pt_select = results > opts.overlap_threshold
selected = selected[pt_select]
results = results[pt_select]
grid, spacing = amrlib.refine_regular_grid(selected, spacing, return_cntr=True)
else:
grid, spacing = amrlib.refine_regular_grid(selected, spacing, return_cntr=opts.setup)
print "%d cells after refinement" % len(grid)
grid = amrlib.prune_duplicate_pts(grid, init_region._bounds, spacing)
#
# Clean up
#
grid = numpy.array(grid)
bounds_mask = amrlib.check_grid(grid, intr_prms, opts.distance_coordinates)
grid = grid[bounds_mask]
print "%d cells after bounds checking" % len(grid)
if len(grid) == 0:
exit("All cells would be removed by physical boundaries.")
# Convert back to physical mass
grid = amrlib.apply_inv_transform(grid, intr_prms, opts.distance_coordinates)
cells = amrlib.grid_to_cells(grid, spacing)
if opts.setup:
grid_group = amrlib.init_grid_hdf(init_region, opts.setup + ".hdf", opts.overlap_threshold, opts.distance_coordinates, intr_prms=intr_prms)
level = amrlib.save_grid_cells_hdf(grid_group, cells, "mass1_mass2", intr_prms=intr_prms)
else:
grp = amrlib.load_grid_level(opts.refine, None)
spacing,
return_cntr=True)
else:
grid, spacing = amrlib.refine_regular_grid(selected,
spacing,
return_cntr=opts.setup)
print "%d cells after refinement" % len(grid)
grid = amrlib.prune_duplicate_pts(grid, init_region._bounds, spacing)
#
# Clean up
#
grid = numpy.array(grid)
bounds_mask = amrlib.check_grid(grid, intr_prms, opts.distance_coordinates)
grid = grid[bounds_mask]
print "%d cells after bounds checking" % len(grid)
if len(grid) == 0:
exit("All cells would be removed by physical boundaries.")
# Convert back to physical mass
grid = amrlib.apply_inv_transform(grid, intr_prms, opts.distance_coordinates)
cells = amrlib.grid_to_cells(grid, spacing)
if opts.setup:
grid_group = amrlib.init_grid_hdf(init_region,
opts.setup + ".hdf",
opts.overlap_threshold,
opts.distance_coordinates,