Source code for yggdrasil.metaschema.datatypes.ObjMetaschemaType

import os
import copy
import numpy as np
import warnings
from yggdrasil import tools
from yggdrasil.metaschema.encoder import encode_json, decode_json
from yggdrasil.metaschema.datatypes import _schema_dir
from yggdrasil.metaschema.datatypes.JSONObjectMetaschemaType import (
    JSONObjectMetaschemaType)
from yggdrasil.metaschema.datatypes.PlyMetaschemaType import (
    trimesh, PlyDict,
    _index_type, _color_type, _coord_type,
    _index_conv, _color_conv, _coord_conv,
    _index_fmt, _color_fmt, _coord_fmt)


# TODO: Add support for groups
    

_schema_file = os.path.join(_schema_dir, 'obj.json')
_default_element_order = ['material', 'vertices', 'params', 'normals', 'texcoords',
                          'points', 'lines', 'faces', 'curves', 'curve2Ds', 'surfaces']
# TODO: Unclear what standard puts colors after coords and how that is
# reconciled with the weight (i.e. do colors go before or after weight)
_default_property_order = {
    'vertices': ['x', 'y', 'z', 'red', 'green', 'blue', 'w'],
    'params': ['u', 'v', 'w'],
    'normals': ['i', 'j', 'k'],
    'texcoords': ['u', 'v', 'w'],
    'points': 'vertex_indices',
    'lines': ('vertex_index', 'texcoord_index'),
    'faces': ('vertex_index', 'texcoord_index', 'normal_index'),
    'curves': ['starting_param', 'ending_param', ['vertex_indices']],
    'curve2Ds': 'param_indices',
    'surfaces': ['starting_param_u', 'ending_param_u',
                 'starting_param_v', 'ending_param_v',
                 {'vertex_indices': ('vertex_index', 'texcoord_index', 'normal_index')}]}
_index_properties = ['vertex_indices', 'vertex_index', 'texcoord_index',
                     'normal_index', 'param_indices']
_default_property_formats = {}
_default_property_converters = {}
for k in ['x', 'y', 'z', 'u', 'v', 'w', 'i', 'j', 'k',
          'starting_param', 'ending_param',
          'starting_param_u', 'ending_param_u',
          'starting_param_v', 'ending_param_v']:
    _default_property_formats[k] = _coord_fmt
    _default_property_converters[k] = _coord_conv
for k in ['red', 'green', 'blue']:
    _default_property_formats[k] = _color_fmt
    _default_property_converters[k] = _color_conv
for k in ['vertex_index', 'texcoord_index', 'normal_index', 'param_index',
          'vertex_indices', 'param_indices']:
    _default_property_formats[k] = _index_fmt
    _default_property_converters[k] = _index_conv
_map_element2code = {'material': 'usemtl', 'vertices': 'v',
                     'params': 'vp', 'normals': 'vn', 'texcoords': 'vt',
                     'points': 'p', 'lines': 'l', 'faces': 'f',
                     'curves': 'curv', 'curve2Ds': 'curv2', 'surfaces': 'surf'}
_map_code2element = {v: k for k, v in _map_element2code.items()}


[docs]def create_schema(overwrite=False): r"""Creates a file containing the Obj schema. Args: overwrite (bool, optional): If True and a file already exists, the existing file will be replaced. If False, an error will be raised if the file already exists. """ if (not overwrite) and os.path.isfile(_schema_file): raise RuntimeError("Schema file already exists.") schema = { 'title': 'obj', 'description': 'A mapping container for Obj 3D data.', 'type': 'object', 'required': ['vertices', 'faces'], 'definitions': { 'vertex': { 'description': 'Map describing a single vertex.', 'type': 'object', 'required': ['x', 'y', 'z'], 'additionalProperties': False, 'properties': {'x': {'type': _coord_type}, 'y': {'type': _coord_type}, 'z': {'type': _coord_type}, 'red': {'type': _color_type}, 'blue': {'type': _color_type}, 'green': {'type': _color_type}, 'w': {'type': _coord_type, 'default': 1.0}}}, 'param': { 'description': 'Map describing a single parameter space point.', 'type': 'object', 'required': ['u', 'v'], 'additionalProperties': False, 'properties': {'u': {'type': _coord_type}, 'v': {'type': _coord_type}, 'w': {'type': _coord_type, 'default': 1.0}}}, 'normal': { 'description': 'Map describing a single normal.', 'type': 'object', 'required': ['i', 'j', 'k'], 'additionalProperties': False, 'properties': {'i': {'type': _coord_type}, 'j': {'type': _coord_type}, 