NCL_xy_4.py

This script illustrates the following concepts:

• Drawing a scatter plot

• Changing the markers in an XY plot

• Changing the marker color in an XY plot

• Changing the marker size in an XY plot

• Creating your own markers for an XY plot

• Drawing a legend

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

• Original NCL script: https://www.ncl.ucar.edu/Applications/Scripts/xy_4.ncl

• Original NCL plots: https://www.ncl.ucar.edu/Applications/Images/xy_4_1_lg.png and https://www.ncl.ucar.edu/Applications/Images/xy_4_2_lg.png

Ways of specifying marks:

• matplotlib.markers has an extensive list of predefined markers

• Mathematical symbols described here can be used

• Unicode characters

• If you still cannot find the symbol you are looking for, a custom made Path instance can be used to draw your own marker

Import packages:

import numpy as np
import xarray as xr
import matplotlib.pyplot as plt
import matplotlib.path as mpath
import math

import geocat.datafiles as gdf
from geocat.viz import util as gvutil

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/AtmJan360_xy_4.nc'),
                     decode_times=False)

# Extract a slice of the data
ds = ds['T']
t = ds.isel(lev=0).drop('lev')
t = t.isel(lat=32).drop('lat')
t = t.isel(lon=29).drop('lon')

Plot with standard markers:

plt.figure(figsize=(8, 8))
ax = plt.axes()

plt.scatter(t.time, t.data, color='red')

# Use geocat.viz.util convenience function to set titles and labels
gvutil.set_titles_and_labels(ax,
                             maintitle="Scatter Plot",
                             xlabel=t['time'].long_name,
                             ylabel=t.long_name)

# Use geocat.viz.util convenience function to add minor and major tick lines
gvutil.add_major_minor_ticks(ax,
                             x_minor_per_major=5,
                             y_minor_per_major=4,
                             labelsize=14)

# Calculate xlim by rounding the min value down and the max value up to a
# multiple of 5
xmin = 5 * math.floor(t.time.min().data / 5)
xmax = 5 * math.ceil(t.time.max().data / 5)

gvutil.set_axes_limits_and_ticks(
    ax,
    xlim=(xmin, xmax),
    ylim=(220.0, 232.0),
    xticklabels=[' ', 131160, ' ', 131170, ' ', 131180, ' ', 131190],
    yticklabels=np.arange(220.0, 233.0, 2.0))

plt.show()

Plot with custom markers:

plt.figure(figsize=(8, 8))
ax = plt.axes()

# Divide the data into arbitrary sections so each can be drawn with a different
# type of marker
data1 = t.data[0:8]
time1 = t.time[0:8]

data2 = t.data[8:16]
time2 = t.time[8:16]

data3 = t.data[16:24]
time3 = t.time[16:24]

data4 = t.data[24:]
time4 = t.time[24:]

# marker='s' creates a square. This is from matplotlib.markers
# This is not to be confused with the kwarg `s` which sets the marker size
plt.scatter(time1, data1, color='blue', marker='s', label='matplotlib.markers')

# Use a mathematical symbol for a marker
plt.scatter(time2,
            data2,
            color='green',
            marker='$\Omega$',
            s=100,
            label='mathematical symbol')

# Unicode symbol marker
plt.scatter(time3,
            data3,
            color='black',
            marker='$\u2608$',
            s=100,
            label='unicode symbol')

# Create custom path for marker
verts = [(-0.5, -0.5), (-0.5, 0.5), (0, 0), (0.5, 0.5), (0.5, -0.5), (0, 0)]
path = mpath.Path(verts)
plt.scatter(time4, data4, color='red', marker=path, s=100, label='custom path')

# Add legend
plt.legend()

# Use geocat.viz.util convenience function to set titles and labels
gvutil.set_titles_and_labels(ax,
                             maintitle="Make your own marker",
                             xlabel=t['time'].long_name,
                             ylabel=t.long_name)

# Use geocat.viz.util convenience function to add minor and major tick lines
gvutil.add_major_minor_ticks(ax,
                             x_minor_per_major=5,
                             y_minor_per_major=4,
                             labelsize=14)

gvutil.set_axes_limits_and_ticks(
    ax,
    xlim=(xmin, xmax),
    ylim=(220.0, 232.0),
    xticklabels=[' ', 131160, ' ', 131170, ' ', 131180, ' ', 131190],
    yticklabels=np.arange(220.0, 233.0, 2.0))

plt.show()