<p><b>mhoffman@lanl.gov</b> 2012-03-06 16:17:36 -0700 (Tue, 06 Mar 2012)</p><p>BRANCH COMMIT -- land_ice<br>
<br>
Fixed the Time dimension in add_land_ice_variables_to_mpas_grid.py to have a value of 1. Previously it had a value of 0 which caused problems when trying to assign values to variables that use that dimension.<br>
Also, fixed a typo in the name of the convert script.<br>
</p><hr noshade><pre><font color="gray">Modified: branches/land_ice_projects/grid_tools/add_land_ice_variables_to_mpas_grid.py
===================================================================
--- branches/land_ice_projects/grid_tools/add_land_ice_variables_to_mpas_grid.py 2012-03-06 23:13:46 UTC (rev 1599)
+++ branches/land_ice_projects/grid_tools/add_land_ice_variables_to_mpas_grid.py 2012-03-06 23:17:36 UTC (rev 1600)
@@ -31,10 +31,18 @@
# It may be better to list them explicitly as I do for the grid variables,
# but this way ensures they all get included and is easier.
for dim in filein.dimensions.keys():
- fileout.createDimension(dim, filein.dimensions[dim])
+ if dim == 'Time':
+ # Note that for some reason getting the current value of the UNLIMITED dimension does not work with this method. The value returned in this case is "None". However, you can always get the current value of any variable dimension via the shape attribute.
+ # This is a limitation of Scientific.IO.NetCDF and may not be an issue with other netcdf python modules.
+ # This workaround should be fine for the time being since there is no need to have the I.C. file have UNLIMITED time dimension.
+ fileout.createDimension('Time', 1)
+ else:
+ fileout.createDimension(dim, filein.dimensions[dim])
# Create nVertLevelsPlus2 dimension
fileout.createDimension('nVertLevelsPlus2', filein.dimensions['nVertLevels'] + 2)
+
+
# Copy over all of the required grid variables to the new file
vars2copy = ('latCell', 'lonCell', 'xCell', 'yCell', 'zCell', 'indexToCellID', 'latEdge', 'lonEdge', 'xEdge', 'yEdge', 'zEdge', 'indexToEdgeID', 'latVertex', 'lonVertex', 'xVertex', 'yVertex', 'zVertex', 'indexToVertexID', 'cellsOnEdge', 'nEdgesOnCell', 'nEdgesOnEdge', 'edgesOnCell', 'edgesOnEdge', 'weightsOnEdge', 'dvEdge', 'dcEdge', 'angleEdge', 'areaCell', 'areaTriangle', 'cellsOnCell', 'verticesOnCell', 'verticesOnEdge', 'edgesOnVertex', 'cellsOnVertex', 'kiteAreasOnVertex')
for varname in vars2copy:
Copied: branches/land_ice_projects/grid_tools/convert_mpas_grid_to_regular_grid_netcdf.py (from rev 1595, branches/land_ice_projects/grid_tools/covert_mpas_grid_to_regular_grid_netcdf.py)
===================================================================
--- branches/land_ice_projects/grid_tools/convert_mpas_grid_to_regular_grid_netcdf.py (rev 0)
+++ branches/land_ice_projects/grid_tools/convert_mpas_grid_to_regular_grid_netcdf.py 2012-03-06 23:17:36 UTC (rev 1600)
@@ -0,0 +1,82 @@
+#!/usr/bin/python
+# Script to convert selected variables from an MPAS run and create a new netCDF file
+# that has those variables on a rectangular grid. The resulting gridded data appears
+# distorted but is adequate for quickly checking output. This is likely to only work
+# with grids created with periodic_hex where the order of cells in each 1d array (e.g. 'nCells')
+# is row by row (or is it column by column). This is a workaround to allow visualization
+# in, e.g. ncview since Paraview has some limitations as to which variables can be read in.
+# Currently, the script is setup to regrid any 2d and 3d variables that have dimensions of both Time
+# and nCells. The output file has the name 'converted.nc'. The output file is a little quirky,
+# but does work with ncview.
+
+import sys, os, glob, shutil, numpy
+from Scientific.IO.NetCDF import *
+# from NetCDF import *
+from optparse import OptionParser
+
+parser = OptionParser()
+parser.add_option("-f", "--file", dest="filename", help="file to convert", metavar="FILE")
+options, args = parser.parse_args()
+if not options.filename:
+ parser.error("Filename is a required input.")
