Cleaned up plotting documentation.

doc/source/new.rst

@@ -1,6 +1,23 @@
 What's New
 ===========
 
+Releases
+-------------
+
+v1.0.0
+^^^^^^^^^^^^^
+
+- Release 1.0.0.
+- Fixed issue with not being able to set the thread-local coordinate cache to 
+  0 to disable it.  Also, the cache will now correctly resize itself when 
+  the size is reduced to less than its current setting.
+- Fixed an issue with the '0000-00-00 00:00:00' time used in geo_em files 
+  causing crashes due to the invalid time.  The time is now set to 
+  numpy.datetime64('NaT').
+- Fixed issue with wrf.cape_3d not working correctly with a single 
+  column of data.
+
+
 Beta Releases
 --------------
 
@@ -67,8 +84,8 @@ v1.0a3
 Known Issues
 --------------
 
-v1.0b3
-^^^^^^^^^^^^^^^
+v1.0.0
+^^^^^^^^
 
 - Currently unable to build on Windows with Python 3.5+ using open source 
   mingw compiler.  The mingwpy project is working on resolving the 

doc/source/plot.rst

@@ -69,8 +69,10 @@ Plotting a Two-dimensional Field
     ax.coastlines('50m', linewidth=0.8)
     
     # Make the contour outlines and filled contours for the smoothed sea level pressure.
-    plt.contour(to_np(lons), to_np(lats), to_np(smooth_slp), 10, colors="black", transform=crs.PlateCarree())
-    plt.contourf(to_np(lons), to_np(lats), to_np(smooth_slp), 10, transform=crs.PlateCarree(), cmap=get_cmap("jet"))
+    plt.contour(to_np(lons), to_np(lats), to_np(smooth_slp), 10, colors="black", 
+                transform=crs.PlateCarree())
+    plt.contourf(to_np(lons), to_np(lats), to_np(smooth_slp), 10, transform=crs.PlateCarree(), 
+                 cmap=get_cmap("jet"))
     
     # Add a color bar
     plt.colorbar(ax=ax, shrink=.62)
@@ -86,6 +88,7 @@ Plotting a Two-dimensional Field
 
     plt.show()
 
+
 Horizontal Interpolation to a Pressure Level
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
@@ -194,8 +197,8 @@ plot, see :ref:`cross_example`.
     slp = getvar(ncfile, "slp")
     smooth_slp = smooth2d(slp, 3)
     ctt = getvar(ncfile, "ctt")
-    z = getvar(ncfile, "z", timeidx=0)
-    dbz = getvar(ncfile, "dbz", timeidx=0)
+    z = getvar(ncfile, "z")
+    dbz = getvar(ncfile, "dbz")
     Z = 10**(dbz/10.)
     wspd =  getvar(ncfile, "wspd_wdir", units="kt")[0,:]
     
@@ -203,10 +206,12 @@ plot, see :ref:`cross_example`.
     start_point = CoordPair(lat=26.76, lon=-80.0)
     end_point = CoordPair(lat=26.76, lon=-77.8)
     
-    # Compute the vertical cross-section interpolation.  Also, include the lat/lon points along the cross-section 
-    # in the metadata by setting latlon to True.
-    z_cross = vertcross(Z, z, wrfin=ncfile, start_point=start_point, end_point=end_point, latlon=True, meta=True)
-    wspd_cross = vertcross(wspd, z, wrfin=ncfile, start_point=start_point, end_point=end_point, latlon=True, meta=True)
+    # Compute the vertical cross-section interpolation.  Also, include the lat/lon 
+    # points along the cross-section in the metadata by setting latlon to True.
+    z_cross = vertcross(Z, z, wrfin=ncfile, start_point=start_point, end_point=end_point, 
+                        latlon=True, meta=True)
+    wspd_cross = vertcross(wspd, z, wrfin=ncfile, start_point=start_point, end_point=end_point, 
+                           latlon=True, meta=True)
     dbz_cross = 10.0 * np.log10(z_cross)
     
