def drawall(self, **kwargs):
if not self.n == self.drawax.shape:
self.drawax = np.ones(self.n, dtype='bool')
if not self.n[1] == self.hrel.shape[0]:
self.hrel = np.ones(self.n[1], dtype='float32')
if not self.n[0] == self.vrel.shape[0]:
self.vrel = np.ones(self.n[0], dtype='float32')
if kwargs.has_key('lw'):
kwargs['linewidth'] = kwargs.pop('lw')
if not kwargs.has_key('linewidth'):
kwargs['linewidth'] = self.linewidth
else:
self.linewidth = kwargs['linewidth']
forcesharex = False
forcesharey = False
if kwargs.has_key('sharex'):
forcesharex = True
if kwargs.has_key('sharey'):
forcesharey = True
inter = pylab.isinteractive()
pylab.interactive(
False) # wait to draw the axes, until they've all been created.
axg = self.axgrid()
for iv in range(self.n[0]):
for ih in range(self.n[1]):
if forcesharex: # I should put this functionality into a func.
pass
elif self.sharex[iv, ih] and self._sharex_ax[self.sharex[iv,
ih]]:
kwargs['sharex'] = self._sharex_ax[self.sharex[iv, ih]]
elif kwargs.has_key('sharex'):
kwargs.pop('sharex')
if forcesharey:
pass
elif self.sharey[iv, ih] and self._sharey_ax[self.sharey[iv,
ih]]:
kwargs['sharey'] = self._sharey_ax[self.sharey[iv, ih]]
elif kwargs.has_key('sharey'):
kwargs.pop('sharey')
if self.drawax[iv, ih]:
#self.ax[iv,ih]=myaxes(axg[iv,ih,:],**kwargs)
self.ax[iv, ih] = axes(axg[iv, ih, :], **kwargs)
self.ax[iv, ih].hold(True)
if self.sharex[
iv,
ih] and not self._sharex_ax[self.sharex[iv, ih]]:
self._sharex_ax[self.sharex[iv, ih]] = self.ax[iv, ih]
if self.sharey[
iv,
ih] and not self._sharey_ax[self.sharey[iv, ih]]:
self._sharey_ax[self.sharey[iv, ih]] = self.ax[iv, ih]
flag = True
self._xlabel_ax = self.ax[-1, 0]
self._ylabel_ax = self._xlabel_ax
pylab.interactive(inter)
pylab.draw_if_interactive()
return self.ax
def drawall(self, **kwargs):
if not self.n == self.drawax.shape:
self.drawax = np.ones(self.n, dtype='bool')
if 'lw' in kwargs.keys():
kwargs['linewidth'] = kwargs.pop('lw', self.linewidth)
if 'linewidth' not in kwargs.keys():
kwargs['linewidth'] = self.linewidth
else:
self.linewidth = kwargs['linewidth']
inter = pylab.isinteractive()
pylab.interactive(False)
# wait to draw the axes, until they've all been
# created.
for iv, ih in self._iter_axinds():
if self.drawax[iv, ih]:
self.ax[iv, ih] = axes(self.axPlacer(iv, ih),
sharex=self.sharex(iv, ih),
sharey=self.sharey(iv, ih),
**kwargs)
self._xlabel_ax = self.ax[-1, 0]
self._ylabel_ax = self._xlabel_ax
pylab.interactive(inter)
pylab.draw_if_interactive()
return self.ax
def drawall(self, **kwargs):
if not self.n == self.drawax.shape:
self.drawax = np.ones(self.n, dtype='bool')
if 'lw' in kwargs.keys():
kwargs['linewidth'] = kwargs.pop('lw', self.linewidth)
if 'linewidth' not in kwargs.keys():
kwargs['linewidth'] = self.linewidth
else:
self.linewidth = kwargs['linewidth']
inter = pylab.isinteractive()
pylab.interactive(False)
# wait to draw the axes, until they've all been
# created.
for iv, ih in self._iter_axinds():
if self.drawax[iv, ih]:
self.ax[iv, ih] = axes(self.axPlacer(iv, ih),
sharex=self.sharex(iv, ih),
sharey=self.sharey(iv, ih),
**kwargs)
self._xlabel_ax = self.ax[-1, 0]
self._ylabel_ax = self._xlabel_ax
pylab.interactive(inter)
pylab.draw_if_interactive()
return self.ax
def draw_networkx(G, pos, with_labels=True, **kwds):
"""Draw the graph G with given node positions pos
Usage:
>>> from networkx_v099 import *
>>> import pylab as P
>>> ax=P.subplot(111)
>>> G=dodecahedral_graph()
>>> pos=spring_layout(G)
>>> draw_networkx(G,pos,ax=ax)
This is same as 'draw' but the node positions *must* be
specified in the variable pos.
pos is a dictionary keyed by vertex with a two-tuple
of x-y positions as the value.
See networkx_v099.layout for functions that compute node positions.
An optional matplotlib axis can be provided through the
optional keyword ax.
with_labels contols text labeling of the nodes
Also see:
draw_networkx_nodes()
draw_networkx_edges()
draw_networkx_labels()
"""
from matplotlib.pylab import draw_if_interactive
node_collection=draw_networkx_nodes(G, pos, **kwds)
edge_collection=draw_networkx_edges(G, pos, **kwds)
if with_labels:
draw_networkx_labels(G, pos, **kwds)
draw_if_interactive()
def format_dateaxis(subplot, freq):
"""
Pretty-formats the date axis (x-axis).
Major and minor ticks are automatically set for the frequency of the
current underlying series. As the dynamic mode is activated by
default, changing the limits of the x axis will intelligently change
the positions of the ticks.
"""
majlocator = TimeSeries_DateLocator(freq,
dynamic_mode=True,
minor_locator=False,
plot_obj=subplot)
minlocator = TimeSeries_DateLocator(freq,
dynamic_mode=True,
minor_locator=True,
plot_obj=subplot)
subplot.xaxis.set_major_locator(majlocator)
subplot.xaxis.set_minor_locator(minlocator)
majformatter = TimeSeries_DateFormatter(freq,
dynamic_mode=True,
minor_locator=False,
plot_obj=subplot)
minformatter = TimeSeries_DateFormatter(freq,
dynamic_mode=True,
minor_locator=True,
plot_obj=subplot)
subplot.xaxis.set_major_formatter(majformatter)
subplot.xaxis.set_minor_formatter(minformatter)
pylab.draw_if_interactive()
def tsplot(series, *args, **kwargs):
"""Plots the series to the current TimeSeries subplot.
If the current plot is not a TimeSeriesPlot, a new TimeSeriesFigure is created."""
# allow callers to override the hold state by passing hold=True|False
b = pylab.ishold()
h = kwargs.pop('hold', None)
if h is not None:
pylab.hold(h)
# Get the current figure, or create one
figManager = _pylab_helpers.Gcf.get_active()
if figManager is not None :
fig = figManager.canvas.figure
if not isinstance(fig, TimeSeriesFigure):
fig = tsfigure(series=series)
else:
fig = tsfigure(series=series)
# Get the current axe, or create one
sub = fig._axstack()
if sub is None:
sub = fig.add_tsplot(111,series=series,**kwargs)
try:
ret = sub.tsplot(series, *args, **kwargs)
pylab.draw_if_interactive()
except:
pylab.hold(b)
raise
pylab.hold(b)
return ret
def format_dateaxis(subplot, freq):
"""
Pretty-formats the date axis (x-axis).
Major and minor ticks are automatically set for the frequency of the
current underlying series. As the dynamic mode is activated by
default, changing the limits of the x axis will intelligently change
the positions of the ticks.
