def _update_bounding_polygon(self):
polygons = [im.polygon for im in self._images]
if len(polygons) == 0:
self._polygon = SphericalPolygon([])
self._radec = []
else:
self._polygon = SphericalPolygon.multi_union(polygons)
self._radec = list(self._polygon.to_radec())
def update_bounding_polygon(self):
""" Recompute bounding polygons of the member images.
"""
polygons = [im.polygon for im in self._images]
if len(polygons) == 0:
self._polygon = SphericalPolygon([])
else:
self._polygon = SphericalPolygon.multi_union(polygons)
def set_members(self, mlist, polygon):
if mlist is None:
member_list = []
elif isinstance(mlist, list):
member_list = mlist
if [1 for m in mlist if not isinstance(m, SkyLineMember)]:
raise ValueError("The \'mlist\' argument must be either "\
"a single \'SkyLineMember\' object or a " \
"Python list of \'SkyLineMember\' objects.")
elif isinstance(mlist, SkyLineMember):
member_list = [mlist]
else:
raise ValueError("The \'mlist\' argument must be either "\
"a single \'SkyLineMember\' object or a " \
"Python list of \'SkyLineMember\' objects.")
self._members = []
# Not using set to preserve order
n = len(member_list)
if n == 0:
if polygon is None:
self.polygon = SphericalPolygon([])
else:
self.polygon = deepcopy(polygon)
self._id = ''
self._is_mf_mosaic = False
elif n == 1:
assert isinstance(member_list[0], SkyLineMember)
if polygon is None:
self.polygon = deepcopy(member_list[0].polygon)
else:
self.polygon = deepcopy(polygon)
self._id = member_list[0].id
self._members.append(member_list[0])
self._is_mf_mosaic = False
else:
assert isinstance(member_list[0], SkyLineMember)
if polygon is None:
mpol = deepcopy(member_list[0].polygon)
else:
mpol = deepcopy(polygon)
self._members.append(member_list[0])
for m in member_list[1:]:
# Report corrupted members list instead of skipping
assert isinstance(m, SkyLineMember)
if m not in self._members:
self._members.append(m)
if polygon is None:
mpol = mpol.union(m.polygon)
self.polygon = mpol
self._update_mosaic_flag_id()
def __init__(self,
image,
wcs_fwd,
wcs_inv,
pix_area=1.0,
convf=1.0,
mask=None,
id=None,
skystat=None,
stepsize=None,
meta=None):
""" Initializes the SkyImage object.
Parameters
----------
image : numpy.ndarray
A 2D array of image data.
wcs_fwd : function
"forward" pixel-to-world transformation function.
wcs_inv : function
"inverse" world-to-pixel transformation function.
pix_area : float, optional
Average pixel's sky area.
convf : float, optional
Conversion factor that when multiplied to `image` data converts
the data to "uniform" (across multiple images) surface
brightness units.
.. note::
The functionality to support this conversion is not yet
implemented and at this moment `convf` is ignored.
mask : numpy.ndarray
A 2D array that indicates
what pixels in the input `image` should be used for sky
computations (``1``) and which pixels should **not** be used
for sky computations (``0``).
id : anything
The value of this parameter is simple stored within the `SkyImage`
object. While it can be of any type, it is prefereble that `id` be
of a type with nice string representation.
skystat : callable, None, optional
A callable object that takes a either a 2D image (2D
`numpy.ndarray`) or a list of pixel values (a Nx1 array) and
returns a tuple of two values: some statistics (e.g., mean,
median, etc.) and number of pixels/values from the input image
used in computing that statistics.
When `skystat` is not set, `SkyImage` will use
:py:class:`~jwst_pipeline.skymatch.skystatistics.SkyStats` object
to perform sky statistics on image data.
stepsize : int, None, optional
Spacing between vertices of the image's bounding polygon. Default
value of `None` creates bounding polygons with four vertices
corresponding to the corners of the image.
meta : dict, None, optional
A dictionary of various items to be stored within the `SkyImage`
object.
