Changeset 41879

Timestamp:

Nov 3, 2021, 12:00:45 PM (5 years ago)

Author:

eugene

Message:

calculate the expmaps in pmStackCombineByPercentile

Location:

branches/eam_branches/psModules.20211028/src/imcombine

Files:

• pmStack.c (modified) (32 diffs)
• pmStack.h (modified) (1 diff)

branches/eam_branches/psModules.20211028/src/imcombine/pmStack.c

@@ -113 +113 @@
 // KMM functions to do bimodality rejection of pixels
 double gaussian(float x, float m, float s) {
-  return(pow(s * sqrt(2 * M_PI),-1) * exp(-0.5 * pow( (x - m) / s, 2)));
+    return(pow(s * sqrt(2 * M_PI),-1) * exp(-0.5 * pow( (x - m) / s, 2)));
 }
 
@@ -122 +122 @@
                          float *pi2, float *m2, float *s2,
                          int xyrdebug) {
-  assert(values);
-  assert(values->type.type == PS_TYPE_F32);
+    assert(values);
+    assert(values->type.type == PS_TYPE_F32);
   
-  double logL_bimodal = 0, logL_unimodal;
-  psVector *P1 = psVectorAlloc(values->n,PS_TYPE_F32);
-  psVector *P2 = psVectorAlloc(values->n,PS_TYPE_F32);
-  int i;
-  int discrepant_index = -1;
-  double discrepant_value = 0;
+    double logL_bimodal = 0, logL_unimodal;
+    psVector *P1 = psVectorAlloc(values->n,PS_TYPE_F32);
+    psVector *P2 = psVectorAlloc(values->n,PS_TYPE_F32);
+    int i;
+    int discrepant_index = -1;
+    double discrepant_value = 0;
 /*   int debug = 0; */
   
-  // Calculate unimodal properties
-  *mU = 0;
-  *sU = 0;
-  logL_unimodal = 0;
-  for (i = 0; i < values->n; i++) { // Calculate mean
-    *mU += values->data.F32[i];
-  }
-  *mU /= values->n;
-  for (i = 0; i < values->n; i++) { // Calculate sigma
-    *sU += pow(values->data.F32[i] - *mU,2);
-
-    // Attempt to guess better starting values
-    if (pow(values->data.F32[i] - *mU,2) > discrepant_value) {
-      discrepant_value = pow(values->data.F32[i] - *mU,2);
-      discrepant_index = i;
-    }
+    // Calculate unimodal properties
+    *mU = 0;
+    *sU = 0;
+    logL_unimodal = 0;
+    for (i = 0; i < values->n; i++) { // Calculate mean
+        *mU += values->data.F32[i];
+    }
+    *mU /= values->n;
+    for (i = 0; i < values->n; i++) { // Calculate sigma
+        *sU += pow(values->data.F32[i] - *mU,2);
+
+        // Attempt to guess better starting values
+        if (pow(values->data.F32[i] - *mU,2) > discrepant_value) {
+            discrepant_value = pow(values->data.F32[i] - *mU,2);
+            discrepant_index = i;
+        }
     
-  }
-  *sU = sqrt(*sU / values->n);
-  for (i = 0; i < values->n; i++) { // Calculate log likelihood
-    logL_unimodal += log(gaussian(values->data.F32[i],*mU,*sU));
-  }
-
-  if (xyrdebug == 1) { 
-      fprintf(stderr,"KMM uni: %d %f %d (%f %f)\n", 
-              xyrdebug,logL_unimodal,discrepant_index, 
-              *mU,*sU); 
-  } 
-
-  // Do EM loop
-  float dL = 0;
-  float oldL = -999;
-  *iter = 0;
-  logL_bimodal = logL_unimodal;
-
-  if (discrepant_index == -1) {
-    *m1 = *mU - 3 * *sU;
-    *m2 = *mU + 3 * *sU;
-    *s1 = *sU / 2;
-    *s2 = *sU / 2;
-  }
-  else {
-    // This is an attempt to speed up convergence. Find the largest contributor to sigma, and set one mean
-    // to that value.  Set the other mean to the mean of all other points with this one removed.  Next,
-    // set the sigmas to be equal to each other.  Take the value of sigma to be such that a point equidistant
-    // to the initial values of the two modes is equally not believed by either mode (2.5 sigma away).
+    }
+    *sU = sqrt(*sU / values->n);
+    for (i = 0; i < values->n; i++) { // Calculate log likelihood
+        logL_unimodal += log(gaussian(values->data.F32[i],*mU,*sU));
+    }
+
+    if (xyrdebug == 1) { 
+        fprintf(stderr,"KMM uni: %d %f %d (%f %f)\n", 
+                xyrdebug,logL_unimodal,discrepant_index, 
+                *mU,*sU); 
+    } 
+
+    // Do EM loop
+    float dL = 0;
+    float oldL = -999;
+    *iter = 0;
+    logL_bimodal = logL_unimodal;
+
+    if (discrepant_index == -1) {
+        *m1 = *mU - 3 * *sU;
+        *m2 = *mU + 3 * *sU;
+        *s1 = *sU / 2;
+        *s2 = *sU / 2;
+    }
+    else {
+        // This is an attempt to speed up convergence. Find the largest contributor to sigma, and set one mean
+        // to that value.  Set the other mean to the mean of all other points with this one removed.  Next,
+        // set the sigmas to be equal to each other.  Take the value of sigma to be such that a point equidistant
+        // to the initial values of the two modes is equally not believed by either mode (2.5 sigma away).
     
