matplotlib-users Mailing List for matplotlib

Jae-Joon Lee wrote:
> On Sun, Sep 11, 2011 at 10:16 PM, Neal Becker <ndb...@gm...> wrote:
>> Yes, that's very helpful. Just one thing. How would I get a bit more bottom
>> margin on the main figure to leave more room for the extra axis?
>>
>> I'm using this as an example. I experimented with plt.subplots_adjust, which
>> seems like it might do the right thing. Is this the 'best' approach?
>> (I really don't know what all these methods do, just guessing)
> 
> Yes, you need to fiddle with subplots_adjust command. The current
> development branch of matplotlib (not yet released) has a new function
> "tight_layout", which does this automatically for you.
> Regards,
> 
> -JJ
Looking forward to that. Any idea of an ETA for a release?

Mpl 1.0.0
The way Annotation.draw (in text.py) is implemented, if an annotation
is created with an annotation point (x,y) and text located at (tx,ty)
and then the you pan around on the graph such that (x,y) is no longer
visible, the annotation suddenly disappears.
I would suggest the following modification to Annotation.draw in
text.py. All it does is set a clip box so that the annotation and
arrow is still drawn, but the arrow is clipped at the axes boundary.
It is a much nicer effect than the annotation disappearing. I have
made this modification in my source locally, and it works very well,
but I thought I would suggest here for inclusion into the main code
base.
Modified lines are marked with a CHANGEME. It is only a four line change.
 @allow_rasterization
 def draw(self, renderer):
 """
 Draw the :class:`Annotation` object to the given *renderer*.
 """
 if renderer is not None:
 self._renderer = renderer
 if not self.get_visible(): return
 xy_pixel = self._get_position_xy(renderer)
 #if not self._check_xy(renderer, xy_pixel): CHANGEME (commented out)
 # return
CHANGEME (commented out)
 self._update_position_xytext(renderer, xy_pixel)
 self.update_bbox_position_size(renderer)
 if self.arrow is not None:
 if self.arrow.figure is None and self.figure is not None:
 self.arrow.figure = self.figure
 self.arrow.set_clip_box(self.axes.bbox) # CHANGEME (new line)
 self.arrow.draw(renderer)
 if self.arrow_patch is not None:
 if self.arrow_patch.figure is None and self.figure is not None:
 self.arrow_patch.figure = self.figure
 self.arrow_patch.set_clip_box(self.axes.bbox) # CHANGEME (new line)
 self.arrow_patch.draw(renderer)
 Text.draw(self, renderer)
--
Daniel Hyams
dh...@gm...

On Sun, Sep 11, 2011 at 10:16 PM, Neal Becker <ndb...@gm...> wrote:
> Yes, that's very helpful. Just one thing. How would I get a bit more bottom
> margin on the main figure to leave more room for the extra axis?
>
> I'm using this as an example. I experimented with plt.subplots_adjust, which
> seems like it might do the right thing. Is this the 'best' approach?
> (I really don't know what all these methods do, just guessing)
Yes, you need to fiddle with subplots_adjust command. The current
development branch of matplotlib (not yet released) has a new function
"tight_layout", which does this automatically for you.
Regards,
-JJ

Just in case, here is a version with "axes_grid1" toolkit. Note that
axes_grid is kind of deprecated.
Regards,
-JJ
import numpy as np
import matplotlib.pyplot as plt
import mpl_toolkits.axes_grid1 as axes_grid1
host = axes_grid1.host_subplot(111)
hplt, = host.plot(np.random.rand(100))
from matplotlib.transforms import Affine2D
transfrom_from_parx_to_host = Affine2D().scale(1000, 1)
parx = host.twin(transfrom_from_parx_to_host)
if 1: # adjust axis postion etc.
 parx.axis["right"].toggle(ticklabels=False)
 parx.axis["top"].toggle(ticklabels=False)
 parx.axis["bottom"].toggle(ticklabels=True)
 parx.axis["bottom"].line.set_visible(True)
 parx.spines["bottom"].set_position(('outward',20))
plt.show()
On Sat, Sep 10, 2011 at 6:14 AM, Gökhan Sever <gok...@gm...> wrote:
> Hi,
> The code below should create a properly placed 2nd x-axis. You might need to
> adjust the placement of the figure canvas to match into the window.
> import numpy as np
> import matplotlib.pyplot as plt
> from mpl_toolkits.axes_grid.parasite_axes import SubplotHost
> fig = plt.figure(figsize=(10,8))
> host = SubplotHost(fig, 111)
> fig.add_subplot(host)
> parx = host.twiny()
> parx.axis["top"].set_visible(False)
> offset = 0, -50
> new_axisline = parx.get_grid_helper().new_fixed_axis
> parx.axis["bottom"] = new_axisline(loc="bottom", axes=parx, offset=offset)
> parx.axis["bottom"].label.set_visible(True)
> hplt, = host.plot(np.random.rand(100))
> p2, = parx.plot(np.linspace(0,20,100), np.random.rand(100)*5.0,
> color='green')
> plt.show()
>
> There is also another example at:
> http://matplotlib.sourceforge.net/mpl_toolkits/axes_grid/users/overview.html#axisartist-with-parasiteaxes
> Hope this helps.
> On Fri, Sep 9, 2011 at 12:50 PM, Neal Becker <ndb...@gm...> wrote:
>>
>> Neal Becker wrote:
>>
>> > I have a semilog plot. I'd like to add a second x axis (maybe below the
>> > existing one, or else maybe on top of graph). This second x axis is
>> > simply
>> > describing the same existing data, in different units.
>> >
>> > For example imagine a plot of
>> >
>> > x - time in seconds
>> > y - velocity
>> >
>> > x2 - time in minutes
>> >
>> >
>>
>> This almost works:
>>  fig = plt.figure()
>>  ax = fig.add_subplot(111)
>> ...
>>  ax2 = ax.twiny()
>>  min_x, max_x = ax.get_xlim()
>>  ax2.set_xlim (min_x-1, max_x-1)
>>
>> except the 2nd x axis is on the top, and prints right on top of the title
>>
>>
>>
>> ------------------------------------------------------------------------------
>> Why Cloud-Based Security and Archiving Make Sense
>> Osterman Research conducted this study that outlines how and why cloud
>> computing security and archiving is rapidly being adopted across the IT
>> space for its ease of implementation, lower cost, and increased
>> reliability. Learn more. http://www.accelacomm.com/jaw/sfnl/114/51425301/
>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>
>
> --
> Gökhan
>
> ------------------------------------------------------------------------------
> Why Cloud-Based Security and Archiving Make Sense
> Osterman Research conducted this study that outlines how and why cloud
> computing security and archiving is rapidly being adopted across the IT
> space for its ease of implementation, lower cost, and increased
> reliability. Learn more. http://www.accelacomm.com/jaw/sfnl/114/51425301/
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>

