matplotlib-users Mailing List for matplotlib (Page 46)

Update 2.

I made a new Anaconda Python 2.7 environment and cycled through some
different MPL versions. Everything works as I would expect in 1.4.0;
however, moving to 1.4.1 is when the problem occurs. I see this same
problem if I do the OO commands instead of pyplot.

import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0, np.pi*2, 1000)
y = np.sin(x)

ax = plt.axes()
fill = ax.fill_between(x, y-0.1, y+0.1)
fill.set_linewidth(0)

plt.show()

On Mon, Dec 8, 2014 at 3:38 PM, Ryan Nelson <rne...@gm...> wrote:

> Update.
>
> This is a problem also in Anaconda Py3.4 with MPL 1.4.2, but it works
> without a problem on MPL 1.4.0.
>
> Ryan
>
> On Mon, Dec 8, 2014 at 12:15 PM, Ryan Nelson <rne...@gm...>
> wrote:
>
>> Hello all,
>>
>> I'm having an issue with fill_between. It seems that setting the keyword
>> `linewidth=0` removes the entire patch, rather than the just the bounding
>> lines. Example:
>>
>> ####
>> import numpy as np
>> import matplotlib.pyplot as plt
>>
>> x = np.linspace(0, 2*np.pi, 1000)
>> y = np.sin(x)
>>
>> plt.fill_between(x, y-0.1, y+0.1, linewidth=0) # Setting this !=0 works
>> fine
>> plt.plot(x, y, 'k')
>> plt.show()
>> ####
>>
>> I'm using MPL version 1.4.2 on Python 2.7.8 (Gentoo Linux). This used to
>> work fine before, but maybe there is a new way to do what...
>>
>> Thanks
>>
>> Ryan
>>
>>
>>
>

Update.

This is a problem also in Anaconda Py3.4 with MPL 1.4.2, but it works
without a problem on MPL 1.4.0.

Ryan

On Mon, Dec 8, 2014 at 12:15 PM, Ryan Nelson <rne...@gm...> wrote:

> Hello all,
>
> I'm having an issue with fill_between. It seems that setting the keyword
> `linewidth=0` removes the entire patch, rather than the just the bounding
> lines. Example:
>
> ####
> import numpy as np
> import matplotlib.pyplot as plt
>
> x = np.linspace(0, 2*np.pi, 1000)
> y = np.sin(x)
>
> plt.fill_between(x, y-0.1, y+0.1, linewidth=0) # Setting this !=0 works
> fine
> plt.plot(x, y, 'k')
> plt.show()
> ####
>
> I'm using MPL version 1.4.2 on Python 2.7.8 (Gentoo Linux). This used to
> work fine before, but maybe there is a new way to do what...
>
> Thanks
>
> Ryan
>
>
>

zypper ~ apt-get 
It did install binaries from a Novell repository.
I checked for previous installed and I could not find anything.

cheers



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Hello all,

I'm having an issue with fill_between. It seems that setting the keyword
`linewidth=0` removes the entire patch, rather than the just the bounding
lines. Example:

####
import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0, 2*np.pi, 1000)
y = np.sin(x)

plt.fill_between(x, y-0.1, y+0.1, linewidth=0) # Setting this !=0 works fine
plt.plot(x, y, 'k')
plt.show()
####

I'm using MPL version 1.4.2 on Python 2.7.8 (Gentoo Linux). This used to
work fine before, but maybe there is a new way to do what...

Thanks

Ryan

Well, a rectangle is just two triangles, right? As for each point having a
different value, that is not a problem. I would take a good look at the
triangulation module. It is design to figure out the triangulations from an
arbitrary set of data, or you can specify the triangulations yourself. You
can then pass that information into any of the tri-* family of plotting
functions.