"""
majlocator = TimeSeries_DateLocator(freq, dynamic_mode=True,
minor_locator=False,
plot_obj=subplot)
minlocator = TimeSeries_DateLocator(freq, dynamic_mode=True,
minor_locator=True,
plot_obj=subplot)
subplot.xaxis.set_major_locator(majlocator)
subplot.xaxis.set_minor_locator(minlocator)
majformatter = TimeSeries_DateFormatter(freq, dynamic_mode=True,
minor_locator=False,
plot_obj=subplot)
minformatter = TimeSeries_DateFormatter(freq, dynamic_mode=True,
minor_locator=True,
plot_obj=subplot)
subplot.xaxis.set_major_formatter(majformatter)
subplot.xaxis.set_minor_formatter(minformatter)
pylab.draw_if_interactive()
def __init__(self, fig=None, rect=None, **kwargs):
if fig is None:
fig = pylab.gcf()
if rect is None:
rect = [.15, .15, .75, .75]
super(myaxes, self).__init__(fig, rect, **kwargs)
fig.add_axes(self)
pylab.draw_if_interactive()
def __init__(self,fig=None,rect=None,**kwargs):
if fig is None:
fig=pylab.gcf()
if rect is None:
rect=[.15,.15,.75,.75]
super(myaxes,self).__init__(fig,rect,**kwargs)
fig.add_axes(self)
pylab.draw_if_interactive()
def add_yaxis(fsp=None, position='right', yscale=None, basey=10, subsy=None,
**kwargs):
"""Adds a second y-axis to a plot.
:Parameters:
`fsp` : Subplot *[None]*
Subplot to which the secondary y-axis is added. If *None*, the current
subplot is selected
`position` : String in `('left','right')` *['right']*
Position of the new axis.
`yscale` : String, in `('log', 'linear')` *[None]*
Scale of the new axis. If None, uses the same scale as the first y
axis
`basey` : Integer *[10]*
Base of the logarithm for the new axis (if needed).
`subsy` : sequence *[None]*
Sequence of the location of the minor ticks;
None defaults to autosubs, which depend on the number of decades in
the plot.
Eg for base 10, subsy=(1,2,5) will put minor ticks on 1,2,5,11,12,15,
21, ....
To turn off minor ticking, set subsy=[]
"""
if fsp is None:
fsp = pylab.gca()
if not isinstance(fsp, TimeSeriesPlot):
raise TypeError("The current plot is not a TimeSeriesPlot")
fig = fsp.figure
axisini = fsp.axis()
fsp_alt_args = (fsp._rows, fsp._cols, fsp._num+1)
fsp_alt = fig.add_tsplot(frameon=False, position=fsp.get_position(),
sharex=fsp, *fsp_alt_args)
# Set position ....................
if position == 'right':
(inipos, newpos) = ('left', 'right')
else:
(inipos, newpos) = ('right','left')
# Force scales tics to one side ...
fsp.yaxis.set_ticks_position(inipos)
fsp.yaxis.set_label_position(inipos)
# Force 2nd ticks to the other side..
fsp_alt.yaxis.set_ticks_position(newpos)
fsp_alt.yaxis.set_label_position(newpos)
# Force period axis scale..........
if yscale is None:
yscale = fsp.get_yscale()
try:
basey = fsp.yaxis.get_major_locator()._base
except AttributeError:
basey = 10.
fsp_alt.set_yscale(yscale, basey=basey, subsy=subsy)
# Guess we're good ................
fsp_alt.set_xticks('')
fsp_alt.set_xticklabels('')
pylab.draw_if_interactive()
return fsp_alt
def drawall(self, **kwargs):
if not self.n == self.drawax.shape:
self.drawax = np.ones(self.n, dtype='bool')
if not self.n[1] == self.hrel.shape[0]:
self.hrel = np.ones(self.n[1], dtype='float32')
if not self.n[0] == self.vrel.shape[0]:
self.vrel = np.ones(self.n[0], dtype='float32')
if 'lw' in kwargs.keys():
kwargs['linewidth'] = kwargs.pop('lw', self.linewidth)
if 'linewidth' not in kwargs.keys():
kwargs['linewidth'] = self.linewidth
else:
self.linewidth = kwargs['linewidth']
forcesharex = False
forcesharey = False
if 'sharex' in kwargs.keys():
forcesharex = True
if 'sharey' in kwargs.keys():
forcesharey = True
inter = pylab.isinteractive()
pylab.interactive(False)
# wait to draw the axes, until they've all been
# created.
axg = self.axgrid()
for iv in range(self.n[0]):
for ih in range(self.n[1]):
if forcesharex: # I should put this functionality into a func.
pass
elif (self.sharex[iv, ih] and
self._sharex_ax[self.sharex[iv, ih]]):
kwargs['sharex'] = self._sharex_ax[self.sharex[iv, ih]]
elif 'sharex' in kwargs.keys():
kwargs.pop('sharex')
if forcesharey:
pass
elif (self.sharey[iv, ih] and
self._sharey_ax[self.sharey[iv, ih]]):
kwargs['sharey'] = self._sharey_ax[self.sharey[iv, ih]]
elif 'sharey' in kwargs.keys():
kwargs.pop('sharey')
if self.drawax[iv, ih]:
# self.ax[iv,ih]=myaxes(axg[iv,ih,:],**kwargs)
self.ax[iv, ih] = axes(axg[iv, ih,:], **kwargs)
self.ax[iv, ih].hold(True)
if self.sharex[iv, ih] and not\
self._sharex_ax[self.sharex[iv, ih]]:
self._sharex_ax[self.sharex[iv, ih]] = self.ax[iv, ih]
if self.sharey[iv, ih] and not\
self._sharey_ax[self.sharey[iv, ih]]:
self._sharey_ax[self.sharey[iv, ih]] = self.ax[iv, ih]
self._xlabel_ax = self.ax[-1, 0]
self._ylabel_ax = self._xlabel_ax
pylab.interactive(inter)
pylab.draw_if_interactive()
return self.ax
def plot_dt(tri, colors=None):
import matplotlib as mpl
from matplotlib import pylab as pl
if colors is None:
colors = [(0,0,0,0.2)]
lc = mpl.collections.LineCollection(np.array([((tri.x[i], tri.y[i]), (tri.x[j], tri.y[j]))
for i, j in tri.edge_db]), colors=colors)
ax = pl.gca()
ax.add_collection(lc)
pl.draw_if_interactive()
def plot_dt(tri, colors=None):
import matplotlib as mpl
from matplotlib import pylab as pl
if colors is None:
colors = [(0,0,0,0.2)]
lc = mpl.collections.LineCollection(sp.array([((tri.x[i], tri.y[i]), (tri.x[j], tri.y[j]))
for i, j in tri.edge_db]), colors=colors)
ax = pl.gca()
ax.add_collection(lc)
pl.draw_if_interactive()
def plot_vo(tri, colors=None):
import matplotlib as mpl
from matplotlib import pylab as pl
if colors is None:
colors = [(0, 1, 0, 0.2)]
lc = mpl.collections.LineCollection(np.array(
[(tri.circumcenters[i], tri.circumcenters[j])
for i in xrange(len(tri.circumcenters))
for j in tri.triangle_neighbors[i] if j != -1]),
colors=colors)
ax = pl.gca()
ax.add_collection(lc)
pl.draw_if_interactive()
def plot_vo(tri, colors=None):
import matplotlib as mpl
from matplotlib import pylab as pl
if colors is None:
colors = [(0, 1, 0, 0.2)]
lc = mpl.collections.LineCollection(np.array(
[(tri.circumcenters[i], tri.circumcenters[j])
for i in xrange(len(tri.circumcenters))
for j in tri.triangle_neighbors[i] if j != -1]),
colors=colors)
ax = pl.gca()
ax.add_collection(lc)
pl.draw_if_interactive()
def plot_cc(tri, edgecolor=None):
import matplotlib as mpl
from matplotlib import pylab as pl
if edgecolor is None:
edgecolor = (0,0,1,0.2)
dxy = (np.array([(tri.x[i], tri.y[i]) for i,j,k in tri.triangle_nodes])
- tri.circumcenters)
r = np.hypot(dxy[:,0], dxy[:,1])
ax = pl.gca()
for i in range(len(r)):
p = mpl.patches.Circle(tri.circumcenters[i], r[i], resolution=100, edgecolor=edgecolor,
facecolor=(1,1,1,0), linewidth=0.2)
ax.add_patch(p)
pl.draw_if_interactive()
def plot_cc(tri, edgecolor=None):
import matplotlib as mpl
from matplotlib import pylab as pl
if edgecolor is None:
edgecolor = (0,0,1,0.2)
dxy = (sp.array([(tri.x[i], tri.y[i]) for i,j,k in tri.triangle_nodes])
- tri.circumcenters)
r = sp.hypot(dxy[:,0], dxy[:,1])
ax = pl.gca()
for i in xrange(len(r)):
p = mpl.patches.Circle(tri.circumcenters[i], r[i], resolution=100, edgecolor=edgecolor,
facecolor=(1,1,1,0), linewidth=0.2)
ax.add_patch(p)
pl.draw_if_interactive()
def format_dateaxis(subplot, freq, index):
"""
Pretty-formats the date axis (x-axis).
