def set_colormap_of_graphics_method(
canvas, parameter_colormap, method, parameters):
if parameter_colormap is not '':
cmap = get_colormap(parameter_colormap, parameters)
if isinstance(cmap, str):
if cmap in vcs.listelements('colormap'):
method.colormap = vcs.getcolormap(cmap)
else:
method.colormap = vcs.matplotlib2vcs(cmap)
cmap_range = get_color_range(method)
else:
# cmap is of type vcs.colormap.Cp
cmap, cmap_range = cmap
method.colormap = cmap
colors = vcs.getcolors(method.levels, colors=cmap_range, white=[
100, 100, 100], split=0)
method.fillareacolors = colors
def plot_panel(n,
fig,
proj,
var,
clevels,
cmap,
title,
parameters,
stats=None):
# var_min = float(var.min())
# var_max = float(var.max())
# var_mean = cdutil.averager(var, axis='xy', weights='generate')
# var = add_cyclic(var)
var.getLongitude()
lat = var.getLatitude()
plev = var.getLevel()
var = ma.squeeze(var.asma())
# Contour levels
levels = None
norm = None
if len(clevels) > 0:
levels = [-1.0e8] + clevels + [1.0e8]
norm = colors.BoundaryNorm(boundaries=levels, ncolors=256)
# Contour plot
ax = fig.add_axes(panel[n], projection=proj)
cmap = get_colormap(cmap, parameters)
p1 = ax.contourf(
lat,
plev,
var,
# transform=ccrs.PlateCarree(),
norm=norm,
levels=levels,
cmap=cmap,
extend='both',
)
ax.set_aspect('auto')
# ax.coastlines(lw=0.3)
if title[0] is not None:
ax.set_title(title[0], loc='left', fontdict=plotSideTitle)
if title[1] is not None:
ax.set_title(title[1], fontdict=plotTitle)
if title[2] is not None:
ax.set_title(title[2], loc='right', fontdict=plotSideTitle)
# ax.set_xticks([0, 60, 120, 180, 240, 300, 359.99], crs=ccrs.PlateCarree())
# ax.set_xticks([-180, -120, -60, 0, 60, 120, 180], crs=ccrs.PlateCarree())
ax.set_xticks([-90, -60, -30, 0, 30, 60, 90]) # , crs=ccrs.PlateCarree())
ax.set_xlim(-90, 90)
# lon_formatter = LongitudeFormatter(
# zero_direction_label=True, number_format='.0f')
LatitudeFormatter()
# ax.xaxis.set_major_formatter(lon_formatter)
# ax.xaxis.set_major_formatter(lat_formatter)
ax.tick_params(labelsize=8.0, direction='out', width=1)
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')
ax.invert_yaxis()
# Color bar
cbax = fig.add_axes(
(panel[n][0] + 0.6635, panel[n][1] + 0.0215, 0.0326, 0.1792))
cbar = fig.colorbar(p1, cax=cbax)
w, h = get_ax_size(fig, cbax)
if levels is None:
cbar.ax.tick_params(labelsize=9.0, length=0)
else:
maxval = np.amax(np.absolute(levels[1:-1]))
if maxval < 10.0:
fmt = "%5.2f"
pad = 25
elif maxval < 100.0:
fmt = "%5.1f"
pad = 25
else:
fmt = "%6.1f"
pad = 30
cbar.set_ticks(levels[1:-1])
labels = [fmt % l for l in levels[1:-1]]
cbar.ax.set_yticklabels(labels, ha='right')
cbar.ax.tick_params(labelsize=9.0, pad=pad, length=0)
# Min, Mean, Max
fig.text(panel[n][0] + 0.6635,
panel[n][1] + 0.2107,
"Max\nMean\nMin",
ha='left',
fontdict=plotSideTitle)
fig.text(panel[n][0] + 0.7635,
panel[n][1] + 0.2107,
"%.2f\n%.2f\n%.2f" % stats[0:3],
ha='right',
fontdict=plotSideTitle)
# RMSE, CORR
if len(stats) == 5:
fig.text(panel[n][0] + 0.6635,
panel[n][1] - 0.0105,
"RMSE\nCORR",
ha='left',
fontdict=plotSideTitle)
fig.text(panel[n][0] + 0.7635,
