def build_extinction(self):
# Add MW dust screen
self.young_av = ExtinctionDistribution()
self.young_av.set_uniform(mw_Av())
self.old_av = ExtinctionDistribution()
self.old_av.set_uniform(mw_Av())
self.rel_extinction = phat_rel_extinction()
def build_extinction(self):
"""Young and old dust at equal here."""
lewis = LewisDustLaw()
max_av = lewis.estimate_mean_extinction(self.poly)
av = np.random.uniform(low=mw_Av(), high=max_av, size=1000)
self.young_av = ExtinctionDistribution()
self.young_av.set_samples(av)
self.old_av = ExtinctionDistribution()
self.old_av.set_samples(av)
self.rel_extinction = phat_rel_extinction()
def build_extinction(self):
# NOTE includes MW extinction from __init__
self.young_av = ExtinctionDistribution()
self.young_av.set_samples(
np.random.uniform(low=self._young_av,
high=self._young_av + self._young_dav,
size=1000))
self.old_av = ExtinctionDistribution()
self.old_av.set_samples(
np.random.uniform(low=self._old_av,
high=self._old_av + self._old_dav,
size=1000))
self.rel_extinction = phat_rel_extinction()
def build_extinction(self):
"""Young and old dust at equal here."""
lewis = LewisDustLaw()
max_av = lewis.estimate_mean_extinction(self.poly)
av = np.random.uniform(low=mw_Av(),
high=max_av,
size=1000)
self.young_av = ExtinctionDistribution()
self.young_av.set_samples(av)
self.old_av = ExtinctionDistribution()
self.old_av.set_samples(av)
self.rel_extinction = phat_rel_extinction()
def build_extinction(self):
"""Young and old dust at equal here."""
# Get the coordinate of the brick
# brick_fits = phat_brick_path(self.brick, 'F814W')
# wcs = astropy.io.WCS(brick_fits[0].header)
# poly = wcs.calc_footprint()
data = PhatCatalog(self.brick) # FIXME pretty brick-specific
poly = data.polygon
lewis = LewisDustLaw()
max_av = lewis.estimate_mean_extinction(poly)
av = np.random.uniform(low=mw_Av(), high=max_av, size=1000)
self.young_av = ExtinctionDistribution()
self.young_av.set_samples(av)
self.old_av = ExtinctionDistribution()
self.old_av.set_samples(av)
self.rel_extinction = phat_rel_extinction()
def build_extinction(self):
# NOTE includes the E(V
self.young_av = ExtinctionDistribution()
if self._young_av > 0.:
av = np.random.normal(loc=self._young_av,
scale=self._young_av * self._av_sigma_ratio,
size=1000)
av[av < 0.] = 0.
self.young_av.set_samples(av + mw_Av())
else:
self.young_av.set_samples(np.zeros(1000) + mw_Av())
self.old_av = ExtinctionDistribution()
if self._old_av > 0.:
av = np.random.normal(loc=self._old_av,
scale=self._old_av * self._av_sigma_ratio,
size=1000)
av[av < 0.] = 0.
self.old_av.set_samples(av + mw_Av())
else:
self.old_av.set_samples(np.zeros(1000) + mw_Av())
self.rel_extinction = phat_rel_extinction()
def plot_isocs_lewis(plot_path, pipeline, dataset):
fig = Figure(figsize=(6.5, 5.), frameon=False)
canvas = FigureCanvas(fig)
gs = gridspec.GridSpec(2, 3,
left=0.08, right=0.85, bottom=0.08, top=0.95,
wspace=0.15, hspace=0.25,
width_ratios=(1, 1, 0.1), height_ratios=(0.1, 1.))
