NCL_conwomap_1.py

This script illustrates the following concepts:

• Drawing a simple line contour plot

• Drawing a line contour plot with multiple colors

• Increasing the thickness of contour lines

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

• Original NCL script: https://www.ncl.ucar.edu/Applications/Scripts/conwomap_1.ncl

• Original NCL plot: https://www.ncl.ucar.edu/Applications/Images/conwomap_1_2_lg.png

Import packages:

import numpy as np
import xarray as xr
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/cone.nc"))
u = ds.u.isel(time=4)

Plot Without Enhancements:

#create figure
plt.figure(figsize=(10, 10))

#create axes
ax = plt.axes()
ax.set_aspect(1.5)

#contour plot data
p = u.plot.contour(ax=ax,
                   vmin=0,
                   vmax=10,
                   levels=11,
                   add_labels=False,
                   colors="black")

#label contours
ax.clabel(p, np.arange(0, 9, 2), colors='black', fmt="%.0f")

# Use geocat.viz.util convenience function to set axes limits & tick values without calling several matplotlib functions
gv.set_axes_limits_and_ticks(ax,
                             xlim=(0, 49),
                             ylim=(0, 29),
                             xticks=np.linspace(0, 40, 5),
                             yticks=np.linspace(0, 25, 6))

# Use geocat.viz.util convenience function to add minor and major tick lines
gv.add_major_minor_ticks(ax,
                         x_minor_per_major=5,
                         y_minor_per_major=5,
                         labelsize=16)

# Use geocat.viz.util convenience function to add titles to left and right of the plot axis.
gv.set_titles_and_labels(ax,
                         lefttitle="Cone amplitude",
                         lefttitlefontsize=18,
                         righttitle="ndim",
                         righttitlefontsize=18,
                         xlabel="X",
                         ylabel="Y",
                         labelfontsize=18)

plt.show()

Plot With Enhancements:

# Make this figure the thumbnail image on the HTML page.
# sphinx_gallery_thumbnail_number = 2

#create figure
plt.figure(figsize=(10, 10))

#create axes
ax = plt.axes()
ax.set_aspect(1.5)

#import colormap
newcmp = cmaps.NCV_jet

#contour plot data
p = u.plot.contour(ax=ax,
                   vmin=0,
                   vmax=10,
                   levels=11,
                   cmap=newcmp,
                   add_labels=False,
                   linewidths=2.3)

# label contours
ax.clabel(p, np.arange(0, 9, 2), colors='black', fmt="%.0f")

# Use geocat.viz.util convenience function to set axes limits & tick values without calling several matplotlib functions
gv.set_axes_limits_and_ticks(ax,
                             xlim=(0, 49),
                             ylim=(0, 29),
                             xticks=np.linspace(0, 40, 5),
                             yticks=np.linspace(0, 25, 6))

# Use geocat.viz.util convenience function to add minor and major tick lines
gv.add_major_minor_ticks(ax,
                         x_minor_per_major=5,
                         y_minor_per_major=5,
                         labelsize=16)

# Use geocat.viz.util convenience function to add titles to left and right of the plot axis.
gv.set_titles_and_labels(ax,
                         lefttitle="Cone amplitude",
                         lefttitlefontsize=18,
                         righttitle="ndim",
                         righttitlefontsize=18,
                         xlabel="X",
                         ylabel="Y",
                         labelfontsize=18)

plt.show()