matplotlib-users Mailing List for matplotlib (Page 2)

Doing this in a general way is quite difficult (if possible) because a
user can set an arbitrary transform for an artist. What we may try to
do is recycling artists whose transform is simple, e.g., transData,
rather than try to come up with a general solution.

I'll see what I can do but I must admit that I'm not very kin to this
kind of feature and it may take a while. I recommend you to open a new
ticket in the feature requests tracker hoping  that other developers
or contributors can take a look.

http://sourceforge.net/tracker/?atid=560723&group_id=80706&func=browse

Regards,

-JJ



On Mon, Mar 29, 2010 at 1:54 PM, Thomas Robitaille
<tho...@gm...> wrote:
> Hi Jae-Joon,
>
> Thanks for your quick reply! Since for example LineCollections can be created independent of the Axes in which they are going to be plotted through the creation of a LineCollection instance, would it not be possible to have a method that allows one to retrieve an Axes-independent LineCollection from an Axes instance? (for example a get_collection method) This would then allow one to 'recycle' existing collections.
>
> Cheers,
>
> Thomas
>
> On Mar 29, 2010, at 1:40 PM, Jae-Joon Lee wrote:
>
>> As far as I can say, moving around artists from one axes to the other
>> is NOT recommended. And I encourage you to create separate artists for
>> each axes rather than try to reuse the existing ones.
>>
>> For your particular example,
>>
>> fig = mpl.figure()
>> ax2 = fig.add_subplot(1,1,1)
>> for c in ax1.collections:
>>    c._transOffset=ax2.transData
>>    ax2.add_collection(c)
>>
>> should work.
>>
>> Regards,
>>
>> -JJ
>>
>>
>>
>>
>> On Mon, Mar 29, 2010 at 12:24 PM, Thomas Robitaille
>> <tho...@gm...> wrote:
>>> Hello,
>>>
>>> In the following example, I am trying to copy over existing collections from one plot to another:
>>>
>>> import matplotlib.pyplot as mpl
>>>
>>> fig = mpl.figure()
>>> ax1 = fig.add_subplot(1,1,1)
>>> ax1.scatter([0.5],[0.5])
>>> fig.savefig('test1.png')
>>>
>>> fig = mpl.figure()
>>> ax2 = fig.add_subplot(1,1,1)
>>> for c in ax1.collections:
>>>    ax2.add_collection(c)
>>> fig.savefig('test2.png')
>>>
>>> However, the circle appears in the wrong place in test2.png (close to 0.4, 0.4 instead of 0.5,0.5). Is it not possible/safe to copy over collections in this way? If not, then how should this be done?
>>>
>>> Thanks,
>>>
>>> Thomas
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>
>
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> Try the new software tools for yourself. Speed compiling, find bugs
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> _______________________________________________
> Matplotlib-users mailing list
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> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

But this example doesn't solve the problem I was thinking of: it shows  
lots of colors in the colorbar that aren't used in the plot.


&C



On Mar 30, 2010, at 6:52 AM, Friedrich Romstedt wrote:

> 2010/3/30 Ariel Rokem <ar...@be...>:
>> I ended up with the code below, using Chloe's previously posted
>> 'subcolormap' and, in order to make the colorbar nicely attached to  
>> the main
>> imshow plot, I use make_axes_locatable in order to generate the  
>> colorbar
>> axes. I tried it out with a couple of use-cases and it seems to do  
>> what it
>> is supposed to, (with ticks only for the edges of the range of the  
>> data and
>> 0, if that is within that range), but I am not entirely sure. Do  
>> you think
>> it works?
>
> I think even Chloe would agree that you should avoid the subcolormap()
> if you can.  I tried to create an as minimalistic as possible but
> working self-contained example, please find the code also attached as
> .py file:
>
> from matplotlib import pyplot as plt
> import matplotlib as mpl
> from mpl_toolkits.axes_grid import make_axes_locatable
> import numpy as np
>
> fig = plt.figure()
> ax_im = fig.add_subplot(1, 1, 1)
> divider = make_axes_locatable(ax_im)
> ax_cb = divider.new_vertical(size = '20%', pad = 0.2, pack_start =  
> True)
> fig.add_axes(ax_cb)
>
> x = np.linspace(-5, 5, 101)
> y = x
> Z = np.sin(x*y[:,None]).clip(-1,1-0.1)
>
> # Leave out if you want:
> Z += 2
>
> min_val = Z.min()
> max_val = Z.max()
> bound = max(np.abs(Z.max()), np.abs(Z.min()))
>
> patch = ax_im.imshow(Z, origin = 'upper', interpolation = 'nearest',
>        vmin = -bound, vmax = bound)
>
> cb = fig.colorbar(patch, cax = ax_cb, orientation = 'horizontal',
>        norm = patch.norm,
>        boundaries = np.linspace(-bound, bound, 256),
>        ticks = [min_val, 0, max_val],
>        format = '%.2f')
>
> plt.show()
>
> Friedrich
> <cbar.py><cbar.png>

Thanks Friedrich,

However, my knowledge of python is very limited, even though I think I
understood what you suggested I do not know how to get the shape (of
the figure?) for this part:

>>> fig.set_size_inches(float(shape[0]) / dpi, float(shape[1]) / dpi)

error is:

Traceback (most recent call last):
  File "blueearth-map.py", line 108, in <module>
    fig.set_size_inches(float(shape[0]) / dpi, float(shape[1]) / dpi)
TypeError: 'function' object is unsubscriptable

It seems that it ended up calling a function shape instead of a variable shape.

