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#!/usr/bin/env python
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#
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# TrouNoir model using PyOpenCL
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#
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# CC BY-NC-SA 2019 : <emmanuel.quemener@ens-lyon.fr>
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#
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# Thanks to Andreas Klockner for PyOpenCL:
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# http://mathema.tician.de/software/pyopencl
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#
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# Original code programmed in Fortran 77 in mars 1994
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# for Practical Work of Numerical Simulation
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# DEA (old Master2) in astrophysics and spatial techniques in Meudon
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# by Herve Aussel & Emmanuel Quemener
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#
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# Conversion in C done by Emmanuel Quemener in august 1997
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# GPUfication in OpenCL under Python in july 2019
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#
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# Thanks to :
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#
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# - Herve Aussel for his part of code of black body spectrum
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# - Didier Pelat for his help to perform this work
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# - Jean-Pierre Luminet for his article published in 1979
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# - Numerical Recipies for Runge Kutta recipies
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# - Luc Blanchet for his disponibility about my questions in General Relativity
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# - Pierre Lena for his passion about science and vulgarisation
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import pyopencl as cl |
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import numpy |
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import time,string |
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from numpy.random import randint as nprnd |
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import sys |
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import getopt |
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import matplotlib.pyplot as plt |
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from socket import gethostname |
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def DictionariesAPI(): |
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PhysicsList={'Einstein':0,'Newton':1} |
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return(PhysicsList)
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BlobOpenCL= """
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#define PI (float)3.14159265359
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#define nbr 256
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#define EINSTEIN 0
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#define NEWTON 1
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float atanp(float x,float y)
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{
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float angle;
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angle=atan2(y,x);
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if (angle<0.e0f)
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{
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angle+=(float)2.e0f*PI;
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}
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return angle;
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}
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float f(float v)
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{
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return v;
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}
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#if PHYSICS == NEWTON
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float g(float u,float m,float b)
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{
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return (-u);
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}
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#else
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float g(float u,float m,float b)
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{
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return (3.e0f*m/b*pow(u,2)-u);
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}
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#endif
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void calcul(float *us,float *vs,float up,float vp,
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float h,float m,float b)
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{
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float c0,c1,c2,c3,d0,d1,d2,d3;
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c0=h*f(vp);
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c1=h*f(vp+c0/2.);
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c2=h*f(vp+c1/2.);
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c3=h*f(vp+c2);
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d0=h*g(up,m,b);
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d1=h*g(up+d0/2.,m,b);
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d2=h*g(up+d1/2.,m,b);
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d3=h*g(up+d2,m,b);
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*us=up+(c0+2.*c1+2.*c2+c3)/6.;
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*vs=vp+(d0+2.*d1+2.*d2+d3)/6.;
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}
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void rungekutta(float *ps,float *us,float *vs,
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float pp,float up,float vp,
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float h,float m,float b)
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{
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calcul(us,vs,up,vp,h,m,b);
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*ps=pp+h;
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}
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float decalage_spectral(float r,float b,float phi,
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float tho,float m)
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{
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return (sqrt(1-3*m/r)/(1+sqrt(m/pow(r,3))*b*sin(tho)*sin(phi)));
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}
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float spectre(float rf,int q,float b,float db,
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float h,float r,float m,float bss)
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{
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float flx;
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flx=exp(q*log(r/m))*pow(rf,4)*b*db*h;
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return(flx);
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}
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float spectre_cn(float rf32,float b32,float db32,
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float h32,float r32,float m32,float bss32)
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{
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#define MYFLOAT double
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MYFLOAT rf=(MYFLOAT)(rf32);
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MYFLOAT b=(MYFLOAT)(b32);
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MYFLOAT db=(MYFLOAT)(db32);
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MYFLOAT h=(MYFLOAT)(h32);
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MYFLOAT r=(MYFLOAT)(r32);
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MYFLOAT m=(MYFLOAT)(m32);
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MYFLOAT bss=(MYFLOAT)(bss32);
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MYFLOAT flx;
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MYFLOAT nu_rec,nu_em,qu,temp_em,flux_int;
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int fi,posfreq;
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#define planck 6.62e-34
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#define k 1.38e-23
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#define c2 9.e16
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#define temp 3.e7
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#define m_point 1.
