HSTWCS Examples

Create an HSTWCS Object

  • Create an HSTWCS object using a pyfits HDUList and an extension number

    fobj = pyfits.open('some_file.fits')

    w = wcsutil.HSTWCS(fobj, 3)

  • Create an HSTWCS object using a qualified file name.

    w = wcsutil.HSTWCS('j9irw4b1q_flt.fits[sci,1]')

  • Create an HSTWCS object using a file name and an extension number.

    w = wcsutil.HSTWCS('j9irw4b1q_flt.fits', ext=2)

  • Create an HSTWCS object from WCS with key ‘O’.

    w = wcsutil.HSTWCS('j9irw4b1q_flt.fits', ext=2, wcskey='O')

  • Create a template HSTWCS object for a DEFAULT object.

    w = wcsutil.HSTWCS(instrument='DEFAULT')

Coordinate Transformation Examples

All coordinate transformation functions accept input coordinates as 2D numpy arrays or 2 sequences of X and Y coordinates.

inpix = np.array([[1., 2.], [1,3], [1,4], [1,5]])


X = [1.,1.,1.,1.]

Y = np.array([2.,3.,4.,5.])

In addition all transformation functions require an origin parameter which specifies if the coordinates are 0 or 1 based. For example in FITS and Fortran, coordinates start from 1, while in Python and C, the index of the first image pixel is (0,0).

  • Apply the entire detector to sky transformation at once:

outpix = w1.all_pix2world(inpix, 1)

outpix = w1.all_pix2world(X, Y, 1)

  • The same transformation can be done in separate steps:

  1. Apply the detector to image correction

dpx = w.det2im(inpix,1)

  1. Aply the SIP polynomial distortion

spx = w.sip_pix2foc(dpx, 1)

  1. Apply the non-polynomial distortion from the lookup table

lutpx = w.p4_pix2foc(dpx,1)

  1. The undistorted coordinates are the sum of the input coordinates with the deltas for the distortion corrections.

fpix = dpx + (spx-dpx) +(lutpx-dpx)

  1. Finally the transformation from undistorted to world coordinates is done by applying the linear WCS.

wpix = w.wcs_pix2sky(fpix, 1)