Changeset 2230 in lmdz_wrf for trunk/tools

Timestamp:

Nov 14, 2018, 9:47:26 PM (6 years ago)

Author:

lfita

Message:

Working version with 'aggregation' of `time_slices'

File:

• trunk/tools/generic_tools.py (modified) (6 diffs)

trunk/tools/generic_tools.py

@@ -14619 +14619 @@
         if timesec != 'season':
             for it in range(dimt):
-                if timesec == 'year': print it, ':', mattimes[it,:]
                 for tvv in tvals:
                     if mattimes[it,itsec] == tvv:
@@ -14646 +14645 @@
                         tvsec[tvv] = vvv
                         break
-                print it, 'Lluis:', mattimes[it,:], tvv, mattimes[it,1]
                
         temporal_desc[timesec]=tvsec
@@ -14693 +14691 @@
         quit(-1)
 
-
     mattimes = CFtimesvar_datetime(tv, tu, cal)
 
@@ -14931 +14928 @@
         pern = per[3:Lper]
         vtemp_desc = temp_desc[pern]
-        print vtemp_desc
         vvtdesc = list(vtemp_desc.keys())
         vvtdesc.sort()
@@ -14939 +14935 @@
         for islc in range(Nslices):
             vvtemp_desc = vtemp_desc[vvtdesc[islc]]
-            print 'islc,', islc, 'vtemp:', vvtemp_desc
             Ltt = len(vvtemp_desc)
             slices.append(vvtemp_desc)
@@ -14975 +14970 @@
     return slices, Nslices
 
-tv = []
-values = []
-totT = 24.
-dT = 7.345
-iTT = 29.
-for it in range(0,10):
-   for itt in range(3):
-        days = iTT+it*totT+dT*itt
-        tv.append(days)
-        #values.append((it*3+itt)*1.)
-        Nyear = int((days-31)/365)
-        dyear = (days-31) - Nyear*365
-        if dyear < 59: 
-            values.append(0.)
-        elif dyear >= 59 and dyear < 151:
-            values.append(1.)
-        elif dyear >= 151 and dyear < 243: 
-            values.append(2.)
-        elif dyear >= 243 and dyear < 334: 
-            values.append(3.)
-
-for it in range(len(values)):
-    print it, tv[it], values[it]
-
-vals = np.array(values)
-itdim = 0
-tu = 'days since 1949-12-01 00:00:00'
-per = 'season'
-calend = 'standard'
-amount = 1
-
-tdes = temporal_desc(tv, tu, calend)
-
-tslc, Ntslc = time_slices(tv, tu, calend, per, amount, tdes)
-
-statn = 'mean'
-tstat = np.ones((Ntslc), dtype=np.float)
-for islc in range(Ntslc):
-    timeslcv = tslc[islc]
-    if per[0:3] != 'agg':
-        timeslc = [slice(timeslcv[0],timeslcv[1],timeslcv[2])]
-        tvals = vals[tuple(timeslc)]
-    else:
-        newshape = list(vals.shape)
-        aggslc = tslc[islc]
-        NNtslc = len(aggslc)
-        newshape[itdim] = NNtslc
-        tvals = np.zeros(tuple(newshape), dtype=vals.dtype)
-        origshape = list(vals.shape)
-        iishape = list(vals.shape)
-        for iislc in range(NNtslc):
-            origshape[itdim] = aggslc[iislc]
-            iishape[itdim] = iislc
-            print iislc, ':', iishape, '<>', origshape, vals[tuple(origshape)]
-            tvals[tuple(iishape)] = vals[tuple(origshape)]
-
-    if statn == 'min':
-        tstat[islc] = np.min(tvals, axis=itdim)
-    elif statn == 'max':
-        tstat[islc] = np.max(tvals, axis=itdim)
-    elif statn == 'mean':
-        tstat[islc] = np.mean(tvals, axis=itdim)
-    elif statn == 'mean2':
-        tstat[islc] = np.mean(tvals**2, axis=itdim)
-    elif statn == 'std':
-        tstat[islc] = np.std(tvals, axis=itdim)
-
-    timeslc = tslc[islc]
-    itime = tv[timeslc[0]]
-    etime = tv[timeslc[1]]
-    print islc, ':', itime, '-', etime, '<>', tvals, '=', tstat[islc]
-quit()
-
-
+#quit()
+
+