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#define lplanck (log(6.62)-34.*log(10.))
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#define lk (log(1.38)-23.*log(10.))
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#define lc2 (log(9.)+16.*log(10.))
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MYFLOAT v=1.-3./r;
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qu=1./sqrt((1.-3./r)*r)*(sqrt(r)-sqrt(6.)+sqrt(3.)/2.*log((sqrt(r)+sqrt(3.))/(sqrt(r)-sqrt(3.))* 0.17157287525380988 ));
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temp_em=temp*sqrt(m)*exp(0.25*log(m_point)-0.75*log(r)-0.125*log(v)+0.25*log(fabs(qu)));
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flux_int=0.;
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flx=0.;
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for (fi=0;fi<nbr;fi++)
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{
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nu_em=bss*(MYFLOAT)fi/(MYFLOAT)nbr;
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nu_rec=nu_em*rf;
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posfreq=(int)(nu_rec*(MYFLOAT)nbr/bss);
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if ((posfreq>0)&&(posfreq<nbr))
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{
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// Initial version
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// flux_int=2.*planck/c2*pow(nu_em,3)/(exp(planck*nu_em/(k*temp_em))-1.);
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// Version with log used
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//flux_int=2.*exp(lplanck-lc2+3.*log(nu_em))/(exp(exp(lplanck-lk+log(nu_em/temp_em)))-1.);
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// flux_int*=pow(rf,3)*b*db*h;
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//flux_int*=exp(3.*log(rf))*b*db*h;
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flux_int=2.*exp(lplanck-lc2+3.*log(nu_em))/(exp(exp(lplanck-lk+log(nu_em/temp_em)))-1.)*exp(3.*log(rf))*b*db*h;
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flx+=flux_int;
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}
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}
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return((float)(flx));
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}
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void impact(float phi,float r,float b,float tho,float m,
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float *zp,float *fp,
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int q,float db,
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float h,int raie)
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{
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float flx,rf,bss;
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rf=decalage_spectral(r,b,phi,tho,m);
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if (raie==0)
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{
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bss=1.e19;
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flx=spectre_cn(rf,b,db,h,r,m,bss);
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}
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else
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{
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bss=2.;
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flx=spectre(rf,q,b,db,h,r,m,bss);
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}
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*zp=1./rf;
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*fp=flx;
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}
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__kernel void EachPixel(__global float *zImage,__global float *fImage,
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float Mass,float InternalRadius,
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float ExternalRadius,float Angle,
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int Line)
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{
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uint xi=(uint)get_global_id(0);
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uint yi=(uint)get_global_id(1);
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uint sizex=(uint)get_global_size(0);
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uint sizey=(uint)get_global_size(1);
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// Perform trajectory for each pixel, exit on hit
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float m,rs,ri,re,tho;
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int q,raie;
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m=Mass;
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rs=2.*m;
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ri=InternalRadius;
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re=ExternalRadius;
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tho=Angle;
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q=-2;
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raie=Line;
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float d,bmx,db,b,h;
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float rp[2048];
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float phi,thi,phd,php,nr,r;
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int nh;
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float zp,fp;
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// Autosize for image
