def contour_plot(field,clevs,lats,lons,title_fontsize=20,title='',cmap='RdBu_r'):
m = make_plots.make_map_plot()
#ax.add_feature(cfeature.LAND)
cs = m.add_filled_contours(lons,lats,field,clevs,cmap=cmap)
plt.title(title,fontsize=title_fontsize)
ax.coastlines()
#ax.add_feature(cfeature.LAND)
return cs
def contour_plot(field,
clevs,
lats,
lons,
title_fontsize=35,
title='',
cmap='RdBu_r',
extent=[50, 290, -30, 60]):
plt.title(title, fontsize=title_fontsize)
m = make_plots.make_map_plot()
cs = m.add_filled_contours(lons, lats, field, clevs, cmap=cmap)
make_plots.add_lat_lon(ax)
m.geography(ax, extent=extent)
ax.set_aspect(1.5)
#ax.set_extent(extent)
return cs
def contour_plot(field,
clevs,
lats,
lons,
climatology=None,
clim_clevs=None,
lats_ua=None,
lons_ua=None,
calculate_significance=True,
title_fontsize=20,
title='',
cmap='RdBu_r',
extent=[0, 359.99, -10, 60],
plot_box=False): #[60,210,0,60]
m = make_plots.make_map_plot()
if calculate_significance == True:
pvals = t_test_autocorr(data_all, data_all[mask, :, :], autocorr=0)
field = np.mean(data_all[mask], axis=0)
cs = m.add_filled_contours(lons, lats, field, clevs, cmap=cmap)
plt.contour(lons,
lats,
pvals,
np.array([0.05]),
colors='k',
transform=ccrs.PlateCarree())
title = title + ' (' + str(data_all[mask].shape[0]) + ')'
else:
cs = m.add_filled_contours(lons, lats, field, clevs, cmap=cmap)
if climatology is not None:
plt.contour(lons_ua,
lats_ua,
climatology,
clim_clevs,
colors='0.75',
transform=ccrs.PlateCarree())
if plot_box == True:
plt.plot([70, 150], [20, 20], color='k', transform=ccrs.PlateCarree())
plt.plot([70, 150], [50, 50], color='k', transform=ccrs.PlateCarree())
plt.plot([70, 70], [20, 50], color='k', transform=ccrs.PlateCarree())
plt.plot([150, 150], [20, 50], color='k', transform=ccrs.PlateCarree())
plt.title(title, fontsize=title_fontsize)
make_plots.add_lat_lon(ax)
m.geography(ax, extent=extent)
ax.set_aspect(1.5)
return cs
def contour_plot(row,
column,
field,
clevs,
lats,
lons,
data_all,
mask,
climatology=None,
clim_clevs=None,
calculate_significance=True,
title_fontsize=35,
title='',
cmap='RdBu_r',
extent=[50, 290, -30, 60]):
ax = plt.subplot(gs[row, column],
projection=ccrs.PlateCarree(central_longitude=180.))
m = make_plots.make_map_plot()
if calculate_significance == True:
pvals = t_test_autocorr(data_all, data_all[mask, :, :], autocorr=0)
field = np.mean(data_all[mask], axis=0)
cs = m.add_filled_contours(lons, lats, field, clevs, cmap=cmap)
plt.contour(lons,
lats,
pvals,
np.array([0.05]),
colors='k',
transform=ccrs.PlateCarree())
title = title + ' (' + str(data_all[mask].shape[0]) + ')'
else:
cs = m.add_filled_contours(lons, lats, field, clevs, cmap=cmap)
if climatology is not None:
plt.contour(lons,
lats,
climatology,
clim_clevs,
colors='0.75',
transform=ccrs.PlateCarree())
plt.title(title, fontsize=title_fontsize)
make_plots.add_lat_lon(ax)
m.geography(ax, extent=extent)
ax.set_aspect(1.5)
return cs
def plot_reg(ax,
field,
lats,
lons,
clevs,
field2=None,
clevs2=None,
title='',
title_fontsize=30,
extent=[10, 220, 0, 70],
pvals=None):
""" Plot the regression patterns """
plt.title(title, fontsize=title_fontsize)
m = make_plots.make_map_plot()
cs = m.add_filled_contours(lons, lats, field, clevs)
if field2 is not None: m.add_contours(lons, lats, field2, clevs2)
make_plots.add_lat_lon(ax, fontsize=15)
m.geography(ax, extent=[30, 330, -15, 70])
#make_plots.plot_box(lon_min=110,lon_max=180,lat_min=20,lat_max=50)
ax.set_aspect(2)
return cs
def plot_mode(ax,
field1,
field2,
lats,
lons,
clevs,
clevs2,
title='',
title_fontsize=30,
extent=[10, 220, 0, 70],
pvals=None):
""" Plot the EOF patterns """
plt.title(title, fontsize=title_fontsize)
m = make_plots.make_map_plot()
cs = m.add_filled_contours(lons, lats, field1, clevs)
m.add_contours(lons, lats, field2, clevs2, contour_labels=False)
make_plots.add_lat_lon(ax)
m.geography(ax, extent=[10, 220, 0, 70])
make_plots.plot_box(lon_min=110, lon_max=180, lat_min=20, lat_max=50)
ax.set_aspect(2)
return cs