I've made some alterations to the hist() function in axes.py (attached
is a diff against the current SVN version). I've added the capability
to use the same interface to make outline histograms instead of bar
histograms (and a third option for outlines with fill - note that this
is NOT the same as calling it twice with the other two, as the widths
are slightly different). There's a slight compatibility issue in that
as it stands in that the returned tuple now has 4 values (I added a
list of the lines that are generated if the steps command is used),
but I can't really imagine how that could break anything but the
poorest-written code... Anyone think this is worth committing to SVN?
(One thing that bothers me a little is the part of the code that adds
the last two edges to the histogram - the problem is that if you have
a line size greater than 1, the outline overshoots the rest of the
outline by a very tiny bit... if anyone knows how to cut off the upper
row of pixels to make it flush with the rest of the outline... it's
perfectly usable as-is, though - that's just a tiny little aesthetic
quibble)
--
Erik Tollerud
Graduate Student
Center For Cosmology
Department of Physics and Astronomy
4155B Frederick Reines Hall
University of California, Irvine
Office Phone: (949)824-2996
Cell: (651)307-9409
[EMAIL PROTECTED]
Index: lib/matplotlib/axes.py
===================================================================
--- lib/matplotlib/axes.py (revision 5027)
+++ lib/matplotlib/axes.py (working copy)
@@ -5168,15 +5168,14 @@
#### Data analysis
-
-
- def hist(self, x, bins=10, normed=0, bottom=None,
+
+ def hist(self, x, bins=10, normed=0, bottom=None, histtype='bar',
align='edge', orientation='vertical', width=None,
- log=False, **kwargs):
+ log=False, lineprops={},**kwargs):
"""
- HIST(x, bins=10, normed=0, bottom=None,
+ HIST(x, bins=10, normed=0, bottom=None, histtype='bar',
align='edge', orientation='vertical', width=None,
- log=False, **kwargs)
+ log=False, lineprops={},**kwargs)
Compute the histogram of x. bins is either an integer number of
bins or a sequence giving the bins. x are the data to be binned.
@@ -5192,6 +5191,10 @@
# trapezoidal integration of the probability density function
pdf, bins, patches = ax.hist(...)
print npy.trapz(pdf, bins)
+
+ histtype = 'bar' | 'step' | 'stepfill'. The type of histogram
+ to draw - 'bar' is a traditional bar-type histogram, 'step'
+ generates a lineplot
align = 'edge' | 'center'. Interprets bins either as edge
or center values
@@ -5200,28 +5203,103 @@
will be used and the "bottom" kwarg will be the left edges.
width: the width of the bars. If None, automatically compute
- the width.
+ the width. Ignored for 'step' type.
log: if True, the histogram axis will be set to a log scale
+
+ lineprops: a mapping to update the properties of the line
+ for the 'step' or 'stepfill' type.
+ %(Line2D)s
kwargs are used to update the properties of the
- hist Rectangles:
+ hist Rectangles for 'bar' or 'stepfill' type.
%(Rectangle)s
"""
if not self._hold: self.cla()
n, bins = npy.histogram(x, bins, range=None, normed=normed)
- if width is None: width = 0.9*(bins[1]-bins[0])
- if orientation == 'horizontal':
- patches = self.barh(bins, n, height=width, left=bottom,
- align=align, log=log)
- elif orientation == 'vertical':
- patches = self.bar(bins, n, width=width, bottom=bottom,
- align=align, log=log)
+ if width is None:
+ if 'step' in histtype:
+ width = (bins[1]-bins[0])
+ kwargs['lw']=0 #make the fill lines non-existent
+ else:
+ width = 0.9*(bins[1]-bins[0])
+ if 'step' in histtype:
+ if orientation == 'horizontal':
+ if align=='edge':
+ lines=self.plot(npy.concatenate((n[-1:],n)),
+ npy.concatenate((bins,bins[-1:]+width)),
+ ls='steps-post')
+ #add lines for the right and left edges
+ lines.append(mlines.Line2D([0,n[0]],[bins[0],bins[0]]))
+ lines[-1].update_from(lines[0])
+ lines[-1].set_ls('-')
+ self.add_line(lines[-1])
+ lines.append(mlines.Line2D([0,n[-1]],[bins[-1:]+width,bins[-1:]+width]))
+ lines[-1].update_from(lines[0])
+ lines[-1].set_ls('-')
+ self.add_line(lines[-1])
+ else:
+ lines=self.plot(npy.concatenate((n[-1:],n)),
+ npy.concatenate((bins,bins[-1:]+width))-width/2,
+ ls='steps-post')
+ #add lines for the right and left edges
+ lines.append(mlines.Line2D([0,n[0]],[bins[0]-width/2,bins[0]-width/2]))
+ lines[-1].update_from(lines[0])
+ lines[-1].set_ls('-')
+ self.add_line(lines[-1])
+ lines.append(mlines.Line2D([0,n[-1]],[bins[-1:]+width/2,bins[-1:]+width/2]))
+ lines[-1].update_from(lines[0])
+ lines[-1].set_ls('-')
+ self.add_line(lines[-1])
+
+ elif orientation == 'vertical':
+ if align=='edge':
+ lines=self.plot(npy.concatenate((bins,bins[-1:]+width)),
+ npy.concatenate((n,n[-1:])),ls='steps-post')
+ #add lines for the right and left edges
+ lines.append(mlines.Line2D([bins[0],bins[0]],[0,n[0]]))
+ lines[-1].update_from(lines[0])
+ lines[-1].set_ls('-')
+ self.add_line(lines[-1])
+ lines.append(mlines.Line2D([bins[-1:]+width,bins[-1:]+width],[0,n[-1]]))
+ lines[-1].update_from(lines[0])
+ lines[-1].set_ls('-')
+ self.add_line(lines[-1])
+ else:
+ lines=self.plot(npy.concatenate((bins,bins[-1:]+width))-width/2,
+ npy.concatenate((n,n[-1:])),ls='steps-post')
+ #add lines for the right and left edges
+ lines.append(mlines.Line2D([bins[0]-width/2,bins[0]-width/2],[0,n[0]]))
+ lines[-1].update_from(lines[0])
+ lines[-1].set_ls('-')
+ self.add_line(lines[-1])
+ lines.append(mlines.Line2D([bins[-1:]+width/2,bins[-1:]+width/2],[0,n[-1]]))
+ lines[-1].update_from(lines[0])
+ lines[-1].set_ls('-')
+ self.add_line(lines[-1])
+ else:
+ raise ValueError, 'invalid orientation: %s' % orientation
+ for l in lines:
+ l.update(lineprops)
else:
- raise ValueError, 'invalid orientation: %s' % orientation
- for p in patches:
- p.update(kwargs)
- return n, bins, cbook.silent_list('Patch', patches)
+ lines=[]
+
+ if histtype != 'step':
+ if orientation == 'horizontal':
+ patches = self.barh(bins, n, height=width, left=bottom,
+ align=align, log=log)
+ elif orientation == 'vertical':
+ patches = self.bar(bins, n, width=width, bottom=bottom,
+ align=align, log=log)
+ else:
+ raise ValueError, 'invalid orientation: %s' % orientation
+ for p in patches:
+ p.update(kwargs)
+ else:
+ patches=[]
+
+ return n, bins, cbook.silent_list('Patch', patches),cbook.silent_list('Line2D', lines)
+
hist.__doc__ = cbook.dedent(hist.__doc__) % martist.kwdocd
def psd(self, x, NFFT=256, Fs=2, Fc=0, detrend=mlab.detrend_none,
-------------------------------------------------------------------------
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