Using the WCS objectΒΆ

This section uses the imaging_wcs.asdf created in Adding distortion to the imaging example to read in a WCS object and demo its methods.

>>> import asdf
>>> asdf_file ="imaging_wcs.asdf")
>>> wcsobj = asdf_file.tree["wcs"]
>>> print(wcsobj)    
         From          Transform
----------------- ----------------
         detector       distortion
undistorted_frame linear_transform
             icrs             None

To see what frames are defined:

>>> print(wcsobj.available_frames)
    ['detector', 'undistorted_frame', 'icrs']
>>> wcsobj.input_frame
     <Frame2D(name="detector", unit=(Unit("pix"), Unit("pix")), axes_names=('x', 'y'), axes_order=(0, 1))>
 >>> wcsobj.output_frame
     <CelestialFrame(name="icrs", unit=(Unit("deg"), Unit("deg")), axes_names=('lon', 'lat'), axes_order=(0, 1), reference_frame=<ICRS Frame>)>

Because the output_frame is a CoordinateFrame object we can get the result of the WCS transform as an SkyCoord object and transform them to other standard coordinate frames supported by astropy.coordinates.

>>> skycoord = wcsobj(1, 2, with_units=True)
>>> print(skycoord)
<SkyCoord (ICRS): (ra, dec) in deg
  (5.52886119, -72.05285219)>
>>> print(skycoord.transform_to("galactic"))
<SkyCoord (Galactic): (l, b) in deg
  (306.11346489, -44.89382103)>

The WCS object has an attribute bounding_box (default value of None) which describes the range of acceptable values for each input axis.

>>> wcsobj.bounding_box = ((0, 2048), (0, 1000))
>>> wcsobj((2,3), (1020, 980))
    array([nan, 133.48248429]), array([nan, -11.24021056])

The WCS object accepts a boolean flag called with_bounding_box with default value of True. Output values which are outside the bounding_box are set to NaN. There are cases when this is not desirable and with_bounding_box=False should be passes.

Calling the footprint() returns the footprint on the sky.

>>> wcsobj.footprint()

Some methods allow managing the transforms in a more detailed manner.

Transforms between frames can be retrieved and evaluated separately.

>>> dist = wcsobj.get_transform('detector', 'undistorted_frame')
>>> dist(1, 2)    
    (47.8, 95.60)

Transforms in the pipeline can be replaced by new transforms.

>>> new_transform = models.Shift(1) & models.Shift(1.5) | distortion
>>> wcsobj.set_transform('detector', 'focal_frame', new_transform)
>>> wcsobj(1, 2)         
    (5.5583005430002785, -72.06028278184611)

A transform can be inserted before or after a frame in the pipeline.

>>> scale = models.Scale(2) & models.Scale(1)
>>> wcsobj.insert_transform('icrs', scale, after=False)
>>> wcsobj(1, 2)          
    (11.116601086000557, -72.06028278184611)