matplotlib-users Mailing List for matplotlib (Page 27)

Following up on this, I’d like to complain about set_aspect()…

If I do:

import matplotlib.pyplot as plt
fig, axes = plt.subplots(nrows=2,sharex=True)
axes[0].set_ylim(0,1.)
axes[0].set_aspect(1.)
plt.show()

the x-axis goes from 0. to 1., but axes[0]’s y-axis goes from 0.32 to 0.67.  Swapping the order of the y_lim call doesn’t help.  This is very un-intuitive, as I’d expect set_ylim() to set what data I see no matter what else is happening w/ the plot.

I see that 
axes[0].set_aspect(1.,adjustable=‘box-forced’)
will give the desired behaviour, but I really think it should be the default, not adjustable=‘datalim'.  I had no idea set_aspect() had this parameter until today, and have had several cursing matches with set_aspect as it kept changing my explicitly set data limits. set_ylim() should set the y limits.   

Just my opinion.  Maybe there is a reason for the default, but I really think the data view should be prioritized over the shape of the axis.

Thanks,   Jody


> On 8 Apr 2015, at  5:53 AM, Thomas Caswell <tca...@gm...> wrote:
> 
> What version had this behavior?  I recall some work on how aspect worked, but not exactly what we did.  I see why it is useful, but on the other hand that sort of coupling seems like could cause some trouble if we are not careful.  This all come back to we need a real layout manager/constraint solver (which no one has yet had time to address).
> 
> For now I think this will do what you want:
> 
> import numpy as np
> import matplotlib.pyplot as plt
> from mpl_toolkits.axes_grid1 import make_axes_locatable
> 
> fig, ax_top = plt.subplots()
> ax_top.set_aspect(1)
> divider = make_axes_locatable(ax_top)
> bax_bottom = divider.append_axes('bottom', 1, pad=0.1,
>                                          sharex=ax_top)
> 
> 
> Please don't use `plt.setp`, it is a MATLABism that I think is past it's time.
> 
> On Wed, Apr 8, 2015 at 8:21 AM Mark Bakker <ma...@gm... <mailto:ma...@gm...>> wrote:
> import matplotlib.pyplot as plt
> %matplotlib qt
> fig, axes = plt.subplots(nrows=2,sharex=True)
> plt.setp(axes[0], aspect=1.0, adjustable='box-forced')
> plt.show()
> 
> This used to create two axes of the same horizontal size. What it does now is that it scales the upper axis so that the aspect=1.0 by changing the physical size of the axis. But the physical size of the lower axis is not changed, while this used to be the case in the past (but that may have been a few years back). That sure used to be the desired behavior.
> 
> Thanks for your help,
> 
> Mark
> 
> 
> 
> On Wed, Apr 8, 2015 at 2:16 PM, Thomas Caswell <tca...@gm... <mailto:tca...@gm...>> wrote:
> Can you please provide a minimal, but complete and runnable example of what you are doing?
> 
> 
> On Wed, Apr 8, 2015, 08:13 Mark Bakker <ma...@gm... <mailto:ma...@gm...>> wrote:
> Thanks, Thomas.
> 
> That works indeed, but it doesn't make the figure adjustable, which is what I wanted (that the physical size of the axes changes while the aspect ratio is fixed to 1). I guess that functionality has been taken out. 
> 
> Mark
> 
> On Wed, Apr 8, 2015 at 12:50 PM, Thomas Caswell <tca...@gm... <mailto:tca...@gm...>> wrote:
> What are the data limits you are using?
> 
> I suspect they you are over constraining the system/order of operations issue. Try dropping the adjustable setting and pre setting both the data limits and the approximate size in figure fraction (ex via grid spec) of the axes.
> 
> Tom
> 
> 
> On Tue, Apr 7, 2015, 15:54 Mark Bakker <ma...@gm... <mailto:ma...@gm...>> wrote:
> Hello list,
> 
> I want to axes above each other. They share the x-axis. The top figure has 'aspect=1' (it is a map), the bottom figure shows a cross-section along a horizontal line on the map, so it doesn't have 'aspect=1'. When I do this with code, for example like this:
> 
> fig, axes = plt.subplots(nrows=2,sharex=True)
> plt.setp(axes[0], aspect=1.0, adjustable='box-forced')
> 
> then the physical size of the top axes is much sorter than the physical size of the bottom axes (although they are poperly linked, as they have the same data limit, and when zooming in the top figure, the bottom figure adjusts). It just looks weird, as the size of the horizontal axis of the bottom figure should have the same physical size as the horizontal axis of the top figure. This used to be possible (a few years ago; haven't tried it for a while). Is there a way to do it with the current matpotlib? (1.4.3)
> 
> Thanks,
> 
> Mark
> ------------------------------------------------------------------------------
> BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT
> Develop your own process in accordance with the BPMN 2 standard
> Learn Process modeling best practices with Bonita BPM through live exercises
> http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual- <http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual-> event?utm_
> source=Sourceforge_BPM_Camp_5_6_15&utm_medium=email&utm_campaign=VA_SF_______________________________________________
> Matplotlib-users mailing list
> Mat...@li... <mailto:Mat...@li...>
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users <https://lists.sourceforge.net/lists/listinfo/matplotlib-users>
> 
> 
> ------------------------------------------------------------------------------
> BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT
> Develop your own process in accordance with the BPMN 2 standard
> Learn Process modeling best practices with Bonita BPM through live exercises
> http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual- event?utm_
> source=Sourceforge_BPM_Camp_5_6_15&utm_medium=email&utm_campaign=VA_SF_______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users

--
Jody Klymak    
http://web.uvic.ca/~jklymak/

Hello, 

how can I plot circles or other shapes in plots which have logarithmic axis? 
I have a grid of 3 plots and want to plot some kind of sketches in the lower
right corner of
each subplot. How should I do that?

import numpy as np
from matplotlib import pyplot as plt
from matplotlib import gridspec

fig = plt.figure(figsize=(6, 10)) 
gs = gridspec.GridSpec(3, 1, height_ratios=[1.5, 1, 1])#, height_ratios=[2,
1, 1])
ax0 = plt.subplot(gs[0])
ax1 = plt.subplot(gs[1])
ax2 = plt.subplot(gs[2])
plt.setp(ax_new.get_yticklabels(), visible=False)
plt.setp(ax_new.get_xticklabels(), visible=False)
ax_new = fig.add_axes([0,0,1,1], frameon=False,aspect="equal")
ax_new.axes.get_yaxis().set_visible(False)
ax_new.axes.get_xaxis().set_visible(False)
circle1=plt.Circle((0.2,0.0),0.05, color="0.8")
circle2=plt.Circle((0.4,0.0),0.05, color="0.8")
ax_new.add_artist(circle1)
ax_new.add_artist(circle2)

ax0.semilogx(x,x**2, "k-", linewidth=2)
ax1.semilogx(x,x**3, "k--", linewidth=2)
ax2.semilogx(x,np.exp(-x)+x**4, "k-.", linewidth=2)
plt.tight_layout()
plt.show()



--
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<html>
  <head>

    <meta http-equiv="content-type" content="text/html; charset=utf-8">
  </head>
  <body bgcolor="#FFFFFF" text="#000000">
    Hello,<br>
    <br>
    I have been fighting with this problem for some time. It seems that
    if, on a plot, I have some text inside a bounding box, it displays
    fine on the screen, saves OK as a PNG, but when I save the plot as a
    PDF the padding on the right side between the text and the box
    disappears. I have attached a minimal example with a text box, but
    this problem occurs for legends as well, if the legend text is
    long-ish. I am also attaching a PNG and a PDF output, as well as how
    the PDF shows up on my viewer. Has anyone else experienced this?<br>
    <br>
    Other relevant info:<br>
    <br>
    <b>$ uname -a</b><br>
    Linux Merlin 3.2.0-77-generic #114-Ubuntu SMP Tue Mar 10 17:26:03
    UTC 2015 x86_64 x86_64 x86_64 GNU/Linux<br>
    <br>
    <b>$ python -c 'import matplotlib; print matplotlib.__version__'</b><br>
    1.3.1<br>
    <br>
    <b>Where I obtained matplotlib:</b> <br>
    The matplotlib SourceForge site<br>
    <br>
    <b>Customisations to </b><b>matplotlibrc:</b><br>
    backend      : Qt4Agg<br>
    lines.markersize  : 10            # markersize, in points<br>
    font.sans-serif      : Ubuntu, Calibri, Liberation Sans<br>
    font.monospace       : Consolas, Inconsolata, Ubuntu Mono, Droid
    Sans Mono<br>
    axes.color_cycle : e41a1c, 377eb8, 4daf4a, 984ea3, ff7f00, ffff33,
    a65628, f781bf, 999999<br>
    pdf.fonttype       : 42         # Output Type 3 (Type3) or Type 42
    (TrueType) # I have tried with fonttype=3 as well, and the bug still
    exists<br>
    <br>
    <b>$ python bug_test.py --verbose-helpful &gt; output.txt</b><br>
    output.txt attached<br>
    <br>
    Thanks,<br>
    Sourish<br>
    <br>
  </body>
</html>

What version had this behavior?  I recall some work on how aspect worked,
but not exactly what we did.  I see why it is useful, but on the other hand
that sort of coupling seems like could cause some trouble if we are not
careful.  This all come back to we need a real layout manager/constraint
solver (which no one has yet had time to address).

