#!/usr/bin/env python # -*- coding: UTF-8 -*- # # Copyright (C) 2009-2017 Ovidio Peña Rodríguez # # This file is part of python-scattnlay # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # The only additional remark is that we expect that all publications # describing work using this software, or all commercial products # using it, cite at least one of the following references: # [1] O. Peña and U. Pal, "Scattering of electromagnetic radiation by # a multilayered sphere," Computer Physics Communications, # vol. 180, Nov. 2009, pp. 2348-2354. # [2] K. Ladutenko, U. Pal, A. Rivera, and O. Peña-Rodríguez, "Mie # calculation of electromagnetic near-field for a multilayered # sphere," Computer Physics Communications, vol. 214, May 2017, # pp. 225-230. # # You should have received a copy of the GNU General Public License # along with this program. If not, see . # This is a test against the program n-mie (version 3a) for the test case # distributed by them (extended for x up to 100) # n-mie is based in the algorithm described in: # Wu Z.P., Wang Y.P. # Electromagnetic scattering for multilayered spheres: # recursive algorithms # Radio Science 1991. V. 26. P. 1393-1401. # Voshchinnikov N.V., Mathis J.S. # Calculating Cross Sections of Composite Interstellar Grains # Astrophys. J. 1999. V. 526. #1. # The test consist in 5 layers with the following parameters # m1=1.8 i1.7 # m2=0.8 i0.7 # m3=1.2 i0.09 # m4=2.8 i0.2 # m5=1.5 i0.4 # v1/Vt=0.1 # v2/Vt=0.26 # v3/Vt=0.044 # v4/Vt=0.3666 import scattnlay import os from scattnlay import scattnlay import numpy as np size = np.linspace(0.1, 100., 1000) x = np.vstack(( 0.1**(1.0/3.0)*size, 0.36**(1.0/3.0)*size, 0.404**(1.0/3.0)*size, 0.7706**(1.0/3.0)*size, size)).transpose() m = np.array((1.8 + 1.7j, 0.8 + 0.7j, 1.2 + 0.09j, 2.8 + 0.2j, 1.5 + 0.4j), dtype = np.complex128) terms, Qext, Qsca, Qabs, Qbk, Qpr, g, Albedo, S1, S2 = scattnlay(x, m) result = np.vstack((x[:, 4], Qext, Qsca, Qabs, Qbk, Qpr, g, Albedo)).transpose() try: import matplotlib.pyplot as plt plt.figure(1) plt.subplot(311) plt.plot(x[:, 4], Qext, 'k') plt.ylabel('Qext') plt.subplot(312) plt.plot(x[:, 4], Qsca, 'r') plt.ylabel('Qsca') plt.subplot(313) plt.plot(x[:, 4], Albedo, 'g') plt.ylabel('Albedo') plt.xlabel('X') plt.show() finally: np.savetxt("test01.txt", result, fmt = "%.5f") print(result)