source: sasmodels/sasmodels/kernel_iq.c @ a6f9577

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Last change on this file since a6f9577 was a6f9577, checked in by Paul Kienzle <pkienzle@…>, 8 years ago

restore support for simple polydispersity (incomplete)

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File size: 7.2 KB
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1
2/*
3    ##########################################################
4    #                                                        #
5    #   !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!   #
6    #   !!                                              !!   #
7    #   !!  KEEP THIS CODE CONSISTENT WITH KERNELPY.PY  !!   #
8    #   !!                                              !!   #
9    #   !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!   #
10    #                                                        #
11    ##########################################################
12*/
13
14#ifndef _PAR_BLOCK_ // protected block so we can include this code twice.
15#define _PAR_BLOCK_
16
17#define MAX_PD 4  // MAX_PD is the max number of polydisperse parameters
18
19typedef struct {
20    int32_t pd_par[MAX_PD];     // id of the nth polydispersity variable
21    int32_t pd_length[MAX_PD];  // length of the nth polydispersity weight vector
22    int32_t pd_offset[MAX_PD];  // offset of pd weights in the par & weight vector
23    int32_t pd_stride[MAX_PD];  // stride to move to the next index at this level
24    int32_t pd_isvol[MAX_PD];   // True if parameter is a volume weighting parameter
25    int32_t par_offset[NPARS];  // offset of par values in the par & weight vector
26    int32_t par_coord[NPARS];   // polydispersity coordination bitvector
27    int32_t fast_coord_pars[NPARS]; // ids of the fast coordination parameters
28    int32_t fast_coord_count;   // number of parameters coordinated with pd 1
29    int32_t theta_var;          // id of spherical correction variable
30} ProblemDetails;
31
32typedef struct {
33    PARAMETER_TABLE;
34} ParameterBlock;
35#endif
36
37
38kernel
39void KERNEL_NAME(
40    int32_t nq,                 // number of q values
41    const int32_t pd_start,     // where we are in the polydispersity loop
42    const int32_t pd_stop,      // where we are stopping in the polydispersity loop
43    global const ProblemDetails *problem,
44    global const double *weights,
45    global const double *pars,
46    global const double *q, // nq q values, with padding to boundary
47    global double *result,  // nq+3 return values, again with padding
48    const double cutoff     // cutoff in the polydispersity weight product
49    )
50{
51  // Storage for the current parameter values.  These will be updated as we
52  // walk the polydispersity cube.
53  local ParameterBlock local_pars;  // current parameter values
54  double *pvec = (double *)(&local_pars);  // Alias named parameters with a vector
55
56  local int offset[NPARS];  // NPARS excludes scale/background
57
58#if 1 // defined(USE_SHORTCUT_OPTIMIZATION)
59  if (problem->pd_length[0] == 1) {
60    // Shouldn't need to copy!!
61
62    for (int k=0; k < NPARS; k++) {
63      pvec[k] = pars[k+2];  // skip scale and background
64    }
65    printf("calculating\n");
66
67    #ifdef USE_OPENMP
68    #pragma omp parallel for
69    #endif
70    for (int i=0; i < nq; i++) {
71      const double scattering = CALL_IQ(q, i, local_pars);
72      result[i] += pars[0]*scattering + pars[1];
73    }
74    printf("returning\n");
75    return;
76  }
77  printf("falling through\n");
78#endif
79
80
81  // Since we are no longer looping over the entire polydispersity hypercube
82  // for each q, we need to track the normalization values for each q in a
83  // separate work vector.
84  double norm;   // contains sum over weights
85  double vol; // contains sum over volume
86  double norm_vol; // contains weights over volume
87
88  // Initialize the results to zero
89  if (pd_start == 0) {
90    norm_vol = 0.0;
91    norm = 0.0;
92    vol = 0.0;
93
94    #ifdef USE_OPENMP
95    #pragma omp parallel for
96    #endif
97    for (int i=0; i < nq; i++) {
98      result[i] = 0.0;
