def time_elliptical_small_subpixel_1():
elliptical_overlap_grid(-4.,
4.,
-4.,
4.,
10,
10,
3.,
2.,
1.,
use_exact=0,
subpixels=1)
def time_elliptical_big_subpixel_5():
elliptical_overlap_grid(-4.,
4.,
-4.,
4.,
100,
100,
3.,
2.,
1.,
use_exact=1,
subpixels=5)
def to_mask(self, x_size, y_size):
"""
This function ...
:param x_size:
:param y_size:
:return:
"""
rel_center = self.center
a = self.radius.x if isinstance(self.radius, Extent) else self.radius
b = self.radius.y if isinstance(self.radius, Extent) else self.radius
# theta in radians !
theta = self.angle.radian
x_min = -rel_center.x
x_max = x_size - rel_center.x
y_min = -rel_center.y
y_max = y_size - rel_center.y
# Calculate the mask
if a * b * x_size * y_size == 0:
fraction = 0
else:
fraction = elliptical_overlap_grid(x_min,
x_max,
y_min,
y_max,
x_size,
y_size,
a,
b,
theta,
use_exact=0,
subpixels=1)
#xmin, xmax, ymin, ymax : float
# Extent of the grid in the x and y direction.
#nx, ny : int
# Grid dimensions.
#rx : float
# The semimajor axis of the ellipse.
#ry : float
# The semiminor axis of the ellipse.
#theta : float
# The position angle of the semimajor axis in radians (counterclockwise).
#use_exact : 0 or 1
# If set to 1, calculates the exact overlap, while if set to 0, uses a
# subpixel sampling method with ``subpixel`` subpixels in each direction.
#subpixels : int
# If ``use_exact`` is 0, each pixel is resampled by this factor in each
# dimension. Thus, each pixel is divided into ``subpixels ** 2``
# subpixels.
return Mask(fraction)
def to_mask(self, x_size, y_size, invert=False):
"""
This function ...
:param x_size:
:param y_size:
:param invert:
:return:
"""
rel_center = self.center
a = self.radius.x
b = self.radius.y
# theta in radians !
theta = self.angle.radian
x_min = - rel_center.x
x_max = x_size - rel_center.x
y_min = - rel_center.y
y_max = y_size - rel_center.y
# Calculate the mask
fraction = elliptical_overlap_grid(x_min, x_max, y_min, y_max, x_size, y_size, a, b, theta, use_exact=0, subpixels=1)
# xmin, xmax, ymin, ymax : float
# Extent of the grid in the x and y direction.
# nx, ny : int
# Grid dimensions.
# rx : float
# The semimajor axis of the ellipse.
# ry : float
# The semiminor axis of the ellipse.
# theta : float
# The position angle of the semimajor axis in radians (counterclockwise).
# use_exact : 0 or 1
# If set to 1, calculates the exact overlap, while if set to 0, uses a
# subpixel sampling method with ``subpixel`` subpixels in each direction.
# subpixels : int
# If ``use_exact`` is 0, each pixel is resampled by this factor in each
# dimension. Thus, each pixel is divided into ``subpixels ** 2``
# subpixels.
mask = Mask(fraction)
# Return
if invert: return mask.inverse()
else: return mask
def calc_masked_aperture(ap, image, method='mmm', mask=None):
positions = ap.positions
extents = np.zeros((len(positions), 4), dtype=int)
if isinstance(ap, EllipticalAnnulus):
radius = ap.a_out
elif isinstance(ap, CircularAnnulus):
radius = ap.r_out
elif isinstance(ap, CircularAperture):
radius = ap.r
elif isinstance(ap, EllipticalAperture):
radius = ap.a
extents[:, 0] = positions[:, 0] - radius + 0.5
extents[:, 1] = positions[:, 0] + radius + 1.5
extents[:, 2] = positions[:, 1] - radius + 0.5
extents[:, 3] = positions[:, 1] + radius + 1.5
ood_filter, extent, phot_extent = get_phot_extents(image, positions,
extents)
x_min, x_max, y_min, y_max = extent
x_pmin, x_pmax, y_pmin, y_pmax = phot_extent
bkg = np.zeros(len(positions))
area = np.zeros(len(positions))
for i in range(len(bkg)):
if isinstance(ap, EllipticalAnnulus):
fraction = elliptical_overlap_grid(x_pmin[i], x_pmax[i],
y_pmin[i], y_pmax[i],
x_max[i] - x_min[i],