Cheers!
Ben Root


On Sat, Dec 6, 2014 at 11:32 AM, Diego Avesani <die...@gm...>
wrote:

> Dear all, Dear Benjamin, Dear Sappy85,
>
> probably I miss the meaning of structured and not-structured grid. In my
> grid I have only rectangular element, but they are not regular.
> Here an example. In what follows you can see the x and y vector of the
> point of one rectangle:
>
> X=0.1000 0.5950 0.5659 0.0951
> Y=0.0 0.0 0.1839 0.0309
>
> I would like to do as the Ben's example (
> http://matplotlib.org/examples/mplot3d/trisurf3d_demo.html), but with non
> regular rectangles.
> Moreover, in my my case each point has a different value.
>
> Am I asking to much?
> Thanks
>
>
> Diego
>
>
> On 5 December 2014 at 17:48, Benjamin Root <ben...@ou...> wrote:
>
>> I am a bit confused. Your variable is "TRI", but you keep saying
>> rectangles. You are also referring to unstructured rectangles, which makes
>> zero sense to me. Do you mean triangles?
>>
>> If you, matplotlib has the "tri-" family of functions and a whole module
>> devoted to triangulation-related tasks:
>> http://matplotlib.org/api/tri_api.html
>> http://matplotlib.org/examples/pylab_examples/tricontour_demo.html
>>
>> Even the mplot3d toolkit has (limited) support:
>> http://matplotlib.org/examples/mplot3d/trisurf3d_demo.html
>>
>> I hope that helps!
>> Ben Root
>>
>>
>> On Fri, Dec 5, 2014 at 11:38 AM, Sappy85 <rob...@gm...> wrote:
>>
>>> Hi diedro,
>>>
>>> try something like this:
>>>
>>> import matplotlib.patches as patches
>>> import matplotlib.pyplot as plt
>>>
>>> fig    = plt.figure()
>>> ax    = fig.add_subplot(111)
>>> verts = [0.2,0.8], [0.1,0.5], [0.7,0.1]
>>> poly  = patches.Polygon(verts, ec='r', fc='g')
>>>
>>> ax.add_patch(poly)
>>> plt.show()
>>>
>>> <http://matplotlib.1069221.n5.nabble.com/file/n44560/help3.png>
>>>
>>> or this:
>>>
>>> import numpy as np
>>> import matplotlib
>>> matplotlib.use('Agg')
>>>
>>> from matplotlib.patches import Polygon
>>> from matplotlib.collections import PatchCollection
>>> import matplotlib.pyplot as plt
>>>
>>> fig, ax = plt.subplots()
>>>
>>> patches = []
>>> x       = np.random.rand(3)
>>> y       = np.random.rand(3)
>>>
>>> for i in range(3):
>>>     polygon = Polygon(np.random.rand(3,2), True)
>>>     patches.append(polygon)
>>>
>>>
>>> colors = 100*np.random.rand(len(patches))
>>> p = PatchCollection(patches, cmap=matplotlib.cm.jet, alpha=0.4)
>>> p.set_array(np.array(colors))
>>> ax.add_collection(p)
>>> plt.colorbar(p)
>>> plt.grid()
>>> plt.savefig('/var/www/img/help2.png',
>>> bbox_inches='tight',pad_inches=0.05)
>>>
>>> <http://matplotlib.1069221.n5.nabble.com/file/n44560/help2.png>
>>>
>>> Regards,
>>> Sappy85
>>>
>>>
>>>
>>>
>>> --
>>> View this message in context:
>>> http://matplotlib.1069221.n5.nabble.com/Patch-facecolors-tp44558p44560.html
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>>>
>>>
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>>
>>
>>
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>>
>

Dear all, Dear Benjamin, Dear Sappy85,

probably I miss the meaning of structured and not-structured grid. In my
grid I have only rectangular element, but they are not regular.
Here an example. In what follows you can see the x and y vector of the
point of one rectangle:

X=0.1000 0.5950 0.5659 0.0951
Y=0.0 0.0 0.1839 0.0309

I would like to do as the Ben's example (
http://matplotlib.org/examples/mplot3d/trisurf3d_demo.html), but with non
regular rectangles.
Moreover, in my my case each point has a different value.

Am I asking to much?
Thanks


Diego


On 5 December 2014 at 17:48, Benjamin Root <ben...@ou...> wrote:

