NCL_hov_3.py

This script illustrates the following concepts:

• Creating a Hovmueller plot

• Hatching fill between contours

See following URLs to see the reproduced NCL plot & script:

• Original NCL script: https://www.ncl.ucar.edu/Applications/Scripts/hov_3.ncl

• Original NCL plot: https://www.ncl.ucar.edu/Applications/Images/hov_3_lg.png

Import packages:

import numpy as np
import xarray as xr

import matplotlib.pyplot as plt

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/chi200_ud_smooth.nc'))

lon = ds.lon
times = ds.time
scale = 1000000
chi = ds.CHI
chi = chi / scale

Plot:

# Initialize figure and axis
fig, ax = plt.subplots(figsize=(7, 7.5))

# Fill area between level 4 contours and level 10 contours with dot hatching
cf = ax.contourf(lon,
                 times,
                 chi,
                 levels=[4, 12],
                 colors='None',
                 hatches=['....'])

# Make all dot-filled areas light gray so contour lines are still visible
for i, collection in enumerate(cf.collections):
    collection.set_edgecolor('lightgray')
    collection.set_linewidth(0.)

# Fill area at the lowest contour level, -6, with line hatching
cf = ax.contourf(lon,
                 times,
                 chi,
                 levels=[-7, -6],
                 colors='None',
                 hatches=['///'])

# Draw contour lines at levels [-6, -4, -2, 0, 2, 4, 6, 8, 10]
cs = ax.contour(lon,
                times,
                chi,
                levels=np.arange(-6, 12, 2),
                colors='black',
                linestyles="-",
                linewidths=.2)

# Set 0 level contour line to a thicker linewidth
# If you try to access the "levels" attribute of cs (cs.levels),
# the list of levels is: [-6, -4, -2, 0, 2, 4, 6, 8, 10]
# level 0 is at the 3rd index of that list, so those contour lines
# can be accessed at cs.collections[3]
cs.collections[3].set_linewidth(1)

# Label the contour levels -4, 0, and 4
cl = ax.clabel(cs, fmt='%d', levels=[-4, 0, 4])

# Use geocat.viz.util convenience function to set axes limits & tick values
gv.set_axes_limits_and_ticks(ax,
                             xlim=[100, 220],
                             ylim=[0, 1.55 * 1e16],
                             xticks=[135, 180],
                             yticks=np.linspace(0, 1.55 * 1e16, 7),
                             xticklabels=['135E', '180'],
                             yticklabels=np.linspace(0, 180, 7, dtype='int'))

# Use geocat.viz.util convenience function to add minor and major tick lines
gv.add_major_minor_ticks(ax,
                         x_minor_per_major=3,
                         y_minor_per_major=3,
                         labelsize=16)

# Use geocat.viz.util convenience function to add titles
gv.set_titles_and_labels(ax,
                         maintitle="Pacific Region",
                         maintitlefontsize=20,
                         lefttitle="Velocity Potential",
                         lefttitlefontsize=18,
                         righttitle="m2/s",
                         righttitlefontsize=18,
                         ylabel="elapsed time",
                         labelfontsize=18)

# Add lower text box
ax.text(1,
        -0.12,
        "CONTOUR FROM -6 TO 10 BY 2",
        horizontalalignment='right',
        transform=ax.transAxes,
        bbox=dict(boxstyle='square, pad=0.25',
                  facecolor='white',
                  edgecolor='black'))

plt.tight_layout()
plt.show()