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bmx=1.25*re;
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b=0.;
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h=4.e0f*PI/(float)2048;
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// set origin as center of image
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float x=(float)xi-(float)(sizex/2)+(float)5e-1f;
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float y=(float)yi-(float)(sizey/2)+(float)5e-1f;
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// angle extracted from cylindric symmetry
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phi=atanp(x,y);
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phd=atanp(cos(phi)*sin(tho),cos(tho));
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float up,vp,pp,us,vs,ps;
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// impact parameter
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b=sqrt(x*x+y*y)*(float)2.e0f/(float)sizex*bmx;
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// step of impact parameter;
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// db=bmx/(float)(sizex/2);
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db=bmx/(float)(sizex);
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up=0.;
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vp=1.;
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pp=0.;
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nh=0;
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rungekutta(&ps,&us,&vs,pp,up,vp,h,m,b);
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rp[nh]=fabs(b/us);
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int ExitOnImpact=0;
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do
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{
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nh++;
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pp=ps;
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up=us;
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vp=vs;
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rungekutta(&ps,&us,&vs,pp,up,vp,h,m,b);
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rp[nh]=fabs(b/us);
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ExitOnImpact = ((fmod(pp,PI)<fmod(phd,PI))&&(fmod(ps,PI)>fmod(phd,PI)))&&(rp[nh]>ri)&&(rp[nh]<re)?1:0;
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} while ((rp[nh]>=rs)&&(rp[nh]<=rp[0])&&(ExitOnImpact==0));
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if (ExitOnImpact==1) {
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impact(phi,rp[nh-1],b,tho,m,&zp,&fp,q,db,h,raie);
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}
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else
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{
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zp=0.;
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fp=0.;
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}
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barrier(CLK_GLOBAL_MEM_FENCE);
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zImage[yi+sizex*xi]=(float)zp;
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fImage[yi+sizex*xi]=(float)fp;
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}
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__kernel void Pixel(__global float *zImage,__global float *fImage,
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__global float *Trajectories,__global int *IdLast,
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uint ImpactParameter,uint TrackPoints,
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float Mass,float InternalRadius,
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float ExternalRadius,float Angle,
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int Line)
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{
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uint xi=(uint)get_global_id(0);
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uint yi=(uint)get_global_id(1);
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uint sizex=(uint)get_global_size(0);
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uint sizey=(uint)get_global_size(1);
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// Perform trajectory for each pixel
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float m,rs,ri,re,tho;
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int q,raie;
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m=Mass;
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rs=2.*m;
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ri=InternalRadius;
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re=ExternalRadius;
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tho=Angle;
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q=-2;
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raie=Line;
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float d,bmx,db,b,h;
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float phi,thi,phd,php,nr,r;
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int nh;
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float zp=0,fp=0;
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// Autosize for image, 25% greater than external radius
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bmx=1.25*re;
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// Angular step of integration
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h=4.e0f*PI/(float)TrackPoints;
