def make_median(fnlist,outfile):
"""Creates a median image from a series of images.
Inputs:
fnlist -> List of strings pointing to fits images
outfile -> Location of resultant median image
"""
imagelist = []
datalist = []
for i in range(len(fnlist)):
imagelist.append(openfits(fnlist[i]))
datalist.append(imagelist[i][0].data)
datalist = np.array(datalist)
meddata = np.median(datalist,axis=0)
medhdu = PrimaryHDU(meddata)
medhdu.writeto(outfile,clobber=True)
for i in range(len(fnlist)):
imagelist[i].close()
return
def test_dtypes(dask_array_in_mem, tmp_path, dtype):
filename = tmp_path / 'test.fits'
array = dask_array_in_mem.astype(dtype)
hdu = PrimaryHDU(data=array)
hdu.writeto(filename)
with fits.open(filename) as hdulist_new:
assert isinstance(hdulist_new[0].data, np.ndarray)
np.testing.assert_allclose(hdulist_new[0].data, array.compute())
def test_save_primary_hdu(dask_array_in_mem, tmp_path):
# Saving a Primary HDU directly
filename = tmp_path / 'test.fits'
hdu = PrimaryHDU(data=dask_array_in_mem)
hdu.writeto(filename)
with fits.open(filename) as hdulist_new:
assert isinstance(hdulist_new[0].data, np.ndarray)
np.testing.assert_allclose(hdulist_new[0].data,
dask_array_in_mem.compute())
def test_scaled_minmax(dask_array_in_mem, tmp_path):
filename = tmp_path / 'test.fits'
hdu = PrimaryHDU(data=dask_array_in_mem)
hdu.scale('int32', option='minmax')
hdu.writeto(filename)
with fits.open(filename) as hdulist_new:
assert isinstance(hdulist_new[0].data, np.ndarray)
np.testing.assert_allclose(hdulist_new[0].data,
dask_array_in_mem.compute(),
atol=1e-5)
def northupeastleft(filename='', data=None, header=None):
from astropy.io.fits import getdata, PrimaryHDU
if filename:
data, header = getdata(filename, header=True)
if header['cd1_1'] > 0:
data = np.fliplr(data)
header['cd1_1'] *= -1
print 'flipping around x'
if header['cd2_2'] < 0:
data = np.flipud(data)
header['cd2_2'] *= -1
print 'flipping around y'
if filename:
from os import remove
remove(filename)
out_fits = PrimaryHDU(data=data, header=header)
out_fits.writeto(filename, clobber=True, output_verify='fix')
else:
return data, header
def northupeastleft(filename='', data=None, header=None):
from astropy.io.fits import getdata, PrimaryHDU
if filename:
data, header = getdata(filename, header=True)
if header['cd1_1'] > 0:
data = np.fliplr(data)
header['cd1_1'] *= -1
print 'flipping around x'
if header['cd2_2'] < 0:
data = np.flipud(data)
header['cd2_2'] *= -1
print 'flipping around y'
if filename:
from os import remove
remove(filename)
out_fits = PrimaryHDU(data=data, header=header)
out_fits.writeto(filename, clobber=True, output_verify='fix')
else:
return data, header
def run_bsmem_using_image(datafile: str,
outputfile: str,
dim: int,
pixelsize: float,
imagehdu: fits.PrimaryHDU,
uvmax: float = None,
alpha: float = None) -> None:
"""Run bsmem using initial/prior image.
Args:
datafile: Input OIFITS data filename.
outputfile: Output FITS filename.
dim: Reconstructed image width (pixels).
pixelsize: Reconstructed image pixel size (mas).
imagehdu: FITS HDU containing initial/prior image.
uvmax: Maximum uv radius to select (waves).
alpha: Regularization hyperparameter.
"""
tempimage = tempfile.NamedTemporaryFile(suffix='.fits',
mode='wb',
delete=False)
imagehdu.writeto(tempimage.name, overwrite=True)
tempimage.close()
args = [
BSMEM, '--noui',
'--data=%s' % datafile, '--clobber',
'--output=%s' % outputfile,
'--dim=%d' % dim,
'--pixelsize=%f' % pixelsize,
'--sf=%s' % tempimage.name
]
if uvmax is not None:
args += ['--uvmax=%f' % uvmax]
if alpha is not None:
args += ['--autoalpha=3', '--alpha=%f' % alpha]
else:
args += ['--autoalpha=4']
fullstdout = os.path.splitext(outputfile)[0] + '-out.txt'
run_bsmem(args, fullstdout)
os.remove(tempimage.name)
def test_long_header(dask_array_in_mem, tmp_path):
# Make sure things work correctly if there is a long header in the HDU.
filename = tmp_path / 'test.fits'
# NOTE: we deliberately set up a long header here rather than add the
# keys one by one to hdu.header as adding the header in one go used to
# cause issues, so this acts as a regression test.
header = fits.Header()
for index in range(2048):
header[f'KEY{index:x}'] = 0.
hdu = PrimaryHDU(data=dask_array_in_mem, header=header)
hdu.writeto(filename)
with fits.open(filename) as hdulist_new:
assert len(hdulist_new[0].header) == 2053
assert isinstance(hdulist_new[0].data, np.ndarray)
np.testing.assert_allclose(hdulist_new[0].data,
dask_array_in_mem.compute())
