pyvista.fit_plane_to_points

fit_plane_to_points(points, return_meta: bool = False, resolution=10, init_normal=None)

Fit a plane to points using its principal_axes().

The plane is automatically sized and oriented to fit the extents of the points.

Changed in version 0.42.0: The generated plane is now sized and oriented to match the points.

Changed in version 0.42.0: The center of the plane (returned if return_meta=True) is now computed as the center of the generated plane mesh. In previous versions, the center of the input points was returned.

Changed in version 0.45.0: The internal method used for fitting the plane has changed. Previously, singular value decomposition (SVD) was used, but eigenvectors are now used instead. See warning below.

Warning

The sign of the plane’s normal vector prior to version 0.45 may differ from the latest version. This may impact methods which rely on the plane’s direction. Use init_normal to control the sign explicitly.

Parameters:

pointsarray_like[float]

Size [N x 3] sequence of points to fit a plane through.

return_metabool, default: False

If True, also returns the center and normal of the generated plane.

resolutionint, default: 10

Number of points on the plane mesh along its edges. Specify two numbers to set the resolution along the plane’s long and short edge (respectively) or a single number to set both edges to have the same resolution.

Added in version 0.45.0.

init_normalVectorLike[float] | str, optional

Flip the normal of the plane such that it best aligns with this vector. Can be a vector or string specifying the axis by name (e.g. 'x' or '-x', etc.).

Added in version 0.45.0.

Returns:

pyvista.PolyData

Plane mesh.

pyvista.pyvista_ndarray

Plane center if return_meta=True.

pyvista.pyvista_ndarray

Plane normal if return_meta=True.

See also

fit_line_to_points

Fit a line using the first principal axis of the points.

principal_axes

Compute axes vectors which best fit a set of points.

Examples

Fit a plane to a random point cloud.

>>> import pyvista as pv
>>> import numpy as np
>>> from pyvista import examples
>>>
>>> rng = np.random.default_rng(seed=0)
>>> cloud = rng.random((10, 3))
>>> cloud[:, 2] *= 0.1
>>>
>>> plane = pv.fit_plane_to_points(cloud)

Plot the point cloud and fitted plane.

>>> pl = pv.Plotter()
>>> _ = pl.add_mesh(plane, style='wireframe', line_width=4)
>>> _ = pl.add_points(
...     cloud,
...     render_points_as_spheres=True,
...     color='r',
...     point_size=30,
... )
>>> pl.show()

Static Scene

Interactive Scene

Fit a plane to a mesh and return its metadata. Set the plane resolution to 1 so that the plane has no internal points or edges.

>>> mesh = examples.download_shark()
>>> plane, center, normal = pv.fit_plane_to_points(
...     mesh.points, return_meta=True, resolution=1
... )

Plot the mesh and fitted plane.

>>> pl = pv.Plotter()
>>> _ = pl.add_mesh(plane, show_edges=True, opacity=0.25)
>>> _ = pl.add_mesh(mesh, color='gray')
>>> pl.camera_position = [
...     (-117, 76, 235),
...     (1.69, -1.38, 0),
...     (0.189, 0.957, -0.22),
... ]
>>> pl.show()

Static Scene

Interactive Scene

Use the metadata with pyvista.DataSetFilter.clip() to split the mesh into two.

>>> first_half, second_half = mesh.clip(
...     origin=center, normal=normal, return_clipped=True
... )

Plot the two halves of the clipped mesh.

>>> pl = pv.Plotter()
>>> _ = pl.add_mesh(first_half, color='red')
>>> _ = pl.add_mesh(second_half, color='blue')
>>> pl.camera_position = [
...     (-143, 43, 40),
...     (-8.7, -11, -14),
...     (0.25, 0.92, -0.29),
... ]
>>> pl.show()

Static Scene

Interactive Scene

Note that it is pointing in the positive z-direction.

>>> normal
pyvista_ndarray([5.2734075e-09, 6.7008443e-08, 1.0000000e+00],
                dtype=float32)

Use init_normal to flip the sign and make it negative instead.

>>> _, _, normal = pv.fit_plane_to_points(
...     mesh.points, return_meta=True, init_normal='-z'
... )
>>> normal
pyvista_ndarray([-5.2734155e-09, -6.7008422e-08, -1.0000000e+00],
                dtype=float32)