Major and minor ticks are automatically set for the frequency of the
current underlying series. As the dynamic mode is activated by
default, changing the limits of the x axis will intelligently change
the positions of the ticks.
"""
from matplotlib import pylab
# handle index specific formatting
# Note: DatetimeIndex does not use this
# interface. DatetimeIndex uses matplotlib.date directly
if isinstance(index, ABCPeriodIndex):
majlocator = TimeSeries_DateLocator(freq,
dynamic_mode=True,
minor_locator=False,
plot_obj=subplot)
minlocator = TimeSeries_DateLocator(freq,
dynamic_mode=True,
minor_locator=True,
plot_obj=subplot)
subplot.xaxis.set_major_locator(majlocator)
subplot.xaxis.set_minor_locator(minlocator)
majformatter = TimeSeries_DateFormatter(freq,
dynamic_mode=True,
minor_locator=False,
plot_obj=subplot)
minformatter = TimeSeries_DateFormatter(freq,
dynamic_mode=True,
minor_locator=True,
plot_obj=subplot)
subplot.xaxis.set_major_formatter(majformatter)
subplot.xaxis.set_minor_formatter(minformatter)
# x and y coord info
subplot.format_coord = functools.partial(_format_coord, freq)
elif isinstance(index, ABCTimedeltaIndex):
subplot.xaxis.set_major_formatter(TimeSeries_TimedeltaFormatter())
else:
raise TypeError("index type not supported")
pylab.draw_if_interactive()
def format_dateaxis(subplot, freq, index):
"""
Pretty-formats the date axis (x-axis).
Major and minor ticks are automatically set for the frequency of the
current underlying series. As the dynamic mode is activated by
default, changing the limits of the x axis will intelligently change
the positions of the ticks.
"""
# handle index specific formatting
# Note: DatetimeIndex does not use this
# interface. DatetimeIndex uses matplotlib.date directly
if isinstance(index, PeriodIndex):
majlocator = TimeSeries_DateLocator(freq, dynamic_mode=True,
minor_locator=False,
plot_obj=subplot)
minlocator = TimeSeries_DateLocator(freq, dynamic_mode=True,
minor_locator=True,
plot_obj=subplot)
subplot.xaxis.set_major_locator(majlocator)
subplot.xaxis.set_minor_locator(minlocator)
majformatter = TimeSeries_DateFormatter(freq, dynamic_mode=True,
minor_locator=False,
plot_obj=subplot)
minformatter = TimeSeries_DateFormatter(freq, dynamic_mode=True,
minor_locator=True,
plot_obj=subplot)
subplot.xaxis.set_major_formatter(majformatter)
subplot.xaxis.set_minor_formatter(minformatter)
# x and y coord info
subplot.format_coord = lambda t, y: (
"t = {0} y = {1:8f}".format(Period(ordinal=int(t), freq=freq), y))
elif isinstance(index, TimedeltaIndex):
subplot.xaxis.set_major_formatter(
TimeSeries_TimedeltaFormatter())
else:
raise TypeError('index type not supported')
pylab.draw_if_interactive()
def tsplot(series, *args, **kwargs):
"""
Plots the series to the current :class:`TimeSeriesPlot`.
If the current plot is not a :class:`TimeSeriesPlot`,
a new :class:`TimeSeriesFigure` is created.
Parameters
----------
series : TimeSeries
The time series to plot
%(mandatoryplotargs)s
kwargs : var
Optional arguments for the creation of the subplot.
"""
# allow callers to override the hold state by passing hold=True|False
b = pylab.ishold()
h = kwargs.pop('hold', None)
if h is not None:
pylab.hold(h)
# Get the current figure, or create one
figManager = _pylab_helpers.Gcf.get_active()
if figManager is not None:
fig = figManager.canvas.figure
if not isinstance(fig, TimeSeriesFigure):
fig = tsfigure(series=series)
else:
fig = tsfigure(series=series)
# Get the current axe, or create one
sub = fig._axstack()
if sub is None:
sub = fig.add_tsplot(111, series=series, **kwargs)
try:
ret = sub.tsplot(series, *args, **kwargs)
pylab.draw_if_interactive()
except:
pylab.hold(b)
raise
pylab.hold(b)
return ret
def tsplot(series, *args, **kwargs):
"""
Plots the series to the current :class:`TimeSeriesPlot`.
If the current plot is not a :class:`TimeSeriesPlot`,
a new :class:`TimeSeriesFigure` is created.
Parameters
----------
series : TimeSeries
The time series to plot
%(mandatoryplotargs)s
kwargs : var
Optional arguments for the creation of the subplot.
"""
# allow callers to override the hold state by passing hold=True|False
b = pylab.ishold()
h = kwargs.pop("hold", None)
if h is not None:
pylab.hold(h)
# Get the current figure, or create one
figManager = _pylab_helpers.Gcf.get_active()
if figManager is not None:
fig = figManager.canvas.figure
if not isinstance(fig, TimeSeriesFigure):
fig = tsfigure(series=series)
else:
fig = tsfigure(series=series)
# Get the current axe, or create one
sub = fig._axstack()
if sub is None:
sub = fig.add_tsplot(111, series=series, **kwargs)
try:
ret = sub.tsplot(series, *args, **kwargs)
pylab.draw_if_interactive()
except:
pylab.hold(b)
raise
pylab.hold(b)
return ret
def draw_networkx(G, pos, with_labels=True, **kwds):
"""Draw the graph G with given node positions pos
Usage:
>>> G=nx.dodecahedral_graph()
>>> pos=nx.spring_layout(G)
>>> nx.draw_networkx(G,pos)
This is same as 'draw' but the node positions *must* be
specified in the variable pos.
pos is a dictionary keyed by vertex with a two-tuple
of x-y positions as the value.
See networkx.layout for functions that compute node positions.
An optional matplotlib axis can be provided through the
optional keyword ax.
with_labels contols text labeling of the nodes
Also see:
draw_networkx_nodes()
draw_networkx_edges()
draw_networkx_labels()
"""
try:
import matplotlib.pylab as pylab
except ImportError:
raise ImportError, "Matplotlib required for draw()"
except RuntimeError:
pass # unable to open display
node_collection = draw_networkx_nodes(G, pos, **kwds)
edge_collection = draw_networkx_edges(G, pos, **kwds)
if with_labels:
draw_networkx_labels(G, pos, **kwds)
pylab.draw_if_interactive()
def draw_networkx(G, pos, with_labels=True, **kwds):
"""Draw the graph G with given node positions pos
Usage:
>>> G=nx.dodecahedral_graph()
>>> pos=nx.spring_layout(G)
>>> nx.draw_networkx(G,pos)
This is same as 'draw' but the node positions *must* be
specified in the variable pos.
pos is a dictionary keyed by vertex with a two-tuple
of x-y positions as the value.
