def _vega_source(mag=0, x=0, y=0):
specs = [vega_spectrum(mag)]
tbl = Table(names=["x", "y", "ref", "weight"],
data=[[x] * u.arcsec, [y] * u.arcsec, [0], [1]])
tbl_source = Source(table=tbl, spectra=specs)
return tbl_source
def test_initialises_with_table_and_2_spectrum(self, ii, input_tables,
input_spectra):
table = input_tables[ii]
src = Source(table=table, spectra=input_spectra)
assert isinstance(src, Source)
assert isinstance(src.spectra[0], SourceSpectrum)
assert isinstance(src.fields[0], Table)
def image_source():
n = 50
unit = u.Unit("ph s-1 m-2 um-1")
wave = np.linspace(0.5, 2.5, n) * u.um
specs = [
SourceSpectrum(Empirical1D,
points=wave,
lookup_table=np.linspace(0, 4, n) * unit)
]
n = 50
im_wcs = wcs.WCS(naxis=2)
im_wcs.wcs.cunit = [u.arcsec, u.arcsec]
im_wcs.wcs.cdelt = [0.2, 0.2]
im_wcs.wcs.crval = [0, 0]
im_wcs.wcs.crpix = [n // 2, n // 2]
im_wcs.wcs.ctype = ["RA---TAN", "DEC--TAN"]
im = np.ones((n + 1, n + 1)) * 1E-11
im[0, n] += 5
im[n, 0] += 5
im[n // 2, n // 2] += 10
im_hdu = fits.ImageHDU(data=im, header=im_wcs.to_header())
im_hdu.header["SPEC_REF"] = 0
im_source = Source(image_hdu=im_hdu, spectra=specs)
return im_source
def _unity_source(dx=0, dy=0, angle=0, weight=1, n=100):
unit = u.Unit("ph s-1 m-2 um-1")
wave = np.linspace(0.5, 2.5, n) * u.um
specs = [
SourceSpectrum(Empirical1D,
points=wave,
lookup_table=np.ones(n) * unit)
]
im_wcs = wcs.WCS(naxis=2)
im_wcs.wcs.cunit = [u.arcsec, u.arcsec]
im_wcs.wcs.cdelt = [1, 1]
im_wcs.wcs.crval = [0, 0]
im_wcs.wcs.crpix = [n / 2, n / 2]
im_wcs.wcs.ctype = ["RA---TAN", "DEC--TAN"]
im = np.ones((n, n))
im_hdu = fits.ImageHDU(data=im, header=im_wcs.to_header())
im_hdu.header["SPEC_REF"] = 0
im_source = Source(image_hdu=im_hdu, spectra=specs)
angle = angle * np.pi / 180
im_source.fields[0].header["CRVAL1"] += dx * u.arcsec.to(u.deg)
im_source.fields[0].header["CRVAL2"] += dy * u.arcsec.to(u.deg)
im_source.fields[0].header["PC1_1"] = np.cos(angle)
im_source.fields[0].header["PC1_2"] = np.sin(angle)
im_source.fields[0].header["PC2_1"] = -np.sin(angle)
im_source.fields[0].header["PC2_2"] = np.cos(angle)
im_source.fields[0].data *= weight
return im_source
def test_initialises_with_filename_and_spectrum(self, ii, dtype,
input_files,
input_spectra):
fname = input_files[ii]
src = Source(filename=fname, spectra=input_spectra)
assert isinstance(src, Source)
assert isinstance(src.spectra[0], SourceSpectrum)
assert isinstance(src.fields[0], dtype)
def test_initialises_with_only_imagehdu_and_arcsec2(self):
hdu = fits.ImageHDU(data=np.ones([3, 3]))
hdu.header["BUNIT"] = "Jy/arcsec2"
hdu.header["CDELT1"] = 0.1
hdu.header["CUNIT1"] = "arcsec"
hdu.header["CDELT2"] = 0.1
hdu.header["CUNIT2"] = "arcsec"
src = Source(image_hdu=hdu)
assert isinstance(src, Source)
assert isinstance(src.spectra[0], SourceSpectrum)
assert isinstance(src.fields[0], fits.ImageHDU)
def _image_source(dx=0, dy=0, angle=0, weight=1):
"""
An image with 3 point sources on a random BG
Parameters
----------
dx, dy : float
[arcsec] Offset from optical axis
angle : float
[deg]
weight : float
Returns
-------
"""
n = 101
unit = u.Unit("ph s-1 m-2 um-1")
wave = np.linspace(0.5, 2.5, n) * u.um
specs = [
