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Improve global map plots by using Robinson projection and add coastlines #112

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26 changes: 13 additions & 13 deletions ww3tools/pvalstats.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1679,6 +1679,7 @@ def plot_global_like_global_plot(
def _grid_pandas(lat, lon, model_1d, obs_1d, dlat, dlon, min_count):
import pandas as _pd
import numpy as _np
import cartopy.crs as ccrs

df = _pd.DataFrame({
"latitude": _np.asarray(lat, dtype=float),
Expand Down Expand Up @@ -1811,44 +1812,43 @@ def _grid_pandas(lat, lon, model_1d, obs_1d, dlat, dlon, min_count):
cmap = "RdBu_r"
if cbar_label is None:
cbar_label = "Bias (model − obs)"
extendvarset="both"
elif metric == "rmse":
vmin, vmax2 = 0.0, float(vmax)
if cmap is None:
cmap = "jet"
cmap = "viridis"
if cbar_label is None:
cbar_label = "RMSE"
extendvarset="max"
else:
vmin = 0.0
vmax2 = float(vmax) if vmax is not None else float(np.nanmax(field))
if cmap is None:
cmap = "viridis"
cmap = "jet"
if cbar_label is None:
cbar_label = "Number of samples"
extendvarset="neither"

fig = plt.figure(figsize=figsize, dpi=dpi)
ax = plt.gca()
ax = plt.axes(projection=ccrs.Robinson()) # create map axes using Robinson projection

pcm = ax.pcolormesh(
LONe, LATe, field,
shading="auto",
cmap=cmap,
vmin=vmin,
vmax=vmax2,
transform=ccrs.PlateCarree() # data are in standard lon/lat coordinates; Cartopy will transform them to the map projection
)
ax.set_global() # Use full global extent for Robinson
ax.gridlines(draw_labels=False, alpha=0)
ax.coastlines()

cb = plt.colorbar(pcm, ax=ax, orientation="vertical")
cb = plt.colorbar(pcm, ax=ax, orientation="vertical", extend=extendvarset)
cb.set_label(cbar_label)

if title:
ax.set_title(title)

ax.set_xlabel("Longitude")
ax.set_ylabel("Latitude")
if lon_0_360:
ax.set_xlim(0, 360)
ax.set_ylim(latmin, latmax)

ax.grid(False)
ax.set_title(title, pad=20, y=1.02)

if outfile is not None:
outdir = os.path.dirname(outfile)
Expand Down