> I am a bit confused. Your variable is "TRI", but you keep saying
> rectangles. You are also referring to unstructured rectangles, which makes
> zero sense to me. Do you mean triangles?
>
> If you, matplotlib has the "tri-" family of functions and a whole module
> devoted to triangulation-related tasks:
> http://matplotlib.org/api/tri_api.html
> http://matplotlib.org/examples/pylab_examples/tricontour_demo.html
>
> Even the mplot3d toolkit has (limited) support:
> http://matplotlib.org/examples/mplot3d/trisurf3d_demo.html
>
> I hope that helps!
> Ben Root
>
>
> On Fri, Dec 5, 2014 at 11:38 AM, Sappy85 <rob...@gm...> wrote:
>
>> Hi diedro,
>>
>> try something like this:
>>
>> import matplotlib.patches as patches
>> import matplotlib.pyplot as plt
>>
>> fig    = plt.figure()
>> ax    = fig.add_subplot(111)
>> verts = [0.2,0.8], [0.1,0.5], [0.7,0.1]
>> poly  = patches.Polygon(verts, ec='r', fc='g')
>>
>> ax.add_patch(poly)
>> plt.show()
>>
>> <http://matplotlib.1069221.n5.nabble.com/file/n44560/help3.png>
>>
>> or this:
>>
>> import numpy as np
>> import matplotlib
>> matplotlib.use('Agg')
>>
>> from matplotlib.patches import Polygon
>> from matplotlib.collections import PatchCollection
>> import matplotlib.pyplot as plt
>>
>> fig, ax = plt.subplots()
>>
>> patches = []
>> x       = np.random.rand(3)
>> y       = np.random.rand(3)
>>
>> for i in range(3):
>>     polygon = Polygon(np.random.rand(3,2), True)
>>     patches.append(polygon)
>>
>>
>> colors = 100*np.random.rand(len(patches))
>> p = PatchCollection(patches, cmap=matplotlib.cm.jet, alpha=0.4)
>> p.set_array(np.array(colors))
>> ax.add_collection(p)
>> plt.colorbar(p)
>> plt.grid()
>> plt.savefig('/var/www/img/help2.png', bbox_inches='tight',pad_inches=0.05)
>>
>> <http://matplotlib.1069221.n5.nabble.com/file/n44560/help2.png>
>>
>> Regards,
>> Sappy85
>>
>>
>>
>>
>> --
>> View this message in context:
>> http://matplotlib.1069221.n5.nabble.com/Patch-facecolors-tp44558p44560.html
>> Sent from the matplotlib - users mailing list archive at Nabble.com.
>>
>>
>> ------------------------------------------------------------------------------
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>>
>
>
>
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>

Woops! You're absolutely right! I was completely confused!

I mixed up the new "nbagg" backend with the way ipython notebooks used to
display matplotlib figures.  The nbagg backend is indeed interactive (and I
have no idea why key press callbacks aren't supported, then).

This is what happens when I reply to e-mail without putting much thought
into it.

Thanks!
-Joe

On Thu, Dec 4, 2014 at 8:58 PM, Brendan Barnwell <bre...@br...>
wrote:

> On 2014-12-04 15:40, Joe Kington wrote:
> > Nbagg is non-interactive, similar to Agg. No events other than draw
> events
> > are supported, as far as I know.
>
>         If that's the case, the release notes should probably make that
> clear.
>   Right now at
> http://matplotlib.org/users/whats_new.html#the-nbagg-backend it says:
> "Phil Elson added a new backend, named “nbagg”, which enables
> interactive figures in a live IPython notebook session."  The word
> "interactive" certainly could lead people to believe that the backend
> is, in fact, interactive.
>
> --
> Brendan Barnwell
> "Do not follow where the path may lead.  Go, instead, where there is no
> path, and leave a trail."
>     --author unknown
>
>
> ------------------------------------------------------------------------------
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> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

I am a bit confused. Your variable is "TRI", but you keep saying
rectangles. You are also referring to unstructured rectangles, which makes
zero sense to me. Do you mean triangles?

If you, matplotlib has the "tri-" family of functions and a whole module
devoted to triangulation-related tasks:
http://matplotlib.org/api/tri_api.html
http://matplotlib.org/examples/pylab_examples/tricontour_demo.html

Even the mplot3d toolkit has (limited) support:
http://matplotlib.org/examples/mplot3d/trisurf3d_demo.html

I hope that helps!
Ben Root


On Fri, Dec 5, 2014 at 11:38 AM, Sappy85 <rob...@gm...> wrote:

