pyvista.ImageDataFilters#

class ImageDataFilters(*args, **kwargs)[source]#

An internal class to manage filters/algorithms for uniform grid datasets.

Methods

ImageDataFilters.cells_to_points([scalars, copy])

Re-mesh image data from a cell-based to a point-based representation.

ImageDataFilters.contour_labeled([n_labels, ...])

Generate labeled contours from 3D label maps.

ImageDataFilters.extract_subset(voi[, rate, ...])

Select piece (e.g., volume of interest).

ImageDataFilters.fft([output_scalars_name, ...])

Apply a fast Fourier transform (FFT) to the active scalars.

ImageDataFilters.gaussian_smooth([...])

Smooth the data with a Gaussian kernel.

ImageDataFilters.high_pass(x_cutoff, ...[, ...])

Perform a Butterworth high pass filter in the frequency domain.

ImageDataFilters.image_dilate_erode([...])

Dilates one value and erodes another.

ImageDataFilters.image_threshold(threshold)

Apply a threshold to scalar values in a uniform grid.

ImageDataFilters.low_pass(x_cutoff, ...[, ...])

Perform a Butterworth low pass filter in the frequency domain.

ImageDataFilters.median_smooth([...])

Smooth data using a median filter.

ImageDataFilters.pad_image([pad_value, ...])

Enlarge an image by padding its boundaries with new points.

ImageDataFilters.points_to_cells([scalars, copy])

Re-mesh image data from a point-based to a cell-based representation.

ImageDataFilters.rfft([output_scalars_name, ...])

Apply a reverse fast Fourier transform (RFFT) to the active scalars.