matplotlib-users Mailing List for matplotlib

Oops, one thing about the graph that I forgot to point out...does the
antialiasing look a little funny?  It seems a bit inconsistent, especially
as the line goes flat.  I increased the line width in an effort to make it
less obvious;  is there some other way to improve this behavior?

> -----Original Message-----
> From: Moore, Eric (NIH/NIDDK) [F]
> Sent: Monday, March 19, 2012 1:48 PM
> To: matplotlib-users
> Subject: Re: [Matplotlib-users] xticks when using twinx()
> 
> Mario,
> 
> When you call fig.add_subplot as you are doing, ax1 is None.  I'm not
> sure why, but you don't need to set the xticks there anyway. Change
> your call to be ax1 = fig.add_subplot(111) that way ax1 != None.  Then
> plot, create ax2, plot.  You can then set the xticks by calling
> ax1.set_xticks([10,40,90]) or equivalently ax2.set_xticks([10,40,90]).
> 
> Eric
> 


Looking at the code for Figure.add_subplot in figure.py, the first line is:

if not len(args): return

Why just silently fail if no position arguments are passed?  At the very least shouldn't this print an error message?  I'm not sure that I understand the rational for just swallowing an error this way.  Anyone know why it does this?

Eric

I'm trying to make a rectangle that "highlights" a straight line of markers
such that:

1) it surrounds/contains the points, basically like:

--------------------------------------------------------------------------------------
|
  |
|       O                    O                   O                  O
         |
|
   |
|-------------------------------------------------------------------------------------

2) its height doesn't change with zoom.  (it should always be approximately
a little taller than the height of the markers' heights).

I can do (1) but so far not (2).  I'm pretty sure I need to use a blended
transform for this somehow....and possibly TransformedPath, but I'm lost as
to how to do this.

Thanks,
Che

On Tue, Mar 20, 2012 at 5:27 AM, kususe <ku...@in...> wrote:
>
> If I set the parameter "transparent" in the "savefig" function, more line are
> plotted out on the same figure, when I use the subplot function too.
> If I don't set it, all works well.
> Suggestions?

I don't follow what you're saying very well. Can you provide a minimal
and complete example to demonstrate this behavior.

Thanks,
-paul

On Tuesday, March 20, 2012, Julien Rebetez <jul...@gm...> wrote:
> Thank you for your answer.
>
> I've read the numpy tutorial and I get it that array and matrices
> behave differently.
>
> Now, what I find kind of strange is that the plot I get when directly
> feeding the matrices to scatter
> doesn't really seem to represent anything.
> I think that, if possible, showing an error or a warning would be much
> more appropriate than showing
> a plot. It would let the user know that the problem is not with her
> dataset, but with the plot.
>
> Wouldn't it be possible to simply check the shape in scatter() and
> display a warning if it has more than one dimension ?
>
> Best,
> Julien

I think this is more of an issue that we simply never tested for matrices.
 As for the shape tests, scatter can take 2d arrays, iirc, with each column
being a different color. (again, all from my memory, which would easily
fail memcheck).

Ben Root

Hi all,

There are a couple of properties I'd like my plot axes to have by default (tick2On=False for the x and ytics, and having no 'right' or 'top' spines). These seem a bit obscure to put into the rcparams, but it would be nice to not have to call some function to fix this up every time I make a new set of axes.

Is there a good way to get this to happen automatically? Some sort of callback I can register? Or would I need to subclass Axes and monkeypatch that in as the default or something?

Any suggestions welcome!

Zach

Thank you for your answer.

I've read the numpy tutorial and I get it that array and matrices
behave differently.

Now, what I find kind of strange is that the plot I get when directly
feeding the matrices to scatter
doesn't really seem to represent anything.
I think that, if possible, showing an error or a warning would be much
more appropriate than showing
a plot. It would let the user know that the problem is not with her
dataset, but with the plot.

Wouldn't it be possible to simply check the shape in scatter() and
display a warning if it has more than one dimension ?

Best,
Julien

On Tue, Mar 20, 2012 at 3:52 PM, Jerzy Karczmarczuk
<jer...@un...> wrote:
> LJulien Rebetez :
>> I've run into a strange behaviour of matplotlib while trying to figure
>> out why my data was displayed incorrectly.
>> I'm note quite sure if this is a bug or expected behaviour, but I feel
>> it's kind of counter-intuitive, so I'm posting here.
>>
>> ...
>> Now there seem to be a difference on how numpy handles A[:,0]
>> depending on if A is a np.array or np.matrix. In the case of
>> an array, a 1D array is returned, in the case of a matrix, a 2D Nx1
>> matrix is returned. Using this matrix seems to confuse matplotlib.
>>
>> Using np.ravel or np.flatten on the slices fix that problem.
>>
>> Is there an explanation for this behaviour or should I fill a bug ?
> Don't fill a bug.
> Read  http://www.scipy.org/Tentative_NumPy_Tutorial , please.
> They explain that a slice of a matrix is a matrix, and its "view" is
> different from what you get for arrays.
>
> But, no need to reshape the stuff. Just use the "array attribute" of the
> matrix :
>
> pl.scatter(B.A[:,0], B.A[:,1], c='b')
>
> //Here 'A' is the name of the attribute, nothing to do with your array
> A; by chance it is the same...//
>
>
> The best
>
> Jerzy Karczmarczuk
>
>
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LJulien Rebetez :
> I've run into a strange behaviour of matplotlib while trying to figure
> out why my data was displayed incorrectly.
> I'm note quite sure if this is a bug or expected behaviour, but I feel
> it's kind of counter-intuitive, so I'm posting here.
>
> ...
> Now there seem to be a difference on how numpy handles A[:,0]
> depending on if A is a np.array or np.matrix. In the case of
> an array, a 1D array is returned, in the case of a matrix, a 2D Nx1
> matrix is returned. Using this matrix seems to confuse matplotlib.
>
> Using np.ravel or np.flatten on the slices fix that problem.
>
> Is there an explanation for this behaviour or should I fill a bug ?
Don't fill a bug.
Read  http://www.scipy.org/Tentative_NumPy_Tutorial , please.
They explain that a slice of a matrix is a matrix, and its "view" is 
different from what you get for arrays.