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// Step of Impact Parameter
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db=bmx/(2.e0*(float)ImpactParameter);
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// set origin as center of image
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float x=(float)xi-(float)(sizex/2)+(float)5e-1f;
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float y=(float)yi-(float)(sizey/2)+(float)5e-1f;
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// angle extracted from cylindric symmetry
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phi=atanp(x,y);
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phd=atanp(cos(phi)*sin(tho),cos(tho));
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// Real Impact Parameter
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b=sqrt(x*x+y*y)*bmx/(float)ImpactParameter;
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// Integer Impact Parameter
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uint bi=(uint)sqrt(x*x+y*y);
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int HalfLap=0,ExitOnImpact=0,ni;
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if (bi<ImpactParameter)
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{
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do
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{
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php=phd+(float)HalfLap*PI;
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nr=php/h;
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ni=(int)nr;
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if (ni<IdLast[bi])
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{
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r=(Trajectories[bi*TrackPoints+ni+1]-Trajectories[bi*TrackPoints+ni])*(nr-ni*1.)+Trajectories[bi*TrackPoints+ni];
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}
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else
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{
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r=Trajectories[bi*TrackPoints+ni];
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}
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if ((r<=re)&&(r>=ri))
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{
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ExitOnImpact=1;
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impact(phi,r,b,tho,m,&zp,&fp,q,db,h,raie);
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}
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HalfLap++;
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} while ((HalfLap<=2)&&(ExitOnImpact==0));
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}
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barrier(CLK_GLOBAL_MEM_FENCE);
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zImage[yi+sizex*xi]=zp;
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fImage[yi+sizex*xi]=fp;
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}
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__kernel void Circle(__global float *Trajectories,__global int *IdLast,
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__global float *zImage,__global float *fImage,
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int TrackPoints,
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float Mass,float InternalRadius,
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float ExternalRadius,float Angle,
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int Line)
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{
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// Integer Impact Parameter ID
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int bi=get_global_id(0);
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// Integer points on circle
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int i=get_global_id(1);
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// Integer Impact Parameter Size (half of image)
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int bmaxi=get_global_size(0);
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// Integer Points on circle
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int imx=get_global_size(1);
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// Perform trajectory for each pixel
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float m,rs,ri,re,tho;
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int q,raie;
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m=Mass;
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rs=2.*m;
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ri=InternalRadius;
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re=ExternalRadius;
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tho=Angle;
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raie=Line;
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float bmx,db,b,h;
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float phi,thi,phd;
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int nh;
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float zp=0,fp=0;
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// Autosize for image
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bmx=1.25*re;
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// Angular step of integration
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h=4.e0f*PI/(float)TrackPoints;
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// impact parameter