For now I think this will do what you want:

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable

fig, ax_top = plt.subplots()
ax_top.set_aspect(1)
divider = make_axes_locatable(ax_top)
bax_bottom = divider.append_axes('bottom', 1, pad=0.1,
                                         sharex=ax_top)


Please don't use `plt.setp`, it is a MATLABism that I think is past it's
time.

On Wed, Apr 8, 2015 at 8:21 AM Mark Bakker <ma...@gm...> wrote:

> import matplotlib.pyplot as plt
> %matplotlib qt
> fig, axes = plt.subplots(nrows=2,sharex=True)
> plt.setp(axes[0], aspect=1.0, adjustable='box-forced')
> plt.show()
>
> This used to create two axes of the same horizontal size. What it does now
> is that it scales the upper axis so that the aspect=1.0 by changing the
> physical size of the axis. But the physical size of the lower axis is not
> changed, while this used to be the case in the past (but that may have been
> a few years back). That sure used to be the desired behavior.
>
> Thanks for your help,
>
> Mark
>
>
>
> On Wed, Apr 8, 2015 at 2:16 PM, Thomas Caswell <tca...@gm...> wrote:
>
>> Can you please provide a minimal, but complete and runnable example of
>> what you are doing?
>>
>> On Wed, Apr 8, 2015, 08:13 Mark Bakker <ma...@gm...> wrote:
>>
>>> Thanks, Thomas.
>>>
>>> That works indeed, but it doesn't make the figure adjustable, which is
>>> what I wanted (that the physical size of the axes changes while the aspect
>>> ratio is fixed to 1). I guess that functionality has been taken out.
>>>
>>> Mark
>>>
>>> On Wed, Apr 8, 2015 at 12:50 PM, Thomas Caswell <tca...@gm...>
>>> wrote:
>>>
>>>> What are the data limits you are using?
>>>>
>>>> I suspect they you are over constraining the system/order of operations
>>>> issue. Try dropping the adjustable setting and pre setting both the data
>>>> limits and the approximate size in figure fraction (ex via grid spec) of
>>>> the axes.
>>>>
>>>> Tom
>>>>
>>>> On Tue, Apr 7, 2015, 15:54 Mark Bakker <ma...@gm...> wrote:
>>>>
>>>>> Hello list,
>>>>>
>>>>> I want to axes above each other. They share the x-axis. The top figure
>>>>> has 'aspect=1' (it is a map), the bottom figure shows a cross-section along
>>>>> a horizontal line on the map, so it doesn't have 'aspect=1'. When I do this
>>>>> with code, for example like this:
>>>>>
>>>>> fig, axes = plt.subplots(nrows=2,sharex=True)
>>>>> plt.setp(axes[0], aspect=1.0, adjustable='box-forced')
>>>>>
>>>>> then the physical size of the top axes is much sorter than the
>>>>> physical size of the bottom axes (although they are poperly linked, as they
>>>>> have the same data limit, and when zooming in the top figure, the bottom
>>>>> figure adjusts). It just looks weird, as the size of the horizontal axis of
>>>>> the bottom figure should have the same physical size as the horizontal axis
>>>>> of the top figure. This used to be possible (a few years ago; haven't tried
>>>>> it for a while). Is there a way to do it with the current matpotlib? (1.4.3)
>>>>>
>>>>> Thanks,
>>>>>
>>>>> Mark
>>>>> ------------------------------------------------------------
>>>>> ------------------
>>>>> BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT
>>>>> Develop your own process in accordance with the BPMN 2 standard
>>>>> Learn Process modeling best practices with Bonita BPM through live
>>>>> exercises
>>>>> http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual-
>>>>> event?utm_
>>>>> source=Sourceforge_BPM_Camp_5_6_15&utm_medium=email&utm_
>>>>> campaign=VA_SF_______________________________________________
>>>>> Matplotlib-users mailing list
>>>>> Mat...@li...
>>>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>>>
>>>>
>>>
>

import matplotlib.pyplot as plt
%matplotlib qt
fig, axes = plt.subplots(nrows=2,sharex=True)
plt.setp(axes[0], aspect=1.0, adjustable='box-forced')
plt.show()

This used to create two axes of the same horizontal size. What it does now
is that it scales the upper axis so that the aspect=1.0 by changing the
physical size of the axis. But the physical size of the lower axis is not
changed, while this used to be the case in the past (but that may have been
a few years back). That sure used to be the desired behavior.

Thanks for your help,

Mark



On Wed, Apr 8, 2015 at 2:16 PM, Thomas Caswell <tca...@gm...> wrote:

> Can you please provide a minimal, but complete and runnable example of
> what you are doing?
>
> On Wed, Apr 8, 2015, 08:13 Mark Bakker <ma...@gm...> wrote:
>
>> Thanks, Thomas.
>>
>> That works indeed, but it doesn't make the figure adjustable, which is
>> what I wanted (that the physical size of the axes changes while the aspect
>> ratio is fixed to 1). I guess that functionality has been taken out.
>>
>> Mark
>>
>> On Wed, Apr 8, 2015 at 12:50 PM, Thomas Caswell <tca...@gm...>
>> wrote:
>>
>>> What are the data limits you are using?
>>>
>>> I suspect they you are over constraining the system/order of operations
>>> issue. Try dropping the adjustable setting and pre setting both the data
>>> limits and the approximate size in figure fraction (ex via grid spec) of
>>> the axes.
>>>
>>> Tom
>>>
>>> On Tue, Apr 7, 2015, 15:54 Mark Bakker <ma...@gm...> wrote:
>>>
>>>> Hello list,
>>>>
>>>> I want to axes above each other. They share the x-axis. The top figure
>>>> has 'aspect=1' (it is a map), the bottom figure shows a cross-section along
>>>> a horizontal line on the map, so it doesn't have 'aspect=1'. When I do this
>>>> with code, for example like this:
>>>>
>>>> fig, axes = plt.subplots(nrows=2,sharex=True)
>>>> plt.setp(axes[0], aspect=1.0, adjustable='box-forced')
>>>>
>>>> then the physical size of the top axes is much sorter than the physical
>>>> size of the bottom axes (although they are poperly linked, as they have the
>>>> same data limit, and when zooming in the top figure, the bottom figure
>>>> adjusts). It just looks weird, as the size of the horizontal axis of the
>>>> bottom figure should have the same physical size as the horizontal axis of
>>>> the top figure. This used to be possible (a few years ago; haven't tried it
>>>> for a while). Is there a way to do it with the current matpotlib? (1.4.3)
>>>>
>>>> Thanks,
>>>>
>>>> Mark
>>>> ------------------------------------------------------------
>>>> ------------------
>>>> BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT
>>>> Develop your own process in accordance with the BPMN 2 standard
>>>> Learn Process modeling best practices with Bonita BPM through live
>>>> exercises
>>>> http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual-
>>>> event?utm_
>>>> source=Sourceforge_BPM_Camp_5_6_15&utm_medium=email&utm_
>>>> campaign=VA_SF_______________________________________________
>>>> Matplotlib-users mailing list
>>>> Mat...@li...
>>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>>
>>>
>>

Can you please provide a minimal, but complete and runnable example of what
you are doing?

