Index: /branches/eam_branches/ipp-20130711/psphot/src/psphotSourceFits.c
===================================================================
--- /branches/eam_branches/ipp-20130711/psphot/src/psphotSourceFits.c	(revision 36063)
+++ /branches/eam_branches/ipp-20130711/psphot/src/psphotSourceFits.c	(revision 36064)
@@ -559,6 +559,10 @@
 
 # define TIMING 0
+# define EXTRA_VERBOSE 0
 
 bool psphotSersicModelGuessPCM (pmPCMdata *pcm, pmSource *source, psImageMaskType maskVal, float psfSize);
+bool psphotFitSersicShapeAndIndex (pmPCMdata *pcm, pmReadout *readout, pmSource *source, pmSourceFitOptions *fitOptions, psImageMaskType maskVal, psImageMaskType markVal, int psfSize);
+bool psphotFitSersicShapeAndIndexGrid (pmPCMdata *pcm, pmReadout *readout, pmSource *source, pmSourceFitOptions *fitOptions, psImageMaskType maskVal, psImageMaskType markVal, int psfSize);
+bool psphotFitSersicShapeAndIndexGridAuto (pmPCMdata *pcm, pmReadout *readout, pmSource *source, pmSourceFitOptions *fitOptions, psImageMaskType maskVal, psImageMaskType markVal, int psfSize);
 
 pmModel *psphotFitPCM (pmReadout *readout, pmSource *source, pmSourceFitOptions *fitOptions, pmModelType modelType, psImageMaskType maskVal, psImageMaskType markVal, int psfSize) {
@@ -586,7 +590,11 @@
 
     if (modelType == pmModelClassGetType("PS_MODEL_SERSIC")) {
-	options.mode = PM_SOURCE_FIT_NO_INDEX;
+	options.mode = PM_SOURCE_FIT_NO_INDEX; // XXX note that there may be a conflict with psphotExtendedSourceFits.c:133
+	options.mode = PM_SOURCE_FIT_EXT_AND_SKY;
+	// if we are ever (in a given psphot implementation) going to fit a parameter, we must set the options here to include
+	// that parameter (otherwise pmPCMupdate will fail to allocate the dmodelFlux image)
+	// thus, if the sersic analysis below uses an index fit, need to use this EXT_AND_SKY mode for init
     } else {
-	options.mode = PM_SOURCE_FIT_EXT_AND_SKY; // XXX note that there may be a conflict with psphotExtendedSourceFits.c:133
+	options.mode = PM_SOURCE_FIT_EXT_AND_SKY;
     }
 
@@ -608,4 +616,15 @@
 	    return model;
 	}
+	if (TIMING) { t2 = psTimerMark ("psphotFitPCM"); }
+
+	// psphotFitSersicShapeAndIndex (pcm, readout, source, fitOptions, maskVal, markVal, psfSize);
+	options.mode = PM_SOURCE_FIT_NO_INDEX;
+	if (!psphotFitSersicShapeAndIndexGridAuto (pcm, readout, source, &options, maskVal, markVal, psfSize)) {
+	    psFree (pcm);
+	    model->flags |= PM_MODEL_STATUS_BADARGS;
+	    psError(PS_ERR_UNKNOWN, true, "Failed to find a index & shape");
+	    psErrorClear (); // clear the polynomial error
+	    return model;
+	}
     } else {
 	// use the source moments, etc to guess basic model parameters
@@ -615,14 +634,7 @@
 	    return model;
 	}
-	// XXX TEST:
-	// pcm->modelConv->params->data.F32[4] = 30.0;
-	// pcm->modelConv->params->data.F32[5] = 30.0;
-    }
-
-    if (TIMING) { t2 = psTimerMark ("psphotFitPCM"); }
-
-    // update the pcm elements if we have changed the circumstance (options.mode or source->pixels)
-    // pmPCMupdate(pcm, source, &options, model);
-    // if (TIMING) { t4 = psTimerMark ("psphotFitPCM"); }
+    }
+
+    if (TIMING) { t4 = psTimerMark ("psphotFitPCM"); }
 
