pyvista.ImageDataFilters#
- class ImageDataFilters(*args, **kwargs)[source]#
An internal class to manage filters/algorithms for uniform grid datasets.
Methods
ImageDataFilters.cells_to_points([scalars, ...])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.
Smooth the data with a Gaussian kernel.
ImageDataFilters.high_pass(x_cutoff, ...[, ...])Perform a Butterworth high pass filter in the frequency domain.
Dilates one value and erodes another.
ImageDataFilters.image_threshold(threshold)Apply a threshold to scalar values in a uniform grid.
ImageDataFilters.label_connectivity(*[, ...])Find and label connected regions in a
ImageData.ImageDataFilters.low_pass(x_cutoff, ...[, ...])Perform a Butterworth low pass filter in the frequency domain.
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, ...])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.