Revision: 3895
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=3895&view=rev
Author: mdboom
Date: 2007-09-26 06:53:53 -0700 (Wed, 26 Sep 2007)
Log Message:
-----------
Fix log limits. For minor speed improvements.
Modified Paths:
--------------
branches/transforms/lib/matplotlib/axes.py
branches/transforms/lib/matplotlib/axis.py
branches/transforms/lib/matplotlib/lines.py
branches/transforms/lib/matplotlib/scale.py
branches/transforms/lib/matplotlib/ticker.py
branches/transforms/lib/matplotlib/transforms.py
Modified: branches/transforms/lib/matplotlib/axes.py
===================================================================
--- branches/transforms/lib/matplotlib/axes.py 2007-09-26 13:41:15 UTC (rev
3894)
+++ branches/transforms/lib/matplotlib/axes.py 2007-09-26 13:53:53 UTC (rev
3895)
@@ -1095,18 +1095,9 @@
line._remove_method = lambda h: self.lines.remove(h)
def _update_line_limits(self, line):
- xdata = line.get_xdata(orig=False)
- ydata = line.get_ydata(orig=False)
+ xydata = line.get_xydata()
+ self.update_datalim( xydata )
- if line.get_transform() != self.transData:
- xys = self._get_verts_in_data_coords(
- line.get_transform(), zip(xdata, ydata))
- xdata = npy.array([x for x,y in xys])
- ydata = npy.array([y for x,y in xys])
-
- self.update_datalim_numerix( xdata, ydata )
-
-
def add_patch(self, p):
"""
Add a patch to the list of Axes patches; the clipbox will be
@@ -1151,7 +1142,6 @@
xys = npy.asarray(xys)
self.update_datalim_numerix(xys[:, 0], xys[:, 1])
-
def update_datalim_numerix(self, x, y):
'Update the data lim bbox with seq of xy tups'
# if no data is set currently, the bbox will ignore it's
Modified: branches/transforms/lib/matplotlib/axis.py
===================================================================
--- branches/transforms/lib/matplotlib/axis.py 2007-09-26 13:41:15 UTC (rev
3894)
+++ branches/transforms/lib/matplotlib/axis.py 2007-09-26 13:53:53 UTC (rev
3895)
@@ -334,6 +334,9 @@
'return the Interval instance for this axis view limits'
return self.axes.viewLim.intervalx
+ def get_minpos(self):
+ return self.axes.dataLim.minposx
+
def get_data_interval(self):
'return the Interval instance for this axis data limits'
return self.axes.dataLim.intervalx
@@ -458,6 +461,9 @@
'return the Interval instance for this axis view limits'
return self.axes.viewLim.intervaly
+ def get_minpos(self):
+ return self.axes.dataLim.minposy
+
def get_data_interval(self):
'return the Interval instance for this axis data limits'
return self.axes.dataLim.intervaly
@@ -518,7 +524,13 @@
def get_scale(self):
return self._scale.name
- def set_scale(self, value, base=10, subs=None):
+ def set_scale(self, value, basex=10, subsx=None, basey=10, subsy=None):
+ if self.axis_name == 'x':
+ base = basex
+ subs = subsx
+ else:
+ base = basey
+ subs = subsy
# MGDTODO: Move these settings (ticker etc.) into the scale class
itself
value = value.lower()
assert value.lower() in ('log', 'linear')
@@ -534,7 +546,7 @@
self.set_minor_locator(LogLocator(base,subs))
# MGDTODO: Pass base along
self._scale = LogScale()
- miny, maxy = getattr(self.axes.viewLim, 'interval' + self.axis)
+ miny, maxy = getattr(self.axes.viewLim, 'interval' +
self.axis_name)
if min(miny, maxy)<=0:
self.axes.autoscale_view()
@@ -980,7 +992,7 @@
class XAxis(Axis):
__name__ = 'xaxis'
- axis = 'x'
+ axis_name = 'x'
def contains(self,mouseevent):
"""Test whether the mouse event occured in the x axis.
@@ -1156,6 +1168,9 @@
'return the Interval instance for this axis view limits'
return self.axes.viewLim.intervalx
+ def get_minpos(self):
+ return self.axes.dataLim.minposx
+
def get_data_interval(self):
'return the Interval instance for this axis data limits'
return self.axes.dataLim.intervalx
@@ -1163,7 +1178,7 @@
class YAxis(Axis):
__name__ = 'yaxis'
- axis = 'y'
+ axis_name = 'y'
def contains(self,mouseevent):
"""Test whether the mouse event occurred in the y axis.