See networkx.layout for functions that compute node positions.
An optional matplotlib axis can be provided through the
optional keyword ax.
with_labels contols text labeling of the nodes
Also see:
draw_networkx_nodes()
draw_networkx_edges()
draw_networkx_labels()
"""
try:
import matplotlib.pylab as pylab
except ImportError:
raise ImportError, "Matplotlib required for draw()"
except RuntimeError:
pass # unable to open display
node_collection = draw_networkx_nodes(G, pos, **kwds)
edge_collection = draw_networkx_edges(G, pos, **kwds)
if with_labels:
draw_networkx_labels(G, pos, **kwds)
pylab.draw_if_interactive()
def draw_networkx(G, pos=None, with_labels=True, **kwds):
"""Draw the graph G using Matplotlib.
Draw the graph with Matplotlib with options for node positions,
labeling, titles, and many other drawing features.
See draw() for simple drawing without labels or axes.
Parameters
----------
G : graph
A networkx graph
pos : dictionary, optional
A dictionary with nodes as keys and positions as values.
If not specified a spring layout positioning will be computed.
See networkx.layout for functions that compute node positions.
ax : Matplotlib Axes object, optional
Draw the graph in the specified Matplotlib axes.
with_labels: bool, optional
Set to True (default) to draw labels on the nodes.
nodelist: list, optional
Draw only specified nodes (default G.nodes())
edgelist: list
Draw only specified edges(default=G.edges())
node_size: scalar or array
Size of nodes (default=300). If an array is specified it must be the
same length as nodelist.
node_color: color string, or array of floats
Node color. Can be a single color format string (default='r'),
or a sequence of colors with the same length as nodelist.
If numeric values are specified they will be mapped to
colors using the cmap and vmin,vmax parameters. Can also be a
dictionary keyed by node, and can be in any matplotlib acceptable
color value.
node_shape: string
The shape of the node. Specification is as matplotlib.scatter
marker, one of 'so^>v<dph8' (default='o').
alpha: float
The node transparency (default=1.0)
cmap: Matplotlib colormap
Colormap for mapping intensities of nodes (default=None)
vmin,vmax: floats
Minimum and maximum for node colormap scaling (default=None)
width: float
Line width of edges (default =1.0)
edge_color: color string, or array of floats
Edge color. Can be a single color format string (default='r'),
or a sequence of colors with the same length as edgelist.
If numeric values are specified they will be mapped to
colors using the edge_cmap and edge_vmin,edge_vmax parameters.
edge_ cmap: Matplotlib colormap
Colormap for mapping intensities of edges (default=None)
edge_vmin,edge_vmax: floats
Minimum and maximum for edge colormap scaling (default=None)
style: string
Edge line style (default='solid') (solid|dashed|dotted,dashdot)
labels: dictionary
Node labels in a dictionary keyed by node of text labels (default=None)
font_size: int
Font size for text labels (default=12)
font_color: string
Font color string (default='k' black)
font_weight: string
Font weight (default='normal')
font_family: string
Font family (default='sans-serif')
Notes
-----
Any keywords not listed above are passed through to draw_networkx_nodes(),
draw_networkx_edges(), and draw_networkx_labels(). For finer control
of drawing you can call those functions directly.
Examples
--------
>>> G=nx.dodecahedral_graph()
>>> nx.draw(G)
>>> nx.draw(G,pos=nx.spring_layout(G)) # use spring layout
>>> import pylab
>>> limits=pylab.axis('off') # turn of axis
Also see the NetworkX drawing examples at
http://networkx.lanl.gov/gallery.html
See Also
--------
draw()
draw_networkx_nodes()
draw_networkx_edges()
draw_networkx_labels()
draw_networkx_edge_labels()
"""
try:
import matplotlib.pylab as pylab
except ImportError:
raise ImportError, "Matplotlib required for draw()"
except RuntimeError:
print "Matplotlib unable to open display"
raise
if pos is None:
pos=nx.drawing.spring_layout(G) # default to spring layout
node_patches=draw_networkx_nodes(G, pos, **kwds)
edge_patches=draw_networkx_edges(G, pos, node_patches, **kwds)
if with_labels:
draw_networkx_labels(G, pos, **kwds)
pylab.draw_if_interactive()
def draw(G, pos=None, ax=None, hold=None, **kwds):
"""Draw the graph G with Matplotlib (pylab).
Draw the graph as a simple representation with no node
labels or edge labels and using the full Matplotlib figure area
and no axis labels by default. See draw_networkx() for more
full-featured drawing that allows title, axis labels etc.
Parameters
----------
G : graph
A networkx graph
pos : dictionary, optional
A dictionary with nodes as keys and positions as values.
If not specified a spring layout positioning will be computed.
See networkx.layout for functions that compute node positions.
ax : Matplotlib Axes object, optional
Draw the graph in specified Matplotlib axes.
hold: bool, optional
Set the Matplotlib hold state. If True subsequent draw
commands will be added to the current axes.
**kwds: optional keywords
See networkx.draw_networkx() for a description of optional keywords.
Examples
--------
>>> G=nx.dodecahedral_graph()
>>> nx.draw(G)
>>> nx.draw(G,pos=nx.spring_layout(G)) # use spring layout
See Also
--------
draw_networkx()
draw_networkx_nodes()
draw_networkx_edges()
draw_networkx_labels()
draw_networkx_edge_labels()
Notes
-----
This function has the same name as pylab.draw and pyplot.draw
so beware when using
>>> from networkx import *
since you might overwrite the pylab.draw function.
Good alternatives are:
With pylab:
>>> import pylab as P #
>>> import networkx as nx
>>> G=nx.dodecahedral_graph()
>>> nx.draw(G) # networkx draw()
>>> P.draw() # pylab draw()
With pyplot
>>> import matplotlib.pyplot as plt
>>> import networkx as nx
>>> G=nx.dodecahedral_graph()
>>> nx.draw(G) # networkx draw()
>>> plt.draw() # pyplot draw()
Also see the NetworkX drawing examples at
http://networkx.lanl.gov/gallery.html
"""
try:
import matplotlib.pylab as pylab
except ImportError:
raise ImportError, "Matplotlib required for draw()"
except RuntimeError:
print "Matplotlib unable to open display"
raise
cf=pylab.gcf()
cf.set_facecolor('w')
if ax is None:
if cf._axstack() is None:
ax=cf.add_axes((0,0,1,1))
else:
ax=cf.gca()
# allow callers to override the hold state by passing hold=True|False
b = pylab.ishold()
h = kwds.pop('hold', None)
if h is not None:
pylab.hold(h)
try:
ax.set_axis_off()
draw_networkx(G,pos=pos,ax=ax,**kwds)
pylab.draw_if_interactive()
except:
pylab.hold(b)
raise
pylab.hold(b)
return
def draw_networkx(G, pos=None, with_labels=True, **kwds):
"""Draw the graph G using Matplotlib.
Draw the graph with Matplotlib with options for node positions,
labeling, titles, and many other drawing features.
See draw() for simple drawing without labels or axes.
Parameters
----------
G : graph
A networkx graph
pos : dictionary, optional
A dictionary with nodes as keys and positions as values.
If not specified a spring layout positioning will be computed.