-    discrepant_value = values->data.F32[discrepant_index];
+        discrepant_value = values->data.F32[discrepant_index];
     
-    if (discrepant_value >  *mU) {
-      *m1 = ((*mU * values->n) - discrepant_value) / (values->n - 1);
-      *m2 = discrepant_value;
-    }
-    else {
-      *m1 = discrepant_value;
-      *m2 = ((*mU * values->n) - discrepant_value) / (values->n - 1);
-    }
-    *s1 = fabs((*m1 - *m2) / 5);
-    *s2 = *s1;
-  }
+        if (discrepant_value >  *mU) {
+            *m1 = ((*mU * values->n) - discrepant_value) / (values->n - 1);
+            *m2 = discrepant_value;
+        }
+        else {
+            *m1 = discrepant_value;
+            *m2 = ((*mU * values->n) - discrepant_value) / (values->n - 1);
+        }
+        *s1 = fabs((*m1 - *m2) / 5);
+        *s2 = *s1;
+    }
     
-  *pi1 = 0.5;
-  *pi2 = 0.5;
-
-  //MEH -- need to be double to help avoid 0 in norm
-  double g1,g2,norm;
-  float w1,w2;
-
-  // These should be options.
-  float KMM_TOLERANCE = 1e-6;
-  int KMM_MAX_ITERATIONS = 30;
-  float KMM_SMALL_NUMBER = 1e-5;
-  while (((dL > KMM_TOLERANCE)||(*iter < 3))&&(*iter < KMM_MAX_ITERATIONS)) {
-    *iter += 1;
-    dL = fabs(logL_bimodal - oldL);
-    oldL = logL_bimodal;
+    *pi1 = 0.5;
+    *pi2 = 0.5;
+
+    //MEH -- need to be double to help avoid 0 in norm
+    double g1,g2,norm;
+    float w1,w2;
+
+    // These should be options.
+    float KMM_TOLERANCE = 1e-6;
+    int KMM_MAX_ITERATIONS = 30;
+    float KMM_SMALL_NUMBER = 1e-5;
+    while (((dL > KMM_TOLERANCE)||(*iter < 3))&&(*iter < KMM_MAX_ITERATIONS)) {
+        *iter += 1;
+        dL = fabs(logL_bimodal - oldL);
+        oldL = logL_bimodal;
 /*     if (debug == 1) { */
 /*       fprintf(stderr,"KMM: %d %f %f %f %f (%f %f %f) (%f %f %f)\n", */
@@ -216 +216 @@
 /*     } */
 
+        if (xyrdebug == 1) { 
+            fprintf(stderr,"KMM EM iter: %d %f %f %f %f (%f %f %e) (%f %f %e)\n", 
+                    *iter,logL_unimodal,logL_bimodal,oldL,dL, 
+                    *m1,*s1,*pi1, 
+                    *m2,*s2,*pi2); 
+        } 
+
+        // Expectation/P-stage
+        for (i = 0; i < values->n; i++) { // Calculate probabilities for each mode
+            g1 = gaussian(values->data.F32[i],*m1,*s1);
+            g2 = gaussian(values->data.F32[i],*m2,*s2);
+            norm = (*pi1 * g1 + *pi2 * g2);
+            //MEH -- must protect denom from norm=0
+            if (norm > 0) {
+                P1->data.F32[i] = (*pi1 * g1) / norm;
+                P2->data.F32[i] = (*pi2 * g2) / norm;
+            } else {
+                P1->data.F32[i] = 0.0;
+                P2->data.F32[i] = 0.0;
+            }    
+ 
+            if (xyrdebug == 1) {
+                fprintf(stderr,"KMM EM-P loop: %d %d %le %le %le\n",
+                        *iter,i,norm,g1,g2);
+            }
+
+        }
+        // Maximization/M-stage
+        logL_bimodal = 0;
+        w1 = 0;
+        w2 = 0;
+        for (i = 0; i < values->n; i++) { // Calculate log likelihood
+            if (!((*pi1 == 0)||(*pi2 == 0))) {
+                logL_bimodal += log(*pi1 * gaussian(values->data.F32[i],*m1,*s1) +
+                                    *pi2 * gaussian(values->data.F32[i],*m2,*s2));
+            }
+        }
+        *m1 = 0;
+        *m2 = 0;
+        *s1 = 0;
+        *s2 = 0;
+        for (i = 0; i < values->n; i++) { // Calculate new means and weights
+            *m1 += values->data.F32[i] * P1->data.F32[i];
+            *m2 += values->data.F32[i] * P2->data.F32[i];
+
+            w1 += P1->data.F32[i];
+            w2 += P2->data.F32[i];
+
+            if (xyrdebug == 1) {
+                fprintf(stderr,"KMM EM-M loop: %d %d (%f %f %f %e) (%f %f %f %e)\n",
+                        *iter,i,*m1,values->data.F32[i],w1,P1->data.F32[i],*m2,values->data.F32[i],w2,P2->data.F32[i]);
+            }
+
+        }
+        *m1 /= w1;
+        *m2 /= w2;
+        for (i = 0; i < values->n; i++) { // Calculate new sigmas
+            *s1 += pow(values->data.F32[i] - *m1,2) * P1->data.F32[i];
+            *s2 += pow(values->data.F32[i] - *m2,2) * P2->data.F32[i];
+        }
+        *s1 = sqrt(*s1 / w1);
+        *s2 = sqrt(*s2 / w2);
+
+        *pi1 = w1 / values->n;
+        *pi2 = w2 / values->n;
+
+        if (!isfinite(*pi1)) { // finite checks
+            *pi1 = 0.0;
+        }
+        if (!isfinite(*pi2)) { // finite checks
+            *pi2 = 0.0;
+        }
+        if (*s1 == 0) { // sigma may not be zero -- MEH -- nor <0 and need additive offset if m~0
+            *s1 = fabsf(KMM_SMALL_NUMBER * *m1) + KMM_SMALL_NUMBER;
+        }
+        if (*s2 == 0) { // sigma may not be zero 
+            *s2 = fabsf(KMM_SMALL_NUMBER * *m2) + KMM_SMALL_NUMBER;
+        }
+
+        if (xyrdebug == 1) { 
+            fprintf(stderr,"KMM EM end: %d %f %f %f %f (%f %e %e %f) (%f %e %e %f)\n", 
+                    *iter,logL_unimodal,logL_bimodal,oldL,dL, 
+                    *m1,*s1,*pi1,w1, 
+                    *m2,*s2,*pi2,w2); 
+        } 
+
+    } // End EM phase
+
+    // Calculate Punimodal
+    double lambda = -2.0 * (logL_unimodal - logL_bimodal);
+    int    df     = 2 + 2 * 1; // I can't find my reference on this. 
+    if (lambda > 0) {
+        *Punimodal = gsl_cdf_chisq_Q(lambda,df);
+    }
+    else { // If lambda <= 0, then logL_unimodal > logL_bimodal, so Punimodal must be by definition 1.0
+        *Punimodal = 1.0;
+    }
+
     if (xyrdebug == 1) { 
-        fprintf(stderr,"KMM EM iter: %d %f %f %f %f (%f %f %e) (%f %f %e)\n", 
-                *iter,logL_unimodal,logL_bimodal,oldL,dL, 
-                *m1,*s1,*pi1, 
-                *m2,*s2,*pi2); 
+        fprintf(stderr,"KMM calc Puni: %d %f %d %f\n", 
+                xyrdebug,lambda,df,*Punimodal); 
     } 
 
