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:

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()
Zonal Wind, Color contours mask filled land, m/s

Total running time of the script: (0 minutes 0.247 seconds)

Gallery generated by Sphinx-Gallery