def __init__(self, vars, title=None, limits={}, cmap=None, colorbar='vertical', axes=None, **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
"""
kwlimits.update(limits)
_MatplotlibViewer.__init__(self, vars=vars, title=title,
cmap=cmap, colorbar=colorbar, axes=axes,
**kwlimits)
self.image = self.axes.imshow(self._getData(),
extent=(self._getLimit('xmin'), self._getLimit('xmax'),
self._getLimit('ymin'), self._getLimit('ymax')),
vmin=self._getLimit(key=('datamin', 'zmin')),
vmax=self._getLimit(key=('datamax', 'zmax')),
cmap=self.cmap)
if title is None:
self.axes.set_title(self.vars[0].getName())
def __init__(self, vars, title=None, scale=None, sparsity=None, limits={}, **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)
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.
"""
kwlimits.update(limits)
_MatplotlibViewer.__init__(self, vars=vars, title=title, **kwlimits)
self.quiver(sparsity=sparsity, scale=scale)
self.colorbar = False
self._plot()
def __init__(self, vars, title=None, limits={}, cmap=None, colorbar='vertical', axes=None, **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
"""
kwlimits.update(limits)
_MatplotlibViewer.__init__(self, vars=vars, title=title,
cmap=cmap, colorbar=colorbar, axes=axes,
**kwlimits)
self._plot()
def __init__(self, vars, title=None, limits={}, **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.
"""
kwlimits.update(limits)
_MatplotlibViewer.__init__(self, vars=vars, title=title, **kwlimits)
self.colorbar = None
self._plot()
import pylab
# colorbar will not automatically update
# http://sourceforge.net/mailarchive/forum.php?thread_id=10159140&forum_id=33405
##from fipy.tools.numerix import array
##self.colorbar = pylab.colorbar(array(self.vars[0]))
self.colorbar = pylab.colorbar()
def __init__(self, vars, title=None, xlog=False, ylog=False, limits={}, legend='upper left', axes=None, **kwlimits):
"""
:Parameters:
vars
a `CellVariable` or tuple of `CellVariable` objects to plot
title
displayed at the top of the `Viewer` window
xlog
log scaling of x axis if `True`
ylog
log scaling of y axis if `True`
limits : dict
a (deprecated) alternative to limit keyword arguments
xmin, xmax, datamin, datamax
displayed range of data. Any limit set to
a (default) value of `None` will autoscale.
(*ymin* and *ymax* are synonyms for *datamin* and *datamax*).
legend
place a legend at the specified position, if not `None`
axes
if not `None`, `vars` will be plotted into this Matplotlib `Axes` object
"""
kwlimits.update(limits)
_MatplotlibViewer.__init__(self, vars=vars, title=title, axes=axes, **kwlimits)
import pylab
if xlog and ylog:
self.lines = [self.axes.loglog(*datum) for datum in self._getData()]
elif xlog:
self.lines = [self.axes.semilogx(*datum) for datum in self._getData()]
elif ylog:
self.lines = [self.axes.semilogy(*datum) for datum in self._getData()]
else:
self.lines = [self.axes.plot(*datum) for datum in self._getData()]
if legend is not None:
self.axes.legend([var.getName() for var in self.vars], loc=legend)
self.axes.set_xlim(xmin=self._getLimit('xmin'),
xmax=self._getLimit('xmax'))
ymin = self._getLimit(('datamin', 'ymin'))
ymax = self._getLimit(('datamax', 'ymax'))
self.axes.set_ylim(ymin=ymin, ymax=ymax)
if ymax is None or ymin is None:
import warnings
warnings.warn("Matplotlib1DViewer efficiency is improved by setting the 'datamax' and 'datamin' keys", UserWarning, stacklevel=2)
def __init__(self, vars, title=None, limits={}, cmap=None, **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 `pylab.cm.jet`
xmin, xmax, ymin, ymax, datamin, datamax
displayed range of data. Any limit set to
a (default) value of `None` will autoscale.
