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- #!/usr/bin/env python
- # -*- coding: UTF-8 -*-
- #
- # Copyright (C) 2009-2015 Ovidio Peña Rodríguez <ovidio@bytesfall.com>
- #
- # 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 the following reference:
- # [1] O. Pena and U. Pal, "Scattering of electromagnetic radiation by
- # a multilayered sphere," Computer Physics Communications,
- # vol. 180, Nov. 2009, pp. 2348-2354.
- #
- # You should have received a copy of the GNU General Public License
- # along with this program. If not, see <http://www.gnu.org/licenses/>.
- # 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.arange(0.25, 100.25, 0.25)
- x = np.ones((len(size), 5), dtype = np.float64)
- x[:, 0] = 0.1**(1.0/3.0)*size
- x[:, 1] = 0.36**(1.0/3.0)*size
- x[:, 2] = 0.404**(1.0/3.0)*size
- x[:, 3] = 0.7706**(1.0/3.0)*size
- x[:, 4] = size
- m = np.ones((len(size), 5), dtype = np.complex128)
- m[:, 0] *= 1.8 + 1.7j
- m[:, 1] *= 0.8 + 0.7j
- m[:, 2] *= 1.2 + 0.09j
- m[:, 3] *= 2.8 + 0.2j
- m[:, 4] *= 1.5 + 0.4j
- 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
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