matplotlib-users Mailing List for matplotlib (Page 3)

Hi all,
how can I create line segments between consecutive selected points of a
scatter plot in an interactive manner ? It should be possible to create
several unclosed polygonal lines. Each polygonal line might have
a different color.
A small example is appreciated.
Thanks in advance.
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It appears you have come across a bug. As a work-around, try adding
"use_gridspec=False" to your call to fig.colorbar(). It looks like the
gridspec version of colorbars is not popping off the anchor (or panchor)
arguments and simply using hardcoded defaults. Those extra keyword
arguments get passed on to the colorbar factory function, which doesn't
recognize it and throws an exception. The gridspec code needs to pop off
the argurments, even if it isn't going to use them.
Ben Root
On Wed, Dec 10, 2014 at 6:06 PM, Yilong Wang <wan...@gm...> wrote:
> Hi all,
> I am using matplotlib-1.4.2, but when I try to plot a colorbar and define
> its position using argument 'anchor', it raises an error:
> TypeError: __init__() got an unexpected keyword argument 'anchor'
> Does anyone have any clue for this?
> Thank you very much!
>
> The test script is as follows:
>
> import numpy as np
> import matplotlib.pyplot as plt
>
> a=np.random.randn(100,150)
> fig,ax=plt.subplots()
> im=ax.imshow(a)
> fig.colorbar(im,anchor=(0.,0.5))
> plt.show()
>
>
>
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>
>
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Hi all,
I am using matplotlib-1.4.2, but when I try to plot a colorbar and define
its position using argument 'anchor', it raises an error:
TypeError: __init__() got an unexpected keyword argument 'anchor'
Does anyone have any clue for this?
Thank you very much!
The test script is as follows:
import numpy as np
import matplotlib.pyplot as plt
a=np.random.randn(100,150)
fig,ax=plt.subplots()
im=ax.imshow(a)
fig.colorbar(im,anchor=(0.,0.5))
plt.show()
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Jody,
perfect - that work's fine.
Regards, Sappy85
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I am getting something, but the speckled stuff is all on one side, and all
monochromatic for most of the pcolormesh plot. I am using basemap 1.0.7 and
a development version of matplotlib. Your code looks correct, so I don't
know what is wrong. Probably worth filing a bug report:
https://github.com/matplotlib/basemap/issues
Ben Root
On Mon, Dec 8, 2014 at 7:24 PM, Timothy W. Hilton <th...@uc...>
wrote:
> Hello,
>
> I am experiencing strange behavior using mpl_toolkits.basemap.Basemap.
> My understanding is that pcolormesh is faster than pcolor, and thus
> preferable. Here is a minimal example (below) where I get a different
> plot from pcolormesh than from pcolor.
>
> On two systems (mac os x 10.9.5; Ubuntu 11.04 (GNU/Linux 2.6.32.28
> x86_64); basemap 1.0.7 on the mac and 1.0.8 on the Ubuntu machine; both
> using matplotlib 1.4.2) I get the expected grid of random colors from
> pcolor, but a monochrome plot from pcolormesh.
>
> Is this expected? Are there circumstances in which I should be using
> pcolor instead of pcolormesh? Is this a bug in matplotlib or in
> basemap?
>
> Many thanks!
>
> Tim
>
> --
>
> Timothy W. Hilton
> Assistant Project Scientist
> School of Engineering
> University of California, Merced
> th...@uc...
>
> #==================================================
> # minimal example
>
> import matplotlib.pyplot as plt
> from mpl_toolkits.basemap import Basemap
> import numpy as np
>
> def setup_map(ax):
>
> m = Basemap(width=8.0e6,
> height=6.5e6,
> projection='aeqd',
> lat_0=54,
> lon_0=-105,
> resolution='l',
> area_thresh=1000,
> rsphere=6371007.181000,
> fix_aspect=True,
> ax=ax)
> m.drawcoastlines()
> m.drawcountries()
> m.drawstates()
> return(m)
>
> # create pseudo-data with longitudes and latitudes
> lon, lat = np.meshgrid(np.arange(-180, 180),
> np.arange(90, -90, -1))
> data = np.random.rand(*lon.shape) * 100
>
> # two-panel figure
> fig, ax = plt.subplots(nrows=1, ncols=2)
>
> # plot pseoddata in left panel using pcolormesh
> m0 = setup_map(ax[0])
> cm = m0.pcolormesh(lon, lat, data, latlon=True,
> vmin=0.0, vmax=100.0, cmap=plt.cm.get_cmap("Blues"))
> plt.colorbar(cm, ax=ax[0])
> ax[0].set_title('pcolormesh')
>
> # plot pseoddata in left panel using pcolor
> m1 = setup_map(ax[1])
> cm = m1.pcolor(lon, lat, data, latlon=True,
> vmin=0.0, vmax=100.0, cmap=plt.cm.get_cmap("Blues"))
> plt.colorbar(cm, ax=ax[1])
> ax[1].set_title('pcolor')
>
> plt.show()
>
>
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A git clone would likely have set the default branch to master, which
tracks our development branch. Releases are tagged, and the latest release
has an active maintenance branch if you want to switch to that.
Cheers!
Ben Root
On Wed, Dec 10, 2014 at 10:24 AM, brown wrap <gr...@ya...> wrote:
> I am a bit confused. I installed the latest version of matplotlib from
> git, which should have been 1.4.2, but it shows up as 1.5.x. That is what
> PKG-INFO says as well in the source tree. I posted this yesterday, but I
> included an attachment.
>
> Greg
>
>
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>