-    // Expectation/P-stage
-    for (i = 0; i < values->n; i++) { // Calculate probabilities for each mode
-      g1 = gaussian(values->data.F32[i],*m1,*s1);
-      g2 = gaussian(values->data.F32[i],*m2,*s2);
-      norm = (*pi1 * g1 + *pi2 * g2);
-      //MEH -- must protect denom from norm=0
-      if (norm > 0) {
-          P1->data.F32[i] = (*pi1 * g1) / norm;
-          P2->data.F32[i] = (*pi2 * g2) / norm;
-      } else {
-          P1->data.F32[i] = 0.0;
-          P2->data.F32[i] = 0.0;
-      }  
- 
-      if (xyrdebug == 1) {
-          fprintf(stderr,"KMM EM-P loop: %d %d %le %le %le\n",
-                         *iter,i,norm,g1,g2);
-      }
-
-    }
-    // Maximization/M-stage
-    logL_bimodal = 0;
-    w1 = 0;
-    w2 = 0;
-    for (i = 0; i < values->n; i++) { // Calculate log likelihood
-      if (!((*pi1 == 0)||(*pi2 == 0))) {
-        logL_bimodal += log(*pi1 * gaussian(values->data.F32[i],*m1,*s1) +
-                            *pi2 * gaussian(values->data.F32[i],*m2,*s2));
-      }
-    }
-    *m1 = 0;
-    *m2 = 0;
-    *s1 = 0;
-    *s2 = 0;
-    for (i = 0; i < values->n; i++) { // Calculate new means and weights
-      *m1 += values->data.F32[i] * P1->data.F32[i];
-      *m2 += values->data.F32[i] * P2->data.F32[i];
-
-      w1 += P1->data.F32[i];
-      w2 += P2->data.F32[i];
-
-      if (xyrdebug == 1) {
-          fprintf(stderr,"KMM EM-M loop: %d %d (%f %f %f %e) (%f %f %f %e)\n",
-                         *iter,i,*m1,values->data.F32[i],w1,P1->data.F32[i],*m2,values->data.F32[i],w2,P2->data.F32[i]);
-      }
-
-    }
-    *m1 /= w1;
-    *m2 /= w2;
-    for (i = 0; i < values->n; i++) { // Calculate new sigmas
-      *s1 += pow(values->data.F32[i] - *m1,2) * P1->data.F32[i];
-      *s2 += pow(values->data.F32[i] - *m2,2) * P2->data.F32[i];
-    }
-    *s1 = sqrt(*s1 / w1);
-    *s2 = sqrt(*s2 / w2);
-
-    *pi1 = w1 / values->n;
-    *pi2 = w2 / values->n;
-
-    if (!isfinite(*pi1)) { // finite checks
-      *pi1 = 0.0;
-    }
-    if (!isfinite(*pi2)) { // finite checks
-      *pi2 = 0.0;
-    }
-    if (*s1 == 0) { // sigma may not be zero -- MEH -- nor <0 and need additive offset if m~0
-      *s1 = fabsf(KMM_SMALL_NUMBER * *m1) + KMM_SMALL_NUMBER;
-    }
-    if (*s2 == 0) { // sigma may not be zero 
-      *s2 = fabsf(KMM_SMALL_NUMBER * *m2) + KMM_SMALL_NUMBER;
-    }
-
-    if (xyrdebug == 1) { 
-        fprintf(stderr,"KMM EM end: %d %f %f %f %f (%f %e %e %f) (%f %e %e %f)\n", 
-                *iter,logL_unimodal,logL_bimodal,oldL,dL, 
-                *m1,*s1,*pi1,w1, 
-                *m2,*s2,*pi2,w2); 
-    } 
-
-  } // End EM phase
-
-  // Calculate Punimodal
-  double lambda = -2.0 * (logL_unimodal - logL_bimodal);
-  int    df     = 2 + 2 * 1; // I can't find my reference on this. 
-  if (lambda > 0) {
-    *Punimodal = gsl_cdf_chisq_Q(lambda,df);
-  }
-  else { // If lambda <= 0, then logL_unimodal > logL_bimodal, so Punimodal must be by definition 1.0
-    *Punimodal = 1.0;
-  }
-
-  if (xyrdebug == 1) { 
-      fprintf(stderr,"KMM calc Puni: %d %f %d %f\n", 
-              xyrdebug,lambda,df,*Punimodal); 
-  } 
-
-  psFree(P1);
-  psFree(P2);
+    psFree(P1);
+    psFree(P2);
 }
 
 static void KMMFindPopular(const psVector *values, float *Punimodal, float *mean, float *sigma, float *pi, int xyrdebug) {
-  float KMM_MINIMUM_PVALUE = 0.05; // Should be an option.
-  float mU,sU;
-  float pi1,m1,s1,pi2,m2,s2;
-  int iter;
-
-  assert(values);
-  assert(values->type.type == PS_TYPE_F32);
+    float KMM_MINIMUM_PVALUE = 0.05; // Should be an option.
+    float mU,sU;
+    float pi1,m1,s1,pi2,m2,s2;
+    int iter;
+
+    assert(values);
+    assert(values->type.type == PS_TYPE_F32);
   
-  KMMcalculate(values,Punimodal,&iter,
-               &mU,&sU,
-               &pi1,&m1,&s1,
-               &pi2,&m2,&s2,xyrdebug);
+    KMMcalculate(values,Punimodal,&iter,
+                 &mU,&sU,
+                 &pi1,&m1,&s1,
+                 &pi2,&m2,&s2,xyrdebug);
 /*   fprintf(stdout,"%g %g : %g %g %g : %g %g %g : %g %d\t", */
 /*        mU,sU, */
@@ -347 +347 @@
 /*   } */
 /*   fprintf(stdout,"\n"); */
-  if (*Punimodal > KMM_MINIMUM_PVALUE) {
-    // Is unimodal
-    *mean = mU;
-    *sigma = sU;
-    *pi = 1.0;
-  }
-  else {
-    // Is bimodal. Select most popular mode.
-    if (pi1 >= pi2) {
-      *mean = m1;
-      *sigma = s1;
-      *pi = pi1;
+    if (*Punimodal > KMM_MINIMUM_PVALUE) {
+        // Is unimodal
+        *mean = mU;
+        *sigma = sU;
+        *pi = 1.0;
     }
     else {
-      *mean = m2;
-      *sigma = s2;
-      *pi = pi2;
-    }
-  }  
+        // Is bimodal. Select most popular mode.
+        if (pi1 >= pi2) {
+            *mean = m1;
+            *sigma = s1;
+            *pi = pi1;
+        }
+        else {
+            *mean = m2;
+            *sigma = s2;
+            *pi = pi2;
+        }
+    }  
 }
 