On Wed, Apr 8, 2015, 08:13 Mark Bakker <ma...@gm...> wrote:

> Thanks, Thomas.
>
> That works indeed, but it doesn't make the figure adjustable, which is
> what I wanted (that the physical size of the axes changes while the aspect
> ratio is fixed to 1). I guess that functionality has been taken out.
>
> Mark
>
> On Wed, Apr 8, 2015 at 12:50 PM, Thomas Caswell <tca...@gm...>
> wrote:
>
>> What are the data limits you are using?
>>
>> I suspect they you are over constraining the system/order of operations
>> issue. Try dropping the adjustable setting and pre setting both the data
>> limits and the approximate size in figure fraction (ex via grid spec) of
>> the axes.
>>
>> Tom
>>
>> On Tue, Apr 7, 2015, 15:54 Mark Bakker <ma...@gm...> wrote:
>>
>>> Hello list,
>>>
>>> I want to axes above each other. They share the x-axis. The top figure
>>> has 'aspect=1' (it is a map), the bottom figure shows a cross-section along
>>> a horizontal line on the map, so it doesn't have 'aspect=1'. When I do this
>>> with code, for example like this:
>>>
>>> fig, axes = plt.subplots(nrows=2,sharex=True)
>>> plt.setp(axes[0], aspect=1.0, adjustable='box-forced')
>>>
>>> then the physical size of the top axes is much sorter than the physical
>>> size of the bottom axes (although they are poperly linked, as they have the
>>> same data limit, and when zooming in the top figure, the bottom figure
>>> adjusts). It just looks weird, as the size of the horizontal axis of the
>>> bottom figure should have the same physical size as the horizontal axis of
>>> the top figure. This used to be possible (a few years ago; haven't tried it
>>> for a while). Is there a way to do it with the current matpotlib? (1.4.3)
>>>
>>> Thanks,
>>>
>>> Mark
>>> ------------------------------------------------------------
>>> ------------------
>>> BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT
>>> Develop your own process in accordance with the BPMN 2 standard
>>> Learn Process modeling best practices with Bonita BPM through live
>>> exercises
>>> http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual-
>>> event?utm_
>>> source=Sourceforge_BPM_Camp_5_6_15&utm_medium=email&utm_
>>> campaign=VA_SF_______________________________________________
>>> Matplotlib-users mailing list
>>> Mat...@li...
>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>
>>
>

Thanks, Thomas.

That works indeed, but it doesn't make the figure adjustable, which is what
I wanted (that the physical size of the axes changes while the aspect ratio
is fixed to 1). I guess that functionality has been taken out.

Mark

On Wed, Apr 8, 2015 at 12:50 PM, Thomas Caswell <tca...@gm...> wrote:

> What are the data limits you are using?
>
> I suspect they you are over constraining the system/order of operations
> issue. Try dropping the adjustable setting and pre setting both the data
> limits and the approximate size in figure fraction (ex via grid spec) of
> the axes.
>
> Tom
>
> On Tue, Apr 7, 2015, 15:54 Mark Bakker <ma...@gm...> wrote:
>
>> Hello list,
>>
>> I want to axes above each other. They share the x-axis. The top figure
>> has 'aspect=1' (it is a map), the bottom figure shows a cross-section along
>> a horizontal line on the map, so it doesn't have 'aspect=1'. When I do this
>> with code, for example like this:
>>
>> fig, axes = plt.subplots(nrows=2,sharex=True)
>> plt.setp(axes[0], aspect=1.0, adjustable='box-forced')
>>
>> then the physical size of the top axes is much sorter than the physical
>> size of the bottom axes (although they are poperly linked, as they have the
>> same data limit, and when zooming in the top figure, the bottom figure
>> adjusts). It just looks weird, as the size of the horizontal axis of the
>> bottom figure should have the same physical size as the horizontal axis of
>> the top figure. This used to be possible (a few years ago; haven't tried it
>> for a while). Is there a way to do it with the current matpotlib? (1.4.3)
>>
>> Thanks,
>>
>> Mark
>> ------------------------------------------------------------
>> ------------------
>> BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT
>> Develop your own process in accordance with the BPMN 2 standard
>> Learn Process modeling best practices with Bonita BPM through live
>> exercises
>> http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual-
>> event?utm_
>> source=Sourceforge_BPM_Camp_5_6_15&utm_medium=email&utm_
>> campaign=VA_SF_______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>

What are the data limits you are using?

I suspect they you are over constraining the system/order of operations
issue. Try dropping the adjustable setting and pre setting both the data
limits and the approximate size in figure fraction (ex via grid spec) of
the axes.

Tom

On Tue, Apr 7, 2015, 15:54 Mark Bakker <ma...@gm...> wrote:

> Hello list,
>
> I want to axes above each other. They share the x-axis. The top figure has
> 'aspect=1' (it is a map), the bottom figure shows a cross-section along a
> horizontal line on the map, so it doesn't have 'aspect=1'. When I do this
> with code, for example like this:
>
> fig, axes = plt.subplots(nrows=2,sharex=True)
> plt.setp(axes[0], aspect=1.0, adjustable='box-forced')
>
> then the physical size of the top axes is much sorter than the physical
> size of the bottom axes (although they are poperly linked, as they have the
> same data limit, and when zooming in the top figure, the bottom figure
> adjusts). It just looks weird, as the size of the horizontal axis of the
> bottom figure should have the same physical size as the horizontal axis of
> the top figure. This used to be possible (a few years ago; haven't tried it
> for a while). Is there a way to do it with the current matpotlib? (1.4.3)
>
> Thanks,
>
> Mark
> ------------------------------------------------------------
> ------------------
> BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT
> Develop your own process in accordance with the BPMN 2 standard
> Learn Process modeling best practices with Bonita BPM through live
> exercises
> http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual-
> event?utm_
> source=Sourceforge_BPM_Camp_5_6_15&utm_medium=email&utm_
> campaign=VA_SF_______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

Hi Ryan,
could you write down, as a tutorial, how you built the example with the qt designer?In the last hours I read all most everything what can be found on the issue of getting matplotlib running with pyqt5 and the designer but as you realized yourself, there is little to be found handy.
I'm stuck at a project, which has to use python3, and pyqt5 and am not allowed by my boss to fall back to pyqt4 or qt_compat. He wants to make sure that we use the latest revisions.
So I#m very pleased to read that someone already set food on this terrain. 
Qt5.4.1 is running and I installed PyQtdesingerplugins, in mind that they were written for PyQt4. Are they usable in 5? I added the env-variables to my bashrc, did get any changes shown in the designer. Of course I did a re-log-in to start fresh, but any changes were noteable.What possible ways of embedding matplotlib into a designer base pyqt5-gui else, are there?
cheers,Christian


 --
"A little learning never caused anyone's head to explode!"

"Ein wenig Lernen hat noch niemandens Kopf zum Explodieren gebracht!" 


     On Wednesday, February 18, 2015 11:59 PM, Ryan Nelson <rne...@gm...> wrote:
   

 Hello list,
A couple months ago, I spent quite a bit of time trying to figure out how to use Qt designer create a GUI with an embedded MPL window. Unfortunately, the Scipy cookbook page (http://wiki.scipy.org/Cookbook/Matplotlib/Qt_with_IPython_and_Designer) is very outdated. A recent post (http://matplotlib.1069221.n5.nabble.com/Re-Keep-list-of-figures-or-plots-and-flip-through-list-using-UI-td44961.html) brought up some questions about a use case very similar to mine, so I redid my example and was going to write a quick tutorial for the docs.
Unfortunately, I'm not a Qt guru, so I thought that I would ask on the list for some advice.  The OP and I were both interested in being able to have a list of figures that you could select from to change the plot window. The embedding examples in the docs create subclasses of FigureClass* and embed the plotting figure/axes/etc. This works but gets tricky, though, when trying to switch plots. Also, for interactive IPython work, I didn't like that the plotting objects were mixed in with all the QtGui.QWidget attributes, which makes introspective searching painful. My solution was to create a dictionary of matplotlib.figure.Figure objects that had all of the plotting stuff defined. Then when I select a new plot from the list, the old one is removed and a new FigureClass object is created using the selected Figure object. Has anyone else successfully done something like this? Is there a better way? Also, it seems if I zoom the current plot, change to a new plot, and change back, the zoom region is retained. Anyone know how to reset the zoom region?
Attached is my example: "window.py" is the Designer-created main window and "custommpl.py" is the subclass of the main window that I wrote. It's about as short as I could make it.