> Hi diedro,
>
> try something like this:
>
> import matplotlib.patches as patches
> import matplotlib.pyplot as plt
>
> fig    = plt.figure()
> ax    = fig.add_subplot(111)
> verts = [0.2,0.8], [0.1,0.5], [0.7,0.1]
> poly  = patches.Polygon(verts, ec='r', fc='g')
>
> ax.add_patch(poly)
> plt.show()
>
> <http://matplotlib.1069221.n5.nabble.com/file/n44560/help3.png>
>
> or this:
>
> import numpy as np
> import matplotlib
> matplotlib.use('Agg')
>
> from matplotlib.patches import Polygon
> from matplotlib.collections import PatchCollection
> import matplotlib.pyplot as plt
>
> fig, ax = plt.subplots()
>
> patches = []
> x       = np.random.rand(3)
> y       = np.random.rand(3)
>
> for i in range(3):
>     polygon = Polygon(np.random.rand(3,2), True)
>     patches.append(polygon)
>
>
> colors = 100*np.random.rand(len(patches))
> p = PatchCollection(patches, cmap=matplotlib.cm.jet, alpha=0.4)
> p.set_array(np.array(colors))
> ax.add_collection(p)
> plt.colorbar(p)
> plt.grid()
> plt.savefig('/var/www/img/help2.png', bbox_inches='tight',pad_inches=0.05)
>
> <http://matplotlib.1069221.n5.nabble.com/file/n44560/help2.png>
>
> Regards,
> Sappy85
>
>
>
>
> --
> View this message in context:
> http://matplotlib.1069221.n5.nabble.com/Patch-facecolors-tp44558p44560.html
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>
>
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>

Hi Jody,

i have posted the code. Here again:

import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
import pygrib

filename   = "file.grib2"
grbs       = pygrib.open('/data/' + filename)
grb        = grbs[2]
data       = grb.values
datac      = data*0.01
lats, lons = grb.latlons()

fig = plt.figure()
m = Basemap(projection='stere',lon_0=5,lat_0=90.0,\
           
llcrnrlon=-25.0,urcrnrlon=60.0,llcrnrlat=30.0,urcrnrlat=60.0,resolution='l')

x, y = m(lons, lats)

levs = range(940,1065,5)
S1=plt.contour(x,y,datac,levs,linewidths=0.5,colors='b')
plt.clabel(S1,inline=1,inline_spacing=0,fontsize=8,fmt='%1.0f',colors='b')

m.drawmapboundary(fill_color='w')
m.drawcoastlines(linewidth=0.2)

plt.savefig('test.png', bbox_inches='tight',pad_inches=0.05, dpi=100) 

Regards,
Sappy85



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Hi diedro,

try something like this:

import matplotlib.patches as patches
import matplotlib.pyplot as plt

fig    = plt.figure()
ax    = fig.add_subplot(111)
verts = [0.2,0.8], [0.1,0.5], [0.7,0.1]
poly  = patches.Polygon(verts, ec='r', fc='g')

ax.add_patch(poly)
plt.show()

<http://matplotlib.1069221.n5.nabble.com/file/n44560/help3.png> 

or this:

import numpy as np
import matplotlib
matplotlib.use('Agg')

from matplotlib.patches import Polygon
from matplotlib.collections import PatchCollection
import matplotlib.pyplot as plt

fig, ax = plt.subplots()

patches = []
x       = np.random.rand(3)
y       = np.random.rand(3)

for i in range(3):
    polygon = Polygon(np.random.rand(3,2), True)
    patches.append(polygon)


colors = 100*np.random.rand(len(patches))
p = PatchCollection(patches, cmap=matplotlib.cm.jet, alpha=0.4)
p.set_array(np.array(colors))
ax.add_collection(p)
plt.colorbar(p)
plt.grid()
plt.savefig('/var/www/img/help2.png', bbox_inches='tight',pad_inches=0.05)

<http://matplotlib.1069221.n5.nabble.com/file/n44560/help2.png> 

Regards, 
Sappy85




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I meant plt.xlim and plt.ylim.  But its hard to tell what the problem is w/o some sample code.

Cheers,   Jody

> On Dec 5, 2014, at  1:07 AM, Sappy85 <rob...@gm...> wrote:
> 
> Hi Jody,
> 
> what exactly du you mean - the plot windows size?
> 
> I tried this:
> fig = plt.figure(figsize=(8.4,5.76))
> 
> But still the same problem.
> 
> Regards 
> 
> 
> 
> --
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> 
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Dear matplotlib users,

I would like to know if there is in matplotlib the following Matlab
function:

*p=patch(x(TRI'),y(TRI'),u(TRI'),u(TRI'));*

*set(p,'FaceColor','interp','EdgeColor','black');*

where TRI are the coordinate of many non regular rectangles.