panel[n][1] - 0.0105,
"%.2f\n%.2f" % stats[3:5],
ha='right',
fontdict=plotSideTitle)
def plot_panel(n, fig, _, var, clevels, cmap, title, parameters, stats=None):
# Contour levels
levels = None
norm = None
if len(clevels) > 0:
levels = [-1.0e8] + clevels + [1.0e8]
norm = colors.BoundaryNorm(boundaries=levels, ncolors=256)
# Contour plot
ax = fig.add_axes(panel[n])
var.getAxis(1)
var.getAxis(0)
cmap = get_colormap(cmap, parameters)
p1 = plt.pcolormesh(var, cmap=cmap, norm=norm)
# Calculate 3 x 3 grids for cloud fraction for nine cloud class
# Place cloud fraction of each cloud class in plot:
cld_3x3 = np.zeros((3, 3))
for j in range(3):
for i in range(3):
if var.id.find('MISR') != -1:
if j == 0:
cld_3x3[j, i] = var[0:6, 2 * i:2 * i + 2].sum()
ax.text(i * 2 + 1,
3,
'%.1f' % cld_3x3[j, i],
horizontalalignment='center',
verticalalignment='center',
fontsize=25)
elif j == 1:
cld_3x3[j, i] = var[6:9, 2 * i:2 * i + 2].sum()
ax.text(i * 2 + 1,
7.5,
'%.1f' % cld_3x3[j, i],
horizontalalignment='center',
verticalalignment='center',
fontsize=25)
elif j == 2:
cld_3x3[j, i] = var[9:, 2 * i:2 * i + 2].sum()
ax.text(i * 2 + 1,
12,
'%.1f' % cld_3x3[j, i],
horizontalalignment='center',
verticalalignment='center',
fontsize=25)
else:
if j == 2:
cld_3x3[j, i] = var[4:7, 2 * i:2 * i + 2].sum()
ax.text(i * 2 + 1,
j * 2 + 1.5,
'%.1f' % cld_3x3[j, i],
horizontalalignment='center',
verticalalignment='center',
fontsize=25)
else:
cld_3x3[j, i] = var[2 * j:2 * j + 2, 2 * i:2 * i + 2].sum()
ax.text(i * 2 + 1,
j * 2 + 1,
'%.1f' % cld_3x3[j, i],
horizontalalignment='center',
verticalalignment='center',
fontsize=25)
cld_3x3.sum()
# Place vertical/horizonal line to separate cloud class
plt.axvline(x=2, linewidth=2, color='k')
plt.axvline(x=4, linewidth=2, color='k')
if var.id.find('MISR') != -1:
plt.axhline(y=6, linewidth=2, color='k')
plt.axhline(y=9, linewidth=2, color='k')
yticks = [0, 0.5, 1, 1.5, 2, 2.5, 3, 4, 5, 7, 9, 11, 13, 15, 17, 23]
ylabels = ['%.1f' % i for i in yticks]
yticks_position = np.linspace(0, 15, 16)
plt.yticks(yticks_position, ylabels)
ax.set_ylabel('Cloud Top Height (km)')
else:
plt.axhline(y=2, linewidth=2, color='k')
plt.axhline(y=4, linewidth=2, color='k')
yticks = [1000., 800., 680., 560., 440., 310., 180., 0.]
ylabels = ['%.1f' % i for i in yticks]
ax.set_yticklabels(ylabels)
ax.set_ylabel('Cloud Top Pressure (mb)')
xticks = [0.3, 1.3, 3.6, 9.4, 23, 60, 379]
xlabels = ['%.1f' % i for i in xticks]
ax.set_xticklabels(xlabels)
ax.set_xlabel('Cloud Optical Thickness')
# xlabels = ['%.1f' %i for i in x.getBounds()[:,0]]+['%.1f' %x.getBounds()[-1,-1]]
# ylabels = ['%.1f' %i for i in y.getBounds()[:,0]]+['%.1f' %y.getBounds()[-1,-1]]
# ax.set_xticklabels(xlabels)
# ax.set_yticklabels(ylabels)
if title[0] is not None:
ax.set_title(title[0], loc='left', fontdict=plotSideTitle)
if title[1] is not None:
ax.set_title(title[1], fontdict=plotTitle)
# ax.set_title('cloud frac: %.1f'%total_cf+'%', loc='right', fontdict=plotSideTitle)
ax.set_title('%', loc='right', fontdict=plotSideTitle)
# if title[2] != None: ax.set_title(title[2], loc='right', fontdict=plotSideTitle)
# ax.set_ylabel('Cloud Top Height (km)')
# Color bar
cbax = fig.add_axes(
