def setUp(self):
np.random.seed(1)
self.bbox = Box2I(Point2I(1000, 2000), Extent2I(200, 100))
self.filters = ["G", "R", "I"]
self.imgValue = 10
images = [ImageF(self.bbox, self.imgValue) for f in self.filters]
mImage = MultibandImage.fromImages(self.filters, images)
self.Mask = Mask[MaskPixel]
# Store the default mask planes for later use
maskPlaneDict = self.Mask().getMaskPlaneDict()
self.defaultMaskPlanes = sorted(maskPlaneDict,
key=maskPlaneDict.__getitem__)
# reset so tests will be deterministic
self.Mask.clearMaskPlaneDict()
for p in ("BAD", "SAT", "INTRP", "CR", "EDGE"):
self.Mask.addMaskPlane(p)
self.maskValue = self.Mask.getPlaneBitMask("BAD")
singles = [self.Mask(self.bbox) for f in range(len(self.filters))]
for n in range(len(singles)):
singles[n].set(self.maskValue)
mMask = MultibandMask.fromMasks(self.filters, singles)
self.varValue = 1e-2
images = [ImageF(self.bbox, self.varValue) for f in self.filters]
mVariance = MultibandImage.fromImages(self.filters, images)
self.maskedImage = MultibandMaskedImage(self.filters,
image=mImage,
mask=mMask,
variance=mVariance)
def fromArrays(filters,
image,
mask=None,
variance=None,
footprint=None,
xy0=None,
thresh=0,
peaks=None):
"""Create a `MultibandFootprint` from an `image`, `mask`, `variance`
Parameters
----------
filters: `list`
List of filter names.
image: array
An array to convert into `HeavyFootprint` objects.
Only pixels above the `thresh` value for at least one band
will be included in the `SpanSet` and resulting footprints.
mask: array
Mask for the `image` array.
variance: array
Variance of the `image` array.
footprint: `Footprint`
`Footprint` that contains the `SpanSet` and `PeakCatalog`
to use for the `HeavyFootprint` in each band.
If `footprint` is `None` then the `thresh` is used to create a
`Footprint` based on the pixels above the `thresh` value.
xy0: `Point2I`
If `image` is an array and `footprint` is `None` then specifying
`xy0` gives the location of the minimum `x` and `y` value of the
`images`.
thresh: float or list of floats
Threshold in each band (or the same threshold to be used in all bands)
to include a pixel in the `SpanSet` of the `MultibandFootprint`.
If `Footprint` is not `None` then `thresh` is ignored.
peaks: `PeakCatalog`
Catalog containing information about the peaks located in the
footprints.
Returns
-------
result: `MultibandFootprint`
MultibandFootprint created from the arrays
"""
# Generate a new Footprint if one has not been specified
if footprint is None:
spans, imageBBox = getSpanSetFromImages(image, thresh, xy0)
footprint = Footprint(spans)
else:
imageBBox = footprint.getBBox()
if peaks is not None:
footprint.setPeakCatalog(peaks)
mMaskedImage = MultibandMaskedImage.fromArrays(filters, image, mask,
variance, imageBBox)
singles = [
makeHeavyFootprint(footprint, maskedImage)
for maskedImage in mMaskedImage
]
return MultibandFootprint(filters, singles)
def fromArrays(filters, image, mask=None, variance=None, footprint=None, xy0=None, thresh=0, peaks=None):
"""Create a `MultibandFootprint` from an `image`, `mask`, `variance`
Parameters
----------
filters: `list`
List of filter names.
image: array
An array to convert into `HeavyFootprint` objects.
Only pixels above the `thresh` value for at least one band
will be included in the `SpanSet` and resulting footprints.
mask: array
Mask for the `image` array.
variance: array
Variance of the `image` array.
footprint: `Footprint`
`Footprint` that contains the `SpanSet` and `PeakCatalog`
to use for the `HeavyFootprint` in each band.
If `footprint` is `None` then the `thresh` is used to create a
`Footprint` based on the pixels above the `thresh` value.
xy0: `Point2I`
If `image` is an array and `footprint` is `None` then specifying
`xy0` gives the location of the minimum `x` and `y` value of the
`images`.
thresh: float or list of floats
Threshold in each band (or the same threshold to be used in all bands)
to include a pixel in the `SpanSet` of the `MultibandFootprint`.
If `Footprint` is not `None` then `thresh` is ignored.
peaks: `PeakCatalog`
Catalog containing information about the peaks located in the
footprints.
Returns
-------
result: `MultibandFootprint`
MultibandFootprint created from the arrays
"""
# Generate a new Footprint if one has not been specified
if footprint is None:
spans, imageBBox = getSpanSetFromImages(image, thresh, xy0)
footprint = Footprint(spans)
else:
imageBBox = footprint.getBBox()
if peaks is not None:
footprint.setPeakCatalog(peaks)
mMaskedImage = MultibandMaskedImage.fromArrays(filters, image, mask, variance, imageBBox)
singles = [makeHeavyFootprint(footprint, maskedImage) for maskedImage in mMaskedImage]
return MultibandFootprint(filters, singles)
def fromImages(filters,
image,
mask=None,
variance=None,
footprint=None,
thresh=0,
peaks=None):
"""Create a `MultibandFootprint` from an `image`, `mask`, `variance`
Parameters
----------
filters: list
List of filter names.
image: `MultibandImage`, or list of `Image`
A `MultibandImage` (or collection of images in each band)
to convert into `HeavyFootprint` objects.
Only pixels above the `thresh` value for at least one band
will be included in the `SpanSet` and resulting footprints.
mask: `MultibandMask` or list of `Mask`
Mask for the `image`.
variance: `MultibandImage`, or list of `Image`
Variance of the `image`.
thresh: `float` or `list` of floats
Threshold in each band (or the same threshold to be used in all bands)
to include a pixel in the `SpanSet` of the `MultibandFootprint`.
If `Footprint` is not `None` then `thresh` is ignored.
peaks: `PeakCatalog`
Catalog containing information about the peaks located in the
footprints.
Returns
-------
result: `MultibandFootprint`
MultibandFootprint created from the image, mask, and variance
"""
# Generate a new Footprint if one has not been specified
if footprint is None:
spans, imageBBox = getSpanSetFromImages(image, thresh)
footprint = Footprint(spans)
if peaks is not None:
footprint.setPeakCatalog(peaks)
mMaskedImage = MultibandMaskedImage(filters, image, mask, variance)
singles = [
makeHeavyFootprint(footprint, maskedImage)
for maskedImage in mMaskedImage
]
return MultibandFootprint(filters, singles)