Fix race condition in plothighsandlows example

Based on the cadence in which the remote files are updated, it is safer
to plot the dataset from yesterday than the dataset from today, because
sometimes the file for today is still not present in the remote.

Author: molinav

doc/examples/plothighsandlows.py

@@ -26,9 +26,9 @@ def extrema(mat, mode="wrap", window=10):
 def main():
     """Main function."""
 
-    # Plot 00 UTC today.
+    # Plot 00 UTC yesterday.
     url = "http://nomads.ncep.noaa.gov/dods/gfs_0p50/gfs%Y%m%d/gfs_0p50_00z"
-    date = dt.datetime.now()
+    date = dt.datetime.now() - dt.timedelta(days=1)
 
     # Open OPeNDAP dataset.
     data = netCDF4.Dataset(date.strftime(url))
@@ -100,7 +100,8 @@ def main():
                 xyplotted.append((x, y))
 
     # Set plot title and show.
-    plt.title("Mean Sea-Level Pressure (with Highs and Lows) %s" % date)
+    datestr = date.strftime("%Y%m%d00")
+    plt.title("Mean Sea-Level Pressure (with Highs and Lows) %s" % datestr)
     plt.show()
 
 

doc/source/users/figures/plothighsandlows.py

@@ -2,13 +2,14 @@
 plot H's and L's on a sea-level pressure map
 (uses scipy.ndimage.filters and netcdf4-python)
 """
+import datetime as dt
 import numpy as np
 import matplotlib.pyplot as plt
-from datetime import datetime
 from mpl_toolkits.basemap import Basemap, addcyclic
 from scipy.ndimage.filters import minimum_filter, maximum_filter
 from netCDF4 import Dataset
 
+
 def extrema(mat,mode='wrap',window=10):
     """find the indices of local extrema (min and max)
     in the input array."""
@@ -19,13 +20,13 @@ def extrema(mat,mode='wrap',window=10):
     # Return the indices of the maxima, minima
     return np.nonzero(mat == mn), np.nonzero(mat == mx)
 
-# plot 00 UTC today.
-date = datetime.now().strftime('%Y%m%d')+'00'
 
-# open OpenDAP dataset.
-data=Dataset("https://nomads.ncep.noaa.gov/dods/gfs_0p50/gfs%s/gfs_0p50_%sz"%\
-        (date[0:8],date[8:10]))
+# Plot 00 UTC yesterday.
+url = "http://nomads.ncep.noaa.gov/dods/gfs_0p50/gfs%Y%m%d/gfs_0p50_00z"
+date = dt.datetime.now() - dt.timedelta(days=1)
 
+# open OpenDAP dataset.
+data = Dataset(date.strftime(url))
 
 # read lats,lons.
 lats = data.variables['lat'][:]
@@ -85,5 +86,7 @@ def extrema(mat,mode='wrap',window=10):
                     ha='center',va='top',color='r',
                     bbox = dict(boxstyle="square",ec='None',fc=(1,1,1,0.5)))
             xyplotted.append((x,y))
-plt.title('Mean Sea-Level Pressure (with Highs and Lows) %s' % date)
+
+datestr = date.strftime("%Y%m%d00")
+plt.title('Mean Sea-Level Pressure (with Highs and Lows) %s' % datestr)
 plt.show()