"""
self.image = image
self.convf = convf
self.meta = meta
self._id = id
self._pix_area = pix_area
# WCS
self.wcs_fwd = wcs_fwd
self.wcs_inv = wcs_inv
# initial sky value:
self._sky = 0.0
# check that mask has the same shape as image:
if mask is None:
self.mask = None
else:
if image is None:
raise ValueError("'mask' must be None when 'image' is None")
self.mask = np.asanyarray(mask, dtype=np.bool)
if self.mask.shape != image.shape:
raise ValueError("'mask' must have the same shape as 'image'.")
# create spherical polygon bounding the image
if image is None or wcs_fwd is None or wcs_inv is None:
self._radec = [(np.array([]), np.array([]))]
self._polygon = SphericalPolygon([])
self._poly_area = 0.0
else:
self.calc_bounding_polygon(stepsize)
# set sky statistics function (NOTE: it must return statistics and
# the number of pixels used after clipping)
if skystat is None:
self.set_builtin_skystat()
else:
self.skystat = skystat
def calc_sky(self, overlap=None, delta=True):
"""
Compute sky background value.
Parameters
----------
overlap : SkyImage, SkyGroup, SphericalPolygon, list of tuples, \
None, optional
Another `SkyImage`, `SkyGroup`,
:py:class:`stsci.sphere.polygons.SphericalPolygon`, or
a list of tuples of (RA, DEC) of vertices of a spherical
polygon. This parameter is used to indicate that sky statistics
should computed only in the region of intersection of *this*
image with the polygon indicated by `overlap`. When `overlap` is
`None`, sky statistics will be computed over the entire image.
delta : bool, optional
Should this function return absolute sky value or the difference
between the computed value and the value of the sky stored in the
`sky` property.
Returns
-------
skyval : float, None
Computed sky value (absolute or relative to the `sky` attribute).
If there are no valid data to perform this computations (e.g.,
because this image does not overlap with the image indicated by
`overlap`), `skyval` will be set to `None`.
npix : int
Number of pixels used to compute sky statistics.
polyarea : float
Area (in srad) of the polygon that bounds data used to compute
sky statistics.
"""
if overlap is None:
if self.mask is None:
data = self.image
else:
data = self.image[self.mask]
polyarea = self.poly_area
else:
fill_mask = np.zeros(self.image.shape, dtype=bool)
if isinstance(overlap, SkyImage):
intersection = self.intersection(overlap)
polyarea = np.fabs(intersection.area())
radec = list(intersection.to_radec())
elif isinstance(overlap, SkyGroup):
radec = []
polyarea = 0.0
for im in overlap:
intersection = self.intersection(im)
polyarea1 = np.fabs(intersection.area())
if polyarea1 == 0.0:
continue
polyarea += polyarea1
radec += list(intersection.to_radec())
elif isinstance(overlap, SphericalPolygon):
radec = []
polyarea = 0.0
for p in overlap._polygons:
intersection = self.intersection(SphericalPolygon([p]))
polyarea1 = np.fabs(intersection.area())
if polyarea1 == 0.0:
continue
polyarea += polyarea1
radec += list(intersection.to_radec())
else: # assume a list of (ra, dec) tuples:
radec = []
polyarea = 0.0
for r, d in overlap:
poly = SphericalPolygon.from_radec(r, d)
polyarea1 = np.fabs(poly.area())
if polyarea1 == 0.0 or len(r) < 4:
continue
polyarea += polyarea1
radec.append(self.intersection(poly).to_radec())
if polyarea == 0.0:
return (None, 0, 0.0)
for ra, dec in radec:
if len(ra) < 4:
continue
# set pixels in 'fill_mask' that are inside a polygon to True:
x, y = self.wcs_inv(ra, dec, 0)
poly_vert = list(zip(*[x, y]))
polygon = region.Polygon(True, poly_vert)
fill_mask = polygon.scan(fill_mask)
if self.mask is not None:
fill_mask &= self.mask
data = self.image[fill_mask]
if data.size < 1:
return (None, 0, 0.0)
# Calculate sky
try:
skyval, npix = self._skystat(data)
except ValueError:
return (None, 0, 0.0)
if delta:
skyval -= self._sky
return skyval, npix, polyarea