Gökhan Sever wrote:
> Hi,
> 
> The code below should create a properly placed 2nd x-axis. You might need to
> adjust the placement of the figure canvas to match into the window.
> 
> import numpy as np
> import matplotlib.pyplot as plt
> from mpl_toolkits.axes_grid.parasite_axes import SubplotHost
> 
> fig = plt.figure(figsize=(10,8))
> host = SubplotHost(fig, 111)
> fig.add_subplot(host)
> parx = host.twiny()
> 
> parx.axis["top"].set_visible(False)
> offset = 0, -50
> new_axisline = parx.get_grid_helper().new_fixed_axis
> parx.axis["bottom"] = new_axisline(loc="bottom", axes=parx, offset=offset)
> parx.axis["bottom"].label.set_visible(True)
> 
> hplt, = host.plot(np.random.rand(100))
> p2, = parx.plot(np.linspace(0,20,100), np.random.rand(100)*5.0,
> color='green')
> 
> plt.show()
> 
> 
> There is also another example at:
> 
http://matplotlib.sourceforge.net/mpl_toolkits/axes_grid/users/overview.html#axisartist-
with-parasiteaxes
> 
> Hope this helps.
Yes, that's very helpful. Just one thing. How would I get a bit more bottom 
margin on the main figure to leave more room for the extra axis?
I'm using this as an example. I experimented with plt.subplots_adjust, which 
seems like it might do the right thing. Is this the 'best' approach?
(I really don't know what all these methods do, just guessing)
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid.parasite_axes import SubplotHost
from matplotlib.backends.backend_pdf import PdfPages
pdf = PdfPages('results.pdf')
fig = plt.figure(figsize=(10,8))
host = SubplotHost(fig, 111)
ax = fig.add_subplot(host)
plt.subplots_adjust (bottom=0.1)
parx = host.twiny()
parx.axis["top"].set_visible(False)
offset = 0, -30
new_axisline = parx.get_grid_helper().new_fixed_axis
parx.axis["bottom"] = new_axisline(loc="bottom", axes=parx, offset=offset)
parx.axis["bottom"].label.set_visible(True)
hplt, = host.plot(np.linspace(0,20,100), np.random.rand(100))
plt.xlabel ('Es/No')
p2, = parx.plot(np.linspace(0,20,100)-5, np.random.rand(100)*5.0, color='green')
parx.set_xlabel ('$Eb_{i}/No$')
#plt.show()
pdf.savefig (fig)
plt.close()
pdf.close()

Sorry, this is the correct link 
http://pcp.oxfordjournals.org/content/52/2/274/F2.expansion.html (Fig2).
Thank you in advance,
On 09/11/2011 04:33 PM, Eric Firing wrote:
> On 09/10/2011 07:57 PM, xyz wrote:
>> Hello,
>> How is it possible to paint this kind graph
>> http://pcp.oxfordjournals.org/content/52/2/274 with Matplotlib?
> Your link leads to a journal abstract, not to a graph. There are
> several figures in the paper. It looks like any of them could be made
> with matplotlib--all are 2-D figures, and mpl is a capable 2-D plotting
> library--but each would require some programming using that library.
>
> Eric
>
>> Thank you in advance.
>>
>> Cheers,
>>
>> Michal
> ------------------------------------------------------------------------------
> Using storage to extend the benefits of virtualization and iSCSI
> Virtualization increases hardware utilization and delivers a new level of
> agility. Learn what those decisions are and how to modernize your storage
> and backup environments for virtualization.
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> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

On 09/10/2011 07:57 PM, xyz wrote:
> Hello,
> How is it possible to paint this kind graph
> http://pcp.oxfordjournals.org/content/52/2/274 with Matplotlib?
Your link leads to a journal abstract, not to a graph. There are 
several figures in the paper. It looks like any of them could be made 
with matplotlib--all are 2-D figures, and mpl is a capable 2-D plotting 
library--but each would require some programming using that library.
Eric
>
> Thank you in advance.
>
> Cheers,
>
> Michal

Hello,
How is it possible to paint this kind graph 
http://pcp.oxfordjournals.org/content/52/2/274 with Matplotlib?
Thank you in advance.
Cheers,
Michal