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lsst-ts · Jun 23, 2023 · f0f3637 · f0f3637
1 parent 4421acf
commit f0f3637
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Showing 2 changed files with 21 additions and 10 deletions.
diff --git a/python/lsst/ts/wep/cwfs/algorithm.py b/python/lsst/ts/wep/cwfs/algorithm.py
@@ -816,9 +816,7 @@ def _singleItr(self, I1, I2, model, tol=1e-3):
                 for compIm in [I1, I2]:
                     if np.sum(np.isnan(compIm.blendOffsetX)) > 0:
                         continue
-                    compIm.makeMask(
-                        self._inst, model, boundaryT, 1
-                    )
+                    compIm.makeMask(self._inst, model, boundaryT, 1)
                     dilatedMask, numPaddingIter = compIm.autoDilateBlendMask(
                         compIm.mask_pupil
                     )
@@ -830,15 +828,27 @@ def _singleItr(self, I1, I2, model, tol=1e-3):
                     )
                     # Mask only blended areas in final stamp
                     compIm.updateImage(
-                        compIm.getImg() * np.invert(
-                            np.array(shiftedMask, dtype=bool)
-                        )
+                        compIm.getImg() * np.invert(np.array(shiftedMask, dtype=bool))
                     )
 
                 # If the compensable image has no blended centroids
                 # this function will just create a single masked donut
-                I1.makeBlendedMask(self._inst, model, boundaryT, 1, compensated=True, blendPadding=self.mask_growth_iter)
-                I2.makeBlendedMask(self._inst, model, boundaryT, 1, compensated=True, blendPadding=self.mask_growth_iter)
+                I1.makeBlendedMask(
+                    self._inst,
+                    model,
+                    boundaryT,
+                    1,
+                    compensated=True,
+                    blendPadding=self.mask_growth_iter,
+                )
+                I2.makeBlendedMask(
+                    self._inst,
+                    model,
+                    boundaryT,
+                    1,
+                    compensated=True,
+                    blendPadding=self.mask_growth_iter,
+                )
 
                 self._makeMasterMask(I1, I2, self.getPoissonSolverName())
 

diff --git a/python/lsst/ts/wep/cwfs/compensableImage.py b/python/lsst/ts/wep/cwfs/compensableImage.py
@@ -1661,11 +1661,12 @@ def calcNumPeaks(imageArray, blendMask):
             medianPixel = np.median(
                 maskedPixelVals[np.where(maskedPixelVals > maskedPixelHist[1][1])]
             )
-            binEdges = np.linspace(0.5 * medianPixel, 1.5*medianPixel, num=11)
+            binEdges = np.linspace(0.5 * medianPixel, 1.5 * medianPixel, num=11)
             binEdges[-1] = 2.5 * medianPixel
             binEdges = np.append(binEdges, 3.0 * medianPixel)
             maskedPixelHist = np.histogram(
-                maskedPixelVals, bins=binEdges, # range=(0.5 * medianPixel, 2.5 * medianPixel)
+                maskedPixelVals,
+                bins=binEdges,  # range=(0.5 * medianPixel, 2.5 * medianPixel)
             )
             print(maskedPixelHist)
             # Find the highest bins