DataSetFilters.plot_over_circular_arc(pointa, pointb, center, resolution=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 circular arc 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.

pointanp.ndarray or list

Location in [x, y, z].

pointbnp.ndarray or list

Location in [x, y, z].

centernp.ndarray or list

Location in [x, y, z].

resolutionint, optional

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

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 the variable name.

figsizetuple(int), optional

The size of the new figure.

figurebool, optional

Flag on whether or not to create a new figure.

showbool, optional

Shows the matplotlib figure when True.

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, optional

Display a progress bar to indicate progress.


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

>>> from pyvista import examples
>>> mesh = examples.load_uniform()
>>> a = [mesh.bounds[0], mesh.bounds[2], mesh.bounds[5]]
>>> b = [mesh.bounds[1], mesh.bounds[2], mesh.bounds[4]]
>>> center = [mesh.bounds[0], mesh.bounds[2], mesh.bounds[4]]
>>> mesh.plot_over_circular_arc(a, b, center, resolution=1000, show=False)