Source code for tvb.adapters.uploaders.obj.surface

# -*- coding: utf-8 -*-
#
#
# TheVirtualBrain-Framework Package. This package holds all Data Management, and 
# Web-UI helpful to run brain-simulations. To use it, you also need to download
# TheVirtualBrain-Scientific Package (for simulators). See content of the
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# (c) 2012-2023, Baycrest Centre for Geriatric Care ("Baycrest") and others
#
# This program is free software: you can redistribute it and/or modify it under the
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"""
.. moduleauthor:: Mihai Andrei <mihai.andrei@codemart.ro>
"""

import numpy as np
from tvb.adapters.uploaders.obj.parser import ObjParser
from tvb.basic.logger.builder import get_logger
from tvb.core.adapters.exceptions import ParseException


[docs] class ObjSurface(object): """ Represents a surface compatible with tvb. self.triangles , self.vertices , self.normals are numpy arrays shaped (n, 3) self.triangles contains indices. """ def __init__(self, obj_file): """ Create a surface from an obj file """ self.logger = get_logger(__name__) try: obj = ObjParser() obj.read(obj_file) self.triangles = [] self.vertices = obj.vertices self.normals = [(0.0, 0.0, 0.0)] * len(self.vertices) self.have_normals = len(obj.normals) for face in obj.faces: triangles = self._triangulate(face) for v_idx, t_idx, n_idx in triangles: self.triangles.append(v_idx) if n_idx != -1: # last normal index wins # alternative: self.normals[v_idx] += obj.normals[n_idx] # The correct behaviour is to duplicate the vertex # self.vertices.append(self.vertices[v_idx]) # self.tex_coords.append(self.tex_coords[v_idx]) self.normals[v_idx] = obj.normals[n_idx] # checks if not self.vertices or not self.triangles: raise ParseException("No geometry data in file.") self._to_numpy() except ValueError as ex: self.logger.exception(" Error in obj") raise ParseException(str(ex)) def _triangulate(self, face): """ Triangulate a quad. Higher order will get truncated. """ if len(face) > 4: self.logger.warning("truncated face to a quad") triangles = face[:3] if len(face) == 4: triangles += [face[0], face[2], face[3]] return triangles def _to_numpy(self): self.vertices = np.array(self.vertices) if self.have_normals: self.normals = np.array(self.normals) # normalise to unit vectors for k in range(len(self.normals)): self.normals[k, :] = self.normals[k, :] / np.sqrt(np.sum(self.normals[k, :] ** 2, axis=0)) else: self.normals = None self.triangles = np.array(self.triangles).reshape((len(self.triangles) // 3, 3))