def animate_double(ii, ax1, ax2):
i = iys[ii]
year = anni[i]
#print(year)
color = cset[i]
tam = tahiss[i] - pimean['tas']
tit = r'{} $\to$ {:+5.1f} $^\circ$C wrt PI'.format(year, tam)
fig.suptitle(tit)
proj = ccrs.PlateCarree()
ax1.clear()
ax2.clear()
map_plot1 = ctl.plot_mapc_on_ax(ax1,
costas[i, ...],
presme.lat,
presme.lon,
proj,
cmappas[0],
cbrangs[0],
draw_grid=True)
map_plot2 = ctl.plot_mapc_on_ax(ax2,
cospr[i, ...],
presme.lat,
presme.lon,
proj,
cmappas[1],
cbrangs[1],
draw_grid=True)
return
def animate_rotate(ii):
i = iys[ii]
clon = clons[ii]
proj = ctl.def_projection('nearside', (clat, clon), bounding_lat=blat)
fig.clear()
ax = plt.subplot(projection=proj)
ax.set_global()
ax.coastlines(linewidth=1)
pc = ccrs.PlateCarree()
map_plot = ctl.plot_mapc_on_ax(ax,
cosoanom[i, ...],
presme.lat,
presme.lon,
pc,
cmappa,
cbar_range,
draw_grid=True)
year = anni[i]
#print(year)
color = cset[i]
tam = tahiss[i] - pimean['tas']
ax.set_title(r'{} $\to$ {:+5.1f} $^\circ$C wrt PI'.format(year, tam))
## Colorbar
cax = plt.axes([0.1, 0.11, 0.8, 0.05]) #horizontal
cb = plt.colorbar(map_plot, cax=cax,
orientation='horizontal') #, labelsize=18)
cb.ax.tick_params(labelsize=14)
if var == 'tas':
cb.set_label('Temperature anomaly wrt 1960-1990 (K)', fontsize=14)
elif var == 'pr':
cb.set_label('Precipitation anomaly wrt 1960-1990 (mm/yr)',
fontsize=14)
top = 0.88 # the top of the subplots
bottom = 0.20 # the bottom of the subplots
left = 0.02 # the left side
right = 0.98 # the right side
hspace = 0.20 # height reserved for white space
wspace = 0.05 # width reserved for blank space
plt.subplots_adjust(left=left,
bottom=bottom,
right=right,
top=top,
wspace=wspace,
hspace=hspace)
return
def animate(i):
proj = ccrs.PlateCarree()
#proj = ccrs.Orthographic(central_longitude=lonstep*i, central_latitude=30.)
ax = plt.subplot(projection=proj)
ax.clear()
map_plot = ctl.plot_mapc_on_ax(ax, yearly_anom[i], lat, lon, proj, cmappa,
cbar_range)
year = anni[i]
color = cset[i]
tit.set_text('{}'.format(year))
#showdate.set_text('{}'.format(year))#, color = color)
#showdate.update(color = color)
ax.relim()
ax.autoscale_view()
return
def animate(ii, ax, plot_margins=None):
i = iys[ii]
proj = ccrs.PlateCarree()
ax.clear()
map_plot = ctl.plot_mapc_on_ax(ax,
cosoanom[i, ...],
presme.lat,
presme.lon,
proj,
cmappa,
cbar_range,
draw_grid=True,
plot_margins=plot_margins)
year = anni[i]
#print(year)
color = cset[i]
tam = tahiss[i] - pimean['tas']
ax.set_title(r'{} $\to$ {:+5.1f} $^\circ$C wrt PI'.format(year, tam))
return
cosdue[var] = cosoanom
#####
print('flat global {} {}'.format(var, ssp))
fig, ax = ctl.get_cartopy_fig_ax(visualization='standard',
central_lat_lon=(0, 0),
bounding_lat=None,
figsize=(16, 9),
coast_lw=1)
#tit = plt.title('1850')
# Plotting figure
proj = ccrs.PlateCarree()
map_plot = ctl.plot_mapc_on_ax(ax, cosoanom[0], presme.lat, presme.lon,
proj, cmappa, cbar_range)
cax = plt.axes([0.1, 0.11, 0.8, 0.05]) #horizontal
cb = plt.colorbar(map_plot, cax=cax,
orientation='horizontal') #, labelsize=18)
cb.ax.tick_params(labelsize=14)
if var == 'tas':
cb.set_label('Temperature anomaly wrt 1960-1990 (K)', fontsize=14)
elif var == 'pr':
#cb.set_label('Relative precipitation anomaly wrt 1960-1990 (mm/yr)', fontsize=14)
cb.set_label('Precipitation anomaly wrt 1960-1990 (mm/yr)',
fontsize=14)
top = 0.88 # the top of the subplots
bottom = 0.20 # the bottom of the subplots
left = 0.02 # the left side
ax = plt.subplot(projection=proj)
ax.clear()
map_plot = ctl.plot_mapc_on_ax(ax, yearly_anom[i], lat, lon, proj, cmappa,
cbar_range)
