Comments (2)
Thanks for posting this. The issue was that your latitudes are sorted north-to-south (descending) instead of south-to-north. I should have accounted for this possibility. Commit d1193ce fixes things; try the example again.
import xarray as xr
import numpy as np
import proplot as plot
ds = xr.open_dataarray('/Users/ldavis/tmp/global_corr.nc')
f, ax = plot.subplots(proj='pcarree', basemap=0, axwidth=8, colorbar='r')
p = ax.contourf(ds.lon, ds.lat, ds, levels=plot.arange(-0.7, 0.7, 0.1), cmap='BuRd', globe=True)
f.rightpanel.colorbar(p)
ProPlot doesn't just fix longitudinal seams, it also "interpolates" to the poles, i.e. adds vectors populated with the mean of the highest/lowest-latitude coordinate data to the top and bottom of the data array (see this docs page). This isn't so important for cylindrical projections but removes an ugly "hole" in your data when using polar projections. In this example, after the fix, the coordinates looked like [-90, 89, 88, ..., -88, -89, 90]
. Which drew a contour patch extending over the whole map and covering the negative contours.
I also improved the gridfix
wrappers by making sure they respect masked arrays/do not destroy the masks.
from proplot.
Good catch! THanks.
from proplot.
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