Thanks
Ryan


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Hi Jody,

Thank you very much for your help. You are right, this is what I wanted :-)

Cheers,
Markus

On 2015-04-07 23:33, Jody Klymak wrote:
> xerr is +/- relative to the data:
>
> *xerr*/*yerr*: [ scalar | N, Nx1, or 2xN array-like ]
>      If a scalar number, len(N) array-like object, or an Nx1
>      array-like object, errorbars are drawn at +/-value relative
>      to the data.
>
>      If a sequence of shape 2xN, errorbars are drawn at -row1
>      and +row2 relative to the data.
>
> I think you want:
>
> xdat=10**data_x_log
> ax.errorbar(10**data_x_log,data_y,xerr=[xdat-error_x_lower,error_x_upper-xdat],ls='',marker='o')
>
> Cheers,   Jody
>
>> On 7 Apr 2015, at  13:51 PM, Markus Haider <mar...@ui...> wrote:
>>
>> I have the error from a table which is in log units, and the error is
>> given to be symmetric in log space.
>>
>> Cheers,
>> Markus
>>
>> On 2015-04-07 16:40, Yuxiang Wang wrote:
>>> Typo - "standard deviation OR standard error of mean", not "OF".
>>>
>>> Sorry.
>>>
>>> Shawn
>>>
>>>
>>> On Tue, Apr 7, 2015 at 10:39 AM, Yuxiang Wang <yw...@vi...> wrote:
>>>> If you error bars denote standard deviation of standard error of mean,
>>>> shouldn't they be non-symmetric in log scale?
>>>>
>>>> Shawn
>>>>
>>>> On Tue, Apr 7, 2015 at 10:11 AM, Markus Haider <mar...@ui...> wrote:
>>>>> Hi,
>>>>>
>>>>> I am trying to make an errorbar plot with a logarithmic x-axis. I have
>>>>> symmetric errors in logspace, however if I plot them, the errors are not
>>>>> symmetric anymore, as you can see in the enclosed image. Am I
>>>>> misunderstanding something or is this a bug?
>>>>>
>>>>> Thanks for your help,
>>>>> Markus
>>>>>
>>>>> Here the code I used to produce the plot:
>>>>>
>>>>> import matplotlib.pyplot as plt
>>>>>
>>>>> import numpy as np
>>>>>
>>>>> data_x_log = np.array([13.0,15.0])
>>>>>
>>>>> data_y = np.array([0.5,1])
>>>>>
>>>>> error_x_log = np.array([0.5,1.])
>>>>>
>>>>> error_x_lower = 10**(data_x_log-error_x_log)
>>>>>
>>>>> error_x_upper = 10**(data_x_log+error_x_log)
>>>>>
>>>>> fig = plt.figure()
>>>>>
>>>>> ax = fig.add_subplot(111)
>>>>>
>>>>> ax.errorbar(10**data_x_log,data_y,xerr=[error_x_lower,error_x_upper],ls='',marker='o')
>>>>>
>>>>> ax.set_xscale('log')
>>>>>
>>>>> ax.set_xlim([1E11,1E17])
>>>>>
>>>>> ax.set_ylim([0,2])
>>>>>
>>>>> plt.savefig('error.png')
>>>>>
>>>>>
>>>>> ------------------------------------------------------------------------------
>>>>> BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT
>>>>> Develop your own process in accordance with the BPMN 2 standard
>>>>> Learn Process modeling best practices with Bonita BPM through live exercises
>>>>> http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual- event?utm_
>>>>> source=Sourceforge_BPM_Camp_5_6_15&utm_medium=email&utm_campaign=VA_SF
>>>>> _______________________________________________
>>>>> Matplotlib-users mailing list
>>>>> Mat...@li...
>>>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>>>
>>>>
>>>> --
>>>> Yuxiang "Shawn" Wang
>>>> Gerling Research Lab
>>>> University of Virginia
>>>> yw...@vi...
>>>> +1 (434) 284-0836
>>>> https://sites.google.com/a/virginia.edu/yw5aj/
>>>
>>
>> ------------------------------------------------------------------------------
>> BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT
>> Develop your own process in accordance with the BPMN 2 standard
>> Learn Process modeling best practices with Bonita BPM through live exercises
>> http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual- event?utm_
>> source=Sourceforge_BPM_Camp_5_6_15&utm_medium=email&utm_campaign=VA_SF
>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> --
> Jody Klymak
> http://web.uvic.ca/~jklymak/
>
>
>
>
>
>
> ------------------------------------------------------------------------------
> BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT
> Develop your own process in accordance with the BPMN 2 standard
> Learn Process modeling best practices with Bonita BPM through live exercises
> http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual- event?utm_
> source=Sourceforge_BPM_Camp_5_6_15&utm_medium=email&utm_campaign=VA_SF
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users

xerr is +/- relative to the data:

*xerr*/*yerr*: [ scalar | N, Nx1, or 2xN array-like ]
    If a scalar number, len(N) array-like object, or an Nx1
    array-like object, errorbars are drawn at +/-value relative
    to the data.

    If a sequence of shape 2xN, errorbars are drawn at -row1
    and +row2 relative to the data.

I think you want:

xdat=10**data_x_log
ax.errorbar(10**data_x_log,data_y,xerr=[xdat-error_x_lower,error_x_upper-xdat],ls='',marker='o')

Cheers,   Jody

> On 7 Apr 2015, at  13:51 PM, Markus Haider <mar...@ui...> wrote:
> 
> I have the error from a table which is in log units, and the error is 
> given to be symmetric in log space.
> 
> Cheers,
> Markus
> 
> On 2015-04-07 16:40, Yuxiang Wang wrote:
>> Typo - "standard deviation OR standard error of mean", not "OF".
>> 
>> Sorry.
>> 
>> Shawn
>> 
>> 
>> On Tue, Apr 7, 2015 at 10:39 AM, Yuxiang Wang <yw...@vi...> wrote:
>>> If you error bars denote standard deviation of standard error of mean,
>>> shouldn't they be non-symmetric in log scale?
>>> 
>>> Shawn
>>> 
>>> On Tue, Apr 7, 2015 at 10:11 AM, Markus Haider <mar...@ui...> wrote:
>>>> Hi,
>>>> 
>>>> I am trying to make an errorbar plot with a logarithmic x-axis. I have
>>>> symmetric errors in logspace, however if I plot them, the errors are not
>>>> symmetric anymore, as you can see in the enclosed image. Am I
>>>> misunderstanding something or is this a bug?
>>>> 
>>>> Thanks for your help,
>>>> Markus
>>>> 
>>>> Here the code I used to produce the plot:
>>>> 
>>>> import matplotlib.pyplot as plt
>>>> 
>>>> import numpy as np
>>>> 
>>>> data_x_log = np.array([13.0,15.0])
>>>> 
>>>> data_y = np.array([0.5,1])
>>>> 
>>>> error_x_log = np.array([0.5,1.])
>>>> 
>>>> error_x_lower = 10**(data_x_log-error_x_log)
>>>> 
>>>> error_x_upper = 10**(data_x_log+error_x_log)
>>>> 
>>>> fig = plt.figure()
>>>> 
>>>> ax = fig.add_subplot(111)
>>>> 
>>>> ax.errorbar(10**data_x_log,data_y,xerr=[error_x_lower,error_x_upper],ls='',marker='o')
>>>> 
>>>> ax.set_xscale('log')
>>>> 
>>>> ax.set_xlim([1E11,1E17])
>>>> 
>>>> ax.set_ylim([0,2])
>>>> 
>>>> plt.savefig('error.png')
>>>> 
>>>> 
>>>> ------------------------------------------------------------------------------
>>>> BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT
>>>> Develop your own process in accordance with the BPMN 2 standard
>>>> Learn Process modeling best practices with Bonita BPM through live exercises
>>>> http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual- event?utm_
>>>> source=Sourceforge_BPM_Camp_5_6_15&utm_medium=email&utm_campaign=VA_SF
>>>> _______________________________________________
>>>> Matplotlib-users mailing list
>>>> Mat...@li...
>>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>> 
>>> 
>>> 
>>> --
>>> Yuxiang "Shawn" Wang
>>> Gerling Research Lab
>>> University of Virginia
>>> yw...@vi...
>>> +1 (434) 284-0836
>>> https://sites.google.com/a/virginia.edu/yw5aj/
>> 
>> 
> 
> 
> ------------------------------------------------------------------------------
> BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT
> Develop your own process in accordance with the BPMN 2 standard
> Learn Process modeling best practices with Bonita BPM through live exercises
> http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual- event?utm_
> source=Sourceforge_BPM_Camp_5_6_15&utm_medium=email&utm_campaign=VA_SF
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users

--
Jody Klymak    
http://web.uvic.ca/~jklymak/

I have the error from a table which is in log units, and the error is 
given to be symmetric in log space.

