Changeset 583 in lmdz_wrf for trunk/tools

Timestamp:

Jul 8, 2015, 11:48:34 AM (10 years ago)

Author:

lfita

Message:

Adding when there is no values within coindtvalues

File:

• trunk/tools/validation_sim.py (modified) (4 diffs)

trunk/tools/validation_sim.py

@@ -1394 +1394 @@
 
 # Temporal statistics
-            sovs = np.array(sovalues[intv[0]:intv[1]])[:,0]
-            minv = np.min(sovs)
-            maxv = np.max(sovs)
-            meanv = np.mean(sovs)
-            stdv = np.std(sovs)
-
-            fsovalues.append([meanv, np.array(sovalues[intv[0]:intv[1]])[0,1], minv, \
-              maxv, stdv])
+            if len(np.array(sovalues[intv[0]:intv[1]]).shape) != 1:
+                sovs = np.array(sovalues[intv[0]:intv[1]])[:,0]
+                minv = np.min(sovs)
+                maxv = np.max(sovs)
+                meanv = np.mean(sovs)
+                stdv = np.std(sovs)
+
+                fsovalues.append([meanv, np.array(sovalues[intv[0]:intv[1]])[0,1],    \
+                  minv, maxv, stdv])
+            else:
+                fsovalues.append([fillValueF, np.ones((2,2),dtype=np.float)*fillValueF\
+                  , fillValueF, fillValueF, fillValueF]) 
+
             if ds.has_key('Z'):
                 if okind == 'trajectory':
@@ -1804 +1809 @@
     print '  ' + main + ': no exact values found!'
     Nexactt = 0
+    quit(-1)
 else:
     Nexactt = len(exacttvalues[:,0])
@@ -1994 +2000 @@
                 if Nexactt == 0:
                     newvar[:] =  np.float64(0.)
-                    simobsSvalues = np.array(np.float(0.))
-                    simobsvalues = np.zeros((1,2), dtype=np.float)
                 else:
                     newvar[:] = exacttvalues[:,3]
+            if Nexactt == 0:
+                simobsSvalues = np.zeros((1,2), dtype=np.float)
+                simobsvalues = np.zeros((1,2), dtype=np.float)
 
             dimt = Nexactt
@@ -2072 +2079 @@
 
 # statisics sim
+        print 'Lluis shapes: ',arrayvals.shape,':',len(simobsvalues)
         simstats[kst,0] = np.min(arrayvals[:,0])
         simstats[kst,1] = np.max(arrayvals[:,0])