sep.sum_circann

sep.sum_circann(data, x, y, rin, rout, err=None, var=None, mask=None, maskthresh=0.0, seg_id=None, segmap=None, gain=None, subpix=5)

Sum data in circular annular aperture(s).

Parameters:

data : ndarray

2-d array to be summed.

x, y, rin, rout : array_like

Center coordinates and inner and outer radii of aperture(s). x corresponds to the second (“fast”) axis of the input array and y 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. It is required that rout >= rin >= 0.0.

err, var : float 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.

maskthresh : float, optional

Threshold for a pixel to be masked. Default is 0.0.

segmap : ndarray, optional

Segmentation image with dimensions of data and dtype np.int32. This is an optional input and corresponds to the segmentation map output by extract.

seg_id : array_like, optional

Array of segmentation ids used to mask additional pixels in the image. Dimensions correspond to the dimensions of x and y. The behavior differs depending on whether seg_id is negative or positive. If seg_id is positive, all pixels belonging to other objects are masked. (Pixel j, i is masked if seg[j, i] != seg_id and seg[j, i] != 0). If seg_id is negative, all pixels other than those belonging to the object of interest are masked. (Pixel j, i is masked if seg[j, i] != -seg_id). NB: must be included if ``segmap` is provided.

gain : float, 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.

subpix : int, optional

Subpixel sampling factor. Default is 5.

Returns:

sum : ndarray

The sum of the data array within the aperture.

sumerr : ndarray

Error on the sum.

flags : ndarray

Integer giving flags. (0 if no flags set.)