# # Build (or retrieve) the initial region # if opts.refine or opts.prerefine: init_region, region_labels = amrlib.load_init_region(opts.refine or opts.prerefine, get_labels=True) else: ####### BEGIN INITIAL GRID CODE ######### init_region, idx = determine_region(pt, pts, ovrlp, opts.overlap_threshold, expand_prms) region_labels = intr_prms # FIXME: To be reimplemented in a different way #if opts.expand_param is not None: #expand_param(init_region, opts.expand_param) # TODO: Alternatively, check density of points in the region to determine # the points to a side grid, spacing = amrlib.create_regular_grid_from_cell(init_region, side_pts=5, return_cells=True) # "Deactivate" cells not close to template points # FIXME: This gets more and more dangerous in higher dimensions # FIXME: Move to function tree = BallTree(grid) if opts.deactivate: get_idx = set() for pt in pts[idx:]: get_idx.add(tree.query(pt, k=1, return_distance=False)[0][0]) selected = grid[numpy.array(list(get_idx))] else: selected = grid # Make sure all our dimensions line up # FIXME: We just need to be consistent from the beginning
opts.overlap_threshold, expand_prms) region_labels = intr_prms # FIXME: To be reimplemented in a different way #if opts.expand_param is not None: #expand_param(init_region, opts.expand_param) else: # Override initial region -- use with care _, init_region = common_cl.parse_param(opts.initial_region) region_labels = init_region.keys() init_region = amrlib.Cell( numpy.vstack(init_region[k] for k in region_labels)) # TODO: Alternatively, check density of points in the region to determine # the points to a side grid, spacing = amrlib.create_regular_grid_from_cell( init_region, side_pts=opts.points_per_side / 2, return_cells=True) # "Deactivate" cells not close to template points # FIXME: This gets more and more dangerous in higher dimensions # FIXME: Move to function tree = BallTree(grid) if opts.deactivate: get_idx = set() for pt in pts[idx:]: get_idx.add( tree.query(numpy.atleast_2d(pt), k=1, return_distance=False)[0][0]) selected = grid[numpy.array(list(get_idx))] else: selected = grid
init_region, region_labels = amrlib.load_init_region(opts.refine or opts.prerefine, get_labels=True) else: ####### BEGIN INITIAL GRID CODE ######### init_region, idx = determine_region(pt, pts, ovrlp, opts.overlap_threshold, expand_prms) region_labels = intr_prms # FIXME: To be reimplemented in a different way #if opts.expand_param is not None: #expand_param(init_region, opts.expand_param) # TODO: Alternatively, check density of points in the region to determine # the points to a side grid, spacing = amrlib.create_regular_grid_from_cell(init_region, side_pts=5, return_cells=True) # "Deactivate" cells not close to template points # FIXME: This gets more and more dangerous in higher dimensions # FIXME: Move to function tree = BallTree(grid) if opts.deactivate: get_idx = set() for pt in pts[idx:]: get_idx.add(tree.query(pt, k=1, return_distance=False)[0][0]) selected = grid[numpy.array(list(get_idx))] else: selected = grid # Make sure all our dimensions line up
####### BEGIN INITIAL GRID CODE ######### if opts.initial_region is None: init_region, idx = determine_region(pt, pts, ovrlp, opts.overlap_threshold, expand_prms) region_labels = intr_prms # FIXME: To be reimplemented in a different way #if opts.expand_param is not None: #expand_param(init_region, opts.expand_param) else: # Override initial region -- use with care _, init_region = common_cl.parse_param(opts.initial_region) region_labels = init_region.keys() init_region = amrlib.Cell(numpy.vstack(init_region[k] for k in region_labels)) # TODO: Alternatively, check density of points in the region to determine # the points to a side grid, spacing = amrlib.create_regular_grid_from_cell(init_region, side_pts=opts.points_per_side / 2, return_cells=True) # "Deactivate" cells not close to template points # FIXME: This gets more and more dangerous in higher dimensions # FIXME: Move to function tree = BallTree(grid) if opts.deactivate: get_idx = set() for pt in pts[idx:]: get_idx.add(tree.query(numpy.atleast_2d(pt), k=1, return_distance=False)[0][0]) selected = grid[numpy.array(list(get_idx))] else: selected = grid # Make sure all our dimensions line up # FIXME: We just need to be consistent from the beginning