Index: trunk/psphot/src/psphotFitSourcesLinear.c
===================================================================
--- trunk/psphot/src/psphotFitSourcesLinear.c	(revision 33994)
+++ trunk/psphot/src/psphotFitSourcesLinear.c	(revision 34086)
@@ -12,10 +12,4 @@
 static bool SetBorderMatrixElements (psSparseBorder *border, pmReadout *readout, psArray *sources, bool constant_weights, int SKY_FIT_ORDER, psImageMaskType markVal);
 
-# if (HAVE_MODEL_VAR)
-bool psphotGenerateModelVariance (pmConfig *config, const pmFPAview *view, pmFPAfile *file, int index, psMetadata *recipe, pmReadout *readout, psArray *sources);
-pmSourceFitVarMode psphotGetFitVarMode (psMetadata *recipe);
-bool psphotFreeModelVariance (pmReadout *readout, psArray *sources);
-# endif
-
 // for now, let's store the detections on the readout->analysis for each readout
 bool psphotFitSourcesLinear (pmConfig *config, const pmFPAview *view, const char *filerule, bool final)
@@ -30,5 +24,4 @@
     assert (recipe);
 
-# if (HAVE_MODEL_VAR)
     pmSourceFitVarMode fitVarMode = psphotGetFitVarMode (recipe);
     if (!fitVarMode) {
@@ -40,5 +33,4 @@
     // do a single pass.
     pmSourceFitVarMode fitVarModePass1 = (fitVarMode == PM_SOURCE_PHOTFIT_MODEL_VAR) ? PM_SOURCE_PHOTFIT_CONST : fitVarMode;
-# endif
 
     int num = psphotFileruleCount(config, filerule);
@@ -68,15 +60,9 @@
         psAssert (psf, "missing psf?");
 
-# if (HAVE_MODEL_VAR)
-        if (!psphotFitSourcesLinearReadout (recipe, readout, sources, psf, final, fitVarModePass1))
-# else
-        if (!psphotFitSourcesLinearReadout (recipe, readout, sources, psf, final))
-# endif
-	{
+        if (!psphotFitSourcesLinearReadout (recipe, readout, sources, psf, final, fitVarModePass1)) {
             psError (PSPHOT_ERR_CONFIG, false, "failed to fit sources (linear) for %s entry %d", filerule, i);
             return false;
         }
 
-# if (HAVE_MODEL_VAR)
 	// the MODEL_VAR weighting scheme requires knowledge of the model fluxes to generate the variance
 	// after we have determined the initial set of fits, then we can generate the variance image and 
@@ -104,5 +90,4 @@
 	    }
 	}
-# endif
 
 	psphotVisualShowResidualImage (readout, (num > 0)); 
@@ -113,5 +98,4 @@
 }
 
-# if (HAVE_MODEL_VAR)
 // look up the fit variance mode from the recipe; older recipes do not have the value
 // 'LINEAR_FIT_VARIANCE_MODE'; in those cases, look for 'CONSTANT_PHOTOMETRIC_WEIGHTS' as a boolean and
@@ -136,4 +120,7 @@
 	return PM_SOURCE_PHOTFIT_IMAGE_VAR;
     }
+    if (!strcasecmp(fitVarModeString, "SKY")   || !strcasecmp(fitVarModeString, "MODEL_SKY")) {
+	return PM_SOURCE_PHOTFIT_MODEL_SKY;
+    }
     if (!strcasecmp(fitVarModeString, "MODEL") || !strcasecmp(fitVarModeString, "MODEL_VAR")) {
 	return PM_SOURCE_PHOTFIT_MODEL_VAR;
@@ -142,12 +129,6 @@
     return PM_SOURCE_PHOTFIT_NONE;
 }
-# endif
-
-# if (HAVE_MODEL_VAR)
-bool psphotFitSourcesLinearReadout (psMetadata *recipe, pmReadout *readout, psArray *sources, pmPSF *psf, bool final, pmSourceFitVarMode fitVarMode)
-# else
-bool psphotFitSourcesLinearReadout (psMetadata *recipe, pmReadout *readout, psArray *sources, pmPSF *psf, bool final)
-# endif
-{
+
+bool psphotFitSourcesLinearReadout (psMetadata *recipe, pmReadout *readout, psArray *sources, pmPSF *psf, bool final, pmSourceFitVarMode fitVarMode) {
     bool status;
     float x;
@@ -185,11 +166,4 @@
     if (psRegionIsNaN (AnalysisRegion)) psAbort("analysis region mis-defined");
 
-# if (!HAVE_MODEL_VAR)
-    bool CONSTANT_PHOTOMETRIC_WEIGHTS =
-        psMetadataLookupBool(&status, recipe, "CONSTANT_PHOTOMETRIC_WEIGHTS");
-    if (!status) {
-        psAbort("You must provide a value for the BOOL recipe CONSTANT_PHOTOMETRIC_WEIGHTS");
-    }
-# endif
     int SKY_FIT_ORDER = psMetadataLookupS32(&status, recipe, "SKY_FIT_ORDER");
     if (!status) {
@@ -299,5 +273,5 @@
 	    source->mode |= PM_SOURCE_MODE_PSFMODEL;
 	}	    
-	
+
         psArrayAdd (fitSources, 100, source);
     }
@@ -319,5 +293,4 @@
     psSparseBorder *border = psSparseBorderAlloc (sparse, nBorder);
 