"""
kwlimits.update(limits)
_MatplotlibViewer.__init__(self, vars=vars, title=title, **kwlimits)
import pylab
if cmap is None:
self.cmap = pylab.cm.jet
else:
self.cmap = cmap
self.image = pylab.imshow(self._getData(),
extent=(self._getLimit('xmin'), self._getLimit('xmax'),
self._getLimit('ymin'), self._getLimit('ymax')),
vmin=self._getLimit(key=('datamin', 'zmin')),
vmax=self._getLimit(key=('datamax', 'zmax')),
cmap=self.cmap)
if title is None:
pylab.title(self.vars[0].getName())
# colorbar will not automatically update
# http://sourceforge.net/mailarchive/forum.php?thread_id=10159140&forum_id=33405
self.colorbar = pylab.colorbar()
self.colorbar.set_label(self.vars[0].getName())
def __init__(self, vars, title=None, limits={}, cmap=None, colorbar=True, axes=None, **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
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
"""
kwlimits.update(limits)
_MatplotlibViewer.__init__(self, vars=vars, title=title, figaspect=1. / 1.3,
cmap=cmap, colorbar=colorbar, axes=axes,
**kwlimits)
self.mesh = self.vars[0].getMesh()
vertexIDs = self.mesh._getOrderedCellVertexIDs()
vertexCoords = self.mesh.getVertexCoords()
xCoords = numerix.take(vertexCoords[0], vertexIDs)
yCoords = numerix.take(vertexCoords[1], vertexIDs)
polys = []
for x, y in zip(xCoords.swapaxes(0,1), yCoords.swapaxes(0,1)):
if hasattr(x, 'mask'):
x = x.compressed()
if hasattr(y, 'mask'):
y = y.compressed()
polys.append(zip(x,y))
import matplotlib
from matplotlib.collections import PolyCollection
self.collection = PolyCollection(polys)
self.collection.set_linewidth(0.5)
try:
self.axes.add_patch(self.collection)
except:
# PolyCollection not child of PatchCollection in matplotlib 0.98
self.axes.add_collection(self.collection)
xmin = self._getLimit('xmin', default=xCoords.min())
xmax = self._getLimit('xmax', default=xCoords.max())
ymin = self._getLimit('ymin', default=yCoords.min())
ymax = self._getLimit('ymax', default=yCoords.max())
self.axes.set_xlim(xmin=xmin, xmax=xmax)
self.axes.set_ylim(ymin=ymin, ymax=ymax)
self._plot()
def __init__(self, vars, title=None, limits={}, cmap=None, **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
cmap
the colormap. Defaults to `pylab.cm.jet`
xmin, xmax, ymin, ymax, datamin, datamax
displayed range of data. Any limit set to
a (default) value of `None` will autoscale.
"""
kwlimits.update(limits)
_MatplotlibViewer.__init__(self, vars=vars, title=title, figaspect=1. / 1.3, **kwlimits)
self.colorbar = None
self.mesh = self.vars[0].getMesh()
vertexIDs = self.mesh._getOrderedCellVertexIDs()
vertexCoords = self.mesh.getVertexCoords()
xCoords = numerix.take(vertexCoords[0], vertexIDs)
yCoords = numerix.take(vertexCoords[1], vertexIDs)
polys = []
for x, y in zip(xCoords.swapaxes(0,1), yCoords.swapaxes(0,1)):
if hasattr(x, 'mask'):
x = x.compressed()
if hasattr(y, 'mask'):
y = y.compressed()
polys.append(zip(x,y))
import pylab
import matplotlib
fig = pylab.figure(self.id)
ax = fig.get_axes()[0]
from matplotlib.collections import PolyCollection
self.collection = PolyCollection(polys)
self.collection.set_linewidth(0.5)
try:
ax.add_patch(self.collection)
except:
# PolyCollection not child of PatchCollection in matplotlib 0.98
ax.add_collection(self.collection)
if self._getLimit('xmin') is None:
xmin = xCoords.min()
else:
xmin = self._getLimit('xmin')
if self._getLimit('xmax') is None:
xmax = xCoords.max()
else:
xmax = self._getLimit('xmax')
if self._getLimit('ymin') is None:
ymin = yCoords.min()
else:
ymin = self._getLimit('ymin')
if self._getLimit('ymax') is None:
ymax = yCoords.max()
else:
ymax = self._getLimit('ymax')
pylab.axis((xmin, xmax, ymin, ymax))
cbax, kw = matplotlib.colorbar.make_axes(ax, orientation='vertical')
# Set the colormap and norm to correspond to the data for which
# the colorbar will be used.
if cmap is None:
self.cmap = matplotlib.cm.jet
else:
self.cmap = cmap
norm = matplotlib.colors.normalize(vmin=-1, vmax=1)
# ColorbarBase derives from ScalarMappable and puts a colorbar
# in a specified axes, so it has everything needed for a
# standalone colorbar. There are many more kwargs, but the
# following gives a basic continuous colorbar with ticks
# and labels.
self.cb = matplotlib.colorbar.ColorbarBase(cbax, cmap=self.cmap,
norm=norm,
orientation='vertical')
self.cb.set_label(self.vars[0].name)
self._plot()