I am a bit confused. I installed the latest version of matplotlib from git, which should have been 1.4.2, but it shows up as 1.5.x. That is what PKG-INFO says as well in the source tree. I posted this yesterday, but I included an attachment.
Greg

Not sure, as I don't use basemap too often, but I bet calling:
m.drawmapboundary(fill_color='w')
before clabel would do the trick
Cheers, Jody
> On Dec 9, 2014, at 16:35 PM, Sappy85 <rob...@gm...> wrote:
> 
> Hi @all,
> the problem seems to be solved. Thanks Jody! 
> What i have done:
> 
> 1.) check out the xlim and ylim after clabel call
> *xmin, xmax = plt.xlim() # return the current xlim
> ymin, ymax = plt.ylim() # return the current ylim
> print xmin,xmax
> print ymin,ymax*
> 
> 2.) use and set these limits before clabel call:
> *plt.xlim(0.0,6475051.47849)
> plt.ylim(0.0,4412688.31468)*
> 
> Yes, that's it. Very confusing! I do not understand why that only goes so
> awkward? 
> 
> Thanks so much!
> Sappy85
> 
> 
> 
> 
> 
> 
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> 
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 The latest version of Matplotlib is supposed to be 1.4.2, yet after the installation, when I checked the version, it came up 1.5.x.
Attached is the PKG-INFO I found in the source tree. Thanks.