-# if (HAVE_MODEL_VAR)
     // if fitVarMode is MODEL_VAR, then we need to generate the model image variance
     // XXX we have two possibilities here: 
@@ -327,5 +300,4 @@
 
     // 2) do a single pass, and use the model guess to define the model variance (but do I trust the Model Guess?)
-# endif
 
     // fill out the sparse matrix elements and border elements (B)
@@ -336,58 +308,29 @@
 
         // diagonal elements of the sparse matrix (auto-cross-product)
-# if (HAVE_MODEL_VAR)
-        f = pmSourceModelDotModel (SRCi, SRCi, fitVarMode, covarFactor, maskVal);
-# else
-        f = pmSourceModelDotModel (SRCi, SRCi, CONSTANT_PHOTOMETRIC_WEIGHTS, covarFactor, maskVal);
-# endif
-        psSparseMatrixElement (sparse, i, i, f);
-
-# if (HAVE_MODEL_VAR)
-        // if we have used CONSTANT errors, then we need to calculate the value of the parameter error
+        float MM = pmSourceModelDotModel (SRCi, SRCi, fitVarMode, covarFactor, maskVal);
+        psSparseMatrixElement (sparse, i, i, MM);
+
+        // if we have used CONSTANT errors, then we need to re-calculate the value of the parameter error
         if (fitVarMode != PM_SOURCE_PHOTFIT_IMAGE_VAR) {
             float var = pmSourceModelDotModel (SRCi, SRCi, PM_SOURCE_PHOTFIT_IMAGE_VAR, covarFactor, maskVal);
             errors->data.F32[i] = 1.0 / sqrt(var);
         } else {
-            errors->data.F32[i] = 1.0 / sqrt(f);
-        }
-# else
-        // the formal error depends on the weighting scheme
-        if (CONSTANT_PHOTOMETRIC_WEIGHTS) {
-            float var = pmSourceModelDotModel (SRCi, SRCi, false, covarFactor, maskVal);
-            errors->data.F32[i] = 1.0 / sqrt(var);
-        } else {
-            errors->data.F32[i] = 1.0 / sqrt(f);
-        }
-# endif
+            errors->data.F32[i] = 1.0 / sqrt(MM);
+        }
 
         // find the image x model value
-# if (HAVE_MODEL_VAR)
-        f = pmSourceDataDotModel (SRCi, SRCi, fitVarMode, covarFactor, maskVal);
-# else
-        f = pmSourceDataDotModel (SRCi, SRCi, CONSTANT_PHOTOMETRIC_WEIGHTS, covarFactor, maskVal);
-# endif
-        psSparseVectorElement (sparse, i, f);
+        float FM = pmSourceDataDotModel (SRCi, SRCi, fitVarMode, covarFactor, maskVal);
+        psSparseVectorElement (sparse, i, FM);
 
         // add the per-source variances (border region)
         switch (SKY_FIT_ORDER) {
           case 1:
-# if (HAVE_MODEL_VAR)
             f = pmSourceModelWeight (SRCi, 1, fitVarMode, covarFactor, maskVal);
             psSparseBorderElementB (border, i, 1, f);
             f = pmSourceModelWeight (SRCi, 2, fitVarMode, covarFactor, maskVal);
             psSparseBorderElementB (border, i, 2, f);
-# else
-            f = pmSourceModelWeight (SRCi, 1, CONSTANT_PHOTOMETRIC_WEIGHTS, covarFactor, maskVal);
-            psSparseBorderElementB (border, i, 1, f);
-            f = pmSourceModelWeight (SRCi, 2, CONSTANT_PHOTOMETRIC_WEIGHTS, covarFactor, maskVal);
-            psSparseBorderElementB (border, i, 2, f);
-# endif
 
           case 0:
-# if (HAVE_MODEL_VAR)
             f = pmSourceModelWeight (SRCi, 0, fitVarMode, covarFactor, maskVal);
-# else
-            f = pmSourceModelWeight (SRCi, 0, CONSTANT_PHOTOMETRIC_WEIGHTS, covarFactor, maskVal);
-# endif
             psSparseBorderElementB (border, i, 0, f);
             break;
@@ -409,9 +352,5 @@
 
             // got an overlap; calculate cross-product and add to output array
-# if (HAVE_MODEL_VAR)
             f = pmSourceModelDotModel (SRCi, SRCj, fitVarMode, covarFactor, maskVal);
-# else
-            f = pmSourceModelDotModel (SRCi, SRCj, CONSTANT_PHOTOMETRIC_WEIGHTS, covarFactor, maskVal);
-# endif
             psSparseMatrixElement (sparse, j, i, f);
         }
@@ -451,9 +390,5 @@
 