@@ -381 +381 @@
                                     const psVector *exps,      // Exposure times to combine
                                     const psVector *weights // Weights to apply
-                                    )
+    )
 {
     assert(mean);
@@ -411 +411 @@
         sumWeight += weights->data.F32[i];
         if (variances) {
-          //            sumVarianceWeight += variances->data.F32[i] * PS_SQR(weights->data.F32[i]);
-          sumVarianceWeight += 1 / variances->data.F32[i];
+            //            sumVarianceWeight += variances->data.F32[i] * PS_SQR(weights->data.F32[i]);
+            sumVarianceWeight += 1 / variances->data.F32[i];
         }
         if (exps) {
@@ -427 +427 @@
     *mean = sumValueWeight / sumWeight;
     if (var) {
-      //*var = sumVarianceWeight / PS_SQR(sumWeight);
-      *var = 1 / sumVarianceWeight;
+        //*var = sumVarianceWeight / PS_SQR(sumWeight);
+        *var = 1 / sumVarianceWeight;
     }
     if (exp) {
@@ -445 +445 @@
                                    const psVector *values, // Values to combine
                                    psVector *sortBuffer // Buffer for sorting
-                                   )
+    )
 {
     assert(values);
@@ -496 +496 @@
                                         float frac, // Fraction to discard
                                         psVector *sortBuffer // Buffer for sorting
-                                        )
+    )
 {
     int numGood = values->n;            // Number of good values
@@ -527 +527 @@
                                       int x, int y, // Pixel
                                       int source // Source image index
-                                      )
+    )
 {
     CHECKPIX(x, y, "Marking image %d, pixel %d,%d for inspection\n", source, x, y);
@@ -545 +545 @@
                                      int x, int y, // Pixel
                                      int source // Source image index
-                                     )
+    )
 {
     CHECKPIX(x, y, "Marking pixel image %d, pixel %d,%d for rejection\n", source, x, y);
@@ -561 +561 @@
 // least popular mode.
 static void KMMRejectUnpopular(const psArray *inputs, int x, int y) {
-  float KMM_MINIMUM_PVALUE = 0.05;
-  float mU,sU;
-  float Punimodal,pi1,m1,s1,pi2,m2,s2;
-  int iter;
-  int j,k;
-
-  psVector *values = psVectorAlloc(inputs->n, PS_TYPE_F32);
-  k = 0;
-  for (j = 0; j < inputs->n; j++) {
-    pmStackData *data = inputs->data[j]; // Stack data of interest
-    if (!data) {
-      k++;
-      continue;
-    }
-    psImage *image = data->readout->image; // Image of interest
-    int xIn = x - data->readout->col0, yIn = y - data->readout->row0; // Coordinates on input readout
-    values->data.F32[j - k] = image->data.F32[yIn][xIn];
-  }
+    float KMM_MINIMUM_PVALUE = 0.05;
+    float mU,sU;
+    float Punimodal,pi1,m1,s1,pi2,m2,s2;
+    int iter;
+    int j,k;
+
+    psVector *values = psVectorAlloc(inputs->n, PS_TYPE_F32);
+    k = 0;
+    for (j = 0; j < inputs->n; j++) {
+        pmStackData *data = inputs->data[j]; // Stack data of interest
+        if (!data) {
+            k++;
+            continue;
+        }
+        psImage *image = data->readout->image; // Image of interest
+        int xIn = x - data->readout->col0, yIn = y - data->readout->row0; // Coordinates on input readout
+        values->data.F32[j - k] = image->data.F32[yIn][xIn];
+    }
   
-  KMMcalculate(values,&Punimodal,&iter,
-               &mU,&sU,
-               &pi1,&m1,&s1,
-               &pi2,&m2,&s2);
-
-   CHECKPIX(x, y, 
-          "KMM Unpopular Test: %d,%d: Puni: %g in %d",x,y,Punimodal,iter);  
-  if (Punimodal < KMM_MINIMUM_PVALUE) {
-    int i;
-    float g1,g2,norm;
-    float P1,P2;
-
-    for (i = 0; i < values->n; i++) { // Calculate probabilities for each mode
-      g1 = gaussian(values->data.F32[i],m1,s1);
-      g2 = gaussian(values->data.F32[i],m2,s2);
-      norm = (pi1 * g1 + pi2 * g2);
-      P1 = (pi1 * g1) / norm;
-      P2 = (pi2 * g2) / norm;
-
-      CHECKPIX(x, y, "KMM Unpopular Rejection: %d,%d: %f(%d): %d %f %f:(%f %f %f ) %f:(%f %f %f) rejection? %d %d\n",
-               x, y,
-               Punimodal,iter,
-               i, values->data.F32[i],
-               P1,m1,s1,pi1,
-               P2,m2,s2,pi2,
-               (pi1 > pi2)&&(P1 < P2),
-               (pi1 < pi2)&&(P1 > P2));
-      if ((pi1 > pi2)&&(P1 < P2)) { // mode 1 is more popular, but this element belongs to mode 2
-        combineMarkReject(inputs,x,y,i);
-      }
-      if ((pi1 < pi2)&&(P1 > P2)) { // mode 2 is more popular, but this element belongs to mode 1
-        combineMarkReject(inputs,x,y,i);
-      }
-    }
-  }
-  psFree(values);
-  // else do nothing.
+    KMMcalculate(values,&Punimodal,&iter,
+                 &mU,&sU,
+                 &pi1,&m1,&s1,
+                 &pi2,&m2,&s2);
+
+    CHECKPIX(x, y, 
+             "KMM Unpopular Test: %d,%d: Puni: %g in %d",x,y,Punimodal,iter);  
+    if (Punimodal < KMM_MINIMUM_PVALUE) {
+        int i;
+        float g1,g2,norm;
+        float P1,P2;
+
+        for (i = 0; i < values->n; i++) { // Calculate probabilities for each mode
+            g1 = gaussian(values->data.F32[i],m1,s1);
+            g2 = gaussian(values->data.F32[i],m2,s2);
+            norm = (pi1 * g1 + pi2 * g2);
+            P1 = (pi1 * g1) / norm;
+            P2 = (pi2 * g2) / norm;
+
+            CHECKPIX(x, y, "KMM Unpopular Rejection: %d,%d: %f(%d): %d %f %f:(%f %f %f ) %f:(%f %f %f) rejection? %d %d\n",
+                     x, y,
+                     Punimodal,iter,
+                     i, values->data.F32[i],
+                     P1,m1,s1,pi1,
+                     P2,m2,s2,pi2,
+                     (pi1 > pi2)&&(P1 < P2),
+                     (pi1 < pi2)&&(P1 > P2));
+            if ((pi1 > pi2)&&(P1 < P2)) { // mode 1 is more popular, but this element belongs to mode 2
+                combineMarkReject(inputs,x,y,i);
+            }
+            if ((pi1 < pi2)&&(P1 > P2)) { // mode 2 is more popular, but this element belongs to mode 1
+                combineMarkReject(inputs,x,y,i);
+            }
+        }
+    }
+    psFree(values);
+    // else do nothing.
 }
 