@@ -1357,6 +1372,9 @@
'return the Interval instance for this axis view limits'
return self.axes.viewLim.intervaly
+ def get_minpos(self):
+ return self.axes.dataLim.minposy
+
def get_data_interval(self):
'return the Interval instance for this axis data limits'
return self.axes.dataLim.intervaly
Modified: branches/transforms/lib/matplotlib/lines.py
===================================================================
--- branches/transforms/lib/matplotlib/lines.py 2007-09-26 13:41:15 UTC (rev
3894)
+++ branches/transforms/lib/matplotlib/lines.py 2007-09-26 13:53:53 UTC (rev
3895)
@@ -564,6 +564,9 @@
return self._yorig
return self._y
+ def get_xydata(self):
+ return self._xy
+
def set_antialiased(self, b):
"""
True if line should be drawin with antialiased rendering
Modified: branches/transforms/lib/matplotlib/scale.py
===================================================================
--- branches/transforms/lib/matplotlib/scale.py 2007-09-26 13:41:15 UTC (rev
3894)
+++ branches/transforms/lib/matplotlib/scale.py 2007-09-26 13:53:53 UTC (rev
3895)
@@ -13,6 +13,66 @@
return IdentityTransform()
class LogScale(ScaleBase):
+ class Log10Transform(Transform):
+ input_dims = 1
+ output_dims = 1
+ def __init__(self):
+ Transform.__init__(self)
+
+ def is_separable(self):
+ return True
+
+ def transform(self, a):
+ return ma.log10(ma.masked_where(a <= 0.0, a * 10.0))
+
+ def inverted(self):
+ return LogScale.InvertedLog10Transform()
+
+ class InvertedLog10Transform(Transform):
+ input_dims = 1
+ output_dims = 1
+ def __init__(self):
+ Transform.__init__(self)
+
+ def is_separable(self):
+ return True
+
+ def transform(self, a):
+ return ma.power(10.0, a) / 10.0
+
+ def inverted(self):
+ return LogScale.Log10Transform()
+
+ class Log2Transform(Transform):
+ input_dims = 1
+ output_dims = 1
+ def __init__(self):
+ Transform.__init__(self)
+
+ def is_separable(self):
+ return True
+
+ def transform(self, a):
+ return ma.log2(ma.masked_where(a <= 0.0, a * 2.0))
+
+ def inverted(self):
+ return LogScale.InvertedLog2Transform()
+
+ class InvertedLog2Transform(Transform):
+ input_dims = 1
+ output_dims = 1
+ def __init__(self):
+ Transform.__init__(self)
+
+ def is_separable(self):
+ return True
+
+ def transform(self, a):
+ return ma.power(2.0, a) / 2.0
+
+ def inverted(self):
+ return LogScale.Log2Transform()
+
class LogTransform(Transform):
input_dims = 1
output_dims = 1
@@ -26,12 +86,12 @@
def transform(self, a):
if len(a) > 10:
print "Log Transforming..."
- return ma.log10(ma.masked_where(a <= 0.0, a * 10.0))
+ return ma.log(ma.masked_where(a <= 0.0, a * self._base)) /
npy.log(self._base)
def inverted(self):
return LogScale.InvertedLogTransform(self._base)
- class InvertedLogTransform(Transform):
+ class InvertedLog2Transform(Transform):
input_dims = 1
output_dims = 1
def __init__(self, base):
@@ -42,14 +102,21 @@
return True
def transform(self, a):
- return ma.power(10.0, a) / 10.0
+ return ma.power(self._base, a) / self._base
def inverted(self):
return LogScale.LogTransform(self._base)
+
+
+ def __init__(self, base=10):
+ if base == 10.0:
+ self._transform = self.Log10Transform()
+ elif base == 2.0:
+ self._transform = self.Log2Transform()
+ # MGDTODO: Natural log etc.