y_max[i] - y_min[i],
ap.a_out, ap.b_out, ap.theta, 0,
1)
b_in = ap.a_in * ap.b_out / ap.a_out
fraction -= elliptical_overlap_grid(x_pmin[i], x_pmax[i],
y_pmin[i], y_pmax[i],
x_max[i] - x_min[i],
y_max[i] - y_min[i],
ap.a_in, b_in, ap.theta,
0, 1)
elif isinstance(ap, CircularAnnulus):
fraction = circular_overlap_grid(x_pmin[i], x_pmax[i],
y_pmin[i], y_pmax[i],
x_max[i] - x_min[i],
y_max[i] - y_min[i],
ap.r_out, 0, 1)
fraction -= circular_overlap_grid(x_pmin[i], x_pmax[i],
y_pmin[i], y_pmax[i],
x_max[i] - x_min[i],
y_max[i] - y_min[i],
ap.r_in, 0, 1)
elif isinstance(ap, CircularAperture):
fraction = circular_overlap_grid(x_pmin[i], x_pmax[i],
y_pmin[i], y_pmax[i],
x_max[i] - x_min[i],
y_max[i] - y_min[i],
ap.r, 0, 1)
elif isinstance(ap, EllipticalAperture):
fraction = elliptical_overlap_grid(x_pmin[i], x_pmax[i],
y_pmin[i], y_pmax[i],
x_max[i] - x_min[i],
y_max[i] - y_min[i],
ap.a, ap.b, ap.theta, 0,
1)
pixel_data = image[y_min[i]:y_max[i], x_min[i]:x_max[i]] * fraction
if mask is not None:
pixel_data[mask[y_min[i]:y_max[i], x_min[i]:x_max[i]]] = 0.0
good_pixels = pixel_data[pixel_data != 0.0].flatten()
if method == 'mmm':
skymod, skysigma, skew = mmm(good_pixels)
bkg[i] = skymod
elif method == 'sum':
bkg[i] = np.sum(good_pixels)
elif method == 'max':
bkg[i] = np.nanmax(good_pixels)
area[i] = len(good_pixels)
return bkg, area
def elliptical_mask(self, major, minor, pa=0.0, xoff=0.0, yoff=0.0, use_exact=1, subsampling=1, transparency=1.0):
"""
Define an elliptical mask within the grid with specified major/minor axes, position angle,
and offset from center by xoff/yoff. Use photutils.geometry to create masks that calculate
the fraction of a pixel subtended by the mask. use_exact=1 performs the exact geometric
calculation while use_exact=0 will sub-sample the pixels by the specfied subsampling parameter
to estimate the subtended area.
Parameters
----------
major: float
Semi-major axis of the elliptical mask
minor: float
Semi-minor axis of the mask
pa: float
Position angle of the ellipse in degrees measured clockwise (positive in +X direction)
xoff: float
X position of the center of the mask
yoff: float
Y position of the center of the mask
use_exact: int (default: 1)
If 1, then use exact geometrical calculation to weight pixels partially covered by mask.
This parameter is passed directly on to photutils.geometry.circular_overlap_grid()
subsampling: int (default: 1)
If use_exact=0, then subsample pixels by this factor to calculate area of each pixel subtended
by the mask. The default value of 1 will force no partial pixels to be included in the mask.
This parameter is passed directly on to photutils.geometry.circular_overlap_grid()
transparency: float (default: 1.0)
Transparency of the mask
Returns
-------
mask: 2D np.ndarray
2D mask image
"""
if transparency < 0.0 or transparency > 1.0:
msg = "Mask transparency, %f, must be in the range of 0.0 (fully opaque) to 1.0 (fully clear)." % transparency
raise EngineInputError(value=msg)
theta = np.pi * pa / 180.0 # photutils uses angles in radians
t = self.as_dict()
# we need to use flipud because we use an origin in the UL corner of an image
# while photutils uses the LL corner.
mask = np.flipud(
elliptical_overlap_grid(
t['x_min'] - xoff,
t['x_max'] - xoff,
t['y_min'] - yoff,
t['y_max'] - yoff,
t['x_size'],
t['y_size'],
major,
minor,
theta,
use_exact,
subsampling
)
)
mask *= transparency
return mask
def time_elliptical_big_subpixel_5():
elliptical_overlap_grid(-4., 4., -4., 4., 100, 100, 3., 2., 1.,
use_exact=1, subpixels=5)
def time_elliptical_small_subpixel_1():
elliptical_overlap_grid(-4., 4., -4., 4., 10, 10, 3., 2., 1.,
use_exact=0, subpixels=1)
