def from_array(cls, wave, fluxd, meta=None, **kwargs):
"""Create standard from arrays.
Parameters
----------
wave : `~astropy.units.Quantity`
The spectral wavelengths.
fluxd : `~astropy.units.Quantity`
The solar flux densities, at 1 au.
meta : dict, optional
Meta data.
**kwargs
Passed to object initialization.
"""
import synphot
source = synphot.SourceSpectrum(synphot.Empirical1D,
points=wave,
lookup_table=fluxd,
meta=meta)
return cls(source, **kwargs)
def from_array(cls, wave, fluxd, meta=None, **kwargs):
"""Create standard from arrays.
Parameters
----------
wave : `~astropy.units.Quantity`
The spectral wavelengths.
fluxd : `~astropy.units.Quantity`
The spectral flux densities.
meta : dict, optional
Meta data.
**kwargs
Passed to object initialization.
"""
try:
import synphot
except ImportError:
raise ImportError('synphot required for {}.'.format(cls.__name__))
source = synphot.SourceSpectrum(synphot.Empirical1D,
points=wave,
lookup_table=fluxd,
meta=meta)
return cls(source, **kwargs)
def test_fluxd(self):
w = u.Quantity(np.linspace(0.3, 1.0), 'um')
f = u.Quantity(np.ones(len(w)), 'W/(m2 um)')
source = synphot.SourceSpectrum(synphot.Empirical1D,
points=w,
lookup_table=f)
s = Star(source)
assert np.allclose(s.fluxd.to(f.unit).value, f.value)
def test_source(self):
w = u.Quantity(np.linspace(0.3, 1.0), 'um')
f = u.Quantity(np.ones(len(w)), 'W/(m2 um)')
source = synphot.SourceSpectrum(synphot.Empirical1D,
points=w,
lookup_table=f)
s = Star(source)
f = s.source(w)
assert s.source == source
def __init__(self, T=None):
super().__init__(None, description='πB(T)')
if T is None:
raise TypeError('T is required.')
self._T = u.Quantity(T, u.K)
self._source = synphot.SourceSpectrum(
synphot.BlackBody1D, temperature=self._T.value) * np.pi
def test_observe_bad_wfb(self):
w = u.Quantity(np.linspace(0.3, 1.0), 'um')
f = u.Quantity(np.ones(len(w)), 'W/(m2 um)')
source = synphot.SourceSpectrum(synphot.Empirical1D,
points=w,
lookup_table=f)
s = Star(source)
with pytest.raises(TypeError):
s.observe(np.arange(5))
def from_file(cls,
filename,
wave_unit=None,
flux_unit=None,
cache=True,
**kwargs):
"""Load the source spectrum from a file.
NaNs are dropped.
Parameters
----------
filename : string
The name of the file. See
`~synphot.SourceSpectrum.from_file` for details.
wave_unit, flux_unit : str or `~astropy.units.Unit`, optional
Wavelength and flux units in the file.
cache : bool, optional
If ``True``, cache the contents of URLs.
**kwargs
Passed to object initialization.
"""
try:
import synphot
except ImportError:
raise ImportError('synphot required for {}.'.format(cls.__name__))
from astropy.utils.data import download_file, _is_url
if filename.lower().endswith(('.fits', '.fit', '.fz')):
read_spec = synphot.specio.read_fits_spec
else:
read_spec = synphot.specio.read_ascii_spec
# URL cache because synphot.SourceSpectrum.from_file does not
if _is_url(filename):
fn = download_file(filename, cache=True)
else:
fn = filename
spec = read_spec(fn, wave_unit=wave_unit, flux_unit=flux_unit)
i = np.isfinite(spec[1] * spec[2])
source = synphot.SourceSpectrum(synphot.Empirical1D,
points=spec[1][i],
lookup_table=spec[2][i],
meta={'header': spec[0]})
return cls(source, **kwargs)
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 from_file(cls, filename, wave_unit=None, flux_unit=None,
cache=True, **kwargs):
"""Load the source spectrum from a file.
Parameters
----------
filename : string
The name of the file. See
`~synphot.SourceSpectrum.from_file` for details.
wave_unit, flux_unit : str or `~astropy.units.core.Unit`, optional
Wavelength and flux units.
cache : bool, optional
If `True`, cache the contents of URLs.
**kwargs
Passed to `Sun` initialization.
