def map_lakepct(var,
lon,
lat,
levels,
title_str,
clrmap,
fig_name,
alone=True,
ax=False):
# figure creation
if alone:
fig, ax = plt.subplots(1,
1,
figsize=(13, 8),
subplot_kw={'projection': ccrs.PlateCarree()})
ax.add_feature(ctp.feature.OCEAN, color='gainsboro')
ax.coastlines(color='darkgrey')
#ax.coastlines(color="grey")
LON, LAT = mpu.infer_interval_breaks(lon, lat)
# add the data to the map (more info on colormaps: https://matplotlib.org/users/colormaps.html)
cmap, norm = mpu.from_levels_and_cmap(levels, clrmap)
# do not show zeros
var[var == 0] = np.nan
cmap.set_over(cmap(0.99))
h = ax.pcolormesh(LON, LAT, var, cmap=cmap, norm=norm)
# set the extent of the cartopy geoAxes to "global"
ax.set_global()
ax.set_title(title_str, pad=10, loc='right')
# remove the frame
ax.outline_patch.set_visible(False)
# plot the colorbar
cbar = mpu.colorbar(h, ax, orientation='horizontal', pad=0.1, extend='max')
cbar.ax.set_xlabel('Natural lake area fraction [%]', size=16)
cbar.set_ticks(np.arange(0, 110, 10)) # horizontal colorbar
#cbar.ax.set_xticklabels(['Low', 'Medium', 'High']) # horizontal colorbar
# if so, save the figure
if fig_name != 0 and alone:
plt.savefig(fig_name + '.jpeg', dpi=1000, bbox_inches='tight')
def plot_region_hc_map(var, region_props, lakes_path, indir_lakedata):
# get region specific info from dictionary
extent = region_props['extent']
continent_extent = region_props['continent_extent']
name = region_props['name']
name_str = region_props['name_str']
ax_location = region_props['ax_location']
levels = region_props['levels']
fig_size = region_props['fig_size']
cb_orientation = region_props['cb_orientation']
path_lakes = lakes_path + name + '.shp'
# settings
clb_label = 'Joule'
title_str = name_str + ' heat content anomaly'
fig_name = 'Heat_content_' + name
cmap = 'YlOrBr'
cmap, norm = mpu.from_levels_and_cmap(levels, cmap, extend='max')
lon, lat = get_lonlat(indir_lakedata)
LON, LAT = mpu.infer_interval_breaks(lon, lat)
lakes = gpd.read_file(path_lakes)
# plotting
fig, ax = plt.subplots(1,
1,
figsize=fig_size,
subplot_kw={'projection': ccrs.PlateCarree()})
ax.add_feature(ctp.feature.OCEAN, color='gainsboro')
ax.coastlines(color="grey")
# add the data to the map (more info on colormaps: https://matplotlib.org/users/colormaps.html)
h = ax.pcolormesh(LON, LAT, var, cmap=cmap, norm=norm)
# load the lake shapefile
lakes.plot(ax=ax, edgecolor='gray', facecolor='none')
# set grid lines
gl = ax.gridlines(crs=ccrs.PlateCarree(),
draw_labels=True,
linewidth=0.5,
color='gainsboro',
alpha=0.5)
gl.xlines = True
gl.xformatter = LONGITUDE_FORMATTER
gl.yformatter = LATITUDE_FORMATTER
gl.xlabels_bottom = None
gl.ylabels_right = None
# set extent (in right way)
extent[1], extent[2] = extent[2], extent[1]
ax.set_extent(extent)
# create effect for map borders:
effect = Stroke(linewidth=1.5, foreground='darkgray')
# set effect for main ax
ax.outline_patch.set_path_effects([effect])
# Create an inset GeoAxes showing the location of the lakes region
#x0 y0 width height
sub_ax = fig.add_axes(ax_location, projection=ccrs.PlateCarree())
sub_ax.set_extent(continent_extent)
#lakes.plot(ax=sub_ax)
sub_ax.outline_patch.set_path_effects([effect])
extent_box = sgeom.box(extent[0], extent[2], extent[1], extent[3])
sub_ax.add_geometries([extent_box],
ccrs.PlateCarree(),
facecolor='none',
edgecolor='red',
linewidth=2)
# Add the land, coastlines and the extent of the inset axis
sub_ax.add_feature(cfeature.LAND, edgecolor='gray')
sub_ax.coastlines(color='gray')
extent_box = sgeom.box(extent[0], extent[2], extent[1], extent[3])
sub_ax.add_geometries([extent_box],
ccrs.PlateCarree(),
facecolor='none',
edgecolor='black',
linewidth=2)
# plot the colorbar
cbar = mpu.colorbar(h,
ax,
extend='max',
orientation=cb_orientation,
pad=0.05)
if cb_orientation == 'vertical':
cbar.ax.set_ylabel(clb_label, size=16)
elif cb_orientation == 'horizontal':
cbar.ax.set_xlabel(clb_label, size=16)
#ax.set_title(title_str, pad=10)
plotdir = '/home/inne/documents/phd/data/processed/isimip_lakeheat/plots/'
plt.savefig(plotdir + fig_name + '.png', dpi=500)
def plot_global_hc_map(name_str, var, lakes_path, indir_lakedata):
# get region specific info from dictionary
if name_str == 'global_absolute':
levels = np.arange(-1e17, 1.1e17, 0.1e17)
elif name_str == 'global':
levels = np.arange(-1e19, 1.1e19, 0.1e19)
cb_orientation = 'horizontal'
path_lakes = lakes_path + name_str + '.shp'
# settings
clb_label = 'Joule'
title_str = name_str + ' heat content anomaly'
fig_name = 'Heat_content_' + name_str
cmap = 'RdBu_r' #, 'YlOrBr'
cmap, norm = mpu.from_levels_and_cmap(levels, cmap, extend='max')
lon, lat = get_lonlat(indir_lakedata)
LON, LAT = mpu.infer_interval_breaks(lon, lat)
# plotting
fig, ax = plt.subplots(1,
1,
figsize=(13, 8),
subplot_kw={'projection': ccrs.PlateCarree()})
ax.add_feature(ctp.feature.OCEAN, color='gainsboro')
ax.coastlines(color="grey")
# add the data to the map (more info on colormaps: https://matplotlib.org/users/colormaps.html)
h = ax.pcolormesh(LON, LAT, var, cmap=cmap, norm=norm)
# set grid lines
gl = ax.gridlines(crs=ccrs.PlateCarree(),
draw_labels=True,
linewidth=0.5,
color='gainsboro',
alpha=0.5)
gl.xlines = True
gl.xformatter = LONGITUDE_FORMATTER
gl.yformatter = LATITUDE_FORMATTER
gl.xlabels_bottom = None
gl.ylabels_right = None
effect = Stroke(linewidth=1.5, foreground='darkgray')
# set effect for main ax
ax.outline_patch.set_path_effects([effect])
# plot the colorbar
cbar = mpu.colorbar(h,
ax,
extend='max',
orientation=cb_orientation,
pad=0.05)
if cb_orientation == 'vertical':
cbar.ax.set_ylabel(clb_label, size=16)
elif cb_orientation == 'horizontal':
cbar.ax.set_xlabel(clb_label, size=16)
#ax.set_title(title_str, pad=10)
plotdir = '/home/inne/documents/phd/data/processed/isimip_lakeheat/plots/'
plt.savefig(plotdir + fig_name + '.png')