     // psTraceSetLevel("psLib.math.psMinimizeLMChi2", 5);
@@ -635,9 +647,11 @@
 	int nPixBig = source->pixels->numCols * source->pixels->numRows;
     	fprintf (stderr, "psphotFitPCM : nIter: %2d, radius: %6.1f, npix: %5d of %5d, t1: %6.4f, t2: %6.4f, t4: %6.4f, t5: %6.4f\n", model->nIter, model->fitRadius, model->nPix, nPixBig, t1, t2, t4, t5);
+    }
+    if (EXTRA_VERBOSE && !TIMING) {
+	int nPixBig = source->pixels->numCols * source->pixels->numRows;
 	float *PAR = model->params->data.F32;
-	fprintf (stderr, "%f - %f %f %f - %f\n", PAR[7], PAR[4], PAR[5], PAR[6], PAR[1]);
-    }
-
-    // psTraceSetLevel("psLib.math.psMinimizeLMChi2", 0);
+	fprintf (stderr, "source %d : %f - %f %f - %f %f %f - %f | nIter: %2d, radius: %6.1f, npix: %5d of %5d, chisq %f\n", source->id, PAR[7], PAR[2], PAR[3], PAR[4], PAR[5], PAR[6], PAR[1], model->nIter, model->fitRadius, model->nPix, nPixBig, model->chisqNorm);
+    }
+
     psFree (pcm);
 
@@ -762,5 +776,6 @@
 # define N_INDEX_GUESS_INV 7
 
-float reffGuess[] = {3.0, 10.0, 20.0, 30.0, 40.0};
+// float reffGuess[] = {3.0, 10.0, 20.0, 30.0, 40.0};
+float reffGuess[] = {0.5, 0.75, 1.0, 1.4, 2.0};
 # define N_REFF_GUESS 5
 
@@ -827,6 +842,6 @@
 
 	psEllipseAxes guessAxes;
-	guessAxes.major = reffGuess[j];
-	guessAxes.minor = (momentAxes.minor / momentAxes.minor) * guessAxes.major;
+	guessAxes.major = reffGuess[j] * source->moments->Mrf;
+	guessAxes.minor = guessAxes.major * (momentAxes.minor / momentAxes.major);
 	guessAxes.theta = momentAxes.theta;
 
@@ -889,6 +904,6 @@
     {
 	psEllipseAxes guessAxes;
-	guessAxes.major = rMin;
-	guessAxes.minor = (momentAxes.minor / momentAxes.minor) * guessAxes.major;
+	guessAxes.major = rMin * source->moments->Mrf;
+	guessAxes.minor = guessAxes.major * (momentAxes.minor / momentAxes.major);
 	guessAxes.theta = momentAxes.theta;
 