'k': {'type': _coord_type}}}, 'texcoord': { 'description': 'Map describing a single texture vertex.', 'type': 'object', 'required': ['u'], 'additionalProperties': False, 'properties': {'u': {'type': _coord_type}, 'v': {'type': _coord_type, 'default': 0.0}, 'w': {'type': _coord_type, 'default': 0.0}}}, 'point': { 'description': 'Array of vertex indices describing a set of points.', 'type': 'array', 'minItems': 1, 'items': {'type': _index_type}}, 'line': { 'description': ('Array of vertex indices and texture indices ' + 'describing a line.'), 'type': 'array', 'minItems': 2, 'items': {'type': 'object', 'required': ['vertex_index'], 'additionalProperties': False, 'properties': {'vertex_index': {'type': _index_type}, 'texcoord_index': {'type': _index_type}}}}, 'face': { 'description': ('Array of vertex, texture, and normal indices ' + 'describing a face.'), 'type': 'array', 'minItems': 3, 'items': {'type': 'object', 'required': ['vertex_index'], 'additionalProperties': False, 'properties': {'vertex_index': {'type': _index_type}, 'texcoord_index': {'type': _index_type}, 'normal_index': {'type': _index_type}}}}, 'curve': { 'description': 'Properties of describing a curve.', 'type': 'object', 'required': ['starting_param', 'ending_param', 'vertex_indices'], 'additionalProperties': False, 'properties': { 'starting_param': {'type': _coord_type}, 'ending_param': {'type': _coord_type}, 'vertex_indices': { 'type': 'array', 'minItems': 2, 'items': {'type': _index_type}}}}, 'curve2D': { 'description': ('Array of parameter indices describine a 2D curve on ' + 'a surface.'), 'type': 'array', 'minItems': 2, 'items': {'type': _index_type}}, 'surface': { 'description': 'Properties describing a surface.', 'type': 'object', 'required': ['starting_param_u', 'ending_param_u', 'starting_param_v', 'ending_param_v', 'vertex_indices'], 'additionalProperties': False, 'properties': { 'starting_param_u': {'type': _coord_type}, 'ending_param_u': {'type': _coord_type}, 'starting_param_v': {'type': _coord_type}, 'ending_param_v': {'type': _coord_type}, 'vertex_indices': { 'type': 'array', 'minItems': 2, 'items': {'type': 'object', 'required': ['vertex_index'], 'additionalProperties': False, 'properties': { 'vertex_index': {'type': _index_type}, 'texcoord_index': {'type': _index_type}, 'normal_index': {'type': _index_type}}}}}}}, 'properties': { 'material': { 'description': 'Name of the material to use.', 'type': ['unicode', 'string']}, 'vertices': { 'description': 'Array of vertices.', 'type': 'array', 'items': {'$ref': '#/definitions/vertex'}}, 'params': { 'description': 'Array of parameter coordinates.', 'type': 'array', 'items': {'$ref': '#/definitions/param'}}, 'normals': { 'description': 'Array of normals.', 'type': 'array', 'items': {'$ref': '#/definitions/normal'}}, 'texcoords': { 'description': 'Array of texture vertices.', 'type': 'array', 'items': {'$ref': '#/definitions/texcoord'}}, 'points': { 'description': 'Array of points.', 'type': 'array', 'items': {'$ref': '#/definitions/point'}}, 'lines': { 'description': 'Array of lines.', 'type': 'array', 'items': {'$ref': '#/definitions/line'}}, 'faces': { 'description': 'Array of faces.', 'type': 'array', 'items': {'$ref': '#/definitions/face'}}, 'curves': { 'description': 'Array of curves.', 'type': 'array', 'items': {'$ref': '#/definitions/curve'}}, 'curve2Ds': { 'description': 'Array of curve2Ds.', 'type': 'array', 'items': {'$ref': '#/definitions/curve2D'}}, 'surfaces': { 'description': 'Array of surfaces.', 'type': 'array', 'items': {'$ref': '#/definitions/surface'}}}, 'dependencies': { 'lines': ['vertices'], 'faces': ['vertices'], 'curves': ['vertices'], 'curve2Ds': ['params'], 'surfaces': ['vertices']}} with open(_schema_file, 'w') as fd: encode_json(schema, fd, indent='\t')
[docs]def get_schema(): r"""Return the Obj schema, initializing it if necessary. Returns: dict: Obj schema. """ if not os.path.isfile(_schema_file): create_schema() with open(_schema_file, 'r') as fd: out = decode_json(fd) return out
if not os.path.isfile(_schema_file): # pragma: debug create_schema()
[docs]class ObjDict(PlyDict): r"""Enhanced dictionary class for storing Obj information."""