@@ -622 +622 @@
 // faintest mode as determined by the KMM test, and rejecting all inputs that belong to the brighest.
 static void KMMRejectBright(const psArray *inputs, int x, int y) {
-  float KMM_MINIMUM_PVALUE = 0.05;
-  float mU,sU;
-  float Punimodal,pi1,m1,s1,pi2,m2,s2;
-  int iter;
-  int j;
-
-  psVector *values = psVectorAlloc(inputs->n, PS_TYPE_F32);
-  for (j = 0; j < inputs->n; j++) {
-    pmStackData *data = inputs->data[j]; // Stack data of interest
-    psImage *image = data->readout->image; // Image of interest
-    int xIn = x - data->readout->col0, yIn = y - data->readout->row0; // Coordinates on input readout
-    values->data.F32[j] = image->data.F32[yIn][xIn];
-  }
+    float KMM_MINIMUM_PVALUE = 0.05;
+    float mU,sU;
+    float Punimodal,pi1,m1,s1,pi2,m2,s2;
+    int iter;
+    int j;
+
+    psVector *values = psVectorAlloc(inputs->n, PS_TYPE_F32);
+    for (j = 0; j < inputs->n; j++) {
+        pmStackData *data = inputs->data[j]; // Stack data of interest
+        psImage *image = data->readout->image; // Image of interest
+        int xIn = x - data->readout->col0, yIn = y - data->readout->row0; // Coordinates on input readout
+        values->data.F32[j] = image->data.F32[yIn][xIn];
+    }
   
-  KMMcalculate(values,&Punimodal,&iter,
-               &mU,&sU,
-               &pi1,&m1,&s1,
-               &pi2,&m2,&s2);
-  if (Punimodal < KMM_MINIMUM_PVALUE) {
-    int i;
-    float g1,g2,norm;
-    float P1,P2;
-
-    for (i = 0; i < values->n; i++) { // Calculate probabilities for each mode
-      g1 = gaussian(values->data.F32[i],m1,s1);
-      g2 = gaussian(values->data.F32[i],m2,s2);
-      norm = (pi1 * g1 + pi2 * g2);
-      P1 = (pi1 * g1) / norm;
-      P2 = (pi2 * g2) / norm;
-
-      if ((m1 > m2)&&(P1 > P2)) { // m1 is larger, and this element belongs to mode 1
-        combineMarkReject(inputs,x,y,i);
-      }
-      if ((m1 < m2)&&(P1 < P2)) { // m2 is larger, and this element belongs to mode 2
-        combineMarkReject(inputs,x,y,i);
-      }
-    }
-  }
-  psFree(values);
-  // else do nothing.
+    KMMcalculate(values,&Punimodal,&iter,
+                 &mU,&sU,
+                 &pi1,&m1,&s1,
+                 &pi2,&m2,&s2);
+    if (Punimodal < KMM_MINIMUM_PVALUE) {
+        int i;
+        float g1,g2,norm;
+        float P1,P2;
+
+        for (i = 0; i < values->n; i++) { // Calculate probabilities for each mode
+            g1 = gaussian(values->data.F32[i],m1,s1);
+            g2 = gaussian(values->data.F32[i],m2,s2);
+            norm = (pi1 * g1 + pi2 * g2);
+            P1 = (pi1 * g1) / norm;
+            P2 = (pi2 * g2) / norm;
+
+            if ((m1 > m2)&&(P1 > P2)) { // m1 is larger, and this element belongs to mode 1
+                combineMarkReject(inputs,x,y,i);
+            }
+            if ((m1 < m2)&&(P1 < P2)) { // m2 is larger, and this element belongs to mode 2
+                combineMarkReject(inputs,x,y,i);
+            }
+        }
+    }
+    psFree(values);
+    // else do nothing.
 }
 #endif // End if(0) to prevent KMMReject{Unpopular|Bright} from being defined.
@@ -682 +682 @@
                            psImageMaskType badMaskBits, // Value to mask as 'bad'
                            psImageMaskType suspectMaskBits // Value to mask as 'suspect'
-                           )
+    )
 {
     // Rudimentary error checking
@@ -795 +795 @@
     // set the mask bits if nGoodBits[i] > f*numGood
     {
-        # define SUSPECT_FRACTION 0.65
+# define SUSPECT_FRACTION 0.65
         *goodMask = 0x0000;
         psImageMaskType value = 0x0001;
@@ -840 +840 @@
                           int nminpix,         // Minimum number of input per pixel
                           float invTotalWeight    // Inverse of total weight for all inputs
-                          )
+    )
 {
     psVector *pixelData = buffer->pixels; // Values for the pixel of interest
@@ -944 +944 @@
                         bool useVariance, // Use variance for rejection when combining?
                         bool safe    // Combine safely?
-                        )
+    )
 {
     if (iter <= 0) {
@@ -968 +968 @@
     bool useKMM = false;
     if (num >= KMM_MINIMUM_INPUTS) {
-      useKMM = true;
+        useKMM = true;
     }
     
