"""
The ``skyimage`` module contains algorithms that are used by
``skymatch`` to manage all of the information for footprints (image outlines)
on the sky as well as perform useful operations on these outlines such as
computing intersections and statistics in the overlap regions.
:Authors: Mihai Cara (contact: help@stsci.edu)
"""
# STDLIB
import abc
import tempfile
# THIRD-PARTY
import numpy as np
from spherical_geometry.polygon import SphericalPolygon
# LOCAL
from . skystatistics import SkyStats
from . import region
__all__ = ['SkyImage', 'SkyGroup', 'DataAccessor', 'NDArrayInMemoryAccessor',
'NDArrayMappedAccessor']
[docs]
class DataAccessor(abc.ABC):
""" Base class for all data accessors. Provides a common interface to
access data.
"""
[docs]
@abc.abstractmethod
def get_data(self): # pragma: no cover
pass
[docs]
@abc.abstractmethod
def set_data(self, data): # pragma: no cover
""" Sets data.
Parameters
----------
data : numpy.ndarray
Data array to be set.
"""
pass
[docs]
@abc.abstractmethod
def get_data_shape(self): # pragma: no cover
pass
[docs]
class NDArrayInMemoryAccessor(DataAccessor):
""" Acessor for in-memory `numpy.ndarray` data. """
def __init__(self, data):
super().__init__()
self._data = data
[docs]
def get_data(self):
return self._data
[docs]
def set_data(self, data):
self._data = data
[docs]
def get_data_shape(self):
return np.shape(self._data)
[docs]
class NDArrayMappedAccessor(DataAccessor):
""" Data accessor for arrays stored in temporary files. """
def __init__(self, data, tmpfile=None, prefix='tmp_skymatch_',
suffix='.npy', tmpdir=''):
super().__init__()
if tmpfile is None:
self._close = True
self._tmp = tempfile.NamedTemporaryFile(
prefix=prefix,
suffix=suffix,
dir=tmpdir
)
if not self._tmp:
raise RuntimeError("Unable to create temporary file.")
else:
# temp file managed by the caller
self._close = False
self._tmp = tmpfile
self.set_data(data)
[docs]
def get_data(self):
self._tmp.seek(0)
return np.load(self._tmp)
[docs]
def set_data(self, data):
data = np.asanyarray(data)
self._data_shape = data.shape
self._tmp.seek(0)
np.save(self._tmp, data)
def __del__(self):
if self._close:
self._tmp.close()
[docs]
def get_data_shape(self):
return self._data_shape
[docs]
class SkyImage:
"""
Container that holds information about properties of a *single*
image such as:
* image data;
* WCS of the chip image;
* bounding spherical polygon;
* id;
* pixel area;
* sky background value;
* sky statistics parameters;
* mask associated image data indicating "good" (1) data.
"""
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,
reduce_memory_usage=True):
""" Initializes the SkyImage object.
Parameters
----------
image : numpy.ndarray, NDArrayDataAccessor
A 2D array of image data or a `NDArrayDataAccessor`.
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, NDArrayDataAccessor
A 2D array or `NDArrayDataAccessor` of a 2D array that indicates
which 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 preferable 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.
reduce_memory_usage : bool, optional
Indicates whether to attempt to minimize memory usage by attaching
input ``image`` and/or ``mask`` `numpy.ndarray` arrays to
file-mapped accessor. This has no effect when input parameters
``image`` and/or ``mask`` are already of `NDArrayDataAccessor`
objects.
"""
self._image = None
self._mask = None
self._image_shape = None
self._mask_shape = None
self._reduce_memory_usage = reduce_memory_usage
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
self._sky_is_valid = False
self.mask = mask
# 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
@property
def mask(self):
""" Set or get `SkyImage`'s ``mask`` data array or `None`. """
if self._mask is None:
return None
else:
return self._mask.get_data()
@mask.setter
def mask(self, mask):
if mask is None:
self._mask = None
self._mask_shape = None
elif isinstance(mask, DataAccessor):
if self._image is None:
raise ValueError("'mask' must be None when 'image' is None")
self._mask = mask
self._mask_shape = mask.get_data_shape()
# check that mask has the same shape as image:
if self._mask_shape != self.image_shape:
raise ValueError("'mask' must have the same shape as 'image'.")