     # Get the lat/lon points
@@ -236,11 +241,11 @@ plot, see :ref:`cross_example`.
     
     # Create the filled cloud top temperature contours
     contour_levels = [-80.0, -70.0, -60, -50, -40, -30, -20, -10, 0, 10]
-    ctt_contours = ax_ctt.contourf(to_np(lons), to_np(lats), to_np(ctt), contour_levels, cmap=get_cmap("Greys"),
-                 transform=crs.PlateCarree(), zorder=2)
+    ctt_contours = ax_ctt.contourf(to_np(lons), to_np(lats), to_np(ctt), contour_levels, 
+                                   cmap=get_cmap("Greys"), transform=crs.PlateCarree(), zorder=2)
     
-    ax_ctt.plot([start_point.lon, end_point.lon], [start_point.lat, end_point.lat], color="yellow", 
-                marker="o", transform=crs.PlateCarree(), zorder=3)
+    ax_ctt.plot([start_point.lon, end_point.lon], [start_point.lat, end_point.lat], 
+                color="yellow", marker="o", transform=crs.PlateCarree(), zorder=3)
     
     # Create the color bar for cloud top temperature
     cb_ctt = fig.colorbar(ctt_contours, ax=ax_ctt, shrink=.60)
@@ -299,6 +304,7 @@ plot, see :ref:`cross_example`.
     
     plt.show()
 
+
 Matplotlib with Basemap
 -----------------------
 
@@ -306,8 +312,7 @@ Although basemap is in maintenance mode only and becoming deprecated, it is stil
 widely used by many programmers.  Cartopy is becoming the preferred package for 
 mapping, however it suffers from growing pains in some areas 
 (can't use latitude/longitude labels for many map projections).  If you 
-run in to these issues, basemap is likely to accomplish what you need, despite 
-slower performance.
+run in to these issues, basemap is likely to accomplish what you need.
 
 
 Plotting a Two-Dimensional Field
@@ -462,8 +467,8 @@ plot, see :ref:`cross_example`.
     slp = getvar(ncfile, "slp")
     smooth_slp = smooth2d(slp, 3)
     ctt = getvar(ncfile, "ctt")
-    z = getvar(ncfile, "z", timeidx=0)
-    dbz = getvar(ncfile, "dbz", timeidx=0)
+    z = getvar(ncfile, "z")
+    dbz = getvar(ncfile, "dbz")
     Z = 10**(dbz/10.)
     wspd =  getvar(ncfile, "wspd_wdir", units="kt")[0,:]
     
@@ -471,10 +476,12 @@ plot, see :ref:`cross_example`.
     start_point = CoordPair(lat=26.76, lon=-80.0)
     end_point = CoordPair(lat=26.76, lon=-77.8)
     
-    # Compute the vertical cross-section interpolation.  Also, include the lat/lon points along the cross-section in 
-    # the metadata by setting latlon to True.
-    z_cross = vertcross(Z, z, wrfin=ncfile, start_point=start_point, end_point=end_point, latlon=True, meta=True)
-    wspd_cross = vertcross(wspd, z, wrfin=ncfile, start_point=start_point, end_point=end_point, latlon=True, meta=True)
+    # Compute the vertical cross-section interpolation.  Also, include the lat/lon points 
+    # along the cross-section in the metadata by setting latlon to True.
+    z_cross = vertcross(Z, z, wrfin=ncfile, start_point=start_point, end_point=end_point, 
+                        latlon=True, meta=True)
+    wspd_cross = vertcross(wspd, z, wrfin=ncfile, start_point=start_point, end_point=end_point, 
+                           latlon=True, meta=True)
     dbz_cross = 10.0 * np.log10(z_cross)
     
     # Get the latitude and longitude points
@@ -609,8 +616,10 @@ plotted using the standard matplotlib API.
     start_point = CoordPair(lat=26.76, lon=-80.0)
     end_point = CoordPair(lat=26.76, lon=-77.8)
     
-    # Compute the vertical cross-section interpolation.  Also, include the lat/lon points along the cross-section.
-    wspd_cross = vertcross(wspd, z, wrfin=ncfile, start_point=start_point, end_point=end_point, latlon=True, meta=True)
+    # Compute the vertical cross-section interpolation.  Also, include the lat/lon 
+    # points along the cross-section.
+    wspd_cross = vertcross(wspd, z, wrfin=ncfile, start_point=start_point, end_point=end_point, 
+                           latlon=True, meta=True)
     
     # Create the figure
     fig = plt.figure(figsize=(12,6))