def __init__(self,
vars,
title=None,
limits={},
cmap=None,
colorbar='vertical',
axes=None,
figaspect='auto',
**kwlimits):
"""
Creates a `Matplotlib2DGridViewer`.
:Parameters:
vars
A `CellVariable` object.
title
displayed at the top of the `Viewer` window
limits : dict
a (deprecated) alternative to limit keyword arguments
cmap
The colormap. Defaults to `matplotlib.cm.jet`
xmin, xmax, ymin, ymax, datamin, datamax
displayed range of data. Any limit set to
a (default) value of `None` will autoscale.
colorbar
plot a colorbar in specified orientation if not `None`
axes
if not `None`, `vars` will be plotted into this Matplotlib `Axes` object
figaspect
desired aspect ratio of figure. If arg is a number, use that aspect
ratio. If arg is 'auto', the aspect ratio will be determined from
the Variable's mesh.
"""
kwlimits.update(limits)
AbstractMatplotlib2DViewer.__init__(self,
vars=vars,
title=title,
cmap=cmap,
colorbar=colorbar,
axes=axes,
figaspect=figaspect,
**kwlimits)
xmin, ymin = self.vars[0].mesh.extents['min']
xmax, ymax = self.vars[0].mesh.extents['max']
self.image = self.axes.imshow(self._data,
extent=(xmin, xmax, ymin, ymax),
vmin=0,
vmax=1,
cmap=self.cmap)
self.axes.set_xlim(xmin=self._getLimit('xmin'),
xmax=self._getLimit('xmax'))
self.axes.set_ylim(ymin=self._getLimit('ymin'),
ymax=self._getLimit('ymax'))
if title is None:
self.axes.set_title(self.vars[0].name)
def __init__(self, vars, title=None, limits={}, cmap=None, colorbar='vertical', axes=None, figaspect='auto', **kwlimits):
"""Creates a `Matplotlib2DViewer`.
:Parameters:
vars
a `CellVariable` object.
title
displayed at the top of the `Viewer` window
limits : dict
a (deprecated) alternative to limit keyword arguments
xmin, xmax, ymin, ymax, datamin, datamax
displayed range of data. Any limit set to
a (default) value of `None` will autoscale.
cmap
the colormap. Defaults to `matplotlib.cm.jet`
colorbar
plot a colorbar in specified orientation if not `None`
axes
if not `None`, `vars` will be plotted into this Matplotlib `Axes` object
figaspect
desired aspect ratio of figure. If arg is a number, use that aspect
ratio. If arg is 'auto', the aspect ratio will be determined from
the Variable's mesh.
"""
kwlimits.update(limits)
AbstractMatplotlib2DViewer.__init__(self, vars=vars, title=title,
cmap=cmap, colorbar=colorbar, axes=axes, figaspect=figaspect,
**kwlimits)
self._plot()
def __init__(self, vars, title=None, scale=None, sparsity=None, log=False, limits={}, axes=None, figaspect='auto', **kwlimits):
"""Creates a `Matplotlib2DViewer`.
:Parameters:
vars
a rank-1 `CellVariable` or `FaceVariable` object.
title
displayed at the top of the `Viewer` window
scale
if not `None`, scale all arrow lengths by this value
sparsity
if not `None`, then this number of arrows will be
randomly chosen (weighted by the cell volume or face area)
log
if `True`, arrow length goes at the base-10 logarithm of the magnitude
limits : dict
a (deprecated) alternative to limit keyword arguments
xmin, xmax, ymin, ymax, datamin, datamax
displayed range of data. Any limit set to
a (default) value of `None` will autoscale.
axes
if not `None`, `vars` will be plotted into this Matplotlib `Axes` object
figaspect
desired aspect ratio of figure. If arg is a number, use that aspect
ratio. If arg is 'auto', the aspect ratio will be determined from
the Variable's mesh.
