matplotlib-users Mailing List for matplotlib

On Sun, Apr 18, 2010 at 11:47 AM, Darren Dale <dsd...@gm...> wrote:

> On Tue, Apr 13, 2010 at 8:14 PM, Gökhan Sever <gok...@gm...>
> wrote:
> > Hello,
> >
> > Could someone confirm me if there is any malfunctioning using these
> simple
> > figure functions?
> >
> > plt.figure(figsize=(2,3))
> >
> > plt.figure(figsize=(5,6))
> >
> > plt.figure(figsize=(9,15))
> >
> > plt.figure(figsize=(19,5))
> >
> > For some reason I can't get Qt4Agg creating last two figures in specified
> > sizes. (WXAgg works fine.)
> >
> > matplotlib.__version__
> > '1.0.svn'
> >
> > matplotlib.__revision__
> > '$Revision: 8226 $'
> >
> > from PyQt4 import QtCore
> > QtCore.PYQT_VERSION_STR
> > '4.7'
>
> I can reproduce this behavior with a pure pyqt4 example with no mpl
> code, see below. I asked for advice on the pyqt mailing list.
>
> import sys
> from PyQt4 import QtCore, QtGui
>
> class Test(QtGui.QWidget):
>
>   def __init__(self, width, height):
>       QtGui.QWidget.__init__(self)
>       #self.setSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)
>       print 'Central widget should have width=%d, height=%d' %(width,
> height)
>       self._width = width
>       self._height = height
>
>   def sizeHint(self):
>       return QtCore.QSize(self._width, self._height)
>
> app = QtGui.QApplication([])
> m = QtGui.QMainWindow()
> c = Test(1000, 700)
> m.setCentralWidget(c)
> m.show()
> s = c.size()
> print 'but central widget has width=%d, height=%d'% (s.width(), s.height())
> sys.exit(app.exec_())
>

Same here with your sample:

Central widget should have width=1000, height=700
but central widget has width=960, height=600

I resorted to WXAgg for the time being. Waiting for some updates till I hear
a resolution. The annoying part is when I created a plot using specified
width and height Qt4Agg doesn't follow these dimensions as in this case and
resulting savefig(file.pdf) produces wrongly sized file unless I manually
extend the figure area and re-issue a savefig afterwards.



-- 
Gökhan

On Tue, Apr 13, 2010 at 8:14 PM, Gökhan Sever <gok...@gm...> wrote:
> Hello,
>
> Could someone confirm me if there is any malfunctioning using these simple
> figure functions?
>
> plt.figure(figsize=(2,3))
>
> plt.figure(figsize=(5,6))
>
> plt.figure(figsize=(9,15))
>
> plt.figure(figsize=(19,5))
>
> For some reason I can't get Qt4Agg creating last two figures in specified
> sizes. (WXAgg works fine.)
>
> matplotlib.__version__
> '1.0.svn'
>
> matplotlib.__revision__
> '$Revision: 8226 $'
>
> from PyQt4 import QtCore
> QtCore.PYQT_VERSION_STR
> '4.7'

I can reproduce this behavior with a pure pyqt4 example with no mpl
code, see below. I asked for advice on the pyqt mailing list.

import sys
from PyQt4 import QtCore, QtGui

class Test(QtGui.QWidget):

   def __init__(self, width, height):
       QtGui.QWidget.__init__(self)
       #self.setSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)
       print 'Central widget should have width=%d, height=%d' %(width, height)
       self._width = width
       self._height = height

   def sizeHint(self):
       return QtCore.QSize(self._width, self._height)

app = QtGui.QApplication([])
m = QtGui.QMainWindow()
c = Test(1000, 700)
m.setCentralWidget(c)
m.show()
s = c.size()
print 'but central widget has width=%d, height=%d'% (s.width(), s.height())
sys.exit(app.exec_())

