Structured points2d exampleΒΆ
An example of how to generate a 2D structured points dataset using numpy arrays. Also shown is a way to visualize this data with the mayavi2 application.
The script can be run like so:
$ mayavi2 -x structured_points2d.py
Alternatively, it can be run as:
$ python structured_points2d.py
Python source code: structured_points2d.py
# Author: Prabhu Ramachandran <prabhu at aero dot iitb dot ac dot in>
# Copyright (c) 2007, Enthought, Inc.
# License: BSD style.
from numpy import arange, sqrt, sin
from tvtk.api import tvtk
from mayavi.scripts import mayavi2
# Generate the scalar values.
x = (arange(0.1, 50.0)-25)/2.0
y = (arange(0.1, 50.0)-25)/2.0
r = sqrt(x[:,None]**2+y**2)
z = 5.0*sin(r)/r #
# Make the tvtk dataset.
# tvtk.ImageData is identical and could also be used here.
spoints = tvtk.StructuredPoints(origin=(-12.5,-12.5,0),
spacing=(0.5,0.5,1),
dimensions=(50,50,1))
# Transpose the array data due to VTK's implicit ordering. VTK assumes
# an implicit ordering of the points: X co-ordinate increases first, Y
# next and Z last. We flatten it so the number of components is 1.
spoints.point_data.scalars = z.T.flatten()
spoints.point_data.scalars.name = 'scalar'
# Uncomment the next two lines to save the dataset to a VTK XML file.
#w = tvtk.XMLImageDataWriter(input=spoints, file_name='spoints2d.vti')
#w.write()
# Now view the data.
@mayavi2.standalone
def view():
from mayavi.sources.vtk_data_source import VTKDataSource
from mayavi.filters.warp_scalar import WarpScalar
from mayavi.filters.poly_data_normals import PolyDataNormals
from mayavi.modules.surface import Surface
mayavi.new_scene()
src = VTKDataSource(data = spoints)
mayavi.add_source(src)
mayavi.add_filter(WarpScalar())
mayavi.add_filter(PolyDataNormals())
s = Surface()
mayavi.add_module(s)
if __name__ == '__main__':
view()