Merge pull request #49 from mnlevy1981/station_2

Station 2

Plots/Station/README.rst

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+.. _station_examples:
+
+.. _station-examples-index:
+
+Station Examples
+================

Plots/Station/station_2.py

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+"""
+station_2
+=========
+
+Plot random data on US, colored according to value
+
+https://www.ncl.ucar.edu/Applications/Scripts/station_2.ncl
+"""
+###################################################
+# Import necessary packages
+import numpy as np
+import matplotlib as mpl
+from matplotlib import pyplot as plt
+import matplotlib.ticker as tic
+import geocat.viz as gcv
+import cartopy
+import cartopy.crs as ccrs
+
+###################################################
+# Define random datasets
+
+# Set up random values
+npts = 100
+np.random.seed(20200127)
+# lat between 25 N and 50 N, lon between 125 W and 70 W
+lat = np.random.uniform(25, 50, npts)
+lon = np.random.uniform(235, 290, npts)-360
+dummy_data = np.random.uniform(-1.2, 35, npts)
+
+###################################################
+# Define colormap for plotting
+
+# Set up colormap:
+# Need to define boundaries for each color map
+# as well as colors for each bin
+
+# Note that len(colors) = len(bin_bounds) + 1
+# color[0] => dummy_data < bin_bounds[0]
+# color[-1] => dummy_data => bin_bounds[-1]
+# color[j] => bin_bounds[j-1] <= dummy_data < bin_bounds[j]
+
+bin_bounds = [0.,5.,10.,15.,20.,23.,26.]
+colors = ['purple', 'darkblue', 'blue', 'lightblue', 'yellow', 'orange', 'red', 'pink']
+
+nbins = len(colors) # One bin for each color
+
+# Define colormap for plotting based on these colors
+cmap = mpl.colors.ListedColormap(colors)
+
+###################################################
+# Both plots rely on same base figure, so
+# make a function to create desired plot
+# with no legend or colorbar
+
+# Set up figure without colorbar or legend
+def make_shared_plot(figsize):
+    fig, ax = plt.subplots(figsize=figsize)
+    ax = plt.axes(projection=ccrs.PlateCarree())
+    gcv.util.nclize_axis(ax, minor_per_major=5)
+    ax.xaxis.set_minor_locator(tic.AutoMinorLocator(n=4))
+    gcv.util.add_lat_lon_ticklabels(ax)
+
+    # Set major and minor ticks
+    plt.xlim([-125,-70])
+    plt.ylim([25,50])
+    plt.xticks(range(-120, -75, 20))
+    plt.yticks(range(30, 51, 10))
+
+    # Turn on continent shading
+    ax.add_feature(cartopy.feature.LAND, edgecolor='lightgray', facecolor='lightgray', zorder=0)
+    ax.add_feature(cartopy.feature.LAKES, edgecolor='white', facecolor='white', zorder=0)
+
+    scatter = plt.scatter(lon, lat, c=dummy_data, cmap=cmap, zorder=1)
+    return scatter, ax
+
+###################################################
+# Make station_2_1 plot
+
+scatter1, ax = make_shared_plot(figsize=(10,5.5))
+
+# add legend
+def legend_func(x):
+    """
+        Returns appropriate legend label
+    """
+    print(x.shape)
+    return()
+
+plt.suptitle('Dummy station data colored according to range of values', y=.9)
+
+# Given how we generated the plot, adding a legend is a little kludgy
+# Basically, we draw a second plot where no data is in frame
+# but the legend for that plot is drawn where we want it
+lax = plt.axes((0, 0, 1, 0.1), frameon=False)
+# Plotting window is [0,1] x [0,1]
+plt.xlim(0,1)
+plt.ylim(0,1)
+plt.axis('off')
+for n, color in enumerate(colors):
+    if n == 0:
+        label = f'x < {bin_bounds[0]:.0f}'
+    elif n == nbins-1:
+        label = f'x >= {bin_bounds[-1]:.0f}'
+    else:
+        label = f'{bin_bounds[n-1]:.0f} <= x < {bin_bounds[n]:.0f}'
+    # Plotting data at (-10, -10) which is not in the plotting window
+    scatter = plt.scatter(-10, -10, color=color, label=label)
+
+# The legend for this second plot is what we are actually interested in
+# We want large font, no frame around the legend, and 4 columns of labels
+lax.legend(loc='center', fontsize='large', frameon=False, ncol=4)
+
+plt.show()
+
+###################################################
+# Make station_2_2 plot
+
+scatter2 = make_shared_plot(figsize=(10,5.25))
+plt.suptitle('Dummy station data colored according to range of values', y=.9)
+
+# add colorbar
+cax = plt.axes((0.225, 0.075, 0.55, 0.025))
+norm = mpl.colors.BoundaryNorm([-1.2] + bin_bounds+ [35], len(colors))
+cb2 = mpl.colorbar.ColorbarBase(cax, cmap=cmap,
+                                norm=norm,
+                                boundaries=[-1.2] + bin_bounds + [35],
+                                ticks=bin_bounds,
+                                orientation='horizontal')