I would like to do that because I have a not-structured grid whose elements
are irregular rectangles. I would like to plot a 3D surface of the values
on each points of the grid.

Thanks in advance to everyone

Hi Jody,

what exactly du you mean - the plot windows size?

I tried this:
fig = plt.figure(figsize=(8.4,5.76))

But still the same problem.

Regards 



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On 2014-12-04 15:40, Joe Kington wrote:
> Nbagg is non-interactive, similar to Agg. No events other than draw events
> are supported, as far as I know.

	If that's the case, the release notes should probably make that clear. 
  Right now at 
http://matplotlib.org/users/whats_new.html#the-nbagg-backend it says: 
"Phil Elson added a new backend, named “nbagg”, which enables 
interactive figures in a live IPython notebook session."  The word 
"interactive" certainly could lead people to believe that the backend 
is, in fact, interactive.

-- 
Brendan Barnwell
"Do not follow where the path may lead.  Go, instead, where there is no 
path, and leave a trail."
    --author unknown

Hi

Your code wans't included, but try setting your x and y limits *before* the call to clabel.  I think that the problem is that clabel makes a space in the contours according to how large your font is, but if you then resize the plot (zoom in) then the blank space is too large for the labels.  

Cheers,   Jody


> On Dec 4, 2014, at  17:47 PM, Sappy85 <rob...@gm...> wrote:
> 
> I have trouble with matplotlib / pyplot / basemap. I plot contour lines (air
> pressure) on a map. I use clabel to show the value of the contour lines. But
> the problem: the padding between the value and the contour line is too much.
> I have found the parameter "inline_spacing", which i have set to zero. But
> there is still to much free space. Any ideas?
> 
> <http://matplotlib.1069221.n5.nabble.com/file/n44554/mslp.png> 
> 
> My code is as follows:
> 
> 
> 
> 
> Thanks a lot. 
> 
> 
> 
> --
> View this message in context: http://matplotlib.1069221.n5.nabble.com/Pyplot-contour-plot-clabel-padding-tp44554.html
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> 
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I have trouble with matplotlib / pyplot / basemap. I plot contour lines (air
pressure) on a map. I use clabel to show the value of the contour lines. But
the problem: the padding between the value and the contour line is too much.
I have found the parameter "inline_spacing", which i have set to zero. But
there is still to much free space. Any ideas?

<http://matplotlib.1069221.n5.nabble.com/file/n44554/mslp.png> 

My code is as follows:




Thanks a lot. 



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Thanks for the response Joe.
I guess keyboard events are just not implemented yet.
Mouse events (at least button_press_event) do seem to work.



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Nbagg is non-interactive, similar to Agg. No events other than draw events
are supported, as far as I know.

I think there are long term plans to change that (eg, webagg and
mplh5canvas), but it's a fairly tricky problem.

How that helps clarify why things aren't working, anyway.
-Joe
On Dec 4, 2014 11:04 AM, "reem17" <elwin@u.northwestern.edu> wrote:

> I'm using matplotlib version 1.4.2 on linux and am having trouble getting
> key
> event
> callbacks when using the nbagg backend in an ipython notebook (i've tried
> in
> firefox and chromium).
> The key press events seem to not be processed (no matter what key I try to
> press).  This code does work with the qt backend.
>
> %matplotlib nbagg
> import matplotlib.pyplot as plt
> f=plt.figure()
> plt.plot([1,2,3,4])
> def handler(event):
>     plt.plot([4,3,2,1])
> f.canvas.mpl_connect('key_press_event',handler);
>
>
> Thanks for any help.
>
>
>
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> View this message in context:
> http://matplotlib.1069221.n5.nabble.com/Key-events-using-nbagg-backend-tp44551.html
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>
>
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I'm using matplotlib version 1.4.2 on linux and am having trouble getting key
event
callbacks when using the nbagg backend in an ipython notebook (i've tried in
firefox and chromium).
The key press events seem to not be processed (no matter what key I try to
press).  This code does work with the qt backend.

