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
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/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
gv.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
gv.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)

gv.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
gv.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
gv.add_major_minor_ticks(ax,
                         x_minor_per_major=5,
                         y_minor_per_major=4,
                         labelsize=14)

gv.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()