Merge pull request #32 from dcherian/panel_1

Add panel_1

Plots/Panels/panel_1.py

@@ -0,0 +1,130 @@
+"""
+panel_1.py
+===============
+Three panel image with shared colorbar and title
+
+
+NCL docs: https://www.ncl.ucar.edu/Applications/panel.shtml
+
+NCL script: https://www.ncl.ucar.edu/Applications/Scripts/panel_1.ncl
+
+NCL output: https://www.ncl.ucar.edu/Applications/Images/panel_1_lg.png
+
+"""
+
+###############################################################################
+# Concepts illustrated:
+#   - Paneling plots vertically on a page ``plt.subplots``
+#   - Adding a common title to paneled plots ``matplotlib.Figure.suptitle``
+#   - Adding a common labelbar (or colorbar) to paneled plots ``matplotlib.Figure.colorbar``
+#   - Subsetting a color map
+
+###############################################################################
+# Lets read the netCDF dataset using xarray and choose the second timestamp.
+import cartopy
+import cartopy.crs as ccrs
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+import numpy as np
+import xarray as xr
+
+from geocat.viz.util import add_lat_lon_ticklabels, nclize_axis
+
+ds = xr.open_dataset("../../data/netcdf_files/uv300.nc").isel(time=1)
+
+###############################################################################
+# Now we'll make three panels (subplots in matplotlib terminology) using ``plt.subplots``
+# We'll specify ``constrained_layout=True`` which will attempt to automatically
+# layout panels, colorbars and axes decorations nicely.
+# https://matplotlib.org/tutorials/intermediate/constrainedlayout_guide.html
+
+f, ax = plt.subplots(
+    3,  # 3 rows
+    1,  # 1 column
+    constrained_layout=True,  # "magic"
+    subplot_kw={"projection": ccrs.PlateCarree()},  # specify plot projection
+)
+
+
+# first add continents
+continents = cartopy.feature.NaturalEarthFeature(
+    name="coastline",
+    category="physical",
+    scale="50m",
+    edgecolor="None",
+    facecolor="lightgray",
+)
+[axes.add_feature(continents) for axes in ax.flat]
+
+
+levels = np.arange(-48, 48, 4)
+
+# Using a dictionary makes it easy to reuse the same keyword arguments twice for the contours
+kwargs = dict(
+    levels=levels,  # contour levels specified outside this function
+    xticks=np.arange(-180, 181, 30),  # nice x ticks
+    yticks=np.arange(-90, 91, 30),  # nice y ticks
+    transform=ccrs.PlateCarree(),  # ds projection
+    add_colorbar=False,  # don't add individual colorbars for each plot call
+    add_labels=False,  # turn off xarray's automatic Lat, lon labels
+    colors="k",  # note plurals in this and following kwargs
+    linestyles="-",
+    linewidths=0.5,
+)
+
+
+# first U
+hdl = ds.U.plot.contour(
+    x="lon",  # not strictly necessary but good to be explicit
+    y="lat",
+    ax=ax[0],  # this is the axes we want to plot to
+    **kwargs,
+)
+# Label the contours
+ax[0].clabel(
+    hdl,
+    np.arange(0, 32, 8),  # only label these contour levels
+    fontsize="small",
+    fmt="%.0f",  # Turn off decimal points
+)
+ax[0].set_title("Zonal Wind [m/s]", loc="left", y=1.05)
+
+# now for V
+hdl = ds.V.plot.contour(x="lon", y="lat", ax=ax[1], **kwargs,)
+ax[1].clabel(
+    hdl,
+    [0],  # only label these contour levels
+    fontsize="small",
+    fmt="%.0f",  # Turn off decimal points
+)
+ax[1].set_title("Meridional Wind [m/s]", loc="left", y=1.05)
+
+# now draw arrows
+# xarray doesn't have a quiver method (yet)
+# the NCL code plots every 4th value in lat, lon
+# this is the equivalent of u(::4, ::4)
+subset = ds.isel(lat=slice(None, None, 4), lon=slice(None, None, 4))
+ax[2].quiver(
+    subset.lon,
+    subset.lat,
+    subset.U,
+    subset.V,
+    width=0.0015,  # thinner than default
+    transform=ccrs.PlateCarree(),
+    zorder=2,  # hack to make sure quiver plots on top of continents
+    scale=1100,  # adjust till it looks right
+)
+ax[2].set_title("Vector Wind", loc="left", y=1.05)
+
+# cartopy axes require this to be manual
+ax[2].set_xticks(kwargs["xticks"])
+ax[2].set_yticks(kwargs["yticks"])
+
+# make axes look nice and add coastlines
+[nclize_axis(axes) for axes in ax.flat]
+[add_lat_lon_ticklabels(axes) for axes in ax.flat]
+
+# nice figure size in inches
+f.set_size_inches((5, 8))
+
+plt.show()