I'm sending attached the script if you are interested in looking at it.

Thanks again. Filipe.


On Sun, Mar 28, 2010 at 3:35 PM, Friedrich Romstedt
<fri...@gm...> wrote:
>
> 2010/3/28 Filipe Pires Alvarenga Fernandes <oc...@gm...>:
> > Hello list
> > I've trying for a while a "python only" solution to remove white spaces that
> > Basemap generate to keep the aspect ratio. I found these two threads that
> > explain  the issue better:
>
> I think maybe you can make use of the Agg Backend to achieve a
> Python-only solution to obtain a PIL Image from a figure without
> bypassing over the HDD:
>
> Furthemore, if this doesn't work, maybe you can use a StringIO as
> "file", then seek() the StringIO and reread with PIL from the
> "file-like" StringIO, or something like that?
>
> #
> # Render the Figure to a PIL Image ...
> #
>
> # Prepare figure to be of pixel extent *shape* ...
>
> dpi = figure.dpi
> figure.set_size_inches(float(shape[0]) / dpi, float(shape[1]) / dpi)
>
> # Create the rendering Canvas ...
> #
> # We also convert the picture to an RGB string.
>
> canvas = matplotlib.backends.backend_agg.FigureCanvasAgg(figure)
> canvas.draw()
> image_string = canvas.tostring_rgb()
>
> # Create a PIL Image from RGB string ...
>
> image = Image.fromstring("RGB", shape, image_string)
>
> # Now do whatever you want with the Image.
>
> Friedrich

>  2010/3/29 Alan G Isaac <ala...@gm...>:
> > Can you explain this:
> > norm = colors.Normalize(vmin = -1, vmax = 1)

On 3/28/2010 10:05 PM, Friedrich Romstedt wrote:
>  The normaliser takes some arbitrary value and returns a value in [0,
>  1].  Hence the name.  The value \in [0, 1] is handed over to the
>  cmap's __call__(), resulting in the color value.  And yes, I guess you
>  can use vmin and vmax directly, it's just a matter of taste.


OK, thanks!
Alan

Hello All.
I just found a bug with the histogramme fonction of matplotlib.
It might been already known, in this case don't pay attention to my message.

The bug append with both OS: Windows XP and Linux (ubuntu). Both using the latest matplotlib release:  0.99.1

The bug is reproductible, with the folliwng script:

What the script shall do:
Let's say you are looking at the color of wagons on trains.
Every trains has 31 wagons.
Each time you see a red one, you write down it's number
At the end, you want to draw the histogramme with 
X axis: Number of the wagon in the tain
Y axis: Number of wagon of a specific number which is red.

My script
#------------------------------------------------------------------------------------------------------------------------------
import matplotlib.pyplot as plt

liste_histo=[2,2,2,6,1,2,7,2,1,2,1,2,2,1,2,2,11,1,2,12,2,2,14,2,2,1,2,6,1,2,2]
plt.figure(1)
plt.hist(sorted(liste_histo),bins=31)
plt.axis([0,31,0,20])
plt.show()
#-----------------------------------------------------------------------------------------------------------------------------

This script should give you a srange historamme, with bins that are half the size they shoud be.

With the same script, but a different countdown of my wagons, it works well:
#-----------------------------------------------------------------------------------------------------------------------------
import matplotlib.pyplot as plt

liste_histo=[2,2,2,6,1,2,7,2,1,2,1,2,2,1,2,2,11,1,2,12,2,2,14,2,2,1,2,6,15,25]
plt.figure(1)
plt.hist(sorted(liste_histo),bins=31)
plt.axis([0,31,0,20])
plt.show()
#-----------------------------------------------------------------------------------------------------------------------------

I corrected this error by adding a 32 (my max value on the histogramme should be a 31).
asking 32 bins, and drawing the histogramme between 1 and 31:

#------------------------------------------------------------------------------------------------------------------------------

import matplotlib.pyplot as plt



liste_histo=[2,2,2,6,1,2,7,2,1,2,1,2,2,1,2,2,11,1,2,12,2,2,14,2,2,1,2,6,1,2,2,32]

plt.figure(1)

plt.hist(sorted(liste_histo),bins=32)

plt.axis([0,31,0,20])

plt.show()

#-----------------------------------------------------------------------------------------------------------------------------

And it works...
Am I the only one to get a probleme here?