Hi @all,
the problem seems to be solved. Thanks Jody! 
What i have done:
1.) check out the xlim and ylim after clabel call
*xmin, xmax = plt.xlim() # return the current xlim
ymin, ymax = plt.ylim() # return the current ylim
print xmin,xmax
print ymin,ymax*
2.) use and set these limits before clabel call:
*plt.xlim(0.0,6475051.47849)
plt.ylim(0.0,4412688.31468)*
Yes, that's it. Very confusing! I do not understand why that only goes so
awkward? 
Thanks so much!
Sappy85
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Ah... That was not clear. I just retried my first example (with
show->savefig) for all of the backends that I have available: Qt4Agg,
TkAgg, PS, PDF, pgf, Cairo, GTK3Cairo, GTK3Agg. All of the *Agg backends
show the same problem: the other backends work as expected. I will file a
bug report now.
Ryan
On Tue, Dec 9, 2014 at 9:50 AM, Benjamin Root <ben...@ou...> wrote:
> Interesting. Just to double-check, when you say that it only happens for
> the "agg" backend, are you saying that backends like "tkagg" are
> unaffected? I think at this point there is enough information here to file
> a bug report.
>
> Ben Root
>
> On Mon, Dec 8, 2014 at 6:14 PM, Ryan Nelson <rne...@gm...> wrote:
>
>> Final update.
>>
>> I've done some more searching, and found a couple more things. It seems
>> that this problem occurs with the backend set to "Agg"
>> (`matplotlib.use("agg")), so it isn't related to the interactive backends.
>> In addition, the problem does not occur with a random Polygon object added
>> to an axes; however, I do see the problem when the same polygon is added to
>> the axes as a PolyCollection. See code below.
>>
>> Ryan
>>
>> #####
>> import numpy as np
>> import matplotlib
>> matplotlib.use("Agg")
>> import matplotlib.pyplot as plt
>> from matplotlib.collections import PolyCollection
>>
>> x = np.linspace(0, np.pi*2, 1000)
>> y = np.sin(x)
>>
>> ax = plt.axes()
>> data =np.array([(0,0), (1,0), (1,1), (0,1)])
>>
>> # These three lines work fine.
>> poly = plt.Polygon(data)
>> poly.set_linewidth(0)
>> ax.add_patch(poly)
>>
>> # Comment out the three lines above
>> # Uncomment next three lines, does not work.
>> #col = PolyCollection([data])
>> #col.set_linewidth(0.0)
>> #ax.add_collection(col)
>>
>> plt.axis([-2, 2, -2, 2])
>> plt.savefig('junk')
>> #####
>>
>> On Mon, Dec 8, 2014 at 5:02 PM, Ryan Nelson <rne...@gm...>
>> wrote:
>>
>>> 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
>>>>>
>>>>>
>>>>>
>>>>
>>>
>>
>>
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>>
>>
>

Interesting. Just to double-check, when you say that it only happens for
the "agg" backend, are you saying that backends like "tkagg" are
unaffected? I think at this point there is enough information here to file
a bug report.
Ben Root
On Mon, Dec 8, 2014 at 6:14 PM, Ryan Nelson <rne...@gm...> wrote:
> Final update.
>
> I've done some more searching, and found a couple more things. It seems
> that this problem occurs with the backend set to "Agg"
> (`matplotlib.use("agg")), so it isn't related to the interactive backends.
> In addition, the problem does not occur with a random Polygon object added
> to an axes; however, I do see the problem when the same polygon is added to
> the axes as a PolyCollection. See code below.
>
> Ryan
>
> #####
> import numpy as np
> import matplotlib
> matplotlib.use("Agg")
> import matplotlib.pyplot as plt
> from matplotlib.collections import PolyCollection
>
> x = np.linspace(0, np.pi*2, 1000)
> y = np.sin(x)
>
> ax = plt.axes()
> data =np.array([(0,0), (1,0), (1,1), (0,1)])
>
> # These three lines work fine.
> poly = plt.Polygon(data)
> poly.set_linewidth(0)
> ax.add_patch(poly)
>
> # Comment out the three lines above
> # Uncomment next three lines, does not work.
> #col = PolyCollection([data])
> #col.set_linewidth(0.0)
> #ax.add_collection(col)
>
> plt.axis([-2, 2, -2, 2])
> plt.savefig('junk')
> #####
>
> On Mon, Dec 8, 2014 at 5:02 PM, Ryan Nelson <rne...@gm...> wrote:
>
>> 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
>>>>
>>>>
>>>>
>>>
>>
>
>
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>

