pymor.discretizers.builtin.gui.visualizers
¶
Module Contents¶
- class pymor.discretizers.builtin.gui.visualizers.OnedVisualizer(grid, codim=1, block=False, backend='jupyter_or_matplotlib')[source]¶
Bases:
pymor.core.base.ImmutableObject
Visualize scalar data associated to a one-dimensional
Grid
as a plot.The grid’s
ReferenceElement
must be the line. The data can either be attached to the subintervals or vertices of the grid.Parameters
- grid
The underlying
Grid
.- codim
The codimension of the entities the data in
U
is attached to (either 0 or 1).- block
If
True
, block execution until the plot window is closed.- backend
Plot backend to use (‘jupyter_or_matplotlib’, ‘jupyter’, ‘matplotlib’).
Methods
Visualize the provided data.
- visualize(U, title=None, legend=None, separate_plots=False, rescale_axes=False, block=None, columns=2)[source]¶
Visualize the provided data.
Parameters
- U
VectorArray
of the data to visualize. Iflen(U) > 1
, the data is visualized as a time series of plots. Alternatively, a tuple ofVectorArrays
can be provided, in which case several plots are made into the same axes. The lengths of all arrays have to agree.- title
Title of the plot.
- legend
Description of the data that is plotted. Most useful if
U
is a tuple in which caselegend
has to be a tuple of strings of the same length.- separate_plots
If
True
, use multiple figures to visualize multipleVectorArrays
.- rescale_axes
If
True
, rescale axes to data in each frame.- block
If
True
, block execution until the plot window is closed. IfNone
, use the default provided during instantiation.- columns
Number of columns the subplots are organized in.
- class pymor.discretizers.builtin.gui.visualizers.PatchVisualizer(grid, codim=2, bounding_box=None, backend='jupyter_or_gl', block=False)[source]¶
Bases:
pymor.core.base.ImmutableObject
Visualize scalar data associated to a two-dimensional
Grid
as a patch plot.The grid’s
ReferenceElement
must be the triangle or square. The data can either be attached to the faces or vertices of the grid.Parameters
- grid
The underlying
Grid
.- codim
The codimension of the entities the data in
U
is attached to (either 0 or 2).- bounding_box
A bounding box in which the grid is contained.
- backend
Plot backend to use (‘jupyter_or_gl’, ‘jupyter’, ‘gl’, ‘matplotlib’).
- block
If
True
, block execution until the plot window is closed.
Methods
Visualize the provided data.
- visualize(U, title=None, legend=None, separate_colorbars=False, rescale_colorbars=False, block=None, filename=None, columns=2)[source]¶
Visualize the provided data.
Parameters
- U
VectorArray
of the data to visualize. Iflen(U) > 1
, the data is visualized as a time series of plots. Alternatively, a tuple ofVectorArrays
can be provided, in which case a subplot is created for each entry of the tuple. The lengths of all arrays have to agree.- title
Title of the plot.
- legend
Description of the data that is plotted. Most useful if
U
is a tuple in which caselegend
has to be a tuple of strings of the same length.- separate_colorbars
If
True
, use separate colorbars for each subplot.- rescale_colorbars
If
True
, rescale colorbars to data in each frame.- block
If
True
, block execution until the plot window is closed. IfNone
, use the default provided during instantiation.- filename
If specified, write the data to a VTK-file using
write_vtk
instead of displaying it.- columns
The number of columns in the visualizer GUI in case multiple plots are displayed at the same time.