+
+# Get some information about the input file
+filein = NetCDFFile(options.filename,'r')
+# These need to be specified!!!! Perhaps these should be supplied as arguments on the command line
+nx = 30
+ny = 35
+times = filein.variables['xtime']
+time_length = times.shape[0]
+vert_levs = filein.dimensions['nVertLevels']
+
+# Define the new file to be output - this should be made a variant of the input file name
+fileout = NetCDFFile("converted.nc","w")
+# Create the new x,y dimensions for the new file
+fileout.createDimension('nx',nx)
+fileout.createDimension('ny',ny)
+# Copy over all the dimensions to the new file
+for dim in filein.dimensions.keys():
+ # print 'DIMENSION: ', dim
+ # print 'HAS VALUE: ', filein.dimensions[dim]
+ fileout.createDimension(dim, filein.dimensions[dim])
+
+# Loop over all variables in file and find the ones we want to convert
+for var in filein.variables.keys():
+ # print var
+ thevar = filein.variables[var]
+ dimflag = 0
+ # Look for variables that have these two dimensions
+ for dim in thevar.dimensions:
+ if dim == 'nCells':
+ # print ' has', dim
+ dimflag += 1
+ if dim == 'Time':
+ # print ' has', dim
+ dimflag += 1
+ if dimflag == 2:
+ # print ' HAS BOTH'
+ # Convert this variable
+ dims2use = ()
+ lastdim = 0
+ for dim in thevar.dimensions:
+ if dim == 'nCells':
+ dims2use = dims2use + ('ny', 'nx')
+ else:
+ dims2use = dims2use + (dim,)
+ if dim == 'nVertLevels':
+ lastdim = vert_levs
+ elif dim == 'nVertLevelsPlus2':
+ lastdim = vert_levs + 2
+ # print dims2use
+ # print thevar.typecode()
+ newVar = fileout.createVariable(var,thevar.typecode(),dims2use)
+ originalvalue = thevar[:]
+ # Determine how to reshape
+ if lastdim == 0:
+ newVar[:] = originalvalue.reshape(time_length,ny,nx)
+ else:
+ newVar[:] = originalvalue.reshape(time_length,ny,nx,lastdim)
+
+
+filein.close()
+fileout.close()
Deleted: branches/land_ice_projects/grid_tools/covert_mpas_grid_to_regular_grid_netcdf.py
===================================================================
--- branches/land_ice_projects/grid_tools/covert_mpas_grid_to_regular_grid_netcdf.py 2012-03-06 23:13:46 UTC (rev 1599)
+++ branches/land_ice_projects/grid_tools/covert_mpas_grid_to_regular_grid_netcdf.py 2012-03-06 23:17:36 UTC (rev 1600)
@@ -1,82 +0,0 @@
-#!/usr/bin/python
-# Script to convert selected variables from an MPAS run and create a new netCDF file
-# that has those variables on a rectangular grid. The resulting gridded data appears
-# distorted but is adequate for quickly checking output. This is likely to only work
-# with grids created with periodic_hex where the order of cells in each 1d array (e.g. 'nCells')
-# is row by row (or is it column by column). This is a workaround to allow visualization
-# in, e.g. ncview since Paraview has some limitations as to which variables can be read in.
-# Currently, the script is setup to regrid any 2d and 3d variables that have dimensions of both Time
-# and nCells. The output file has the name 'converted.nc'. The output file is a little quirky,
-# but does work with ncview.
-
-import sys, os, glob, shutil, numpy
-from Scientific.IO.NetCDF import *
-# from NetCDF import *
-from optparse import OptionParser
-
-parser = OptionParser()
-parser.add_option("-f", "--file", dest="filename", help="file to convert", metavar="FILE")
-options, args = parser.parse_args()
-if not options.filename:
- parser.error("Filename is a required input.")
-
-# Get some information about the input file
-filein = NetCDFFile(options.filename,'r')
-# These need to be specified!!!! Perhaps these should be supplied as arguments on the command line
-nx = 30
-ny = 35
-times = filein.variables['xtime']
-time_length = times.shape[0]
-vert_levs = filein.dimensions['nVertLevels']
-
-# Define the new file to be output - this should be made a variant of the input file name
-fileout = NetCDFFile("converted.nc","w")
-# Create the new x,y dimensions for the new file
-fileout.createDimension('nx',nx)
-fileout.createDimension('ny',ny)
-# Copy over all the dimensions to the new file
-for dim in filein.dimensions.keys():
- # print 'DIMENSION: ', dim
- # print 'HAS VALUE: ', filein.dimensions[dim]
- fileout.createDimension(dim, filein.dimensions[dim])
-
-# Loop over all variables in file and find the ones we want to convert
-for var in filein.variables.keys():
- # print var
- thevar = filein.variables[var]
- dimflag = 0
- # Look for variables that have these two dimensions
- for dim in thevar.dimensions:
- if dim == 'nCells':
- # print ' has', dim
- dimflag += 1
- if dim == 'Time':
- # print ' has', dim
- dimflag += 1
- if dimflag == 2:
- # print ' HAS BOTH'
- # Convert this variable
- dims2use = ()
- lastdim = 0
- for dim in thevar.dimensions:
- if dim == 'nCells':
- dims2use = dims2use + ('ny', 'nx')
- else:
- dims2use = dims2use + (dim,)
- if dim == 'nVertLevels':
- lastdim = vert_levs
- elif dim == 'nVertLevelsPlus2':
- lastdim = vert_levs + 2
- # print dims2use
- # print thevar.typecode()
- newVar = fileout.createVariable(var,thevar.typecode(),dims2use)
- originalvalue = thevar[:]
- # Determine how to reshape
- if lastdim == 0:
- newVar[:] = originalvalue.reshape(time_length,ny,nx)
- else:
- newVar[:] = originalvalue.reshape(time_length,ny,nx,lastdim)
-
-
-filein.close()
-fileout.close()
</font>
</pre>