function to use. Defaults to loglog_func.

• force_update (bool, optional) – Whether to force update the material. Defaults to False.

get_data()

Get the data for the material.

Returns:

A dictionary containing the data for the material. dict: A dictionary containing DataSet objects for each data file.

Return type:

dict

update_data()

Update the data for the material.

Returns:

A dictionary containing the updated data for the material. dict: A dictionary containing updated DataSet objects for each data file.

Return type:

dict

update_material()

Update the material after adding a dataset

fit_data(n_param=None, p0=None, bounds=None)

Fit the data for the material.

Parameters:

• n_param (int, optional) – The number of parameters for the fit. Defaults to 8.

• p0 (array-like, optional) – Initial guess for the fit parameters. Defaults to None.

• bounds (tuple, optional) – Bounds for the fit parameters. Defaults to None.

Returns:

Optimal values for the fit parameters. pcov (np.ndarray): Covariance matrix of the fit parameters.

Return type:

popt (np.ndarray)

update_fit(new_fit_type, fit_index_to_replace: int, n_param=None)

Use this function to change the default fit type for the material and refit the data. Be careful when doing this with a parent material as the parent material may have multiple fits that match the ‘data’ fit source and you may accidently update the wrong fit.

Parameters:

• new_fit_type (str) – The new fit type to use.

• fit_index_to_replace (int) – The index of the fit in the material.fits list to replace with the new fit. Be careful to choose the correct index, especially if there are multiple fits with source “data”.

• n_param (int, optional) – Number of parameters for the new fit. Defaults to None.

Returns:

The updated Material object with the new fit.

Return type:

self (Material)

interpolate(preferred_fit: None)

Interpolate the thermal conductivity data for the material. :param preferred_fit: A Fit object that should be preferred in the interpolation. Defaults to None. :type preferred_fit: Fit, optional

Returns:

An interpolation function for the thermal conductivity data.

Return type:

interp_func (function)

plot_data(loglog=True)

Plot the experimental data for the material.

plot_data_fit()

Plot the experimental data and the fit to the data for the material.

plot_interpolation(loglog=True)

Plot the interpolation fit for the material.

plot_all_fits(loglog=True)

Plot all the available fits for the material.

save_fits()

Converts the self.fits to a dictionary and saves as a json file

get_fits()

Returns the list of Fit objects for the material.

add_fits(fit_name: str, source: str, fit_range: tuple, parameters: ndarray, parameter_covariance: ndarray, fit_type: str, fit_error: float = None, reference: str = None)

Adds a new fit to the material. :param fit_name: Name of the fit (usually material + source). :type fit_name: str :param source: Source of the fit (e.g., “data”, “literature”). :type source: str :param fit_range: Temperature range over which the fit is valid. :type fit_range: tuple :param parameters: Parameters of the fit function. :type parameters: np.ndarray :param parameter_covariance: Covariance matrix of the fit parameters. :type parameter_covariance: np.ndarray :param fit_type: Type of fit function used. :type fit_type: str :param fit_error: Optional error metric for the fit. Defaults to None. :type fit_error: float, optional

Alternatively, a Fit object can be created externally and added to the material by appending to self.fits.

save()

Save the material class as a pickle file.

fit_by_name(fit_name)

Retrieves the fit object for a specified fit name.

Fit Class

class thermal_conductivity.material_class.Fit(material: str, source: str, range: tuple, parameters: ndarray, parameter_covariance: ndarray, fit_type=None, fit_error: float = None, reference: str = None)

A class to represent a fit applied to the data.

material

Name of the material.

Type:

str

source

Source of the fit (e.g., “data”, “literature”).

Type:

str

name

Name of the fit (usually material + source).

Type:

str

range

Temperature range over which the fit is valid.

Type:

tuple

parameters

Parameters of the fit function.

Type:

np.ndarray

parameter_covariance

Covariance matrix of the fit parameters.

Type:

np.ndarray

fit_type

Type of fit function used.

Type:

str

fit_error

Optional error metric for the fit.

Type:

float

reference

Reference for the fit.

Type:

str

function()

Returns the function type used for the fit as a callable. E.g. Fit.function()(x, *params) will evaluate the fit function at x.

calc_tc(T: Unit('K'))

Calculate the thermal conductivity at a specific temperature. :param T: Temperature at which to calculate thermal conductivity. :type T: u.K

Returns:

Thermal conductivity at temperature T.

Return type:

k (u.W/m/K)

Uses astropy units to ensure correct unit handling.

evaluate(T)

Evaluate the fit function at a specific temperature without astropy units. :param T: Temperature at which to evaluate the fit function. :type T: float

Returns:

Thermal conductivity at temperature T.

Return type:

k (float)

tc_integral(T1: Unit('K'), T2: Unit('K'))

Calculate the integral of the thermal conductivity over a temperature range. :param T1: Lower temperature limit. :type T1: u.K :param T2: Upper temperature limit. :type T2: u.K

Returns:

The integral of thermal conductivity from T1 to T2. error (float): Estimated error of the integral.

Return type:

integral (u.W/m)

Uses astropy units to ensure correct unit handling.

add_reference(reference: str)

Adds a reference string to the fit.

Parameters:

reference (str) – The reference string to add in the format ‘Title, Author, Journal/Year’.

DataSet Class

class material_class.DataSet(name: str, data: ndarray, ref_string: str)

A class to represent a dataset from a CSV file. .. attribute:: name

Name of the dataset (usually the filename).

type:

str

data

The data array with temperature and property values.

Type:

np.ndarray

include

Whether to include this dataset in fits.

Type:

bool

inclusion_state(state=True)

Set or get the inclusion state of the dataset (whether to include in the data fit of the material). :param state: If provided, sets the inclusion state. Defaults to True. :type state: bool, optional

Returns:

The current inclusion state.

Return type:

bool