(panel[n][0] + 0.6635, panel[n][1] + 0.0215, 0.0326, 0.1792))
cbar = fig.colorbar(p1, cax=cbax, extend='both')
w, h = get_ax_size(fig, cbax)
if levels is None:
cbar.ax.tick_params(labelsize=9.0, length=0)
else:
cbar.set_ticks(levels[1:-1])
labels = ["%4.1f" % l for l in levels[1:-1]]
cbar.ax.set_yticklabels(labels, ha='right')
# cbar.ax.set_yticklabels(labels,ha='right')
cbar.ax.tick_params(labelsize=9.0, pad=25, length=0)
def plot_panel_map(n,
fig,
proj,
var,
clevels,
cmap,
title,
parameter,
conf=None,
stats={}):
var = add_cyclic(var)
lon = var.getLongitude()
lat = var.getLatitude()
var = ma.squeeze(var.asma())
# Contour levels
levels = None
norm = None
if len(clevels) > 0:
levels = [-1.0e8] + clevels + [1.0e8]
norm = colors.BoundaryNorm(boundaries=levels, ncolors=256)
# Contour plot
ax = fig.add_axes(panel[n], projection=proj)
region_str = parameter.regions[0]
region = regions_specs[region_str]
if "domain" in region.keys(): # type: ignore
# Get domain to plot
domain = region["domain"] # type: ignore
else:
# Assume global domain
domain = cdutil.region.domain(latitude=(-90.0, 90, "ccb"))
kargs = domain.components()[0].kargs
lon_west, lon_east, lat_south, lat_north = (0, 360, -90, 90)
if "longitude" in kargs:
lon_west, lon_east, _ = kargs["longitude"]
if "latitude" in kargs:
lat_south, lat_north, _ = kargs["latitude"]
lon_covered = lon_east - lon_west
lon_step = determine_tick_step(lon_covered)
xticks = np.arange(lon_west, lon_east, lon_step)
# Subtract 0.50 to get 0 W to show up on the right side of the plot.
# If less than 0.50 is subtracted, then 0 W will overlap 0 E on the left side of the plot.
# If a number is added, then the value won't show up at all.
xticks = np.append(xticks, lon_east - 0.50)
lat_covered = lat_north - lat_south
lat_step = determine_tick_step(lat_covered)
yticks = np.arange(lat_south, lat_north, lat_step)
yticks = np.append(yticks, lat_north)
ax.set_extent([lon_west, lon_east, lat_south, lat_north], crs=proj)
cmap = get_colormap(cmap, parameter)
contours = ax.contourf(
lon,
lat,
var,
transform=ccrs.PlateCarree(),
norm=norm,
levels=levels,
cmap=cmap,
extend="both",
)
if conf is not None:
conf = add_cyclic(conf)
conf = ma.squeeze(conf.asma())
# Values in conf will be either 0 or 1. Thus, there are only two levels -
# represented by the no-hatching and hatching levels.
ax.contourf(
lon,
lat,
conf,
2,
transform=ccrs.PlateCarree(),
norm=norm,
colors="none",
extend="both",
hatches=[None, "//"],
)
# Full world would be aspect 360/(2*180) = 1
ax.set_aspect((lon_east - lon_west) / (2 * (lat_north - lat_south)))
ax.coastlines(lw=0.3)
if title[0] is not None:
ax.set_title(title[0], loc="left", fontdict=plotSideTitle)
if title[1] is not None:
ax.set_title(title[1], fontdict=plotTitle)
if title[2] is not None:
ax.set_title(title[2], loc="right", fontdict=plotSideTitle)
ax.set_xticks(xticks, crs=ccrs.PlateCarree())
ax.set_yticks(yticks, crs=ccrs.PlateCarree())
lon_formatter = LongitudeFormatter(zero_direction_label=True,
number_format=".0f")
lat_formatter = LatitudeFormatter()
