def METHOD_NAME():
    # Parse command line arguements
    args = Args()
    progress(0, 1)
    dataset = Dataset(args.file(), 'r')
    dimPartitions = dataset.dimensions['partitions']
    dimElementSides = dataset.dimensions['element_sides']
    varElemSize = dataset.variables['element_size']
    varBoundaries = dataset.variables['element_boundaries']
    varNeighborSide = dataset.variables['element_neighbor_sides']
    varOrientation = dataset.variables['element_side_orientations']
    varNeighborRanks = dataset.variables['element_neighbor_ranks']
    # Known boundries
    boundaries = {1: 0, 3: 0, 5: 0}
    mpiDrBoundaries = 0
    local = [0]*4
    fluxes = [[[0]*3 for j in range(4)] for i in range(4)]
    for i in range(len(dimPartitions)):
        size = varElemSize[i]
        b = varBoundaries[i]
        n = varNeighborSide[i]
        o = varOrientation[i]
        r = varNeighborRanks[i]
        for j in xrange(size):
            for k in range(len(dimElementSides)):
                if b[j][k] == 0:
                    fluxes[k][n[j][k]][o[j][k]] += 1
                    local[k] += 1
                else:
                    boundaries[b[j][k]] += 1
                    if b[j][k] == 1:
                        local[k] += 2
                    elif b[j][k] == 3:
                        if r[j][k] != i:
                            mpiDrBoundaries += 1
                    elif b[j][k]:
                        local[k] += 1
        progress(i+1, len(dimPartitions))
    sys.stderr.write(' '*25+"\r") # Clear status bar
    print '# Boundary faces:'
    for b,n in boundaries.items():
        print str(b)+':', n
    print 'DR MPI boundary faces:', mpiDrBoundaries    
    print
    print 'Local matrices'
    for i in range(4):
        print str(i)+','+str(local[i])
    print 'local face,neighbor face,orientation'
    for i in range(4):
        for j in range(4):
            for k in range(3):
                print ','.join(map(str, [i, j, k]))+','+str(fluxes[i][j][k])
    dataset.close()