@@ -906,2 +921,322 @@
     return true;
 }
+
+// we have a set of guess parameters, do a small number of iterations fitting only SHAPE then only INDEX 
+bool psphotFitSersicShapeAndIndex (pmPCMdata *pcm, pmReadout *readout, pmSource *source, pmSourceFitOptions *fitOptions, psImageMaskType maskVal, psImageMaskType markVal, int psfSize) {
+
+    pmModel *model = pcm->modelConv;
+
+    assert (model->type == pmModelClassGetType("PS_MODEL_SERSIC"));
+
+    pmSourceFitOptions options = *fitOptions;
+    
+    for (int i = 0; i < 3; i++) {
+      // fit EXT (not PSF) model (set/unset the pixel mask)
+      options.mode = PM_SOURCE_FIT_SHAPE;
+      options.nIter = 2;
+
+      // update the pcm elements if we have changed the circumstance (here, options.mode)
+      pmPCMupdate(pcm, source, &options, model);
+      
+      pmSourceFitPCM (pcm, source, &options, maskVal, markVal, psfSize);
+      if (EXTRA_VERBOSE) {
+	float *PAR = model->params->data.F32;
+	fprintf (stderr, "%d >>> %d %f : %f - %f %f - %f %f %f - %f\n", source->id, model->nIter, model->chisqNorm, PAR[7], PAR[2], PAR[3], PAR[4], PAR[5], PAR[6], PAR[1]);
+      }
+      
+      // fit EXT (not PSF) model (set/unset the pixel mask)
+      options.mode = PM_SOURCE_FIT_INDEX;
+      // options.mode = PM_SOURCE_FIT_EXT_AND_SKY;
+      options.nIter = 30;
+      
+      // update the pcm elements if we have changed the circumstance (here, options.mode)
+      pmPCMupdate(pcm, source, &options, model);
+      
+      pmSourceFitPCM (pcm, source, &options, maskVal, markVal, psfSize);
+      if (EXTRA_VERBOSE) {
+	float *PAR = model->params->data.F32;
+	fprintf (stderr, "%d >>> %d %f : %f - %f %f - %f %f %f - %f\n", source->id, model->nIter, model->chisqNorm, PAR[7], PAR[2], PAR[3], PAR[4], PAR[5], PAR[6], PAR[1]);
+      }
+    }
+
+    // update the pcm elements if we have changed the circumstance (here, options.mode)
+    pmPCMupdate(pcm, source, fitOptions, model);
+
+    return true;
+}
+
+// we have a set of guess parameters, do a small number of iterations fitting only SHAPE then only INDEX 
+bool psphotFitSersicShapeAndIndexGridAuto (pmPCMdata *pcm, pmReadout *readout, pmSource *source, pmSourceFitOptions *fitOptions, psImageMaskType maskVal, psImageMaskType markVal, int psfSize) {
+
+    pmModel *model = pcm->modelConv;
+
+    assert (model->type == pmModelClassGetType("PS_MODEL_SERSIC"));
+
+    pmSourceFitOptions options = *fitOptions;
+    
+    psF32 *PAR = pcm->modelConv->params->data.F32;
+
+    options.mode = PM_SOURCE_FIT_SHAPE;
+    options.nIter = 7;
+    
+    // update the pcm elements if we have changed the circumstance (here, options.mode)
+    pmPCMupdate(pcm, source, &options, model);
+    
+    // we have been provided a guess at the index (P[7]) from the list of indexGuessInv
+
+    // find the matching indexGuessInv
+    int nStart = -1;
+    for (int i = 0; i < N_INDEX_GUESS_INV; i++) {
+	if (fabs(PAR[PM_PAR_7] - indexGuessInv[i]) < 0.01) {
+	    nStart = i;
+	    break;
+	}
+    }
+    if (nStart == -1) {
+	fprintf (stderr, "WARNING: could not find start guess %f\n", PAR[PM_PAR_7]);
+	return false;
+    }
+
+    psVector *chi2 = psVectorAllocEmpty (16, PS_TYPE_F32);
+    psVector *Sidx = psVectorAllocEmpty (16, PS_TYPE_F32);
+
+    PAR[PM_PAR_7] = indexGuessInv[nStart];
+    pmSourceFitPCM (pcm, source, &options, maskVal, markVal, psfSize);