[docs] @classmethod def from_array_dict(cls, in_dict): r"""Get a version of the object from a dictionary of arrays.""" kws = {} for k in ['material', 'vertices', 'params', 'normals', 'texcoords', 'lines', 'faces', 'points', 'curves', 'curve2Ds', 'surfaces']: if k in in_dict: kws[k] = copy.deepcopy(in_dict[k]) if isinstance(kws.get('vertices', None), np.ndarray): old_vert = kws['vertices'] nvert = old_vert.shape[1] assert(nvert in (3, 4)) kws['vertices'] = [ {k: old_vert[i, j] for j, k in enumerate('xyzw'[:nvert]) if ((j < 3) or (not np.isnan(old_vert[i, j])))} for i in range(old_vert.shape[0])] if isinstance(in_dict.get('vertex_colors', None), np.ndarray): old_colr = in_dict['vertex_colors'] assert(old_colr.shape == (len(kws['vertices']), 3)) for i in range(old_colr.shape[0]): for j, k in enumerate(['red', 'green', 'blue']): kws['vertices'][i][k] = old_colr[i, j] if isinstance(kws.get('params', None), np.ndarray): old_parm = kws['params'] nparm = old_parm.shape[1] assert(nparm in [2, 3]) kws['params'] = [ {k: old_parm[i, j] for j, k in enumerate('uvw'[:nparm]) if ((j < 2) or (not np.isnan(old_parm[i, j])))} for i in range(old_parm.shape[0])] if isinstance(kws.get('normals', None), np.ndarray): old_norm = kws['normals'] assert(old_norm.shape[1] == 3) kws['normals'] = [ {k: old_norm[i, j] for j, k in enumerate('ijk')} for i in range(old_norm.shape[0])] if isinstance(kws.get('texcoords', None), np.ndarray): old_texc = kws['texcoords'] ntexc = old_texc.shape[1] assert(ntexc in [1, 2, 3]) kws['texcoords'] = [ {k: old_texc[i, j] for j, k in enumerate('uvw'[:ntexc]) if ((j < 1) or (not np.isnan(old_texc[i, j])))} for i in range(old_texc.shape[0])] # Composites of above if isinstance(kws.get('lines', None), np.ndarray): old_edge = kws['lines'] assert(old_edge.shape[1] == 2) kws['lines'] = [ [{'vertex_index': np.int32(old_edge[i, j])} for j in range(old_edge.shape[1]) if (not np.isnan(old_edge[i, j]))] for i in range(old_edge.shape[0])] if isinstance(kws.get('faces', None), np.ndarray): old_face = kws['faces'] assert(old_face.shape[1] >= 3) kws['faces'] = [ [{'vertex_index': np.int32(old_face[i, j])} for j in range(old_face.shape[1]) if (not np.isnan(old_face[i, j]))] for i in range(old_face.shape[0])] if isinstance(in_dict.get('face_texcoords', None), np.ndarray): old_texc = in_dict['face_texcoords'] assert(old_texc.shape[0] == len(kws.get('faces', []))) for i in range(old_texc.shape[0]): for j in range(old_texc.shape[1]): if not np.isnan(old_texc[i, j]): kws['faces'][i][j]['texcoord_index'] = np.int32( old_texc[i, j]) if isinstance(in_dict.get('face_normals', None), np.ndarray): old_norm = in_dict['face_normals'] assert(old_norm.shape[0] == len(kws.get('faces', []))) for i in range(old_norm.shape[0]): for j in range(old_norm.shape[1]): if not np.isnan(old_norm[i, j]): kws['faces'][i][j]['normal_index'] = np.int32( old_norm[i, j]) if isinstance(kws.get('points', None), np.ndarray): old_pnts = kws['points'] kws['points'] = [ [np.int32(old_pnts[i, j]) for j in range(old_pnts.shape[1]) if (not np.isnan(old_pnts[i, j]))] for i in range(old_pnts.shape[0])] if isinstance(kws.get('curves', None), np.ndarray): old_curv = kws['curves'] kws['curves'] = [ {'vertex_indices': [ np.int32(old_curv[i, j]) for j in range(old_curv.shape[1]) if (not np.isnan(old_curv[i, j]))]} for i in range(old_curv.shape[0])] assert('curve_params' in in_dict) if isinstance(in_dict['curve_params'], np.ndarray): old_parm = in_dict['curve_params'] assert(old_parm.shape == (len(kws['curves']), 2)) for i in range(old_parm.shape[0]): kws['curves'][i]['starting_param'] = old_parm[i, 0] kws['curves'][i]['ending_param'] = old_parm[i, 1] if isinstance(kws.get('curve2Ds', None), np.ndarray): old_curv = kws['curve2Ds'] kws['curve2Ds'] = [ [np.int32(old_curv[i, j]) for j in range(old_curv.shape[1]) if (not np.isnan(old_curv[i, j]))] for i in range(old_curv.shape[0])] if isinstance(kws.get('surfaces', None), np.ndarray): old_surf = kws['surfaces'] kws['surfaces'] = [ {'vertex_indices': [ {'vertex_index': np.int32(old_surf[i, j])} for j in range(old_surf.shape[1]) if (not np.isnan(old_surf[i, j]))]} for i in range(old_surf.shape[0])] assert('surface_params' in