DataSetFilters.plot_over_line

DataSetFilters.plot_over_line#

DataSetFilters.plot_over_line(
pointa: VectorLike[float],
pointb: VectorLike[float],
resolution: int | None = None,
scalars: str | None = None,
title: str | None = None,
ylabel: str | None = None,
figsize: tuple[int, int] | None = None,
figure: bool = True,
show: bool = True,
tolerance: float | None = None,
fname: str | None = None,
progress_bar: bool = False,
component: int | None = None,
) → None[source]#

Sample a dataset along a high resolution line and plot.

Plot the variables of interest in 2D using Matplotlib 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:
pointasequence[float]

Location in [x, y, z].

pointbsequence[float]

Location in [x, y, z].

resolutionint, optional

Number of pieces to divide line 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 variable name.

figsizetuple(int, int), optional

The size of the new figure.

figurebool, default: True

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.

componentint, optional

Set component of vector-valued scalars to plot. Must be nonnegative and less than the number of components. If None, all components are plotted.