+    if (EXTRA_VERBOSE) fprintf (stderr, "%d >>> %d %f : %f - %f %f - %f %f %f - %f\n", source->id, model->nIter, model->chisqNorm, PAR[7], PAR[2], PAR[3], PAR[4], PAR[5], PAR[6], PAR[1]);
+    psVectorAppend (Sidx, 100*PAR[PM_PAR_7]);
+    psVectorAppend (chi2, model->chisqNorm);
+
+    PAR[PM_PAR_7] = (nStart < N_INDEX_GUESS_INV - 1) ? 0.5*(indexGuessInv[nStart + 1] + indexGuessInv[nStart]) : 0.1;
+    pmSourceFitPCM (pcm, source, &options, maskVal, markVal, psfSize);
+    if (EXTRA_VERBOSE) fprintf (stderr, "%d >>> %d %f : %f - %f %f - %f %f %f - %f\n", source->id, model->nIter, model->chisqNorm, PAR[7], PAR[2], PAR[3], PAR[4], PAR[5], PAR[6], PAR[1]);
+    psVectorAppend (Sidx, 100*PAR[PM_PAR_7]);
+    psVectorAppend (chi2, model->chisqNorm);
+
+    PAR[PM_PAR_7] = (nStart > 0) ? 0.5*(indexGuessInv[nStart - 1] + indexGuessInv[nStart]) : 0.55;
+    pmSourceFitPCM (pcm, source, &options, maskVal, markVal, psfSize);
+    if (EXTRA_VERBOSE) fprintf (stderr, "%d >>> %d %f : %f - %f %f - %f %f %f - %f\n", source->id, model->nIter, model->chisqNorm, PAR[7], PAR[2], PAR[3], PAR[4], PAR[5], PAR[6], PAR[1]);
+    psVectorAppend (Sidx, 100*PAR[PM_PAR_7]);
+    psVectorAppend (chi2, model->chisqNorm);
+
+    if (chi2->data.F32[1] < chi2->data.F32[2]) {
+      if (nStart == N_INDEX_GUESS_INV - 1) {
+	PAR[PM_PAR_7] = 0.11;
+      } else {
+	PAR[PM_PAR_7] = indexGuessInv[nStart + 1];
+      }
+    } else {
+      if (nStart == 0) {
+	PAR[PM_PAR_7] = 0.52;
+      } else {
+	PAR[PM_PAR_7] = indexGuessInv[nStart - 1];
+      }
+    }
+
+    psPolynomial1D *poly = psPolynomial1DAlloc (PS_POLYNOMIAL_ORD, 2);
+    if (!psVectorFitPolynomial1D (poly, NULL, 0, chi2, NULL, Sidx)) {
+        psError(PS_ERR_UNKNOWN, true, "Failed to find a good chisq parabola");
+	psFree (chi2);
+	psFree (Sidx);
+	psFree (poly);
+	return false;
+    }
+
+    // where is the minimum of this polynomial fit?
+    float Smin = -0.5 * poly->coeff[1] / poly->coeff[2] / 100.0;
+
+    // constrain Smin to be in a valid range (1.0 - 0.1, corresponding to 0.5 (Gauss) to 5.0 (slightly peakier than Dev)
+    Smin = PS_MAX(PS_MIN(Smin, 1.0), 0.1);
+    PAR[PM_PAR_7] = Smin;
+
+    // return to the original fitting mode (fitOptions)
+    pmPCMupdate(pcm, source, fitOptions, model);
+
+    psFree (chi2);
+    psFree (Sidx);
+    psFree (poly);
+
+    return true;
+}
+
+ 
+// we have a set of guess parameters, do a small number of iterations fitting only SHAPE then only INDEX 
+bool psphotFitSersicShapeAndIndexGridAutoScaled (pmPCMdata *pcm, pmReadout *readout, pmSource *source, pmSourceFitOptions *fitOptions, psImageMaskType maskVal, psImageMaskType markVal, int psfSize) {
+
+    pmModel *model = pcm->modelConv;
+
+    assert (model->type == pmModelClassGetType("PS_MODEL_SERSIC"));
+
+    pmSourceFitOptions options = *fitOptions;
+    
+    psF32 *PAR = pcm->modelConv->params->data.F32;
+
+    options.mode = PM_SOURCE_FIT_SHAPE;
+    options.nIter = 5;
+    
+    // update the pcm elements if we have changed the circumstance (here, options.mode)
+    pmPCMupdate(pcm, source, &options, model);
+    
+    float parStart[8];
+    for (int i = 0; i < 8; i++) parStart[i] = PAR[i];
+
+    // we start with a guess at the index (P[7])
+
+    // get chisq for P[7], P[7]*1.1, P[7]*1.25 (or *0.75 depending on the result of 1.1)
+
+    psVector *chi2 = psVectorAllocEmpty (16, PS_TYPE_F32);