cax_ages = fig.add_subplot(gs[0, 0])
cax_phases = fig.add_subplot(gs[1, 2])
ax_ages = fig.add_subplot(gs[1, 0])
ax_phases = fig.add_subplot(gs[1, 1])
isoc_set = get_demo_age_grid(**dict(isoc_kind='parsec_CAF09_v1.2S',
photsys_version='yang'))
# Get extinction in F475W and F160W
Av = mw_Av()
rel_av = phat_rel_extinction()
A_475 = rel_av[2] * Av
A_814 = rel_av[3] * Av
plane_key = 'lewis'
# Plot the observed Hess diagram in each axes
for ax in [ax_ages, ax_phases]:
pipeline.plot_obs_hess(ax_ages, dataset, plane_key, imshow=None)
pipeline.plot_obs_hess(ax_phases, dataset, plane_key, imshow=None)
# Plot isochrones by age
cmap = palettable.cubehelix.perceptual_rainbow_16.mpl_colormap
scalar_map = mpl.cm.ScalarMappable(norm=mpl.colors.Normalize(vmin=7.,
vmax=10.1),
cmap=cmap)
scalar_map.set_array(np.array([isoc.age for isoc in isoc_set]))
d = Distance(785 * u.kpc)
for isoc in isoc_set:
ax_ages.plot(isoc['F475W'] + A_475 - isoc['F814W'] + A_814,
isoc['F814W'] + A_814 + d.distmod.value,
c=scalar_map.to_rgba(np.log10(isoc.age)))
cax_ages = plt.colorbar(mappable=scalar_map, cax=cax_ages, ax=ax_ages,
orientation='horizontal')
cax_ages.set_label(r"$\log(A/\mathrm{yr})$")
# Plot phases
phase_labels = {0: 'Pre-MS', 1: 'MS', 2: 'SGB', 3: 'RGB',
4: 'CHeB(1)', 5: 'CHeB(2)', 6: 'CHeB(3)',
7: 'E-AGB', 8: 'TP-AGB'}
cmap = mpl.colors.ListedColormap(
palettable.colorbrewer.qualitative.Set1_9.mpl_colors)
scalar_map = mpl.cm.ScalarMappable(norm=mpl.colors.Normalize(vmin=-0.5,
vmax=8.5),
cmap=cmap)
scalar_map.set_array(np.array(range(0, 9)))
d = Distance(785 * u.kpc)
for isoc in isoc_set:
phases = np.unique(isoc['stage'])
srt = np.argsort(phases)
phases = phases[srt]
for p in phases:
s = np.where(isoc['stage'] == p)[0]
ax_phases.plot(isoc['F475W'][s] + A_475 - isoc['F814W'][s] + A_814,
isoc['F814W'][s] + A_814 + d.distmod.value,
c=scalar_map.to_rgba(p),
lw=0.8)
cb_phases = plt.colorbar(mappable=scalar_map,
cax=cax_phases, ax=ax_phases, ticks=range(0, 9),
orientation='vertical')
# for tl in ax.get_xmajorticklabels():
# tl.set_visible(False)
# for label in cb_phases.ax.get_xmajorticklabels():
# label.set_rotation('vertical')
cb_phases.ax.set_yticklabels([phase_labels[p] for p in range(0, 9)])
cb_phases.set_label(r"Stage")
# cb_phases.update_ticks()
for ax in [ax_ages, ax_phases]:
ax.xaxis.set_major_locator(mpl.ticker.MultipleLocator(base=0.5))
for tl in ax_phases.get_ymajorticklabels():
tl.set_visible(False)
ax_phases.set_ylabel('')
gs.tight_layout(fig, pad=1.08, h_pad=None, w_pad=None, rect=None)
canvas.print_figure(plot_path + ".pdf", format="pdf")
def plot_isocs_lewis(plot_path, pipeline, dataset):
fig = Figure(figsize=(6.5, 5.), frameon=False)
canvas = FigureCanvas(fig)
gs = gridspec.GridSpec(2,
3,
left=0.08,
right=0.85,
bottom=0.08,
top=0.95,
wspace=0.15,
hspace=0.25,
width_ratios=(1, 1, 0.1),
height_ratios=(0.1, 1.))
