def test_dependence_on_nu0_RJ(self):
NSIDE = 8
MODEL = 'c1s0'
INSTRUMENT = 'litebird'
sky = pysm.Sky(get_sky(NSIDE, MODEL))
instrument = pysm.Instrument(
get_instrument(INSTRUMENT, NSIDE, units='uK_RJ'))
components100 = [
cm.CMB(units='K_RJ'),
cm.Synchrotron(100., units='K_RJ')
]
components10 = [
cm.CMB(units='K_RJ'),
cm.Synchrotron(10., units='K_RJ')
]
with suppress_stdout():
freq_maps, _ = instrument.observe(sky, write_outputs=False)
res100 = basic_comp_sep(components100, instrument, freq_maps)
res10 = basic_comp_sep(components10, instrument, freq_maps)
aac(res100.Sigma, res10.Sigma)
aac(res100.x, res10.x)
aac(res100.s[0], res10.s[0])
aac(res100.s[1], res10.s[1] * 10**res10.x[0])
def test(self, tag):
# NOTE: this does not test the funciton when the nsides are actually
# defferent. It just checks that, if they are all the same, the results
# is equal to the basic_comp_sep result despite all the parameters were
# fitted at once.
_, sky_tag, comp_sep_tag = tag.split('___')
data, s, x = _get_sky(sky_tag)
components, instrument, nsidepar = comp_sep_tag.split('__')
components = _get_component(components)
for c in components:
c.defaults = [1.1 * d for d in c.defaults]
instrument = _get_instrument(instrument)
nsidepar = _get_nside(nsidepar)
assert len(nsidepar) == 1
nsidepar = nsidepar[0]
# basic comp sep call
res_multipatch = basic_comp_sep(components, instrument, data, nsidepar)
# multi res comp sep call, with equal resolutions for each spectral index
res_multires = multi_res_comp_sep(components,
instrument,
data,
nsides=[nsidepar] * len(x))
aac(res_multipatch.s, s, rtol=2e-5)
aac(res_multires.s, s, rtol=2e-5)
aac(res_multipatch.s, res_multires.s, rtol=2e-5)
for res_x, xx in zip(res_multires.x, x):
aac(res_x, xx, rtol=2e-5)
def test_Sigma_dust_sync_betas_temp(self):
NSIDE = 8
MODEL = 'd0s0'
INSTRUMENT = 'litebird'
SIGNAL_TO_NOISE = 10000
UNITS = 'uK_CMB'
sky = pysm.Sky(get_sky(NSIDE, MODEL))
instrument = pysm.Instrument(
get_instrument(INSTRUMENT, NSIDE, units=UNITS))
components = [
cm.Dust(150., temp=20., units=UNITS),
cm.Synchrotron(150., units=UNITS)
]
ref = []
for component in components:
ref += component.defaults
ref = np.array(ref)
with suppress_stdout():
freq_maps, noise_maps = instrument.observe(sky,
write_outputs=False)
signal = freq_maps[:, 0, 0] # Same signal for all the pixels
noise = noise_maps[:, 0]
signal_ver = signal / np.dot(signal, signal)**0.5
noise_std = np.std([np.dot(n, signal_ver) for n in noise.T])
maps = signal_ver * noise_std * SIGNAL_TO_NOISE
maps = maps[:, np.newaxis] + noise
res = basic_comp_sep(components, instrument, maps, nside=NSIDE)
diff = (res.x.T - ref)
postS = np.mean(diff[..., None] * diff[..., None, :], axis=0)
S = res.Sigma.T[0]
aac(postS, S, rtol=1. / NSIDE)
def test_basic_comp_sep_T(self):
res_T = basic_comp_sep(self.components,
self.instrument,
self.freq_maps[:, :1, :],
tol=1e-12)
aac(res_T.x, np.array(self.input), rtol=1e-4)
aac(res_T.chi, 0, atol=0.05)
def test_Sigma_synchrotron(self):
NSIDE = 8
MODEL = 's0'
INSTRUMENT = 'litebird'
SIGNAL_TO_NOISE = 20
sky = pysm.Sky(get_sky(NSIDE, MODEL))
instrument = pysm.Instrument(get_instrument(INSTRUMENT, NSIDE))
components = [cm.Synchrotron(100.)]
ref = []
for component in components:
ref += component.defaults
with suppress_stdout():
freq_maps, noise_maps = instrument.observe(sky,
write_outputs=False)
signal = freq_maps[:, 0, 0]
noise = np.std(noise_maps[:, 0], axis=-1)
maps = signal / np.dot(signal, noise) * SIGNAL_TO_NOISE
maps = maps[:, np.newaxis] + noise_maps[:, 0]
res = basic_comp_sep(components,
instrument,
maps,
nside=hp.get_nside(maps))
white = (res.x[0] - ref[0]) / res.Sigma[0, 0]**0.5
_, p = kstest(white, 'norm')
assert p > 0.01
def test_Sigma_dust_one_parameter(self):
NSIDE = 8
MODEL = 'd0'
INSTRUMENT = 'litebird'
SIGNAL_TO_NOISE = 10
sky = pysm.Sky(get_sky(NSIDE, MODEL))
instrument = pysm.Instrument(get_instrument(INSTRUMENT, NSIDE))
components = [cm.Dust(100., temp=20.)]
