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PLASMA_SIM
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main
Config.py
171 строка
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Zlalex
Stable Ver 1.0
14 фев 2025, 22:20
14 фев 2025, 22:20
14b3950
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import numpy as np # Физические константы k_B = 1.38e-23 # Постоянная Больцмана (Дж/К) m_p = 1.67e-27 # Масса протона (кг) e = 1.6e-19 # Заряд электрона (Кл) mu_0 = 4 * np.pi * 1e-7 # Магнитная проницаемость вакуума (Гн/м) gamma = 5 / 3 # Адиабатический индекс mu = 1.0 # Магнитная проницаемость eta = 0.01 # Магнитная диффузия nu = 0 # Вязкость m_D = 3.3437e-27 m_T = 5.0075e-27 m_He = 6.6449e-27 Lx, Ly = 10.0, 10.0 # Размеры области по x и y Nx, Ny = 100, 100 # Число точек сетки dx, dy = Lx / Nx, Ly / Ny def MevToK(mev): return 11604525006.17*mev def concatenate_arrays(drho, dV_magnitude, dp, dB, dT, dn_D, dn_T, dn_He): """ Concatenate multiple 2D arrays into a single 1D array. Parameters: - drho: Change in density (2D array) - dV_magnitude: Change in velocity magnitude (2D array) - dp: Change in pressure (2D array) - dB: Change in magnetic field (2D array) - dT: Change in temperature (2D array) - dn_D: Change in density of D (2D array) - dn_T: Change in density of T (2D array) - dn_He: Change in density of He (2D array) Returns: - A single 1D NumPy array containing all concatenated values. """ return np.concatenate([ drho.flatten(), dV_magnitude.flatten(), dp.flatten(), dB.flatten(), dT.flatten(), dn_D.flatten(), dn_T.flatten(), dn_He.flatten() ]) def decode_arrays(concatenated_array, Nx, Ny): """ Decode a 1D array back into multiple 2D arrays. Parameters: - concatenated_array: A single 1D NumPy array containing all values. - Nx: Number of rows. - Ny: Number of columns. Returns: - A tuple of eight 2D NumPy arrays corresponding to the original data. """ # Calculate the size of each individual array size = Nx * Ny # Extract each array from the concatenated array drho = concatenated_array[0:size].reshape((Nx, Ny)) dV_magnitude = concatenated_array[size:size*2].reshape((Nx, Ny)) dp = concatenated_array[size*2:size*3].reshape((Nx, Ny)) dB = concatenated_array[size*3:size*4].reshape((Nx, Ny)) dT = concatenated_array[size*4:size*5].reshape((Nx, Ny)) dn_D = concatenated_array[size*5:size*6].reshape((Nx, Ny)) dn_T = concatenated_array[size*6:size*7].reshape((Nx, Ny)) dn_He = concatenated_array[size*7:size*8].reshape((Nx, Ny)) return drho, dV_magnitude, dp, dB, dT, dn_D, dn_T, dn_He def decode_solve_ivp_result(sol, Nx, Ny): """ Decode the result from solve_ivp into individual 2D arrays. Parameters: - sol: The solution object returned by scipy.integrate.solve_ivp. - Nx: Number of rows (grid points in x-direction). - Ny: Number of columns (grid points in y-direction). Returns: - A tuple of eight 2D NumPy arrays corresponding to the original data: (density_change, velocity_magnitude_change, pressure_change, magnetic_field_change, temperature_change, n_D_change, n_T_change, n_He_change) """ # The solution object contains an attribute 'y' which is the concatenated array concatenated_array = sol.y.flatten() # Flatten to ensure it's a 1D array # Calculate the size of each individual array size = Nx * Ny # Extract each array from the concatenated array density_change = concatenated_array[0:size].reshape((Nx, Ny)) velocity_magnitude_change = concatenated_array[size:size*2].reshape((Nx, Ny)) pressure_change = concatenated_array[size*2:size*3].reshape((Nx, Ny)) magnetic_field_change = concatenated_array[size*3:size*4].reshape((Nx, Ny)) temperature_change = concatenated_array[size*4:size*5].reshape((Nx, Ny)) n_D_change = concatenated_array[size*5:size*6].reshape((Nx, Ny)) n_T_change = concatenated_array[size*6:size*7].reshape((Nx, Ny)) n_He_change = concatenated_array[size*7:size*8].reshape((Nx, Ny)) return (density_change, velocity_magnitude_change, pressure_change, magnetic_field_change, temperature_change, n_D_change, n_T_change, n_He_change) def extract_frames_from_solution(sol, Nx, Ny): """ Extracts frames of data from the solution object returned by solve_ivp. Parameters: - sol: The solution object returned by scipy.integrate.solve_ivp. - Nx: Number of rows (grid points in x-direction). - Ny: Number of columns (grid points in y-direction). Returns: - A dictionary containing arrays of shape (num_frames, Nx, Ny) for each variable. """ # Number of time steps num_frames = sol.y.shape[1] # Prepare arrays to hold frames for each variable density_frames = np.zeros((num_frames, Nx, Ny)) velocity_magnitude_frames = np.zeros((num_frames, Nx, Ny)) pressure_frames = np.zeros((num_frames, Nx, Ny)) magnetic_field_frames = np.zeros((num_frames, Nx, Ny)) temperature_frames = np.zeros((num_frames, Nx, Ny)) n_D_frames = np.zeros((num_frames, Nx, Ny)) n_T_frames = np.zeros((num_frames, Nx, Ny)) n_He_frames = np.zeros((num_frames, Nx, Ny)) # Loop through each time step and extract data for i in range(num_frames): # Get the concatenated array for this time step concatenated_array = sol.y[:, i] # Decode the concatenated array into individual variables size = Nx * Ny density_frames[i] = concatenated_array[0:size].reshape((Nx, Ny)) velocity_magnitude_frames[i] = concatenated_array[size:size*2].reshape((Nx, Ny)) pressure_frames[i] = concatenated_array[size*2:size*3].reshape((Nx, Ny)) magnetic_field_frames[i] = concatenated_array[size*3:size*4].reshape((Nx, Ny)) temperature_frames[i] = concatenated_array[size*4:size*5].reshape((Nx, Ny)) n_D_frames[i] = concatenated_array[size*5:size*6].reshape((Nx, Ny)) n_T_frames[i] = concatenated_array[size*6:size*7].reshape((Nx, Ny)) n_He_frames[i] = concatenated_array[size*7:size*8].reshape((Nx, Ny)) return { 'density': density_frames, 'velocity_magnitude': velocity_magnitude_frames, 'pressure': pressure_frames, 'magnetic_field': magnetic_field_frames, 'temperature': temperature_frames, 'n_D': n_D_frames, 'n_T': n_T_frames, 'n_He': n_He_frames } # Example usage after solving with solveMe # sol = solveMe(duration, initial_data) # frames = extract_frames_from_solution(sol, Nx, Ny) # Access individual frames like this: # density_frame_at_t0 = frames['density'][0] # velocity_frame_at_t1 = frames['velocity_magnitude'][1] # Example usage after solving with solveMe # sol = solveMe(duration, initial_data) # decoded_arrays = decode_solve_ivp_result(sol, Nx, Ny)