def combine_fitsheader(headers, cdelt=None, pa=None):
"""
Returns a FITS header which encompasses all input headers.
"""
if not isinstance(headers, (list, tuple)):
header = (headers, )
if len(headers) == 1 and cdelt is None and pa is None:
return headers[0]
crval = barycenter_lonlat([h['CRVAL1'] for h in headers],
[h['CRVAL2'] for h in headers])
if cdelt is None or pa is None:
cdeltpa = [get_cdelt_pa(h) for h in headers]
if cdelt is None:
cdelt = min([np.min(abs(cdelt)) for cdelt, pa in cdeltpa])
if pa is None:
pa = tmf.mean_degrees(np.array([pa for cdelt, pa in cdeltpa]))
header0 = create_fitsheader((1, 1),
cdelt=cdelt,
pa=pa,
crpix=(1, 1),
crval=crval)
proj0 = wcs.Projection(header0)
xy0 = []
for h in headers:
proj = wcs.Projection(h)
nx = h['NAXIS1']
ny = h['NAXIS2']
x = h['CRPIX1']
y = h['CRPIX2']
edges = proj.toworld(
([0.5, x, nx + 0.5, 0.5, x, nx + 0.5, 0.5, x, nx + 0.5],
[0.5, 0.5, 0.5, y, y, y, ny + 0.5, ny + 0.5, ny + 0.5]))
xy0.append(proj0.topixel(edges))
xmin0 = np.round(min([min(c[0]) for c in xy0]))
xmax0 = np.round(max([max(c[0]) for c in xy0]))
ymin0 = np.round(min([min(c[1]) for c in xy0]))
ymax0 = np.round(max([max(c[1]) for c in xy0]))
header0['NAXIS1'] = int(xmax0 - xmin0 + 1)
header0['NAXIS2'] = int(ymax0 - ymin0 + 1)
header0['CRPIX1'] = 2 - xmin0
header0['CRPIX2'] = 2 - ymin0
return header0
def combine_fitsheader(headers, cdelt=None, pa=None):
"""
Returns a FITS header which encompasses all input headers.
"""
if not isinstance(headers, (list, tuple)):
header = (headers,)
if len(headers) == 1 and cdelt is None and pa is None:
return headers[0]
crval = barycenter_lonlat([h['CRVAL1'] for h in headers],
[h['CRVAL2'] for h in headers])
if cdelt is None or pa is None:
cdeltpa = [get_cdelt_pa(h) for h in headers]
if cdelt is None:
cdelt = min([np.min(abs(cdelt)) for cdelt, pa in cdeltpa])
if pa is None:
pa = tmf.mean_degrees(np.array([pa for cdelt, pa in cdeltpa]))
header0 = create_fitsheader((1,1), cdelt=cdelt, pa=pa, crpix=(1,1),
crval=crval)
proj0 = wcs.Projection(header0)
xy0 = []
for h in headers:
proj = wcs.Projection(h)
nx = h['NAXIS1']
ny = h['NAXIS2']
x = h['CRPIX1']
y = h['CRPIX2']
edges = proj.toworld(([0.5,x,nx+0.5,0.5,x,nx+0.5,0.5,x,nx+0.5],
[0.5,0.5,0.5,y,y,y,ny+0.5,ny+0.5,ny+0.5]))
xy0.append(proj0.topixel(edges))
xmin0 = np.round(min([min(c[0]) for c in xy0]))
xmax0 = np.round(max([max(c[0]) for c in xy0]))
ymin0 = np.round(min([min(c[1]) for c in xy0]))
ymax0 = np.round(max([max(c[1]) for c in xy0]))
header0['NAXIS1'] = int(xmax0 - xmin0 + 1)
header0['NAXIS2'] = int(ymax0 - ymin0 + 1)
header0['CRPIX1'] = 2 - xmin0
header0['CRPIX2'] = 2 - ymin0
return header0
def mean_degrees(array):
"""
Returns the mean value of an array of values in degrees, by taking into
account the discrepancy at 0 degree
"""
return tmf.mean_degrees(np.asarray(array, dtype=var.FLOAT_DTYPE).ravel())
def mean_degrees(array):
"""
Returns the mean value of an array of values in degrees, by taking into
account the discrepancy at 0 degree
"""
return tmf.mean_degrees(np.asarray(array, dtype=var.FLOAT_DTYPE).ravel())
