import re import logging from interp.grid import grid as basegrid, cell from subprocess import Popen, PIPE def get_qdelaunay_dump(g): """ pass in interp.grid g, and get back lines from a qhull triangulation: qdelaunay Qt f """ cmd = 'qdelaunay Qt f' p = Popen(cmd.split(), bufsize=1, stdin=PIPE, stdout=PIPE) so, se = p.communicate(g.for_qhull()) for i in so.splitlines(): yield i def get_qdelaunay_dump_str(g): return "\n".join(get_qdelaunay_dump(g)) def get_index_only(g): cmd = 'qdelaunay Qt i' p = Popen(cmd.split(), bufsize=1, stdin=PIPE, stdout=PIPE) so, se = p.communicate(g.for_qhull()) for i in so.splitlines(): yield i def get_index_only_str(g): return "\n".join(get_index_only(g)) class grid(basegrid): cell_re = re.compile(r''' -\s+(?Pf\d+).*? vertices:\s(?P.*?)\n.*? neighboring\s facets:\s+(?P[\sf\d]*) ''', re.S|re.X) point_re = re.compile(r''' -\s+(?Pp\d+).*? neighbors:\s+(?P[\sf\d]*) ''', re.S|re.X) vert_re = re.compile(r''' (p\d+) ''', re.S|re.X) def __init__(self, verts, q = None): basegrid.__init__(self, verts,q) def get_containing_simplex(self, X): if not self.cells: self.construct_connectivity() # get closest point (dist, indicies) = self.tree.query(X, 2) closest_point = indicies[0] logging.debug('X: %s' % X) logging.debug('point index: %d' % closest_point) logging.debug('actual point %s' % self.verts[closest_point]) logging.debug('distance = %0.4f' % dist[0]) simplex = None checked_cells = [] cells_to_check = self.cells_for_vert[closest_point] attempts = 0 while not simplex and cells_to_check: attempts += 1 # if attempts > 20: # raise Exception("probably recursing to many times") cur_cell = cells_to_check.pop(0) checked_cells.append(cur_cell) if cur_cell.contains(X, self): simplex = cur_cell continue for neighbor in cur_cell.neighbors: if (neighbor not in checked_cells) and (neighbor not in cells_to_check): cells_to_check.append(neighbor) if not simplex: raise Exception('no containing simplex found') R = self.create_mesh(simplex.verts) logging.debug('total attempts before finding simplex: %d' % attempts) return R def get_simplex_and_nearest_points(self, X, extra_points = 3, simplex_size = 3): """ this returns two grid objects: R and S. R is a grid object that is supposedly a containing simplex around point X (it tends not to be) S is S_j from baker's paper : some verts from all point that are not the simplex """ logging.debug("extra verts: %d" % extra_points) logging.debug("simplex size: %d" % simplex_size) r_mesh = self.get_containing_simplex(X) # logging.debug("R:\n%s" % r_mesh) # and some UNIQUE extra verts (dist, indicies) = self.tree.query(X, simplex_size + extra_points) unique_indicies = [] for index in indicies: if self.verts[index] not in r_mesh.verts: unique_indicies.append(index) logging.debug("indicies: %s" % ",".join([str(i) for i in indicies])) logging.debug("indicies: %s" % ",".join([str(i) for i in unique_indicies])) s_mesh = self.create_mesh(unique_indicies)# indicies[simplex_size:]) # TODO: eventually remove this test: for point in s_mesh.verts: if point in r_mesh.verts: logging.error("ERROR") logging.error("\n%s\nin\n%s" % (point, r_mesh)) raise Exception("repeating point S and R") return (r_mesh, s_mesh) def get_points_conn(self, X): """ this returns two grid objects: R and S. this function differes from the get_simplex_and_nearest_points function in that it builds up the extra verts based on connectivity information, not just nearest-neighbor. in theory, this will work much better for situations like verts near a short edge in a boundary layer cell where the nearest verts would all be colinear also, it guarantees that we find a containing simplex R is a grid object that is the (a) containing simplex around point X S is a connectivity-based nearest-neighbor lookup, limited to 3 extra verts """ if not self.cells: self.construct_connectivity() # get closest point (dist, indicies) = self.tree.query(X, 2) simplex = None for cell in self.cells_for_vert[indicies[0]]: if cell.contains(X, self): simplex = cell break if not simplex: raise AssertionError('no containing simplex found') # self.create_mesh(simplex.verts) R = self.get_containing_simplex(X) s = [] for c,i in enumerate(simplex.neighbors): s.extend([guy for guy in i.verts if not guy in simplex.verts]) S = self.create_mesh(s) return R, S def run_baker(self, X, extra_points = 3, order = 2): answer = None try: (R, S) = self.get_simplex_and_nearest_points(X) if not contains(X, R.verts): raise Exception("run_baker with get_simplex_and_nearest_points returned non-containing simplex") answer = run_baker(X, R, S, order) except Exception, e: logging.error("caught error: %s, trying with connectivity-based mesh" % e) (R, S) = self.get_points_conn(X) answer = run_baker(X, R, S, order) return answer def construct_connectivity(self): """ a call to this method prepares the internal connectivity structure. this is part of the __init__ for a rect_grid, but can be called from any grid object """ logging.debug('start') qdelaunay_string = get_qdelaunay_dump_str(self) with open('/tmp/qdel.out', 'w') as of: of.write(qdelaunay_string) cell_to_cells = [] for matcher in grid.cell_re.finditer(qdelaunay_string): d = matcher.groupdict() cell_name = d['cell'] verticies = d['verts'] neighboring_cells = d['neigh'] cur_cell = cell(cell_name) self.cells[cell_name] = cur_cell for v in grid.vert_re.findall(verticies): vertex_index = int(v[1:]) cur_cell.add_vert(vertex_index) self.cells_for_vert[vertex_index].append(cur_cell) nghbrs = [(cell_name, i) for i in neighboring_cells.split()] cell_to_cells.extend(nghbrs) logging.debug(cell_to_cells) for rel in cell_to_cells: if rel[1] in self.cells: self.cells[rel[0]].add_neighbor(self.cells[rel[1]]) logging.debug(self.cells) logging.debug('end')