"""
kwlimits.update(limits)
AbstractMatplotlib2DViewer.__init__(self, vars=vars, title=title, axes=axes, figaspect=figaspect, **kwlimits)
self.quiver(sparsity=sparsity, scale=scale)
self.log = log
self._plot()
def __init__(self, vars, title=None, limits={}, cmap=None, colorbar='vertical', axes=None, figaspect='auto', **kwlimits):
"""Creates a `Matplotlib2DViewer`.
:Parameters:
vars
a `CellVariable` object.
title
displayed at the top of the `Viewer` window
limits : dict
a (deprecated) alternative to limit keyword arguments
xmin, xmax, ymin, ymax, datamin, datamax
displayed range of data. Any limit set to
a (default) value of `None` will autoscale.
cmap
the colormap. Defaults to `matplotlib.cm.jet`
colorbar
plot a colorbar in specified orientation if not `None`
axes
if not `None`, `vars` will be plotted into this Matplotlib `Axes` object
figaspect
desired aspect ratio of figure. If arg is a number, use that aspect
ratio. If arg is 'auto', the aspect ratio will be determined from
the Variable's mesh.
"""
kwlimits.update(limits)
AbstractMatplotlib2DViewer.__init__(self, vars=vars, title=title,
cmap=cmap, colorbar=colorbar, axes=axes, figaspect=figaspect,
**kwlimits)
self._plot()
def __init__(self,
vars,
title=None,
limits={},
cmap=None,
colorbar='vertical',
axes=None,
number=10,
levels=None,
figaspect='auto',
**kwlimits):
"""Creates a `Matplotlib2DContourViewer`.
:Parameters:
vars
a `CellVariable` object.
title
displayed at the top of the `Viewer` window
limits : dict
a (deprecated) alternative to limit keyword arguments
xmin, xmax, ymin, ymax, datamin, datamax
displayed range of data. Any limit set to
a (default) value of `None` will autoscale.
cmap
the colormap. Defaults to `matplotlib.cm.jet`
colorbar
plot a colorbar in specified orientation if not `None`
axes
if not `None`, `vars` will be plotted into this Matplotlib `Axes` object
number
contour `number` automatically-chosen levels
*levels* [level0, level1, ..., leveln]
A list of floating point numbers indicating the level
curves to draw; eg to draw just the zero contour pass
``levels=[0]``
figaspect
desired aspect ratio of figure. If arg is a number, use that aspect
ratio. If arg is 'auto', the aspect ratio will be determined from
the Variable's mesh.
"""
kwlimits.update(limits)
AbstractMatplotlib2DViewer.__init__(self,
vars=vars,
title=title,
cmap=cmap,
colorbar=colorbar,
axes=axes,
figaspect=figaspect,
**kwlimits)
self.number = number
self.levels = levels
self._plot()
def __init__(self,
vars,
title=None,
limits={},
cmap=None,
colorbar='vertical',
axes=None,
figaspect='auto',
**kwlimits):
"""Creates a `Matplotlib2DGridViewer`.
Parameters
----------
vars : ~fipy.variables.cellVariable.CellVariable
the `Variable` to display.
title : str, optional
displayed at the top of the `Viewer` window
limits : dict, optional
a (deprecated) alternative to limit keyword arguments
cmap : ~matplotlib.colors.Colormap, optional
the :class:`~matplotlib.colors.Colormap`.
Defaults to `matplotlib.cm.jet`
float xmin, xmax, ymin, ymax, datamin, datamax : float, optional
displayed range of data. Any limit set to
a (default) value of `None` will autoscale.
colorbar : bool, optional
plot a color bar in specified orientation if not `None`
axes : ~matplotlib.axes.Axes, optional
if not `None`, `vars` will be plotted into this Matplotlib `Axes` object
figaspect : float, optional
desired aspect ratio of figure. If arg is a number, use that aspect
ratio. If arg is `auto`, the aspect ratio will be determined from
the Variable's mesh.
