source: sasview/sansmodels/src/c_models/triaxialellipsoid.cpp @ 08648c0

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Last change on this file since 08648c0 was 82c11d3, checked in by Mathieu Doucet <doucetm@…>, 13 years ago

refactored bunch of models

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1/**
2        This software was developed by the University of Tennessee as part of the
3        Distributed Data Analysis of Neutron Scattering Experiments (DANSE)
4        project funded by the US National Science Foundation.
5
6        If you use DANSE applications to do scientific research that leads to
7        publication, we ask that you acknowledge the use of the software with the
8        following sentence:
9
10        "This work benefited from DANSE software developed under NSF award DMR-0520547."
11
12        copyright 2008, University of Tennessee
13 */
14
15/**
16 * Scattering model classes
17 * The classes use the IGOR library found in
18 *   sansmodels/src/libigor
19 *
20 */
21
22#include <math.h>
23#include "parameters.hh"
24#include <stdio.h>
25#include <stdlib.h>
26using namespace std;
27#include "triaxial_ellipsoid.h"
28
29extern "C" {
30#include "libCylinder.h"
31#include "libStructureFactor.h"
32}
33
34typedef struct {
35  double scale;
36  double semi_axisA;
37  double semi_axisB;
38  double semi_axisC;
39  double sldEll;
40  double sldSolv;
41  double background;
42  double axis_theta;
43  double axis_phi;
44  double axis_psi;
45
46} TriaxialEllipsoidParameters;
47
48static double triaxial_ellipsoid_kernel(TriaxialEllipsoidParameters *pars, double q, double alpha, double nu) {
49  double t,a,b,c;
50  double kernel;
51
52  a = pars->semi_axisA ;
53  b = pars->semi_axisB ;
54  c = pars->semi_axisC ;
55
56  t = q * sqrt(a*a*cos(nu)*cos(nu)+b*b*sin(nu)*sin(nu)*sin(alpha)*sin(alpha)+c*c*cos(alpha)*cos(alpha));
57  if (t==0.0){
58    kernel  = 1.0;
59  }else{
60    kernel  = 3.0*(sin(t)-t*cos(t))/(t*t*t);
61  }
62  return kernel*kernel;
63}
64
65
66/**
67 * Function to evaluate 2D scattering function
68 * @param pars: parameters of the triaxial ellipsoid
69 * @param q: q-value
70 * @param q_x: q_x / q
71 * @param q_y: q_y / q
72 * @return: function value
73 */
74static double triaxial_ellipsoid_analytical_2D_scaled(TriaxialEllipsoidParameters *pars, double q, double q_x, double q_y) {
75  double cyl_x, cyl_y, cyl_z, ell_x, ell_y;
76  double q_z;
77  double cos_nu,nu;
78  double alpha, vol, cos_val;
79  double answer;
80  double pi = 4.0*atan(1.0);
81
82  //convert angle degree to radian
83  double theta = pars->axis_theta * pi/180.0;
84  double phi = pars->axis_phi * pi/180.0;
85  double psi = pars->axis_psi * pi/180.0;
86
87  // Cylinder orientation
88  cyl_x = sin(theta) * cos(phi);
89  cyl_y = sin(theta) * sin(phi);
90  cyl_z = cos(theta);
91
92  // q vector
93  q_z = 0.0;
94
95  //dx = 1.0;
96  //dy = 1.0;
97  // Compute the angle btw vector q and the
98  // axis of the cylinder
99  cos_val = cyl_x*q_x + cyl_y*q_y + cyl_z*q_z;
100
101  // The following test should always pass
102  if (fabs(cos_val)>1.0) {
103    printf("cyl_ana_2D: Unexpected error: cos(alpha)>1\n");
104    return 0;
105  }
106
107  // Note: cos(alpha) = 0 and 1 will get an
108  // undefined value from CylKernel
109  alpha = acos( cos_val );
110
111  //ellipse orientation:
112  // the elliptical corss section was transformed and projected
113  // into the detector plane already through sin(alpha)and furthermore psi remains as same
114  // on the detector plane.
115  // So, all we need is to calculate the angle (nu) of the minor axis of the ellipse wrt
116  // the wave vector q.
117
118  //x- y- component on the detector plane.
