def PlotResultsFlow(results, onSurf = False):
x, y = np.mgrid[0:512, 0:512]
w = np.zeros((512, 512))
if onSurf:
return mlab.flow(x, y, results['combineMap'],
results['sU'], results['sV'], results['combineMap'])
else:
return mlab.flow(results['sU'], results['sV'], w, seed_resolution=100,
seed_scale=1.0)
def do(self):
############################################################
# Imports.
from enthought.mayavi import mlab
############################################################
# Create a new scene and set up the visualization.
s = self.new_scene()
############################################################
# run all the "test_foobar" functions in the mlab module.
for name, func in getmembers(mlab):
if not callable(func) or not name[:4] in ('test', 'Test'):
continue
mlab.clf()
func()
# Mayavi has become too fast: the operator cannot see if the
# Test function was succesful.
sleep(0.1)
############################################################
# Test some specific corner-cases
import numpy
x, y, z = numpy.mgrid[1:10, 1:10, 1:10]
u, v, w = numpy.mgrid[1:10, 1:10, 1:10]
s = numpy.sqrt(u**2 + v**2)
mlab.clf()
# Test the extra argument "scalars"
mlab.quiver3d(x, y, z, u, v, w, scalars=s)
# Test surf with strange-shaped inputs
X, Y = numpy.ogrid[-10:10, -10:10]
Z = X**2 + Y**2
mlab.surf(X, Y, Z)
mlab.surf(X.ravel(), Y.ravel(), Z)
x, y, z = numpy.mgrid[-10:10, -10:10, -3:2]
mlab.flow(x, y, z)
# Test glyphs with number-only coordinnates
mlab.points3d(0, 0, 0, resolution=50)
def show_lorenz(new_fig=True):
x, y, z = np.mgrid[-50:50:100j,-50:50:100j,-10:60:70j]
u, v, w = lorenz(x, y, z)
if new_fig:
fig = mlab.figure(size=(600,600), bgcolor=(0, 0, 0))
# Plot the flow of trajectories with suitable parameters.
f = mlab.flow(x, y, z, u, v, w, line_width=3, colormap='Paired')
f.module_manager.scalar_lut_manager.reverse_lut = True
f.stream_tracer.integration_direction = 'both'
f.stream_tracer.maximum_propagation = 200
def show_lorenz(new_fig=True):
x, y, z = np.mgrid[-50:50:100j, -50:50:100j, -10:60:70j]
u, v, w = lorenz(x, y, z)
if new_fig:
fig = mlab.figure(size=(600, 600), bgcolor=(0, 0, 0))
# Plot the flow of trajectories with suitable parameters.
f = mlab.flow(x, y, z, u, v, w, line_width=3, colormap='Paired')
f.module_manager.scalar_lut_manager.reverse_lut = True
f.stream_tracer.integration_direction = 'both'
f.stream_tracer.maximum_propagation = 200
def test_probe_data(self):
""" Test probe_data
"""
x, y, z = np.mgrid[0:1:10j, 0:1:10j, 0:1:10j]
r = np.sqrt(x**2 + y**2 + z**2)
iso = mlab.contour3d(x, y, z, r)
x_, y_, z_ = np.random.random((3, 10, 4, 2))
r_ = mlab.pipeline.probe_data(iso, x_, y_, z_)
np.testing.assert_array_almost_equal(r_,
np.sqrt(x_**2 + y_**2 + z_**2),
decimal=2)
flow = mlab.flow(x, y, z, x, y, z)
u_, v_, w_ = mlab.pipeline.probe_data(flow, x_, y_, z_, type='vectors')
np.testing.assert_array_almost_equal(u_, x_, decimal=2)
np.testing.assert_array_almost_equal(v_, y_, decimal=2)
np.testing.assert_array_almost_equal(w_, z_, decimal=3)
def test_probe_data(self):
""" Test probe_data
"""
x, y, z = np.mgrid[0:1:10j, 0:1:10j, 0:1:10j]
r = np.sqrt(x**2 + y**2 + z**2)
iso = mlab.contour3d(x, y, z, r)
x_, y_, z_ = np.random.random((3, 10, 4, 2))
r_ = mlab.pipeline.probe_data(iso, x_, y_, z_)
np.testing.assert_array_almost_equal(r_,
np.sqrt(x_**2 + y_**2 + z_**2),
decimal=2)
flow = mlab.flow(x, y, z, x, y, z)
u_, v_, w_ = mlab.pipeline.probe_data(flow, x_, y_, z_,
type='vectors')
np.testing.assert_array_almost_equal(u_, x_,
decimal=2)
np.testing.assert_array_almost_equal(v_, y_,
decimal=2)
np.testing.assert_array_almost_equal(w_, z_,
decimal=3)
from enthought.mayavi import mlab
def lorenz(x, y, z, s=10.,r=28., b=8./3.):
"""The Lorenz system."""