%matplotlib nbagg
import matplotlib.pyplot as plt
f=plt.figure()
plt.plot([1,2,3,4])
def handler(event):
    plt.plot([4,3,2,1])
f.canvas.mpl_connect('key_press_event',handler);


Thanks for any help. 



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Hello,

try doing:

import matplotlib.pyplot as plt
import random

rolls = list()
for i in range(1000):
    rolls.append(random.randint(1,6))


plt.hist(rolls, bins=6)
plt.show()

Reason why your histogram is weird is because you only can have 6 bins
in your example. But the default bin number for hist function is 10.
The borders of bins are therefore set at half intervals. When you roll
1, bin 0 to 0.6 gets incremented, when you roll 2.2 bin 2-2.6 gets
incremented, but the bin 0.6-2.2 never does.

Follow me? (also I just made those numbers up...) Point is only the
bottom bins of your roll values are filled which leaves a gap in your
image.

Dino

2014-12-03 21:51 GMT+01:00 Amit Saha <ami...@gm...>:
> On Thu, Dec 4, 2014 at 6:45 AM, Brendan Barnwell <bre...@br...> wrote:
>> On 2014-12-03 12:39, Amit Saha wrote:
>>>
>>> Hi,
>>>
>>> Please find attached a simple histogram created using the hist()
>>> function. Any idea why the last two bars are squeezed into each other?
>>> Is there a simple way to fix this while plotting?
>>
>>
>>         It looks like the bins are set up so that there are empty bins
>> between each of the other bars.  How are you setting the bins?  You could
>> try adjusting the bin boundaries.
>
> Thanks for the reply. This is my program:
>
> import matplotlib.pyplot as plt
> import random
>
> def roll():
>     return random.randint(1, 6)
>
> if __name__ == '__main__':
>     rolls = []
>     for i in range(1000):
>         rolls.append(roll())
>     # create a histogram plot
>     plt.hist(rolls)
>     plt.show()
>
>
> So, just using the hist() function for now.
>
> Thanks, Amit.
>
>>
>> --
>> Brendan Barnwell
>> "Do not follow where the path may lead.  Go, instead, where there is no
>> path, and leave a trail."
>>    --author unknown
>
>
>
> --
> http://echorand.me
>
> ------------------------------------------------------------------------------
> Download BIRT iHub F-Type - The Free Enterprise-Grade BIRT Server
> from Actuate! Instantly Supercharge Your Business Reports and Dashboards
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On Thu, Dec 4, 2014 at 6:45 AM, Brendan Barnwell <bre...@br...> wrote:
> On 2014-12-03 12:39, Amit Saha wrote:
>>
>> Hi,
>>
>> Please find attached a simple histogram created using the hist()
>> function. Any idea why the last two bars are squeezed into each other?
>> Is there a simple way to fix this while plotting?
>
>
>         It looks like the bins are set up so that there are empty bins
> between each of the other bars.  How are you setting the bins?  You could
> try adjusting the bin boundaries.

Thanks for the reply. This is my program:

import matplotlib.pyplot as plt
import random

def roll():
    return random.randint(1, 6)

if __name__ == '__main__':
    rolls = []
    for i in range(1000):
        rolls.append(roll())
    # create a histogram plot
    plt.hist(rolls)
    plt.show()


So, just using the hist() function for now.

Thanks, Amit.

>
> --
> Brendan Barnwell
> "Do not follow where the path may lead.  Go, instead, where there is no
> path, and leave a trail."
>    --author unknown



-- 
http://echorand.me

On 2014-12-03 12:39, Amit Saha wrote:
> Hi,
>
> Please find attached a simple histogram created using the hist()
> function. Any idea why the last two bars are squeezed into each other?
> Is there a simple way to fix this while plotting?

	It looks like the bins are set up so that there are empty bins between 
each of the other bars.  How are you setting the bins?  You could try 
adjusting the bin boundaries.

-- 
Brendan Barnwell
"Do not follow where the path may lead.  Go, instead, where there is no 
path, and leave a trail."
    --author unknown

Hi,

Please find attached a simple histogram created using the hist()
function. Any idea why the last two bars are squeezed into each other?
Is there a simple way to fix this while plotting?

Thanks,
Amit.

Ok, then this looks like a legitimate bug in span_where(). It probably
isn't applying units, somehow. This isn't really a problem with pandas, it
is an issue where we aren't being consistent in applying units for all
plotting functions. Could you file a bug report, please?