+ else:
+ self._transform = self.LogTransform(base)
- def __init__(self, base=10):
- self._transform = self.LogTransform(base)
-
def get_transform(self):
return self._transform
Modified: branches/transforms/lib/matplotlib/ticker.py
===================================================================
--- branches/transforms/lib/matplotlib/ticker.py 2007-09-26 13:41:15 UTC
(rev 3894)
+++ branches/transforms/lib/matplotlib/ticker.py 2007-09-26 13:53:53 UTC
(rev 3895)
@@ -919,21 +919,21 @@
def autoscale(self):
'Try to choose the view limits intelligently'
- vmin, vmax = self.axis.get_view_interval()
+ vmin, vmax = self.axis.get_data_interval()
if vmax<vmin:
vmin, vmax = vmax, vmin
-# minpos = self.dataInterval.minpos()
+ minpos = self.axis.get_minpos()
-# if minpos<=0:
-# raise RuntimeError('No positive data to plot')
+ if minpos<=0:
+ raise RuntimeError('No positive data to plot')
- # MGDTODO: Find a good way to track minpos
- if vmin <= 0.0:
- vmin = 0.1
-
+ if vmin <= minpos:
+ vmin = minpos
+
if not is_decade(vmin,self._base): vmin = decade_down(vmin,self._base)
if not is_decade(vmax,self._base): vmax = decade_up(vmax,self._base)
+
if vmin==vmax:
vmin = decade_down(vmin,self._base)
vmax = decade_up(vmax,self._base)
Modified: branches/transforms/lib/matplotlib/transforms.py
===================================================================
--- branches/transforms/lib/matplotlib/transforms.py 2007-09-26 13:41:15 UTC
(rev 3894)
+++ branches/transforms/lib/matplotlib/transforms.py 2007-09-26 13:53:53 UTC
(rev 3895)
@@ -224,6 +224,7 @@
def __init__(self, points):
BboxBase.__init__(self)
self._points = npy.asarray(points, npy.float_)
+ self._minpos = npy.array([0.0000001, 0.0000001])
self._invalid = False
[EMAIL PROTECTED]
@@ -252,15 +253,22 @@
return result
def update_from_data(self, x, y, ignore=True):
- if ignore:
+ if ignore:
+ self._points = npy.array(
+ [[x.min(), y.min()], [x.max(), y.max()]],
+ npy.float_)
+ self._minpos = npy.array(
+ [npy.where(x > 0.0, x, npy.inf).min(), npy.where(y > 0.0, y,
npy.inf).min()],
+ npy.float_)
+ else:
self._points = npy.array(
- [[x.min(), y.min()], [x.max(), y.max()]],
- npy.float_)
- else:
- self._points = npy.array(
[[min(x.min(), self.xmin), min(y.min(), self.ymin)],
[max(x.max(), self.xmax), max(y.max(), self.ymax)]],
npy.float_)
+ minpos = npy.array(
+ [npy.where(x > 0.0, x, npy.inf).min(), npy.where(y > 0.0, y,
npy.inf).min()],
+ npy.float_)
+ self._minpos = npy.minimum(minpos, self._minpos)
self.invalidate()
def _set_xmin(self, val):
@@ -309,6 +317,18 @@
self.invalidate()
bounds = property(BboxBase._get_bounds, _set_bounds)
+ def _get_minpos(self):
+ return self._minpos
+ minpos = property(_get_minpos)
+
+ def _get_minposx(self):
+ return self._minpos[0]
+ minposx = property(_get_minposx)
+
+ def _get_minposy(self):
+ return self._minpos[1]
+ minposy = property(_get_minposy)
+
def get_points(self):
self._invalid = False
return self._points
@@ -541,7 +561,7 @@
# print "".join(traceback.format_stack())
# print points
mtx = self.get_matrix()
- points = npy.asarray(values, npy.float_)
+ # points = npy.asarray(values, npy.float_)
return points * mtx[0,0] + mtx[0,1]
transform_affine = transform
@@ -695,10 +715,15 @@
# print "".join(traceback.format_stack())
# print points
mtx = self.get_matrix()
- points = npy.asarray(points, npy.float_)
- points = points.transpose()
- points = npy.dot(mtx[0:2, 0:2], points)
- points = points + mtx[0:2, 2:]
+ if ma.isarray(points):
+ points = points.transpose()
+ points = ma.dot(mtx[0:2, 0:2], points)
+ points = points + mtx[0:2, 2:]
+ else:
+ points = npy.asarray(points, npy.float_)
+ points = points.transpose()
+ points = npy.dot(mtx[0:2, 0:2], points)
+ points = points + mtx[0:2, 2:]
return points.transpose()
transform_affine = transform
@@ -869,7 +894,7 @@
y_points = y.transform(points[:, 1])
y_points = y_points.reshape((len(y_points), 1))
- return npy.concatenate((x_points, y_points), 1)
+ return ma.concatenate((x_points, y_points), 1)
transform_non_affine = transform
def transform_affine(self, points):
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