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#!/usr/bin/env python
"""A simple example showing an animation. The example illustrates a
few things.
1. You can pass a numpy array of scalars and use it directly with
tvtk.
2. The tvtk arrays are views of numpy arrays. Thus changing the
array in-place will also change the underlying VTK data.
3. When changing the numpy data you must call `modified` on a
relevant tvtk object.
The example is a little contrived since there are better ways of
achieving the same effect but the present form nicely illustrates item
2 mentioned above.
"""
# Author: Prabhu Ramachandran <prabhu_r@users.sf.net>
# Copyright (c) 2004-2020, Enthought, Inc.
# License: BSD Style.
from tvtk.api import tvtk
from tvtk.common import configure_input
import numpy as np
import time
# First create a structured points data set.
sp = tvtk.StructuredPoints(origin=(-10., -10., 0.0),
dimensions=(80, 80, 1),
spacing=(0.25, 0.25, 0.0))
# Create some nice data at these points.
x = np.arange(-10., 10., 0.25)
y = x
r = np.sqrt(x[:,None]**2+y**2)
# We need the transpose so the data is as per VTK's expected format
# where X coords vary fastest, Y next and then Z.
try:
import scipy.special
z = np.reshape(np.transpose(5.0*scipy.special.j0(r)), (-1,) )
except ImportError:
z = np.reshape(np.transpose(5.0*np.sin(r)/r), (-1,) )
# Now set the scalar data for the StructuredPoints object. The
# scalars of the structured points object will be a view into our
# Numeric array. Thus, if we change `z` in-place, the changes will
# automatically affect the VTK arrays.
sp.point_data.scalars = z
# Convert this to a PolyData object.
geom_filter = tvtk.ImageDataGeometryFilter()
configure_input(geom_filter, sp)
# Now warp this using the scalar value to generate a carpet plot.
warp = tvtk.WarpScalar()
configure_input(warp, geom_filter)
# Smooth the resulting data so it looks good.
normals = tvtk.PolyDataNormals()
configure_input(normals, warp)
# The rest of the VTK pipeline.
m = tvtk.PolyDataMapper(scalar_range=(min(z), max(z)))
configure_input(m, normals)
a = tvtk.Actor(mapper=m)
ren = tvtk.Renderer(background=(0.5, 0.5, 0.5))
ren.add_actor(a)
# Get a nice view.
cam = ren.active_camera
cam.azimuth(-60)
cam.roll(90)
# Create a RenderWindow, add the renderer and set its size.
rw = tvtk.RenderWindow(size=(600, 600))
rw.add_renderer(ren)
# Create the RenderWindowInteractor
rwi = tvtk.RenderWindowInteractor(render_window=rw)
rwi.initialize()
ren.reset_camera()
rwi.render()
# The following is a crude approach but illustrates the point.
scale = old_scale = 1.0
for i in np.arange(np.pi*0.5, 2.5*np.pi, 0.2):
if abs(i) < 1.0e-10:
continue
scale = np.sin(i)
# We change 'z' in-place
z *= scale/old_scale
# Reset the scalar range.
m.scalar_range = min(z), max(z)
# Now explicitly notify `sp` that its data has changed. If this
# is not done, VTK has no way of knowing the data changed in order
# to flush the pipeline.
sp.modified()
# Re-render the scene to actually flush the VTK pipeline.
rwi.render()
old_scale = scale
time.sleep(0.1) # Just in case your hardware is really fast.
# Start the VTK event loop.
rwi.start()
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