def testGMixToMultiShapelet(self):
np.random.seed(5) # value doesn't matter, but we want deterministic numbers
msf1 = MultiShapeletFunction([self.makeRandomShapeletFunction(order=0) for n in range(4)])
gmix1 = convertMultiShapeletToGMix(msf1)
msf2 = convertGMixToMultiShapelet(gmix1)
# Test that we've round-tripped through GMix
self.compareMultiShapeletFunctions(msf1, msf2, simplify=False)
# Test that LSST and ngmix make images that agree
bbox = Box2I(Point2I(-20, -15), Point2I(20, 15))
image1 = Image(bbox, dtype=np.float64)
msf1.evaluate().addToImage(image1)
image2 = Image(bbox, dtype=np.float64)
image2.array[:, :] = gmix1.make_image(image2.array.shape)
self.assertImagesAlmostEqual(image1, image2)
# Should reject ShapeletFunctions with order > 0, unless ignoreHighOrder==True
with self.assertRaises(ValueError):
problematic = MultiShapeletFunction([self.makeRandomShapeletFunction(order=2) for n in range(4)])
convertMultiShapeletToGMix(problematic)
ok = convertMultiShapeletToGMix(problematic, ignoreHighOrder=True)
truncated1 = convertGMixToMultiShapelet(ok)
truncated2 = MultiShapeletFunction([ShapeletFunction(0, HERMITE, p.getEllipse(),
p.getCoefficients()[0:1])
for p in problematic.getComponents()])
self.compareMultiShapeletFunctions(truncated1, truncated2)
def _doComputeKernelImage(self, position=None, color=None):
bbox = self.computeBBox()
img = Image(bbox, dtype=np.float64)
x, y = np.ogrid[bbox.minY:bbox.maxY + 1, bbox.minX:bbox.maxX + 1]
rsqr = x**2 + y**2
img.array[:] = np.exp(-0.5 * rsqr / self.sigma**2)
img.array /= np.sum(img.array)
return img
def _doComputeKernelImage(self, position=None, color=None):
bbox = Box2I(Point2I(-3, -3), Extent2I(7, 7))
img = Image(bbox, dtype=np.float64)
x, y = np.ogrid[bbox.minY:bbox.maxY + 1, bbox.minX:bbox.maxX + 1]
rsqr = x**2 + y**2
if position.x >= 0.0:
img.array[:] = np.exp(-0.5 * rsqr)
else:
img.array[:] = np.exp(-0.5 * rsqr / 4)
img.array /= np.sum(img.array)
return img
def _doImage(self, position, center):
# Follow Piff conventions for center.
# None => draw as if star at position
# True => draw in center of image
gsimg = self._piffResult.draw(position.x,
position.y,
stamp_size=self.width,
center=center)
bbox = self._doBBox(position, center)
img = Image(bbox, dtype=np.float64)
img.array[:] = gsimg.array
img.array /= np.sum(img.array)
return img
def setUp(self):
dimensions = Extent2I(7, 7)
self.bbox = Box2I(Point2I(-dimensions/2), dimensions)
self.img = Image(self.bbox, dtype=np.float64)
x, y = np.ogrid[-3:4, -3:4]
rsqr = x**2 + y**2
# Some arbitrary circular double Gaussian
self.img.array[:] = np.exp(-0.5*rsqr**2) + np.exp(-0.5*rsqr**2/4)
self.img.array /= np.sum(self.img.array)
self.psf = MyTestImagePsf(self.img)
def testImageFitsReader(self):
for n, dtypeIn in enumerate(self.dtypes):
with self.subTest(dtypeIn=dtypeIn):
imageIn = Image(self.bbox, dtype=dtypeIn)
imageIn.array[:, :] = np.random.randint(low=1, high=5, size=imageIn.array.shape)
with lsst.utils.tests.getTempFilePath(".fits") as fileName:
imageIn.writeFits(fileName)
reader = ImageFitsReader(fileName)
self.assertEqual(reader.readBBox(), self.bbox)
self.assertEqual(reader.readDType(), dtypeIn)
self.assertEqual(reader.fileName, fileName)
for args in self.args:
with self.subTest(args=args):
array1 = reader.readArray(*args)
image1 = reader.read(*args)
subIn = imageIn.subset(*args) if args else imageIn
self.assertEqual(dtypeIn, array1.dtype)
self.assertTrue(np.all(subIn.array == array1))
self.assertEqual(subIn.getXY0(), reader.readXY0(*args))
self.assertImagesEqual(subIn, image1)
for dtype2 in self.dtypes[n:]:
for args in self.args:
with self.subTest(dtype2=dtype2, args=args):
subIn = imageIn.subset(*args) if args else imageIn
array2 = reader.readArray(*args, dtype=dtype2)
image2 = reader.read(*args, dtype=dtype2)
self.assertEqual(dtype2, array2.dtype)
self.assertTrue(np.all(subIn.array == array2))
self.assertEqual(subIn.getXY0(), reader.readXY0(*args))
self.assertEqual(subIn.getBBox(), image2.getBBox())
self.assertTrue(np.all(image2.array == array2))
def checkMultiPlaneReader(self, reader, objectIn, fileName, dtypesOut,
compare):
"""Test operations common to MaskedImageFitsReader and ExposureFitsReader.
