sep.sum_ellipse¶
- sep.sum_ellipse(data, x, y, a, b, theta, r, err=None, var=None, mask=None, maskthresh=0.0, seg_id=None, segmap=None, bkgann=None, gain=None, subpix=5)¶
Sum data in elliptical aperture(s).
- Parameters
- data
ndarray
2-d array to be summed.
- x, yarray_like
Center coordinates and radius (radii) of aperture(s).
x
corresponds to the second (“fast”) axis of the input array andy
corresponds to the first (“slow”) axis.x, y = (0.0, 0.0)
corresponds to the center of the first element of the array. These inputs obey numpy broadcasting rules.- a, b, thetaarray_like
Ellipse parameters. These inputs, along with
x
,y
, andr
, obey numpy broadcasting rules.a
is the semi-major axis,b
is the semi-minor axis andtheta
is angle in radians between the positive x axis and the major axis. It must be in the range[-pi/2, pi/2]
. It is also required thata >= b >= 0.0
.- rarray_like, optional
Scaling factor for the semi-minor and semi-major axes. The actual ellipse used will have semi-major axis
a * r
and semi-minor axisb * r
. Setting this parameter to a value other than 1.0 is exactly equivalent to scaling botha
andb
by the same value. Default is 1.0.- err, varfloat or
ndarray
Error or variance (specify at most one).
- mask
ndarray
, optional Mask array. If supplied, a given pixel is masked if its value is greater than
maskthresh
.- maskthreshfloat, optional
Threshold for a pixel to be masked. Default is
0.0
.- segmap
ndarray
, optional Segmentation image with dimensions of
data
and dtypenp.int32
. This is an optional input and corresponds to the segmentation map output byextract
.- seg_idarray_like, optional
Array of segmentation ids used to mask additional pixels in the image. Dimensions correspond to the dimensions of
x
andy
. The behavior differs depending on whetherseg_id
is negative or positive. Ifseg_id
is positive, all pixels belonging to other objects are masked. (Pixelj, i
is masked ifseg[j, i] != seg_id and seg[j, i] != 0
). Ifseg_id
is negative, all pixels other than those belonging to the object of interest are masked. (Pixelj, i
is masked ifseg[j, i] != -seg_id
). NB: must be included if ``segmap` is provided.- bkganntuple, optional
Length 2 tuple giving the inner and outer radius of a “background annulus”. If supplied, the background is estimated by averaging unmasked pixels in this annulus. If supplied, the inner and outer radii obey numpy broadcasting rules, along with
x
,y
, and ellipse parameters.- gainfloat, optional
Conversion factor between data array units and poisson counts, used in calculating poisson noise in aperture sum. If
None
(default), do not add poisson noise.- subpixint, optional
Subpixel sampling factor. Default is 5.
- data
- Returns