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b=(float)bi/(float)bmaxi*bmx;
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db=bmx/(2.e0*(float)bmaxi);
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phi=2.*PI/(float)imx*(float)i;
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phd=atanp(cos(phi)*sin(tho),cos(tho));
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int yi=(int)((float)bi*sin(phi))+bmaxi;
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int xi=(int)((float)bi*cos(phi))+bmaxi;
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int HalfLap=0,ExitOnImpact=0,ni;
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float php,nr,r;
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432 |
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do
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{
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php=phd+(float)HalfLap*PI;
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nr=php/h;
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ni=(int)nr;
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if (ni<IdLast[bi])
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{
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r=(Trajectories[bi*TrackPoints+ni+1]-Trajectories[bi*TrackPoints+ni])*(nr-ni*1.)+Trajectories[bi*TrackPoints+ni];
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}
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else
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{
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r=Trajectories[bi*TrackPoints+ni];
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}
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if ((r<=re)&&(r>=ri))
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{
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ExitOnImpact=1;
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impact(phi,r,b,tho,m,&zp,&fp,q,db,h,raie);
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}
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HalfLap++;
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} while ((HalfLap<=2)&&(ExitOnImpact==0));
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zImage[yi+2*bmaxi*xi]=zp;
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fImage[yi+2*bmaxi*xi]=fp;
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barrier(CLK_GLOBAL_MEM_FENCE);
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}
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|
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__kernel void Trajectory(__global float *Trajectories,
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__global int *IdLast,int TrackPoints,
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float Mass,float InternalRadius,
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float ExternalRadius,float Angle,
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int Line)
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{
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// Integer Impact Parameter ID
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int bi=get_global_id(0);
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// Integer Impact Parameter Size (half of image)
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int bmaxi=get_global_size(0);
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|
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// Perform trajectory for each pixel
|
476 |
|
477 |
float m,rs,ri,re,tho;
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int raie,q;
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479 |
|
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m=Mass;
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rs=2.*m;
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ri=InternalRadius;
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re=ExternalRadius;
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tho=Angle;
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q=-2;
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raie=Line;
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487 |
|
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float d,bmx,db,b,h;
|
489 |
float phi,thi,phd,php,nr,r;
|
490 |
int nh;
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491 |
float zp,fp;
|
492 |
|
493 |
// Autosize for image
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494 |
bmx=1.25*re;
|
495 |
|
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// Angular step of integration
|
497 |
h=4.e0f*PI/(float)TrackPoints;
|
498 |
|
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// impact parameter
|
500 |
b=(float)bi/(float)bmaxi*bmx;
|
501 |
|
502 |
float up,vp,pp,us,vs,ps;
|
503 |
|
504 |
up=0.;
|
505 |
vp=1.;
|
506 |
|
507 |
pp=0.;
|
508 |
nh=0;
|
509 |
|
510 |
rungekutta(&ps,&us,&vs,pp,up,vp,h,m,b);
|
511 |
|
512 |
// b versus us
|
513 |
float bvus=fabs(b/us);
|
514 |
float bvus0=bvus;
|
515 |
Trajectories[bi*TrackPoints+nh]=bvus;
|
516 |
|
517 |
do
|
518 |
{
|
519 |
nh++;
|
520 |
pp=ps;
|
521 |
up=us;
|
522 |
vp=vs;
|
523 |
rungekutta(&ps,&us,&vs,pp,up,vp,h,m,b);
|
524 |
bvus=fabs(b/us);
|
525 |
Trajectories[bi*TrackPoints+nh]=bvus;
|
526 |
|
527 |
} while ((bvus>=rs)&&(bvus<=bvus0));
|
528 |
|
529 |
IdLast[bi]=nh;
|
530 |
|
531 |
barrier(CLK_GLOBAL_MEM_FENCE);
|
532 |
|
533 |
}
|
534 |
"""
|
535 |
|
536 |
# def ImageOutput(sigma,prefix):
|
537 |
# from PIL import Image
|
538 |
# Max=sigma.max()
|
539 |
# Min=sigma.min()
|
540 |
|
541 |
# # Normalize value as 8bits Integer
|