Thanks for reading me

Julien




      

Hi Friedrich,

Thanks a lot - very nice!

Cheers - Ariel

On Tue, Mar 30, 2010 at 6:52 AM, Friedrich Romstedt <
fri...@gm...> wrote:

> 2010/3/30 Ariel Rokem <ar...@be...>:
> > I ended up with the code below, using Chloe's previously posted
> > 'subcolormap' and, in order to make the colorbar nicely attached to the
> main
> > imshow plot, I use make_axes_locatable in order to generate the colorbar
> > axes. I tried it out with a couple of use-cases and it seems to do what
> it
> > is supposed to, (with ticks only for the edges of the range of the data
> and
> > 0, if that is within that range), but I am not entirely sure. Do you
> think
> > it works?
>
> I think even Chloe would agree that you should avoid the subcolormap()
> if you can.  I tried to create an as minimalistic as possible but
> working self-contained example, please find the code also attached as
> .py file:
>
> from matplotlib import pyplot as plt
> import matplotlib as mpl
> from mpl_toolkits.axes_grid import make_axes_locatable
> import numpy as np
>
> fig = plt.figure()
> ax_im = fig.add_subplot(1, 1, 1)
> divider = make_axes_locatable(ax_im)
> ax_cb = divider.new_vertical(size = '20%', pad = 0.2, pack_start = True)
> fig.add_axes(ax_cb)
>
> x = np.linspace(-5, 5, 101)
> y = x
> Z = np.sin(x*y[:,None]).clip(-1,1-0.1)
>
> # Leave out if you want:
> Z += 2
>
> min_val = Z.min()
> max_val = Z.max()
> bound = max(np.abs(Z.max()), np.abs(Z.min()))
>
> patch = ax_im.imshow(Z, origin = 'upper', interpolation = 'nearest',
>        vmin = -bound, vmax = bound)
>
> cb = fig.colorbar(patch, cax = ax_cb, orientation = 'horizontal',
>        norm = patch.norm,
>        boundaries = np.linspace(-bound, bound, 256),
>        ticks = [min_val, 0, max_val],
>        format = '%.2f')
>
> plt.show()
>
> Friedrich
>



-- 
Ariel Rokem
Helen Wills Neuroscience Institute
University of California, Berkeley
http://argentum.ucbso.berkeley.edu/ariel

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2010/3/30 Ariel Rokem <ar...@be...>:
> I ended up with the code below, using Chloe's previously posted
> 'subcolormap' and, in order to make the colorbar nicely attached to the main
> imshow plot, I use make_axes_locatable in order to generate the colorbar
> axes. I tried it out with a couple of use-cases and it seems to do what it
> is supposed to, (with ticks only for the edges of the range of the data and
> 0, if that is within that range), but I am not entirely sure. Do you think
> it works?

I think even Chloe would agree that you should avoid the subcolormap()
if you can.  I tried to create an as minimalistic as possible but
working self-contained example, please find the code also attached as
.py file:

from matplotlib import pyplot as plt
import matplotlib as mpl
from mpl_toolkits.axes_grid import make_axes_locatable
import numpy as np

fig = plt.figure()
ax_im = fig.add_subplot(1, 1, 1)
divider = make_axes_locatable(ax_im)
ax_cb = divider.new_vertical(size = '20%', pad = 0.2, pack_start = True)
fig.add_axes(ax_cb)

x = np.linspace(-5, 5, 101)
y = x
Z = np.sin(x*y[:,None]).clip(-1,1-0.1)

# Leave out if you want:
Z += 2

min_val = Z.min()
max_val = Z.max()
bound = max(np.abs(Z.max()), np.abs(Z.min()))

patch = ax_im.imshow(Z, origin = 'upper', interpolation = 'nearest',
        vmin = -bound, vmax = bound)

cb = fig.colorbar(patch, cax = ax_cb, orientation = 'horizontal',
        norm = patch.norm,
        boundaries = np.linspace(-bound, bound, 256),
        ticks = [min_val, 0, max_val],
        format = '%.2f')

plt.show()

Friedrich

David Carmean <dlc-sfl@...> writes:

> At what point is a line Collection useful?  

More efficient for adding or manipulating many lines in one go. It saved my life 
(some hours of it, anyway) the other day:

http://article.gmane.org/gmane.comp.python.matplotlib.general/22149

Hi -

I ended up with the code below, using Chloe's previously posted
'subcolormap' and, in order to make the colorbar nicely attached to the main
imshow plot, I use make_axes_locatable in order to generate the colorbar
axes. I tried it out with a couple of use-cases and it seems to do what it
is supposed to, (with ticks only for the edges of the range of the data and
0, if that is within that range), but I am not entirely sure. Do you think
it works?