ax.xaxis.set_major_formatter(lon_formatter)
ax.yaxis.set_major_formatter(lat_formatter)
ax.tick_params(labelsize=8.0, direction="out", width=1)
ax.xaxis.set_ticks_position("bottom")
ax.yaxis.set_ticks_position("left")
# Place a vertical line in the middle of the plot - i.e. 180 degrees
ax.axvline(x=0.5, color="k", linewidth=0.5)
# Color bar
cbax = fig.add_axes(
(panel[n][0] + 0.6635, panel[n][1] + 0.0115, 0.0326, 0.1792))
cbar = fig.colorbar(contours, cax=cbax)
w, h = get_ax_size(fig, cbax)
if levels is None:
cbar.ax.tick_params(labelsize=9.0, length=0)
else:
maxval = np.amax(np.absolute(levels[1:-1]))
if maxval < 1.0:
fmt = "%5.3f"
pad = 30
elif maxval < 10.0:
fmt = "%5.2f"
pad = 25
elif maxval < 100.0:
fmt = "%5.1f"
pad = 25
else:
fmt = "%6.1f"
pad = 30
cbar.set_ticks(levels[1:-1])
labels = [fmt % level for level in levels[1:-1]]
cbar.ax.set_yticklabels(labels, ha="right")
cbar.ax.tick_params(labelsize=9.0, pad=pad, length=0)
# Display stats
if stats:
top_stats = (stats["max"], stats["min"], stats["mean"], stats["std"])
top_text = "Max\nMin\nMean\nSTD"
fig.text(
panel[n][0] + 0.6635,
panel[n][1] + 0.2107,
top_text,
ha="left",
fontdict=plotSideTitle,
)
fig.text(
panel[n][0] + 0.7635,
panel[n][1] + 0.2107,
"%.2f\n%.2f\n%.2f\n%.2f" % top_stats,
ha="right",
fontdict=plotSideTitle,
)
if "rmse" in stats.keys():
bottom_stats = (stats["rmse"], stats["corr"])
bottom_text = "RMSE\nCORR"
fig.text(
panel[n][0] + 0.6635,
panel[n][1] - 0.0205,
bottom_text,
ha="left",
fontdict=plotSideTitle,
)
fig.text(
panel[n][0] + 0.7635,
panel[n][1] - 0.0205,
"%.2f\n%.2f" % bottom_stats,
ha="right",
fontdict=plotSideTitle,
)
# Hatch text
if conf is not None:
hatch_text = "Hatched when pvalue < 0.05"
fig.text(
panel[n][0] + 0.25,
panel[n][1] - 0.0355,
hatch_text,
ha="right",
fontdict=plotSideTitle,
)
def plot_panel(n,
fig,
proj,
var,
clevels,
cmap,
title,
parameters,
stats=None):
var = add_cyclic(var)
lon = var.getLongitude()
lat = var.getLatitude()
var = ma.squeeze(var.asma())
# Contour levels
levels = None
norm = None
if len(clevels) > 0:
levels = [-1.0e8] + clevels + [1.0e8]
norm = colors.BoundaryNorm(boundaries=levels, ncolors=256)
# ax.set_global()
region_str = parameters.regions[0]
region = regions_specs[region_str]
global_domain = True
full_lon = True
if "domain" in region.keys(): # type: ignore
# Get domain to plot
domain = region["domain"] # type: ignore
global_domain = False
else:
# Assume global domain
domain = cdutil.region.domain(latitude=(-90.0, 90, "ccb"))
kargs = domain.components()[0].kargs
lon_west, lon_east, lat_south, lat_north = (0, 360, -90, 90)
if "longitude" in kargs:
full_lon = False
lon_west, lon_east, _ = kargs["longitude"]
# Note cartopy Problem with gridlines across the dateline:https://github.com/SciTools/cartopy/issues/821. Region cross dateline is not supported yet.
if lon_west > 180 and lon_east > 180:
lon_west = lon_west - 360
lon_east = lon_east - 360
if "latitude" in kargs:
lat_south, lat_north, _ = kargs["latitude"]
lon_covered = lon_east - lon_west
lon_step = determine_tick_step(lon_covered)
xticks = np.arange(lon_west, lon_east, lon_step)