in_dict) if isinstance(in_dict['surface_params'], np.ndarray): old_parm = in_dict['surface_params'] assert(old_parm.shape == (len(kws['surfaces']), 4)) for i in range(old_parm.shape[0]): kws['surfaces'][i]['starting_param_u'] = old_parm[i, 0] kws['surfaces'][i]['ending_param_u'] = old_parm[i, 1] kws['surfaces'][i]['starting_param_v'] = old_parm[i, 2] kws['surfaces'][i]['ending_param_v'] = old_parm[i, 3] if isinstance(in_dict.get('surface_texcoords', None), np.ndarray): old_texc = in_dict['surface_texcoords'] assert(old_texc.shape[0] == len(kws['surfaces'])) for i in range(old_texc.shape[0]): for j in range(old_texc.shape[1]): if not np.isnan(old_texc[i, j]): kws['surfaces'][i]['vertex_indices'][j][ 'texcoord_index'] = np.int32(old_texc[i, j]) if isinstance(in_dict.get('surface_normals', None), np.ndarray): old_norm = in_dict['surface_normals'] assert(old_norm.shape[0] == len(kws['surfaces'])) for i in range(old_norm.shape[0]): for j in range(old_norm.shape[1]): if not np.isnan(old_norm[i, j]): kws['surfaces'][i]['vertex_indices'][j][ 'normal_index'] = np.int32(old_norm[i, j]) return cls.from_dict(kws)
[docs] def as_array_dict(self): r"""Get a version of the object as a dictionary of arrays.""" out = {} if self.get('material', None): out['material'] = self['material'] if self.get('vertices', None): out['vertices'] = np.asarray( [[v.get(k, np.NaN) for k in 'xyzw'] for v in self['vertices']]) out['vertex_colors'] = np.asarray( [[v.get(k, np.NaN) for k in ['red', 'green', 'blue']] for v in self['vertices']]) if np.all(np.isnan(out['vertices'][:, 3])): out['vertices'] = out['vertices'][:, :3] if np.all(np.isnan(out['vertex_colors'])): out.pop('vertex_colors') if self.get('params', None): out['params'] = np.asarray( [[v.get(k, np.NaN) for k in 'uvw'] for v in self['params']]) if np.all(np.isnan(out['params'][:, 2])): out['params'] = out['params'][:, :2] if self.get('normals', None): out['normals'] = np.asarray( [[v[k] for k in 'ijk'] for v in self['normals']]) if self.get('texcoords', None): out['texcoords'] = np.asarray( [[v.get(k, np.NaN) for k in 'uvw'] for v in self['texcoords']]) if np.all(np.isnan(out['texcoords'][:, 1:])): out['texcoords'] = out['texcoords'][:, :1] elif np.all(np.isnan(out['texcoords'][:, 2])): out['texcoords'] = out['texcoords'][:, :2] if self.get('lines', None): out['lines'] = np.NaN * np.ones( (len(self['lines']), len(max(self['lines'], key=len))), dtype='int32') for i, vlist in enumerate(self['lines']): for j, v in enumerate(vlist): out['lines'][i, j] = v['vertex_index'] if self.get('faces', None): face_shp = (len(self['faces']), len(max(self['faces'], key=len))) out['faces'] = np.NaN * np.ones(face_shp, dtype='int32') out['face_texcoords'] = np.NaN * np.ones(face_shp, dtype='int32') out['face_normals'] = np.NaN * np.ones(face_shp, dtype='int32') for i, vlist in enumerate(self['faces']): for j, v in enumerate(vlist): out['faces'][i, j] = v['vertex_index'] out['face_texcoords'][i, j] = v.get( 'texcoord_index', np.NaN) out['face_normals'][i, j] = v.get('normal_index', np.NaN) if np.all(np.isnan(out['face_texcoords'])): out.pop('face_texcoords') if np.all(np.isnan(out['face_normals'])): out.pop('face_normals') if self.get('points', None): out['points'] = np.NaN * np.ones( (len(self['points']), len(max(self['points'], key=len))), dtype='int32') for i, vlist in enumerate(self['points']): out['points'][i, :len(vlist)] = vlist if self.get('curves', None): def fkey(x): return len(x['vertex_indices']) out['curves'] = np.NaN * np.ones( (len(self['curves']), len(max(self['curves'], key=fkey))), dtype='int32') out['curve_params'] = np.zeros((out['curves'].shape[0], 2)) for i, curv in enumerate(self['curves']): out['curve_params'][i, :] = [curv['starting_param'], curv['ending_param']] out['curves'][i, :fkey(curv)] = curv['vertex_indices'] if self.get('curve2Ds', None): out['curve2Ds'] = np.NaN * np.ones( (len(self['curve2Ds']), len(max(self['curve2Ds'], key=len))), dtype='int32') for i, vlist in enumerate(self['curve2Ds']): out['curve2Ds'][i, :len(vlist)] = vlist if self.get('surfaces', None): def fkey(x): return len(x['vertex_indices']) surf_shp = (len(self['surfaces']), len(max(self['surfaces'], key=fkey))) out['surfaces'] = np.NaN * np.ones(surf_shp, dtype='int32') out['surface_params'] = np.zeros((surf_shp[0], 4)) out['surface_texcoords'] = np.NaN * np.ones(surf_shp, dtype='int32') out['surface_normals'] = np.NaN * np.ones(surf_shp, dtype='int32') for i, surf in enumerate(self['surfaces']): out['surface_params'][i, :] = [surf['starting_param_u'], surf['ending_param_u'], surf['starting_param_v'], surf['ending_param_v']] for j, v in enumerate(surf['vertex_indices']): out['surfaces'][i, j] = v['vertex_index'] out['surface_texcoords'][i, j] = v.get( 'texcoord_index', np.NaN) out['surface_normals'][i, j] = v.get( 'normal_index', np.NaN) if np.all(np.isnan(out['surface_texcoords'])): out.pop('surface_texcoords') if np.all(np.isnan(out['surface_normals'])): out.pop('surface_normals') return out
[docs] @classmethod def from_trimesh(cls, in_mesh): r"""Get a version of the object from a trimesh class.""" kws = dict(vertices=in_mesh.vertices, vertex_colors=in_mesh.visual.vertex_colors, faces=in_mesh.faces.astype('int32')) weights = (kws['vertex_colors'][:, 3].astype('float32') + 1.0) / 256 weights[weights == 1.0] = np.NaN kws['vertex_colors'] = kws['vertex_colors'][:, :3] kws['vertices'] = np.hstack([kws['vertices'], weights[..., None]]) return cls.from_array_dict(kws)
[docs] def as_trimesh(self, **kwargs): r"""Get a version of the object as a trimesh class.""" kws0 = self.as_array_dict() kws = {'vertices': kws0.get('vertices', None), 'vertex_colors': kws0.get('vertex_colors', None), 'faces': kws0.get('faces', None)} if (kws['vertices'] is not None) and (kws['vertices'].shape[1] == 4): weights = kws['vertices'][:, 3] * 256 - 1.0 weights[np.isnan(weights)] = 255 kws['vertices'] = kws['vertices'][:, :3] if kws['vertex_colors'] is not None: kws['vertex_colors'] = np.hstack( [kws['vertex_colors'], weights[..., None]]) kws.update(kwargs, process=False) return trimesh.base.Trimesh(**kws)
@property def mesh(self): r"""list: Vertices for each face in the structure.""" mesh = [] for f in self['faces']: imesh = [] for v in f: imesh.append([self['vertices'][v['vertex_index']][k] for k in ['x', 'y', 'z']]) mesh.append(imesh) return mesh @property def vertex_normals(self): mesh = None if 'normals' in self: mesh = [] for f in self['faces']: imesh = [] for v in f: imesh.append([self['normals'][v['normal_index']][k] for k in ['i', 'j', 'k']]) mesh.append(imesh) return mesh
[docs] @classmethod def from_shape(cls, shape, d, conversion=1.0): # pragma: lpy r"""Create a ply dictionary from a PlantGL shape and descritizer. Args: scene (openalea.plantgl.scene): Scene that should be descritized. d (openalea.plantgl.descritizer): Descritizer. conversion (float, optional): Conversion factor that should be applied to the vertex positions. Defaults to 1.0. """ iobj = super(ObjDict, cls).from_shape(shape, d, conversion=conversion, _as_obj=True) if iobj is not None: # Texcoords if d.result.texCoordList: iobj.setdefault('texcoords', []) for t in d.result.texCoordList: # TODO: Should the coords be scaled? iobj['texcoords'].append({'u': t.x, 'v': t.y}) if d.result.texCoordIndexList: for i, t in enumerate(d.result.texCoordIndexList): if t[0] < len(iobj['texcoords']): for j in range(3): iobj['faces'][i][j]['texcoord_index'] = t[j] # Normals if d.result.normalList: iobj.setdefault('normals', []) for n in d.result.normalList: iobj['normals'].append({'i': n.x, 'j': n.y, 'k': n.z}) if d.result.normalIndexList: for i, n in enumerate(d.result.normalIndexList): if n[0] < len(iobj['normals']): for j in range(3): iobj['faces'][i][j]['normal_index'] = n[j] return iobj