Cheers,

Ariel

    from mpl_toolkits.axes_grid import make_axes_locatable

    fig=plt.figure()
    ax_im = fig.add_subplot(1,1,1)
    divider = make_axes_locatable(ax_im)
    ax_cb = divider.new_vertical(size="20%", pad=0.2, pack_start=True)
    fig.add_axes(ax_cb)
    #Extract the minimum and maximum values for scaling of the
colormap/colorbar:
    max_val = np.max(m[np.where(m<1)])
    min_val = np.min(m)

    #This makes sure that 0 is always the center of the colormap:
    if min_val<-max_val:
        ax_max = -min_val
        ax_min = min_val
    else:
        ax_max = max_val
        ax_min = -max_val

    #Keyword args to imshow:
    kw = {'origin': 'upper',
          'interpolation': 'nearest',
          'cmap':cmap,
          'vmin':ax_min,
          'vmax':ax_max}

    im=ax_im.imshow(m,**kw)

    #The following produces the colorbar and sets the ticks
    if colorbar:
        delta = ax_max-ax_min #The size of the entire interval of data
        min_p = (min_val-ax_min)/delta
        max_p = (max_val-ax_min)/delta
        print min_p
        print max_p
        cnorm = mpl.colors.Normalize(vmin=min_val,vmax=max_val)
        subcmap = subcolormap(min_p,max_p,cmap)
        cb = mpl.colorbar.ColorbarBase(ax_cb, cmap=subcmap,
                                       orientation='horizontal',norm=cnorm)

        #Set the ticks - if 0 is in the interval of values, set that, as
well
        #as the maximal and minimal values:
        if min_val<0:
            cb.set_ticks([min_val,0,max_val])
            cb.set_ticklabels(['%.2f'%min_val,'0','%.2f'%max_val])
        #Otherwise - only set the minimal and maximal value:
        else:
            cb.set_ticks([min_val,max_val])
            cb.set_ticklabels(['%.2f'%min_val,'%.2f'%max_val])



On Mon, Mar 29, 2010 at 6:41 AM, Friedrich Romstedt <
fri...@gm...> wrote:

> 2010/3/29 Friedrich Romstedt <fri...@gm...>:
> > Note that the ticking is a bit weird, there is also a bug in
> > matplotlib I will report on right after this e-mail, whose bugfix you
> > will maybe want to apply to get ticking properly working.  When you
> > have insane values for C.min() and C.max() anyway, I'm afraid you have
> > to retick manually with *ticks* to colorbar().  The ticker.MaxNLocator
> > is only used when not using the *boundaries* arg to colorbar(),
> > unfortunately.  Otherwise it tries to create maximal many and less
> > than 11 ticks by using the lowest value and an appropriate step in
> > *boundaries*.  I think the implementation of ticking is cumbersome and
> > never optimal.
>
> You can get rid of this night mare by giving the kwarg "ticks =
> matplotlib.ticker.MaxNLocator()" to fig.colorbar().  Then the
> *boundaries* aren't used for ticking (but still for plotting).
>
> Friedrich
>



-- 
Ariel Rokem
Helen Wills Neuroscience Institute
University of California, Berkeley
http://argentum.ucbso.berkeley.edu/ariel

Hello,

This is my first time trying out this list, so please forgive me if I've doing this wrong.

I'm trying to create a plot that has its origin in the upper-left hand corner, rather than the lower-left hand corner. I've discovered that I get the same effect if I do:

plt.plot( xcoords, ycoords, 'ro' )
plt.axis( [0, maxX, maxY, 0] )

However, the x-axis still appears on the bottom of the graph rather than the top.

Is there a way that I can shift the location of the origin more easily, or at least shift where the axis is written at? 

Thanks!

Solved. Sort of. If I run using python it works. It fails if I run using
ipython with --pylab.

On Mon, Mar 29, 2010 at 3:46 PM, Mathew Yeates <mat...@gm...> wrote:

