Merge branch 'main' into panel_4

NCAR · Jul 15, 2022 · f80d112 · f80d112
2 parents 0151126 + 7d76b2c
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diff --git a/Gallery/MapProjections/NCL_native_1.py b/Gallery/MapProjections/NCL_native_1.py
@@ -22,7 +22,6 @@
 import numpy as np
 import cartopy.crs as ccrs
 import matplotlib.pyplot as plt
-import matplotlib.ticker as mticker
 import cmaps
 
 import geocat.viz as gv
@@ -58,22 +57,6 @@
 # and 42.25N to 49.25N
 ax.set_extent([4.25, 15.25, 42.25, 49.25], ccrs.PlateCarree())
 
-# Draw gridlines
-gl = ax.gridlines(crs=ccrs.PlateCarree(),
-                  draw_labels=True,
-                  dms=False,
-                  x_inline=False,
-                  y_inline=False,
-                  linewidth=1,
-                  color="black",
-                  alpha=0.25)
-
-# Manipulate latitude and longitude gridline numbers and spacing
-gl.xlocator = mticker.FixedLocator(np.arange(4, 18, 2))
-gl.ylocator = mticker.FixedLocator(np.arange(43, 50))
-gl.xlabel_style = {"rotation": 0, "size": 14}
-gl.ylabel_style = {"rotation": 0, "size": 14}
-
 # Create colormap by choosing colors from existing colormap
 # The brightness of the colors in cmocean_speed increase linearly. This
 # makes the colormap easier to interpret for those with vision impairments
@@ -106,19 +89,26 @@
              pad=0.1,
              shrink=0.8)
 
+# Use geocat-viz utility function to add gridlines to the map
+gl = gv.add_lat_lon_gridlines(
+    ax,
+    color='black',
+    labelsize=14,
+    xlocator=np.arange(4, 18, 2),  # longitudes for gridlines
+    ylocator=np.arange(43, 50))  # latitudes for gridlines
+
+# Add padding between figure and longitude labels
+gl.xpadding = 12
+
 # Use geocat.viz.util function to easily set left and right titles
 gv.set_titles_and_labels(ax,
                          lefttitle="topography",
-                         lefttitlefontsize=14,
+                         lefttitlefontsize=16,
                          righttitle="m",
-                         righttitlefontsize=14)
+                         righttitlefontsize=16)
 
 # Add a main title above the left and right titles
-plt.title("Native Sterographic Example",
-          loc="center",
-          y=1.1,
-          size=18,
-          fontweight="bold")
+plt.title("Native Stereographic Example", y=1.1, size=18, fontweight="bold")
 
 # Remove whitespace around plot
 plt.tight_layout()

diff --git a/Gallery/TaylorDiagrams/NCL_taylor_2.py b/Gallery/TaylorDiagrams/NCL_taylor_2.py
@@ -0,0 +1,78 @@
+"""
+NCL_taylor_2.py
+===============
+Concepts illustrated:
+  - Creating a simple Taylor Diagram
+  - Adding background options for the diagram
+
+See following URLs to see the reproduced NCL plot & script:
+    - Original NCL script: https://www.ncl.ucar.edu/Applications/Scripts/taylor_2.ncl
+    - Original NCL plot: https://www.ncl.ucar.edu/Applications/Images/taylor_2_lg.png
+
+Note: Due to to limitations of matplotlib's axisartist toolkit, we cannot include minor tick marks
+        between 0.9 and 0.99, as seen in the original NCL plot.
+"""
+
+###############################################################################
+# Import packages:
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+import geocat.viz as gv
+
+###############################################################################
+# Create dummy data:
+
+# p dataset
+pstddev = [0.6, 0.5, 0.45, 0.75, 1.15]  # standard deviation
+pcorrcoef = [0.24, 0.75, 1, 0.93, 0.37]  # correlation coefficient
+
+# t dataset
+tstddev = [0.75, 0.64, 0.4, 0.85, 1.15]
+tcorrcoef = [0.24, 0.75, 0.47, 0.88, 0.73]
+
+###############################################################################
+# Plot
+
+# Create figure and Taylor Diagram instance
+fig = plt.figure(figsize=(12, 12))
+dia = gv.TaylorDiagram(fig=fig, label='REF')
+ax = plt.gca()
+
+# Add model sets for p and t datasets
+dia.add_model_set(
+    pstddev,
+    pcorrcoef,
+    fontsize=20,
+    xytext=(-5, 10),  # marker label location, in pixels
+    color='red',
+    marker='o',
+    facecolors='none',
+    s=100)  # marker size
+dia.add_model_set(
+    tstddev,
+    tcorrcoef,
+    fontsize=20,
+    xytext=(-5, 10),  # marker label location, in pixels
+    color='blue',
+    marker='D',
+    facecolors='none',
+    s=100)
+
+# Add RMS contours, and label them
+dia.add_contours(levels=np.arange(0, 1.1, 0.25),
+                 colors='lightgrey',
+                 linewidths=0.5)
+
+# Add y axis grid
+dia.add_ygrid(np.array([0.5, 1.5]), color='grey')
+
+# Add x axis grid
+dia.add_xgrid(np.array([0.6, 0.9]))
+
+# Add figure title
+plt.title("Example", size=26, pad=45)
+
+# Show the plot
+plt.show()
diff --git a/Gallery/TaylorDiagrams/README.rst b/Gallery/TaylorDiagrams/README.rst
@@ -0,0 +1,6 @@
+.. _taylor_diagrams_examples:
+
+.. _taylor-diagrams-index:
+
+Taylor Diagrams
+===============
diff --git a/Gallery/Vectors/NCL_vector_1.py b/Gallery/Vectors/NCL_vector_1.py
@@ -3,6 +3,11 @@
 ===============
 Plot U & V vector over SST
 