[docs] def to_geom_args(self, conversion=1.0, name=None): # pragma: lpy r"""Get arguments for creating a PlantGL geometry. Args: conversion (float, optional): Conversion factor that should be applied to the vertices. Defaults to 1.0. name (str, optional): Name that should be given to the created PlantGL symbol. Defaults to None and is ignored. Returns: tuple: Class, arguments and keyword arguments for PlantGL geometry. """ import openalea.plantgl.all as pgl smb_class, args, kwargs = super(ObjDict, self).to_geom_args( conversion=conversion, name=name, _as_obj=True) index_class = pgl.Index array_class = pgl.IndexArray # Texture coords if self.get('texcoords', []): obj_texcoords = [] for t in self['texcoords']: obj_texcoords.append(pgl.Vector2(np.float64(t['u']), np.float64(t.get('v', 0.0)))) kwargs['texCoordList'] = pgl.Point2Array(obj_texcoords) obj_ftexcoords = [] for i, f in enumerate(self['faces']): entry = [] for _f in f: if 'texcoord_index' not in _f: if i > 0: # pragma: debug warnings.warn(("'texcoord_index' missing from face" + "%d, texcoord indices will be " + "ignored.") % i) obj_ftexcoords = [] entry = [] break entry.append(int(_f['texcoord_index'])) if not entry: break obj_ftexcoords.append(index_class(*entry)) if obj_ftexcoords: kwargs['texCoordIndexList'] = array_class(obj_ftexcoords) # Normals if self.get('normals', []): obj_normals = [] for n in self['normals']: obj_normals.append(pgl.Vector3(np.float64(n['i']), np.float64(n['j']), np.float64(n['k']))) kwargs['normalList'] = pgl.Point3Array(obj_normals) obj_fnormals = [] for i, f in enumerate(self['faces']): entry = [] for _f in f: if 'normal_index' not in _f: if i > 0: # pragma: debug warnings.warn(("'normal_index' missing from face" + "%d, normal indices will be " + "ignored.") % i) obj_fnormals = [] entry = [] break entry.append(int(_f['normal_index'])) if not entry: break obj_fnormals.append(index_class(*entry)) if obj_fnormals: kwargs['normalIndexList'] = array_class(obj_fnormals) return smb_class, args, kwargs
[docs] def append(self, solf): r"""Append new ply information to this dictionary. Args: solf (ObjDict): Another ply to append to this one. """ exist_map = {'vertex_index': len(self.get('vertices', [])), 'texcoord_index': len(self.get('texcoords', [])), 'normal_index': len(self.get('normals', [])), 'param_index': len(self.get('params', []))} exist_map.update(points=exist_map['vertex_index'], curve2Ds=exist_map['param_index']) # Vertex fields for k in ['vertices', 'texcoords', 'normals', 'params']: if k in solf: if k not in self: self[k] = [] self[k] += solf[k] # Points/2D curves for k in ['points', 'curve2Ds']: if k in solf: if k not in self: self[k] = [] for x in solf[k]: self[k].append([v + exist_map[k] for v in x]) # Face/line fields for k in ['lines', 'faces']: if k in solf: if k not in self: self[k] = [] for x in solf[k]: iele = [{ik: v[ik] + exist_map[ik] for ik in v.keys()} for v in x] self[k].append(iele) # Curves k = 'curves' if k in solf: if k not in self: self[k] = [] for x in solf[k]: iele = copy.deepcopy(x) iele['vertex_indices'] = [v + exist_map['vertex_index'] for v in x['vertex_indices']] # Surfaces k = 'surfaces' if k in solf: if k not in self: self[k] = [] for x in solf[k]: iele = copy.deepcopy(x) iele['vertex_indices'] = [{ik: v[ik] + exist_map[ik] for ik in v.keys()} for v in x['vertex_indices']] # Merge material using first in list material = None for x in [self, solf]: if x.get('material', None) is not None: material = x['material'] break if material is not None: self['material'] = material return self
[docs] def apply_scalar_map(self, *args, **kwargs): r"""Set the color of faces in a 3D object based on a scalar map. This creates a copy unless no_copy is True. Args: scalar_arr (arr): Scalar values that should be mapped to colors for each face. color_map (str, optional): The name of the color map that should be used. Defaults to 'plasma'. vmin (float, optional): Value that should map to the minimum of the colormap. Defaults to min(scalar_arr). vmax (float, optional): Value that should map to the maximum of the colormap. Defaults to max(scalar_arr). scaling (str, optional): Scaling that should be used to map the scalar array onto the colormap. Defaults to 'linear'. scale_by_area (bool, optional): If True, the elements of the scalar array will be multiplied by the area of the corresponding face. If True, vmin and vmax should be in terms of the scaled array. Defaults to False. no_copy (bool, optional): If True, the returned object will not be a copy. Defaults to False. Returns: dict: Obj with updated vertex colors. """ kwargs['_as_obj'] = True return super(ObjDict, self).apply_scalar_map(*args, **kwargs)