See networkx.layout for functions that compute node positions.
with_labels : bool, optional (default=True)
Set to True to draw labels on the nodes.
ax : Matplotlib Axes object, optional
Draw the graph in the specified Matplotlib axes.
nodelist : list, optional (default G.nodes())
Draw only specified nodes
edgelist : list, optional (default=G.edges())
Draw only specified edges
node_size : scalar or array, optional (default=300)
Size of nodes. If an array is specified it must be the
same length as nodelist.
node_color : color string, or array of floats, (default='r')
Node color. Can be a single color format string,
or a sequence of colors with the same length as nodelist.
If numeric values are specified they will be mapped to
colors using the cmap and vmin,vmax parameters. See
matplotlib.scatter for more details.
node_shape : string, optional (default='o')
The shape of the node. Specification is as matplotlib.scatter
marker, one of 'so^>v<dph8'.
alpha : float, optional (default=1.0)
The node transparency
cmap : Matplotlib colormap, optional (default=None)
Colormap for mapping intensities of nodes
vmin,vmax : float, optional (default=None)
Minimum and maximum for node colormap scaling
linewidths : [None | scalar | sequence]
Line width of symbol border (default =1.0)
width : float, optional (default=1.0)
Line width of edges
edge_color : color string, or array of floats (default='r')
Edge color. Can be a single color format string,
or a sequence of colors with the same length as edgelist.
If numeric values are specified they will be mapped to
colors using the edge_cmap and edge_vmin,edge_vmax parameters.
edge_ cmap : Matplotlib colormap, optional (default=None)
Colormap for mapping intensities of edges
edge_vmin,edge_vmax : floats, optional (default=None)
Minimum and maximum for edge colormap scaling
style : string, optional (default='solid')
Edge line style (solid|dashed|dotted,dashdot)
labels : dictionary, optional (default=None)
Node labels in a dictionary keyed by node of text labels
font_size : int, optional (default=12)
Font size for text labels
font_color : string, optional (default='k' black)
Font color string
font_weight : string, optional (default='normal')
Font weight
font_family : string, optional (default='sans-serif')
Font family
label : string, optional
Label for graph legend
Examples
--------
>>> G=nx.dodecahedral_graph()
>>> nx.draw(G)
>>> nx.draw(G,pos=nx.spring_layout(G)) # use spring layout
>>> import pylab
>>> limits=pylab.axis('off') # turn of axis
Also see the NetworkX drawing examples at
http://networkx.lanl.gov/gallery.html
See Also
--------
draw()
draw_networkx_nodes()
draw_networkx_edges()
draw_networkx_labels()
draw_networkx_edge_labels()
"""
try:
import matplotlib.pylab as pylab
except ImportError:
raise ImportError("Matplotlib required for draw()")
except RuntimeError:
print("Matplotlib unable to open display")
raise
if pos is None:
pos=nx.drawing.spring_layout(G) # default to spring layout
node_collection=draw_networkx_nodes(G, pos, **kwds)
edge_collection=draw_networkx_edges(G, pos, **kwds)
if with_labels:
draw_networkx_labels(G, pos, **kwds)
pylab.draw_if_interactive()
def plot(self,*args,**kwargs):
# This just makes sure that my lines get drawn,
# otherwise it just calls the axes' plot instance.
super(myaxes,self).plot(*args,**kwargs)
pylab.draw_if_interactive()
def draw(G, pos=None, ax=None, hold=None, **kwds):
"""Draw the graph G with Matplotlib (pylab).
Draw the graph as a simple representation with no node
labels or edge labels and using the full Matplotlib figure area
and no axis labels by default. See draw_networkx() for more
full-featured drawing that allows title, axis labels etc.
Parameters
----------
G : graph
A networkx graph
pos : dictionary, optional
A dictionary with nodes as keys and positions as values.
If not specified a spring layout positioning will be computed.
See networkx.layout for functions that compute node positions.
ax : Matplotlib Axes object, optional
Draw the graph in specified Matplotlib axes.
hold : bool, optional
Set the Matplotlib hold state. If True subsequent draw
commands will be added to the current axes.
**kwds : optional keywords
See networkx.draw_networkx() for a description of optional keywords.
Examples
--------
>>> G=nx.dodecahedral_graph()
>>> nx.draw(G)
>>> nx.draw(G,pos=nx.spring_layout(G)) # use spring layout
See Also
--------
draw_networkx()
draw_networkx_nodes()
draw_networkx_edges()
draw_networkx_labels()
draw_networkx_edge_labels()
Notes
-----
This function has the same name as pylab.draw and pyplot.draw
so beware when using
>>> from networkx import *
since you might overwrite the pylab.draw function.
Good alternatives are:
With pylab:
>>> import pylab as P #
>>> import networkx as nx
>>> G=nx.dodecahedral_graph()
>>> nx.draw(G) # networkx draw()
>>> P.draw() # pylab draw()
With pyplot
>>> import matplotlib.pyplot as plt
>>> import networkx as nx
>>> G=nx.dodecahedral_graph()
>>> nx.draw(G) # networkx draw()
>>> plt.draw() # pyplot draw()
Also see the NetworkX drawing examples at
http://networkx.lanl.gov/gallery.html
"""
try:
import matplotlib.pylab as pylab
except ImportError:
raise ImportError("Matplotlib required for draw()")
except RuntimeError:
print("Matplotlib unable to open display")
raise
cf=pylab.gcf()
cf.set_facecolor('w')
if ax is None:
if cf._axstack() is None:
ax=cf.add_axes((0,0,1,1))
else:
ax=cf.gca()
# allow callers to override the hold state by passing hold=True|False
b = pylab.ishold()
h = kwds.pop('hold', None)
if h is not None:
pylab.hold(h)
try:
draw_networkx(G,pos=pos,ax=ax,**kwds)
ax.set_axis_off()
pylab.draw_if_interactive()
except:
pylab.hold(b)
raise
pylab.hold(b)
return
def axes(*args, **kwargs):
"""
Add an axes at position rect specified by:
- ``axes()`` by itself creates a default full ``subplot(111)`` window axis.
- ``axes(rect, axisbg='w')`` where *rect* = [left, bottom, width,
height] in normalized (0, 1) units. *axisbg* is the background
color for the axis, default white.
- ``axes(h)`` where *h* is an axes instance makes *h* the current
axis. An :class:`~matplotlib.axes.Axes` instance is returned.
======= ============ ================================================
kwarg Accepts Desctiption
======= ============ ================================================
axisbg color the axes background color
frameon [True|False] display the frame?
sharex otherax current axes shares xaxis attribute with otherax
sharey otherax current axes shares yaxis attribute with otherax
polar [True|False] use a polar axes?
======= ============ ================================================
Examples:
* :file:`examples/pylab_examples/axes_demo.py` places custom axes.
* :file:`examples/pylab_examples/shared_axis_demo.py` uses
*sharex* and *sharey*.
This was copied from the pyplot axes function. Several methods
have been added to the axes.
