NCL_conwomap_3.py

Concepts illustrated:
  • Drawing a simple contour plot

  • Generating dummy data using “random_normal”

  • Drawing a filled polygon over area on a contour plot with missing data

  • Turning off the bottom and right borders of a contour plot

  • Changing the labels and tickmarks on a contour plot

  • Adding a complex Greek character to a contour plot

  • Moving the contour informational label into the plot

  • Forcing tickmarks and labels to be drawn on the top X axis in a contour plot

See following URLs to see the reproduced NCL plot & script:
import matplotlib.pyplot as plt

Import packages:

import numpy as np
from geocat.viz import util as gvutil

Generate random data:

xlist = np.linspace(0, 31.0, 31)
ylist = np.linspace(0, 31.0, 31)
xdata, ydata = np.meshgrid(xlist, ylist)

zdata = np.random.normal(0, 3.0, size=(31, 31))

Create figure

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

# Create axes
ax = plt.axes()

# Use geocat.viz.util convenience function to set axes limits & tick values without calling several matplotlib functions
gvutil.set_axes_limits_and_ticks(ax,
                                 xlim=(0, 30),
                                 ylim=(0, 30),
                                 xticks=None,
                                 yticks=None,
                                 xticklabels=None,
                                 yticklabels=None)

# Use geocat.viz.util to add major and minor tics
gvutil.add_major_minor_ticks(ax,
                             x_minor_per_major=5,
                             y_minor_per_major=5,
                             labelsize=18)

# Use geocat.viz.util convenience function to add titles to left and right of the plot axis.
gvutil.set_titles_and_labels(ax, ylabel="wave number", labelfontsize=24)

# Set ticks and labels only on left and top of plot
ax.xaxis.tick_top()
ax.yaxis.tick_left()

# Set color of right and bottom axes to make them invisible
ax.spines['right'].set_color('white')
ax.spines['bottom'].set_color('white')

# Create a numpy array of the length of xlist
x = np.arange(0, len(xlist))

# Plot a step function
plt.step(x, x, color='black', zorder=7)

# Plot contour data
cp = ax.contour(xdata, ydata, zdata, colors='black', linewidths=1.0)

# Label contours
ax.clabel(cp, inline=True, fontsize=10, colors='black', fmt="%.0f")

# Ignore second half of the graph
y1 = np.full(shape=len(xlist), fill_value=0, dtype=np.int)
y2 = x
ax.fill_between(x,
                y1,
                y2,
                where=y2 >= y1,
                color='white',
                step='pre',
                alpha=1.0,
                zorder=4)

# Set properties for the text boxes
props1 = dict(facecolor='white', edgecolor='white', alpha=0.5)
props2 = dict(facecolor='white', edgecolor='black', alpha=0.5)

# Place first text box
ax.text(0.70,
        0.35,
        'J(${\u03B1}$)',
        transform=ax.transAxes,
        fontsize=25,
        bbox=props1,
        zorder=5)

# Place second text box
ax.text(0.70,
        0.05,
        'CONTOUR FROM -8 TO 6 BY 1',
        transform=ax.transAxes,
        fontsize=10,
        bbox=props2,
        zorder=5)

plt.show()
NCL conwomap 3

Total running time of the script: ( 0 minutes 0.899 seconds)

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