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- # Copyright (C) 2009-2017 Ovidio Pena <ovidio@bytesfall.com>
- # Copyright (C) 2013-2017 Konstantin Ladutenko <kostyfisik@gmail.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/>.
- # distutils: language = c++
- # distutils: sources = nmie.cc
- from __future__ import division
- import numpy as np
- cimport numpy as np
- from libcpp.vector cimport vector
- from libcpp.vector cimport complex
- cdef inline double *npy2c(np.ndarray a):
- assert a.dtype == np.float64
- if not (<object>a).flags["C_CONTIGUOUS"]: # Array is not contiguous, need to make contiguous copy
- a = a.copy('C')
- # Return data pointer
- return <double *>(a.data)
- cdef extern from "py_nmie.h":
- cdef int ScattCoeffs(int L, int pl, vector[double] x, vector[complex] m, int nmax, double anr[], double ani[], double bnr[], double bni[])
- cdef int nMie(int L, int pl, vector[double] x, vector[complex] m, int nTheta, vector[double] Theta, int nmax, double *Qext, double *Qsca, double *Qabs, double *Qbk, double *Qpr, double *g, double *Albedo, double S1r[], double S1i[], double S2r[], double S2i[])
- cdef int nField(int L, int pl, vector[double] x, vector[complex] m, int nmax, int nCoords, vector[double] Xp, vector[double] Yp, vector[double] Zp, double Erx[], double Ery[], double Erz[], double Eix[], double Eiy[], double Eiz[], double Hrx[], double Hry[], double Hrz[], double Hix[], double Hiy[], double Hiz[])
- def scattcoeffs(np.ndarray[np.float64_t, ndim = 2] x, np.ndarray[np.complex128_t, ndim = 2] m, np.int_t nmax, np.int_t pl = -1):
- cdef Py_ssize_t i
- cdef np.ndarray[np.int_t, ndim = 1] terms = np.zeros(x.shape[0], dtype = np.int)
- cdef np.ndarray[np.complex128_t, ndim = 2] an = np.zeros((x.shape[0], nmax), dtype = np.complex128)
- cdef np.ndarray[np.complex128_t, ndim = 2] bn = np.zeros((x.shape[0], nmax), dtype = np.complex128)
- cdef np.ndarray[np.float64_t, ndim = 1] anr
- cdef np.ndarray[np.float64_t, ndim = 1] ani
- cdef np.ndarray[np.float64_t, ndim = 1] bnr
- cdef np.ndarray[np.float64_t, ndim = 1] bni
- for i in range(x.shape[0]):
- anr = np.zeros(nmax, dtype = np.float64)
- ani = np.zeros(nmax, dtype = np.float64)
- bnr = np.zeros(nmax, dtype = np.float64)
- bni = np.zeros(nmax, dtype = np.float64)
- terms[i] = ScattCoeffs(x.shape[1], pl, x[i].copy('C'), m[i].copy('C'), nmax, npy2c(anr), npy2c(ani), npy2c(bnr), npy2c(bni))
- an[i] = anr.copy('C') + 1.0j*ani.copy('C')
- bn[i] = bnr.copy('C') + 1.0j*bni.copy('C')
- return terms, an, bn
- def scattnlay(np.ndarray[np.float64_t, ndim = 2] x, np.ndarray[np.complex128_t, ndim = 2] m, np.ndarray[np.float64_t, ndim = 1] theta = np.zeros(0, dtype = np.float64), np.int_t nmax = -1, np.int_t pl = -1):
- cdef Py_ssize_t i
- cdef np.ndarray[np.int_t, ndim = 1] terms = np.zeros(x.shape[0], dtype = np.int)
- cdef np.ndarray[np.float64_t, ndim = 1] Qext = np.zeros(x.shape[0], dtype = np.float64)
- cdef np.ndarray[np.float64_t, ndim = 1] Qabs = np.zeros(x.shape[0], dtype = np.float64)
- cdef np.ndarray[np.float64_t, ndim = 1] Qsca = np.zeros(x.shape[0], dtype = np.float64)
- cdef np.ndarray[np.float64_t, ndim = 1] Qbk = np.zeros(x.shape[0], dtype = np.float64)
- cdef np.ndarray[np.float64_t, ndim = 1] Qpr = np.zeros(x.shape[0], dtype = np.float64)
- cdef np.ndarray[np.float64_t, ndim = 1] g = np.zeros(x.shape[0], dtype = np.float64)
- cdef np.ndarray[np.float64_t, ndim = 1] Albedo = np.zeros(x.shape[0], dtype = np.float64)