@@ -986 +986 @@
             }
 # endif
-          KMMFindPopular(pixelData,&Punimodal,&KMMmean,&KMMsigma,&KMMpi,xyrdebug);
-          CHECKPIX(x,y,"KMM Popularity Contest: (%d,%d) Puni: %g Mean: %f Sigma %f Pi: %f\n",
-                   x,y,Punimodal,KMMmean,KMMsigma,KMMpi);
+            KMMFindPopular(pixelData,&Punimodal,&KMMmean,&KMMsigma,&KMMpi,xyrdebug);
+            CHECKPIX(x,y,"KMM Popularity Contest: (%d,%d) Puni: %g Mean: %f Sigma %f Pi: %f\n",
+                     x,y,Punimodal,KMMmean,KMMsigma,KMMpi);
         }
         for (int i = 0; i < num; i++) {
@@ -994 +994 @@
         }
         for (int i = 0; i < num; i++) {
-          // Systematic error contributes to the rejection level
-          float sysVar;
-          if (useKMM) { // If we can trust KMM results, set the systematic variance
-            sysVar = PS_SQR(KMMsigma);
-          }
-          else { // Otherwise, use the 10% systematic variance we've done in the past.
-            sysVar = PS_SQR(sys * pixelData->data.F32[i]);
-          }
+            // Systematic error contributes to the rejection level
+            float sysVar;
+            if (useKMM) { // If we can trust KMM results, set the systematic variance
+                sysVar = PS_SQR(KMMsigma);
+            }
+            else { // Otherwise, use the 10% systematic variance we've done in the past.
+                sysVar = PS_SQR(sys * pixelData->data.F32[i]);
+            }
 
             CHECKPIX(x, y, "Variance %d (%d), pixel %d,%d: %f %f %f\n", 
@@ -1151 +1151 @@
           default: {
               if (useVariance) {
-                float median;
-                if ((useKMM)&&(Punimodal < 0.05)) {
-                  median = KMMmean;
-                }
-                else {
-                  median = combinationWeightedOlympic(pixelData, pixelWeights,
-                                                      olympic, buffer->sort); // Median for stack
-                }
+                  float median;
+                  if ((useKMM)&&(Punimodal < 0.05)) {
+                      median = KMMmean;
+                  }
+                  else {
+                      median = combinationWeightedOlympic(pixelData, pixelWeights,
+                                                          olympic, buffer->sort); // Median for stack
+                  }
                 
                   CHECKPIX(x, y, "Flag with variance pixel %d,%d: median = %f\n", x, y, median);
@@ -1170 +1170 @@
                       float diff2 = PS_SQR(diff); // Square difference
                       CHECKPIX(x,y, "Input %d, pixel %d,%d (%" PRIu16 "): %f %f (%f) %f %f :: %f %f %f %f\n",
-                              i, x, y, pixelSources->data.U16[j], pixelData->data.F32[j], pixelVariances->data.F32[j],
-                              1.0, pixelWeights->data.F32[j], 1.0,
-                              pixelLimits->data.F32[j], diff2, diff2 / pixelLimits->data.F32[j],worst);
+                               i, x, y, pixelSources->data.U16[j], pixelData->data.F32[j], pixelVariances->data.F32[j],
+                               1.0, pixelWeights->data.F32[j], 1.0,
+                               pixelLimits->data.F32[j], diff2, diff2 / pixelLimits->data.F32[j],worst);
 
