changed StateToGrid

da/ct/tools.py

@@ -15,25 +15,19 @@ import datetime
 
 identifier = 'CarbonTracker CO2'
 
-def StateToGrid(DaInfo,values,reverse=False,avg=False):
+def StateToGrid(values,regionmap,reverse=False,avg=False):
     """ 
     This method converts parameters from a CarbonTracker StateVector object to a gridded map of linear multiplication values. These
     can subsequently be used in the transport model code to multiply/manipulate fluxes
 
     """
-    import Nio
-
-    mapfile   = os.path.join(DaInfo.da_settings['datadir'],DaInfo.da_settings['regionsfile'])
-    ncf       = Nio.open_file(mapfile,'r')
-    regionmap = ncf.variables['budget_region'].get_value()
-    dummy     = ncf.close()
-
+    import numpy as np
     nregions  = regionmap.max()
 
     # dictionary for region <-> map conversions
 
     regs={}
-    for r in arange(1,nregions+1):
+    for r in np.arange(1,nregions+1):
          sel=(regionmap.flat == r).nonzero()
          if len(sel[0])>0: regs[r]=sel
 
@@ -43,7 +37,7 @@ def StateToGrid(DaInfo,values,reverse=False,avg=False):
 
         """ project 1x1 degree map onto ecoregions """
 
-        result=zeros(nregions,float)
+        result=np.zeros(nregions,float)
         for k,v in regionselect.iteritems():
             if avg: 
                 result[k-1]=values.ravel().take(v).mean()
@@ -55,7 +49,7 @@ def StateToGrid(DaInfo,values,reverse=False,avg=False):
 
         """ project ecoregion properties onto 1x1 degree map """
 
-        result=zeros((180,360,),float)
+        result=np.zeros((180,360,),float)
         for k,v in regionselect.iteritems():
             result.put(v,values[k-1])