542 |
# SigmaInt=(255*(sigma-Min)/(Max-Min)).astype('uint8')
|
543 |
# image = Image.fromarray(SigmaInt)
|
544 |
# image.save("%s.jpg" % prefix)
|
545 |
|
546 |
def ImageOutput(sigma,prefix,Colors): |
547 |
import matplotlib.pyplot as plt |
548 |
if Colors == 'Red2Yellow': |
549 |
plt.imsave("%s.png" % prefix, sigma, cmap='afmhot') |
550 |
else:
|
551 |
plt.imsave("%s.png" % prefix, sigma, cmap='Greys_r') |
552 |
|
553 |
def BlackHoleCL(zImage,fImage,InputCL): |
554 |
|
555 |
kernel_params = {} |
556 |
|
557 |
print(InputCL) |
558 |
|
559 |
Device=InputCL['Device']
|
560 |
GpuStyle=InputCL['GpuStyle']
|
561 |
VariableType=InputCL['VariableType']
|
562 |
Size=InputCL['Size']
|
563 |
Mass=InputCL['Mass']
|
564 |
InternalRadius=InputCL['InternalRadius']
|
565 |
ExternalRadius=InputCL['ExternalRadius']
|
566 |
Angle=InputCL['Angle']
|
567 |
Method=InputCL['Method']
|
568 |
TrackPoints=InputCL['TrackPoints']
|
569 |
Physics=InputCL['Physics']
|
570 |
|
571 |
PhysicsList=DictionariesAPI() |
572 |
|
573 |
if InputCL['BlackBody']: |
574 |
# Spectrum is Black Body one
|
575 |
Line=0
|
576 |
else:
|
577 |
# Spectrum is Monochromatic Line one
|
578 |
Line=1
|
579 |
|
580 |
Trajectories=numpy.zeros((InputCL['Size']/2,InputCL['TrackPoints']), |
581 |
dtype=numpy.float32) |
582 |
IdLast=numpy.zeros(InputCL['Size']/2,dtype=numpy.int32) |
583 |
|
584 |
# Je detecte un peripherique GPU dans la liste des peripheriques
|
585 |
Id=0
|
586 |
HasXPU=False
|
587 |
for platform in cl.get_platforms(): |
588 |
for device in platform.get_devices(): |
589 |
if Id==Device:
|
590 |
XPU=device |
591 |
print "CPU/GPU selected: ",device.name.lstrip() |
592 |
HasXPU=True
|
593 |
Id+=1
|
594 |
|
595 |
if HasXPU==False: |
596 |
print "No XPU #%i found in all of %i devices, sorry..." % (Device,Id-1) |
597 |
sys.exit() |
598 |
|
599 |
ctx = cl.Context([XPU]) |
600 |
queue = cl.CommandQueue(ctx, |
601 |
properties=cl.command_queue_properties.PROFILING_ENABLE) |
602 |
|
603 |
|
604 |
# BlackHoleCL = cl.Program(ctx,KERNEL_CODE.substitute(kernel_params)).build()
|
605 |
|
606 |
BuildOptions="-cl-mad-enable -DPHYSICS=%i " % (PhysicsList[Physics])
|
607 |
|
608 |
BlackHoleCL = cl.Program(ctx,BlobOpenCL).build(options = BuildOptions) |
609 |
|
610 |
# Je recupere les flag possibles pour les buffers
|
611 |
mf = cl.mem_flags |
612 |
|
613 |
TrajectoriesCL = cl.Buffer(ctx, mf.WRITE_ONLY | mf.COPY_HOST_PTR, hostbuf=Trajectories) |
614 |
zImageCL = cl.Buffer(ctx, mf.WRITE_ONLY | mf.COPY_HOST_PTR, hostbuf=zImage) |
615 |
fImageCL = cl.Buffer(ctx, mf.WRITE_ONLY | mf.COPY_HOST_PTR, hostbuf=fImage) |
616 |
IdLastCL = cl.Buffer(ctx, mf.WRITE_ONLY | mf.COPY_HOST_PTR, hostbuf=IdLast) |
617 |
|
618 |
start_time=time.time() |
619 |
|
620 |
if Method=='EachPixel': |
621 |
CLLaunch=BlackHoleCL.EachPixel(queue,(zImage.shape[0],zImage.shape[1]), |
622 |
None,zImageCL,fImageCL,
|
623 |
numpy.float32(Mass), |
624 |
numpy.float32(InternalRadius), |
625 |
numpy.float32(ExternalRadius), |
626 |
numpy.float32(Angle), |
627 |
numpy.int32(Line)) |
628 |
CLLaunch.wait() |
629 |
elif Method=='TrajectoCircle': |
630 |
CLLaunch=BlackHoleCL.Trajectory(queue,(Trajectories.shape[0],),
|
631 |
None,TrajectoriesCL,IdLastCL,
|
632 |
numpy.uint32(Trajectories.shape[1]),
|
633 |
numpy.float32(Mass), |
634 |
numpy.float32(InternalRadius), |
635 |
numpy.float32(ExternalRadius), |
636 |
numpy.float32(Angle), |
637 |
numpy.int32(Line)) |
638 |
|
639 |
CLLaunch=BlackHoleCL.Circle(queue,(Trajectories.shape[0],
|
640 |
zImage.shape[0]*4),None, |
641 |
TrajectoriesCL,IdLastCL, |
642 |
zImageCL,fImageCL, |
643 |
numpy.uint32(Trajectories.shape[1]),
|
644 |
numpy.float32(Mass), |
645 |
numpy.float32(InternalRadius), |
646 |
numpy.float32(ExternalRadius), |
647 |
numpy.float32(Angle), |
648 |
numpy.int32(Line)) |
649 |
CLLaunch.wait() |
650 |
else:
|
651 |
CLLaunch=BlackHoleCL.Trajectory(queue,(Trajectories.shape[0],),
|
652 |
None,TrajectoriesCL,IdLastCL,
|
653 |
numpy.uint32(Trajectories.shape[1]),
|
654 |
numpy.float32(Mass), |
655 |
numpy.float32(InternalRadius), |
656 |
numpy.float32(ExternalRadius), |
657 |
numpy.float32(Angle), |
658 |
numpy.int32(Line)) |
659 |
|
660 |
CLLaunch=BlackHoleCL.Pixel(queue,(zImage.shape[0],
|
661 |
zImage.shape[1]),None, |
662 |
zImageCL,fImageCL,TrajectoriesCL,IdLastCL, |
663 |
numpy.uint32(Trajectories.shape[0]),
|
664 |
numpy.uint32(Trajectories.shape[1]),
|
665 |
numpy.float32(Mass), |
666 |
numpy.float32(InternalRadius), |
667 |
numpy.float32(ExternalRadius), |
668 |
numpy.float32(Angle), |
669 |
numpy.int32(Line)) |
670 |
CLLaunch.wait() |
671 |
|
672 |
elapsed = time.time()-start_time |
673 |
print("\nElapsed Time : %f" % elapsed)
|
674 |
|
675 |
cl.enqueue_copy(queue,zImage,zImageCL).wait() |
676 |
cl.enqueue_copy(queue,fImage,fImageCL).wait() |
677 |
cl.enqueue_copy(queue,Trajectories,TrajectoriesCL).wait() |
678 |
cl.enqueue_copy(queue,IdLast,IdLastCL).wait() |
679 |
|
680 |
zMaxPosition=numpy.where(zImage[:,:]==zImage.max()) |
681 |
fMaxPosition=numpy.where(fImage[:,:]==fImage.max()) |
682 |
print("Z max @(%i,%i) : %f" % (zMaxPosition[0],zMaxPosition[1],zImage.max())) |
683 |
print("Flux max @(%i,%i) : %f\n" % (fMaxPosition[0],fMaxPosition[1],fImage.max())) |
684 |
zImageCL.release() |
685 |
fImageCL.release() |
686 |
|
687 |
TrajectoriesCL.release() |
688 |
IdLastCL.release() |
689 |
|
690 |
return(elapsed)
|
691 |
|
692 |
if __name__=='__main__': |
693 |
|
694 |
GpuStyle = 'OpenCL'
|
695 |
Mass = 1.
|
696 |
# Internal Radius 3 times de Schwarzschild Radius
|
697 |
InternalRadius=6.*Mass
|
698 |
#
|
699 |
ExternalRadius=12.