if trimesh: python_types = (dict, ObjDict, trimesh.base.Trimesh) else: python_types = (dict, ObjDict) # The base class could be anything since it is discarded during registration, # but is set to JSONObjectMetaschemaType here for transparancy since this is # what the base class is determined to be on loading the schema
[docs]class ObjMetaschemaType(JSONObjectMetaschemaType): r"""Obj 3D structure map.""" _empty_msg = {'vertices': [], 'faces': []} python_types = python_types schema_file = _schema_file _replaces_existing = False @classmethod def _encode_object_property(cls, obj, order, req_keys=False): if req_keys: sep = '/' else: sep = ' ' plist = [] if isinstance(obj, (list, tuple)): for x in obj: plist.append(cls._encode_object_property(x, order, req_keys=True)) return sep.join(plist) elif isinstance(obj, dict): for i, k in enumerate(order): if isinstance(k, dict): assert(len(k) == 1) ksub = list(k.keys())[0] if ksub in obj: plist.append(cls._encode_object_property(obj[ksub], k[ksub])) elif isinstance(k, (list, tuple)): assert(len(k) == 1) ksub = k[0] if ksub in obj: plist.append(cls._encode_object_property(obj[ksub], ksub)) else: if k in obj: plist.append(cls._encode_object_property(obj[k], k)) elif req_keys: plist.append('') return sep.join(plist) else: if order in _index_properties: # Add one at write to indexes as .obj is not zero indexed return _default_property_formats[order] % (obj + 1) else: return _default_property_formats[order] % obj @classmethod def _decode_object_property(cls, values, order): if isinstance(values, (list, tuple)): if not isinstance(order, (list, tuple)): out = [cls._decode_object_property(v, order) for v in values] elif (len(values) > 0) and ('/' in values[0]) or isinstance(order, tuple): out = [cls._decode_object_property(v, order) for v in values] else: out = {} for i, (o, v) in enumerate(zip(order, values)): if not v: continue if isinstance(o, dict): assert(len(o) == 1) osub = list(o.keys())[0] out[osub] = cls._decode_object_property(values[i:], o[osub]) break elif isinstance(o, (list, tuple)): assert(len(o) == 1) osub = o[0] out[osub] = cls._decode_object_property(values[i:], osub) else: out[o] = cls._decode_object_property(v, o) else: if not isinstance(order, (list, tuple)): ftranslate = _default_property_converters[order] out = ftranslate(values) if order in _index_properties: # Subtract 1 from indexes because .obj is not zero indexed out -= 1 elif '/' in values: subvalues = values.split('/') assert(isinstance(order, tuple)) assert(len(order) == len(subvalues)) out = cls._decode_object_property(subvalues, list(order)) else: out = cls._decode_object_property([values], [order[0]]) return out
[docs] @classmethod def encode_data(cls, obj, typedef, comments=[], newline='\n'): r"""Encode an object's data. Args: obj (object): Object to encode. typedef (dict): Type definition that should be used to encode the object. comments (list, optional): List of comments that should be included in the file header. Defaults to lines describing the automated origin of the file. newline (str, optional): String that should be used to delineated end of lines. Defaults to '\n'. Returns: bytes, str: Serialized message. """ if trimesh and isinstance(obj, trimesh.base.Trimesh): obj = ObjDict.from_trimesh(obj) # Encode header header = ['# Author ygg_auto', '# Generated by yggdrasil'] header += ['# ' + c for c in comments] header += [''] # Encode body body = [] for e in _default_element_order: if (e not in obj): continue if (e == 'material'): body.append('%s %s' % (_map_element2code[e], obj['material'])) continue for ie in obj[e]: ivalue = cls._encode_object_property(ie, _default_property_order[e]) iline = '%s %s' % (_map_element2code[e], ivalue) body.append(iline.strip()) # Ensure trailing spaces are removed return newline.join(header + body) + newline
[docs] @classmethod def encode_data_readable(cls, obj, typedef): r"""Encode an object's data in a readable format. Args: obj (object): Object to encode. typedef (dict): Type definition that should be used to encode the object. Returns: string: Encoded object. """ return cls.encode_data(obj, typedef)
