def import_image_from_fits(fitsfile: str) -> Image:
""" Read an Image from fits
:param fitsfile:
:return: Image
"""
fim = Image()
warnings.simplefilter('ignore', FITSFixedWarning)
hdulist = fits.open(fitsfile)
fim.data = hdulist[0].data
fim.wcs = WCS(fitsfile)
hdulist.close()
if len(fim.data) == 2:
fim.polarisation_frame = PolarisationFrame('stokesI')
else:
try:
fim.polarisation_frame = polarisation_frame_from_wcs(
fim.wcs, fim.data.shape)
except ValueError:
fim.polarisation_frame = PolarisationFrame('stokesI')
log.debug(
"import_image_from_fits: created %s image of shape %s, size %.3f (GB)"
% (fim.data.dtype, str(fim.shape), image_sizeof(fim)))
log.debug("import_image_from_fits: Max, min in %s = %.6f, %.6f" %
(fitsfile, fim.data.max(), fim.data.min()))
assert isinstance(fim, Image)
return fim
def create_image_from_array(data: numpy.array, wcs: WCS, polarisation_frame: PolarisationFrame) -> Image:
""" Create an image from an array and optional wcs
The output image preserves a reference to the input array.
:param data: Numpy.array
:param wcs: World coordinate system
:param polarisation_frame: Polarisation Frame
:return: Image
"""
fim = Image()
fim.polarisation_frame = polarisation_frame
fim.data = data
if wcs is None:
fim.wcs = None
else:
fim.wcs = wcs.deepcopy()
if image_sizeof(fim) >= 1.0:
log.debug("create_image_from_array: created %s image of shape %s, size %.3f (GB)" %
(fim.data.dtype, str(fim.shape), image_sizeof(fim)))
assert isinstance(fim, Image), "Type is %s" % type(fim)
return fim
def copy_image(im: Image):
""" Create an image from an array
Performs deepcopy of data_models, breaking reference semantics
:param im:
:return: Image
"""
if im is None:
return im
assert isinstance(im, Image), im
fim = Image()
fim.polarisation_frame = im.polarisation_frame
fim.data = copy.deepcopy(im.data)
if im.wcs is None:
fim.wcs = None
else:
fim.wcs = copy.deepcopy(im.wcs)
if image_sizeof(fim) >= 1.0:
log.debug("copy_image: copied %s image of shape %s, size %.3f (GB)" %
(fim.data.dtype, str(fim.shape), image_sizeof(fim)))
assert type(fim) == Image
return fim
def replicate_image(im: Image, polarisation_frame=PolarisationFrame('stokesI'), frequency=numpy.array([1e8])) \
-> Image:
""" Make a new canonical shape Image, extended along third and fourth axes by replication.
The order of the data is [chan, pol, dec, ra]
:param frequency:
:param im:
:param polarisation_frame: Polarisation_frame
:return: Image
"""
if len(im.data.shape) == 2:
fim = Image()
newwcs = WCS(naxis=4)
newwcs.wcs.crpix = [
im.wcs.wcs.crpix[0] + 1.0, im.wcs.wcs.crpix[1] + 1.0, 1.0, 1.0
]
newwcs.wcs.cdelt = [im.wcs.wcs.cdelt[0], im.wcs.wcs.cdelt[1], 1.0, 1.0]
newwcs.wcs.crval = [
im.wcs.wcs.crval[0], im.wcs.wcs.crval[1], 1.0, frequency[0]
]
newwcs.wcs.ctype = [
im.wcs.wcs.ctype[0], im.wcs.wcs.ctype[1], 'STOKES', 'FREQ'
]
nchan = len(frequency)
npol = polarisation_frame.npol
fim.polarisation_frame = polarisation_frame
fim.wcs = newwcs
fshape = [nchan, npol, im.data.shape[1], im.data.shape[0]]
fim.data = numpy.zeros(fshape)
log.info("replicate_image: replicating shape %s to %s" %
(im.data.shape, fim.data.shape))
for i3 in range(nchan):
fim.data[i3, 0, :, :] = im.data[:, :]
return fim
else:
return im
def create_empty_image_like(im: Image) -> Image:
""" Create an empty image like another in shape and wcs
:param im:
:return: Image
"""
assert isinstance(im, Image), im
fim = Image()
fim.polarisation_frame = im.polarisation_frame
fim.data = numpy.zeros_like(im.data)
if im.wcs is None:
fim.wcs = None
else:
fim.wcs = copy.deepcopy(im.wcs)
if image_sizeof(im) >= 1.0:
log.debug("create_empty_image_like: created %s image of shape %s, size %.3f (GB)" %
(fim.data.dtype, str(fim.shape), image_sizeof(fim)))
assert isinstance(fim, Image), "Type is %s" % type(fim)
return fim