|
700 |
#
|
701 |
# Angle with normal to disc 10 degrees
|
702 |
Angle = numpy.pi/180.*(90.-10.) |
703 |
# Radiation of disc : BlackBody or Monochromatic
|
704 |
BlackBody = False
|
705 |
# Size of image
|
706 |
Size=256
|
707 |
# Variable Type
|
708 |
VariableType='FP32'
|
709 |
# ?
|
710 |
q=-2
|
711 |
# Method of resolution
|
712 |
Method='TrajectoPixel'
|
713 |
# Colors for output image
|
714 |
Colors='Greyscale'
|
715 |
# Physics
|
716 |
Physics='Einstein'
|
717 |
# No output as image
|
718 |
NoImage = False
|
719 |
|
720 |
HowToUse='%s -h [Help] -b [BlackBodyEmission] -n [NoImage] -p <Einstein/Newton> -s <SizeInPixels> -m <Mass> -i <DiscInternalRadius> -x <DiscExternalRadius> -a <AngleAboveDisc> -d <DeviceId> -c <Greyscale/Red2Yellow> -g <CUDA/OpenCL> -t <EachPixel/TrajectoCircle/TrajectoPixel> -v <FP32/FP64>'
|
721 |
|
722 |
try:
|
723 |
opts, args = getopt.getopt(sys.argv[1:],"hbns:m:i:x:a:d:g:v:t:c:p:",["blackbody","noimage","camera","size=","mass=","internal=","external=","angle=","device=","gpustyle=","variabletype=","method=","colors=","physics="]) |
724 |
except getopt.GetoptError:
|
725 |
print(HowToUse % sys.argv[0])
|
726 |
sys.exit(2)
|
727 |
|
728 |
# List of Devices
|
729 |
Devices=[] |
730 |
Alu={} |
731 |
|
732 |
for opt, arg in opts: |
733 |
if opt == '-h': |
734 |
print(HowToUse % sys.argv[0])
|
735 |
|
736 |
print("\nInformations about devices detected under OpenCL API:")
|
737 |
# For PyOpenCL import
|
738 |
try:
|
739 |
import pyopencl as cl |
740 |
Id=0
|
741 |
for platform in cl.get_platforms(): |
742 |
for device in platform.get_devices(): |
743 |
#deviceType=cl.device_type.to_string(device.type)
|
744 |
deviceType="xPU"
|
745 |
print("Device #%i from %s of type %s : %s" % (Id,platform.vendor.lstrip(),deviceType,device.name.lstrip()))
|
746 |
Id=Id+1
|
747 |
|
748 |
except:
|
749 |
print("Your platform does not seem to support OpenCL")
|
750 |
|
751 |
print("\nInformations about devices detected under CUDA API:")
|
752 |
# For PyCUDA import
|
753 |
try:
|
754 |
import pycuda.driver as cuda |
755 |
cuda.init() |
756 |
for Id in range(cuda.Device.count()): |
757 |
device=cuda.Device(Id) |
758 |
print("Device #%i of type GPU : %s" % (Id,device.name()))
|
759 |
print
|
760 |
except:
|
761 |
print("Your platform does not seem to support CUDA")
|
762 |
|
763 |
sys.exit() |
764 |
|
765 |
elif opt in ("-d", "--device"): |
766 |
# Devices.append(int(arg))
|
767 |
Device=int(arg)
|
768 |
elif opt in ("-g", "--gpustyle"): |
769 |
GpuStyle = arg |
770 |
elif opt in ("-v", "--variabletype"): |
771 |
VariableType = arg |
772 |
elif opt in ("-s", "--size"): |
773 |
Size = int(arg)
|
774 |
elif opt in ("-m", "--mass"): |
775 |
Mass = float(arg)
|
776 |
elif opt in ("-i", "--internal"): |
777 |
InternalRadius = float(arg)
|
778 |
elif opt in ("-e", "--external"): |
779 |
ExternalRadius = float(arg)
|
780 |
elif opt in ("-a", "--angle"): |
781 |
Angle = numpy.pi/180.*(90.-float(arg)) |
782 |
elif opt in ("-b", "--blackbody"): |
783 |
BlackBody = True
|
784 |
elif opt in ("-n", "--noimage"): |
785 |
NoImage = True
|
786 |
elif opt in ("-t", "--method"): |