+Note: The colormap on this plot has been changed from the original NCL colormap
+      in order to follow best practices for colormaps. See other examples here:
+      https://geocat-examples.readthedocs.io/en/latest/gallery/index.html#colors
+
+
 This script illustrates the following concepts:
   - Overlaying vectors and filled contours on a map
   - Changing the scale of the vectors on the plot
@@ -18,12 +23,13 @@
 ###############################################################################
 # Import packages
 
-import xarray as xr
+import matplotlib.pyplot as plt
+import matplotlib as mpl
 import numpy as np
-from matplotlib import pyplot as plt
-import cartopy
+import xarray as xr
+import cartopy.feature as cfeature
 import cartopy.crs as ccrs
-import cmaps
+from cartopy.mpl.gridliner import LongitudeFormatter, LatitudeFormatter
 
 import geocat.datafiles as gdf
 import geocat.viz as gv
@@ -47,105 +53,117 @@
 v = uv_in['V'].sel(date=198801, lev=1000)
 
 # Read in grid information
-lat_sst = sst['lat']
-lon_sst = sst['lon']
 lat_uv = u['lat']
 lon_uv = u['lon']
 
 ###############################################################################
 # Plot:
 
+# Define map projection to use
+proj = ccrs.PlateCarree()
+
 # Generate figure (set its size (width, height) in inches)
 plt.figure(figsize=(10, 7))
 