Cheers,
Markus

On 2015-04-07 16:40, Yuxiang Wang wrote:
> Typo - "standard deviation OR standard error of mean", not "OF".
>
> Sorry.
>
> Shawn
>
>
> On Tue, Apr 7, 2015 at 10:39 AM, Yuxiang Wang <yw...@vi...> wrote:
>> If you error bars denote standard deviation of standard error of mean,
>> shouldn't they be non-symmetric in log scale?
>>
>> Shawn
>>
>> On Tue, Apr 7, 2015 at 10:11 AM, Markus Haider <mar...@ui...> wrote:
>>> Hi,
>>>
>>> I am trying to make an errorbar plot with a logarithmic x-axis. I have
>>> symmetric errors in logspace, however if I plot them, the errors are not
>>> symmetric anymore, as you can see in the enclosed image. Am I
>>> misunderstanding something or is this a bug?
>>>
>>> Thanks for your help,
>>> Markus
>>>
>>> Here the code I used to produce the plot:
>>>
>>> import matplotlib.pyplot as plt
>>>
>>> import numpy as np
>>>
>>> data_x_log = np.array([13.0,15.0])
>>>
>>> data_y = np.array([0.5,1])
>>>
>>> error_x_log = np.array([0.5,1.])
>>>
>>> error_x_lower = 10**(data_x_log-error_x_log)
>>>
>>> error_x_upper = 10**(data_x_log+error_x_log)
>>>
>>> fig = plt.figure()
>>>
>>> ax = fig.add_subplot(111)
>>>
>>> ax.errorbar(10**data_x_log,data_y,xerr=[error_x_lower,error_x_upper],ls='',marker='o')
>>>
>>> ax.set_xscale('log')
>>>
>>> ax.set_xlim([1E11,1E17])
>>>
>>> ax.set_ylim([0,2])
>>>
>>> plt.savefig('error.png')
>>>
>>>
>>> ------------------------------------------------------------------------------
>>> BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT
>>> Develop your own process in accordance with the BPMN 2 standard
>>> Learn Process modeling best practices with Bonita BPM through live exercises
>>> http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual- event?utm_
>>> source=Sourceforge_BPM_Camp_5_6_15&utm_medium=email&utm_campaign=VA_SF
>>> _______________________________________________
>>> Matplotlib-users mailing list
>>> Mat...@li...
>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>
>>
>>
>> --
>> Yuxiang "Shawn" Wang
>> Gerling Research Lab
>> University of Virginia
>> yw...@vi...
>> +1 (434) 284-0836
>> https://sites.google.com/a/virginia.edu/yw5aj/
>
>

Hello list,

I want to axes above each other. They share the x-axis. The top figure has
'aspect=1' (it is a map), the bottom figure shows a cross-section along a
horizontal line on the map, so it doesn't have 'aspect=1'. When I do this
with code, for example like this:

fig, axes = plt.subplots(nrows=2,sharex=True)
plt.setp(axes[0], aspect=1.0, adjustable='box-forced')

then the physical size of the top axes is much sorter than the physical
size of the bottom axes (although they are poperly linked, as they have the
same data limit, and when zooming in the top figure, the bottom figure
adjusts). It just looks weird, as the size of the horizontal axis of the
bottom figure should have the same physical size as the horizontal axis of
the top figure. This used to be possible (a few years ago; haven't tried it
for a while). Is there a way to do it with the current matpotlib? (1.4.3)

Thanks,

Mark

Hi Tom,

Thanks for your help.

interpolation='nearest' doesn't produce any problems. I'm currently 
using TkAgg, and I checked with a buddy of mine, using MacOSX backend. 
Neither of us see any problems using interpolation='nearest'. He is 
using an older version of MPL which doesn't let him use 
interpolation='none'.

I will ask around to see if anyone can run a few more test cases.

Steven

On 4/7/15 10:39 AM, Thomas Caswell wrote:
> This probably should be made into an issue on github as this is 
> clearly a bug.
>
> On further consideration, the fact that in my example the bad pixels 
> show up only on the edge and are not symmetric makes me think that my 
> original suggestion is wrong.  Does `interpoltation='nearest'` work 
> any better?
>
> I also am not sure that the rasterzation is happening so this may be 
> an issue on the renderer end.
>
> This needs more investigation that I have time for today.
>
> Tom
>
> On Tue, Apr 7, 2015 at 11:02 AM Steven Boada <bo...@ph... 
> <mailto:bo...@ph...>> wrote:
>
>     Thomas,
>
>     Thanks for the smaller example. I would have come up with one, but I
>     wasn't sure what was causing it to begin with.
>
>     Is there anything to be done to prevent this? Just use another
>     backend?
>
>     Steven
>
>     On 4/6/15 8:47 PM, Thomas Caswell wrote:
>     > This is probaly due to issues with not all of the vector backends
>     > supporting alpha gracefully.
>     >
>     > This can be reproduced more simply by
>     >
>     > x, y = np.ogrid[-5:5:.1, -5:5:.1]
>     > dd = np.exp(-(x**2 + y**2))
>     > dd[dd < .1] = np.nan
>     >
>     > fig, ax = plt.subplots()
>     > ax.imshow(dd, interpolation='none', cmap='gray_r')
>     > plt.savefig('test.pdf')
>     >
>     > @steven In the future it is best to report bugs with minimal
>     > copy-paste able examples.
>     >
>     > On Mon, Apr 6, 2015 at 5:41 PM Steven Boada
>     <bo...@ph... <mailto:bo...@ph...>
>     > <mailto:bo...@ph... <mailto:bo...@ph...>>>
>     wrote:
>     >
>     >     Getting some strange artifacts when I save a figure as a PDF in
>     >     matplotlib. Here are some screen shots. PDF
>     >     <http://imgur.com/oQDXkWn> and PNG
>     <http://imgur.com/bCw3Fn4>. Any
>     >     idea why that is happening?
>     >
>     >     Here is (most of) the source code that makes the plot. I
>     stripped
>     >     out the data generation, because it is long and involved, and
>     >     doesn't really matter. Basically what the script is supposed
>     to do
>     >     is make a scatter plot where the density is below some
>     threshold,
>     >     and a 2d histogram when it is above that threshold. The code
>     seems
>     >     to work fine, but when I save the figure (using savefig in
>     >     Ipython) it shows up funny.
>     >
>     >     Thanks.
>     >
>     >         import pylab as pyl
>     >
>     >         bins = [50,50]
>     >         thresh = 3
>     >
>     >         xdat = #generate or load some data
>     >         ydat = #generate or load some data
>     >
>     >         hh, locx, locy = pyl.histogram2d(xdat, ydat,
>     >     range=[[-1,4],[-26,-10]], bins=bins)
>     >         posx = pyl.digitize(xdat, locx)
>     >         posy = pyl.digitize(ydat, locy)
>     >
>     >         # finds the bins which contain points. posx = 0 for points
>     >     outside "range"
>     >         ind = (posx > 0) & (posx <= bins[0]) & (posy > 0) & (posy <=
>     >     bins[1])
>     >         # values of histogram with points in the bins.
>     >         hhsub = hh[posx[ind] - 1, posy[ind] - 1]
>     >
>     >         xdat1 = xdat[ind][hhsub < thresh] # low density points
>     >         ydat1 = ydat[ind][hhsub < thresh]
>     >         hh[hh < thresh] = pyl.nan # fill the areas with low
>     density by
>     >     NaNs
>     >
>     >         pyl.scatter(xdat1, ydat1, s=20, c='0.8')
>     >         pyl.imshow(pyl.log10(hh.T), cmap='gray_r',
>     >             extent=pyl.array([[-1,4],[-26,-10]]).flatten(),
>     >     interpolation='none')
>     >
>     >         pyl.show()
>     >
>     >     --
>     >
>     >     Steven Boada
>     >
>     >     Doctoral Student
>     >     Dept of Physics and Astronomy
>     >     Texas A&M University
>     > bo...@ph... <mailto:bo...@ph...>
>     <mailto:bo...@ph... <mailto:bo...@ph...>>
>     >
>     >   
>      ------------------------------------------------------------------------------
>     >     BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT
>     >     Develop your own process in accordance with the BPMN 2 standard
>     >     Learn Process modeling best practices with Bonita BPM
>     through live
>     >     exercises
>     > http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual-
>     >     event?utm_
>     >   
>      source=Sourceforge_BPM_Camp_5_6_15&utm_medium=email&utm_campaign=VA_SF_______________________________________________
>     >     Matplotlib-users mailing list
>     > Mat...@li...
>     <mailto:Mat...@li...>
>     >     <mailto:Mat...@li...
>     <mailto:Mat...@li...>>
>     > https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>     >
>
>     --
>
>     Steven Boada
>
>     Doctoral Student
>     Dept of Physics and Astronomy
>     Texas A&M University
>     bo...@ph... <mailto:bo...@ph...>
>
>
>     ------------------------------------------------------------------------------
>     BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT
>     Develop your own process in accordance with the BPMN 2 standard
>     Learn Process modeling best practices with Bonita BPM through live
>     exercises
>     http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual-
>     event?utm_
>     source=Sourceforge_BPM_Camp_5_6_15&utm_medium=email&utm_campaign=VA_SF
>     _______________________________________________
>     Matplotlib-users mailing list
>     Mat...@li...
>     <mailto:Mat...@li...>
>     https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