> I don't understand why the following fails.
>
> fig = Figure(figsize=(5,5), dpi=100)
> canvas = FigureCanvas(fig)
> ax = fig.add_subplot(111)
> m = Basemap(resolution='c',projection='cyl',lon_0=0,ax=ax)
> m.drawcoastlines(color='gray',ax=ax)
>
> fails with
> mpl_toolkits\basemap\__init__.pyc in set_axes_limits ....
>    2531         if is_interactive():
>    2532             figManager = _pylab_helpers.Gcf.get_active()
> -> 2533             figManager.canvas.draw()
>
> AttributeError: 'NoneType' object has no attribute 'canvas'
>
> Why isn't my figure being set as active??
>
> Mathew
>
>
>
>
>
>
>
>
> On Mon, Mar 29, 2010 at 11:12 AM, Yeates, Mathew C (388D) <
> mat...@jp...> wrote:
>
>>  Hi
>>
>> Anyone have an example? I found some older examples which no longer work.
>>
>>
>>
>> TIA
>>
>>
>>
>> Mathew
>>
>>
>>
>> For grins …. The following does not work. I’ve tried many different
>> variations …
>>
>>
>>
>> import matplotlib.pyplot as plt
>>
>>
>>
>> import gtk
>>
>> from mpl_toolkits.basemap import Basemap
>>
>> import matplotlib
>>
>> from matplotlib.figure import Figure
>>
>> fig=plt.Figure()
>>
>> ax=fig.add_subplot(111)
>>
>> m = Basemap(llcrnrlon=1, \
>>
>>             llcrnrlat=40.6, \
>>
>>             urcrnrlon=8.8, \
>>
>>             urcrnrlat = 49.6, \
>>
>>             projection = 'tmerc', \
>>
>>             lon_0 = 4.9, \
>>
>>             lat_0 = 45.1,ax=ax)
>>
>>
>>
>> from matplotlib.backends.backend_gtkagg import \
>>
>>                         FigureCanvasGTKAgg as FigureCanvas
>>
>> canvas = FigureCanvas(fig)
>>
>> m.drawcoastlines(color='gray')
>>
>> m.drawcountries(color='gray')
>>
>> m.fillcontinents(color='beige')
>>
>> builder = gtk.Builder()
>>
>> builder.add_from_file("fluxtool.glade")
>>
>> window1=builder.get_object("window1")
>>
>> window1.connect("destroy", lambda x: gtk.main_quit())
>>
>>
>>
>>
>>
>> vbox=builder.get_object("vbox1")
>>
>> vbox.pack_start(canvas)
>>
>> window1.show()
>>
>> gtk.main()
>>
>>
>>
>>
>> ------------------------------------------------------------------------------
>> Download Intel&#174; Parallel Studio Eval
>> Try the new software tools for yourself. Speed compiling, find bugs
>> proactively, and fine-tune applications for parallel performance.
>> See why Intel Parallel Studio got high marks during beta.
>> http://p.sf.net/sfu/intel-sw-dev
>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>>
>

I don't understand why the following fails.

fig = Figure(figsize=(5,5), dpi=100)
canvas = FigureCanvas(fig)
ax = fig.add_subplot(111)
m = Basemap(resolution='c',projection='cyl',lon_0=0,ax=ax)
m.drawcoastlines(color='gray',ax=ax)

fails with
mpl_toolkits\basemap\__init__.pyc in set_axes_limits ....
   2531         if is_interactive():
   2532             figManager = _pylab_helpers.Gcf.get_active()
-> 2533             figManager.canvas.draw()

AttributeError: 'NoneType' object has no attribute 'canvas'

Why isn't my figure being set as active??

Mathew








On Mon, Mar 29, 2010 at 11:12 AM, Yeates, Mathew C (388D) <
mat...@jp...> wrote:

>  Hi
>
> Anyone have an example? I found some older examples which no longer work.
>
>
>
> TIA
>
>
>
> Mathew
>
>
>
> For grins …. The following does not work. I’ve tried many different
> variations …
>
>
>
> import matplotlib.pyplot as plt
>
>
>
> import gtk
>
> from mpl_toolkits.basemap import Basemap
>
> import matplotlib
>
> from matplotlib.figure import Figure
>
> fig=plt.Figure()
>
> ax=fig.add_subplot(111)
>
> m = Basemap(llcrnrlon=1, \
>
>             llcrnrlat=40.6, \
>
>             urcrnrlon=8.8, \
>
>             urcrnrlat = 49.6, \
>
>             projection = 'tmerc', \
>
>             lon_0 = 4.9, \
>
>             lat_0 = 45.1,ax=ax)
>
>
>
> from matplotlib.backends.backend_gtkagg import \
>
>                         FigureCanvasGTKAgg as FigureCanvas
>
> canvas = FigureCanvas(fig)
>
> m.drawcoastlines(color='gray')
>
> m.drawcountries(color='gray')
>
> m.fillcontinents(color='beige')
>
> builder = gtk.Builder()
>
> builder.add_from_file("fluxtool.glade")
>
> window1=builder.get_object("window1")
>
> window1.connect("destroy", lambda x: gtk.main_quit())
>
>
>
>
>
> vbox=builder.get_object("vbox1")
>
> vbox.pack_start(canvas)
>
> window1.show()
>
> gtk.main()
>
>
>
>
> ------------------------------------------------------------------------------
> Download Intel&#174; Parallel Studio Eval
> Try the new software tools for yourself. Speed compiling, find bugs
> proactively, and fine-tune applications for parallel performance.
> See why Intel Parallel Studio got high marks during beta.
> http://p.sf.net/sfu/intel-sw-dev
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>

Sami-Matias Niemi wrote:
> Hi,
> 
> When using scatter plotting method and linestyles argument the output  
> seems to ignore the linestyles keyword value at least in SVN. Can  
> someone confirm this or did I misunderstood the functionality?