u = s*(y-x)
v = r*x -y - x*z
w = x*y - b*z
return u, v, w
# Sample the space in an interesting region.
x, y, z = numpy.mgrid[-50:50:100j,-50:50:100j,-10:60:70j]
u, v, w = lorenz(x, y, z)
fig = mlab.figure(size=(400, 300), bgcolor=(0, 0, 0))
# Plot the flow of trajectories with suitable parameters.
f = mlab.flow(x, y, z, u, v, w, line_width=3, colormap='Paired',seedtype="point")
f.module_manager.scalar_lut_manager.reverse_lut = True
f.stream_tracer.integration_direction = 'both'
f.stream_tracer.integration_direction = 'forward'
f.stream_tracer.maximum_propagation = 2000
# Uncomment the following line if you want to hide the seed:
#f.seed.widget.enabled = False
# Extract the z-velocity from the vectors and plot the 0 level set
# hence producing the z-nullcline.
src = f.mlab_source.m_data
e = mlab.pipeline.extract_vector_components(src)
e.component = 'z-component'
zc = mlab.pipeline.iso_surface(e, opacity=0.5, contours=[0,],
color=(0.6, 1, 0.2))
from enthought.mayavi import mlab
def lorenz(x, y, z, s=10.,r=28., b=8./3.):
"""The Lorenz system."""
u = s*(y-x)
v = r*x -y - x*z
w = x*y - b*z
return u, v, w
# Sample the space in an interesting region.
x, y, z = numpy.mgrid[-50:50:100j,-50:50:100j,-10:60:70j]
u, v, w = lorenz(x, y, z)
fig = mlab.figure(size=(400, 300), bgcolor=(0, 0, 0))
# Plot the flow of trajectories with suitable parameters.
f = mlab.flow(x, y, z, u, v, w, line_width=3, colormap='Paired')
f.module_manager.scalar_lut_manager.reverse_lut = True
f.stream_tracer.integration_direction = 'both'
f.stream_tracer.maximum_propagation = 200
# Uncomment the following line if you want to hide the seed:
#f.seed.widget.enabled = False
# Extract the z-velocity from the vectors and plot the 0 level set
# hence producing the z-nullcline.
src = f.mlab_source.m_data
e = mlab.pipeline.extract_vector_components(src)
e.component = 'z-component'
zc = mlab.pipeline.iso_surface(e, opacity=0.5, contours=[0,],
color=(0.6, 1, 0.2))
# When using transparency, hiding 'backface' triangles often gives better
# results
import numpy as np from enthought.mayavi import mlab p, r, b = (10.0, 28.0, 3.0) x, y, z = np.mgrid[-17:20:20j, -21:28:20j, 0:48:20j] u, v, w = p*(y-x), x*(r-z)-y, x*y-b*z mlab.figure(size=(600, 600)) mlab.quiver3d(x, y, z, u, v, w) mlab.figure(size=(600, 600)) vectors = mlab.quiver3d(x, y, z, u, v, w) vectors.glyph.mask_input_points = True vectors.glyph.mask_points.on_ratio = 20 vectors.glyph.glyph.scale_factor = 5.0 mlab.figure(size=(600, 600)) src = mlab.pipeline.vector_field(x, y, z, u, v, w) mlab.pipeline.vector_cut_plane(src, mask_points=2, scale_factor=5) magnitude = mlab.pipeline.extract_vector_norm(src) surface = mlab.pipeline.iso_surface(magnitude) surface.actor.property.opacity = 0.3 mlab.gcf().scene.background = (0.8, 0.8, 0.8) mlab.figure(size=(600, 600)) mlab.flow(x, y, z, u, v, w) mlab.show()
import numpy as np from enthought.mayavi import mlab p, r, b = (10.0, 28.0, 3.0) x, y, z = np.mgrid[-17:20:20j, -21:28:20j, 0:48:20j] u, v, w = p * (y - x), x * (r - z) - y, x * y - b * z mlab.figure(size=(600, 600)) mlab.quiver3d(x, y, z, u, v, w) mlab.figure(size=(600, 600)) vectors = mlab.quiver3d(x, y, z, u, v, w) vectors.glyph.mask_input_points = True vectors.glyph.mask_points.on_ratio = 20 vectors.glyph.glyph.scale_factor = 5.0 mlab.figure(size=(600, 600)) src = mlab.pipeline.vector_field(x, y, z, u, v, w) mlab.pipeline.vector_cut_plane(src, mask_points=2, scale_factor=5) magnitude = mlab.pipeline.extract_vector_norm(src) surface = mlab.pipeline.iso_surface(magnitude) surface.actor.property.opacity = 0.3 mlab.gcf().scene.background = (0.8, 0.8, 0.8) mlab.figure(size=(600, 600)) mlab.flow(x, y, z, u, v, w) mlab.show()