"""
nargs = len(args)
if nargs == 0:
args = [[.1, .1, .8, .8]]
if nargs > 1:
raise TypeError('Only one non keyword arg to axes allowed')
arg = args[0]
axd = {}
newd = {}
newd['lw'] = rcParams['axes.linewidth']
try:
axd['axisbg'] = kwargs.pop('axisbg')
except:
pass
for nm in [
'axisbg',
'frameon',
'sharex',
'sharey',
'polar',
]:
if nm in kwargs.keys():
axd[nm] = kwargs.pop(nm)
if 'ticksize' in kwargs.keys():
newd['xticksize'] = kwargs.get('ticksize')
newd['yticksize'] = kwargs.pop('ticksize')
for nm in [('lw', 'linewidth'), 'linewidth', 'xticksize', 'yticksize',
('fs', 'fontsize'), 'fontsize', 'xlocation', 'ylocation']:
if nm.__class__ is tuple:
ky = nm[0]
nm = nm[1]
else:
ky = nm
nm = nm
if ky in kwargs:
newd[nm] = kwargs.pop(ky)
if ('fig' not in kwargs.keys()) and ('figure' not in kwargs.keys()):
fig = pylab.gcf()
elif 'figure' in kwargs.keys():
fig = kwargs.pop('figure')
else:
fig = kwargs.pop('fig')
if isinstance(arg, mpl.axes.Axes):
a = fig.sca(arg)
else:
rect = arg
a = fig.add_axes(rect, **axd)
a.set(**kwargs)
if 'xlocation' in newd.keys():
a.xaxis.set_ticks_position(newd['xlocation'])
if newd['xlocation'] == 'top':
a.spines['bottom'].set_visible(False)
elif newd['xlocation'] == 'bottom':
a.spines['top'].set_visible(False)
if 'ylocation' in newd.keys():
a.yaxis.set_ticks_position(newd['ylocation'])
if newd['ylocation'] == 'right':
a.spines['left'].set_visible(False)
elif newd['ylocation'] == 'left':
a.spines['right'].set_visible(False)
if 'lw' in newd.keys():
for sp in a.spines:
a.spines[sp].set_linewidth(newd['lw'])
for tck in a.xaxis.get_ticklines():
tck.set_mew(newd['lw'])
for tck in a.yaxis.get_ticklines():
tck.set_mew(newd['lw'])
if 'xticksize' in newd.keys():
for tck in a.xaxis.get_ticklines():
tck.set_ms(newd['xticksize'])
if 'yticksize' in newd.keys():
for tck in a.yaxis.get_ticklines():
tck.set_ms(newd['yticksize'])
if 'fontsize' in newd.keys():
for tklbl in a.xaxis.get_ticklabels():
tklbl.set_fontsize(newd['fontsize'])
for tklbl in a.yaxis.get_ticklabels():
tklbl.set_fontsize(newd['fontsize'])
a.transAxesXDataY = transforms.blended_transform_factory(
a.transAxes, a.transData)
a.transDataXAxesY = transforms.blended_transform_factory(
a.transData, a.transAxes)
a.shadex = new.instancemethod(bf.shadex, a, Axes)
a.shadey = new.instancemethod(bf.shadey, a, Axes)
a.setaxesframe = new.instancemethod(bf._setaxesframe, a, Axes)
a.annoteCorner = new.instancemethod(bf.annoteCorner, a, Axes)
a.offset_text = new.instancemethod(bf.offset_text, a, Axes)
a.cpcolor = new.instancemethod(bf.cpcolor, a, Axes)
a.labelax = new.instancemethod(bf.labelax, a, Axes)
a.skip_ticklabels = new.instancemethod(skip_ticklabels, a, Axes)
a.errorshadex = new.instancemethod(bf.errorshadex, a, Axes)
# a.plot_specobj=new.instancemethod(plot_specobj,a,Axes)
pylab.draw_if_interactive()
return a
def add_yaxis(fsp=None, position="right", yscale=None, basey=10, subsy=None):
"""
Adds a second y-axis to a :class:`Subplot`.
This function can also be used as a method.
Parameters
----------
fsp : {None, Subplot}
Subplot to which the secondary y-axis is added.
If None, the current subplot is selected: in that case, it should be
a valid :class:`Subplot`.
When used as a :class:`Subplot` method, this parameter points
automatically to the calling subplot.
position : {string}
Position of the new axis, as either ``'left'`` or ``'right'``.
yscale : {string}
Scale of the new axis, as either ``'log'``, ``'linear'`` or ``None``.
If None, uses the same scale as the first y axis.
basey : {integer}
Base of the logarithm for the new axis (if needed).
subsy : {sequence}
Sequence of the location of the minor ticks;
None defaults to autosubs, which depend on the number of decades in
the plot.
Eg for base 10, ``subsy=(1,2,5)`` will put minor ticks on 1, 2, 5, 11,
12,15, 21, ....
To turn off minor ticking, set ``subsy=[]``.
Raises
------
TypeError
If the selected subplot is not a valid :class:`Subplot` object.
"""
if fsp is None:
fsp = pylab.gca()
fig = fsp.figure
axisini = fsp.axis()
fsp_alt_args = (fsp._rows, fsp._cols, fsp._num + 1)
fsp_alt = fig.add_subplot(frameon=False, position=fsp.get_position(), sharex=fsp, *fsp_alt_args)
# Set position ....................
if position.lower() == "right":
(inipos, newpos) = ("left", "right")
else:
(inipos, newpos) = ("right", "left")
# Force scales tics to one side ...
fsp.yaxis.set_ticks_position(inipos)
fsp.yaxis.set_label_position(inipos)
# Force 2nd ticks to the other side..
fsp_alt.yaxis.set_ticks_position(newpos)
fsp_alt.yaxis.set_label_position(newpos)
# Force period axis scale..........
if yscale is None:
yscale = fsp.get_yscale()
try:
basey = fsp.yaxis.get_major_locator()._base
except AttributeError:
basey = 10.0
fsp_alt.set_yscale(yscale, basey=basey, subsy=subsy)
pylab.draw_if_interactive()
return fsp_alt
def draw(G, pos=None, ax=None, hold=None, **kwds):
"""Draw the graph G with matplotlib (pylab).
This is a pylab friendly function that will use the
current pylab figure axes (e.g. subplot).
pos is a dictionary keyed by vertex with a two-tuple
of x-y positions as the value.
See networkx.layout for functions that compute node positions.
Usage:
>>> from networkx import *
>>> G=dodecahedral_graph()
>>> draw(G)
>>> pos=graphviz_layout(G)
>>> draw(G,pos)
>>> draw(G,pos=spring_layout(G))
Also see doc/examples/draw_*
:Parameters:
- `nodelist`: list of nodes to be drawn (default=G.nodes())
- `edgelist`: list of edges to be drawn (default=G.edges())
- `node_size`: scalar or array of the same length as nodelist (default=300)
- `node_color`: single color string or numeric/numarray array of floats (default='r')
- `node_shape`: node shape (default='o'), or 'so^>v<dph8' see pylab.scatter
- `alpha`: transparency (default=1.0)
- `cmap`: colormap for mapping intensities (default=None)
- `vmin,vmax`: min and max for colormap scaling (default=None)
- `width`: line width of edges (default =1.0)
- `edge_color`: scalar or array (default='k')
- `edge_cmap`: colormap for edge intensities (default=None)
- `edge_vmin,edge_vmax`: min and max for colormap edge scaling (default=None)
- `style`: edge linestyle (default='solid') (solid|dashed|dotted,dashdot)
- `labels`: dictionary keyed by node of text labels (default=None)
- `font_size`: size for text labels (default=12)
- `font_color`: (default='k')
- `font_weight`: (default='normal')
- `font_family`: (default='sans-serif')
- `ax`: matplotlib axes instance
for more see pylab.scatter
NB: this has the same name as pylab.draw so beware when using
>>> from networkx import *
since you will overwrite the pylab.draw function.
A good alternative is to use
>>> import pylab as P
>>> import networkx as NX
>>> G=NX.dodecahedral_graph()
and then use
>>> NX.draw(G) # networkx draw()
and
>>> P.draw() # pylab draw()
"""
try:
import matplotlib.pylab as pylab
except ImportError:
raise ImportError, "Matplotlib required for draw()"
except RuntimeError:
pass # unable to open display
if pos is None:
pos=networkx.drawing.spring_layout(G) # default to spring layout
cf=pylab.gcf()
cf.set_facecolor('w')
if ax is None:
if cf._axstack() is None:
ax=cf.add_axes((0,0,1,1))
else:
ax=cf.gca()
# allow callers to override the hold state by passing hold=True|False
b = pylab.ishold()
h = kwds.pop('hold', None)
if h is not None:
pylab.hold(h)
try:
draw_networkx(G,pos,ax=ax,**kwds)
ax.set_axis_off()
pylab.draw_if_interactive()
except:
pylab.hold(b)
raise
pylab.hold(b)
return
def axes(*args, **kwargs):
"""
Add an axes at position rect specified by:
- ``axes()`` by itself creates a default full ``subplot(111)`` window axis.