119  ell_x =  cos(psi);
120  ell_y =  sin(psi);
121
122  // calculate the axis of the ellipse wrt q-coord.
123  cos_nu = ell_x*q_x + ell_y*q_y;
124  nu = acos(cos_nu);
125
126  // Call the IGOR library function to get the kernel
127  answer = triaxial_ellipsoid_kernel(pars, q, alpha, nu);
128
129  // Multiply by contrast^2
130  answer *= (pars->sldEll- pars->sldSolv)*(pars->sldEll- pars->sldSolv);
131
132  //normalize by cylinder volume
133  //NOTE that for this (Fournet) definition of the integral, one must MULTIPLY by Vcyl
134  vol = 4.0* pi/3.0  * pars->semi_axisA * pars->semi_axisB * pars->semi_axisC;
135  answer *= vol;
136  //convert to [cm-1]
137  answer *= 1.0e8;
138  //Scale
139  answer *= pars->scale;
140
141  // add in the background
142  answer += pars->background;
143
144  return answer;
145}
146
147/**
148 * Function to evaluate 2D scattering function
149 * @param pars: parameters of the triaxial ellipsoid
150 * @param q: q-value
151 * @return: function value
152 */
153static double triaxial_ellipsoid_analytical_2DXY(TriaxialEllipsoidParameters *pars, double qx, double qy) {
154  double q;
155  q = sqrt(qx*qx+qy*qy);
156  return triaxial_ellipsoid_analytical_2D_scaled(pars, q, qx/q, qy/q);
157}
158
159
160
161TriaxialEllipsoidModel :: TriaxialEllipsoidModel() {
162  scale      = Parameter(1.0);
163  semi_axisA     = Parameter(35.0, true);
164  semi_axisA.set_min(0.0);
165  semi_axisB     = Parameter(100.0, true);
166  semi_axisB.set_min(0.0);
167  semi_axisC  = Parameter(400.0, true);
168  semi_axisC.set_min(0.0);
169  sldEll   = Parameter(1.0e-6);
170  sldSolv   = Parameter(6.3e-6);
171  background = Parameter(0.0);
172  axis_theta  = Parameter(57.325, true);
173  axis_phi    = Parameter(57.325, true);
174  axis_psi    = Parameter(0.0, true);
175}
176
177/**
178 * Function to evaluate 1D scattering function
179 * The NIST IGOR library is used for the actual calculation.
180 * @param q: q-value
181 * @return: function value
182 */
183double TriaxialEllipsoidModel :: operator()(double q) {
184  double dp[7];
185
186  // Fill parameter array for IGOR library
187  // Add the background after averaging
188  dp[0] = scale();
189  dp[1] = semi_axisA();
190  dp[2] = semi_axisB();
191  dp[3] = semi_axisC();
192  dp[4] = sldEll();
193  dp[5] = sldSolv();
194  dp[6] = 0.0;
195
196  // Get the dispersion points for the semi axis A
197  vector<WeightPoint> weights_semi_axisA;
198  semi_axisA.get_weights(weights_semi_axisA);
199
200  // Get the dispersion points for the semi axis B
201  vector<WeightPoint> weights_semi_axisB;
202  semi_axisB.get_weights(weights_semi_axisB);
203
204  // Get the dispersion points for the semi axis C
205  vector<WeightPoint> weights_semi_axisC;
206  semi_axisC.get_weights(weights_semi_axisC);
207
208  // Perform the computation, with all weight points
209  double sum = 0.0;
210  double norm = 0.0;
211  double vol = 0.0;
212
213  // Loop over semi axis A weight points
214  for(int i=0; i< (int)weights_semi_axisA.size(); i++) {
215    dp[1] = weights_semi_axisA[i].value;
216
217    // Loop over semi axis B weight points
218    for(int j=0; j< (int)weights_semi_axisB.size(); j++) {
219      dp[2] = weights_semi_axisB[j].value;
220
221      // Loop over semi axis C weight points
222      for(int k=0; k< (int)weights_semi_axisC.size(); k++) {
223        dp[3] = weights_semi_axisC[k].value;
224        //Un-normalize  by volume
225        sum += weights_semi_axisA[i].weight
226            * weights_semi_axisB[j].weight * weights_semi_axisC[k].weight* TriaxialEllipsoid(dp, q)
227        * weights_semi_axisA[i].value*weights_semi_axisB[j].value*weights_semi_axisC[k].value;
228        //Find average volume
229        vol += weights_semi_axisA[i].weight
230            * weights_semi_axisB[j].weight * weights_semi_axisC[k].weight
231            * weights_semi_axisA[i].value*weights_semi_axisB[j].value*weights_semi_axisC[k].value;
232
233        norm += weights_semi_axisA[i].weight
234            * weights_semi_axisB[j].weight * weights_semi_axisC[k].weight;
235      }
236    }
237  }
238  if (vol != 0.0 && norm != 0.0) {
239    //Re-normalize by avg volume
240    sum = sum/(vol/norm);}
241
242  return sum/norm + background();
243}
244
245/**
246 * Function to evaluate 2D scattering function