# Subtract 0.50 to get 0 W to show up on the right side of the plot.
# If less than 0.50 is subtracted, then 0 W will overlap 0 E on the left side of the plot.
# If a number is added, then the value won't show up at all.
if global_domain or full_lon:
xticks = np.append(xticks, lon_east - 0.50)
proj = ccrs.PlateCarree(central_longitude=180)
else:
xticks = np.append(xticks, lon_east)
lat_covered = lat_north - lat_south
lat_step = determine_tick_step(lat_covered)
yticks = np.arange(lat_south, lat_north, lat_step)
yticks = np.append(yticks, lat_north)
# Contour plot
ax = fig.add_axes(panel[n], projection=proj)
ax.set_extent([lon_west, lon_east, lat_south, lat_north], crs=proj)
cmap = get_colormap(cmap, parameters)
p1 = ax.contourf(
lon,
lat,
var,
transform=ccrs.PlateCarree(),
norm=norm,
levels=levels,
cmap=cmap,
extend="both",
)
# ax.set_aspect('auto')
# Full world would be aspect 360/(2*180) = 1
ax.set_aspect((lon_east - lon_west) / (2 * (lat_north - lat_south)))
ax.coastlines(lw=0.3)
if not global_domain and "RRM" in region_str:
ax.coastlines(resolution="50m", color="black", linewidth=1)
state_borders = cfeature.NaturalEarthFeature(
category="cultural",
name="admin_1_states_provinces_lakes",
scale="50m",
facecolor="none",
)
ax.add_feature(state_borders, edgecolor="black")
if title[0] is not None:
ax.set_title(title[0], loc="left", fontdict=plotSideTitle)
if title[1] is not None:
ax.set_title(title[1], fontdict=plotTitle)
if title[2] is not None:
ax.set_title(title[2], loc="right", fontdict=plotSideTitle)
ax.set_xticks(xticks, crs=ccrs.PlateCarree())
ax.set_yticks(yticks, crs=ccrs.PlateCarree())
lon_formatter = LongitudeFormatter(zero_direction_label=True,
number_format=".0f")
lat_formatter = LatitudeFormatter()
ax.xaxis.set_major_formatter(lon_formatter)
ax.yaxis.set_major_formatter(lat_formatter)
ax.tick_params(labelsize=8.0, direction="out", width=1)
ax.xaxis.set_ticks_position("bottom")
ax.yaxis.set_ticks_position("left")
# Color bar
cbax = fig.add_axes(
(panel[n][0] + 0.6635, panel[n][1] + 0.0215, 0.0326, 0.1792))
cbar = fig.colorbar(p1, cax=cbax)
w, h = get_ax_size(fig, cbax)
if levels is None:
cbar.ax.tick_params(labelsize=9.0, length=0)
else:
maxval = np.amax(np.absolute(levels[1:-1]))
if maxval < 10.0:
fmt = "%5.2f"
pad = 25
elif maxval < 100.0:
fmt = "%5.1f"
pad = 25
else:
fmt = "%6.1f"
pad = 30
cbar.set_ticks(levels[1:-1])
labels = [fmt % level for level in levels[1:-1]]
cbar.ax.set_yticklabels(labels, ha="right")
cbar.ax.tick_params(labelsize=9.0, pad=pad, length=0)
# Min, Mean, Max
fig.text(
panel[n][0] + 0.6635,
panel[n][1] + 0.2107,
"Max\nMean\nMin",
ha="left",
fontdict=plotSideTitle,
)
fig.text(
panel[n][0] + 0.7635,
panel[n][1] + 0.2107,
"%.2f\n%.2f\n%.2f" % stats[0:3],
ha="right",
fontdict=plotSideTitle,
)
# RMSE, CORR
if len(stats) == 5:
fig.text(
panel[n][0] + 0.6635,
panel[n][1] - 0.0105,
"RMSE\nCORR",
ha="left",
fontdict=plotSideTitle,
)
fig.text(
panel[n][0] + 0.7635,
panel[n][1] - 0.0105,
"%.2f\n%.2f" % stats[3:5],
ha="right",
fontdict=plotSideTitle,
)
# grid resolution info:
if n == 2 and "RRM" in region_str:
dlat = lat[2] - lat[1]
dlon = lon[2] - lon[1]
fig.text(
panel[n][0] + 0.4635,
panel[n][1] - 0.04,
"Resolution: {:.2f}x{:.2f}".format(dlat, dlon),
ha="left",
fontdict=plotSideTitle,
)
def plot_panel(n,
fig,
proj,
pole,
var,
clevels,
cmap,
title,
parameters,
stats=None):
var = add_cyclic(var)
lon = var.getLongitude()
lat = var.getLatitude()
var = ma.squeeze(var.asma())
# Contour levels
levels = None
norm = None
if len(clevels) > 0:
levels = [-1.0e8] + clevels + [1.0e8]
