def test_vrad(self):
"""Testing component vs spectrum with some vrad shift."""
# create spectrum
wave = np.linspace(4500, 9300, 3500)
spec = Spectrum(flux=np.random.rand(3500), wave=wave)
# create component
cmp = StarComponent(spec)
# redshift original spectrum
spec.redshift(100.)
# create params and interpolate
spec_cmp = cmp(v=100., sig=0.)
# test for equal
assert np.array_equal(spec.wave, spec_cmp.wave)
assert np.array_equal(spec.flux, spec_cmp.flux)
def test_load(self):
"""Test loading a filter."""
# load it via Filter
f = Filter('V', path=data_filename('filters'))
# load it as Spectrum
s = Spectrum.load(data_filename('filters/V.txt'))
# should be identical
assert np.array_equal(f.wave, s.wave)
assert np.array_equal(f.throughput, s.flux)
def test_squared(self):
# filename for spectrum
filename = data_filename('spectra/ngc6397id000010554jd2456865p5826f000.fits')
# load spectrum and sigma
spec = Spectrum.load(filename)
sigma = fits.getdata(filename, 'SIGMA')
# create weight
weight = WeightFromSigma(squared=True)
# compare
diff = weight(spec, filename) - 1./sigma**2
assert np.max(np.abs(diff)) < 1e-5
def test_restframe(self):
"""Testing component vs spectrum."""
# create spectrum
wave = np.linspace(4500, 9300, 3500)
spec = Spectrum(flux=np.random.rand(3500), wave=wave)
# create component
cmp = StarComponent(spec)
# create params and interpolate
spec_cmp = cmp(v=0., sig=0.)
# test for equal
assert np.array_equal(spec.wave, spec_cmp.wave)
assert np.array_equal(spec.flux, spec_cmp.flux)
def test_default(self):
# filename for spectrum
filename = data_filename(
'spectra/ngc6397id000010554jd2456865p5826f000.fits')
# load spectrum and sigma
spec = Spectrum.load(filename)
# create weight
weight = WeightRanges(ranges=[(4841., 4881., 10.)], initial=1.)
w = weight(spec, filename)
# first pixel should be one
assert w[0] == 1.
# get pixel at 4861AA and test it
i = spec.index_of_wave(4861)
assert w[i] == 10.
def test_apply(self):
"""Test applying a filter."""
# load it via Filter
f = Filter('V', path=data_filename('filters'))
# load spectrum, fix flux (which is given in 1e20erg/s/cm/cm2) and resample filter
s = Spectrum.load(
data_filename('spectra/ngc6397id000010554jd2456865p5826f000.fits'))
s /= 1e20
f.resample(spec=s, inplace=True)
# calculate V mag as ST and VEGAMAG
st = f.stmag(s)
vega = f.vegamag(s)
# F606W mag is 13.17, V mag should be close to 13.4
assert abs(st - 13.4) < 0.1
assert abs(vega - 13.4) < 0.1
def test_resample(self):
"""Test resampling a filter."""
# load it via Filter
f = Filter('V', path=data_filename('filters'))
# integrate it
int1 = np.trapz(f.throughput, f.wave)
# load spectrum and resample filter
s = Spectrum.load(
data_filename('spectra/ngc6397id000010554jd2456865p5826f000.fits'))
f.resample(spec=s, inplace=True)
# integrate it again
int2 = np.trapz(f.throughput, f.wave)
# integral should not have changed significantly
assert abs(int1 - int2) < 1
def test_truediv(self, spectrum):
"""Tests __mul__ method.
Checking, whether we can divide a spectrum by a number, an array, and another spectrum."""
# divide by number
result = spectrum / 10.
assert np.array_equal(result, spectrum.flux / 10.)
# divide by array
div = np.arange(1., 10., 1.)
result = spectrum / div
assert np.array_equal(result, spectrum.flux / div)
# divide by spectrum
other = Spectrum(flux=div,
wave=spectrum.wave,
wave_mode=spectrum.wave_mode)
result = spectrum / other
assert np.array_equal(result, spectrum.flux / other.flux)
def test_add(self, spectrum):
"""Tests __add__ method.
Checking, whether we can add a spectrum to a number, an array, and another spectrum."""
# add number
result = spectrum * 10.
assert np.array_equal(result, spectrum.flux * 10.)
# add array
div = np.arange(1., 10., 1.)
result = spectrum + div
assert np.array_equal(result, spectrum.flux + div)
# add spectrum
other = Spectrum(flux=div,
wave=spectrum.wave,
wave_mode=spectrum.wave_mode)
result = spectrum + other
assert np.array_equal(result, spectrum.flux + other.flux)
def test_mul(self, spectrum):
"""Tests __mul__ method.
Checking, whether we can multiply a spectrum with a number, an array, and another spectrum."""
# multiply with number
result = spectrum * 10.
assert np.array_equal(result, spectrum.flux * 10.)
# multiply with array
div = np.arange(1., 10., 1.)
result = spectrum * div
assert np.array_equal(result, spectrum.flux * div)
# multiply with spectrum
other = Spectrum(flux=div,
wave=spectrum.wave,
wave_mode=spectrum.wave_mode)
result = spectrum * other
assert np.array_equal(result, spectrum.flux * other.flux)
def spec_grid_1d():
# create some random spectra
wave = np.linspace(4500, 9300, 3500)
specs = {
(5500., ): Spectrum(flux=np.random.rand(3500), wave=wave),
(5600., ): Spectrum(flux=np.random.rand(3500), wave=wave),
(5700., ): Spectrum(flux=np.random.rand(3500), wave=wave),
(5800., ): Spectrum(flux=np.random.rand(3500), wave=wave),
(5900., ): Spectrum(flux=np.random.rand(3500), wave=wave),
(6000., ): Spectrum(flux=np.random.rand(3500), wave=wave)
}
# define axis
ax = GridAxis(name='Teff', values=[5500, 5600, 5700, 5800, 5900, 6000])
# return new grid
return ValuesGrid([ax], specs)
def _fit_func(self, params: Parameters) -> np.ndarray:
"""Fit function for LM optimization
Args:
params: Parameters to evaluate.
Returns:
Weights scaled residuals between spec and model.
"""
try:
# evaluate params
self._model = self._get_model(params)
# calc residuals
return (self._model.flux[self._valid] -
self._spec.flux[self._valid]) * self._weight[self._valid]
except (KeyError, pd.core.indexing.IndexingError, ValueError):
# could not interpolate
self.log.exception('Could not interpolate model.')
self._model = Spectrum(spec=self._spec)
self._model.flux[:] = 0
return np.ones((len(self._spec.flux[self._valid]))) * 1e100
def spectrum():
wave = np.arange(1., 10., 1.)
flux = np.arange(1001., 1010., 1.)
yield Spectrum(flux=flux, wave=wave, wave_mode=Spectrum.Mode.LAMBDA)
def spectrum():
wave = np.arange(1, 10, 1)
flux = np.random.uniform(0, 1, len(wave))
yield Spectrum(flux=flux, wave=wave, wave_mode=Spectrum.Mode.LAMBDA)