cax_ages = fig.add_subplot(gs[0, 0])
cax_phases = fig.add_subplot(gs[1, 2])
ax_ages = fig.add_subplot(gs[1, 0])
ax_phases = fig.add_subplot(gs[1, 1])
isoc_set = get_demo_age_grid(
**dict(isoc_kind='parsec_CAF09_v1.2S', photsys_version='yang'))
# Get extinction in F475W and F160W
Av = mw_Av()
rel_av = phat_rel_extinction()
A_475 = rel_av[2] * Av
A_814 = rel_av[3] * Av
plane_key = 'lewis'
# Plot the observed Hess diagram in each axes
for ax in [ax_ages, ax_phases]:
pipeline.plot_obs_hess(ax_ages, dataset, plane_key, imshow=None)
pipeline.plot_obs_hess(ax_phases, dataset, plane_key, imshow=None)
# Plot isochrones by age
cmap = palettable.cubehelix.perceptual_rainbow_16.mpl_colormap
scalar_map = mpl.cm.ScalarMappable(norm=mpl.colors.Normalize(vmin=7.,
vmax=10.1),
cmap=cmap)
scalar_map.set_array(np.array([isoc.age for isoc in isoc_set]))
d = Distance(785 * u.kpc)
for isoc in isoc_set:
ax_ages.plot(isoc['F475W'] + A_475 - isoc['F814W'] + A_814,
isoc['F814W'] + A_814 + d.distmod.value,
c=scalar_map.to_rgba(np.log10(isoc.age)))
cax_ages = plt.colorbar(mappable=scalar_map,
cax=cax_ages,
ax=ax_ages,
orientation='horizontal')
cax_ages.set_label(r"$\log(A/\mathrm{yr})$")
# Plot phases
phase_labels = {
0: 'Pre-MS',
1: 'MS',
2: 'SGB',
3: 'RGB',
4: 'CHeB(1)',
5: 'CHeB(2)',
6: 'CHeB(3)',
7: 'E-AGB',
8: 'TP-AGB'
}
cmap = mpl.colors.ListedColormap(
palettable.colorbrewer.qualitative.Set1_9.mpl_colors)
scalar_map = mpl.cm.ScalarMappable(norm=mpl.colors.Normalize(vmin=-0.5,
vmax=8.5),
cmap=cmap)
scalar_map.set_array(np.array(range(0, 9)))
d = Distance(785 * u.kpc)
for isoc in isoc_set:
phases = np.unique(isoc['stage'])
srt = np.argsort(phases)
phases = phases[srt]
for p in phases:
s = np.where(isoc['stage'] == p)[0]
ax_phases.plot(isoc['F475W'][s] + A_475 - isoc['F814W'][s] + A_814,
isoc['F814W'][s] + A_814 + d.distmod.value,
c=scalar_map.to_rgba(p),
lw=0.8)
cb_phases = plt.colorbar(mappable=scalar_map,
cax=cax_phases,
ax=ax_phases,
ticks=range(0, 9),
orientation='vertical')
# for tl in ax.get_xmajorticklabels():
# tl.set_visible(False)
# for label in cb_phases.ax.get_xmajorticklabels():
# label.set_rotation('vertical')
cb_phases.ax.set_yticklabels([phase_labels[p] for p in range(0, 9)])
cb_phases.set_label(r"Stage")
# cb_phases.update_ticks()
for ax in [ax_ages, ax_phases]:
ax.xaxis.set_major_locator(mpl.ticker.MultipleLocator(base=0.5))
for tl in ax_phases.get_ymajorticklabels():
tl.set_visible(False)
ax_phases.set_ylabel('')
gs.tight_layout(fig, pad=1.08, h_pad=None, w_pad=None, rect=None)
canvas.print_figure(plot_path + ".pdf", format="pdf")