matplotlib-devel Mailing List for matplotlib

On Thu, Jul 29, 2010 at 6:17 PM, Benjamin Root <ben...@ou...> wrote:

> As a side-note, it looks like various files that have been changed due to
> svnmerge.py are still showing themselves as having their properties
> modified.  Is this ok?

Yes, for some reason some of the files, like axes3d examples, are
always tagged with property changes on svn merges.  It's a nuisance.
but harmless.  In the handling of weights vs x, I notice in some
places we call np.array and others np.asarray.  Shouldn't we be using
asarray in all of these cases, eg

Index: lib/matplotlib/axes.py
===================================================================
--- lib/matplotlib/axes.py	(revision 8606)
+++ lib/matplotlib/axes.py	(working copy)
@@ -7401,11 +7401,13 @@
              **kwargs):
         """
         call signature::
+
+          def hist(x, bins=10, range=None, normed=False, weights=None,
+                 cumulative=False, bottom=None, histtype='bar', align='mid',
+                 orientation='vertical', rwidth=None, log=False,
+                 color=None, label=None,
+                 **kwargs):

-          hist(x, bins=10, range=None, normed=False, cumulative=False,
-               bottom=None, histtype='bar', align='mid',
-               orientation='vertical', rwidth=None, log=False, **kwargs)
-
         Compute and draw the histogram of *x*. The return value is a
         tuple (*n*, *bins*, *patches*) or ([*n0*, *n1*, ...], *bins*,
         [*patches0*, *patches1*,...]) if the input contains multiple
@@ -7567,7 +7569,7 @@
                     'this looks transposed (shape is %d x %d)' % x.shape[::-1])
         else:
             # multiple hist with data of different length
-            x = [np.array(xi) for xi in x]
+            x = [np.asarray(xi) for xi in x]

         nx = len(x) # number of datasets

@@ -7582,7 +7584,7 @@
         # We need to do to 'weights' what was done to 'x'
         if weights is not None:
             if isinstance(weights, np.ndarray) or not iterable(weights[0]) :
-                w = np.array(weights)
+                w = np.asarray(weights)
                 if w.ndim == 2:
                     w = w.T
                 elif w.ndim == 1:
@@ -7590,7 +7592,7 @@
                 else:
                     raise ValueError("weights must be 1D or 2D")
             else:
-                w = [np.array(wi) for wi in weights]
+                w = [np.asarray(wi) for wi in weights]

             if len(w) != nx:
                 raise ValueError('weights should have the same shape as x')

I don't think this is just an issue of "bbox_inches" option. For
example, if you create an axes of rect=[0,0,1,1] and save the figure
(w/o bbox_inches option), you will see a similar behavior.
Also, I believe that the result depends on the backends.

I think this kind of issue is quite difficult to resolve and I doubt
if this will be solved anytime soon.
Any contribution will be very much appreciated.

Regards,

-JJ




On Sat, Jul 31, 2010 at 5:48 AM, Damon McDougall
<D.M...@wa...> wrote:
> Aha! Even without the text, i.e. setting label1On = False for all the major ticks, the behaviour I see is that with bbox_inches = 'tight' and pad_inches = 0.0 I get the saved figure which includes the black border line for the bottom and left edges, but not the top and right edges. This may have something to do with it. Maybe it's an issue with the bounding box not being 'inclusive' and leaving out the end points?
>
> Regards,
> -- Damon
>
> --------------------------
> Damon McDougall
> Mathematics Institute
> University of Warwick
> Coventry
> CV4 7AL
> d.m...@wa...
>
>
>
> On 30 Jul 2010, at 20:33, Eric Firing wrote:
>
>> On 07/30/2010 06:32 AM, Damon McDougall wrote:
>>> Hmm, it seems as though tick labels get clipped on the top and on the right when passing bbox_inches='tight' and pad_inches=0.0. I wouldn't expect this behaviour. Is there perhaps a bug in Bbox.union that's causing this?
>>>
>>
>> Not likely.  Much more likely is a problem in calculating the rendered
>> size of the text.
>>
>> Eric
>>
>>> Regards,
>>> -- Damon
>>>
>>> --------------------------
>>> Damon McDougall
>>> Mathematics Institute
>>> University of Warwick
>>> Coventry
>>> CV4 7AL
>>> d.m...@wa...
>>>
>>>
>>>
>>> On 30 Jul 2010, at 16:03, Tony S Yu wrote:
>>>
>>>>
>>>> On Jul 30, 2010, at 10:54 AM, Damon McDougall wrote:
>>>>
>>>>> Hi,
>>>>>
>>>>> I'm interested in fiddling around with the matplotlib source. Let's say we set up various things:
>>>>>
>>>>> from matplotlib.figure import Figure()
>>>>> from matplotlib.backends.backend_pdf import FigureCanvasPdf as FigureCanvas
>>>>>
>>>>> fig = Figure()
>>>>> canvas = FigureCanvas(fig)
>>>>> ax = fig.add_subplot(1, 1, 1)
>>>>> fig.savefig('asd.pdf', bbox_inches='tight')
>>>>>
>>>>> I would like to know what exactly happens when bbox_inches='tight' is passed to savefig(). I've been searching in the figure.py source and nowhere can I see the bbox_inches='tight' keyword being tested for in the savefig() method. Having said that, all of the kwargs do get passed on to the canvas.print_figure() method, so I looked in the backend_pdf.py file but couldn't find a print_figure() method. Could someone point me in the right direction?
>>>>>
>>>>> Regards,
>>>>> -- Damon
>>>>
>>>> That's funny: I was just looking at bbox_inches='tight' recently. You'll find the relevant section in matplotlib.backend_bases.print_figure.
>>>>
>>>> Best,
>>>> -Tony
>>>>
>>>
>>>
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