- ``axes(rect, axisbg='w')`` where *rect* = [left, bottom, width,
height] in normalized (0, 1) units. *axisbg* is the background
color for the axis, default white.
- ``axes(h)`` where *h* is an axes instance makes *h* the current
axis. An :class:`~matplotlib.axes.Axes` instance is returned.
======= ============ ================================================
kwarg Accepts Desctiption
======= ============ ================================================
axisbg color the axes background color
frameon [True|False] display the frame?
sharex otherax current axes shares xaxis attribute with otherax
sharey otherax current axes shares yaxis attribute with otherax
polar [True|False] use a polar axes?
======= ============ ================================================
Examples:
* :file:`examples/pylab_examples/axes_demo.py` places custom axes.
* :file:`examples/pylab_examples/shared_axis_demo.py` uses
*sharex* and *sharey*.
This was copied from the pyplot axes function
"""
nargs = len(args)
if nargs==0:
args=[[.1,.1,.8,.8]]
if nargs>1:
raise TypeError('Only one non keyword arg to axes allowed')
arg = args[0]
axd={}
newd={}
newd['lw']=rcParams['axes.linewidth']
if kwargs.has_key('axisbg'):
axd['axisbg']=kwargs.pop('axisbg')
if kwargs.has_key('frameon'):
axd['frameon']=kwargs.pop('frameon')
if kwargs.has_key('sharex'):
axd['sharex']=kwargs.pop('sharex')
if kwargs.has_key('sharey'):
axd['sharey']=kwargs.pop('sharey')
if kwargs.has_key('polar'):
axd['polar']=kwargs.pop('polar')
if kwargs.has_key('linewidth'):
newd['lw']=kwargs.pop('linewidth')
if kwargs.has_key('lw'):
newd['lw']=kwargs.pop('lw')
if kwargs.has_key('ticksize'):
newd['xticksize']=kwargs.get('ticksize')
newd['yticksize']=kwargs.pop('ticksize')
if kwargs.has_key('xticksize'):
newd['xticksize']=kwargs.pop('xticksize')
if kwargs.has_key('yticksize'):
newd['yticksize']=kwargs.pop('yticksize')
if kwargs.has_key('fs'):
newd['fontsize']=kwargs.pop('fs')
if kwargs.has_key('fontsize'):
newd['fontsize']=kwargs.pop('fontsize')
if kwargs.has_key('xlocation'):
newd['xlocation']=kwargs.pop('xlocation')
if kwargs.has_key('ylocation'):
newd['ylocation']=kwargs.pop('ylocation')
if (not kwargs.has_key('fig')) and (not kwargs.has_key('figure')):
fig=pylab.gcf()
elif kwargs.has_key('figure'):
fig=kwargs.pop('figure')
else:
fig=kwargs.pop('fig')
if isinstance(arg, mpl.axes.Axes):
a = fig.sca(arg)
else:
rect = arg
a = fig.add_axes(rect, **axd)
a.set(**kwargs)
if newd.has_key('xlocation'):
a.xaxis.set_ticks_position(newd['xlocation'])
if newd['xlocation']=='top':
a.spines['bottom'].set_visible(False)
elif newd['xlocation']=='bottom':
a.spines['top'].set_visible(False)
if newd.has_key('ylocation'):
a.yaxis.set_ticks_position(newd['ylocation'])
if newd['ylocation']=='right':
a.spines['left'].set_visible(False)
elif newd['ylocation']=='left':
a.spines['right'].set_visible(False)
if newd.has_key('lw'):
for sp in a.spines:
a.spines[sp].set_linewidth(newd['lw'])
for tck in a.xaxis.get_ticklines():
tck.set_mew(newd['lw'])
for tck in a.yaxis.get_ticklines():
tck.set_mew(newd['lw'])
if newd.has_key('xticksize'):
for tck in a.xaxis.get_ticklines():
tck.set_ms(newd['xticksize'])
if newd.has_key('yticksize'):
for tck in a.yaxis.get_ticklines():
tck.set_ms(newd['yticksize'])
if newd.has_key('fontsize'):
for tklbl in a.xaxis.get_ticklabels():
tklbl.set_fontsize(newd['fontsize'])
for tklbl in a.yaxis.get_ticklabels():
tklbl.set_fontsize(newd['fontsize'])
a.transAxesXDataY=transforms.blended_transform_factory(a.transAxes,a.transData)
a.transDataXAxesY=transforms.blended_transform_factory(a.transData,a.transAxes)
a.hln=new.instancemethod(_hln,a,Axes)
a.vln=new.instancemethod(_vln,a,Axes)
a.shadex=new.instancemethod(shadex,a,Axes)
a.shadey=new.instancemethod(shadey,a,Axes)
a.setaxesframe=new.instancemethod(_setaxesframe,a,Axes)
a.annoteCorner=new.instancemethod(annoteCorner,a,Axes)
a.offset_text=new.instancemethod(offset_text,a,Axes)
a.cpcolor=new.instancemethod(cpcolor,a,Axes)
a.cbar=new.instancemethod(cbar,a,Axes)
a.labelax=new.instancemethod(labelax,a,Axes)
a.skip_ticklabels=new.instancemethod(skip_ticklabels,a,Axes)
a.errorshadex=new.instancemethod(errorshadex,a,Axes)
#a.plot_specobj=new.instancemethod(plot_specobj,a,Axes)
pylab.draw_if_interactive()
return a
def add_yaxis(fsp=None, position='right', yscale=None, basey=10, subsy=None):
"""
Adds a second y-axis to a :class:`TimeSeriesPlot`.
This function can also be used as a method.
Parameters
----------
fsp : {None, TimeSeriesPlot}
Subplot to which the secondary y-axis is added.
If None, the current subplot is selected: in that case, it should be
a valid :class:`TimeSeriesPlot`.
When used as a :class:`TimeSeriesPlot` method, this parameter points
automatically to the calling subplot.
position : {string}
Position of the new axis, as either ``'left'`` or ``'right'``.
yscale : {string}
Scale of the new axis, as either ``'log'``, ``'linear'`` or ``None``.
If None, uses the same scale as the first y axis.
basey : {integer}
Base of the logarithm for the new axis (if needed).
subsy : {sequence}
Sequence of the location of the minor ticks;
None defaults to autosubs, which depend on the number of decades in
the plot.
Eg for base 10, ``subsy=(1,2,5)`` will put minor ticks on 1, 2, 5, 11,
12,15, 21, ....
To turn off minor ticking, set ``subsy=[]``.
Raises
------
TypeError
If the selected subplot is not a valid :class:`TimeSeriesPlot` object.
"""
if fsp is None:
fsp = pylab.gca()
if not isinstance(fsp, TimeSeriesPlot):
raise TypeError("The current plot is not a TimeSeriesPlot")
fig = fsp.figure
axisini = fsp.axis()
fsp_alt_args = (fsp._rows, fsp._cols, fsp._num + 1)
fsp_alt = fig.add_tsplot(frameon=False,
position=fsp.get_position(),
sharex=fsp,
*fsp_alt_args)
# Set position ....................
if position.lower() == 'right':
(inipos, newpos) = ('left', 'right')
else:
(inipos, newpos) = ('right', 'left')
# Force scales tics to one side ...
fsp.yaxis.set_ticks_position(inipos)
fsp.yaxis.set_label_position(inipos)
# Force 2nd ticks to the other side..
fsp_alt.yaxis.set_ticks_position(newpos)
fsp_alt.yaxis.set_label_position(newpos)
# Force period axis scale..........
if yscale is None:
yscale = fsp.get_yscale()
try:
basey = fsp.yaxis.get_major_locator()._base
except AttributeError:
basey = 10.
fsp_alt.set_yscale(yscale, basey=basey, subsy=subsy)
pylab.draw_if_interactive()
return fsp_alt
def draw_networkx(G, pos=None, with_labels=True, **kwds):
"""Draw the graph G using Matplotlib.
