1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
|
from numpy import c_, zeros, arange
from traits.api import Bool, HasStrictTraits, Instance
from mayavi.sources.vtk_data_source import VTKDataSource
from mayavi.sources.array_source import ArraySource
from mayavi.core.source import Source
from mayavi.core.trait_defs import ArrayOrNone
from tvtk.api import tvtk
############################################################################
# The DataSourceFactory class
############################################################################
class DataSourceFactory(HasStrictTraits):
""" Factory for creating data sources. The information about the
organisation of the data is given by setting the public traits.
"""
# Whether the position is implicitly inferred from the array indices
position_implicit = Bool(False)
# Whether the data is on an orthogonal grid
orthogonal_grid = Bool(False)
# If the data is unstructured
unstructured = Bool(False)
# If the factory should attempt to connect the data points
connected = Bool(True)
# The position of the data points
position_x = ArrayOrNone
position_y = ArrayOrNone
position_z = ArrayOrNone
# Connectivity array. If none, it is implicitly inferred from the array
# indices
connectivity_triangles = ArrayOrNone
# Whether or not the data points should be connected.
lines = Bool(False)
# The scalar data array
scalar_data = ArrayOrNone
# Whether there is vector data
has_vector_data = Bool(False)
# The vector components
vector_u = ArrayOrNone
vector_v = ArrayOrNone
vector_w = ArrayOrNone
#----------------------------------------------------------------------
# Private traits
#----------------------------------------------------------------------
_vtk_source = Instance(tvtk.DataSet)
_mayavi_source = Instance(Source)
#----------------------------------------------------------------------
# Private interface
#----------------------------------------------------------------------
def _add_scalar_data(self):
""" Adds the scalar data to the vtk source.
"""
if self.scalar_data is not None:
scalars = self.scalar_data.ravel()
self._vtk_source.point_data.scalars = scalars
def _add_vector_data(self):
""" Adds the vector data to the vtk source.
"""
if self.has_vector_data:
vectors = c_[self.vector_u.ravel(),
self.vector_v.ravel(),
self.vector_w.ravel(),
]
self._vtk_source.point_data.vectors = vectors
def _mk_polydata(self):
""" Creates a PolyData vtk data set using the factory's
attributes.
"""
points = c_[self.position_x.ravel(),
self.position_y.ravel(),
self.position_z.ravel(),
]
lines = None
if self.lines:
np = len(points) - 1
lines = zeros((np, 2), 'l')
lines[:, 0] = arange(0, np - 0.5, 1, 'l')
lines[:, 1] = arange(1, np + 0.5, 1, 'l')
self._vtk_source = tvtk.PolyData(points=points, lines=lines)
if (self.connectivity_triangles is not None and
self.connected):
assert self.connectivity_triangles.shape[1] == 3, \
"The connectivity list must be Nx3."
self._vtk_source.polys = self.connectivity_triangles
self._mayavi_source = VTKDataSource(data=self._vtk_source)
def _mk_image_data(self):
""" Creates an ImageData VTK data set and the associated ArraySource
using the factory's attributes.
"""
self._mayavi_source = ArraySource(transpose_input_array=True,
scalar_data=self.scalar_data,
origin=[0., 0., 0],
spacing=[1, 1, 1])
self._vtk_source = self._mayavi_source.image_data
def _mk_rectilinear_grid(self):
""" Creates a RectilinearGrid VTK data set using the factory's
attributes.
"""
rg = tvtk.RectilinearGrid()
x = self.position_x.squeeze()
if x.ndim == 3:
x = x[:, 0, 0]
y = self.position_y.squeeze()
if y.ndim == 3:
y = y[0, :, 0]
z = self.position_z.squeeze()
if z.ndim == 3:
z = z[0, 0, :]
# FIXME: We should check array size here.
rg.dimensions = (x.size, y.size, z.size)
rg.x_coordinates = x
rg.y_coordinates = y
rg.z_coordinates = z
self._vtk_source = rg
self._mayavi_source = VTKDataSource(data=self._vtk_source)
def _mk_structured_grid(self):
""" Creates a StructuredGrid VTK data set using the factory's
attributes.
"""
# FIXME: We need to figure out the dimensions of the data
# here, if any.
sg = tvtk.StructuredGrid(dimensions=self.scalar_data.shape)
sg.points = c_[self.position_x.ravel(),
self.position_y.ravel(),
self.position_z.ravel(),
]
self._vtk_source = sg
self._mayavi_source = VTKDataSource(data=self._vtk_source)
#----------------------------------------------------------------------
# Public interface
#----------------------------------------------------------------------
def build_data_source(self, **traits):
""" Uses all the information given by the user on his data
structure to figure out the right data structure.
"""
self.trait_set(**traits)
if not self.lines:
if self.position_implicit:
self._mk_image_data()
elif self.orthogonal_grid:
self._mk_rectilinear_grid()
elif self.connectivity_triangles is None:
if self.unstructured:
self._mk_polydata()
else:
self._mk_structured_grid()
else:
self._mk_polydata()
else:
self._mk_polydata()
self._add_scalar_data()
self._add_vector_data()
return self._mayavi_source
def view(src):
""" Open up a mayavi scene and display the dataset in it.
"""
from mayavi import mlab
mayavi = mlab.get_engine()
fig = mlab.figure(bgcolor=(1, 1, 1), fgcolor=(0, 0, 0),)
mayavi.add_source(src)
mlab.pipeline.surface(src, opacity=0.1)
mlab.pipeline.surface(mlab.pipeline.extract_edges(src),
color=(0, 0, 0), )
def test_image_data():
from numpy import random
scalars = random.random((3, 3, 3))
factory = DataSourceFactory()
image_data = factory.build_data_source(scalar_data=scalars,
position_implicit=True,)
view(image_data)
def test_rectilinear_grid():
from numpy import random, mgrid
factory = DataSourceFactory()
scalars = random.random((3, 3, 3))
x = arange(3) ** 2
y = 0.5 * arange(3) ** 2
z = arange(3) ** 2
rectilinear_grid = factory.build_data_source(scalar_data=scalars,
position_implicit=False,
orthogonal_grid=True,
position_x=x,
position_y=y,
position_z=z)
view(rectilinear_grid)
def test_structured_grid():
from numpy import random, mgrid
factory = DataSourceFactory()
scalars = random.random((3, 3, 3))
x, y, z = mgrid[0:3, 0:3, 0:3]
x = x + 0.5 * random.random(x.shape)
y = y + 0.5 * random.random(y.shape)
z = z + 0.5 * random.random(z.shape)
structured_grid = factory.build_data_source(scalar_data=scalars,
position_x=x,
position_y=y,
position_z=z)
view(structured_grid)
if __name__ == '__main__':
from pyface.api import GUI
test_image_data()
test_rectilinear_grid()
test_structured_grid()
GUI().start_event_loop()
|
