def convert_polimage_to_stokes(im: Image):
"""Convert a polarisation image to stokes IQUV (complex)
For example:
imIQUV = convert_polimage_to_stokes(impol)
:param im: Complex Image in linear or circular
:returns: Complex image
See also
:py:func:`rascil.processing_components.image.convert_stokes_to_polimage`
:py:func:`rascil.data_models.polarisation.convert_stokes_to_circular`
:py:func:`rascil.data_models.polarisation.convert_stokes_to_linear`
"""
assert isinstance(im, Image)
assert im.data.dtype == 'complex'
if im.polarisation_frame == PolarisationFrame('linear'):
cimarr = convert_linear_to_stokes(im.data)
return create_image_from_array(cimarr, im.wcs, PolarisationFrame('stokesIQUV'))
elif im.polarisation_frame == PolarisationFrame('circular'):
cimarr = convert_circular_to_stokes(im.data)
return create_image_from_array(cimarr, im.wcs, PolarisationFrame('stokesIQUV'))
else:
raise ValueError("Cannot convert %s to stokes" % (im.polarisation_frame.type))
def convert_polimage_to_stokes(im: Image, complex_image=False, **kwargs):
"""Convert a polarisation image to stokes IQUV (complex)
For example:
imIQUV = convert_polimage_to_stokes(impol)
:param im: Complex Image in linear or circular
:param complex_image: Return complex image?
:returns: Complex or Real image
See also
:py:func:`rascil.processing_components.image.operations.convert_stokes_to_polimage`
:py:func:`rascil.data_models.polarisation.convert_stokes_to_circular`
:py:func:`rascil.data_models.polarisation.convert_stokes_to_linear`
"""
assert isinstance(im, Image)
assert im.data.dtype == 'complex'
def to_required(cimarr):
if complex_image:
return cimarr
else:
return numpy.real(cimarr)
if im.polarisation_frame == PolarisationFrame('linear'):
cimarr = convert_linear_to_stokes(im.data)
return create_image_from_array(to_required(cimarr), im.wcs,
PolarisationFrame('stokesIQUV'))
elif im.polarisation_frame == PolarisationFrame('linearnp'):
cimarr = convert_linear_to_stokes(im.data)
return create_image_from_array(to_required(cimarr), im.wcs,
PolarisationFrame('stokesIQ'))
elif im.polarisation_frame == PolarisationFrame('circular'):
cimarr = convert_circular_to_stokes(im.data)
return create_image_from_array(to_required(cimarr), im.wcs,
PolarisationFrame('stokesIQUV'))
elif im.polarisation_frame == PolarisationFrame('circularnp'):
cimarr = convert_circular_to_stokes(im.data)
return create_image_from_array(to_required(cimarr), im.wcs,
PolarisationFrame('stokesIV'))
elif im.polarisation_frame == PolarisationFrame('stokesI'):
return create_image_from_array(to_required(im.data), im.wcs,
PolarisationFrame('stokesI'))
else:
raise ValueError("Cannot convert %s to stokes" %
(im.polarisation_frame.type))
def convert_visibility_to_stokes(vis):
"""Convert the polarisation frame data into Stokes parameters.
:param vis: Visibility
:return: Converted visibility data.
"""
poldef = vis.polarisation_frame
if poldef == PolarisationFrame('linear'):
vis.data['vis'] = convert_linear_to_stokes(vis.data['vis'], polaxis=1)
vis.polarisation_frame = PolarisationFrame('stokesIQUV')
elif poldef == PolarisationFrame('circular'):
vis.data['vis'] = convert_circular_to_stokes(vis.data['vis'],
polaxis=1)
vis.polarisation_frame = PolarisationFrame('stokesIQUV')
return vis
def convert_blockvisibility_to_stokes(vis):
"""Convert the polarisation frame data into Stokes parameters.
Args:
vis (obj): RASCIL visibility data.
Returns:
vis: Converted visibility data.
"""
poldef = vis.polarisation_frame
if poldef == PolarisationFrame('linear'):
vis.data['vis'] = convert_linear_to_stokes(vis.data['vis'], polaxis=4)
vis.polarisation_frame = PolarisationFrame('stokesIQUV')
elif poldef == PolarisationFrame('circular'):
vis.data['vis'] = convert_circular_to_stokes(vis.data['vis'],
polaxis=4)
vis.polarisation_frame = PolarisationFrame('stokesIQUV')
return vis
def convert_blockvisibility_to_stokes(vis):
"""Convert the polarisation frame data into Stokes parameters.
:param vis: Visibility
:return: Converted visibility data.
"""
poldef = vis.polarisation_frame
if poldef == PolarisationFrame('linear'):
vis.data['vis'] = convert_linear_to_stokes(vis.data['vis'], polaxis=4)
vis.data['flags'] = \
numpy.logical_or(vis.flags[..., 0], vis.flags[..., 3])[
..., numpy.newaxis]
vis.polarisation_frame = PolarisationFrame('stokesIQUV')
elif poldef == PolarisationFrame('circular'):
vis.data['vis'] = convert_circular_to_stokes(vis.data['vis'],
polaxis=4)
vis.data['flags'] = \
numpy.logical_or(vis.flags[..., 0], vis.flags[..., 3])[
..., numpy.newaxis]
vis.polarisation_frame = PolarisationFrame('stokesIQUV')
return vis
def test_vis_conversion(self):
stokes = numpy.array(random.uniform(-1.0, 1.0, [1000, 3, 4]))
cir = convert_stokes_to_circular(stokes, polaxis=2)
st = convert_circular_to_stokes(cir, polaxis=2)
assert_array_almost_equal(st.real, stokes, 15)
def test_image_conversion(self):
stokes = numpy.array(random.uniform(-1.0, 1.0, [3, 4, 128, 128]))
cir = convert_stokes_to_circular(stokes)
st = convert_circular_to_stokes(cir)
assert_array_almost_equal(st.real, stokes, 15)
def test_stokes_circular_stokes_conversion(self):
stokes = numpy.array([1, 0.5, 0.2, -0.1])
circular = convert_stokes_to_circular(stokes)
assert_array_almost_equal(
convert_circular_to_stokes(circular).real, stokes, 15)
def test_stokes_circularnp_stokesIV_conversion(self):
stokes = numpy.array([1, 0.5])
circularnp = convert_stokes_to_circular(stokes, 0)
assert_array_almost_equal(
convert_circular_to_stokes(circularnp, 0).real, stokes, 15)