fipy.viewers.matplotlibViewer¶

Functions

MatplotlibViewer(vars[, title, limits, ...])

Generic function for creating a MatplotlibViewer.

fipy.viewers.matplotlibViewer.MatplotlibViewer(vars, title=None, limits={}, cmap=None, colorbar='vertical', axes=None, **kwlimits)¶

Generic function for creating a MatplotlibViewer.

The MatplotlibViewer factory will search the module tree and return an instance of the first MatplotlibViewer it finds of the correct dimension and rank.

It is possible to view different Variable instances against different Matplotlib Axes

>>> from matplotlib import pyplot as plt
>>> from fipy import *

>>> plt.ion()
>>> fig = plt.figure()

>>> ax1 = plt.subplot((221))
>>> ax2 = plt.subplot((223))
>>> ax3 = plt.subplot((224))

>>> k = Variable(name="k", value=0.)

>>> mesh1 = Grid1D(nx=100)
>>> x, = mesh1.cellCenters
>>> xVar = CellVariable(mesh=mesh1, name="x", value=x)
>>> viewer1 = MatplotlibViewer(vars=(numerix.sin(0.1 * k * xVar), numerix.cos(0.1 * k * xVar / numerix.pi)),
...                            limits={'xmin': 10, 'xmax': 90},
...                            datamin=-0.9, datamax=2.0,
...                            title="Grid1D test",
...                            axes=ax1,
...                            legend=None)

>>> mesh2 = Grid2D(nx=50, ny=100, dx=0.1, dy=0.01)
>>> x, y = mesh2.cellCenters
>>> xyVar = CellVariable(mesh=mesh2, name="x y", value=x * y)
>>> viewer2 = MatplotlibViewer(vars=numerix.sin(k * xyVar),
...                            limits={'ymin': 0.1, 'ymax': 0.9},
...                            datamin=-0.9, datamax=2.0,
...                            title="Grid2D test",
...                            axes=ax2,
...                            colorbar=None)

>>> mesh3 = (Grid2D(nx=5, ny=10, dx=0.1, dy=0.1)
...          + (Tri2D(nx=5, ny=5, dx=0.1, dy=0.1)
...             + ((0.5,), (0.2,))))
>>> x, y = mesh3.cellCenters
>>> xyVar = CellVariable(mesh=mesh3, name="x y", value=x * y)
>>> viewer3 = MatplotlibViewer(vars=numerix.sin(k * xyVar),
...                            limits={'ymin': 0.1, 'ymax': 0.9},
...                            datamin=-0.9, datamax=2.0,
...                            title="Irregular 2D test",
...                            axes=ax3,
...                            cmap = plt.cm.OrRd)

>>> viewer = MultiViewer(viewers=(viewer1, viewer2, viewer3))
>>> for kval in range(10):
...     k.setValue(kval)
...     viewer.plot()

>>> viewer._promptForOpinion()

Parameters:

vars (CellVariable or list) – the Variable objects to display.
title (str, optional) – displayed at the top of the Viewer window
limits (dict) – a (deprecated) alternative to limit keyword arguments
xmin (float, optional) – displayed range of data. A 1D Viewer will only use xmin and xmax, a 2D viewer will also use ymin and ymax. All viewers will use datamin and datamax. Any limit set to a (default) value of None will autoscale.
xmax (float, optional) – displayed range of data. A 1D Viewer will only use xmin and xmax, a 2D viewer will also use ymin and ymax. All viewers will use datamin and datamax. Any limit set to a (default) value of None will autoscale.
ymin (float, optional) – displayed range of data. A 1D Viewer will only use xmin and xmax, a 2D viewer will also use ymin and ymax. All viewers will use datamin and datamax. Any limit set to a (default) value of None will autoscale.
ymax (float, optional) – displayed range of data. A 1D Viewer will only use xmin and xmax, a 2D viewer will also use ymin and ymax. All viewers will use datamin and datamax. Any limit set to a (default) value of None will autoscale.
datamin (float, optional) – displayed range of data. A 1D Viewer will only use xmin and xmax, a 2D viewer will also use ymin and ymax. All viewers will use datamin and datamax. Any limit set to a (default) value of None will autoscale.
datamax (float, optional) – displayed range of data. A 1D Viewer will only use xmin and xmax, a 2D viewer will also use ymin and ymax. All viewers will use datamin and datamax. Any limit set to a (default) value of None will autoscale.
cmap (Colormap, optional) – the Colormap. Defaults to matplotlib.cm.jet
colorbar (bool, optional) – plot a color bar in specified orientation if not None
axes (Axes, optional) – if not None, vars will be plotted into this Matplotlib Axes object

Modules

`abstractMatplotlib2DViewer`
`abstractMatplotlibViewer`
`matplotlib1DViewer`
`matplotlib2DContourViewer`
`matplotlib2DGridContourViewer`
`matplotlib2DGridViewer`
`matplotlib2DViewer`
`matplotlibSparseMatrixViewer`
`matplotlibStreamViewer`
`matplotlibVectorViewer`
`test`	Test numeric implementation of the mesh

Last updated on May 15, 2026. Created using Sphinx 9.1.0.