else:
if self._image is None:
raise ValueError("'mask' must be None when 'image' is None")
mask = np.asanyarray(mask, dtype=bool)
self._mask_shape = mask.shape
# check that mask has the same shape as image:
if self._mask_shape != self.image_shape:
raise ValueError("'mask' must have the same shape as 'image'.")
if self._mask is None:
if self._reduce_memory_usage:
self._mask = NDArrayMappedAccessor(
mask,
prefix='tmp_skymatch_mask_'
)
else:
self._mask = NDArrayInMemoryAccessor(mask)
else:
self._mask.set_data(mask)
@property
def image(self):
""" Set or get `SkyImage`'s ``image`` data array. """
if self._image is None:
return None
else:
return self._image.get_data()
@image.setter
def image(self, image):
if image is None:
self._image = None
self._image_shape = None
self.mask = None
if isinstance(image, DataAccessor):
self._image = image
self._image_shape = image.get_data_shape()
else:
image = np.asanyarray(image)
self._image_shape = image.shape
if self._image is None:
if self._reduce_memory_usage:
self._image = NDArrayMappedAccessor(
image,
prefix='tmp_skymatch_image_'
)
else:
self._image = NDArrayInMemoryAccessor(image)
else:
self._image.set_data(image)
@property
def image_shape(self):
""" Get `SkyImage`'s ``image`` data shape. """
if self._image_shape is None and self._image is not None:
self._image_shape = self._image.get_data_shape()
return self._image_shape
@property
def id(self):
""" Set or get `SkyImage`'s `id`.
While `id` can be of any type, it is preferable that `id` be
of a type with nice string representation.
"""
return self._id
@id.setter
def id(self, id):
self._id = id
@property
def pix_area(self):
""" Set or get mean pixel area.
"""
return self._pix_area
@pix_area.setter
def pix_area(self, pix_area):
self._pix_area = pix_area
@property
def poly_area(self):
""" Get bounding polygon area in srad units.
"""
return self._poly_area
@property
def sky(self):
""" Sky background value. See `calc_sky` for more details.
"""
return self._sky
@sky.setter
def sky(self, sky):
self._sky = sky
@property
def is_sky_valid(self):
"""
Indicates whether sky value was successfully computed.
Must be set externally.
"""
return self._sky_is_valid
@is_sky_valid.setter
def is_sky_valid(self, valid):
self._sky_is_valid = valid
@property
def radec(self):
"""
Get RA and DEC of the vertices of the bounding polygon as a
`~numpy.ndarray` of shape (N, 2) where N is the number of vertices + 1.
"""
return self._radec
@property
def polygon(self):
""" Get image's bounding polygon.
"""
return self._polygon
[docs]
def intersection(self, skyimage):
"""
Compute intersection of this `SkyImage` object and another
`SkyImage`, `SkyGroup`, or
:py:class:`~spherical_geometry.polygon.SphericalPolygon`
object.
Parameters
----------
skyimage : SkyImage, SkyGroup, SphericalPolygon
Another object that should be intersected with this `SkyImage`.
Returns
-------
polygon : SphericalPolygon
A :py:class:`~spherical_geometry.polygon.SphericalPolygon` that is
the intersection of this `SkyImage` and `skyimage`.
"""
if isinstance(skyimage, (SkyImage, SkyGroup)):
other = skyimage.polygon
else:
other = skyimage
pts1 = np.sort(list(self._polygon.points)[0], axis=0)
pts2 = np.sort(list(other.points)[0], axis=0)
if np.allclose(pts1, pts2, rtol=0, atol=5e-9):
intersect_poly = self._polygon.copy()
else:
intersect_poly = self._polygon.intersection(other)
return intersect_poly
[docs]
def calc_bounding_polygon(self, stepsize=None):
""" Compute image's bounding polygon.
Parameters
----------
stepsize : int, None, optional
Indicates the maximum separation between two adjacent vertices
of the bounding polygon along each side of the image. Corners
of the image are included automatically. If `stepsize` is `None`,
bounding polygon will contain only vertices of the image.