Hello,
I am experiencing strange behavior using mpl_toolkits.basemap.Basemap.
My understanding is that pcolormesh is faster than pcolor, and thus
preferable. Here is a minimal example (below) where I get a different
plot from pcolormesh than from pcolor.
On two systems (mac os x 10.9.5; Ubuntu 11.04 (GNU/Linux 2.6.32.28
x86_64); basemap 1.0.7 on the mac and 1.0.8 on the Ubuntu machine; both
using matplotlib 1.4.2) I get the expected grid of random colors from
pcolor, but a monochrome plot from pcolormesh.
Is this expected? Are there circumstances in which I should be using
pcolor instead of pcolormesh? Is this a bug in matplotlib or in
basemap?
Many thanks!
Tim
--
Timothy W. Hilton
Assistant Project Scientist
School of Engineering
University of California, Merced
th...@uc... 
#==================================================
# minimal example
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
import numpy as np
def setup_map(ax):
 m = Basemap(width=8.0e6,
 height=6.5e6,
 projection='aeqd',
 lat_0=54,
 lon_0=-105,
 resolution='l',
 area_thresh=1000, 
 rsphere=6371007.181000,
 fix_aspect=True,
 ax=ax)
 m.drawcoastlines()
 m.drawcountries()
 m.drawstates()
 return(m)
# create pseudo-data with longitudes and latitudes
lon, lat = np.meshgrid(np.arange(-180, 180), 
 np.arange(90, -90, -1))
data = np.random.rand(*lon.shape) * 100
# two-panel figure
fig, ax = plt.subplots(nrows=1, ncols=2)
# plot pseoddata in left panel using pcolormesh
m0 = setup_map(ax[0])
cm = m0.pcolormesh(lon, lat, data, latlon=True, 
 vmin=0.0, vmax=100.0, cmap=plt.cm.get_cmap("Blues"))
plt.colorbar(cm, ax=ax[0])
ax[0].set_title('pcolormesh')
# plot pseoddata in left panel using pcolor
m1 = setup_map(ax[1])
cm = m1.pcolor(lon, lat, data, latlon=True, 
 vmin=0.0, vmax=100.0, cmap=plt.cm.get_cmap("Blues"))
plt.colorbar(cm, ax=ax[1])
ax[1].set_title('pcolor')
plt.show()

Final update.
I've done some more searching, and found a couple more things. It seems
that this problem occurs with the backend set to "Agg"
(`matplotlib.use("agg")), so it isn't related to the interactive backends.
In addition, the problem does not occur with a random Polygon object added
to an axes; however, I do see the problem when the same polygon is added to
the axes as a PolyCollection. See code below.
Ryan
#####
import numpy as np
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
from matplotlib.collections import PolyCollection
x = np.linspace(0, np.pi*2, 1000)
y = np.sin(x)
ax = plt.axes()
data =np.array([(0,0), (1,0), (1,1), (0,1)])
# These three lines work fine.
poly = plt.Polygon(data)
poly.set_linewidth(0)
ax.add_patch(poly)
# Comment out the three lines above
# Uncomment next three lines, does not work.
#col = PolyCollection([data])
#col.set_linewidth(0.0)
#ax.add_collection(col)
plt.axis([-2, 2, -2, 2])
plt.savefig('junk')
#####
On Mon, Dec 8, 2014 at 5:02 PM, Ryan Nelson <rne...@gm...> wrote:
> 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 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
>>> Sent from the matplotlib - users mailing list archive at Nabble.com.
>>>
>>>
>>> ------------------------------------------------------------------------------
>>> Download BIRT iHub F-Type - The Free Enterprise-Grade BIRT Server
>>> from Actuate! Instantly Supercharge Your Business Reports and Dashboards
>>> with Interactivity, Sharing, Native Excel Exports, App Integration & more
>>> Get technology previously reserved for billion-dollar corporations, FREE
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>>
>>
>>
>> ------------------------------------------------------------------------------
>> Download BIRT iHub F-Type - The Free Enterprise-Grade BIRT Server
>> from Actuate! Instantly Supercharge Your Business Reports and Dashboards
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>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>>
>

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.
>>
>>
>> ------------------------------------------------------------------------------
>> Download BIRT iHub F-Type - The Free Enterprise-Grade BIRT Server
>> from Actuate! Instantly Supercharge Your Business Reports and Dashboards
>> with Interactivity, Sharing, Native Excel Exports, App Integration & more
>> Get technology previously reserved for billion-dollar corporations, FREE
>>
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>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>
>
>
> ------------------------------------------------------------------------------
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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年12月04日 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
>
>
> ------------------------------------------------------------------------------
> Download BIRT iHub F-Type - The Free Enterprise-Grade BIRT Server
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> _______________________________________________
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> 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
> Sent from the matplotlib - users mailing list archive at Nabble.com.
>
>
> ------------------------------------------------------------------------------
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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 
> 
> 
> 
> --
> View this message in context: http://matplotlib.1069221.n5.nabble.com/Pyplot-contour-plot-clabel-padding-tp44554p44557.html
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> 
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