787 |
Method = arg |
788 |
elif opt in ("-c", "--colors"): |
789 |
Colors = arg |
790 |
elif opt in ("-p", "--physics"): |
791 |
Physics = arg |
792 |
|
793 |
print("Device Identification selected : %s" % Device)
|
794 |
print("GpuStyle used : %s" % GpuStyle)
|
795 |
print("VariableType : %s" % VariableType)
|
796 |
print("Size : %i" % Size)
|
797 |
print("Mass : %f" % Mass)
|
798 |
print("Internal Radius : %f" % InternalRadius)
|
799 |
print("External Radius : %f" % ExternalRadius)
|
800 |
print("Angle with normal of (in radians) : %f" % Angle)
|
801 |
print("Black Body Disc Emission (monochromatic instead) : %s" % BlackBody)
|
802 |
print("Method of resolution : %s" % Method)
|
803 |
print("Colors for output images : %s" % Colors)
|
804 |
print("Physics used for Trajectories : %s" % Physics)
|
805 |
|
806 |
if GpuStyle=='CUDA': |
807 |
print("\nSelection of CUDA device")
|
808 |
try:
|
809 |
# For PyCUDA import
|
810 |
import pycuda.driver as cuda |
811 |
|
812 |
cuda.init() |
813 |
for Id in range(cuda.Device.count()): |
814 |
device=cuda.Device(Id) |
815 |
print("Device #%i of type GPU : %s" % (Id,device.name()))
|
816 |
if Id in Devices: |
817 |
Alu[Id]='GPU'
|
818 |
|
819 |
except ImportError: |
820 |
print("Platform does not seem to support CUDA")
|
821 |
|
822 |
if GpuStyle=='OpenCL': |
823 |
print("\nSelection of OpenCL device")
|
824 |
try:
|
825 |
# For PyOpenCL import
|
826 |
import pyopencl as cl |
827 |
Id=0
|
828 |
for platform in cl.get_platforms(): |
829 |
for device in platform.get_devices(): |
830 |
#deviceType=cl.device_type.to_string(device.type)
|
831 |
deviceType="xPU"
|
832 |
print("Device #%i from %s of type %s : %s" % (Id,platform.vendor.lstrip().rstrip(),deviceType,device.name.lstrip().rstrip()))
|
833 |
|
834 |
if Id in Devices: |
835 |
# Set the Alu as detected Device Type
|
836 |
Alu[Id]=deviceType |
837 |
Id=Id+1
|
838 |
except ImportError: |
839 |
print("Platform does not seem to support OpenCL")
|
840 |
|
841 |
# print(Devices,Alu)
|
842 |
|
843 |
# MyImage=numpy.where(numpy.random.zeros(Size,Size)>0,1,-1).astype(numpy.float32)
|
844 |
TrackPoints=2048
|
845 |
zImage=numpy.zeros((Size,Size),dtype=numpy.float32) |
846 |
fImage=numpy.zeros((Size,Size),dtype=numpy.float32) |
847 |
|
848 |
InputCL={} |
849 |
InputCL['Device']=Device
|
850 |
InputCL['GpuStyle']=GpuStyle
|
851 |
InputCL['VariableType']=VariableType
|
852 |
InputCL['Size']=Size
|
853 |
InputCL['Mass']=Mass
|
854 |
InputCL['InternalRadius']=InternalRadius
|
855 |
InputCL['ExternalRadius']=ExternalRadius
|
856 |
InputCL['Angle']=Angle
|
857 |
InputCL['BlackBody']=BlackBody
|
858 |
InputCL['Method']=Method
|
859 |
InputCL['TrackPoints']=TrackPoints
|
860 |
InputCL['Physics']=Physics
|
861 |
|
862 |
duration=BlackHoleCL(zImage,fImage,InputCL) |
863 |
|
864 |
Hostname=gethostname() |
865 |
Date=time.strftime("%Y%m%d_%H%M%S")
|
866 |
ImageInfo="%s_Device%i_%s_%s" % (Method,Device,Hostname,Date)
|
867 |
|
868 |
|
869 |
if not NoImage: |
870 |
ImageOutput(zImage,"TrouNoirZ_%s" % ImageInfo,Colors)
|
871 |
ImageOutput(fImage,"TrouNoirF_%s" % ImageInfo,Colors)
|