year = anni[i]
color = cset[i]
tit.set_text('{}'.format(year))
#showdate.set_text('{}'.format(year))#, color = color)
#showdate.update(color = color)
ax.relim()
ax.autoscale_view()
return
# Plotting figure
map_plot = ctl.plot_mapc_on_ax(ax, yearly_anom[0], lat, lon, proj, cmappa,
cbar_range)
cax = plt.axes([0.1, 0.11, 0.8, 0.05]) #horizontal
cb = plt.colorbar(map_plot, cax=cax,
orientation='horizontal') #, labelsize=18)
cb.ax.tick_params(labelsize=14)
cb.set_label('Temp anomaly (K)', fontsize=16)
top = 0.88 # the top of the subplots
bottom = 0.20 # the bottom of the subplots
left = 0.02 # the left side
right = 0.98 # the right side
hspace = 0.20 # height reserved for white space
wspace = 0.05 # width reserved for blank space
plt.subplots_adjust(left=left,
bottom=bottom,
coso.values[~np.isnan(coso)] = 1
coso.values[np.isnan(coso)] = 0
monreg[(ru, iiy)] = coso
#### Figurez
# only stab
fig, ax = ctl.get_cartopy_fig_ax(coast_lw=0.1)
proj = ccrs.PlateCarree()
for ru, col in zip(allru, colors):
coso = monreg[(ru, 'stab')]
ctl.plot_mapc_on_ax(ax,
coso.values,
coso.lat.values,
coso.lon.values,
proj,
None, (0, 1),
plot_type='binary_contour',
lw_contour=2.,
line_color=col)
ctl.custom_legend(fig, colors, allru, ncol=4)
fig.savefig(cart_out + 'monsoon_stab.pdf')
cosi = [mpi[(ru, 'stab')] for ru in allru]
for co in cosi:
co.values[co < 0.5] = np.nan
ctl.plot_multimap_contour(cosi,
filename=cart_out + 'monsoon_all.pdf',
cbar_range=(0.5, 1.),
# Shade from the northwest, with the sun 45 degrees from horizontal
ls = LightSource(azdeg=315, altdeg=45)
hillsh = ls.hillshade(elev, vert_exag=100, dx=10000, dy=10000)
ax.pcolormesh(lon,
lat,
hillsh,
cmap='gray',
transform=ccrs.PlateCarree(),
alpha=1.0)
map = ctl.plot_mapc_on_ax(ax,
elev,
lat,
lon,
proj,
cmappa,
cbar_range,
clevels=clevels,
draw_grid=True,
alphamap=0.7)
#cb = plt.colorbar(map, orientation='horizontal')
# #### N/S Polar
proj = ctl.def_projection('nearside', (88, 0), bounding_lat=0)
fig2 = plt.figure(figsize=(32, 24))
ax2 = plt.subplot(projection=proj)
ax2.set_global()
ax2.coastlines(linewidth=2)
ax2.pcolormesh(lon,
lat,
#mod_anoms, varmean, varstd = all_res[var]
stpl_mask = dict()
for ke in varanom:
stpl_mask[ke] = np.zeros(varanom[ke].shape)
oksig = abs(varanom[ke]) > 2*varstd[ke]
stpl_mask[ke][oksig] = 1
oksig = abs(varanom[ke]) < varstd[ke]
stpl_mask[ke][oksig] = -1
fig = plt.figure(figsize = (16, 12))
seas = 'JJA'
ax = fig.add_subplot(221, projection = proj)
data = varanom[seas]
map_plot = ctl.plot_mapc_on_ax(ax, data, lat, lon, proj, cmappa, cbar_ranges[var], n_color_levels = len(paletta[var])-1, add_hatching = stpl_mask[seas], hatch_styles = ['///', '', '...'], hatch_levels = [-1.5, -0.5, 0.5, 1.5], colors = paletta[var], clevels = clevels[var])
ax.set_title(r'$\Delta$ Temperature {}'.format(seas))
ax = fig.add_subplot(222, projection = proj)
data = varstd[seas]
map_plot = ctl.plot_mapc_on_ax(ax, data, lat, lon, proj, cmappa, cbar_ranges[var], n_color_levels = len(paletta[var])-1, colors = paletta[var], clevels = clevels[var])
ax.set_title(r'$\sigma$ Temperature {}'.format(seas))
seas = 'DJF'
ax = fig.add_subplot(223, projection = proj)
data = varanom[seas]
map_plot = ctl.plot_mapc_on_ax(ax, data, lat, lon, proj, cmappa, cbar_ranges[var], n_color_levels = len(paletta[var])-1, add_hatching = stpl_mask[seas], colors = paletta[var], hatch_styles = ['///', '', '...'], hatch_levels = [-1.5, -0.5, 0.5, 1.5], clevels = clevels[var])
ax.set_title(r'$\Delta$ Temperature {}'.format(seas))
ax = fig.add_subplot(224, projection = proj)
data = varstd[seas]