Yes, scatter is designed to plot markers only, and it does ignore the 
linestyles kw.

> 
> I am trying to make a plot where the colour of the line changes as a  
> function of data value, but I don't want that each point (marker) is  
> plotted separately, but that the colour changes smoothly. I believe  
> scatter method could be used when optional arguments "c = values" and  
> linestyles = 'solid' are used. However, independent what the  
> linestyles argument value is, I always get the markers plotted and no  
> line appears.

We don't have anything that gives this behavior directly, but it can be 
simulated with a LineCollection.  See 
http://www.scipy.org/Cookbook/Matplotlib/MulticoloredLine.

Eric

> 
> 
> Cheers,
> Sami
> 
> 
> Example code (markers, but no solid line!?):
> 
> import numpy as np
> import pylab as p
> 
> data = np.arange(10)
> 
> p.scatter(data, data, c = data, s = data*10, linestyles = 'solid')
> 
> 
> 
> ------------------------------------------------------------------------------
> Download Intel® Parallel Studio Eval
> Try the new software tools for yourself. Speed compiling, find bugs
> proactively, and fine-tune applications for parallel performance.
> See why Intel Parallel Studio got high marks during beta.
> http://p.sf.net/sfu/intel-sw-dev
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users

Hi
Anyone have an example? I found some older examples which no longer work.

TIA

Mathew

For grins .... The following does not work. I've tried many different variations ...

import matplotlib.pyplot as plt

import gtk
from mpl_toolkits.basemap import Basemap
import matplotlib
from matplotlib.figure import Figure
fig=plt.Figure()
ax=fig.add_subplot(111)
m = Basemap(llcrnrlon=1, \
            llcrnrlat=40.6, \
            urcrnrlon=8.8, \
            urcrnrlat = 49.6, \
            projection = 'tmerc', \
            lon_0 = 4.9, \
            lat_0 = 45.1,ax=ax)

from matplotlib.backends.backend_gtkagg import \
                        FigureCanvasGTKAgg as FigureCanvas
canvas = FigureCanvas(fig)
m.drawcoastlines(color='gray')
m.drawcountries(color='gray')
m.fillcontinents(color='beige')
builder = gtk.Builder()
builder.add_from_file("fluxtool.glade")
window1=builder.get_object("window1")
window1.connect("destroy", lambda x: gtk.main_quit())


vbox=builder.get_object("vbox1")
vbox.pack_start(canvas)
window1.show()
gtk.main()

Hi,

When using scatter plotting method and linestyles argument the output  
seems to ignore the linestyles keyword value at least in SVN. Can  
someone confirm this or did I misunderstood the functionality?

I am trying to make a plot where the colour of the line changes as a  
function of data value, but I don't want that each point (marker) is  
plotted separately, but that the colour changes smoothly. I believe  
scatter method could be used when optional arguments "c = values" and  
linestyles = 'solid' are used. However, independent what the  
linestyles argument value is, I always get the markers plotted and no  
line appears.


Cheers,
Sami


Example code (markers, but no solid line!?):

import numpy as np
import pylab as p

data = np.arange(10)

p.scatter(data, data, c = data, s = data*10, linestyles = 'solid')

Hi Jae-Joon,

Thanks for your quick reply! Since for example LineCollections can be created independent of the Axes in which they are going to be plotted through the creation of a LineCollection instance, would it not be possible to have a method that allows one to retrieve an Axes-independent LineCollection from an Axes instance? (for example a get_collection method) This would then allow one to 'recycle' existing collections.

Cheers,

Thomas

On Mar 29, 2010, at 1:40 PM, Jae-Joon Lee wrote:

> As far as I can say, moving around artists from one axes to the other
> is NOT recommended. And I encourage you to create separate artists for
> each axes rather than try to reuse the existing ones.
> 
> For your particular example,
> 
> fig = mpl.figure()
> ax2 = fig.add_subplot(1,1,1)
> for c in ax1.collections:
>    c._transOffset=ax2.transData
>    ax2.add_collection(c)
> 
> should work.
> 
> Regards,
> 
> -JJ
> 
> 
> 
> 
> On Mon, Mar 29, 2010 at 12:24 PM, Thomas Robitaille
> <tho...@gm...> wrote:
>> Hello,
>> 
>> In the following example, I am trying to copy over existing collections from one plot to another:
>> 
>> import matplotlib.pyplot as mpl
>> 
>> fig = mpl.figure()
>> ax1 = fig.add_subplot(1,1,1)
>> ax1.scatter([0.5],[0.5])
>> fig.savefig('test1.png')
>> 
>> fig = mpl.figure()
>> ax2 = fig.add_subplot(1,1,1)
>> for c in ax1.collections:
>>    ax2.add_collection(c)
>> fig.savefig('test2.png')
>> 
>> However, the circle appears in the wrong place in test2.png (close to 0.4, 0.4 instead of 0.5,0.5). Is it not possible/safe to copy over collections in this way? If not, then how should this be done?
>> 
>> Thanks,
>> 
>> Thomas
>> ------------------------------------------------------------------------------
>> Download Intel&#174; Parallel Studio Eval
>> Try the new software tools for yourself. Speed compiling, find bugs
>> proactively, and fine-tune applications for parallel performance.
>> See why Intel Parallel Studio got high marks during beta.
>> http://p.sf.net/sfu/intel-sw-dev
>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>> 