norm = colors.BoundaryNorm(boundaries=levels, ncolors=256)
# Contour plot
ax = fig.add_axes(panel[n], projection=proj)
ax.set_global()
ax.gridlines()
if pole == 'N':
ax.set_extent([-180, 180, 50, 90], crs=ccrs.PlateCarree())
elif pole == 'S':
ax.set_extent([-180, 180, -55, -90], crs=ccrs.PlateCarree())
cmap = get_colormap(cmap, parameters)
p1 = ax.contourf(
lon,
lat,
var,
transform=ccrs.PlateCarree(),
norm=norm,
levels=levels,
cmap=cmap,
extend='both',
)
ax.set_aspect('auto')
ax.coastlines(lw=0.3)
theta = np.linspace(0, 2 * np.pi, 100)
center, radius = [0.5, 0.5], 0.5
verts = np.vstack([np.sin(theta), np.cos(theta)]).T
circle = mpath.Path(verts * radius + center)
ax.set_boundary(circle, transform=ax.transAxes)
# Plot titles
for i in range(3):
if title[i] is None:
title[i] = ''
t = ax.set_title('%s\n%s' % (title[0], title[2]),
loc='left',
fontdict=plotSideTitle)
t = ax.set_title(title[1], fontdict=plotTitle)
if title[0] != '' or title[2] != '':
t.set_position([.5, 1.06])
# Color bar
cbax = fig.add_axes(
(panel[n][0] + 0.35, panel[n][1] + 0.0354, 0.0326, 0.1792))
cbar = fig.colorbar(p1, cax=cbax)
w, h = get_ax_size(fig, cbax)
if levels is None:
cbar.ax.tick_params(labelsize=9.0, length=0)
else:
maxval = np.amax(np.absolute(levels[1:-1]))
if maxval < 10.0:
fmt = "%5.2f"
pad = 25
elif maxval < 100.0:
fmt = "%5.1f"
pad = 25
else:
fmt = "%6.1f"
pad = 30
cbar.set_ticks(levels[1:-1])
labels = [fmt % l for l in levels[1:-1]]
cbar.ax.set_yticklabels(labels, ha='right')
cbar.ax.tick_params(labelsize=9.0, pad=pad, length=0)
# Min, Mean, Max
fig.text(panel[n][0] + 0.35,
panel[n][1] + 0.225,
"Max\nMean\nMin",
ha='left',
fontdict=plotSideTitle)
fig.text(panel[n][0] + 0.45,
panel[n][1] + 0.225,
"%.2f\n%.2f\n%.2f" % stats[0:3],
ha='right',
fontdict=plotSideTitle)
# RMSE, CORR
if len(stats) == 5:
fig.text(panel[n][0] + 0.35,
panel[n][1] + 0.,
"RMSE\nCORR",
ha='left',
fontdict=plotSideTitle)
fig.text(panel[n][0] + 0.45,
panel[n][1] + 0.,
"%.2f\n%.2f" % stats[3:5],
ha='right',
fontdict=plotSideTitle)
def plot_panel(n, fig, var, clevels, cmap, title, parameters, stats=None):
mon = var.getTime()
lat = var.getLatitude()
var = np.transpose(var)
# Contour levels
levels = None
norm = None
if len(clevels) > 0:
levels = [-1.0e8] + clevels + [1.0e8]
norm = colors.BoundaryNorm(boundaries=levels, ncolors=256)
# Contour plot
ax = fig.add_axes(panel[n])
cmap = get_colormap(cmap, parameters)
p1 = ax.contourf(
mon,
lat,
var,
norm=norm,
levels=levels,
cmap=cmap,
extend="both",
)
if title[0] is not None:
ax.set_title(title[0], loc="left", fontdict=plotSideTitle)
if title[1] is not None:
ax.set_title(title[1], fontdict=plotTitle)
if title[2] is not None:
ax.set_title(title[2], loc="right", fontdict=plotSideTitle)
mon_xticks = ["J", "F", "M", "A", "M", "J", "J", "A", "S", "O", "N", "D"]
plt.xticks(mon, mon_xticks)
lat_formatter = LatitudeFormatter()
ax.yaxis.set_major_formatter(lat_formatter)
ax.tick_params(labelsize=8.0, direction="out", width=1)
ax.xaxis.set_ticks_position("bottom")
ax.yaxis.set_ticks_position("left")
# Color bar
cbax = fig.add_axes(
(panel[n][0] + 0.6635, panel[n][1] + 0.0215, 0.0326, 0.1792))
cbar = fig.colorbar(p1, cax=cbax)
w, h = get_ax_size(fig, cbax)
if levels is None:
cbar.ax.tick_params(labelsize=9.0, length=0)
else:
maxval = np.amax(np.absolute(levels[1:-1]))
if maxval < 10.0:
fmt = "%5.2f"
pad = 25
elif maxval < 100.0:
fmt = "%5.1f"
pad = 25
else:
fmt = "%6.1f"
pad = 30
cbar.set_ticks(levels[1:-1])
labels = [fmt % level for level in levels[1:-1]]
cbar.ax.set_yticklabels(labels, ha="right")
cbar.ax.tick_params(labelsize=9.0, pad=pad, length=0)
