def Wavelet(extent=(-10, 10, -10, 10, -10, 10),
center=(0, 0, 0),
maximum=255,
x_freq=60,
y_freq=30,
z_freq=40,
x_mag=10,
y_mag=18,
z_mag=5,
std=0.5,
subsample_rate=1):
"""Create a wavelet."""
wavelet_source = _vtk.vtkRTAnalyticSource()
wavelet_source.SetWholeExtent(*extent)
wavelet_source.SetCenter(center)
wavelet_source.SetMaximum(maximum)
wavelet_source.SetXFreq(x_freq)
wavelet_source.SetYFreq(y_freq)
wavelet_source.SetZFreq(z_freq)
wavelet_source.SetXMag(x_mag)
wavelet_source.SetYMag(y_mag)
wavelet_source.SetZMag(z_mag)
wavelet_source.SetStandardDeviation(std)
wavelet_source.SetSubsampleRate(subsample_rate)
wavelet_source.Update()
return pyvista.wrap(wavelet_source.GetOutput())
def Wavelet(extent=(-10, 10, -10, 10, -10, 10),
center=(0, 0, 0),
maximum=255,
x_freq=60,
y_freq=30,
z_freq=40,
x_mag=10,
y_mag=18,
z_mag=5,
std=0.5,
subsample_rate=1):
"""Create a wavelet.
Produces images with pixel values determined by
``Maximum*Gaussian*x_mag*sin(x_freq*x)*sin(y_freq*y)*cos(z_freq*z)``
Values are float scalars on point data with name ``"RTData"``.
Parameters
----------
extent : sequence, optional
Set/Get the extent of the whole output image. Default
``(-10, 10, -10, 10, -10, 10)``.
center : list, optional
Center of the wavelet.
maximum : float, optional
Maximum of the wavelet function.
x_freq : float, optional
Natural frequency in the x direction.
y_freq : float, optional
Natural frequency in the y direction.
z_freq : float, optional
Natural frequency in the z direction.
x_mag : float, optional
Magnitude in the x direction.
y_mag : float, optional
Magnitude in the y direction.
z_mag : float, optional
Magnitude in the z direction.
std : float, optional
Standard deviation.
subsample_rate : int, optional
The sub-sample rate.
Returns
-------
pyvista.PolyData
Wavelet mesh.
Examples
--------
>>> import pyvista
>>> wavelet = pyvista.Wavelet(extent=(0, 50, 0, 50, 0, 10), x_freq=20,
... y_freq=10, z_freq=1, x_mag=100, y_mag=100,
... z_mag=1000)
>>> wavelet.plot(show_scalar_bar=False)
Extract lower valued cells of the wavelet and create a surface from it.
>>> thresh = wavelet.threshold(800).extract_surface()
>>> thresh.plot(show_scalar_bar=False)
Smooth it to create "waves"
>>> waves = thresh.smooth(n_iter=100, relaxation_factor=0.1)
>>> waves.plot(color='white', smooth_shading=True, show_edges=True)
"""
wavelet_source = _vtk.vtkRTAnalyticSource()
wavelet_source.SetWholeExtent(*extent)
wavelet_source.SetCenter(center)
wavelet_source.SetMaximum(maximum)
wavelet_source.SetXFreq(x_freq)
wavelet_source.SetYFreq(y_freq)
wavelet_source.SetZFreq(z_freq)
wavelet_source.SetXMag(x_mag)
wavelet_source.SetYMag(y_mag)
wavelet_source.SetZMag(z_mag)
wavelet_source.SetStandardDeviation(std)
wavelet_source.SetSubsampleRate(subsample_rate)
wavelet_source.Update()
return pyvista.wrap(wavelet_source.GetOutput())