Draw the graph with Matplotlib with options for node positions,
labeling, titles, and many other drawing features.
See draw() for simple drawing without labels or axes.
Parameters
----------
G : graph
A networkx graph
pos : dictionary, optional
A dictionary with nodes as keys and positions as values.
If not specified a spring layout positioning will be computed.
See networkx.layout for functions that compute node positions.
with_labels : bool, optional (default=True)
Set to True to draw labels on the nodes.
ax : Matplotlib Axes object, optional
Draw the graph in the specified Matplotlib axes.
nodelist : list, optional (default G.nodes())
Draw only specified nodes
edgelist : list, optional (default=G.edges())
Draw only specified edges
node_size : scalar or array, optional (default=300)
Size of nodes. If an array is specified it must be the
same length as nodelist.
node_color : color string, or array of floats, (default='r')
Node color. Can be a single color format string,
or a sequence of colors with the same length as nodelist.
If numeric values are specified they will be mapped to
colors using the cmap and vmin,vmax parameters. See
matplotlib.scatter for more details.
node_shape : string, optional (default='o')
The shape of the node. Specification is as matplotlib.scatter
marker, one of 'so^>v<dph8'.
alpha : float, optional (default=1.0)
The node transparency
cmap : Matplotlib colormap, optional (default=None)
Colormap for mapping intensities of nodes
vmin,vmax : float, optional (default=None)
Minimum and maximum for node colormap scaling
linewidths : [None | scalar | sequence]
Line width of symbol border (default =1.0)
width : float, optional (default=1.0)
Line width of edges
edge_color : color string, or array of floats (default='r')
Edge color. Can be a single color format string,
or a sequence of colors with the same length as edgelist.
If numeric values are specified they will be mapped to
colors using the edge_cmap and edge_vmin,edge_vmax parameters.
edge_ cmap : Matplotlib colormap, optional (default=None)
Colormap for mapping intensities of edges
edge_vmin,edge_vmax : floats, optional (default=None)
Minimum and maximum for edge colormap scaling
style : string, optional (deafult='solid')
Edge line style (solid|dashed|dotted,dashdot)
labels : dictionary, optional (deafult=None)
Node labels in a dictionary keyed by node of text labels
font_size : int, optional (default=12)
Font size for text labels
font_color : string, optional (default='k' black)
Font color string
font_weight : string, optional (default='normal')
Font weight
font_family : string, optional (default='sans-serif')
Font family
label : string, optional
Label for graph legend
Examples
--------
>>> G=nx.dodecahedral_graph()
>>> nx.draw(G)
>>> nx.draw(G,pos=nx.spring_layout(G)) # use spring layout
>>> import pylab
>>> limits=pylab.axis('off') # turn of axis
Also see the NetworkX drawing examples at
http://networkx.lanl.gov/gallery.html
See Also
--------
draw()
draw_networkx_nodes()
draw_networkx_edges()
draw_networkx_labels()
draw_networkx_edge_labels()
"""
try:
import matplotlib.pylab as pylab
except ImportError:
raise ImportError("Matplotlib required for draw()")
except RuntimeError:
print("Matplotlib unable to open display")
raise
if pos is None:
pos=nx.drawing.spring_layout(G) # default to spring layout
node_collection=draw_networkx_nodes(G, pos, **kwds)
edge_collection=draw_networkx_edges(G, pos, **kwds)
if with_labels:
draw_networkx_labels(G, pos, **kwds)
pylab.draw_if_interactive()
def draw_networkx(G, pos=None, with_labels=True, **kwds):
"""Draw the graph G using Matplotlib.
Draw the graph with Matplotlib with options for node positions,
labeling, titles, and many other drawing features.
See draw() for simple drawing without labels or axes.
Parameters
----------
G : graph
A networkx graph
pos : dictionary, optional
A dictionary with nodes as keys and positions as values.
If not specified a spring layout positioning will be computed.
See networkx.layout for functions that compute node positions.
ax : Matplotlib Axes object, optional
Draw the graph in the specified Matplotlib axes.
with_labels: bool, optional
Set to True (default) to draw labels on the nodes.
nodelist: list, optional
Draw only specified nodes (default G.nodes())
edgelist: list
Draw only specified edges(default=G.edges())
node_size: scalar or array
Size of nodes (default=300). If an array is specified it must be the
same length as nodelist.
node_color: color string, or array of floats
Node color. Can be a single color format string (default='r'),
or a sequence of colors with the same length as nodelist.
If numeric values are specified they will be mapped to
colors using the cmap and vmin,vmax parameters. Can also be a
dictionary keyed by node, and can be in any matplotlib acceptable
color value.
node_shape: string
The shape of the node. Specification is as matplotlib.scatter
marker, one of 'so^>v<dph8' (default='o').
alpha: float
The node transparency (default=1.0)
cmap: Matplotlib colormap
Colormap for mapping intensities of nodes (default=None)
vmin,vmax: floats
Minimum and maximum for node colormap scaling (default=None)
width: float
Line width of edges (default =1.0)
edge_color: color string, or array of floats
Edge color. Can be a single color format string (default='r'),
or a sequence of colors with the same length as edgelist.
If numeric values are specified they will be mapped to
colors using the edge_cmap and edge_vmin,edge_vmax parameters.
edge_ cmap: Matplotlib colormap
Colormap for mapping intensities of edges (default=None)
edge_vmin,edge_vmax: floats
Minimum and maximum for edge colormap scaling (default=None)
style: string
Edge line style (default='solid') (solid|dashed|dotted,dashdot)
labels: dictionary
Node labels in a dictionary keyed by node of text labels (default=None)
font_size: int
Font size for text labels (default=12)
font_color: string
Font color string (default='k' black)
font_weight: string
Font weight (default='normal')
font_family: string
Font family (default='sans-serif')
Notes
-----
Any keywords not listed above are passed through to draw_networkx_nodes(),
draw_networkx_edges(), and draw_networkx_labels(). For finer control
of drawing you can call those functions directly.
Examples
--------
>>> G=nx.dodecahedral_graph()
>>> nx.draw(G)
>>> nx.draw(G,pos=nx.spring_layout(G)) # use spring layout
>>> import pylab
>>> limits=pylab.axis('off') # turn of axis
Also see the NetworkX drawing examples at
http://networkx.lanl.gov/gallery.html
See Also
--------
draw()
draw_networkx_nodes()
draw_networkx_edges()
draw_networkx_labels()
draw_networkx_edge_labels()
"""
try:
import matplotlib.pylab as pylab
except ImportError:
raise ImportError, "Matplotlib required for draw()"
except RuntimeError:
print "Matplotlib unable to open display"
raise
if pos is None:
pos = nx.drawing.spring_layout(G) # default to spring layout
node_patches = draw_networkx_nodes(G, pos, **kwds)
edge_patches = draw_networkx_edges(G, pos, node_patches, **kwds)
if with_labels:
draw_networkx_labels(G, pos, **kwds)
pylab.draw_if_interactive()
def plot(self, *args, **kwargs):
# This just makes sure that my lines get drawn,
# otherwise it just calls the axes' plot instance.
super(myaxes, self).plot(*args, **kwargs)
pylab.draw_if_interactive()
