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DM-34566: Fix deprecation warnings #225

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Jun 30, 2022
Merged

DM-34566: Fix deprecation warnings #225

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7618c22
Fix numpy deprecation warnings
erinleighh Jun 28, 2022
e5665bd
Fix filterLabel and use filter property
erinleighh Jun 28, 2022
04e3282
Use photoCalib and wcs properties
erinleighh Jun 28, 2022
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10 changes: 5 additions & 5 deletions python/lsst/ip/diffim/dcrModel.py
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Original file line number Diff line number Diff line change
Expand Up @@ -561,7 +561,7 @@ def regularizeModelFreq(self, modelImages, bbox, statsCtrl, regularizationFactor
# The noise should be lower in the smoothed image by
# sqrt(Nsmooth) ~ fwhm pixels
noiseLevel /= fwhm
smoothRef = ndimage.filters.gaussian_filter(referenceImage, filterWidth, mode='constant')
smoothRef = ndimage.gaussian_filter(referenceImage, filterWidth, mode='constant')
# Add a three sigma offset to both the reference and model to prevent
# dividing by zero. Note that this will also slightly suppress faint
# variations in color.
Expand All @@ -574,12 +574,12 @@ def regularizeModelFreq(self, modelImages, bbox, statsCtrl, regularizationFactor
highThreshold=highThreshold,
lowThreshold=lowThreshold,
regularizationWidth=regularizationWidth)
smoothModel = ndimage.filters.gaussian_filter(model.array, filterWidth, mode='constant')
smoothModel = ndimage.gaussian_filter(model.array, filterWidth, mode='constant')
smoothModel += 3.*noiseLevel
relativeModel = smoothModel/smoothRef
# Now sharpen the smoothed relativeModel using an alpha of 3.
alpha = 3.
relativeModel2 = ndimage.filters.gaussian_filter(relativeModel, filterWidth/alpha)
relativeModel2 = ndimage.gaussian_filter(relativeModel, filterWidth/alpha)
relativeModel += alpha*(relativeModel - relativeModel2)
model.array = relativeModel*referenceImage

Expand Down Expand Up @@ -653,13 +653,13 @@ def applyImageThresholds(self, image, highThreshold=None, lowThreshold=None, reg
highPixels = image > highThreshold
if regularizationWidth > 0:
# Erode and dilate ``highPixels`` to exclude noisy pixels.
highPixels = ndimage.morphology.binary_opening(highPixels, structure=filterStructure)
highPixels = ndimage.binary_opening(highPixels, structure=filterStructure)
image[highPixels] = highThreshold[highPixels]
if lowThreshold is not None:
lowPixels = image < lowThreshold
if regularizationWidth > 0:
# Erode and dilate ``lowPixels`` to exclude noisy pixels.
lowPixels = ndimage.morphology.binary_opening(lowPixels, structure=filterStructure)
lowPixels = ndimage.binary_opening(lowPixels, structure=filterStructure)
image[lowPixels] = lowThreshold[lowPixels]


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2 changes: 1 addition & 1 deletion python/lsst/ip/diffim/dipoleFitTask.py
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Expand Up @@ -727,7 +727,7 @@ def dipoleModelFunctor(x, flux, xcenPos, ycenPos, xcenNeg, ycenNeg, fluxNeg=None
gmod.set_param_hint('y2Neg', value=bgParsNeg[5])

y, x = np.mgrid[bbox.getBeginY():bbox.getEndY(), bbox.getBeginX():bbox.getEndX()]
in_x = np.array([x, y]).astype(np.float)
in_x = np.array([x, y]).astype(np.float64)
in_x[0, :] -= in_x[0, :].mean() # center it!
in_x[1, :] -= in_x[1, :].mean()

Expand Down
8 changes: 4 additions & 4 deletions tests/test_dcrModel.py
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Expand Up @@ -455,11 +455,11 @@ def testRegularizationSmallClamp(self):
np.max(model.array - templateImage))
highThreshold = templateImage*clampFrequency
highPix = model.array > highThreshold
highPix = ndimage.morphology.binary_opening(highPix, iterations=regularizationWidth)
highPix = ndimage.binary_opening(highPix, iterations=regularizationWidth)
self.assertFalse(np.all(highPix))
lowThreshold = templateImage/clampFrequency
lowPix = model.array < lowThreshold
lowPix = ndimage.morphology.binary_opening(lowPix, iterations=regularizationWidth)
lowPix = ndimage.binary_opening(lowPix, iterations=regularizationWidth)
self.assertFalse(np.all(lowPix))

def testRegularizationSidelobes(self):
Expand Down Expand Up @@ -517,11 +517,11 @@ def testRegularizeModelIter(self):
# Check that all of the outliers are clipped
highThreshold = oldModel.array*modelClampFactor
highPix = newModel.array > highThreshold
highPix = ndimage.morphology.binary_opening(highPix, iterations=regularizationWidth)
highPix = ndimage.binary_opening(highPix, iterations=regularizationWidth)
self.assertFalse(np.all(highPix))
lowThreshold = oldModel.array/modelClampFactor
lowPix = newModel.array < lowThreshold
lowPix = ndimage.morphology.binary_opening(lowPix, iterations=regularizationWidth)
lowPix = ndimage.binary_opening(lowPix, iterations=regularizationWidth)
self.assertFalse(np.all(lowPix))

def testIterateModel(self):
Expand Down
12 changes: 6 additions & 6 deletions tests/test_subtractTask.py
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Expand Up @@ -631,9 +631,9 @@ def _run_and_check_images(doDecorrelation):

# check PSF, WCS, bbox, filterLabel, photoCalib, aperture correction
self._compare_apCorrMaps(apCorrMap, output.difference.info.getApCorrMap())
self.assertWcsAlmostEqualOverBBox(science.getWcs(), output.difference.getWcs(), science.getBBox())
self.assertEqual(science.getFilterLabel(), output.difference.getFilterLabel())
self.assertEqual(science.getPhotoCalib(), output.difference.getPhotoCalib())
self.assertWcsAlmostEqualOverBBox(science.wcs, output.difference.wcs, science.getBBox())
self.assertEqual(science.filter, output.difference.filter)
self.assertEqual(science.photoCalib, output.difference.photoCalib)
_run_and_check_images(doDecorrelation=True)
_run_and_check_images(doDecorrelation=False)

Expand Down Expand Up @@ -680,9 +680,9 @@ def _run_and_check_images(doDecorrelation):

# check PSF, WCS, bbox, filterLabel, photoCalib, aperture correction
self._compare_apCorrMaps(apCorrMap, output.difference.info.getApCorrMap())
self.assertWcsAlmostEqualOverBBox(science.getWcs(), output.difference.getWcs(), science.getBBox())
self.assertEqual(science.getFilterLabel(), output.difference.getFilterLabel())
self.assertEqual(science.getPhotoCalib(), output.difference.getPhotoCalib())
self.assertWcsAlmostEqualOverBBox(science.wcs, output.difference.wcs, science.getBBox())
self.assertEqual(science.filter, output.difference.filter)
self.assertEqual(science.photoCalib, output.difference.photoCalib)

_run_and_check_images(doDecorrelation=True)
_run_and_check_images(doDecorrelation=False)
Expand Down