+    psVector *Sidx = psVectorAllocEmpty (16, PS_TYPE_F32);
+
+    PAR[PM_PAR_7] = parStart[7];
+    pmSourceFitPCM (pcm, source, &options, maskVal, markVal, psfSize);
+      if (EXTRA_VERBOSE) fprintf (stderr, "%d >>> %d %f : %f - %f %f - %f %f %f - %f\n", source->id, model->nIter, model->chisqNorm, PAR[7], PAR[2], PAR[3], PAR[4], PAR[5], PAR[6], PAR[1]);
+    psVectorAppend (Sidx, 100*PAR[PM_PAR_7]);
+    psVectorAppend (chi2, model->chisqNorm);
+
+    float fI = 1.1;
+    PAR[PM_PAR_7] = parStart[7]*fI;
+    pmSourceFitPCM (pcm, source, &options, maskVal, markVal, psfSize);
+      if (EXTRA_VERBOSE) fprintf (stderr, "%d >>> %d %f : %f - %f %f - %f %f %f - %f\n", source->id, model->nIter, model->chisqNorm, PAR[7], PAR[2], PAR[3], PAR[4], PAR[5], PAR[6], PAR[1]);
+    psVectorAppend (Sidx, 100*PAR[PM_PAR_7]);
+    psVectorAppend (chi2, model->chisqNorm);
+
+    if (chi2->data.F32[1] < chi2->data.F32[0]) {
+      fI = 1.3;
+    } else {
+      fI = 1.0 / 1.3;
+    }
+    
+    PAR[PM_PAR_7] = parStart[7]*fI;
+    pmSourceFitPCM (pcm, source, &options, maskVal, markVal, psfSize);
+      if (EXTRA_VERBOSE) fprintf (stderr, "%d >>> %d %f : %f - %f %f - %f %f %f - %f\n", source->id, model->nIter, model->chisqNorm, PAR[7], PAR[2], PAR[3], PAR[4], PAR[5], PAR[6], PAR[1]);
+    psVectorAppend (Sidx, 100*PAR[PM_PAR_7]);
+    psVectorAppend (chi2, model->chisqNorm);
+
+    // can we fit the 3 pts with a parabola?
+    int nTry = 0;
+    psPolynomial1D *poly = psPolynomial1DAlloc (PS_POLYNOMIAL_ORD, 2);
+    while (!psVectorFitPolynomial1D (poly, NULL, 0, chi2, NULL, Sidx)) {
+      psErrorClear (); // clear the polynomial error
+      if (nTry > 4) {
+        psError(PS_ERR_UNKNOWN, true, "Failed to find a good chisq parabola");
+	psFree (chi2);
+	psFree (Sidx);
+	psFree (poly);
+	return false;
+      }
+      fI = (fI < 1.0) ? fI / 1.3 : fI * 1.3;
+      PAR[PM_PAR_7] = parStart[7]*fI;
+      pmSourceFitPCM (pcm, source, &options, maskVal, markVal, psfSize);
+      if (EXTRA_VERBOSE) fprintf (stderr, "%d >>> %d %f : %f - %f %f - %f %f %f - %f\n", source->id, model->nIter, model->chisqNorm, PAR[7], PAR[2], PAR[3], PAR[4], PAR[5], PAR[6], PAR[1]);
+      psVectorAppend (Sidx, 100*PAR[PM_PAR_7]);
+      psVectorAppend (chi2, model->chisqNorm);
+      nTry ++;
+    }
+
+    // where is the minimum of this polynomial fit?
+    float Smin = -0.5 * poly->coeff[1] / poly->coeff[2] / 100.0;
+
+    // constrain Smin to be in a valid range (1.0 - 0.1, corresponding to 0.5 (Gauss) to 5.0 (slightly peakier than Dev)
+    Smin = PS_MAX(PS_MIN(Smin, 1.0), 0.1);
+    PAR[PM_PAR_7] = Smin;
+
+    // pmSourceFitPCM (pcm, source, &options, maskVal, markVal, psfSize);
+    // if (EXTRA_VERBOSE) fprintf (stderr, "%d >>> %d %f : %f - %f %f - %f %f %f - %f\n", source->id, model->nIter, model->chisqNorm, PAR[7], PAR[2], PAR[3], PAR[4], PAR[5], PAR[6], PAR[1]);
+    
+    //// for (int i = 0; i < 8; i++) PAR[i] = parStart[i];
+    //// 
+    //// for (float fI = 0.0; fI < 0.15; fI += 0.01) {
+    ////   PAR[PM_PAR_7] = parStart[7] - fI;
+    //// 
+    ////   // fit EXT (not PSF) model (set/unset the pixel mask)
+    ////   
+    ////   pmSourceFitPCM (pcm, source, &options, maskVal, markVal, psfSize);
+    ////   if (TIMING) {
+    //// 	float *PAR = model->params->data.F32;
+    //// 	fprintf (stderr, "%d %f : %f - %f %f %f - %f\n", model->nIter, model->chisqNorm, PAR[7], PAR[4], PAR[5], PAR[6], PAR[1]);