"""
from astropy.utils.data import download_file
from astropy.utils.data import _is_url
import synphot
from synphot.specio import read_fits_spec, read_ascii_spec
# URL cache because synphot.SourceSpectrum.from_file does not
if _is_url(filename):
if filename.lower().endswith(('.fits', '.fit')):
read_spec = read_fits_spec
else:
read_spec = read_ascii_spec
fn = download_file(filename, cache=True)
spec = read_spec(fn, wave_unit=wave_unit, flux_unit=flux_unit)
source = synphot.SourceSpectrum(
synphot.Empirical1D, points=spec[1], lookup_table=spec[2],
meta={'header': spec[0]})
else:
source = synphot.SourceSpectrum.from_file(
filename, wave_unit=wave_unit, flux_unit=flux_unit)
return cls(source, **kwargs)
def __init__(self):
super().__init__(
synphot.SourceSpectrum(synphot.ConstFlux1D,
amplitude=1 * u.W / u.m**2 / u.um))
def get_sky_spectrum(self, return_type="table", filename=None):
from astropy import table
if filename is None:
filename = "skycalc_temp.fits"
if not self.validate_params():
raise ValueError("Object contains invalid parameters. "
"Not calling ESO")
skm = SkyModel()
skm.callwith(self.values)
skm.write(filename)
with fits.open(filename) as hdu:
tbl = table.Table(hdu[1].data)
tbl["lam"].unit = u.um
for colname in tbl.colnames:
if "flux" in colname:
tbl[colname].unit = u.Unit("ph s-1 m-2 um-1 arcsec-2")
date_created = dt.now().strftime('%Y-%m-%dT%H:%M:%S')
meta_data = {
"DESCRIPT": "Sky transmission and emission curves",
"SOURCE": "ESO Skycalc utility",
"AUTHOR": "ESO Skycalc utility",
"STATUS": "Tested - Generated from ESO Skycalc utility",
"DATE_CRE": date_created,
"ETYPE": "TERCurve",
"EDIM": 1
}
params = {k: (self.values[k], self.comments[k]) for k in self.keys}
meta_data.update(params)
if "tab" in return_type:
tbl.meta.update(meta_data)
if "ext" in return_type:
tbl_return = tbl
else:
tbl_small = table.Table()
tbl_small.add_columns([tbl["lam"], tbl["trans"], tbl["flux"]])
tbl_return = tbl_small
return tbl_return
elif "arr" in return_type:
wave = tbl["lam"].data * tbl["lam"].unit
trans = tbl["trans"].data
flux = tbl["flux"].data * tbl["flux"].unit
return wave, trans, flux
elif "syn" in return_type:
import synphot as sp
trans = sp.SpectralElement(sp.Empirical1D,
points=tbl["lam"].data *
tbl["lam"].unit,
lookup_table=tbl["trans"].data)
funit = u.Unit("ph s-1 m-2 um-1")
flux = sp.SourceSpectrum(sp.Empirical1D,
points=tbl["lam"].data * tbl["lam"].unit,
lookup_table=tbl["flux"].data * funit)
print("Warning: synphot doesn't accept surface brightnesses \n"
"The resulting spectrum should be multiplied by arcsec-2")
return trans, flux
elif "fit" in return_type:
hdu0 = fits.PrimaryHDU()
for key in meta_data:
hdu0.header[key] = meta_data[key]
hdu1 = fits.table_to_hdu(tbl)
hdu = fits.HDUList([hdu0, hdu1])
return hdu
time = Time('2025-03-01')
sun = get_sun(time).transform_to(GeocentricTrueEcliptic(equinox=time))
coord = SkyCoord(sun.lon + 180 * u.deg,
lat * u.deg,
frame=GeocentricTrueEcliptic(equinox=time))
st.markdown('## Source')
spectrum = st.radio('Spectrum',
('Thermal', 'Flat in frequency (AB mag = const)',
'Flat in wavelength (ST mag = const)'))
if spectrum == 'Thermal':
temperature = st.number_input('Temperature (K)', 0, 20000, 10000, 1000)
source = synphot.SourceSpectrum(synphot.BlackBodyNorm1D,
temperature=temperature * u.K)
elif spectrum == 'Flat in frequency (AB mag = const)':
source = synphot.SourceSpectrum(synphot.ConstFlux1D, amplitude=0 * u.ABmag)
elif spectrum == 'Flat in wavelength (ST mag = const)':
source = synphot.SourceSpectrum(synphot.ConstFlux1D, amplitude=0 * u.STmag)
spectra = pd.DataFrame({
'wavelength':
bandpass.waveset.to_value(u.nm),
'aeff': (bandpass(bandpass.waveset) *
dorado.sensitivity.constants.AREA).to_value(u.cm**2),
'source':
source(bandpass.waveset, u.erg * u.s**-1 * u.cm**-2 * u.nm**-1)
})
palette = [to_hex(color) for color in seaborn.color_palette('colorblind', 2)]