247 * @param q_x: value of Q along x
248 * @param q_y: value of Q along y
249 * @return: function value
250 */
251double TriaxialEllipsoidModel :: operator()(double qx, double qy) {
252  TriaxialEllipsoidParameters dp;
253  // Fill parameter array
254  dp.scale      = scale();
255  dp.semi_axisA   = semi_axisA();
256  dp.semi_axisB     = semi_axisB();
257  dp.semi_axisC     = semi_axisC();
258  dp.sldEll   = sldEll();
259  dp.sldSolv   = sldSolv();
260  dp.background = 0.0;
261  dp.axis_theta  = axis_theta();
262  dp.axis_phi    = axis_phi();
263  dp.axis_psi    = axis_psi();
264
265  // Get the dispersion points for the semi_axis A
266  vector<WeightPoint> weights_semi_axisA;
267  semi_axisA.get_weights(weights_semi_axisA);
268
269  // Get the dispersion points for the semi_axis B
270  vector<WeightPoint> weights_semi_axisB;
271  semi_axisB.get_weights(weights_semi_axisB);
272
273  // Get the dispersion points for the semi_axis C
274  vector<WeightPoint> weights_semi_axisC;
275  semi_axisC.get_weights(weights_semi_axisC);
276
277  // Get angular averaging for theta
278  vector<WeightPoint> weights_theta;
279  axis_theta.get_weights(weights_theta);
280
281  // Get angular averaging for phi
282  vector<WeightPoint> weights_phi;
283  axis_phi.get_weights(weights_phi);
284
285  // Get angular averaging for psi
286  vector<WeightPoint> weights_psi;
287  axis_psi.get_weights(weights_psi);
288
289  // Perform the computation, with all weight points
290  double sum = 0.0;
291  double norm = 0.0;
292  double norm_vol = 0.0;
293  double vol = 0.0;
294  double pi = 4.0*atan(1.0);
295  // Loop over semi axis A weight points
296  for(int i=0; i< (int)weights_semi_axisA.size(); i++) {
297    dp.semi_axisA = weights_semi_axisA[i].value;
298
299    // Loop over semi axis B weight points
300    for(int j=0; j< (int)weights_semi_axisB.size(); j++) {
301      dp.semi_axisB = weights_semi_axisB[j].value;
302
303      // Loop over semi axis C weight points
304      for(int k=0; k < (int)weights_semi_axisC.size(); k++) {
305        dp.semi_axisC = weights_semi_axisC[k].value;
306
307        // Average over theta distribution
308        for(int l=0; l< (int)weights_theta.size(); l++) {
309          dp.axis_theta = weights_theta[l].value;
310
311          // Average over phi distribution
312          for(int m=0; m <(int)weights_phi.size(); m++) {
313            dp.axis_phi = weights_phi[m].value;
314            // Average over psi distribution
315            for(int n=0; n <(int)weights_psi.size(); n++) {
316              dp.axis_psi = weights_psi[n].value;
317              //Un-normalize  by volume
318              double _ptvalue = weights_semi_axisA[i].weight
319                  * weights_semi_axisB[j].weight
320                  * weights_semi_axisC[k].weight
321                  * weights_theta[l].weight
322                  * weights_phi[m].weight
323                  * weights_psi[n].weight
324                  * triaxial_ellipsoid_analytical_2DXY(&dp, qx, qy)
325              * weights_semi_axisA[i].value*weights_semi_axisB[j].value*weights_semi_axisC[k].value;
326              if (weights_theta.size()>1) {
327                _ptvalue *= fabs(sin(weights_theta[k].value*pi/180.0));
328              }
329              sum += _ptvalue;
330              //Find average volume
331              vol += weights_semi_axisA[i].weight
332                  * weights_semi_axisB[j].weight
333                  * weights_semi_axisC[k].weight
334                  * weights_semi_axisA[i].value*weights_semi_axisB[j].value*weights_semi_axisC[k].value;
335              //Find norm for volume
336              norm_vol += weights_semi_axisA[i].weight
337                  * weights_semi_axisB[j].weight
338                  * weights_semi_axisC[k].weight;
339
340              norm += weights_semi_axisA[i].weight
341                  * weights_semi_axisB[j].weight
342                  * weights_semi_axisC[k].weight
343                  * weights_theta[l].weight
344                  * weights_phi[m].weight
345                  * weights_psi[n].weight;
346            }
347          }
348
349        }
350      }
351    }
352  }
353  // Averaging in theta needs an extra normalization
354  // factor to account for the sin(theta) term in the
355  // integration (see documentation).