On Sun, Apr 18, 2010 at 12:10 AM, Gary Ruben <gr...@bi...> wrote:
> I've been helping a fairly new Python user (an astronomer using
> numpy/scipy/matplotlib) in my office get up to speed with matplotlib and
> thought I'd pass on a couple of small thoughts about the documentation
> which we think would make life clearer for new users. I'm putting this
> out for discussion, because it may be totally off-the-mark. On the other
> hand, it may point to some easy changes to make things clearer for new
> users.
>
> First, I think that a new user, presented with the mpl homepage, reads
> the intro on that page, then perhaps clicks through to either the
> pyplot, examples, or gallery pages. They may take example code from
> examples or gallery and modify them for their own plots, but they will
> at some point be referencing the pyplot page (this is also my
> most-visited page on the site).
>
> The matplotlib.pyplot page would really benefit from a few introductory
> paragraphs or even a single sentence with a link to the relevant section
> in the docs, explaining what the relationship of pyplot is to the other
> parts of mpl.
> Specifically, I think confusion arises because the explanation about the
> stateful nature of the pyplot interface is (I think) first mentioned at
> the start of the pyplot tutorial page, and is perhaps not emphasized
> enough. It may also be worth stating somewhere in the front-page mpl
> intro that it is recommended that new users do the pyplot tutorial.
>
> The signatures that a new user sees are full of *args and **kwargs which
> is confusing for the new user. There is an explanation in the coding
> guide so perhaps another paragraph or sentence+link to this would help,
> but I think it's probably not a good idea to be directing new users into
> the coding guide. I know about the history of this and I gather that
> most or all of the args are actually tabulated in the documentation now,
> but new users don't necessarily know what *args and **kwargs mean. I
> think there's still a general lack of consistency in the pyplot docs
> related to this. Some docstrings have the call signature shown, with
> default values shown. It's confusing that some kwargs have explicit
> descriptions and appear in the call signature whereas others are just
> "additional kwargs". This split seems to me to be exposing the
> underlying implementation of the function to the user. I don't know
> whether there is logic behind this.
>
> The final area of confusion is to do with jargon, as this seems to creep
> into examples and list discussions. The introduction to the Artist
> Tutorial is quite useful for understanding mpl's plotting model.
> However, for the new user, it is pretty much impenetrable due to the
> jargon and references to other libraries and coding concepts that a new
> user doesn't need to know. I think a gentler description of mpl's
> plotting model in the introduction or in a standalone small chapter
> would be helpful for new users.

The documentation exists to help the users, so if you're having
trouble with them, the docs probably *are* lacking. I know I'm not
likely to get to this any time soon however, so patches are welcome.
:)

If you're interested, the docs live here:
http://matplotlib.svn.sourceforge.net/viewvc/matplotlib/trunk/matplotlib/doc/

Ryan

-- 
Ryan May
Graduate Research Assistant
School of Meteorology
University of Oklahoma

I've been helping a fairly new Python user (an astronomer using 
numpy/scipy/matplotlib) in my office get up to speed with matplotlib and 
thought I'd pass on a couple of small thoughts about the documentation 
which we think would make life clearer for new users. I'm putting this 
out for discussion, because it may be totally off-the-mark. On the other 
hand, it may point to some easy changes to make things clearer for new 
users.

First, I think that a new user, presented with the mpl homepage, reads 
the intro on that page, then perhaps clicks through to either the 
pyplot, examples, or gallery pages. They may take example code from 
examples or gallery and modify them for their own plots, but they will 
at some point be referencing the pyplot page (this is also my 
most-visited page on the site).

The matplotlib.pyplot page would really benefit from a few introductory 
paragraphs or even a single sentence with a link to the relevant section 
in the docs, explaining what the relationship of pyplot is to the other 
parts of mpl.
Specifically, I think confusion arises because the explanation about the 
stateful nature of the pyplot interface is (I think) first mentioned at 
the start of the pyplot tutorial page, and is perhaps not emphasized 
enough. It may also be worth stating somewhere in the front-page mpl 
intro that it is recommended that new users do the pyplot tutorial.

The signatures that a new user sees are full of *args and **kwargs which 
is confusing for the new user. There is an explanation in the coding 
guide so perhaps another paragraph or sentence+link to this would help, 
but I think it's probably not a good idea to be directing new users into 
the coding guide. I know about the history of this and I gather that 
most or all of the args are actually tabulated in the documentation now, 
but new users don't necessarily know what *args and **kwargs mean. I 
think there's still a general lack of consistency in the pyplot docs 
related to this. Some docstrings have the call signature shown, with 
default values shown. It's confusing that some kwargs have explicit 
descriptions and appear in the call signature whereas others are just 
"additional kwargs". This split seems to me to be exposing the 
underlying implementation of the function to the user. I don't know 
whether there is logic behind this.

The final area of confusion is to do with jargon, as this seems to creep 
into examples and list discussions. The introduction to the Artist 
Tutorial is quite useful for understanding mpl's plotting model. 
However, for the new user, it is pretty much impenetrable due to the 
jargon and references to other libraries and coding concepts that a new 
user doesn't need to know. I think a gentler description of mpl's 
plotting model in the introduction or in a standalone small chapter 
would be helpful for new users.

Gary R.