Dear All,
                 I want to make minor ticks working in following program.
Here only major ticks are dis[played in grpah though i have declared the
minor ticks
minorticks_on() doesnt work in my code. How to fix that.Please help me
out.Thanks in advance !!!!!!!!!!!!'
Regards
Yogesh

from numpy import *
from scipy import *
from scipy import signal, misc
import sys,time,os,gc
import matplotlib
import matplotlib.pyplot as plt
from numpy.random import *
from pylab import plot, show, ylim, yticks,xlim
from pylab import *
x=loadtxt('/home/jaguar/Desktop/45.txt')
x=x[0:1399]
y=arange(len(x))
plt.figure(2)
plt.plot(y,x,'k-')
#minorticks_on()
grid(True)#, color="r", ls="-")
gca().xaxis.grid(True, which="minor", color="r")
#gca().yaxis.grid(True, which='minor')
#grid(True, which="minor", color="r")

show()#l

As far as I can say, moving around artists from one axes to the other
is NOT recommended. And I encourage you to create separate artists for
each axes rather than try to reuse the existing ones.

For your particular example,

fig = mpl.figure()
ax2 = fig.add_subplot(1,1,1)
for c in ax1.collections:
    c._transOffset=ax2.transData
    ax2.add_collection(c)

should work.

Regards,

-JJ




On Mon, Mar 29, 2010 at 12:24 PM, Thomas Robitaille
<tho...@gm...> wrote:
> Hello,
>
> In the following example, I am trying to copy over existing collections from one plot to another:
>
> import matplotlib.pyplot as mpl
>
> fig = mpl.figure()
> ax1 = fig.add_subplot(1,1,1)
> ax1.scatter([0.5],[0.5])
> fig.savefig('test1.png')
>
> fig = mpl.figure()
> ax2 = fig.add_subplot(1,1,1)
> for c in ax1.collections:
>    ax2.add_collection(c)
> fig.savefig('test2.png')
>
> However, the circle appears in the wrong place in test2.png (close to 0.4, 0.4 instead of 0.5,0.5). Is it not possible/safe to copy over collections in this way? If not, then how should this be done?
>
> Thanks,
>
> Thomas
> ------------------------------------------------------------------------------
> Download Intel&#174; Parallel Studio Eval
> Try the new software tools for yourself. Speed compiling, find bugs
> proactively, and fine-tune applications for parallel performance.
> See why Intel Parallel Studio got high marks during beta.
> http://p.sf.net/sfu/intel-sw-dev
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

Hello,

In the following example, I am trying to copy over existing collections from one plot to another:

import matplotlib.pyplot as mpl

fig = mpl.figure()
ax1 = fig.add_subplot(1,1,1)
ax1.scatter([0.5],[0.5])
fig.savefig('test1.png')

fig = mpl.figure()
ax2 = fig.add_subplot(1,1,1)
for c in ax1.collections:
    ax2.add_collection(c)
fig.savefig('test2.png')

However, the circle appears in the wrong place in test2.png (close to 0.4, 0.4 instead of 0.5,0.5). Is it not possible/safe to copy over collections in this way? If not, then how should this be done?

Thanks,

Thomas

Hi Matthias,

Thanks for the help. The problem is, however, that the 'extent' parameter
only manipulates the range of the (integer) values on the axis. Before
setting the *axis_date property, I need to set the axes data to arrays of
(non-equidistant) floats.

Best Regards,
Micha


Matthias Michler wrote:
> 
> 
> Did you already set the date-xaxis by hand?
> -> for axes 'ax' using e.g.
> ax.xaxis_date(tz=None)
> ax.yaxis_date(tz=None)
> 
> 

-- 
View this message in context: http://old.nabble.com/matshow---imshow-with-date-axis-tp28068228p28070890.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

Friedrich Romstedt wrote:
> 2010/3/29 Eric Firing <ef...@ha...>:
>> It already has this.  You can pass in a custom locator or set of tick
>> locations via the "ticks" kwarg, but if you don't, a locator is chosen
>> automatically.  Except in special cases, this will be a MaxNLocator. See the
>> ColorbarBase._ticker method.
> 
> Ah, thanks, It escaped my notice that there is a toplevel "if
> self.locator is None:" statement ... ok.
> 
>> Ah, maybe what you mean is a text option to the "ticks" kwarg that would
>> specify MaxNLocator without requiring one to instantiate a MaxNLocator? I
>> don't think this makes sense for the case when boundaries are specified
>> explicitly.
> 
> No, what I intended is exactly what you pointed out.
> 
> Btw, can you tell me what the *values* kwarg's semantic is?  I guess,
> it shall be the center values of the values displayed, but then the
> implementation for this in ColorbarBase._process_values() would be
> broken.