356  if (weights_theta.size()>1) norm = norm / asin(1.0);
357
358  if (vol != 0.0 && norm_vol != 0.0) {
359    //Re-normalize by avg volume
360    sum = sum/(vol/norm_vol);}
361
362  return sum/norm + background();
363}
364
365/**
366 * Function to evaluate 2D scattering function
367 * @param pars: parameters of the triaxial ellipsoid
368 * @param q: q-value
369 * @param phi: angle phi
370 * @return: function value
371 */
372double TriaxialEllipsoidModel :: evaluate_rphi(double q, double phi) {
373  double qx = q*cos(phi);
374  double qy = q*sin(phi);
375  return (*this).operator()(qx, qy);
376}
377/**
378 * Function to calculate effective radius
379 * @return: effective radius value
380 */
381double TriaxialEllipsoidModel :: calculate_ER() {
382  TriaxialEllipsoidParameters dp;
383
384  dp.semi_axisA   = semi_axisA();
385  dp.semi_axisB     = semi_axisB();
386  //polar axis C
387  dp.semi_axisC     = semi_axisC();
388
389  double rad_out = 0.0;
390  //Surface average radius at the equat. cross section.
391  double suf_rad = sqrt(dp.semi_axisA * dp.semi_axisB);
392
393  // Perform the computation, with all weight points
394  double sum = 0.0;
395  double norm = 0.0;
396
397  // Get the dispersion points for the semi_axis A
398  vector<WeightPoint> weights_semi_axisA;
399  semi_axisA.get_weights(weights_semi_axisA);
400
401  // Get the dispersion points for the semi_axis B
402  vector<WeightPoint> weights_semi_axisB;
403  semi_axisB.get_weights(weights_semi_axisB);
404
405  // Get the dispersion points for the semi_axis C
406  vector<WeightPoint> weights_semi_axisC;
407  semi_axisC.get_weights(weights_semi_axisC);
408
409  // Loop over semi axis A weight points
410  for(int i=0; i< (int)weights_semi_axisA.size(); i++) {
411    dp.semi_axisA = weights_semi_axisA[i].value;
412
413    // Loop over semi axis B weight points
414    for(int j=0; j< (int)weights_semi_axisB.size(); j++) {
415      dp.semi_axisB = weights_semi_axisB[j].value;
416
417      // Loop over semi axis C weight points
418      for(int k=0; k < (int)weights_semi_axisC.size(); k++) {
419        dp.semi_axisC = weights_semi_axisC[k].value;
420
421        //Calculate surface averaged radius
422        suf_rad = sqrt(dp.semi_axisA * dp.semi_axisB);
423
424        //Sum
425        sum += weights_semi_axisA[i].weight
426            * weights_semi_axisB[j].weight
427            * weights_semi_axisC[k].weight * DiamEllip(dp.semi_axisC, suf_rad)/2.0;
428        //Norm
429        norm += weights_semi_axisA[i].weight* weights_semi_axisB[j].weight
430            * weights_semi_axisC[k].weight;
431      }
432    }
433  }
434  if (norm != 0){
435    //return the averaged value
436    rad_out =  sum/norm;}
437  else{
438    //return normal value
439    rad_out = DiamEllip(dp.semi_axisC, suf_rad)/2.0;}
440
441  return rad_out;
442}
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