pymor.discretizers.builtin.gui.visualizers
¶
Module Contents¶
Classes¶
Visualize scalar data associated to a twodimensional 

Visualize scalar data associated to a onedimensional 
 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 twodimensional
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.
 visualize(self, 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 VTKfile 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.
 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 onedimensional
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’).
 visualize(self, U, title=None, legend=None, separate_plots=True, separate_axes=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 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. block
If
True
, block execution until the plot window is closed. IfNone
, use the default provided during instantiation.