superphot_pipeline.image_utilities module

Class Inheritance Diagram

A collection of functions for working with pipeline images.

superphot_pipeline.image_utilities.bin_image(image, bin_factor)

Bins the image to a lower resolution (must be exact factor of image shape).

The output pixels are the sum of the pixels in each bin.

Parameters:

• image – The image to bin.
• bin_factor – Either a single integer in which case this is the binning in both directions, or a pair of integers, specifying different binnin in each direction.

Returns:

The binned image with a resolution decreased by the

binning factor for each axis, which has the same total flux as the input image.

Return type:

binned_image

superphot_pipeline.image_utilities.get_pointing_from_header(frame)

Return the sky coordinates of this frame’s pointing per its header.

Parameters:frame –

The frame to return the pointing of. Could be in one of the following formats:

• string: the filanema of a FITS frame. The pointing information

  is extracted from the header of the first non-trivial HDU.

• HDUList: Same as above, only this time the file is

  already opened.

• astropy.io.fits ImageHDU or TableHDU, containing the header to

  extract the pointing information from.

• asrtopy.io.fits.Header instance: the header from which to

  extract the pointing information.

Returns:

An instance of astropy.coordinates.SkyCoord containing the

frame pointing information contained in the header.

Return type:pointing

superphot_pipeline.image_utilities.read_image_components(fits_fname, *, read_image=True, read_error=True, read_mask=True, read_header=True)

Read image, its error estimate, mask and header from pipeline FITS file.

Parameters:

• fits_fname – The filename of the FITS file to read the componets of. Must have been produced by the pipeline.
• read_image – Should the pixel values of the primary image be read.
• read_error – Should the error extension be searched for and read.
• read_mask – Should the mask extension be searched for and read.
• read_header – Should the header of the image extension be returned.

Returns:

The primary image in the file. Always present.

error: The error estimate of image, identified by IMAGETYP==’error’.

Set to None if none of the extensions have IMAGETYP==’error’. This is omitted from the output if read_error == False.

mask: A bitmask of quality flags for each image pixel (identified

by IMAGETYP=’mask’). Set to None if none of the extensions have IMAGETYP=’mask’. This is omitted from the output if read_mask == False.

header: The header of the image HDU in the file. This is omitted from

the output if read_header == False.

Return type:

image

superphot_pipeline.image_utilities.zoom_image(image, zoom, interp_order)

Increase the resolution of an image using flux conserving interpolation.

Interpolation is performed using the following recipe:

1. create a cumulative image (C), i.e. C(x, y) = sum( image(x’, y’), {x’, 0, x}, {y’, 0, y}). Note that C’s x and y resolutions are both bigger than image’s by one with all entries in the first row and the first column being zero.

2. Interpolate the cumulative image using a bivariate spline to get a continuous cumulative flux F(x, y).

3. Create the final image I by setting each pixel to the flux implied by F(x, y) from step 2, i.e. if zx is the zoom factor along x and zy is the zoom factor along y:

   I(x, y) = F((x+1)/z, (y+1)/z)
             - F((x+1)/z, y/z)
             - F(x/z, (y+1)/z)
             + F(x/z, y/z)
   

Since this is a flux conserving method, zooming and then binning an image reproduces the original image with close to machine precision.

Parameters:

• image – The image to zoom.
• zoom – The factor(s) by which to zoom the image. Should be either an integer defining a common zoom factor both dimensions or a pair of numbers, specifying the zoom along each axis (y first, then x).
• interp_order – The order of the interpolation of the cumulative array.