def make_image(uu_m,
vv_m,
amps,
freq_hz,
im_size,
cell_size_uv_m,
image_root_name,
algorithm='fft'):
"""Make a FITS image from the specified data.
This function is slightly unusual in that the image size is specified
using a grid pixel size rather than image pixel size or field-of-view.
Args:
uu_m (array_like, float): Baseline uu coordinates, in metres
vv_m (array_like, float): Baseline vv coordinates, in metres
amps (array_like, complex): Visibility amplitudes
freq_hz (float): Observation frequency, in Hz
im_size (int): Image dimension (assumes square image)
cell_size_uv_m (float): Image grid pixel separation, in metres
image_root_name (str): Output FITS image root name.
algorithm (str): Imaging algorithm to use (FFT or W-projection)
Returns:
(dict, str): Dictionary containing the grid used to make the image,
filename of the output fits image created.
"""
ra_deg, dec_deg = 0, 90
ww_m = np.zeros_like(uu_m)
image_type = 'I'
wavelength = const.c.value / freq_hz
uv_cellsize_wavelengths = cell_size_uv_m / wavelength
fov_rad = Imager.uv_cellsize_to_fov(uv_cellsize_wavelengths, im_size)
# Create FITS image
imager = Imager(precision='double')
imager.set(fov_deg=degrees(fov_rad),
size=im_size,
algorithm=algorithm,
weighting='natural',
image_type=image_type,
wprojplanes=-1,
output_root=image_root_name)
imager.set_vis_frequency(freq_hz)
imager.set_vis_phase_centre(ra_deg, dec_deg)
imager_data = imager.run(uu_m, vv_m, ww_m, amps, return_grids=1)
image_grid = imager_data['grids'].squeeze()
return image_grid, '%s_%s.fits' % (image_root_name, image_type)
