Note
Go to the end to download the full example code
NCL_coneff_16.py#
- This script illustrates the following concepts:
Showing features of the new color display model
Using a NCL colormap with levels to assign a color palette to contours
Drawing partially transparent filled contours
- See following URLs to see the reproduced NCL plot & script:
Original NCL script: https://www.ncl.ucar.edu/Applications/Scripts/coneff_16.ncl
Original NCL plot: https://www.ncl.ucar.edu/Applications/Images/coneff_16_1_lg.png
Import packages:
import numpy as np
import xarray as xr
import cartopy.crs as ccrs
import matplotlib.pyplot as plt
import cmaps
import geocat.datafiles as gdf
import geocat.viz as gv
Read in data:
# Open a netCDF data file using xarray default engine and load the data into xarrays
ds = xr.open_dataset(gdf.get('netcdf_files/uv300.nc'))
U = ds.U[1, :, :]
Plot:
# Generate figure (set its size (width, height) in inches)
plt.figure(figsize=(14, 7))
# Generate axes, using Cartopy
projection = ccrs.PlateCarree()
ax = plt.axes(projection=projection)
# Use global map and draw coastlines
ax.set_global()
ax.coastlines()
# Import an NCL colormap
newcmp = cmaps.BlueYellowRed
# Contourf-plot data (for filled contours)
# Note, min-max contour levels are hard-coded. contourf's automatic contour value selector produces fractional values.
p = U.plot.contourf(ax=ax,
vmin=-16.0,
vmax=44,
levels=16,
cmap=newcmp,
add_colorbar=False,
transform=projection,
extend='neither')
# Add horizontal colorbar
cbar = plt.colorbar(p, orientation='horizontal', shrink=0.5)
cbar.ax.tick_params(labelsize=14)
cbar.set_ticks(np.linspace(-12, 40, 14))
# Use geocat.viz.util convenience function to set axes tick values
gv.set_axes_limits_and_ticks(ax,
xticks=np.linspace(-180, 180, 13),
yticks=np.linspace(-90, 90, 7))
# Use geocat.viz.util convenience function to make plots look like NCL plots by using latitude, longitude tick labels
gv.add_lat_lon_ticklabels(ax)
# Use geocat.viz.util convenience function to add minor and major tick lines
gv.add_major_minor_ticks(ax, labelsize=12)
# Use geocat.viz.util convenience function to add titles to left and right of the plot axis.
gv.set_titles_and_labels(ax,
maintitle="Color contours mask filled land",
lefttitle=U.long_name,
lefttitlefontsize=16,
righttitle=U.units,
righttitlefontsize=16,
xlabel="",
ylabel="")
# Show the plot
plt.show()

Total running time of the script: ( 0 minutes 0.261 seconds)