def convert_stokes_to_polimage(im: Image, polarisation_frame: PolarisationFrame):
"""Convert a stokes image in IQUV to polarisation_frame
For example::
impol = convert_stokes_to_polimage(imIQUV, Polarisation_Frame('linear'))
:param im: Image to be converted
:param polarisation_frame: desired polarisation frame
:returns: Complex image
See also
:py:func:`rascil.processing_components.image.convert_polimage_to_stokes`
:py:func:`rascil.data_models.polarisation.convert_circular_to_stokes`
:py:func:`rascil.data_models.polarisation.convert_linear_to_stokes`
"""
assert isinstance(im, Image)
assert image_is_canonical(im)
assert isinstance(polarisation_frame, PolarisationFrame)
if polarisation_frame == PolarisationFrame('linear'):
cimarr = convert_stokes_to_linear(im.data)
return create_image_from_array(cimarr, im.wcs, polarisation_frame)
elif polarisation_frame == PolarisationFrame('circular'):
cimarr = convert_stokes_to_circular(im.data)
return create_image_from_array(cimarr, im.wcs, polarisation_frame)
else:
raise ValueError("Cannot convert stokes to %s" % (polarisation_frame.type))
def test_stokes_linear_conversion(self):
stokes = numpy.array([1.0, 0.0, 0.0, 0.0])
linear = convert_stokes_to_linear(stokes)
assert_array_almost_equal(
linear, numpy.array([1.0 + 0j, 0.0 + 0j, 0.0 + 0j, 1.0 + 0j]))
stokes = numpy.array([0.0, 1.0, 0.0, 0.0])
linear = convert_stokes_to_linear(stokes)
assert_array_almost_equal(linear,
numpy.array([1.0 + 0j, 0j, 0j, -1.0 + 0j]))
stokes = numpy.array([0.0, 0.0, 1.0, 0.0])
linear = convert_stokes_to_linear(stokes)
assert_array_almost_equal(
linear, numpy.array([0.0 + 0j, 1.0 + 0j, 1.0 + 0j, 0.0 + 0j]))
stokes = numpy.array([0.0, 0.0, 0.0, 1.0])
linear = convert_stokes_to_linear(stokes)
assert_array_almost_equal(
linear, numpy.array([0.0 + 0j, +1.0j, -1.0j, 0.0 + 0j]))
def test_stokes_linear_conversion(self):
stokes = numpy.array([1.0, 0.0, 0.0, 0.0])
linear = convert_stokes_to_linear(stokes, 0)
assert_array_almost_equal(
linear, numpy.array([1.0 + 0j, 0.0 + 0j, 0.0 + 0j, 1.0 + 0j]))
stokes = numpy.array([1.0, 0.0])
linearnp = convert_stokes_to_linear(stokes, 0)
assert_array_almost_equal(linearnp, numpy.array([1.0 + 0j, 1.0 + 0j]))
stokes = numpy.array([0.0, 1.0, 0.0, 0.0])
linear = convert_stokes_to_linear(stokes, 0)
assert_array_almost_equal(linear,
numpy.array([1.0 + 0j, 0j, 0j, -1.0 + 0j]))
stokes = numpy.array([0.0, 0.0, 1.0, 0.0])
linear = convert_stokes_to_linear(stokes, 0)
assert_array_almost_equal(
linear, numpy.array([0.0 + 0j, 1.0 + 0j, 1.0 + 0j, 0.0 + 0j]))
stokes = numpy.array([0.0, 0.0, 0.0, 1.0])
linear = convert_stokes_to_linear(stokes, 0)
assert_array_almost_equal(
linear, numpy.array([0.0 + 0j, +1.0j, -1.0j, 0.0 + 0j]))
stokes = numpy.array([1.0, -0.8, 0.2, 0.01])
linear = convert_stokes_to_linear(stokes, 0)
assert_array_almost_equal(
linear,
numpy.array([0.2 + 0.j, 0.2 + 0.01j, 0.2 - 0.01j, 1.8 + 0.j]))
def test_stokes_linear_stokes_conversion(self):
stokes = numpy.array([1, 0.5, 0.2, -0.1])
linear = convert_stokes_to_linear(stokes)
assert_array_almost_equal(
convert_linear_to_stokes(linear).real, stokes, 15)
def test_stokes_linearnp_stokesIQ_conversion(self):
stokes = numpy.array([1, 0.5])
linearnp = convert_stokes_to_linear(stokes, 0)
assert_array_almost_equal(
convert_linear_to_stokes(linearnp, 0).real, stokes, 15)