99    }
100  } else {
101    //Pulling values from previous segment
102    norm = result[nq];
103    vol = result[nq+1];
104    norm_vol = result[nq+2];
105  }
106
107  // Location in the polydispersity hypercube, one index per dimension.
108  local int pd_index[MAX_PD];
109
110  // Trigger the reset behaviour that happens at the end the fast loop
111  // by setting the initial index >= weight vector length.
112  pd_index[0] = problem->pd_length[0];
113
114
115  // need product of weights at every Iq calc, so keep product of
116  // weights from the outer loops so that weight = partial_weight * fast_weight
117  double partial_weight = NAN; // product of weight w4*w3*w2 but not w1
118  double partial_volweight = NAN;
119  double weight = 1.0;        // set to 1 in case there are no weights
120  double vol_weight = 1.0;    // set to 1 in case there are no vol weights
121  double spherical_correction = 1.0;  // correction for latitude variation
122
123  // Loop over the weights then loop over q, accumulating values
124  for (int loop_index=pd_start; loop_index < pd_stop; loop_index++) {
125    // check if indices need to be updated
126    if (pd_index[0] >= problem->pd_length[0]) {
127
128      // RESET INDICES
129      pd_index[0] = loop_index%problem->pd_length[0];
130      partial_weight = 1.0;
131      partial_volweight = 1.0;
132      for (int k=1; k < MAX_PD; k++) {
133        pd_index[k] = (loop_index%problem->pd_length[k])/problem->pd_stride[k];
134        const double wi = weights[problem->pd_offset[0]+pd_index[0]];
135        partial_weight *= wi;
136        if (problem->pd_isvol[k]) partial_volweight *= wi;
137      }
138      for (int k=0; k < NPARS; k++) {
139        int coord = problem->par_coord[k];
140        int this_offset = problem->par_offset[k];
141        int block_size = 1;
142        for (int bit=0; bit < MAX_PD && coord != 0; bit++) {
143          if (coord&1) {
144              this_offset += block_size * pd_index[bit];
145              block_size *= problem->pd_length[bit];
146          }
147          coord /= 2;
148        }
149        offset[k] = this_offset;
150        pvec[k] = pars[this_offset];
151      }
152      weight = partial_weight * weights[problem->pd_offset[0]+pd_index[0]];
153      if (problem->theta_var >= 0) {
154        spherical_correction = fabs(cos(M_PI_180*pvec[problem->theta_var]));
155      }
156      if (problem->theta_var == problem->pd_par[0]) {
157        weight *= spherical_correction;
158      }
159
160    } else {
161
162      // INCREMENT INDICES
163      pd_index[0] += 1;
164      const double wi = weights[problem->pd_offset[0]+pd_index[0]];
165      weight = partial_weight*wi;
166      if (problem->pd_isvol[0]) vol_weight *= wi;
167      for (int k=0; k < problem->fast_coord_count; k++) {
168        pvec[problem->fast_coord_pars[k]]
169            = pars[offset[problem->fast_coord_pars[k]]++];
170      }
171      if (problem->theta_var ==problem->pd_par[0]) {
172        weight *= fabs(cos(M_PI_180*pvec[problem->theta_var]));
173      }
174    }
175
176    #ifdef INVALID
177    if (INVALID(local_pars)) continue;
178    #endif
179
180    // Accumulate I(q)
181    // Note: weight==0 must always be excluded
182    if (weight > cutoff) {
183      norm += weight;
184      vol += vol_weight * CALL_VOLUME(local_pars);
185      norm_vol += vol_weight;
186
187      #ifdef USE_OPENMP
188      #pragma omp parallel for
189      #endif
190      for (int i=0; i < nq; i++) {
191        const double scattering = CALL_IQ(q, i, local_pars);
192        result[i] += weight*scattering;
193      }
194    }
195  }
196  //Makes a normalization avialable for the next round
197  result[nq] = norm;
198  result[nq+1] = vol;
199  result[nq+2] = norm_vol;
200
201  //End of the PD loop we can normalize
202  if (pd_stop >= problem->pd_stride[MAX_PD-1]) {
203    #ifdef USE_OPENMP
204    #pragma omp parallel for
205    #endif
206    for (int i=0; i < nq; i++) {
207      if (vol*norm_vol != 0.0) {
208        result[i] *= norm_vol/vol;
209      }
210      result[i] = pars[0]*result[i]/norm + pars[1];
211    }
212  }
213}
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