SourceSpectrum(Empirical1D,
points=wave,
lookup_table=np.linspace(0, 4, n) * unit)
]
n = 50
im_wcs = wcs.WCS(naxis=2)
im_wcs.wcs.cunit = [u.arcsec, u.arcsec]
im_wcs.wcs.cdelt = [0.2, 0.2]
im_wcs.wcs.crval = [0, 0]
im_wcs.wcs.crpix = [n // 2, n // 2]
im_wcs.wcs.ctype = ["RA---TAN", "DEC--TAN"]
im = np.random.random(size=(n + 1, n + 1)) * 1e-9 * weight
im[n - 1, 1] += 5 * weight
im[1, 1] += 5 * weight
im[n // 2, n // 2] += 10 * weight
im[n // 2, n - 1] += 5 * weight
im_hdu = fits.ImageHDU(data=im, header=im_wcs.to_header())
im_hdu.header["SPEC_REF"] = 0
im_source = Source(image_hdu=im_hdu, spectra=specs)
angle = angle * np.pi / 180
im_source.fields[0].header["CRVAL1"] += dx / 3600
im_source.fields[0].header["CRVAL2"] += dy / 3600
im_source.fields[0].header["PC1_1"] = np.cos(angle)
im_source.fields[0].header["PC1_2"] = np.sin(angle)
im_source.fields[0].header["PC2_1"] = -np.sin(angle)
im_source.fields[0].header["PC2_2"] = np.cos(angle)
return im_source
def _single_table_source(weight=1, n=3):
unit = u.Unit("ph s-1 m-2 um-1")
wave = np.linspace(0.5, 2.5, n) * u.um
specs = [
SourceSpectrum(Empirical1D,
points=wave,
lookup_table=np.ones(n) * weight * unit)
]
tbl = Table(names=["x", "y", "ref", "weight"],
data=[[0] * u.arcsec, [0] * u.arcsec, [0], [1]])
tbl_source = Source(table=tbl, spectra=specs)
return tbl_source
def _empty_sky():
n = 3
unit = u.Unit("ph s-1 m-2 um-1")
wave = np.linspace(0.5, 2.5, n) * u.um
specs = [
SourceSpectrum(Empirical1D,
points=wave,
lookup_table=np.zeros(n) * unit)
]
tbl = Table(names=["x", "y", "ref", "weight"], data=[[0], [0], [0], [0]])
tbl_source = Source(table=tbl, spectra=specs)
return tbl_source
def test_initialised_with_old_style_arrays(self):
x, y = [0, 1], [0, -1]
ref, weight = [0, 0], [1, 10]
lam = np.linspace(0.5, 2.5, 11) * u.um
spectra = np.ones(11) * PHOTLAM
src = Source(x=x,
y=y,
ref=ref,
weight=weight,
lam=lam,
spectra=spectra)
assert isinstance(src, Source)
assert isinstance(src.spectra[0], SourceSpectrum)
assert isinstance(src.fields[0], Table)
def _fits_image_source():
n = 50
unit = u.Unit("ph s-1 m-2 um-1")
wave = np.linspace(0.5, 2.5, n) * u.um
specs = [
SourceSpectrum(Empirical1D,
points=wave,
lookup_table=np.linspace(0, 4, n) * unit)
]
hdulist = fits.open(os.path.join(FILES_PATH, "test_image.fits"))
fits_src = Source(image_hdu=hdulist[0], spectra=specs)
return fits_src
def yaml_file_can_be_loaded_into_optical_train(self):
# .. todo: get this working on Travis
filename = os.path.join(TEST_PATH, "MICADO_SCAO_WIDE_2.yaml")
cmds = UserCommands(yamls=[filename])
assert isinstance(cmds, UserCommands)
assert isinstance(cmds.yaml_dicts, list)
psf_file = cmds.yaml_dicts[1]["effects"][0]["kwargs"]["filename"]
if find_file(psf_file) is None:
new_file = "test_FVPSF.fits"
cmds.yaml_dicts[1]["effects"][0]["kwargs"]["filename"] = new_file
opt = OpticalTrain(cmds=cmds)
assert isinstance(opt, OpticalTrain)
assert isinstance(opt.optics_manager, OpticsManager)
assert isinstance(
opt.optics_manager.get_all(efs.FieldVaryingPSF)[0],
efs.FieldVaryingPSF)
assert isinstance(opt.image_plane, ImagePlane)
assert opt.image_plane.hdu.header["NAXIS1"] >= 4096
assert isinstance(opt.fov_manager, FOVManager)
