def f(x, pos):
return aq.to_datetime(x).strftime('%d/%m\n%H:%M')
def plot_profile(plot_type,
d,
cax=None,
subcolumn=0,
sigma=5,
remove_bmol=True,
vlim=None,
vlog=None,
zres=50,
zlim=None,
**opts):
if plot_type == 'backscatter':
cmap = copy.copy(mpl.cm.get_cmap('viridis'))
under = '#222222'
label = 'Att. vol. backscattering coef. (×10$^{-6}$ m$^{-1}$sr$^{-1}$)'
if vlim is None:
vlim = [0.1, 200]
if vlog is None:
vlog = True
if len(d['backscatter'].shape) == 3:
b = d['backscatter'][:, :, subcolumn]
cloud_mask = d['cloud_mask'][:, :, subcolumn]
bsd = d['backscatter_sd'][:,:,subcolumn] if 'backscatter_sd' in d \
else np.zeros(b.shape, dtype=np.float64)
else:
b = d['backscatter']
cloud_mask = d['cloud_mask']
bsd = d['backscatter_sd'] if 'backscatter_sd' in d \
else np.zeros(b.shape, dtype=np.float64)
if sigma > 0:
b -= sigma * bsd
if remove_bmol and 'backscatter_mol' in d:
bmol = d['backscatter_mol']
mask = ~np.isnan(bmol)
b[mask] -= bmol[mask]
x = b * 1e6
x[x <= 0.] = 0.5 * vlim[0] # A value below the limit.
time = d['time']
zfull = d['zfull']
elif plot_type in ('clw', 'cli', 'cl'):
cmap = copy.copy(
mpl.cm.get_cmap({
'clw': 'Reds',
'cli': 'Blues',
'cl': 'Greys_r',
}[plot_type]))
under = {
'clw': 'white',
'cli': 'white',
'cl': 'k',
}[plot_type]
label = {
'clw': 'Cloud water (g/kg)',
'cli': 'Cloud ice (g/kg)',
'cl': 'Cloud fraction (%)',
}[plot_type]
if vlim is None:
vlim = {
'clw': [1e-3, 1],
'cli': [1e-3, 1],
'cl': [0, 100],
}[plot_type]
if vlog is None:
vlog = {'clw': True, 'cli': True, 'cl': False}[plot_type]
x = d[plot_type]
if plot_type in ('clw', 'cli', 'clw+cli'):
x *= 1e3
if x.shape == 3:
x = x[:, :, subcolumn]
if zlim is None:
zlim = [np.min(d['zfull']), np.max(d['zfull'])]
zhalf = np.arange(zlim[0], zlim[1] + zres, zres)
zfull = 0.5 * (zhalf[1:] + zhalf[:-1])
xp = np.full((x.shape[0], len(zfull)), np.nan, np.float64)
for i in range(xp.shape[0]):
zhalfi = misc.half(d['zfull'][i, :])
xp[i, :] = algorithms.interp(zhalfi, x[i, :], zhalf)
x = xp
time = d['time']
else:
raise ValueError('Invalid plot type "%s"' % plot_type)
if vlog:
norm = LogNorm(vlim[0], vlim[1])
else:
norm = Normalize(vlim[0], vlim[1])
t1 = time[0] - 0.5 * (time[1] - time[0])
t2 = time[-1] + 0.5 * (time[-1] - time[-2])
z1 = zfull[0] - 0.5 * (zfull[1] - zfull[0])
z2 = zfull[-1] + 0.5 * (zfull[-1] - zfull[-2])
im = plt.imshow(
x.T,
extent=(t1, t2, z1 * 1e-3, z2 * 1e-3),
aspect='auto',
origin='lower',
norm=norm,
cmap=cmap,
)
im.cmap.set_under(under)
cb = plt.colorbar(
cax=cax,
label=label,
pad=0.03,
fraction=0.05,
aspect='auto',
extend='both',
)
if zlim is not None:
plt.ylim(zlim[0] * 1e-3, zlim[1] * 1e-3)
plt.xlabel('Time (UTC)')
plt.ylabel('Height (km)')
formatter = plt.FuncFormatter(lambda t, p: \
aq.to_datetime(t).strftime('%d/%m\n%H:%M'))
locator = AutoDateLocator()
plt.gca().xaxis.set_major_formatter(formatter)
plt.gca().xaxis.set_major_locator(locator)
if plot_type == 'backscatter' and opts.get('cloud_mask'):
cf = plt.contour(
d['time'],
d['zfull'] * 1e-3,
cloud_mask.T,
colors='red',
linewidths=1,
linestyles='dashed',
levels=[-1., 0.5, 2.],
)
plot_legend(handles=[
mlines.Line2D([], [],
color='red',
linestyle='dashed',
label='Cloud mask')
],
theme='dark')
if 'altitude' in d:
plt.plot(d['time'], d['altitude'] * 1e-3, color='red', lw=0.5)
def formatter_f(t, pos):
return aq.to_datetime(t).strftime('%d/%m\n%H:%M')