Using datasets for transport properties for DFN model

[basabrdg]

Example 1-20240709_090551__R01_c2_over_Diff-Coeff_Data Export.csv
I have datasets for transport properties that depend on concentration of electrolyte as well as Temperature. But I am unable to do interpolation and use it for pybamm use. I have edited one of the existing parameter sets to modify the functions. However, I get error and understand that c_e and T are symbolic so these require a functional form. How should I approach this problem? FYI, the regularr grid interpolator does a great job to fit the data if I just do it in a separate python notebook.

def fit_and_create_interpolator(csv_file_path):
"""
Fit the data from CSV and create an interpolator.

Parameters:
- csv_file_path: str, path to the CSV file containing data.

Returns:
- interp_func: RegularGridInterpolator function for diffusivity.
"""
# Load the data
data = pd.read_csv(csv_file_path)

# Extract concentration column and convert to mol/m^3
c2 = data['c2'].values * 1000

# Extract temperature values from column names and convert to Kelvin
temp_columns = [col for col in data.columns if 'Diff Coeff' in col]
temperatures_celsius = [float(col.split('.')[0]) for col in temp_columns]
temperatures_kelvin = [temp + 273.15 for temp in temperatures_celsius]

# Extract diffusion coefficient columns for each temperature
diff_coeffs = [data[col].values for col in temp_columns]

# Prepare data for RegularGridInterpolator
diff_coeff_matrix = np.array(diff_coeffs).T

# Create RegularGridInterpolator
interp_func = RegularGridInterpolator((c2, temperatures_kelvin), diff_coeff_matrix, method='linear', bounds_error=False, fill_value=None)

return interp_func

def electrolyte_diffusivity_AEM(c_e, T, interp_func, c2_bounds, temp_bounds):
"""
Diffusivity of LiPF6 in EC:EMC (3:7) as a function of ion concentration and temperature.

Parameters
----------
c_e: :class:`pybamm.Symbol`
    Dimensional electrolyte concentration in mol/m^3
T: :class:`pybamm.Symbol`
    Dimensional temperature in Kelvin
interp_func: RegularGridInterpolator
    Interpolator function for diffusivity
c2_bounds: tuple
    Bounds for concentration
temp_bounds: tuple
    Bounds for temperature

Returns
-------
:class:`pybamm.Symbol`
    Solid diffusivity
"""
def diffusivity_function(c_e, T):
    # Clamp values to the bounds
    c_e_clamped = np.clip(c_e, c2_bounds[0], c2_bounds[1])
    T_clamped = np.clip(T, temp_bounds[0], temp_bounds[1])
    # Interpolator requires inputs in 2D array form
    return interp_func((c_e_clamped, T_clamped))[0]

return pybamm.Function(diffusivity_function, c_e, T)