-# Generate axes using Cartopy projection
-ax = plt.axes(projection=ccrs.PlateCarree())
-
-# Draw vector plot
-Q = plt.quiver(lon_uv,
-               lat_uv,
-               u,
-               v,
-               color='white',
-               pivot='middle',
-               width=.0025,
-               scale=75,
-               zorder=2)
-
-# Turn on continent shading
-ax.add_feature(cartopy.feature.LAND,
-               edgecolor='lightgray',
-               facecolor='lightgray',
-               zorder=1)
-
-# Define levels for contour map (24, 24.1, ..., 28.8, 28.9)
-levels = np.linspace(24, 28.9, 50)
-
-# Import an NCL colormap, truncating it by using geocat.viz.util convenience function
-gv.truncate_colormap(cmaps.BlAqGrYeOrReVi200,
-                     minval=0.08,
-                     maxval=0.96,
-                     n=len(levels),
-                     name='BlAqGrYeOrReVi200')
-
-# Contourf-plot the SST data
-cf = sst.plot.contourf('lon',
-                       'lat',
-                       extend='both',
-                       levels=levels,
-                       cmap='BlAqGrYeOrReVi200',
-                       zorder=0,
-                       add_labels=False,
-                       add_colorbar=False)
-
-# Add color bar
-cbar_ticks = np.arange(24, 29.1, .3)
-cbar = plt.colorbar(cf,
-                    orientation='vertical',
-                    drawedges=True,
-                    shrink=0.75,
-                    pad=0.05,
-                    ticks=cbar_ticks)
-
-# Draw the key for the quiver plot as a rectangle patch
-rect = plt.Rectangle((92.9, 22.6),
-                     2,
-                     2,
-                     facecolor='white',
-                     edgecolor=None,
-                     zorder=2)
-ax.add_patch(rect)
-ax.quiverkey(Q,
-             0.9675,
-             0.9,
-             3,
-             '4',
-             labelpos='N',
-             color='black',
-             coordinates='axes',
-             fontproperties={'size': 14},
-             labelsep=0.1)
-
-# Use geocat.viz.util convenience function to set axes tick values
+# Define axis using Cartopy and zoom in on the region of interest
+ax = plt.axes(projection=proj)
+ax.set_extent((66, 96, 5, 25), crs=ccrs.PlateCarree())
+
+# Create the filled contour plot
+sst_plot = sst.plot.contourf(
+    ax=ax,
+    transform=proj,
+    levels=50,
+    vmin=24,
+    vmax=28.8,
+    cmap="magma",
+    add_colorbar=False,
+)
+
+# Remove default x and y labels from plot
+plt.xlabel("")
+plt.ylabel("")
+
+# add land feature
+ax.add_feature(cfeature.LAND, facecolor="lightgrey", zorder=1)
+
+# Add vectors onto the plot
+Q = plt.quiver(
+    lon_uv,
+    lat_uv,
+    u,
+    v,
+    color='white',
+    pivot='middle',
+    width=.0025,
+    scale=75,
+)
+
+# Use geocat-viz utility function to format title
+gv.set_titles_and_labels(ax,
+                         maintitle='',
+                         maintitlefontsize=18,
+                         lefttitle="Sea Surface Temperature",
+                         lefttitlefontsize=18,
+                         righttitle="C",
+                         righttitlefontsize=18,
+                         xlabel=None,
+                         ylabel=None,
+                         labelfontsize=16)
+
+# Format tick labels as latitude and longitudes
+gv.add_lat_lon_ticklabels(ax=ax)
+
+# Use geocat-viz utility function to customize tick marks
 gv.set_axes_limits_and_ticks(ax,
                              xlim=(65, 95),
                              ylim=(5, 25),
                              xticks=range(70, 95, 10),
                              yticks=range(5, 27, 5))
 
-# Use geocat.viz.util convenience function to add minor and major tick lines
+# Remove degree symbol from tick labels
+ax.yaxis.set_major_formatter(LatitudeFormatter(degree_symbol=''))
+ax.xaxis.set_major_formatter(LongitudeFormatter(degree_symbol=''))
+
+# Add minor tick marks
 gv.add_major_minor_ticks(ax,
-                         x_minor_per_major=5,
-                         y_minor_per_major=5,
+                         x_minor_per_major=4,
+                         y_minor_per_major=4,
                          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)
+# Draw the key for the quiver plot as a rectangle patch
+rect = mpl.patches.Rectangle(
+    (91.7, 22.7),  # (x, y)
+    3.2,  # width
+    2.2,  # height
+    facecolor='white',
+    edgecolor='k',
+)
+ax.add_patch(rect)
 
-# Use geocat.viz.util convenience function to add titles to left and right of the plot axis.
-gv.set_titles_and_labels(ax,
-                         lefttitle='Sea Surface Temperature',
-                         righttitle='C')
+qk = ax.quiverkey(
+    Q,  # the quiver instance
+    0.95,  # x position of the key
+    0.9,  # y position of the key
+    4,  # length of the key
+    '4',  # label for the key
+    labelpos='N',  # position the label to the 'north' of the arrow
+    color='black',
+    coordinates='axes',
+    fontproperties={'size': 14},
+    labelsep=0.1,  # Distance between arrow and label
+)
+
+# Add and customize colorbar
+cbar_ticks = np.arange(24, 28.8, .3)
+plt.colorbar(ax=ax,
+             mappable=sst_plot,
+             extendrect=True,
+             extendfrac='auto',
+             shrink=0.75,
+             aspect=10,
+             ticks=cbar_ticks,
+             drawedges=True)
 
 # Show the plot
 plt.show()