def set_vars(data, plottype=None, lonin=[-1.,361.], thresh=0.):
# Load up variables to plot, depending on plot type
edge_loc, psi_max, psi_max_loc = get_edge_psi(data, thresh=thresh, lev=lev, lonin=lonin, nh=True, sanity_check=True)
if plottype == 'mse':
data_mse = peak_mse(data, lonin=lonin)
vars_out = (data_mse.mse_max_loc, psi_max)
elif plottype == 'pcent':
data = precip_centroid(data,lonin=lonin)
vars_out = (data.p_cent, psi_max)
elif plottype == None:
vars_out = (edge_loc, psi_max)
return vars_out
def set_vars(data, type=None, lonin=[-1., 361.], thresh=0.):
edge_loc, psi_max, psi_max_loc = get_edge_psi(data,
thresh=thresh,
lev=lev,
lonin=lonin)
if type == 'mse':
data_mse = peak_mse(data, lonin=lonin)
vars_out = (data_mse.mse_max_loc, psi_max)
elif type == 'pcent':
data = precip_centroid(data, lonin=lonin)
vars_out = (data.p_cent, psi_max)
elif type == None:
vars_out = (edge_loc, psi_max)
return vars_out
def precip_mse_plot(data,
ax_in,
lonin=[-1., 361.],
do_xlabels=False,
plot_type=None,
precip_contour=8.,
p_cent=True,
mse_max=True,
month_labels=True,
lat_bound=45.):
lons = pick_lons(data, lonin)
try:
precip_plot = (data.precipitation * 86400.).sel(lon=lons).mean('lon')
except:
precip_plot = ((data.convection_rain + data.condensation_rain) *
86400.).sel(lon=lons).mean('lon')
mse_plot = (data.temp * cp + data.sphum * L +
data.height * g).mean('lon') / 1000.
if plot_type == None:
# Default case, plot precip with mse overlaid. Choice of whether or not to highlight a specific precip contour
f1 = precip_plot.plot.contourf(ax=ax_in,
x='xofyear',
y='lat',
levels=np.arange(2., 15., 2.),
add_colorbar=False,
add_labels=False,
extend='max',
cmap='Blues')
if not precip_contour == None:
precip_plot.plot.contour(ax=ax_in,
x='xofyear',
y='lat',
levels=np.arange(precip_contour - 100.,
200., 100.),
add_labels=False,
add_colorbar=False,
colors='k',
linewidth=2)
cs = mse_plot.sel(pfull=850.).plot.contour(ax=ax_in,
x='xofyear',
y='lat',
levels=np.arange(
200., 401., 10.),
add_labels=False,
colors='0.7',
add_colorbar=False,
linewidths=2)
plt.clabel(cs, fontsize=15, inline_spacing=-1, fmt='%1.0f')
if p_cent:
data = precip_centroid(data, lonin=lonin, lat_bound=lat_bound)
data.p_cent.plot.line(color='w', ax=ax_in)
ax_in.set_xlabel('')
elif plot_type == 'precip':
# No mse, plot precip and precip centroid
f1 = precip_plot.plot.contourf(ax=ax_in,
x='xofyear',
y='lat',
levels=np.arange(3., 16., 3.),
add_colorbar=False,
add_labels=False,
extend='max',
cmap='Blues',
linewidth=2)
if p_cent:
data = precip_centroid(data, lonin=lonin, lat_bound=lat_bound)
data.p_cent.plot.line(color='k', ax=ax_in, linewidth=2)
ax_in.set_xlabel('')
elif plot_type == 'mse':
# Plot mse in colour, overplot max mse
f1 = mse_plot.sel(pfull=850.).plot.contourf(ax=ax_in,
x='xofyear',
y='lat',
levels=np.arange(
200., 401., 10.),
add_labels=False,
extend='both',
add_colorbar=False)
if mse_max:
data_mse = peak_mse(data, lonin=lonin)
data_mse.mse_max_loc.plot.line('k', ax=ax_in)
ax_in.set_xlabel('')
ax_in.set_ylabel('Latitude')
ax_in.set_ylim(-60, 60)
ax_in.set_yticks(np.arange(-60., 61., 30.))
ax_in.grid(True, linestyle=':')
if month_labels:
mn_dic = month_dic(1)
tickspace = range(13, 72, 18)
labels = [mn_dic[(k + 5) / 6] for k in tickspace]
ax_in.set_xlim((1, 72))
ax_in.set_xticks(tickspace)
if do_xlabels:
ax_in.set_xlabel('')
ax_in.set_xticklabels(labels, rotation=25)
return f1