Impossible to write this expression in ASPECT muparser format

I solved the problem at the end, it was due to the angle that need to be putted in radians instead of degree. I leave here a python script and the ASCII file.

I suggest to write a cookbook about how to setup the ascii correctly (POINTS, COLUMNS etc.)

Thank you for the help and Best regards

30-3-p30-P400.txt (1004.7 KB)

import matplotlib.pyplot as plt
import numpy as np
import math

# Parametri
r_inner = 3481000  # Raggio interno in metri
r_outer = 6371000  # Raggio esterno in metri
p_large = 400.0  # Ampiezza delle grandi perturbazioni
p_small = 30.0  # Ampiezza delle piccole perturbazioni
frequency_large = 3  # Frequenza delle grandi perturbazioni
frequency_small = 30  # Frequenza delle piccole perturbazioni
spread_angle_large_degrees = 90  # Angolo di diffusione delle grandi perturbazioni in gradi
start_angle_degrees = 330  # Angolo di partenza per la perturbazione in gradi

# Funzione di temperatura modificata per utilizzare i gradi e gestire gli array
def temperature_function_degrees_array(r, theta_degrees):
    # Aggiusta theta per spostare l'angolo di inizio della perturbazione
    adjusted_theta_degrees = theta_degrees + start_angle_degrees
    adjusted_theta_degrees = adjusted_theta_degrees % 360

    # Inizializza l'array della temperatura
    temp = np.zeros_like(r)

    # Determina la grande perturbazione usando un approccio a funzione gradino
    large_perturbation_mask = (adjusted_theta_degrees < spread_angle_large_degrees) | (adjusted_theta_degrees > 360 - spread_angle_large_degrees)
    temp[large_perturbation_mask] = p_large * np.sin(np.pi * (r[large_perturbation_mask] - r_inner) / (r_outer - r_inner)) * np.sin(frequency_large * np.radians(theta_degrees[large_perturbation_mask]))

    # Applica piccole perturbazioni dove non si applicano le grandi perturbazioni
    small_perturbation_mask = ~large_perturbation_mask
    temp[small_perturbation_mask] = p_small * np.sin(np.pi * (r[small_perturbation_mask] - r_inner) / (r_outer - r_inner)) * np.sin(frequency_small * np.radians(theta_degrees[small_perturbation_mask]))

    return temp

# Generazione dei dati per la visualizzazione
theta = np.linspace(0, 360, 360)  # Angoli da 0 a 360 gradi
radius = np.linspace(r_inner, r_outer, 100)  # Raggi da r_inner a r_outer

# Creazione di una griglia per il plotting
R, Theta = np.meshgrid(radius, theta)
Temp = temperature_function_degrees_array(R, Theta)

def write_ascii_data(radius, theta_degrees, temperatures, filename):
    with open(filename, 'w') as file:
        file.write("# Test data for ascii data initial conditions.\n")
        file.write("# Only next line is parsed in format: [nx] [ny] [nz] because of keyword \"POINTS:\"\n")
        file.write("# POINTS: 100 360 1\n")
        file.write("# Columns: r phi      temperature [K]\n")

        for j in range(len(theta_degrees)):
            for i in range(len(radius)):
                r = radius[i]
                phi = theta_degrees[j]
                temp = temperatures[j, i]

                # Formattazione migliorata
                r_str = f"{r:.1f}"
                phi_str = f"{phi:.4f}" if not phi.is_integer() else f"{int(phi)}"
                temp_str = f"{temp:.1f}" if not temp.is_integer() else f"{int(temp)}"

                # Allineamento delle colonne con spostamento della seconda colonna
                file.write(f"{r_str:<10} {phi_str:<11}{temp_str}\n")

# Conversione delle coordinate polari in coordinate cartesiane per il plotting
X = R * np.cos(np.radians(Theta))
Y = R * np.sin(np.radians(Theta))

# Plotting
plt.figure(figsize=(8, 6))
contour = plt.contourf(X, Y, Temp, levels=50, cmap='viridis')
plt.colorbar(contour, label='Temperatura')
plt.title('Distribuzione della Temperatura in Coordinate Polari')
plt.xlabel('Coordinata X (m)')
plt.ylabel('Coordinata Y (m)')

# Uso della funzione write_ascii_data per salvare i dati
write_ascii_data(radius, theta, Temp, '30-3-p30-P400.txt')

import math

def convert_to_radians(degrees):
    """Convert degrees to radians."""
    return degrees * (math.pi / 180)

def convert_file_angles(input_file_path, output_file_path):
    """Convert the angles in the second column of the file from degrees to radians."""
    with open(input_file_path, 'r') as file:
        content = file.readlines()

    converted_lines = content[:4]  # Keep the header lines unchanged
    for line in content[4:]:
        columns = line.split()
        if len(columns) == 3:
            radius, angle_deg, temperature = columns
            angle_rad = convert_to_radians(float(angle_deg))
            converted_line = f"{radius}  {angle_rad:.8f}  {temperature}\n"

    with open(output_file_path, 'w') as file:

# Example usage
input_file_path = '30-3-p30-P400.txt'  # Replace with your input file path
output_file_path = '30-3-p30-P400.txt'  # Replace with your desired output file path

convert_file_angles(input_file_path, output_file_path)

@Francyrad I’m very glad to hear that you solved the problem!

Regarding the cookbook: Would you be willing to write such a cookbook with your experiences? I think that would be fantastic!


Obviously yes! I would love to!

I need to write the .prm and the section for the userguide, right?

Yes, that’s basically it. You might want to look at other examples in the cookbooks/ directory. Perhaps a similar case to what you are trying to do is in the cookbooks/geomio/ directory.


dear @bangerth

I wrote the tutorial, what is the best option to publish it in the wiki? Or i just send it to you?

@Francyrad - thank you for writing the cookbook! The ideal case would be for you to submit a pull request to add the new cookbook, and if you have not done this before we are of course happy to help you getting started on the workflows. There is also a section in the manual here on contributing via PRs. If this is not going to be feasible for various reasons, let’s discuss other options (another developer can open a PR with your proposed changes).

@jbnaliboff I did a pull request. I’m sorry for the late reply, but i’ve been very busy. I’ll do also a tutorial for a 3D ascii perturbation model.

@Francyrad - Thanks for submitting the cookbook PR, and I’ve provided some initial feedback there! One question - just to be sure, is the temperature perturbation in the current PR indeed correct and not affected by the issue reported in your other forum post today? Thanks again!

The new issue is in 3D, the 2D in PR works perfectly

I’ll do the corrections as soon as I can