                       if (diff2 > pixelLimits->data.F32[j]) {
@@ -1435 +1435 @@
 
 bool pmStackSimpleMedianCombine(
-                                pmReadout *combined,
-                                psArray *input) {
-  int num = input->n;
-  //  int numCols, numRows;
-  int minInputCols, maxInputCols, minInputRows, maxInputRows; // Smallest and largest values to combine
-  int xSize, ySize;                   // Size of the output image
-
-  psArray *stack = psArrayAlloc(num); // Stack of readouts  
-  for (int i = 0; i < num; i++) {
-    //    pmStackData *data = input->data[i]; // Stack data for this input
-    pmReadout *ro = input->data[i]; // data->readout;  // Readout of interest
-    if (!ro) {
-      continue;
-    }
-    stack->data[i] = psMemIncrRefCounter(ro);
-  }    
-
-  if (!pmReadoutStackValidate(&minInputCols, &maxInputCols, &minInputRows, &maxInputRows, &xSize, &ySize,
-                              stack)) {
-    psError(psErrorCodeLast(), false, "Input stack is not valid.");
+    pmReadout *combined,
+    psArray *input) {
+    int num = input->n;
+    //  int numCols, numRows;
+    int minInputCols, maxInputCols, minInputRows, maxInputRows; // Smallest and largest values to combine
+    int xSize, ySize;                   // Size of the output image
+
+    psArray *stack = psArrayAlloc(num); // Stack of readouts  
+    for (int i = 0; i < num; i++) {
+        //    pmStackData *data = input->data[i]; // Stack data for this input
+        pmReadout *ro = input->data[i]; // data->readout;  // Readout of interest
+        if (!ro) {
+            continue;
+        }
+        stack->data[i] = psMemIncrRefCounter(ro);
+    }    
+
+    if (!pmReadoutStackValidate(&minInputCols, &maxInputCols, &minInputRows, &maxInputRows, &xSize, &ySize,
+                                stack)) {
+        psError(psErrorCodeLast(), false, "Input stack is not valid.");
+        psFree(stack);
+        return false;
+    }
+
+    psVector *pixelData = psVectorAlloc(input->n,PS_TYPE_F32);
+    psVector *pixelMask = psVectorAlloc(input->n,PS_TYPE_VECTOR_MASK);
+    psStats  *stats     = psStatsAlloc(PS_STAT_ROBUST_MEDIAN);
+
+    for (int y = minInputRows; y < maxInputRows; y++) {
+        for (int x = minInputCols; x < maxInputCols; x++) {
+            for (int i = 0; i < input->n; i++) {
+                pmReadout *ro  = stack->data[i];
+                psImage *image = ro->image;
+                pixelMask->data.PS_TYPE_VECTOR_MASK_DATA[i] = 0;
+                pixelData->data.F32[i] = image->data.F32[y][x];
+                if (isfinite(image->data.F32[y][x])&&
+                    (fabs(image->data.F32[y][x]) < 1e5)) {
+                    pixelMask->data.PS_TYPE_VECTOR_MASK_DATA[i] = 0;
+                }
+                else {
+                    pixelMask->data.PS_TYPE_VECTOR_MASK_DATA[i] = 1;
+                }
+#if (0)
+                if ((x == 59)&&(y > 40)&&(y < 50)) {
+                    fprintf(stderr,"%d %d %d %d %g\n",
+                            x,y,i,pixelMask->data.PS_TYPE_VECTOR_MASK_DATA[i],pixelData->data.F32[i]);
+                }
+#endif
+            }
+            if (!psVectorStats(stats,pixelData,NULL,pixelMask,1)) {
+                psError(PS_ERR_UNKNOWN, false, "Unable to calculate median");
+                psFree(stats);
+                psFree(pixelData);
+                psFree(pixelMask);
+                psFree(stack);
+                return(false);
+            }
+            combined->image->data.F32[y][x] = stats->robustMedian;
+            if (combined->mask) {
+                combined->mask->data.PS_TYPE_IMAGE_MASK_DATA[y][x] = 0;
+            }
+#if (0)
+            if ((x == 59)&&(y > 40)&&(y < 50)) {
+                fprintf(stderr,"%d %d %d %d %g\n",
+                        x,y,-1,combined->mask->data.PS_TYPE_IMAGE_MASK_DATA[y][x],
+                        combined->image->data.F32[y][x]);
+            }
+#endif
+        }
+    }
+  
+    psFree(stats);
+    psFree(pixelData);
+    psFree(pixelMask);
     psFree(stack);
-    return false;
-  }
-
-  psVector *pixelData = psVectorAlloc(input->n,PS_TYPE_F32);
-  psVector *pixelMask = psVectorAlloc(input->n,PS_TYPE_VECTOR_MASK);
-  psStats  *stats     = psStatsAlloc(PS_STAT_ROBUST_MEDIAN);
-
-  for (int y = minInputRows; y < maxInputRows; y++) {
-    for (int x = minInputCols; x < maxInputCols; x++) {
-      for (int i = 0; i < input->n; i++) {
-        pmReadout *ro  = stack->data[i];
-        psImage *image = ro->image;
-        pixelMask->data.PS_TYPE_VECTOR_MASK_DATA[i] = 0;
-        pixelData->data.F32[i] = image->data.F32[y][x];
-        if (isfinite(image->data.F32[y][x])&&
-            (fabs(image->data.F32[y][x]) < 1e5)) {
-          pixelMask->data.PS_TYPE_VECTOR_MASK_DATA[i] = 0;
-        }
-        else {
-          pixelMask->data.PS_TYPE_VECTOR_MASK_DATA[i] = 1;
-        }
-#if (0)
-      if ((x == 59)&&(y > 40)&&(y < 50)) {
-          fprintf(stderr,"%d %d %d %d %g\n",
-                  x,y,i,pixelMask->data.PS_TYPE_VECTOR_MASK_DATA[i],pixelData->data.F32[i]);
-        }
-#endif
-      }
-      if (!psVectorStats(stats,pixelData,NULL,pixelMask,1)) {
-        psError(PS_ERR_UNKNOWN, false, "Unable to calculate median");
-        psFree(stats);
-        psFree(pixelData);
-        psFree(pixelMask);
-        psFree(stack);
-        return(false);
-      }
-      combined->image->data.F32[y][x] = stats->robustMedian;
-      if (combined->mask) {
-        combined->mask->data.PS_TYPE_IMAGE_MASK_DATA[y][x] = 0;
-      }
-#if (0)
-      if ((x == 59)&&(y > 40)&&(y < 50)) {
-        fprintf(stderr,"%d %d %d %d %g\n",
-                x,y,-1,combined->mask->data.PS_TYPE_IMAGE_MASK_DATA[y][x],
-                combined->image->data.F32[y][x]);
-      }
-#endif
-    }
-  }
-  
-  psFree(stats);
-  psFree(pixelData);
-  psFree(pixelMask);
-  psFree(stack);
-  return (true);
+    return (true);
 }
 
@@ -1519 +1519 @@
 #define SORT_VV_COMPARE(A,B) (pixelData->data.F32[A] < pixelData->data.F32[B])
 #define SORT_VV_SWAP(TYPE,A,B) {                                        \
-    if (A != B) {                                                       \
-      psF32 tempVal = pixelData->data.F32[A];                           \
-      pixelData->data.F32[A] = pixelData->data.F32[B];                  \
-      pixelData->data.F32[B] = tempVal;                                 \
-      psF32 tempVar = pixelVariances->data.F32[A];                      \
-      pixelVariances->data.F32[A] = pixelVariances->data.F32[B];                \
-      pixelVariances->data.F32[B] = tempVar;                            \
-    }                                                                   \
-}
-
-#define SORT_VALUE_AND_VAR(A,B) { PSSORT(A->n, SORT_VV_COMPARE, SORT_VV_SWAP, F32); }
-  
+        if (A != B) {                                                   \
+            psF32 tempVal = pixelData->data.F32[A];                     \
+            pixelData->data.F32[A] = pixelData->data.F32[B];            \
+            pixelData->data.F32[B] = tempVal;                           \
+            psF32 tempVar = pixelVariances->data.F32[A];                \
+            pixelVariances->data.F32[A] = pixelVariances->data.F32[B];  \
+            pixelVariances->data.F32[B] = tempVar;                      \
+            if (expTime) {                                              \
+                psF32 tempExp = expTime->data.F32[A];                   \
+                expTime->data.F32[A] = expTime->data.F32[B];            \
+                expTime->data.F32[B] = tempExp;                         \
+            }                                                           \
+        }                                                               \
+    }
+
+// this macro uses the macros above which assume pixelData, pixelVariances, expTime
+#define SORT_VALUES(NVALUES) { PSSORT(NVALUES, SORT_VV_COMPARE, SORT_VV_SWAP, F32); }
 
