def do_pyspeck_fits_2comp(
pcube,
cube303m=None,
vrange=(-105, 125),
m1=None,
guesses_simple=[1, 15, 5, 0.5, 0.7, 1] + [1, 36, 5, 0.5, 0.7, 1],
limits=[(0, 20), (-105, 125), (1, 40), (0, 1), (0.3, 1.1), (0, 1e5)],
):
if m1 is None:
m1 = cube303m.moment1(axis=0).to(u.km / u.s)
# Need to show pcube which pixels to ignore: m1 has nans
pcube.mapplot.plane = m1.value
pcube.fiteach(
fittype='h2co_simple',
multifit=True,
guesses=guesses_simple,
limited=[(True, True)] * len(guesses_simple),
limits=limits,
multicore=8,
)
pcube.mapplot(estimator=0)
pcube_orig = pcube.parcube.copy()
pcube2 = remove_bad_pars(pcube.parcube,
pcube.errcube,
len(guesses_simple),
min_nsig=4)
return pcube2
def do_pyspeck_fits_1comp(pcube, cube303m=None, vguesses='moment',
guesses=[1,None,5,0.5,0.7,1], vrange=(-105,125),
peaks=None,
m1=None,
limits=[(0,20), (-105,125),(1,40),(0,1),(0.3,1.1),(0,1e5)],
start_from_point=(0,0),
**kwargs):
if m1 is None:
m1 = cube303m.moment1(axis=0).to(u.km/u.s)
if vguesses == 'moment':
guesses_simple = np.array([guesses[0:1]+[x]+guesses[2:]
for x in m1.value.flat]).T.reshape((len(guesses),)+m1.shape)
bad = (guesses_simple[1,:,:] < vrange[0]) | (guesses_simple[1,:,:] > vrange[1])
guesses_simple[1,bad] = 25
else:
guesses_simple = guesses
g0 = guesses_simple
if peaks is not None:
# Wow, this is complicated
# First, guesses needs to be reshaped to have the n_guesses as trailing axis
# Then, it needs to be remade to have the first element be the appropriate peak...
flatguesses = guesses_simple.reshape(guesses_simple.shape[0],
np.prod(guesses_simple.shape[1:])).T
guesses_simple = np.array([[peak]+g[1:].tolist()
for peak,g in zip(peaks.value.flat,
flatguesses,)
]
).T.reshape((len(guesses),)+peaks.shape)
# Can't accept guesses being wrong, and I've made too many mistakes...
assert np.all(np.nan_to_num(g0[1:,0,0]) == np.nan_to_num(guesses_simple[1:,0,0]))
assert np.all(np.nan_to_num(g0[1:,start_from_point[1],
start_from_point[0]]) ==
np.nan_to_num(guesses_simple[1:,start_from_point[1],
start_from_point[0]]))
# Need to show pcube which pixels to ignore: m1 has nans
pcube.mapplot.plane = m1.value
pcube.fiteach(fittype='h2co_simple', multifit=True,
guesses=guesses_simple,
limited=[(True,True)] * len(guesses_simple),
limits=limits,
multicore=8,
integral=False,
**kwargs
)
#pcube.mapplot(estimator=0)
pcube_orig = pcube.parcube.copy()
pcube2 = remove_bad_pars(pcube.parcube, pcube.errcube, len(guesses),
min_nsig=4)
def do_pyspeck_fits_2comp(pcube, cube303m=None, vrange=(-105,125),
m1=None,
guesses_simple=[1,15,5,0.5,0.7,1] +
[1,36,5,0.5,0.7,1],
limits=[(0,20),(-105,125),(1,40),(0,1),(0.3,1.1),(0,1e5)],
):
if m1 is None:
m1 = cube303m.moment1(axis=0).to(u.km/u.s)
# Need to show pcube which pixels to ignore: m1 has nans
pcube.mapplot.plane = m1.value
pcube.fiteach(fittype='h2co_simple', multifit=True,
guesses=guesses_simple,
limited=[(True,True)] * len(guesses_simple),
limits=limits,
multicore=8,
)
pcube.mapplot(estimator=0)
pcube_orig = pcube.parcube.copy()
pcube2 = remove_bad_pars(pcube.parcube, pcube.errcube, len(guesses_simple),
min_nsig=4)
return pcube2
def do_pyspeck_fits_1comp(pcube,
cube303m=None,
vguesses='moment',
guesses=[1, None, 5, 0.5, 0.7, 1],
vrange=(-105, 125),
peaks=None,
m1=None,
limits=[(0, 20), (-105, 125), (1, 40), (0, 1),
(0.3, 1.1), (0, 1e5)],
start_from_point=(0, 0),
**kwargs):
if m1 is None:
m1 = cube303m.moment1(axis=0).to(u.km / u.s)
if vguesses == 'moment':
guesses_simple = np.array([
guesses[0:1] + [x] + guesses[2:] for x in m1.value.flat
]).T.reshape((len(guesses), ) + m1.shape)
bad = (guesses_simple[1, :, :] < vrange[0]) | (guesses_simple[1, :, :]
> vrange[1])
guesses_simple[1, bad] = 25
else:
guesses_simple = guesses
g0 = guesses_simple
if peaks is not None:
# Wow, this is complicated
# First, guesses needs to be reshaped to have the n_guesses as trailing axis
# Then, it needs to be remade to have the first element be the appropriate peak...
flatguesses = guesses_simple.reshape(guesses_simple.shape[0],
np.prod(
guesses_simple.shape[1:])).T
guesses_simple = np.array([[peak] + g[1:].tolist() for peak, g in zip(
peaks.value.flat,
flatguesses,
)]).T.reshape((len(guesses), ) + peaks.shape)
# Can't accept guesses being wrong, and I've made too many mistakes...
assert np.all(
np.nan_to_num(g0[1:, 0, 0]) == np.nan_to_num(guesses_simple[1:, 0, 0]))
assert np.all(
np.nan_to_num(g0[1:, start_from_point[1], start_from_point[0]]) ==
np.nan_to_num(guesses_simple[1:, start_from_point[1],
start_from_point[0]]))
# Need to show pcube which pixels to ignore: m1 has nans
pcube.mapplot.plane = m1.value
pcube.fiteach(fittype='h2co_simple',
multifit=True,
guesses=guesses_simple,
limited=[(True, True)] * len(guesses_simple),
limits=limits,
multicore=8,
integral=False,
**kwargs)
#pcube.mapplot(estimator=0)
pcube_orig = pcube.parcube.copy()
pcube2 = remove_bad_pars(pcube.parcube,
pcube.errcube,
len(guesses),
min_nsig=4)