-- 

Steven Boada

Doctoral Student
Dept of Physics and Astronomy
Texas A&M University
bo...@ph...

This probably should be made into an issue on github as this is clearly a
bug.

On further consideration, the fact that in my example the bad pixels show
up only on the edge and are not symmetric makes me think that my original
suggestion is wrong.  Does `interpoltation='nearest'` work any better?

I also am not sure that the rasterzation is happening so this may be an
issue on the renderer end.

This needs more investigation that I have time for today.

Tom

On Tue, Apr 7, 2015 at 11:02 AM Steven Boada <bo...@ph...> wrote:

> Thomas,
>
> Thanks for the smaller example. I would have come up with one, but I
> wasn't sure what was causing it to begin with.
>
> Is there anything to be done to prevent this? Just use another backend?
>
> Steven
>
> On 4/6/15 8:47 PM, Thomas Caswell wrote:
> > This is probaly due to issues with not all of the vector backends
> > supporting alpha gracefully.
> >
> > This can be reproduced more simply by
> >
> > x, y = np.ogrid[-5:5:.1, -5:5:.1]
> > dd = np.exp(-(x**2 + y**2))
> > dd[dd < .1] = np.nan
> >
> > fig, ax = plt.subplots()
> > ax.imshow(dd, interpolation='none', cmap='gray_r')
> > plt.savefig('test.pdf')
> >
> > @steven In the future it is best to report bugs with minimal
> > copy-paste able examples.
> >
> > On Mon, Apr 6, 2015 at 5:41 PM Steven Boada <bo...@ph...
> > <mailto:bo...@ph...>> wrote:
> >
> >     Getting some strange artifacts when I save a figure as a PDF in
> >     matplotlib. Here are some screen shots. PDF
> >     <http://imgur.com/oQDXkWn> and PNG <http://imgur.com/bCw3Fn4>. Any
> >     idea why that is happening?
> >
> >     Here is (most of) the source code that makes the plot. I stripped
> >     out the data generation, because it is long and involved, and
> >     doesn't really matter. Basically what the script is supposed to do
> >     is make a scatter plot where the density is below some threshold,
> >     and a 2d histogram when it is above that threshold. The code seems
> >     to work fine, but when I save the figure (using savefig in
> >     Ipython) it shows up funny.
> >
> >     Thanks.
> >
> >         import pylab as pyl
> >
> >         bins = [50,50]
> >         thresh = 3
> >
> >         xdat = #generate or load some data
> >         ydat = #generate or load some data
> >
> >         hh, locx, locy = pyl.histogram2d(xdat, ydat,
> >     range=[[-1,4],[-26,-10]], bins=bins)
> >         posx = pyl.digitize(xdat, locx)
> >         posy = pyl.digitize(ydat, locy)
> >
> >         # finds the bins which contain points. posx = 0 for points
> >     outside "range"
> >         ind = (posx > 0) & (posx <= bins[0]) & (posy > 0) & (posy <=
> >     bins[1])
> >         # values of histogram with points in the bins.
> >         hhsub = hh[posx[ind] - 1, posy[ind] - 1]
> >
> >         xdat1 = xdat[ind][hhsub < thresh] # low density points
> >         ydat1 = ydat[ind][hhsub < thresh]
> >         hh[hh < thresh] = pyl.nan # fill the areas with low density by
> >     NaNs
> >
> >         pyl.scatter(xdat1, ydat1, s=20, c='0.8')
> >         pyl.imshow(pyl.log10(hh.T), cmap='gray_r',
> >             extent=pyl.array([[-1,4],[-26,-10]]).flatten(),
> >     interpolation='none')
> >
> >         pyl.show()
> >
> >     --
> >
> >     Steven Boada
> >
> >     Doctoral Student
> >     Dept of Physics and Astronomy
> >     Texas A&M University
> >     bo...@ph...  <mailto:bo...@ph...>
> >
> >     ------------------------------------------------------------
> ------------------
> >     BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT
> >     Develop your own process in accordance with the BPMN 2 standard
> >     Learn Process modeling best practices with Bonita BPM through live
> >     exercises
> >     http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual-
> >     event?utm_
> >     source=Sourceforge_BPM_Camp_5_6_15&utm_medium=email&utm_
> campaign=VA_SF_______________________________________________
> >     Matplotlib-users mailing list
> >     Mat...@li...
> >     <mailto:Mat...@li...>
> >     https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> >
>
> --
>
> Steven Boada
>
> Doctoral Student
> Dept of Physics and Astronomy
> Texas A&M University
> bo...@ph...
>
>
> ------------------------------------------------------------
> ------------------
> BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT
> Develop your own process in accordance with the BPMN 2 standard
> Learn Process modeling best practices with Bonita BPM through live
> exercises
> http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual-
> event?utm_
> source=Sourceforge_BPM_Camp_5_6_15&utm_medium=email&utm_campaign=VA_SF
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

Thomas,

Thanks for the smaller example. I would have come up with one, but I 
wasn't sure what was causing it to begin with.

Is there anything to be done to prevent this? Just use another backend?