"""
ny, nx = self.image_shape
if stepsize is None:
nintx = 2
ninty = 2
else:
nintx = max(2, int(np.ceil((nx + 1.0) / stepsize)))
ninty = max(2, int(np.ceil((ny + 1.0) / stepsize)))
xs = np.linspace(-0.5, nx - 0.5, nintx, dtype=float)
ys = np.linspace(-0.5, ny - 0.5, ninty, dtype=float)[1:-1]
nptx = xs.size
npty = ys.size
npts = 2 * (nptx + npty)
borderx = np.empty((npts + 1,), dtype=float)
bordery = np.empty((npts + 1,), dtype=float)
# "bottom" points:
borderx[:nptx] = xs
bordery[:nptx] = -0.5
# "right"
sl = np.s_[nptx:nptx + npty]
borderx[sl] = nx - 0.5
bordery[sl] = ys
# "top"
sl = np.s_[nptx + npty:2 * nptx + npty]
borderx[sl] = xs[::-1]
bordery[sl] = ny - 0.5
# "left"
sl = np.s_[2 * nptx + npty:-1]
borderx[sl] = -0.5
bordery[sl] = ys[::-1]
# close polygon:
borderx[-1] = borderx[0]
bordery[-1] = bordery[0]
ra, dec = self.wcs_fwd(borderx, bordery, with_bounding_box=False)
# TODO: for strange reasons, occasionally ra[0] != ra[-1] and/or
# dec[0] != dec[-1] (even though we close the polygon in the
# previous two lines). Then SphericalPolygon fails because
# points are not closed. Therefore we force it to be closed:
ra[-1] = ra[0]
dec[-1] = dec[0]
self._radec = [(ra, dec)]
self._polygon = SphericalPolygon.from_radec(ra, dec)
self._poly_area = np.fabs(self._polygon.area())
@property
def skystat(self):
""" Stores/retrieves 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.
"""
return self._skystat
@skystat.setter
def skystat(self, skystat):
self._skystat = skystat
[docs]
def set_builtin_skystat(self, skystat='median', lower=None, upper=None,
nclip=5, lsigma=4.0, usigma=4.0, binwidth=0.1):
"""
Replace already set `skystat` with a "built-in" version of a
statistics callable object used to measure sky background.
See :py:class:`~jwst_pipeline.skymatch.skystatistics.SkyStats` for the
parameter description.
"""
self._skystat = SkyStats(
skystat=skystat,
lower=lower,
upper=upper,
nclip=nclip,
lsig=lsigma,
usig=usigma,
binwidth=binwidth
)
# TODO: due to a bug in the sphere package, see
# https://github.com/spacetelescope/sphere/issues/74
# intersections with polygons formed as union does not work.
# For this reason I re-implement 'calc_sky' below with
# a workaround for the bug.
# The original implementation (now called ``_calc_sky_orig``
# should replace current 'calc_sky' once the bug is fixed.
#
[docs]
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:`spherical_geometry.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.get_data()]
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)
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.get_data()
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 not np.isfinite(skyval):
return None, 0, 0.0
if delta:
skyval -= self._sky
return skyval, npix, polyarea
# def _calc_sky_orig(self, overlap=None, delta=True):
# """
# Compute sky background value.
#
# Parameters
# ----------
# overlap : SkyImage, SkyGroup, SphericalPolygon, list of tuples, \
# None, optional
# Another `SkyImage`, `SkyGroup`,
# :py:class:`spherical_geometry.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.get_data()]
#
# polyarea = self.poly_area
#
# else:
# fill_mask = np.zeros(self.image_shape, dtype=bool)
#
# if isinstance(overlap, (SkyImage, SkyGroup, SphericalPolygon)):
# intersection = self.intersection(overlap)
# polyarea = np.fabs(intersection.area())
# radec = 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)
# 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.get_data()
#
# 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
[docs]
def copy(self):
"""
Return a shallow copy of the `SkyImage` object.
"""
si = SkyImage(
image=None,
wcs_fwd=self.wcs_fwd,
wcs_inv=self.wcs_inv,
pix_area=self.pix_area,
convf=self.convf,
mask=None,
id=self.id,
stepsize=None,
meta=self.meta
)
si._image = self._image
si._mask = self._mask
si._image_shape = self._image_shape
si._mask_shape = self._mask_shape
si._reduce_memory_usage = self._reduce_memory_usage
si._radec = self._radec
si._polygon = self._polygon
si._poly_area = self._poly_area
si.sky = self.sky
return si
[docs]
class SkyGroup:
"""
Holds multiple :py:class:`SkyImage` objects whose sky background values
must be adjusted together.
`SkyGroup` provides methods for obtaining bounding polygon of the group
of :py:class:`SkyImage` objects and to compute sky value of the group.