assert len(opt.fov_manager.fovs) == 64
if PLOTS:
for fov in opt.fov_manager.fovs:
sky_cnrs, det_cnrs = fov.corners
plt.plot(sky_cnrs[0], sky_cnrs[1])
plt.show()
r = np.arange(-25, 25)
x, y = np.meshgrid(r, r)
x = x.flatten() * u.arcsec
y = y.flatten() * u.arcsec
ref = [0] * len(x)
weight = [1] * len(x)
spec = sp.SourceSpectrum(sp.Empirical1D,
points=[0.5, 3.0] * u.um,
lookup_table=[1e3, 1e3] *
u.Unit("ph s-1 m-2 um-1"))
src = Source(x=x, y=y, ref=ref, weight=weight, spectra=[spec])
opt.observe(src)
if PLOTS:
plt.imshow(opt.image_plane.image.T, origin="lower", norm=LogNorm())
plt.colorbar()
plt.show()
def _table_source():
n = 101
unit = u.Unit("ph s-1 m-2 um-1")
wave = np.linspace(0.5, 2.5, n) * u.um
specs = [
SourceSpectrum(Empirical1D,
points=wave,
lookup_table=4 * np.ones(n) * unit),
SourceSpectrum(Empirical1D,
points=wave,
lookup_table=np.linspace(0, 4, n) * unit),
SourceSpectrum(Empirical1D,
points=wave,
lookup_table=np.linspace(0, 4, n)[::-1] * unit)
]
tbl = Table(names=["x", "y", "ref", "weight"],
data=[[5, 0, -5, 0] * u.arcsec, [5, -10, 5, 0] * u.arcsec,
[2, 0, 1, 0], [1, 1, 1, 2]])
tbl_source = Source(table=tbl, spectra=specs)
return tbl_source
def mock_extended_source_object():
from scipy.misc import face
im = face()[::-1, :, 0]
im = im / np.max(im)
hdr = {
"CDELT1": 0.1,
"CDELT2": 0.1,
"CRVAL1": 0.,
"CRVAL2": 0.,
"CRPIX1": im.shape[1] / 2,
"CRPIX2": im.shape[0] / 2,
"CTYPE1": "LINEAR",
"CTYPE2": "LINEAR",
"CUNIT1": "ARCSEC",
"CUNIT2": "ARCSEC"
}
hdu = fits.ImageHDU(data=im, header=fits.Header(hdr))
spec = SourceSpectrum(Empirical1D,
points=[1.0, 2.5] * u.um,
lookup_table=[1, 1] * PHOTLAM)
src = Source(image_hdu=hdu, spectra=spec)
return src
def mock_point_source_object():
"""
Three point sources, 1 up and 2 below the optical axis, fit inside the
above defined apertures
"""
wave = [1.0, 2.5] * u.um
flat = SourceSpectrum(Empirical1D,
points=wave,
lookup_table=[100, 100] * PHOTLAM)
down = SourceSpectrum(Empirical1D,
points=wave,
lookup_table=[60, 1] * PHOTLAM)
up = SourceSpectrum(Empirical1D,
points=wave,
lookup_table=[1, 60] * PHOTLAM)
src = Source(x=[0, -2, 2],
y=[1, -1, -1],
ref=[0, 1, 2],
spectra=[flat, up, down])
return src
def test_initialises_with_image_and_flux(self, input_hdulist):
src = Source(image_hdu=input_hdulist[0], flux=20 * u.ABmag)
assert isinstance(src, Source)
assert isinstance(src.spectra[0], SourceSpectrum)
assert isinstance(src.fields[0], fits.ImageHDU)
def test_initialises_with_nothing(self):
src = Source()
assert isinstance(src, Source)
def test_initialises_with_image_and_0_spectra(self, input_hdulist):
with pytest.raises(NotImplementedError):
src = Source(image_hdu=input_hdulist[0])
def test_initialises_with_image_and_1_spectrum(self, input_hdulist,
input_spectra):
src = Source(image_hdu=input_hdulist[0], spectra=input_spectra)
assert isinstance(src, Source)
assert isinstance(src.spectra[0], SourceSpectrum)
assert isinstance(src.fields[0], fits.PrimaryHDU)
def test_initialises_with_only_image(self, input_hdulist):
input_hdulist[0].header["BUNIT"] = "ph s-1 cm-2 AA-1"
src = Source(image_hdu=input_hdulist[0])
assert len(src.spectra) == 1
assert src.fields[0].header["SPEC_REF"] == 0