"""
kwlimits.update(limits)
AbstractMatplotlib2DViewer.__init__(self,
vars=vars,
title=title,
cmap=cmap,
colorbar=colorbar,
axes=axes,
figaspect=figaspect,
**kwlimits)
self.axes.set_xlim(xmin=self._getLimit('xmin'),
xmax=self._getLimit('xmax'))
self.axes.set_ylim(ymin=self._getLimit('ymin'),
ymax=self._getLimit('ymax'))
if title is None:
self.axes.set_title(self.vars[0].name)
def __init__(self,
vars,
title=None,
scale=None,
sparsity=None,
log=False,
limits={},
axes=None,
figaspect='auto',
**kwlimits):
"""Creates a `Matplotlib2DViewer`.
:Parameters:
vars
a rank-1 `CellVariable` or `FaceVariable` object.
title
displayed at the top of the `Viewer` window
scale
if not `None`, scale all arrow lengths by this value
sparsity
if not `None`, then this number of arrows will be
randomly chosen (weighted by the cell volume or face area)
log
if `True`, arrow length goes at the base-10 logarithm of the magnitude
limits : dict
a (deprecated) alternative to limit keyword arguments
xmin, xmax, ymin, ymax, datamin, datamax
displayed range of data. Any limit set to
a (default) value of `None` will autoscale.
axes
if not `None`, `vars` will be plotted into this Matplotlib `Axes` object
figaspect
desired aspect ratio of figure. If arg is a number, use that aspect
ratio. If arg is 'auto', the aspect ratio will be determined from
the Variable's mesh.
"""
kwlimits.update(limits)
AbstractMatplotlib2DViewer.__init__(self,
vars=vars,
title=title,
axes=axes,
figaspect=figaspect,
**kwlimits)
self.quiver(sparsity=sparsity, scale=scale)
self.log = log
self._plot()
def __init__(self, vars, title=None, limits={}, cmap=None, colorbar='vertical', axes=None, figaspect='auto', **kwlimits):
"""
Creates a `Matplotlib2DGridViewer`.
:Parameters:
vars
A `CellVariable` object.
title
displayed at the top of the `Viewer` window
limits : dict
a (deprecated) alternative to limit keyword arguments
cmap
The colormap. Defaults to `matplotlib.cm.jet`
xmin, xmax, ymin, ymax, datamin, datamax
displayed range of data. Any limit set to
a (default) value of `None` will autoscale.
colorbar
plot a colorbar in specified orientation if not `None`
axes
if not `None`, `vars` will be plotted into this Matplotlib `Axes` object
figaspect
desired aspect ratio of figure. If arg is a number, use that aspect
ratio. If arg is 'auto', the aspect ratio will be determined from
the Variable's mesh.
"""
kwlimits.update(limits)
AbstractMatplotlib2DViewer.__init__(self, vars=vars, title=title,
cmap=cmap, colorbar=colorbar, axes=axes, figaspect=figaspect,
**kwlimits)
xmin, ymin = self.vars[0].mesh.extents['min']
xmax, ymax = self.vars[0].mesh.extents['max']
self.image = self.axes.imshow(self._data,
extent=(xmin, xmax, ymin, ymax),
vmin=0, vmax=1,
cmap=self.cmap)
self.axes.set_xlim(xmin=self._getLimit('xmin'),
xmax=self._getLimit('xmax'))
self.axes.set_ylim(ymin=self._getLimit('ymin'),
ymax=self._getLimit('ymax'))
if title is None:
self.axes.set_title(self.vars[0].name)
def __init__(self, vars, title=None, limits={}, cmap=None, colorbar='vertical', axes=None, number=10, levels=None, figaspect='auto', **kwlimits):
"""Creates a `Matplotlib2DContourViewer`.
Parameters
----------
vars : ~fipy.variables.cellVariable.CellVariable
`Variable` to display
title : str, optional
displayed at the top of the `Viewer` window
limits : dict, optional
a (deprecated) alternative to limit keyword arguments
float xmin, xmax, ymin, ymax, datamin, datamax : float, optional
displayed range of data. Any limit set to
a (default) value of `None` will autoscale.
cmap : ~matplotlib.colors.Colormap, optional
the Colormap.
