def computeEdgesCenter(edges):
alpha = fileutil.DEGTORAD(edges[0])
dec = fileutil.DEGTORAD(edges[1])
xmean = np.mean(np.cos(dec)*np.cos(alpha))
ymean = np.mean(np.cos(dec)*np.sin(alpha))
zmean = np.mean(np.sin(dec))
crval1 = fileutil.RADTODEG(np.arctan2(ymean,xmean))%360.0
crval2 = fileutil.RADTODEG(np.arctan2(zmean,np.sqrt(xmean*xmean+ymean*ymean)))
return crval1,crval2
def build_pixel_transform(chip,output_wcs):
driz_pars = {}
driz_pars['pxg'] = np.zeros([2,2],dtype=np.float32)
driz_pars['pyg'] = np.zeros([2,2],dtype=np.float32)
# Use default C mapping function
_inwcs = np.zeros([8],dtype=np.float64)
driz_pars['inwcs'] = convertWCS(output_wcs.wcs,_inwcs)
indx = chip.outputNames['data'].find('.fits')
driz_pars['coeffs_name'] = chip.outputNames['data'][:indx]+'_coeffs'+str(chip.detnum)+'.dat'
#
# Need to compute and write out coeffs files for each chip as well.
#
xcoeffs,ycoeffs = coeff_converter.sip2idc(chip.wcs)
# account for the case where no IDCSCALE has been set, due to a
# lack of IDCTAB or to 'coeffs=False'.
idcscale = chip.wcs.idcscale
if idcscale is None: idcscale = chip.wcs.pscale
xcoeffs /= idcscale
ycoeffs /= idcscale
driz_pars['coeffs'] = [xcoeffs,ycoeffs]
abxt,cdyt = wcsfit(chip.wcs,output_wcs)
#abxt[2] -= xzero
#cdyt[2] -= yzero
driz_pars['abxt'] = abxt
driz_pars['cdyt'] = cdyt
driz_pars['delta_rot'] = fileutil.RADTODEG(np.arctan2(abxt[1],cdyt[0]))
# Compute scale from fit to allow WFPC2 (and similar) data to be handled correctly
driz_pars['scale'] = 1./np.sqrt(abxt[0]**2 + abxt[1]**2)
driz_pars['tddalpha'] = chip.header['tddalpha']
driz_pars['tddbeta'] = chip.header['tddbeta']
return driz_pars
def fitlin_rscale(xy, uv, verbose=False):
""" Performs a linear, orthogonal fit between matched
lists of positions 'xy' (input) and 'uv' (output).
Output: (same as for fit_arrays_general)
"""
mu = uv[:, 0].mean()
mv = uv[:, 1].mean()
mx = xy[:, 0].mean()
my = xy[:, 1].mean()
u = uv[:, 0] - mu
v = uv[:, 1] - mv
x = xy[:, 0] - mx
y = xy[:, 1] - my
Sxx = np.dot(x, x)
Syy = np.dot(y, y)
Sux = np.dot(u, x)
Suy = np.dot(u, y)
Svx = np.dot(v, x)
Svy = np.dot(v, y)
# implement parity check
if (np.dot(Sux, Svy) > 0):
p = 1
else:
p = -1
XX = p * Sux + Svy
YY = Suy - p * Svx
# derive output values
theta_deg = fileutil.RADTODEG(np.arctan2(YY, XX)) % 360.0
scale = np.sqrt(XX**2 + YY**2) / (Sxx + Syy)
shift = (mu - mx, mv - my)
if verbose:
print('Linear RSCALE fit: rotation = ', theta_deg, ' scale = ', scale,
' offset = ', shift)
coeffs = scale * fileutil.buildRotMatrix(-theta_deg)
P = [coeffs[0, 0], coeffs[0, 1], shift[0]]
Q = [coeffs[1, 1], coeffs[1, 0], shift[1]]
return P, Q