Revision: 6315
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=6315&view=rev
Author: efiring
Date: 2008-10-24 00:08:58 +0000 (Fri, 24 Oct 2008)
Log Message:
-----------
Support autoscaling with shared axes
Modified Paths:
--------------
trunk/matplotlib/CHANGELOG
trunk/matplotlib/lib/matplotlib/axes.py
trunk/matplotlib/lib/matplotlib/ticker.py
Modified: trunk/matplotlib/CHANGELOG
===================================================================
--- trunk/matplotlib/CHANGELOG 2008-10-23 19:56:04 UTC (rev 6314)
+++ trunk/matplotlib/CHANGELOG 2008-10-24 00:08:58 UTC (rev 6315)
@@ -1,3 +1,5 @@
+2008-10-23 Autoscaling is now supported with shared axes - EF
+
2008-10-23 Fixed exception in dviread that happened with Minion - JKS
2008-10-21 set_xlim, ylim now return a copy of the viewlim array to
Modified: trunk/matplotlib/lib/matplotlib/axes.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/axes.py 2008-10-23 19:56:04 UTC (rev
6314)
+++ trunk/matplotlib/lib/matplotlib/axes.py 2008-10-24 00:08:58 UTC (rev
6315)
@@ -1451,20 +1451,30 @@
"""
# if image data only just use the datalim
if not self._autoscaleon: return
+ if scalex:
+ xshared = self._shared_x_axes.get_siblings(self)
+ dl = [ax.dataLim for ax in xshared]
+ bb = mtransforms.BboxBase.union(dl)
+ x0, x1 = bb.intervalx
+ if scaley:
+ yshared = self._shared_y_axes.get_siblings(self)
+ dl = [ax.dataLim for ax in yshared]
+ bb = mtransforms.BboxBase.union(dl)
+ y0, y1 = bb.intervaly
if (tight or (len(self.images)>0 and
len(self.lines)==0 and
len(self.patches)==0)):
-
- if scalex: self.set_xbound(self.dataLim.intervalx)
-
- if scaley: self.set_ybound(self.dataLim.intervaly)
+ if scalex:
+ self.set_xbound(x0, x1)
+ if scaley:
+ self.set_ybound(y0, 11)
return
if scalex:
- XL = self.xaxis.get_major_locator().autoscale()
+ XL = self.xaxis.get_major_locator().view_limits(x0, x1)
self.set_xbound(XL)
if scaley:
- YL = self.yaxis.get_major_locator().autoscale()
+ YL = self.yaxis.get_major_locator().view_limits(y0, y1)
self.set_ybound(YL)
#### Drawing
Modified: trunk/matplotlib/lib/matplotlib/ticker.py
===================================================================
--- trunk/matplotlib/lib/matplotlib/ticker.py 2008-10-23 19:56:04 UTC (rev
6314)
+++ trunk/matplotlib/lib/matplotlib/ticker.py 2008-10-24 00:08:58 UTC (rev
6315)
@@ -641,9 +641,17 @@
'Return the locations of the ticks'
raise NotImplementedError('Derived must override')
+ def view_limits(self, vmin, vmax):
+ """
+ select a scale for the range from vmin to vmax
+
+ Normally This will be overridden.
+ """
+ return mtransforms.nonsingular(vmin, vmax)
+
def autoscale(self):
'autoscale the view limits'
- return mtransforms.nonsingular(*self.axis.get_view_interval())
+ return self.view_limits(*self.axis.get_view_interval())
def pan(self, numsteps):
'Pan numticks (can be positive or negative)'
@@ -773,11 +781,9 @@
def _set_numticks(self):
self.numticks = 11 # todo; be smart here; this is just for dev
- def autoscale(self):
+ def view_limits(self, vmin, vmax):
'Try to choose the view limits intelligently'
- vmin, vmax = self.axis.get_data_interval()
-
if vmax<vmin:
vmin, vmax = vmax, vmin
@@ -859,13 +865,11 @@
locs = vmin + np.arange(n+1) * base
return locs
- def autoscale(self):
+ def view_limits(self, dmin, dmax):
"""
Set the view limits to the nearest multiples of base that
contain the data
"""
- dmin, dmax = self.axis.get_data_interval()
-
vmin = self._base.le(dmin)
vmax = self._base.ge(dmax)
if vmin==vmax:
@@ -946,8 +950,7 @@
vmin, vmax = mtransforms.nonsingular(vmin, vmax, expander = 0.05)
return self.bin_boundaries(vmin, vmax)
- def autoscale(self):
- dmin, dmax = self.axis.get_data_interval()
+ def view_limits(self, dmin, dmax):
if self._symmetric:
maxabs = max(abs(dmin), abs(dmax))
dmin = -maxabs
@@ -1043,9 +1046,9 @@
return np.array(ticklocs)
- def autoscale(self):
+ def view_limits(self, vmin, vmax):
'Try to choose the view limits intelligently'
- vmin, vmax = self.axis.get_data_interval()
+
if vmax<vmin:
vmin, vmax = vmax, vmin
@@ -1114,10 +1117,9 @@
ticklocs = np.sign(decades) * b ** np.abs(decades)
return np.array(ticklocs)
- def autoscale(self):
+ def view_limits(self, vmin, vmax):
'Try to choose the view limits intelligently'
b = self._transform.base
- vmin, vmax = self.axis.get_data_interval()
if vmax<vmin:
vmin, vmax = vmax, vmin
@@ -1167,13 +1169,12 @@
d = abs(vmax-vmin)
self._locator = self.get_locator(d)
- def autoscale(self):
+ def view_limits(self, vmin, vmax):
'Try to choose the view limits intelligently'
- vmin, vmax = self.axis.get_data_interval()
d = abs(vmax-vmin)
self._locator = self.get_locator(d)
- return self._locator.autoscale()
+ return self._locator.view_limits(vmin, vmax)
def get_locator(self, d):
'pick the best locator based on a distance'
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