Defaults to `matplotlib.cm.jet`
colorbar : bool, optional
plot a color bar in specified orientation if not `None`
axes : ~matplotlib.axes.Axes, optional
if not `None`, `vars` will be plotted into this Matplotlib `Axes` object
number : int, optional
contour `number` automatically-chosen levels
levels : :obj:`list` of :obj:`float`, optional
A list of numbers indicating the level
curves to draw; e.g. to draw just the zero contour pass
``levels=[0]``
figaspect : float
desired aspect ratio of figure. If arg is a number, use that aspect
ratio. If arg is `auto`, the aspect ratio will be determined from
the Variable's mesh.
"""
kwlimits.update(limits)
AbstractMatplotlib2DViewer.__init__(self, vars=vars, title=title,
cmap=cmap, colorbar=colorbar, axes=axes,
figaspect=figaspect,
**kwlimits)
self.number = number
self.levels = levels
self._plot()
def __init__(self, vars, title=None, limits={}, cmap=None, colorbar='vertical', axes=None, number=10, levels=None, figaspect='auto', **kwlimits):
"""Creates a `Matplotlib2DContourViewer`.
:Parameters:
vars
a `CellVariable` object.
title
displayed at the top of the `Viewer` window
limits : dict
a (deprecated) alternative to limit keyword arguments
xmin, xmax, ymin, ymax, datamin, datamax
displayed range of data. Any limit set to
a (default) value of `None` will autoscale.
cmap
the colormap. Defaults to `matplotlib.cm.jet`
colorbar
plot a colorbar in specified orientation if not `None`
axes
if not `None`, `vars` will be plotted into this Matplotlib `Axes` object
number
contour `number` automatically-chosen levels
*levels* [level0, level1, ..., leveln]
A list of floating point numbers indicating the level
curves to draw; e.g. to draw just the zero contour pass
``levels=[0]``
figaspect
desired aspect ratio of figure. If arg is a number, use that aspect
ratio. If arg is 'auto', the aspect ratio will be determined from
the Variable's mesh.
"""
kwlimits.update(limits)
AbstractMatplotlib2DViewer.__init__(self, vars=vars, title=title,
cmap=cmap, colorbar=colorbar, axes=axes,
figaspect=figaspect,
**kwlimits)
self.number = number
self.levels = levels
self._plot()
def __init__(self,
vars,
title=None,
log=False,
limits={},
axes=None,
figaspect='auto',
density=1,
linewidth=None,
color=None,
cmap=None,
norm=None,
arrowsize=1,
arrowstyle='-|>',
minlength=0.1,
**kwlimits):
"""Creates a `MatplotlibStreamViewer`.
:Parameters:
vars
a rank-1 `CellVariable` or `FaceVariable` object.
title
displayed at the top of the `Viewer` window
log
if `True`, arrow length goes at the base-10 logarithm of the magnitude
limits : dict
a (deprecated) alternative to limit keyword arguments
xmin, xmax, ymin, ymax, datamin, datamax
displayed range of data. Any limit set to
a (default) value of `None` will autoscale.
axes
if not `None`, `vars` will be plotted into this Matplotlib `Axes` object
figaspect
desired aspect ratio of figure. If arg is a number, use that aspect
ratio. If arg is 'auto', the aspect ratio will be determined from
the Variable's mesh.
*density* : float or 2-tuple
Controls the closeness of streamlines. When `density = 1`, the domain
is divided into a 25x25 grid---*density* linearly scales this grid.
Each cell in the grid can have, at most, one traversing streamline.
For different densities in each direction, use [density_x, density_y].
linewidth : Numeric or rank-0 `MeshVariable`
vary linewidth when given a `CellVariable` or `FaceVariable` of same
type as vars.
*color* : matplotlib color code, or rank-0 `MeshVariable`
Streamline color. When given an array with the type as vars,
*color* values are converted to colors using *cmap*.
*cmap* : :class:`~matplotlib.colors.Colormap`
Colormap used to plot streamlines and arrows. Only necessary when using
an `MeshVariable` input for *color*.
*norm* : :class:`~matplotlib.colors.Normalize`
Normalize object used to scale luminance data to 0, 1. If None, stretch
(min, max) to (0, 1). Only necessary when *color* is an `MeshVariable`.