- cdef np.ndarray[np.complex128_t, ndim = 2] S1 = np.zeros((x.shape[0], theta.shape[0]), dtype = np.complex128)
- cdef np.ndarray[np.complex128_t, ndim = 2] S2 = np.zeros((x.shape[0], theta.shape[0]), dtype = np.complex128)
- cdef np.ndarray[np.float64_t, ndim = 1] S1r
- cdef np.ndarray[np.float64_t, ndim = 1] S1i
- cdef np.ndarray[np.float64_t, ndim = 1] S2r
- cdef np.ndarray[np.float64_t, ndim = 1] S2i
- for i in range(x.shape[0]):
- S1r = np.zeros(theta.shape[0], dtype = np.float64)
- S1i = np.zeros(theta.shape[0], dtype = np.float64)
- S2r = np.zeros(theta.shape[0], dtype = np.float64)
- S2i = np.zeros(theta.shape[0], dtype = np.float64)
- terms[i] = nMie(x.shape[1], pl, x[i].copy('C'), m[i].copy('C'), theta.shape[0], theta.copy('C'), nmax, &Qext[i], &Qsca[i], &Qabs[i], &Qbk[i], &Qpr[i], &g[i], &Albedo[i], npy2c(S1r), npy2c(S1i), npy2c(S2r), npy2c(S2i))
- S1[i] = S1r.copy('C') + 1.0j*S1i.copy('C')
- S2[i] = S2r.copy('C') + 1.0j*S2i.copy('C')
- return terms, Qext, Qsca, Qabs, Qbk, Qpr, g, Albedo, S1, S2
- def fieldnlay(np.ndarray[np.float64_t, ndim = 2] x, np.ndarray[np.complex128_t, ndim = 2] m, np.ndarray[np.float64_t, ndim = 2] coords, np.int_t nmax = -1, np.int_t pl = -1):
- cdef Py_ssize_t i
- cdef np.ndarray[np.int_t, ndim = 1] terms = np.zeros(x.shape[0], dtype = np.int)
- cdef np.ndarray[np.complex128_t, ndim = 3] E = np.zeros((x.shape[0], coords.shape[0], 3), dtype = np.complex128)
- cdef np.ndarray[np.complex128_t, ndim = 3] H = np.zeros((x.shape[0], coords.shape[0], 3), dtype = np.complex128)
- cdef np.ndarray[np.float64_t, ndim = 1] Erx
- cdef np.ndarray[np.float64_t, ndim = 1] Ery
- cdef np.ndarray[np.float64_t, ndim = 1] Erz
- cdef np.ndarray[np.float64_t, ndim = 1] Eix
- cdef np.ndarray[np.float64_t, ndim = 1] Eiy
- cdef np.ndarray[np.float64_t, ndim = 1] Eiz
- cdef np.ndarray[np.float64_t, ndim = 1] Hrx
- cdef np.ndarray[np.float64_t, ndim = 1] Hry
- cdef np.ndarray[np.float64_t, ndim = 1] Hrz
- cdef np.ndarray[np.float64_t, ndim = 1] Hix
- cdef np.ndarray[np.float64_t, ndim = 1] Hiy
- cdef np.ndarray[np.float64_t, ndim = 1] Hiz
- for i in range(x.shape[0]):
- Erx = np.zeros(coords.shape[0], dtype = np.float64)
- Ery = np.zeros(coords.shape[0], dtype = np.float64)
- Erz = np.zeros(coords.shape[0], dtype = np.float64)
- Eix = np.zeros(coords.shape[0], dtype = np.float64)
- Eiy = np.zeros(coords.shape[0], dtype = np.float64)
- Eiz = np.zeros(coords.shape[0], dtype = np.float64)
- Hrx = np.zeros(coords.shape[0], dtype = np.float64)
- Hry = np.zeros(coords.shape[0], dtype = np.float64)
- Hrz = np.zeros(coords.shape[0], dtype = np.float64)
- Hix = np.zeros(coords.shape[0], dtype = np.float64)
- Hiy = np.zeros(coords.shape[0], dtype = np.float64)
- Hiz = np.zeros(coords.shape[0], dtype = np.float64)
- terms[i] = nField(x.shape[1], pl, x[i].copy('C'), m[i].copy('C'), nmax, coords.shape[0], coords[:, 0].copy('C'), coords[:, 1].copy('C'), coords[:, 2].copy('C'), npy2c(Erx), npy2c(Ery), npy2c(Erz), npy2c(Eix), npy2c(Eiy), npy2c(Eiz), npy2c(Hrx), npy2c(Hry), npy2c(Hrz), npy2c(Hix), npy2c(Hiy), npy2c(Hiz))
- E[i] = np.vstack((Erx.copy('C') + 1.0j*Eix.copy('C'), Ery.copy('C') + 1.0j*Eiy.copy('C'), Erz.copy('C') + 1.0j*Eiz.copy('C'))).transpose()
- H[i] = np.vstack((Hrx.copy('C') + 1.0j*Hix.copy('C'), Hry.copy('C') + 1.0j*Hiy.copy('C'), Hrz.copy('C') + 1.0j*Hiz.copy('C'))).transpose()
- return terms, E, H
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