NCL_scatter_3.py

This script illustrates the following concepts:

• Drawing a scatter plot over a map

• Choosing marker color, size, and style

• Drawing markers on a map indicating the locations of station data

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

• Original NCL script: https://www.ncl.ucar.edu/Applications/Scripts/scatter_3.ncl

• Original NCL plot: https://www.ncl.ucar.edu/Applications/Images/scatter_3_1_lg.png and https://www.ncl.ucar.edu/Applications/Images/scatter_3_2_lg.png

Import packages:

import xarray as xr
import cartopy.crs as ccrs
import cartopy.feature as cfeature
from cartopy.mpl.gridliner import LongitudeFormatter, LatitudeFormatter
import matplotlib.pyplot as plt

import geocat.viz as gv
import geocat.datafiles as gdf

Open a netCDF data file using xarray default engine and load the data into xarrays

ds = xr.open_dataset(gdf.get("netcdf_files/95031800_sao.cdf"),
                     decode_times=False)
lat = ds.lat.isel()
lon = ds.lon.isel()

Plot

def Plots(xlim, ylim, xtic, ytic, xminor, yminor, size, color):
    """Creates plot using user specified variables.

    Parameters
    ----------
    xext : 'tuple'
        Inclusive extent of projection in format (xstart, xend) with values between -180
        and 180.
    yext : 'tuple'
        Inclusive extent of projection in format (ystart, yend) with values between -90
        and 90.
    xtic : 'int'
        Step number of major x tick label instances in format of number between each tick.
        This is passed to range() as the 'step' argument.
    ytic : 'int'
        Step number of major y tick label instances in format of number between each tick.
        This is passed to range() as the 'step' argument.
    xminor : 'int'
        Exclusive number of minor ticks between each major x-axis tick mark
    yminor : 'int'
        Exclusive number of minor ticks between each major y-axis tick mark
    size : 'int'
        Size of marker being used in format of font size number.
    color : 'str'
        Matplotlib color of marker being used in format 'color'.
    """

    # Generate figure (set its size (width, height) in inches) and axes using Cartopy projection
    plt.figure(figsize=(12, 12))

    # Generate axes using Cartopy
    ax = plt.axes(projection=ccrs.PlateCarree())

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

    # Use geocat.viz.util convenience function to make plots look like NCL plots by using latitude, longitude tick labels
    gv.add_lat_lon_ticklabels(ax)

    # 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=xlim,
                                 ylim=ylim,
                                 xticks=range(-180, 180, xtic),
                                 yticks=range(-90, 90, ytic))

    # Remove the degree symbol from tick labels
    ax.yaxis.set_major_formatter(LatitudeFormatter(degree_symbol=''))
    ax.xaxis.set_major_formatter(LongitudeFormatter(degree_symbol=''))

    # Turn on continent shading
    ax.add_feature(cfeature.LAND,
                   edgecolor='lightgray',
                   facecolor='lightgray',
                   zorder=0)
    ax.add_feature(cfeature.LAKES,
                   edgecolor='white',
                   facecolor='white',
                   zorder=0)

    # Scatter-plot the location data on the map
    plt.scatter(lon, lat, s=size, c=color, marker='+', linewidth=0.5, zorder=1)

    plt.title("Locations of stations",
              loc="center",
              y=1.03,
              size=15,
              fontweight="bold")

    plt.show()


Plots((-180, 160), (-20, 90), 30, 30, 3, 3, 50, 'firebrick')
Plots((-125, -65), (21, 60), 20, 10, 4, 5, 50, 'blue')

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