def test_initialises_from_array_dict(self):
n = 5
kwargs = surf_list_kwargs(n)
surf_list = sl.SurfaceList(**kwargs)
assert len(surf_list.data) == n
assert isinstance(surf_list, sl.SurfaceList)
assert surf_list.surfaces["M1"].area == 1 * u.m**2
def test_adds_bg_to_source_if_source_has_no_bg(self):
n = 11
kwargs = surf_list_kwargs(n)
surf_list = sl.SurfaceList(**kwargs)
src = so._vega_source()
wave = np.linspace(1, 2.5, 1000) * u.um
flux_before = src.spectra[0](wave).value
src = surf_list.apply_to(src)
flux_after = src.spectra[0](wave).value
assert np.average(flux_after / flux_before) == approx(0.985**n)
assert src.fields[-1].header["BG_SRC"] is True
assert src.fields[-1].header["SPEC_REF"] == 1
if PLOTS:
plt.semilogy(wave, flux_before)
plt.semilogy(wave, flux_after)
plt.show()
def test_combines_emission_correctly(self):
n = 5
kwargs = surf_list_kwargs(n)
surf_list = sl.SurfaceList(**kwargs)
wave = np.arange(0.8, 2.5, 0.01) * u.um
sum_values = np.sum([surf_list.surfaces[key].emission(wave).value
for key in surf_list.surfaces], axis=0)
comb_value = surf_list.emission(wave).value
sollwert = np.sum([0.985 ** n for n in range(n)]) / n
assert np.average(comb_value / sum_values) == approx(sollwert, rel=1e-5)
# print(sum_values, comb_value, comb_value / sum_values, sollwert)
if PLOTS:
wave = np.linspace(0.8, 2.5, 100) * u.um
for key, surf in surf_list.surfaces.items():
plt.semilogy(wave, surf.emission(wave))
plt.semilogy(wave, surf_list.emission(wave))
plt.show()
def test_initialises_with_nothing(self):
assert isinstance(sl.SurfaceList(), sl.SurfaceList)
def micado_surf_list():
return sl.SurfaceList(filename="LIST_mirrors_MICADO_Wide.tbl")
def test_plotting(self):
if PLOTS:
surf_list = micado_surf_list()
surf_list = sl.SurfaceList(**surf_list_kwargs(2))
surf_list.plot("xe")
plt.show()