But, no need to reshape the stuff. Just use the "array attribute" of the 
matrix :

pl.scatter(B.A[:,0], B.A[:,1], c='b')

//Here 'A' is the name of the attribute, nothing to do with your array 
A; by chance it is the same...//


The best

Jerzy Karczmarczuk

On Mon, Mar 19, 2012 at 5:28 PM, questions anon <que...@gm...>wrote:

> So when I add "np.logical_or" to the beginning of the script it makes no
> difference to the error message that I receive.
>
> I have tried reshaping the array but I receive an error message of:
> Traceback (most recent call last):
>   File "<pyshell#0>", line 1, in <module>
>     f.reshape(691,886)
> ValueError: total size of new array must be unchanged
>
> Is there a way to use np.genfromtxt and define the rows and columns on
> import?
>
> Thanks
>
>
I think you have two completely separate problems.  They are completely
unrelated to each other.  The np.logical_or() issue happens within Basemap
while your np.genfromtext() happens in your module.  For the
np.logical_or() issue, I suspect that there is something wrong with your
installation (maybe EPD is conflicting with a pre-existing python
install?).  As for np.genfromtext(), I would put the code back to the way
it was before (the original call looked right to me).

Ben Root

Hello,
I've run into a strange behaviour of matplotlib while trying to figure
out why my data was displayed incorrectly.
I'm note quite sure if this is a bug or expected behaviour, but I feel
it's kind of counter-intuitive, so I'm posting here.

The attached python script does a scatter plot of some data. I'm using
the first column as the x coordinates and the second as
y. Looking at the matrix (x == y), I'd expect the three data point to
be on a diagonal line.

Now there seem to be a difference on how numpy handles A[:,0]
depending on if A is a np.array or np.matrix. In the case of
an array, a 1D array is returned, in the case of a matrix, a 2D Nx1
matrix is returned. Using this matrix seems to confuse matplotlib.

Using np.ravel or np.flatten on the slices fix that problem.

Is there an explanation for this behaviour or should I fill a bug ?

Best regards,
Julien Rebetez

If I set the parameter "transparent" in the "savefig" function, more line are
plotted out on the same figure, when I use the subplot function too. 
If I don't set it, all works well. 
Suggestions?

thanks in advance, 
K.
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I'd like to save an image with sole the graph. 
I set up  

ax.set_xticklabels([]) 
ax.set_frame_on(False) 

but I get an image with tra graph and some lines on the frame level, wich I
wanna remove. 
I attach the image to be more understandable (I circle in red what I'd like
to get off).
Suggestions??

Thanks in advance
http://old.nabble.com/file/p33537650/geo.png 
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Worked out. 
Thanks. 


Paul Hobson-2 wrote:
> 
> Sorry...That first line should be:
> fig, axes = plt.subplots(ncols=3)  # note: subplotS not subplot
> 
> On Mon, Mar 19, 2012 at 5:45 PM, Paul Hobson <pmh...@gm...> wrote:
>> Try it like this:
>>
>>               fig, axes = plt.subplots(3,1,1)
>>               ax1, ax2, ax3 = axes
>>               p1, = ax1.plot(self.data0,self.data1)
>>               p2, = ax2.plot(self.data0,self.data2)
>>               p3, = ax3.plot(self.data0,self.data4)
>>               for ax in axes:
>>                       ax.set_xticks([])
>>
>> -paul
> 
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> 

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The normal shape of a figure is a rectangle. But how can I create a oblique
figure, i.e. with side length not perpendicular each other. Thanks!

-- 
*Yi-Xin Liu, PHD*
*Department of Macromolecular Science*
*Fudan University*
*Room 415, Yuejing Building *
*Handan Rd. 220, **Shanghai, China*
*Tel +86-021-65642863*
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Hi Mike,

On 03/19/2012 06:53 PM, Michael Droettboom wrote:
> What are you using to view the SVG?  This works for me in Inkscape,
> Firefox and Google Chrome, but fails using rsvg 2.34 (which is used by
> ImageMagick and emacs, for example).  It seems that rsvg doesn't like
> the clip path to appear after the object that uses it, even though this
> is allowed by the SVG spec.  SVG compliance is pretty spotty between
> different renderers, but I generally think rsvg is one of the worst.
thanks for the fast reply. actually i was using geeqie and i looks like
it is using a bad renderer. i am now using inkscape to render my svg
(not just for editing) and so far it do what i need it to do.