Steven

On 4/6/15 8:47 PM, Thomas Caswell wrote:
> This is probaly due to issues with not all of the vector backends 
> supporting alpha gracefully.
>
> This can be reproduced more simply by
>
> x, y = np.ogrid[-5:5:.1, -5:5:.1]
> dd = np.exp(-(x**2 + y**2))
> dd[dd < .1] = np.nan
>
> fig, ax = plt.subplots()
> ax.imshow(dd, interpolation='none', cmap='gray_r')
> plt.savefig('test.pdf')
>
> @steven In the future it is best to report bugs with minimal 
> copy-paste able examples.
>
> On Mon, Apr 6, 2015 at 5:41 PM Steven Boada <bo...@ph... 
> <mailto:bo...@ph...>> wrote:
>
>     Getting some strange artifacts when I save a figure as a PDF in
>     matplotlib. Here are some screen shots. PDF
>     <http://imgur.com/oQDXkWn> and PNG <http://imgur.com/bCw3Fn4>. Any
>     idea why that is happening?
>
>     Here is (most of) the source code that makes the plot. I stripped
>     out the data generation, because it is long and involved, and
>     doesn't really matter. Basically what the script is supposed to do
>     is make a scatter plot where the density is below some threshold,
>     and a 2d histogram when it is above that threshold. The code seems
>     to work fine, but when I save the figure (using savefig in
>     Ipython) it shows up funny.
>
>     Thanks.
>
>         import pylab as pyl
>
>         bins = [50,50]
>         thresh = 3
>
>         xdat = #generate or load some data
>         ydat = #generate or load some data
>
>         hh, locx, locy = pyl.histogram2d(xdat, ydat,
>     range=[[-1,4],[-26,-10]], bins=bins)
>         posx = pyl.digitize(xdat, locx)
>         posy = pyl.digitize(ydat, locy)
>
>         # finds the bins which contain points. posx = 0 for points
>     outside "range"
>         ind = (posx > 0) & (posx <= bins[0]) & (posy > 0) & (posy <=
>     bins[1])
>         # values of histogram with points in the bins.
>         hhsub = hh[posx[ind] - 1, posy[ind] - 1]
>
>         xdat1 = xdat[ind][hhsub < thresh] # low density points
>         ydat1 = ydat[ind][hhsub < thresh]
>         hh[hh < thresh] = pyl.nan # fill the areas with low density by
>     NaNs
>
>         pyl.scatter(xdat1, ydat1, s=20, c='0.8')
>         pyl.imshow(pyl.log10(hh.T), cmap='gray_r',
>             extent=pyl.array([[-1,4],[-26,-10]]).flatten(),
>     interpolation='none')
>
>         pyl.show()
>
>     -- 
>
>     Steven Boada
>
>     Doctoral Student
>     Dept of Physics and Astronomy
>     Texas A&M University
>     bo...@ph...  <mailto:bo...@ph...>
>
>     ------------------------------------------------------------------------------
>     BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT
>     Develop your own process in accordance with the BPMN 2 standard
>     Learn Process modeling best practices with Bonita BPM through live
>     exercises
>     http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual-
>     event?utm_
>     source=Sourceforge_BPM_Camp_5_6_15&utm_medium=email&utm_campaign=VA_SF_______________________________________________
>     Matplotlib-users mailing list
>     Mat...@li...
>     <mailto:Mat...@li...>
>     https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

-- 

Steven Boada

Doctoral Student
Dept of Physics and Astronomy
Texas A&M University
bo...@ph...

Typo - "standard deviation OR standard error of mean", not "OF".

Sorry.

Shawn


On Tue, Apr 7, 2015 at 10:39 AM, Yuxiang Wang <yw...@vi...> wrote:
> If you error bars denote standard deviation of standard error of mean,
> shouldn't they be non-symmetric in log scale?
>
> Shawn
>
> On Tue, Apr 7, 2015 at 10:11 AM, Markus Haider <mar...@ui...> wrote:
>> Hi,
>>
>> I am trying to make an errorbar plot with a logarithmic x-axis. I have
>> symmetric errors in logspace, however if I plot them, the errors are not
>> symmetric anymore, as you can see in the enclosed image. Am I
>> misunderstanding something or is this a bug?
>>
>> Thanks for your help,
>> Markus
>>
>> Here the code I used to produce the plot:
>>
>> import matplotlib.pyplot as plt
>>
>> import numpy as np
>>
>> data_x_log = np.array([13.0,15.0])
>>
>> data_y = np.array([0.5,1])
>>
>> error_x_log = np.array([0.5,1.])
>>
>> error_x_lower = 10**(data_x_log-error_x_log)
>>
>> error_x_upper = 10**(data_x_log+error_x_log)
>>
>> fig = plt.figure()
>>
>> ax = fig.add_subplot(111)
>>
>> ax.errorbar(10**data_x_log,data_y,xerr=[error_x_lower,error_x_upper],ls='',marker='o')
>>
>> ax.set_xscale('log')
>>
>> ax.set_xlim([1E11,1E17])
>>
>> ax.set_ylim([0,2])
>>
>> plt.savefig('error.png')
>>
>>
>> ------------------------------------------------------------------------------
>> BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT
>> Develop your own process in accordance with the BPMN 2 standard
>> Learn Process modeling best practices with Bonita BPM through live exercises
>> http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual- event?utm_
>> source=Sourceforge_BPM_Camp_5_6_15&utm_medium=email&utm_campaign=VA_SF
>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>
>
>
> --
> Yuxiang "Shawn" Wang
> Gerling Research Lab
> University of Virginia
> yw...@vi...
> +1 (434) 284-0836
> https://sites.google.com/a/virginia.edu/yw5aj/



-- 
Yuxiang "Shawn" Wang
Gerling Research Lab
University of Virginia
yw...@vi...
+1 (434) 284-0836
https://sites.google.com/a/virginia.edu/yw5aj/

If you error bars denote standard deviation of standard error of mean,
shouldn't they be non-symmetric in log scale?

Shawn

On Tue, Apr 7, 2015 at 10:11 AM, Markus Haider <mar...@ui...> wrote:
> Hi,
>
> I am trying to make an errorbar plot with a logarithmic x-axis. I have
> symmetric errors in logspace, however if I plot them, the errors are not
> symmetric anymore, as you can see in the enclosed image. Am I
> misunderstanding something or is this a bug?
>
> Thanks for your help,
> Markus
>
> Here the code I used to produce the plot:
>
> import matplotlib.pyplot as plt
>
> import numpy as np
>
> data_x_log = np.array([13.0,15.0])
>
> data_y = np.array([0.5,1])
>
> error_x_log = np.array([0.5,1.])
>
> error_x_lower = 10**(data_x_log-error_x_log)
>
> error_x_upper = 10**(data_x_log+error_x_log)
>
> fig = plt.figure()
>
> ax = fig.add_subplot(111)
>
> ax.errorbar(10**data_x_log,data_y,xerr=[error_x_lower,error_x_upper],ls='',marker='o')
>
> ax.set_xscale('log')
>
> ax.set_xlim([1E11,1E17])
>
> ax.set_ylim([0,2])
>
> plt.savefig('error.png')
>
>
> ------------------------------------------------------------------------------
> BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT
> Develop your own process in accordance with the BPMN 2 standard
> Learn Process modeling best practices with Bonita BPM through live exercises
> http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual- event?utm_
> source=Sourceforge_BPM_Camp_5_6_15&utm_medium=email&utm_campaign=VA_SF
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>



-- 
Yuxiang "Shawn" Wang
Gerling Research Lab
University of Virginia
yw...@vi...
+1 (434) 284-0836
https://sites.google.com/a/virginia.edu/yw5aj/

Hi,

I am trying to make an errorbar plot with a logarithmic x-axis. I have 
symmetric errors in logspace, however if I plot them, the errors are not 
symmetric anymore, as you can see in the enclosed image. Am I 
misunderstanding something or is this a bug?

Thanks for your help,
Markus

Here the code I used to produce the plot:

import matplotlib.pyplot as plt

import numpy as np

data_x_log = np.array([13.0,15.0])

data_y = np.array([0.5,1])

error_x_log = np.array([0.5,1.])

error_x_lower = 10**(data_x_log-error_x_log)

error_x_upper = 10**(data_x_log+error_x_log)

fig = plt.figure()

ax = fig.add_subplot(111)

ax.errorbar(10**data_x_log,data_y,xerr=[error_x_lower,error_x_upper],ls='',marker='o')

ax.set_xscale('log')

ax.set_xlim([1E11,1E17])

ax.set_ylim([0,2])

plt.savefig('error.png')

Dear All,

I have made a post on Stackoverflow that has not garnered any help so far,
and I'm drawing this to your attention here because it seems like this could
be a bug:

http://stackoverflow.com/questions/29469179/potential-bug-in-either-matplotlib-or-pandas


Please look at my post, and I would greatly appreciate any help! I'm do
puzzled by that behavior!

Thank you.



