pyvista.DataSetFilters.plot_over_circular_arc_normal#

DataSetFilters.plot_over_circular_arc_normal(
center,
resolution=None,
normal=None,
polar=None,
angle=None,
scalars=None,
title=None,
ylabel=None,
figsize=None,
figure=True,
show=True,
tolerance=None,
fname=None,
progress_bar=False,
)[source]#

Sample a dataset along a resolution circular arc defined by a normal and polar vector and plot it.

Plot the variables of interest in 2D where the X-axis is distance from Point A and the Y-axis is the variable of interest. Note that this filter returns None.

Parameters:
centersequence[int]

Location in [x, y, z].

resolutionint, optional

Number of pieces to divide circular arc into. Defaults to number of cells in the input mesh. Must be a positive integer.

normalsequence[float], optional

The normal vector to the plane of the arc. By default it points in the positive Z direction.

polarsequence[float], optional

Starting point of the arc in polar coordinates. By default it is the unit vector in the positive x direction.

anglefloat, optional

Arc length (in degrees), beginning at the polar vector. The direction is counterclockwise. By default it is 360.

scalarsstr, optional

The string name of the variable in the input dataset to probe. The active scalar is used by default.

titlestr, optional

The string title of the matplotlib figure.

ylabelstr, optional

The string label of the Y-axis. Defaults to variable name.

figsizetuple(int), optional

The size of the new figure.

figurebool, optional

Flag on whether or not to create a new figure.

showbool, default: True

Shows the matplotlib figure.

tolerancefloat, optional

Tolerance used to compute whether a point in the source is in a cell of the input. If not given, tolerance is automatically generated.

fnamestr, optional

Save the figure this file name when set.

progress_barbool, default: False

Display a progress bar to indicate progress.

Examples

Sample a dataset along a high resolution circular arc and plot.

>>> from pyvista import examples
>>> mesh = examples.load_uniform()
>>> normal = normal = [0, 0, 1]
>>> polar = [0, 9, 0]
>>> angle = 90
>>> center = [mesh.bounds[0], mesh.bounds[2], mesh.bounds[4]]
>>> mesh.plot_over_circular_arc_normal(
...     center, polar=polar, angle=angle
... )