`pymor.discretizers.builtin.gui.qt`¶

Visualization of grid data using Qt.

This module provides a few methods and classes for visualizing data associated to grids. We use the Qt widget toolkit for the GUI.

Module Contents¶

Classes¶

PlotMainWindow

Base class for plot main windows.

Functions¶

`background_visualization_method`
`_launch_qt_app`	Wrapper to display plot in a separate process.
`visualize_patch`	Visualize scalar data associated to a two-dimensional `Grid` as a patch plot.
`visualize_matplotlib_1d`	Visualize scalar data associated to a one-dimensional `Grid` as a plot.

Attributes¶

`_qt_app`
`_qt_windows`

pymor.discretizers.builtin.gui.qt.background_visualization_method(method='ipython_if_possible')[source]¶

pymor.discretizers.builtin.gui.qt._launch_qt_app(main_window_factory, block)[source]¶: Wrapper to display plot in a separate process.

class pymor.discretizers.builtin.gui.qt.PlotMainWindow(U, plot, length=1, title=None)[source]¶

Bases: qtpy.QtWidgets.QWidget

Base class for plot main windows.

slider_changed(self, ind)[source]¶

speed_changed(self, val)[source]¶

update_solution(self)[source]¶

toggle_play(self, checked)[source]¶

rewind(self)[source]¶

to_end(self)[source]¶

step_forward(self)[source]¶

step_backward(self)[source]¶

closeEvent(self, event)[source]¶

pymor.discretizers.builtin.gui.qt._qt_app[source]¶

pymor.discretizers.builtin.gui.qt._qt_windows[source]¶

pymor.discretizers.builtin.gui.qt.visualize_patch(grid, U, bounding_box=([0, 0], [1, 1]), codim=2, title=None, legend=None, separate_colorbars=False, rescale_colorbars=False, backend='gl', block=False, columns=2)[source]¶

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.
U: VectorArray of the data to visualize. If len(U) > 1, the data is visualized as a time series of plots. Alternatively, a tuple of VectorArrays can be provided, in which case a subplot is created for each entry of the tuple. The lengths of all arrays have to agree.
bounding_box: A bounding box in which the grid is contained.
codim: The codimension of the entities the data in U is attached to (either 0 or 2).
title: Title of the plot.
legend: Description of the data that is plotted. Most useful if U is a tuple in which case legend 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.
backend: Plot backend to use (‘gl’ or ‘matplotlib’).
block: If True, block execution until the plot window is closed.
columns: The number of columns in the visualizer GUI in case multiple plots are displayed at the same time.

pymor.discretizers.builtin.gui.qt.visualize_matplotlib_1d(grid, U, codim=1, title=None, legend=None, separate_plots=False, block=False)[source]¶

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.