*arrowsize* : float
Factor scale arrow size.
*arrowstyle* : str
Arrow style specification.
See :class:`~matplotlib.patches.FancyArrowPatch`.
*minlength* : float
Minimum length of streamline in axes coordinates.
"""
kwlimits.update(limits)
AbstractMatplotlib2DViewer.__init__(self,
vars=vars,
title=title,
axes=axes,
figaspect=figaspect,
**kwlimits)
self.log = log
self.kwargs = dict(density=density,
cmap=cmap,
norm=norm,
arrowsize=arrowsize,
arrowstyle=arrowstyle,
minlength=minlength)
self.linewidth = linewidth
self.color = color
self._stream = None
self._plot()
def __init__(self,
vars,
title=None,
log=False,
limits={},
axes=None,
figaspect='auto',
density=1,
linewidth=None,
color=None,
cmap=None,
norm=None,
arrowsize=1,
arrowstyle='-|>',
minlength=0.1,
**kwlimits):
"""Creates a `MatplotlibStreamViewer`.
Parameters
----------
vars : ~fipy.variables.cellVariable.CellVariable or ~fipy.variables.faceVariable.FaceVariable
rank-1 `Variable` to display
title : str, optional
displayed at the top of the `Viewer` window
log : bool, optional
if `True`, arrow length goes at the base-10 logarithm of the magnitude
limits : dict, optional
a (deprecated) alternative to limit keyword arguments
float xmin, xmax, ymin, ymax, datamin, datamax : float
displayed range of data. Any limit set to
a (default) value of `None` will autoscale.
axes : ~matplotlib.axes.Axes, optional
if not `None`, `vars` will be plotted into this Matplotlib `Axes` object
figaspect : float, optional
desired aspect ratio of figure. If arg is a number, use that aspect
ratio. If arg is `auto`, the aspect ratio will be determined from
the Variable's mesh.
density : float or (float, float), optional
Controls the closeness of streamlines. When ``density = 1``,
the domain is divided into a 30x30 grid. *density* linearly
scales this grid. Each cell in the grid can have, at most, one
traversing streamline. For different densities in each
direction, use a tuple (density_x, density_y).
linewidth : array_like or ~fipy.variables.cellVariable.CellVariable or ~fipy.variables.faceVariable.FaceVariable, optional
The width of the stream lines. With a rank-0 `CellVariable` or
`FaceVariable` the line width can be varied across the grid.
The MeshVariable must have the same type and be defined on
the same `Mesh` as *vars*.
color : str or ~fipy.variables.cellVariable.CellVariable or ~fipy.variables.faceVariable.FaceVariable, optional
The streamline color as a matplotlib color code or a field of
numbers. If given a rank-0 `CellVariable` or `FaceVariable`,
its values are converted to colors using *cmap* and *norm*.
The MeshVariable must have the same type and be defined on the
same `Mesh` as *vars*.
cmap : ~matplotlib.colors.Colormap, optional
Colormap used to plot streamlines and arrows. This is only
used if *color* is a MeshVariable.
norm : ~matplotlib.colors.Normalize, optional
Normalize object used to scale luminance data to 0, 1. If
``None``, stretch (min, max) to (0, 1). Only necessary when
*color* is a MeshVariable.
arrowsize : float, optional
Scaling factor for the arrow size.
arrowstyle : str, optional
Arrow style specification.
See `~matplotlib.patches.FancyArrowPatch`.
minlength : float, optional
Minimum length of streamline in axes coordinates.
"""
kwlimits.update(limits)
AbstractMatplotlib2DViewer.__init__(self,
vars=vars,
title=title,
axes=axes,
figaspect=figaspect,
**kwlimits)
self.log = log
self.kwargs = dict(density=density,
cmap=cmap,
norm=norm,
arrowsize=arrowsize,
arrowstyle=arrowstyle,
minlength=minlength)
self.linewidth = linewidth
self.color = color
self._stream = None
self._plot()