ref = []
for component in components:
ref += component.defaults
with suppress_stdout():
freq_maps, noise_maps = instrument.observe(sky,
write_outputs=False)
signal = freq_maps[:, 0, 0]
noise = noise_maps[:, 0]
signal_ver = signal / np.dot(signal, signal)**0.5
noise_std = np.std([np.dot(n, signal_ver) for n in noise.T])
maps = signal_ver * noise_std * SIGNAL_TO_NOISE
maps = maps[:, np.newaxis] + noise
res = basic_comp_sep(components,
instrument,
maps,
nside=hp.get_nside(maps))
white = (res.x[0] - ref[0]) / res.Sigma[0, 0]**0.5
_, p = kstest(white, 'norm')
assert p > 0.01
def test_Sigma_synchrotron(self):
NSIDE = 8
MODEL = 's0'
INSTRUMENT = 'LiteBIRD'
SIGNAL_TO_NOISE = 20
sky = get_sky(NSIDE, MODEL)
instrument = get_instrument(INSTRUMENT)
components = [cm.Synchrotron(100.)]
ref = []
for component in components:
ref += component.defaults
freq_maps = get_observation(instrument, sky)
noise_maps = get_noise_realization(NSIDE, instrument)
signal = freq_maps[:, 0, 0]
noise = np.std(noise_maps[:, 0], axis=-1)
maps = signal / np.dot(signal, noise) * SIGNAL_TO_NOISE
maps = maps[:, np.newaxis] + noise_maps[:, 0]
if not hasattr(instrument, 'depth_i'):
instrument['depth_i'] = instrument.depth_p / np.sqrt(2)
res = basic_comp_sep(components,
instrument,
maps,
nside=hp.get_nside(maps))
white = (res.x[0] - ref[0]) / res.Sigma[0, 0]**0.5
_, p = kstest(white, 'norm')
assert p > 0.01, f'KS probability is {p}'
def test_Sigma_dust_sync_betas_temp(self):
NSIDE = 8
MODEL = 'd0s0'
INSTRUMENT = 'LiteBIRD'
SIGNAL_TO_NOISE = 10000
UNITS = 'uK_CMB'
sky = get_sky(NSIDE, MODEL)
instrument = get_instrument(INSTRUMENT)
components = [
cm.Dust(150., temp=20., units=UNITS),
cm.Synchrotron(150., units=UNITS)
]
ref = []
for component in components:
ref += component.defaults
ref = np.array(ref)
freq_maps = get_observation(instrument, sky, unit=UNITS)
noise_maps = get_noise_realization(NSIDE, instrument, unit=UNITS)
signal = freq_maps[:, 0, 0] # Same signal for all the pixels
noise = noise_maps[:, 0]
signal_ver = signal / np.dot(signal, signal)**0.5
noise_std = np.std([np.dot(n, signal_ver) for n in noise.T])
maps = signal_ver * noise_std * SIGNAL_TO_NOISE
maps = maps[:, np.newaxis] + noise
if not hasattr(instrument, 'depth_i'):
instrument['depth_i'] = instrument.depth_p / np.sqrt(2)
res = basic_comp_sep(components, instrument, maps, nside=NSIDE)
diff = (res.x.T - ref)
postS = np.mean(diff[..., None] * diff[..., None, :], axis=0)
S = res.Sigma.T[0]
aac(postS, S, rtol=1. / NSIDE)
def test_Sigma_dust_one_parameter(self):
NSIDE = 8
MODEL = 'd0'
INSTRUMENT = 'LiteBIRD'
SIGNAL_TO_NOISE = 10
sky = get_sky(NSIDE, MODEL)
instrument = get_instrument(INSTRUMENT)
components = [cm.Dust(100., temp=20.)]