Parameters
----------
reader : `MaskedImageFitsReader` or `ExposureFitsReader` instance
Reader object to test.
objectIn : `MaskedImage` or `Exposure`
Object originally saved, to compare against.
fileName : `str`
Name of the file the reader is reading.
dtypesOut : sequence of `numpy.dype`
Compatible image pixel types to try to read in.
compare : callable
Callable that compares objects of the same type as objectIn and
asserts if they are not equal.
"""
dtypeIn = objectIn.image.dtype
self.assertEqual(reader.readBBox(), self.bbox)
self.assertEqual(reader.readImageDType(), dtypeIn)
self.assertEqual(reader.readMaskDType(), MaskPixel)
self.assertEqual(reader.readVarianceDType(), VariancePixel)
self.assertEqual(reader.fileName, fileName)
for args in self.args:
with self.subTest(args=args):
object1 = reader.read(*args)
subIn = objectIn.subset(*args) if args else objectIn
self.assertEqual(object1.image.array.dtype, dtypeIn)
self.assertEqual(object1.mask.array.dtype, MaskPixel)
self.assertEqual(object1.variance.array.dtype, VariancePixel)
self.assertImagesEqual(subIn.image, reader.readImage(*args))
self.assertImagesEqual(subIn.mask, reader.readMask(*args))
self.assertImagesEqual(subIn.variance,
reader.readVariance(*args))
compare(subIn, object1)
for dtype2 in dtypesOut:
with self.subTest(dtype2=dtype2, args=args):
object2 = reader.read(*args, dtype=dtype2)
image2 = reader.readImage(*args, dtype=dtype2)
self.assertEqual(object2.image.array.dtype, dtype2)
self.assertEqual(object2.mask.array.dtype, MaskPixel)
self.assertEqual(object2.variance.array.dtype,
VariancePixel)
self.assertImagesEqual(
subIn.image, Image(image2,
deep=True,
dtype=dtypeIn))
self.assertImagesEqual(image2, object2.image)
compare(subIn, object2)
def testImageFitsReader(self):
for n, dtypeIn in enumerate(self.dtypes):
with self.subTest(dtypeIn=dtypeIn):
imageIn = Image(self.bbox, dtype=dtypeIn)
imageIn.array[:, :] = np.random.randint(
low=1, high=5, size=imageIn.array.shape)
with lsst.utils.tests.getTempFilePath(".fits") as fileName:
imageIn.writeFits(fileName)
reader = ImageFitsReader(fileName)
self.assertEqual(reader.readBBox(), self.bbox)
self.assertEqual(reader.readDType(), dtypeIn)
self.assertEqual(reader.fileName, fileName)
for args in self.args:
with self.subTest(args=args):
array1 = reader.readArray(*args)
image1 = reader.read(*args)
subIn = imageIn.subset(*args) if args else imageIn
self.assertEqual(dtypeIn, array1.dtype)
self.assertTrue(np.all(subIn.array == array1))
self.assertEqual(subIn.getXY0(),
reader.readXY0(*args))
self.assertImagesEqual(subIn, image1)
for dtype2 in self.dtypes[n:]:
for args in self.args:
with self.subTest(dtype2=dtype2, args=args):
subIn = imageIn.subset(
*args) if args else imageIn
array2 = reader.readArray(*args, dtype=dtype2)
image2 = reader.read(*args, dtype=dtype2)
self.assertEqual(dtype2, array2.dtype)
self.assertTrue(np.all(subIn.array == array2))
self.assertEqual(subIn.getXY0(),
reader.readXY0(*args))
self.assertEqual(subIn.getBBox(),
image2.getBBox())
self.assertTrue(np.all(image2.array == array2))