90 lines
2.6 KiB
Python
90 lines
2.6 KiB
Python
import pickle
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from itertools import combinations
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from collections import defaultdict
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import numpy as np
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from scipy.spatial import KDTree
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from interp.grid import grid
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from interp.grid.simplex import face
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from interp.tools import exact_func
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class gmsh_grid(grid):
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THREE_NODE_TRIANGLE = 2
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def __init__(self, filename):
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"""
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construct an interp.grid.grid-compliant grid
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object out of a 2D gmsh file
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"""
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gmsh_file = open(filename, 'r')
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gmsh_file.readline() # $MeshFormat
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format = gmsh_file.readline()
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gmsh_file.readline() # $EndMeshFormat
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gmsh_file.readline() # $Nodes
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node_count = int(gmsh_file.readline())
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self.verts = np.empty((node_count, 3))
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self.q = np.empty(node_count)
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for i in xrange(node_count):
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cur_line = gmsh_file.readline()
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(index, x,y,z) = cur_line.split()
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index = int(index) - 1
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self.verts[i][0] = float(x)
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self.verts[i][1] = float(y)
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self.verts[i][2] = float(z)
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self.q[i] = exact_func(self.verts[i])
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grid.__init__(self)
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gmsh_file.readline() # $EndNodes
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gmsh_file.readline() # $Elements
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# temporary dict used to compute face connectivity
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neighbors = {}
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element_count = int(gmsh_file.readline())
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for i in xrange(element_count):
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cur_line = gmsh_file.readline()
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cur_line = cur_line.split()
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cur_face_index, node_type, rest = (int(cur_line[0]),
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int(cur_line[1]),
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[int(j) for j in cur_line[2:]])
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if(node_type == gmsh_grid.THREE_NODE_TRIANGLE):
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points_for_cur_face = [i-1 for i in rest[rest[0]+1:]]
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cur_face = face(cur_face_index)
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for cur_point in points_for_cur_face:
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self.faces_for_vert[cur_point].append(cur_face)
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cur_face.verts = points_for_cur_face
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self.faces[cur_face_index] = cur_face
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edges = [tuple(sorted(i)) for i in combinations(points_for_cur_face, 2)]
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# edge is two verts
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for edge in edges:
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if edge in neighbors:
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neighbors[edge].append(cur_face_index)
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else:
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neighbors[edge] = [cur_face_index]
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for k,v in neighbors.iteritems():
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if len(v) > 1:
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self.faces[v[0]].add_neighbor(self.faces[v[1]])
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self.faces[v[1]].add_neighbor(self.faces[v[0]])
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def dump_to_blender_files(self, pfile = '/tmp/points.p', ffile = '/tmp/faces.p'):
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pickle.dump([(p[0], p[1], p[2]) for p in self.verts], open(pfile, 'w'))
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pickle.dump([f.verts for f in self.faces.itervalues()], open(ffile, 'w'))
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