"""
def __init__(self, images, id=None, sky=0.0):
if isinstance(images, SkyImage):
self._images = [images]
elif hasattr(images, '__iter__'):
self._images = []
for im in images:
if not isinstance(im, SkyImage):
raise TypeError("Each element of the 'images' parameter "
"must be an 'SkyImage' object.")
self._images.append(im)
else:
raise TypeError(
"Parameter 'images' must be either a single 'SkyImage' object "
"or a list of 'SkyImage' objects"
)
self._id = id
self._update_bounding_polygon()
self._sky = sky
for im in self._images:
im.sky += sky
@property
def id(self):
""" Set or get `SkyImage`'s `id`.
While `id` can be of any type, it is preferable that `id` be
of a type with nice string representation.
"""
return self._id
@id.setter
def id(self, id):
self._id = id
@property
def sky(self):
""" Sky background value. See `calc_sky` for more details.
"""
return self._sky
@sky.setter
def sky(self, sky):
delta_sky = sky - self._sky
self._sky = sky
for im in self._images:
im.sky += delta_sky
@property
def radec(self):
"""
Get RA and DEC of the vertices of the bounding polygon as a
`~numpy.ndarray` of shape (N, 2) where N is the number of vertices + 1.
"""
return self._radec
@property
def polygon(self):
""" Get image's bounding polygon.
"""
return self._polygon
[docs]
def intersection(self, skyimage):
"""
Compute intersection of this `SkyImage` object and another
`SkyImage`, `SkyGroup`, or
:py:class:`~spherical_geometry.polygon.SphericalPolygon`
object.
Parameters
----------
skyimage : SkyImage, SkyGroup, SphericalPolygon
Another object that should be intersected with this `SkyImage`.
Returns
-------
intersect_poly : SphericalPolygon
A :py:class:`~spherical_geometry.polygon.SphericalPolygon` that is
the intersection of this `SkyImage` and `skyimage`.
"""
if isinstance(skyimage, (SkyImage, SkyGroup)):
other = skyimage.polygon
else:
other = skyimage
pts1 = np.sort(list(self._polygon.points)[0], axis=0)
pts2 = np.sort(list(other.points)[0], axis=0)
if np.allclose(pts1, pts2, rtol=0, atol=1e-8):
intersect_poly = self._polygon.copy()
else:
intersect_poly = self._polygon.intersection(other)
return intersect_poly
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 __len__(self):
return len(self._images)
def __getitem__(self, idx):
return self._images[idx]
def __setitem__(self, idx, value):
if not isinstance(value, SkyImage):
raise TypeError("Item must be of 'SkyImage' type")
value.sky += self._sky
self._images[idx] = value
self._update_bounding_polygon()
def __delitem__(self, idx):
del self._images[idx]
if len(self._images) == 0:
self._sky = 0.0
self._id = None
self._update_bounding_polygon()
def __iter__(self):
for image in self._images:
yield image
[docs]
def insert(self, idx, value):
"""Inserts a `SkyImage` into the group.
"""
if not isinstance(value, SkyImage):
raise TypeError("Item must be of 'SkyImage' type")
value.sky += self._sky
self._images.insert(idx, value)
self._update_bounding_polygon()
[docs]
def append(self, value):
"""Appends a `SkyImage` to the group.
"""
if not isinstance(value, SkyImage):
raise TypeError("Item must be of 'SkyImage' type")
value.sky += self._sky
self._images.append(value)
self._update_bounding_polygon()
[docs]
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:`spherical_geometry.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 len(self._images) == 0:
return None, 0, 0.0
wght = 0
area = 0.0
if overlap is None:
# compute minimum sky across all images in the group:
wsky = None
for image in self._images:
# make sure all images have the same background:
image.background = self._sky
sky, npix, imarea = image.calc_sky(overlap=None, delta=delta)
if sky is None:
continue
if wsky is None or wsky > sky:
wsky = sky
wght = npix
area = imarea
return wsky, wght, area
# compute weighted sky in various overlaps:
wsky = 0.0
for image in self._images:
# make sure all images have the same background:
image.background = self._sky
sky, npix, area1 = image.calc_sky(overlap=overlap, delta=delta)
area += area1
if sky is not None and npix > 0:
pix_area = npix * image.pix_area
wsky += sky * pix_area
wght += pix_area
if wght == 0.0 or area == 0.0:
return None, wght, area
else:
return wsky / wght, wght, area