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View this message in context: http://matplotlib.1069221.n5.nabble.com/Perplexing-behavior-from-combined-use-of-Matplotlib-and-pandas-tp45345.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

This is probaly due to issues with not all of the vector backends
supporting alpha gracefully.

This can be reproduced more simply by

x, y = np.ogrid[-5:5:.1, -5:5:.1]
dd = np.exp(-(x**2 + y**2))
dd[dd < .1] = np.nan

fig, ax = plt.subplots()
ax.imshow(dd, interpolation='none', cmap='gray_r')
plt.savefig('test.pdf')

@steven In the future it is best to report bugs with minimal copy-paste
able examples.

On Mon, Apr 6, 2015 at 5:41 PM Steven Boada <bo...@ph...> wrote:

>  Getting some strange artifacts when I save a figure as a PDF in
> matplotlib. Here are some screen shots. PDF <http://imgur.com/oQDXkWn>
> and PNG <http://imgur.com/bCw3Fn4>.  Any idea why that is happening?
>
> Here is (most of) the source code that makes the plot. I stripped out the
> data generation, because it is long and involved, and doesn't really
> matter. Basically what the script is supposed to do is make a scatter plot
> where the density is below some threshold, and a 2d histogram when it is
> above that threshold. The code seems to work fine, but when I save the
> figure (using savefig in Ipython) it shows up funny.
>
> Thanks.
>
>     import pylab as pyl
>
>     bins = [50,50]
>     thresh = 3
>
>     xdat = #generate or load some data
>     ydat = #generate or load some data
>
>     hh, locx, locy = pyl.histogram2d(xdat, ydat, range=[[-1,4],[-26,-10]],
> bins=bins)
>     posx = pyl.digitize(xdat, locx)
>     posy = pyl.digitize(ydat, locy)
>
>     # finds the bins which contain points. posx = 0 for points outside
> "range"
>     ind = (posx > 0) & (posx <= bins[0]) & (posy > 0) & (posy <= bins[1])
>     # values of histogram with points in the bins.
>     hhsub = hh[posx[ind] - 1, posy[ind] - 1]
>
>     xdat1 = xdat[ind][hhsub < thresh] # low density points
>     ydat1 = ydat[ind][hhsub < thresh]
>     hh[hh < thresh] = pyl.nan # fill the areas with low density by NaNs
>
>     pyl.scatter(xdat1, ydat1, s=20, c='0.8')
>     pyl.imshow(pyl.log10(hh.T), cmap='gray_r',
>         extent=pyl.array([[-1,4],[-26,-10]]).flatten(),
> interpolation='none')
>
>     pyl.show()
>
> --
>
> Steven Boada
>
> Doctoral Student
> Dept of Physics and Astronomy
> Texas A&M Uni...@ph...
>
>  ------------------------------------------------------------
> ------------------
> BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT
> Develop your own process in accordance with the BPMN 2 standard
> Learn Process modeling best practices with Bonita BPM through live
> exercises
> http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual-
> event?utm_
> source=Sourceforge_BPM_Camp_5_6_15&utm_medium=email&utm_
> campaign=VA_SF_______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

Getting some strange artifacts when I save a figure as a PDF in 
matplotlib. Here are some screen shots. PDF <http://imgur.com/oQDXkWn> 
and PNG <http://imgur.com/bCw3Fn4>.  Any idea why that is happening?

Here is (most of) the source code that makes the plot. I stripped out 
the data generation, because it is long and involved, and doesn't really 
matter. Basically what the script is supposed to do is make a scatter 
plot where the density is below some threshold, and a 2d histogram when 
it is above that threshold. The code seems to work fine, but when I save 
the figure (using savefig in Ipython) it shows up funny.

Thanks.

     import pylab as pyl

     bins = [50,50]
     thresh = 3

     xdat = #generate or load some data
     ydat = #generate or load some data

     hh, locx, locy = pyl.histogram2d(xdat, ydat, 
range=[[-1,4],[-26,-10]], bins=bins)
     posx = pyl.digitize(xdat, locx)
     posy = pyl.digitize(ydat, locy)

     # finds the bins which contain points. posx = 0 for points outside 
"range"
     ind = (posx > 0) & (posx <= bins[0]) & (posy > 0) & (posy <= bins[1])
     # values of histogram with points in the bins.
     hhsub = hh[posx[ind] - 1, posy[ind] - 1]

     xdat1 = xdat[ind][hhsub < thresh] # low density points
     ydat1 = ydat[ind][hhsub < thresh]
     hh[hh < thresh] = pyl.nan # fill the areas with low density by NaNs

     pyl.scatter(xdat1, ydat1, s=20, c='0.8')
     pyl.imshow(pyl.log10(hh.T), cmap='gray_r',
         extent=pyl.array([[-1,4],[-26,-10]]).flatten(), 
interpolation='none')

     pyl.show()

-- 

Steven Boada

Doctoral Student
Dept of Physics and Astronomy
Texas A&M University
bo...@ph...

The second example on
http://matplotlib.org/examples/pylab_examples/zorder_demo.html seems to
expose a bug, which is clearly visible in the vector version:

The blue curve with zorder=2 is plotted below the frame and all others with
zorder >= 3 are plotted above the frame. This is because the frame zorder is
hardcoded to be 2.5. This behaviour is certainly unexpected by most users.
How can one modify the mutual zorder of lines without conflicting with
standard axis elements?



--
View this message in context: http://matplotlib.1069221.n5.nabble.com/bug-in-zorder-example-tp45342.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

INTRO
=====

please consider the following code (I'm trying to draw a timeline)

1 from matplotlib import pyplot, patches
2 fig = pyplot.figure()
3 ax = fig.add_subplot('111')
4 ax.add_patch(patches.Rectangle((1933,0.25), 73, 0.5))
5 pyplot.show()

that gives me a plot with the x axis that goes from 0.0 to 1.0,
now consider

  ...
5 ax.set_xlim((1933,1933+73))
6 pyplot.show()

this gives me an x axis that goes _exactly_ from 1933 to 2006,
eventually drawing a line superposed to the lower spine

  ...
5 ax.plot((1933,1933+73),(0,0))
6 pyplot.show()

gives me what I really want, that is an x axis running from 1930 to
2010, with the limits automatically rounded by matplotlib...

(I noted that the extra line forces a rounding also for the y axis
limits, but that's not a problem...)

QUESTION
========

I want matplotlib to round the limits of the x axis automatically,
when given explicitly the lower and upper limits of the data, how to?

Thank you in advance

-- 
"We have met the enemy and he is us."
                                                        --- Pogo.

Hey Julian,

I'm not familiar enough from gridspec to help, but your emails were
received by the list.

If no one on the list has (time to write) a response, I would recommend
making your example a little more reproducible (e.g., what are a and b?)
and posting it on stackoverflow.


On Fri, Apr 3, 2015 at 1:11 PM, Julian Irwin <jul...@gm...> wrote:

> Hey,
>
> Just checking if I sent this out properly. Can someone reply to let me
> know that this was seen, even if you don't have an answer?
>
> Thanks,
> Julian
>
> On Mon, Mar 30, 2015 at 10:10 PM, Julian Irwin <jul...@gm...>
> wrote:
>
>> Hey,
>>
>> I am making a plot using nested GridSpec objects. I would like to adjust
>> the space between the the different GridSpecs.
>>
>> This works fine if I do something like:
>>
>> gs0 = gridspec.GridSpec(a, b)
>> gs1 = gridspec.GridSpec(c, d)
>>
>> gs0.update(...)
>> gs1.update(...)
>>
>>
>> However, If I use GridSpecFromSubplotSpec to make the gridspec-like
>> objects, this update() method is not provided:
>>
>> root_gs = gridspec.GridSpec(2, 1)
>>
>> gs0 = gridspec.GridSpecFromSubplotSpec(a, b, root_gs[0])
>> gs1 = gridspec.GridSpecFromSubplotSpec(c, d, root_gs[1])
>>
>> gs0.update() #not a method!!
>>
>> I probed around in gs0.__dict__ and dir(gs0) but I couldn't find the
>> right attributes...Can anyone suggest a solutions or a workaround?
>>
>> Thanks!
>> Julian
>>
>>
>
>
> ------------------------------------------------------------------------------
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>