-- 
Regards
 Sebastian Ohl

 --
 Sebastian Ohl              seb...@oh...
 Kurzekampstr. 14           Tel +49 531 7998221
 D-38104 Braunschweig       Mobil +49 172 1837678

Setting interpolation="none" in imshow fixed the problem.

Thanks for the help,

Joshua

On Mon, Mar 19, 2012 at 11:34 AM, Joshua Lande <jos...@gm...> wrote:
> Hi. I have attached a screenshot of the way the image looks when
> viewed by Preview on my mac, evince on my RHEL5 machine, and the built
> in google docs image viewer.
>
> The image should look like 22x22 square pixels, but (at least for me)
> has stripes of strange looking rectangular pixels. The preview
> screenshot shows both the good and bad version of the image.
>
> I hope this makes sense.
>
> Joshua
>
> On Mon, Mar 19, 2012 at 10:59 AM, Benjamin Root <ben...@ou...> wrote:
>> On Sun, Mar 18, 2012 at 5:07 PM, Joshua Lande <jos...@gm...> wrote:
>>>
>>> Hello.
>>>
>>> I have run into a strange error where matplotlib compresses images
>>> that are saved with the eps backend. Strangely, this compression seems
>>> to happen only for images saved with certain figure sizes. I created a
>>> very simple example which produces this behavior.
>>>
>>>    import pylab as P
>>>    import numpy as np
>>>    np.random.seed(0)
>>>    z=np.random.uniform(size=(22,22))
>>>
>>>    for figsize in [.5,.55]:
>>>        F = P.figure(None,(figsize,figsize))
>>>        ax = F.add_subplot(111)
>>>        im = ax.imshow(z, origin="lower", interpolation="nearest")
>>>        ax.xaxis.set_ticks([])
>>>        ax.yaxis.set_ticks([])
>>>
>>>        P.savefig('test_%.2f.eps' % figsize)
>>>
>>> This code produces test_0.50.eps (attached) which shows ugly
>>> compression whereas test_0.55.eps (also attached) is uncompressed.
>>>
>>> Is there an easy way to disable this compression?
>>>
>>> For reference, I am using python version 2.7.2, matplotlib version
>>> 1.1.0, and for clarity I do not have a matplotlibrc file.
>>>
>>> Thanks for your help,
>>>
>>> Joshua
>>>
>>
>> Using Firefox, I see no difference between the two images.  What are you
>> using?
>>
>> Ben Root
>>

Sorry...That first line should be:
fig, axes = plt.subplots(ncols=3)  # note: subplotS not subplot

On Mon, Mar 19, 2012 at 5:45 PM, Paul Hobson <pmh...@gm...> wrote:
> Try it like this:
>
>               fig, axes = plt.subplots(3,1,1)
>               ax1, ax2, ax3 = axes
>               p1, = ax1.plot(self.data0,self.data1)
>               p2, = ax2.plot(self.data0,self.data2)
>               p3, = ax3.plot(self.data0,self.data4)
>               for ax in axes:
>                       ax.set_xticks([])
>
> -paul

Try it like this:

               fig, axes = plt.subplots(3,1,1)
               ax1, ax2, ax3 = axes
               p1, = ax1.plot(self.data0,self.data1)
               p2, = ax2.plot(self.data0,self.data2)
               p3, = ax3.plot(self.data0,self.data4)
               for ax in axes:
                       ax.set_xticks([])

-paul

On Thu, Mar 15, 2012 at 1:06 AM, kususe <ku...@in...> wrote:
>
>
>
> On Wed, Mar 14, 2012 at 2:38 PM, kususe <ku...@in...> wrote:
>
>>
>> I got an error using the first subplot function because I have to specify
>> 3
>> parameters.
>> If i do it, I get that "AxesSubplot' object is not iterable"
>> I coded using 3 subplot functions, getting the same error.
>>
>> Thanks
>> K.
>>
>>
> Note that I wrote `subplots` with an "s", which is a different command than
> `subplot`. (You're really having problems with "s"s today :)
>
> BTW, would you mind interleaving or bottom-posting
> replies<http://en.wikipedia.org/wiki/Posting_style#Placement_of_replies>.
> It's a bit easier to follow the conversation that way.
>
> -Tony
>
>
> Yes, for sure I coded:
>
>                fig, axes = plt.subplot(3,1,1)
>                ax1, ax2, ax3 = axes
>                p1, = ax1.plot(self.data0,self.data1)
>                ....
>                plt.subplot(3,1,2)
>                p2, = ax2.plot(self.data0,self.data2)
>                .......
>                plt.subplot(3,1,3)
>                p3, = ax3.plot(self.data0,self.data4)
>                ........
>                for ax in axes:
>                        ax.set_xticks([])
>
> but I got the error which said you.
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>
>
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