 bool pmStackCombineByPercentile(
@@ -1537 +1542 @@
     psArray *stackData,                 // input exposures
     psF64 rejectFraction,               // outlier fraction of pixels to reject
-    psF64 maxRange,
     psImageMaskType badMaskBits,        // treat these bits as 'bad'
     psImageMaskType suspectMaskBits,    // treat these bits as 'suspect'
     psImageMaskType blankMaskBits       // use this mask value for pixels missing input data (distinguish between Ninput = 0 and Ngood = 0?)
-) {
+    ) {
     int minInputCols, maxInputCols, minInputRows, maxInputRows; // Smallest and largest values to combine
     int xSize, ySize;                   // Size of the output image
@@ -1562 +1566 @@
     // make sure the output readout matches the inputs, and set to blank by default
     pmReadoutUpdateSize(combined, minInputCols, minInputRows, xSize, ySize, true, true, blankMaskBits);
-
-    psImage *exp = NULL, *expnum = NULL, *expweight = NULL; // Exposure map and exposure number
     if (expmaps) {
-        if (!expmaps->image) { exp = expmaps->image = psImageAlloc(numCols, numRows, PS_TYPE_F32); }
-        if (!expmaps->mask) { expnum = expmaps->mask = psImageAlloc(numCols, numRows, PS_TYPE_IMAGE_MASK); }
-        if (!expmaps->variance) { expweight = expmaps->variance = psImageAlloc(numCols, numRows, PS_TYPE_F32); }
+        // if we are generating the expmaps, update to match the images, set blank mask areas to 0
+        pmReadoutUpdateSize(expmaps, minInputCols, minInputRows, xSize, ySize, expmaps->mask != NULL, expmaps->variance != NULL, 0);
     }
    
     psVector *pixelData      = psVectorAlloc(stackData->n, PS_TYPE_F32);
     psVector *pixelVariances = psVectorAlloc(stackData->n, PS_TYPE_F32);
-    psVector *pixelMask      = psVectorAlloc(stackData->n, PS_TYPE_VECTOR_MASK);
-
-    psVector *expTime        = expmask ? psVectorAlloc(stackData->n, PS_TYPE_F32) : NULL;
-    psVector *expNum         = expmask ? psVectorAlloc(stackData->n, PS_TYPE_VECTOR_MASK): NULL;
+
+    // if we are asking for the exptime maps, generate a storage vector expTime
+    psVector *expTime        = expmaps && expmaps->image ? psVectorAlloc(stackData->n, PS_TYPE_F32) : NULL;
 
     int nGoodBits[16]; // accumulate the good pixel bits here for fuzzy logic
@@ -1589 +1589 @@
                 pmStackData *data = stackData->data[i]; // Stack data for this input
                 pmReadout *ro = data->readout;  // Readout of interest
+
+                psAssert (ro->mask,     "must must exist, but does not");
+                psAssert (ro->variance, "variance must exist, but does not");
 
                 psImage *image    = ro->image;
@@ -1607 +1610 @@
                 psImageMaskType value = 0x0001;
                 for (int nbit = 0; nbit < 16; nbit ++) {
-                  if (mask->data.PS_TYPE_IMAGE_MASK_DATA[yIn][xIn] & value) {
-                    nGoodBits[nbit] ++;
-                  }
-                  value <<= 1;
+                    if (mask->data.PS_TYPE_IMAGE_MASK_DATA[yIn][xIn] & value) {
+                        nGoodBits[nbit] ++;
+                    }
+                    value <<= 1;
                 }
 
-                // pixelWeights->data.F32[nGood] = data->weight;
-                // pixelExps->data.F32[nGood] = data->exp;
-                // pixelSources->data.U16[nGood] = i;
-
+                // accumulate pixel data and variance values:
                 pixelData->data.F32[nGood] = image->data.F32[yIn][xIn];
-                if (variance) { pixelVariances->data.F32[nGood] = variance->data.F32[yIn][xIn]; }
-                if (expmask) { pixelVariances->data.F32[nGood] = variance->data.F32[yIn][xIn]; }
+                pixelVariances->data.F32[nGood] = variance->data.F32[yIn][xIn];
+
+                // accumulate exposure times if required
+                if (expTime)  { expTime->data.F32[nGood] = data->exp; }
 
                 nGood ++;
@@ -1647 +1649 @@
                 combined->mask->data.PS_TYPE_IMAGE_MASK_DATA[y][x] = blankMaskBits; // probably not needed since it was set above.
                 if (expmaps) {
-                    expmaps->image->F32[y][x] = NAN;
+                    expmaps->image->F32[y][x] = NAN; // XXX should this value be NAN or 0?
                     expmaps->variance->F32[y][x] = NAN;
                     expmaps->mask->PS_TYPE_IMAGE_MASK_DATA[y][x] = 0;
@@ -1654 +1656 @@
             }
 
-            // sort both pixelData and pixelVariance
-            SORT_VALUE_AND_VAR (pixelData, pixelVariances);
+            // sort pixelData, pixelVariance, expTime (if it exists)
+            SORT_VALUES (pixelData->n);
 
             // set the given (suspect) mask bit if nGoodBits[i] > f*nGood
@@ -1663 +1665 @@
             psImageMaskType outputMask = 0x0000;
             for (int nbit = 0; nbit < 16; nbit ++) {
-              if (nGoodBits[nbit] > SUSPECT_FRACTION*nGood) {
-                outputMask |= value;
-              }
-              value <<= 1;
+                if (nGoodBits[nbit] > SUSPECT_FRACTION*nGood) {
+                    outputMask |= value;
+                }
+                value <<= 1;
             }
 
@@ -1688 +1690 @@
             combined->variance->data.F32[y][x] = varValue;
             combined->mask->data.PS_TYPE_IMAGE_MASK_DATA[y][x] = outputMask;
-        }
-    }
-  
+
+            if (expTime) { 
+                float sum = 0.0;
+                for (int n = Ns; n < Ne; n++) {
+                    sum += expTime->data.F32[n];
+                }
+                expmaps->image->data.F32[y][x] = sum;
+            }
+            if (expNum) { expmaps->mask->data.F32[y][x] = Ne - Ns; }
+        }
+    }
     psFree(pixelData);
-    psFree(pixelMask);
-
+    psFree(pixelVariance);
+    psFree(expTime);
     return (true);
 }

branches/eam_branches/psModules.20211028/src/imcombine/pmStack.h

@@ -49 +49 @@
 bool pmStackCombineByPercentile(
     pmReadout *combined,
+    pmReadout *expmaps,
     psArray *input,
-    psF64 minRange,
-    psF64 maxRange,
+    psF64 rejectFraction,
     psImageMaskType badMaskBits,        // treat these bits as 'bad'
     psImageMaskType suspectMaskBits,    // treat these bits as 'suspect'