     // set the sky, sky_x, sky_y components of border matrix
-# if (HAVE_MODEL_VAR)
     SetBorderMatrixElements (border, readout, fitSources, (fitVarMode == PM_SOURCE_PHOTFIT_CONST), SKY_FIT_ORDER, markVal);
-# else
-    SetBorderMatrixElements (border, readout, fitSources, CONSTANT_PHOTOMETRIC_WEIGHTS, SKY_FIT_ORDER, markVal);
-# endif
 
     psSparseConstraint constraint;
@@ -500,4 +435,9 @@
     psLogMsg ("psphot.ensemble", PS_LOG_MINUTIA, "sub models: %f sec (%d elements)\n", psTimerMark ("psphot.linear"), sparse->Nelem);
 
+    // mean stats on fit windows
+    float sumRadius = 0.0;
+    float sumPixels = 0.0;
+    float sumSource = 0.0;
+
     // measure chisq for each source
     // for (int i = 0; final && (i < fitSources->n); i++) {
@@ -505,4 +445,10 @@
         pmSource *source = fitSources->data[i];
         pmModel *model = pmSourceGetModel (NULL, source);
+
+	// accumulate fit windows statistics
+        sumRadius += model->fitRadius;
+	sumPixels += M_PI*PS_SQR(model->fitRadius);
+	sumSource += 1.0;
+
         if (!(source->mode & PM_SOURCE_MODE_NONLINEAR_FIT)) {
 	    model->nPar = 1; // LINEAR-only sources have 1 parameter; NONLINEAR sources have their original value
@@ -511,4 +457,7 @@
     }
     psLogMsg ("psphot.ensemble", PS_LOG_MINUTIA, "get chisqs: %f sec (%d elements)\n", psTimerMark ("psphot.linear"), sparse->Nelem);
+
+    float meanRadius = sumRadius / sumSource;
+    float meanPixels = sumPixels / sumSource;
 
     // psFree (index);
@@ -520,5 +469,5 @@
     psFree (border);
 
-    psLogMsg ("psphot.ensemble", PS_LOG_WARN, "measure ensemble of PSFs: %f sec\n", psTimerMark ("psphot.linear"));
+    psLogMsg ("psphot.ensemble", PS_LOG_WARN, "measure ensemble of PSFs (mean radius = %f pixels, mean area = %f pixels: %f sec\n", meanRadius, meanPixels, psTimerMark ("psphot.linear"));
 
     psphotVisualPlotChisq (sources);
@@ -531,7 +480,4 @@
     return true;
 }
-
-// XXX do we need this?
-// XXX disallow the simultaneous sky fit and remove this code...
 
 // Calculate the weight terms for the sky fit component of the matrix.  This function operates
@@ -614,5 +560,4 @@
 }
 
-# if (HAVE_MODEL_VAR)
 bool psphotModelBackgroundReadout(psImage *model,  // Model image
 				  psImage *modelStdev, // Model stdev image
@@ -624,5 +569,5 @@
     );
 
-bool psphotGenerateModelVariance (pmConfig *config, const pmFPAview *view, pmFPAfile *file, int index, psMetadata *recipe, pmReadout *readout, psArray *sources) {
+ bool psphotGenerateModelVariance (pmConfig *config, const pmFPAview *view, pmFPAfile *file, int index, psMetadata *recipe, pmReadout *readout, psArray *sources) {
 
     bool status = false;
@@ -650,4 +595,5 @@
     psImage *varModelStdev = psImageAlloc(backBinning->nXruff, backBinning->nYruff, PS_TYPE_F32); // Background model
 
+    // generate an image of the mean variance image in DN
     if (!psphotModelBackgroundReadout(varModel, varModelStdev, NULL, readout, backBinning, config, true)) {
 	psError(PS_ERR_UNKNOWN, false, "Unable to generate background model");
@@ -664,10 +610,17 @@
 	return false;
     }
-
     psFree (varModel);
     psFree (varModelStdev);
 
-    // XXX for a test:
-    psphotSaveImage (NULL, modelVar, "model.bck.fits");
+    float gain = 1.0;  // accept 1.0 as a default since it is not critical to the analysis
+    pmCell *cell = readout->parent; // The parent cell
+    if (cell) {
+      gain = psMetadataLookupF32(&status, cell->concepts, "CELL.GAIN"); // Cell gain
+      if (!status) {
+	gain = 1.0;	      // set note above
+      }
+    }
+    if (gain > 2.0) { /* warn? */ }
+    // XXX we are not actually using the gain, but need to test it to avoid gcc pedantic warnings
 
     // insert all of the source models
@@ -690,10 +643,9 @@
 
 	// add the source model to the model variance image
+	// XXX note that this should be added with gain applied
+	// var_DN = flux_DN / gain [e/DN]
+	// to do this requires an API upgrade...
 	pmSourceAdd (source, PM_MODEL_OP_MODELVAR, maskVal);
     }
-
-    // XXX for a test:
-    psphotSaveImage (NULL, modelVar, "model.var.fits");
-    psphotSaveImage (NULL, readout->variance, "image.var.fits");
 
     // we save the model variance for future reference
@@ -724,3 +676,2 @@
     return true;
 }
-# endif