[docs] @classmethod def decode_data(cls, msg, typedef): r"""Decode an object. Args: msg (string): Encoded object to decode. typedef (dict): Type definition that should be used to decode the object. Returns: object: Decoded object. """ msg = tools.bytes2str(msg) lines = msg.splitlines() metadata = {'comments': []} out = {} # Parse for line_count, line in enumerate(lines): if line.startswith('#'): metadata['comments'].append(line) continue values = line.split() if not values: continue if values[0] not in _map_code2element: raise ValueError("Type code '%s' on line %d not understood" % (values[0], line_count)) e = _map_code2element[values[0]] if e not in out: out[e] = [] if e in ['material']: out[e] = values[1] continue else: out[e].append( cls._decode_object_property(values[1:], _default_property_order[e])) # Return # out.update(**metadata) return ObjDict(out)
[docs] @classmethod def coerce_type(cls, obj, typedef=None, **kwargs): r"""Coerce objects of specific types to match the data type. Args: obj (object): Object to be coerced. typedef (dict, optional): Type defintion that object should be coerced to. Defaults to None. **kwargs: Additional keyword arguments are metadata entries that may aid in coercing the type. Returns: object: Coerced object. """ if trimesh and isinstance(obj, trimesh.base.Trimesh): obj = ObjDict.from_trimesh(obj) if isinstance(obj, dict) and ('material' in obj): obj['material'] = tools.bytes2str(obj['material']) return super(ObjMetaschemaType, cls).coerce_type( obj, typedef=typedef, **kwargs)
[docs] @classmethod def updated_fixed_properties(cls, obj): r"""Get a version of the fixed properties schema that includes information from the object. Args: obj (object): Object to use to put constraints on the fixed properties schema. Returns: dict: Fixed properties schema with object dependent constraints. """ out = super(ObjMetaschemaType, cls).updated_fixed_properties(obj) # Constrain dependencies for indexes into other elements depend_map = {'vertex_index': 'vertices', 'vertex_indices': 'vertices', 'texcoord_index': 'texcoords', 'normal_index': 'normals'} check_depends = {'lines': ['texcoord_index'], 'faces': ['texcoord_index', 'normal_index'], 'surfaces:vertex_indices': ['texcoord_index', 'normal_index']} for e, props in check_depends.items(): sube = None if ':' in e: e, sube = e.split(':') if not ((e in obj) and isinstance(obj[e], (list, tuple))): continue req_flags = {k: False for k in props} for o in obj[e]: if sum(req_flags.values()) == len(props): break if isinstance(o, dict): assert(sube) if (((sube not in o) or (not isinstance(o[sube], (list, tuple))) or (len(o[sube]) == 0) or (not isinstance(o[sube][0], dict)))): continue for p in props: if p in o[sube][0]: req_flags[p] = True elif isinstance(o, (list, tuple)): if (len(o) == 0) or (not isinstance(o[0], dict)): continue for p in props: if p in o[0]: req_flags[p] = True # Set dependencies for p in req_flags.keys(): if not req_flags[p]: continue if depend_map[p] not in out['dependencies'][e]: out['dependencies'][e].append(depend_map[p]) # Contrain indices on number of elements refered to if ('vertices' in obj) and isinstance(obj['vertices'], (list, tuple)): out['definitions']['curve']['properties']['vertex_indices']['items'][ 'maximum'] = len(obj['vertices']) - 1 if ('params' in obj) and isinstance(obj['params'], (list, tuple)): out['definitions']['curve2D']['items']['maximum'] = len(obj['params']) - 1 for e in ['line', 'face', 'surface']: if e == 'surface': iprop = out['definitions'][e]['properties']['vertex_indices'][ 'items']['properties'] else: iprop = out['definitions'][e]['items']['properties'] for k, e_depends in depend_map.items(): if k in iprop: if (e_depends in obj) and isinstance(obj[e_depends], (list, tuple)): iprop[k]['maximum'] = len(obj[e_depends]) - 1 return out
@classmethod def _generate_data(cls, typedef, **kwargs): r"""Generate mock data for the specified type. Args: typedef (dict): Type definition. Returns: object: Python object of the specified type. """ kwargs.setdefault('numeric_value', 0) out = super(ObjMetaschemaType, cls)._generate_data(typedef, **kwargs) out['texcoords'][0].update(v=1.0, w=1.0) return out
ObjDict._type_class = ObjMetaschemaType