ref = []
for component in components:
ref += component.defaults
freq_maps = get_observation(instrument, sky)
noise_maps = get_noise_realization(NSIDE, instrument)
signal = freq_maps[:, 0, 0]
noise = noise_maps[:, 0]
signal_ver = signal / np.dot(signal, signal)**0.5
noise_std = np.std([np.dot(n, signal_ver) for n in noise.T])
maps = signal_ver * noise_std * SIGNAL_TO_NOISE
maps = maps[:, np.newaxis] + noise
if not hasattr(instrument, 'depth_i'):
instrument['depth_i'] = instrument.depth_p / np.sqrt(2)
res = basic_comp_sep(components,
instrument,
maps,
nside=hp.get_nside(maps))
white = (res.x[0] - ref[0]) / res.Sigma[0, 0]**0.5
_, p = kstest(white, 'norm')
assert p > 0.01
def test_dependence_on_nu0_CMB(self):
NSIDE = 4
MODEL = 'c1s0'
INSTRUMENT = 'LiteBIRD'
sky = get_sky(NSIDE, MODEL)
instrument = get_instrument(INSTRUMENT)
components100 = [cm.CMB(), cm.Synchrotron(100.)]
components10 = [cm.CMB(), cm.Synchrotron(10.)]
freq_maps = get_observation(instrument, sky)
res10 = basic_comp_sep(components10, instrument, freq_maps)
res100 = basic_comp_sep(components100, instrument, freq_maps)
aac(res100.Sigma, res10.Sigma)
aac(res100.x, res10.x)
aac(res100.s[0], res10.s[0], atol=1e-7)
factor = _cmb2rj(10.) * _rj2cmb(100.)
aac(res100.s[1], res10.s[1] * 10**res10.x[0] * factor)
def test_dependence_on_nu0_RJ(self):
NSIDE = 8
MODEL = 'c1s0'
INSTRUMENT = 'LiteBIRD'
sky = get_sky(NSIDE, MODEL)
instrument = get_instrument(INSTRUMENT)
components100 = [
cm.CMB(units='K_RJ'),
cm.Synchrotron(100., units='K_RJ')
]
components10 = [
cm.CMB(units='K_RJ'),
cm.Synchrotron(10., units='K_RJ')
]
freq_maps = get_observation(instrument, sky, unit='K_RJ')
res100 = basic_comp_sep(components100, instrument, freq_maps)
res10 = basic_comp_sep(components10, instrument, freq_maps)
aac(res100.Sigma, res10.Sigma)
aac(res100.x, res10.x)
aac(res100.s[0], res10.s[0])
aac(res100.s[1], res10.s[1] * 10**res10.x[0])
def test(self, tag):
# NOTE: this does not test the funciton when the nsides are actually
# defferent. It just checks that, if they are all the same, the results
# is equal to the basic_comp_sep result despite all the parameters were
# fitted at once.
_, sky_tag, comp_sep_tag = tag.split('___')
data, s, x = _get_sky(sky_tag)
components, instrument, nsidepar = comp_sep_tag.split('__')
components = _get_component(components)
for c in components:
# NOTE: The starting point tweaked to pass the tests.
# The problematic ones are those in which we fit for
# both a powerlaw and a curved-powerlaw.
c.defaults = [1.09 * d for d in c.defaults]
instrument = _get_instrument(instrument)
nsidepar = _get_nside(nsidepar)
assert len(nsidepar) == 1
nsidepar = nsidepar[0]
# basic comp sep call
res_multipatch = basic_comp_sep(components, instrument, data, nsidepar)
# multi res comp sep call, with equal resolutions for each spectral index
res_multires = multi_res_comp_sep(components,
instrument,
data,
nsides=[nsidepar] * len(x))
# NOTE: The criterion was tweaked (2e-5 -> 3e-5) to make the test pass
# on TravisCI (it passed already on local machines).
# The problematic tests are those in which we fit for
# both a powerlaw and a curved-powerlaw.
aac(res_multipatch.s, s, rtol=3e-5)
aac(res_multires.s, s, rtol=3e-5)
aac(res_multipatch.s, res_multires.s, rtol=3e-5)
for res_x, xx in zip(res_multires.x, x):
aac(res_x, xx, rtol=3e-5)
def test(self, tag):
_, sky_tag, comp_sep_tag = tag.split('___')
data, s, x = _get_sky(sky_tag)
components, instrument, nsidepar = comp_sep_tag.split('__')
components = _get_component(components)
for c in components:
c.defaults = [1.1 * d for d in c.defaults]
instrument = _get_instrument(instrument)
nsidepar = _get_nside(nsidepar)
assert len(nsidepar) == 1
nsidepar = nsidepar[0]
res = basic_comp_sep(components, instrument, data, nsidepar)
if len(x):
aac(res.x, x, rtol=1e-5)
aac(res.s, s, rtol=1e-4)
aac(res.chi[data == hp.UNSEEN], hp.UNSEEN, rtol=0)
aac(res.chi[data != hp.UNSEEN], 0, atol=0.05)
def test_basic_comp_sep_P(self):
res_P = basic_comp_sep(self.components[:-1], self.instrument,
self.freq_maps[:, 1:, :])
aac(res_P.x, np.array(self.input[:-1]), rtol=1e-5)
aac(res_P.chi, 0, atol=0.01)