Cheers!
Ben Root

On Tue, Dec 2, 2014 at 11:15 AM, Fabien <fab...@gm...> wrote:

> On 02.12.2014 16:59, Benjamin Root wrote:
> > Does the workaround posted here fix things for you?
> >
> https://github.com/matplotlib/matplotlib/issues/3727#issuecomment-60899590
>
> sorry it doesn't.
>
> I updated the test case below (including the workaround, I hope I got it
> right). The strange thing is that fill_between() works fine, but
> pan_where() is the problem.
>
> Thanks!
>
> #-------------------------------------------
> import pandas as pd
> import numpy as np
> from datetime import datetime as dt
> import matplotlib.pyplot as plt
> import matplotlib.collections as collections
> span_where = collections.BrokenBarHCollection.span_where
> import matplotlib.units as units
>
> units.registry[np.datetime64] = pd.tseries.converter.DatetimeConverter()
>
> # init the dataframe
> time = pd.date_range(pd.datetime(1950,1,1), periods=5, freq='MS')
> df = pd.DataFrame(np.arange(5), index=time, columns=['data'])
> df['cond'] = df['data'] >= 3
>
> # This is working (but its not what I want)
> x = np.arange(5)
> fig = plt.figure()
> ax = fig.add_subplot(111)
> plt.plot(x, df['data'], 'k')
> c = span_where(x, ymin=0, ymax=4, where=df['cond'], color='green')
> ax.add_collection(c)
> plt.show()
>
> #This is not
> x = df.index.values
> fig = plt.figure()
> ax = fig.add_subplot(111)
> plt.plot(x, df['data'], 'k')
> c = span_where(x, ymin=0, ymax=4, where=df['cond'], color='green')
> ax.add_collection(c)
> plt.show()
>
> #This is producing an error
> x = df.index
> fig = plt.figure()
> ax = fig.add_subplot(111)
> plt.plot(x, df['data'], 'k')
> c = span_where(x, ymin=0, ymax=4, where=df['cond'], color='green')
> ax.add_collection(c)
> plt.show()
> #-------------------------------------------
>
>
>
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OK I just filled a bug report:
https://github.com/matplotlib/matplotlib/issues/3872

my first bug report ever!


On 02.12.2014 17:15, Fabien wrote:
> On 02.12.2014 16:59, Benjamin Root wrote:
>> Does the workaround posted here fix things for you?
>> https://github.com/matplotlib/matplotlib/issues/3727#issuecomment-60899590
>
> sorry it doesn't.
>
> I updated the test case below (including the workaround, I hope I got it
> right). The strange thing is that fill_between() works fine, but
> pan_where() is the problem.
>
> Thanks!
>
> #-------------------------------------------
> import pandas as pd
> import numpy as np
> from datetime import datetime as dt
> import matplotlib.pyplot as plt
> import matplotlib.collections as collections
> span_where = collections.BrokenBarHCollection.span_where
> import matplotlib.units as units
>
> units.registry[np.datetime64] = pd.tseries.converter.DatetimeConverter()
>
> # init the dataframe
> time = pd.date_range(pd.datetime(1950,1,1), periods=5, freq='MS')
> df = pd.DataFrame(np.arange(5), index=time, columns=['data'])
> df['cond'] = df['data'] >= 3
>
> # This is working (but its not what I want)
> x = np.arange(5)
> fig = plt.figure()
> ax = fig.add_subplot(111)
> plt.plot(x, df['data'], 'k')
> c = span_where(x, ymin=0, ymax=4, where=df['cond'], color='green')
> ax.add_collection(c)
> plt.show()
>
> #This is not
> x = df.index.values
> fig = plt.figure()
> ax = fig.add_subplot(111)
> plt.plot(x, df['data'], 'k')
> c = span_where(x, ymin=0, ymax=4, where=df['cond'], color='green')
> ax.add_collection(c)
> plt.show()
>
> #This is producing an error
> x = df.index
> fig = plt.figure()
> ax = fig.add_subplot(111)
> plt.plot(x, df['data'], 'k')
> c = span_where(x, ymin=0, ymax=4, where=df['cond'], color='green')
> ax.add_collection(c)
> plt.show()
> #-------------------------------------------