pyvista.PolyDataFilters.contour_banded

PolyDataFilters.contour_banded(n_contours, rng=None, scalars=None, component=0, clip_tolerance=1e-06, generate_contour_edges=True, scalar_mode='value', clipping=True, progress_bar=False)

Generate filled contours.

Generates filled contours for vtkPolyData. Filled contours are bands of cells that all have the same cell scalar value, and can therefore be colored the same. The method is also referred to as filled contour generation.

This filter implements vtkBandedPolyDataContourFilter.

Parameters:

n_contoursint

Number of contours.

rngSequence, optional

Range of the scalars. Optional and defaults to the minimum and maximum of the active scalars of scalars.

scalarsstr, optional

The name of the scalar array to use for contouring. If None, the active scalar array will be used.

componentint, default: 0

The component to use of an input scalars array with more than one component.

clip_tolerancefloat, default: 1e-6

Set/Get the clip tolerance. Warning: setting this too large will certainly cause numerical issues. Change from the default value at your own risk. The actual internal clip tolerance is computed by multiplying clip_tolerance by the scalar range.

generate_contour_edgesbool, default: True

Controls whether contour edges are generated. Contour edges are the edges between bands. If enabled, they are generated from polygons/triangle strips and returned as a second output.

scalar_modestr, default: ‘value’

Control whether the cell scalars are output as an integer index or a scalar value. If 'index', the index refers to the bands produced by the clipping range. If 'value', then a scalar value which is a value between clip values is used.

clippingbool, default: True

Indicate whether to clip outside rng and only return cells with values within rng.

progress_barbool, default: False

Display a progress bar to indicate progress.

Returns:

outputpyvista.PolyData

Surface containing the contour surface.

edgespyvista.PolyData

Optional edges when generate_contour_edges is True.

Examples

Plot the random hills dataset and with 8 contour lines. Note how we use 7 colors here (n_contours - 1).

>>> import pyvista as pv
>>> from pyvista import examples

>>> mesh = examples.load_random_hills()
>>> n_contours = 8
>>> _, edges = mesh.contour_banded(n_contours)

>>> pl = pv.Plotter()
>>> _ = pl.add_mesh(
...     edges,
...     line_width=5,
...     render_lines_as_tubes=True,
...     color='k',
... )
>>> _ = pl.add_mesh(mesh, n_colors=n_contours - 1, cmap='Set3')
>>> pl.show()

Static Scene

Interactive Scene

Extract the surface from the uniform grid dataset and plot its contours alongside the output from the banded contour filter.

>>> surf = examples.load_uniform().extract_surface()
>>> n_contours = 5
>>> rng = [200, 500]
>>> output, edges = surf.contour_banded(n_contours, rng=rng)

>>> dargs = dict(n_colors=n_contours - 1, clim=rng)
>>> pl = pv.Plotter()
>>> _ = pl.add_mesh(
...     edges,
...     line_width=5,
...     render_lines_as_tubes=True,
...     color='k',
... )
>>> _ = pl.add_mesh(surf, opacity=0.3, **dargs)
>>> _ = pl.add_mesh(output, **dargs)
>>> pl.show()

Static Scene

Interactive Scene