PolyDataFilters.ribbon

PolyDataFilters.ribbon#

PolyDataFilters.ribbon( *, width: float | None = None, scalars: str | None = None, angle: float = 0.0, factor: float = 2.0, normal: VectorLikeFloat | None = None, tcoords: bool | str = False, preference: PointLiteral | CellLiteral = 'point', progress_bar: bool = False, ) → PolyData[source]#

Create a ribbon of the lines in this dataset.

Note

If there are no lines in the input dataset, then the output will be an empty pyvista.PolyData mesh.

Parameters:

widthfloat, optional: Set the “half” width of the ribbon. If the width is allowed to vary, this is the minimum width. The default is 10% the length.
scalarsstr, optional: String name of the scalars array to use to vary the ribbon width. This is only used if a scalars array is specified.
anglefloat, optional: Angle in degrees of the offset angle of the ribbon from the line normal. The default is 0.0.
factorfloat, optional: Set the maximum ribbon width in terms of a multiple of the minimum width. The default is 2.0.
normalVectorLikeFloat, optional: Normal to use as default.
tcoordsbool, str, optional: If True, generate texture coordinates along the ribbon. This can also be specified to generate the texture coordinates with either 'length' or 'normalized'.
preferencestr, optional: The field preference when searching for the scalars array by name.
progress_barbool, default: False: Display a progress bar to indicate progress.

Returns:

pyvista.PolyData: Ribbon mesh. Empty if there are no lines in the input dataset.

Examples#

Download Python source code | Download Jupyter notebook

Convert a line to a ribbon and plot it.

>>> import numpy as np
>>> import pyvista as pv
>>> n = 1000
>>> theta = np.linspace(-10 * np.pi, 10 * np.pi, n)
>>> z = np.linspace(-2, 2, n)
>>> r = z**2 + 1
>>> x = r * np.sin(theta)
>>> y = r * np.cos(theta)
>>> points = np.column_stack((x, y, z))
>>> pdata = pv.PolyData(points)
>>> pdata.lines = np.hstack((n, range(n)))
>>> pdata['distance'] = range(n)
>>> ribbon = pdata.ribbon(width=0.2)
>>> ribbon.plot(show_scalar_bar=False)