The ColorbarBase simply makes a strip of colored blocks, with their 
sizes and locations determined by the boundaries kwarg (together with 
the "spacing" kwarg) and their colors determined from the values kwarg 
via color mapping.  If either or both of these kwargs is None, the 
boundaries and/or values will be generated  in _process_values.  The use 
of the non-default values kwarg is illustrated by the special-case 
handling of colorbars for contouring in the Colorbar class.

Can you give a test case showing a problem with _process_values?

> 
> Friedrich
> 
> P.S.: I assume you have be caught by the "misconfiguration" of the
> list that the sender is used as the default recipient, so I post back
> to the list?

The mpl lists have been unusual (at least compared to lists for numpy, 
scipy, and cython) in this respect for years.  Usually I remember to 
reply to all, but you are right--this time I goofed.

Eric

2010/3/29 Friedrich Romstedt <fri...@gm...>:
> Note that the ticking is a bit weird, there is also a bug in
> matplotlib I will report on right after this e-mail, whose bugfix you
> will maybe want to apply to get ticking properly working.  When you
> have insane values for C.min() and C.max() anyway, I'm afraid you have
> to retick manually with *ticks* to colorbar().  The ticker.MaxNLocator
> is only used when not using the *boundaries* arg to colorbar(),
> unfortunately.  Otherwise it tries to create maximal many and less
> than 11 ticks by using the lowest value and an appropriate step in
> *boundaries*.  I think the implementation of ticking is cumbersome and
> never optimal.

You can get rid of this night mare by giving the kwarg "ticks =
matplotlib.ticker.MaxNLocator()" to fig.colorbar().  Then the
*boundaries* aren't used for ticking (but still for plotting).

Friedrich

Hello,

It looks like the zlib website removes previous version of its library that were previously available for download, so the part in make.osx where http://www.zlib.net/zlib-1.2.3.tar.gz is fetched now fails (since the current version is 1.2.4). The error in the matplotlib building is not explicit enough (incorrect archive type) - maybe one could catch such 404s and print out an error suggesting to increase the ZLIBVERSION variable?

I tried changing ZLIBVERSION to 1.2.4 and the following occurs when building zlib:

...
gcc -arch i386 -arch x86_64 -I/Users/tom/install/include -I/Users/tom/install/include/freetype2 -isysroot /Developer/SDKs/MacOSX10.6.sdk   -c -o inftrees.o inftrees.c
gcc -arch i386 -arch x86_64 -I/Users/tom/install/include -I/Users/tom/install/include/freetype2 -isysroot /Developer/SDKs/MacOSX10.6.sdk   -c -o trees.o trees.c
gcc -arch i386 -arch x86_64 -I/Users/tom/install/include -I/Users/tom/install/include/freetype2 -isysroot /Developer/SDKs/MacOSX10.6.sdk   -c -o uncompr.o uncompr.c
gcc -arch i386 -arch x86_64 -I/Users/tom/install/include -I/Users/tom/install/include/freetype2 -isysroot /Developer/SDKs/MacOSX10.6.sdk   -c -o zutil.o zutil.c
make[1]: *** No rule to make target `libz.dylib', needed by `install-libs'.  Stop.
make[1]: *** Waiting for unfinished jobs....
make: *** [zlib] Error 2

If I manually go to the zlib directory and type make, it builds without a problem, so it looks like there is some kind of problem in the make.osx script.

Thanks in advance for any help,

Thomas

2010/3/29 Eric Firing <ef...@ha...>:
> It already has this.  You can pass in a custom locator or set of tick
> locations via the "ticks" kwarg, but if you don't, a locator is chosen
> automatically.  Except in special cases, this will be a MaxNLocator. See the
> ColorbarBase._ticker method.

Ah, thanks, It escaped my notice that there is a toplevel "if
self.locator is None:" statement ... ok.

> Ah, maybe what you mean is a text option to the "ticks" kwarg that would
> specify MaxNLocator without requiring one to instantiate a MaxNLocator? I
> don't think this makes sense for the case when boundaries are specified
> explicitly.

No, what I intended is exactly what you pointed out.

Btw, can you tell me what the *values* kwarg's semantic is?  I guess,
it shall be the center values of the values displayed, but then the
implementation for this in ColorbarBase._process_values() would be
broken.

Friedrich

P.S.: I assume you have be caught by the "misconfiguration" of the
list that the sender is used as the default recipient, so I post back
to the list?