+    ////   }
+    //// }
+
+    // return to the original fitting mode (fitOptions)
+    pmPCMupdate(pcm, source, fitOptions, model);
+
+    psFree (chi2);
+    psFree (Sidx);
+    psFree (poly);
+
+    return true;
+}
+
+ 
+// we have a set of guess parameters, do a small number of iterations fitting only SHAPE then only INDEX 
+bool psphotFitSersicShapeAndIndexGrid (pmPCMdata *pcm, pmReadout *readout, pmSource *source, pmSourceFitOptions *fitOptions, psImageMaskType maskVal, psImageMaskType markVal, int psfSize) {
+
+    pmModel *model = pcm->modelConv;
+
+    assert (model->type == pmModelClassGetType("PS_MODEL_SERSIC"));
+
+    pmSourceFitOptions options = *fitOptions;
+    
+    psF32 *PAR = pcm->modelConv->params->data.F32;
+
+    options.mode = PM_SOURCE_FIT_SHAPE;
+    options.nIter = 10;
+    
+    // update the pcm elements if we have changed the circumstance (here, options.mode)
+    pmPCMupdate(pcm, source, &options, model);
+    
+    psVector *chi2 = psVectorAllocEmpty (16, PS_TYPE_F32);
+    psVector *Sidx = psVectorAllocEmpty (16, PS_TYPE_F32);
+
+    float par7[] = {0.100, 0.125, 0.150, 0.175, 0.200, 0.225, 0.250};
+    for (int i = 0; i < 7; i++) {
+      PAR[PM_PAR_7] = par7[i];
+      pmSourceFitPCM (pcm, source, &options, maskVal, markVal, psfSize);
+      if (EXTRA_VERBOSE) fprintf (stderr, "%d >>> %d %f : %f - %f %f - %f %f %f - %f\n", source->id, model->nIter, model->chisqNorm, PAR[7], PAR[2], PAR[3], PAR[4], PAR[5], PAR[6], PAR[1]);
+      psVectorAppend (Sidx, PAR[PM_PAR_7]);
+      psVectorAppend (chi2, model->chisqNorm);
+    }
+
+    psPolynomial1D *poly = psPolynomial1DAlloc (PS_POLYNOMIAL_ORD, 2);
+    if (!psVectorFitPolynomial1D (poly, NULL, 0, chi2, NULL, Sidx)) {
+      psError(PS_ERR_UNKNOWN, true, "Failed to find a good chisq parabola");
+      psFree (chi2);
+      psFree (Sidx);
+      psFree (poly);
+      return false;
+    }
+
+    // where is the minimum of this polynomial fit?
+    fprintf (stderr, "fit1d: %f + %f x + %f x^2\n", poly->coeff[0], poly->coeff[1], poly->coeff[2]);
+    float Smin = -0.5 * poly->coeff[1] / poly->coeff[2];
+
+    // constrain Smin to be in a valid range (1.0 - 0.1, corresponding to 0.5 (Gauss) to 5.0 (slightly peakier than Dev)
+    Smin = PS_MAX(PS_MIN(Smin, 1.0), 0.1);
+    PAR[PM_PAR_7] = Smin;
+    pmSourceFitPCM (pcm, source, &options, maskVal, markVal, psfSize);
+    if (EXTRA_VERBOSE) fprintf (stderr, "%d >>> %d %f : %f - %f %f - %f %f %f - %f\n", source->id, model->nIter, model->chisqNorm, PAR[7], PAR[2], PAR[3], PAR[4], PAR[5], PAR[6], PAR[1]);
+    
+    //// for (int i = 0; i < 8; i++) PAR[i] = parStart[i];
+    //// 
+    //// for (float fI = 0.0; fI < 0.15; fI += 0.01) {
+    ////   PAR[PM_PAR_7] = parStart[7] - fI;
+    //// 
+    ////   // fit EXT (not PSF) model (set/unset the pixel mask)
+    ////   
+    ////   pmSourceFitPCM (pcm, source, &options, maskVal, markVal, psfSize);
+    ////   if (TIMING) {
+    //// 	float *PAR = model->params->data.F32;
+    //// 	fprintf (stderr, "%d %f : %f - %f %f %f - %f\n", model->nIter, model->chisqNorm, PAR[7], PAR[4], PAR[5], PAR[6], PAR[1]);
+    ////   }
+    //// }
+
+    // return to the original fitting mode (fitOptions)
+    pmPCMupdate(pcm, source, fitOptions, model);
+
+    psFree (chi2);
+    psFree (Sidx);
+    psFree (poly);
+
+    return true;
+}
+
+