pyvista.Wavelet#

Wavelet(
extent=(-10, 10, -10, 10, -10, 10),
center=(0.0, 0.0, 0.0),
maximum=255.0,
x_freq=60.0,
y_freq=30.0,
z_freq=40.0,
x_mag=10.0,
y_mag=18.0,
z_mag=5.0,
std=0.5,
subsample_rate=1,
)[source]#

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:
extentsequence[int], default: (-10, 10, -10, 10, -10, 10)

Set/Get the extent of the whole output image.

centersequence[float], default: (0.0, 0.0, 0.0)

Center of the wavelet.

maximumfloat, default: 255.0

Maximum of the wavelet function.

x_freqfloat, default: 60.0

Natural frequency in the x direction.

y_freqfloat, default: 30.0

Natural frequency in the y direction.

z_freqfloat, default: 40.0

Natural frequency in the z direction.

x_magfloat, default: 10.0

Magnitude in the x direction.

y_magfloat, default: 18.0

Magnitude in the y direction.

z_magfloat, default: 5.0

Magnitude in the z direction.

stdfloat, default: 0.5

Standard deviation.

subsample_rateint, default: 1

The sub-sample rate.

Returns:
pyvista.PolyData

Wavelet mesh.

Examples

>>> import pyvista as pv
>>> wavelet = pv.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)
../../../_images/pyvista-Wavelet-1_00_00.png

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)
../../../_images/pyvista-Wavelet-1_01_00.png

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)
../../../_images/pyvista-Wavelet-1_02_00.png