matplotlib-users Mailing List for matplotlib

yes, you should be able to do "conda update matplotlib" or something to
that effect.
On Mon, Sep 22, 2014 at 3:24 PM, Gabriele Brambilla <
gb....@gm...> wrote:
> 1.3.1
>
> I'm using Anaconda...do you know if do a package exist of Anaconda with
> 1.4.0?
>
> thanks
>
> Gabriele
>
>
>
> 2014年09月22日 17:47 GMT+02:00 Benjamin Root <ben...@ou...>:
>
>> quite likely. To know for sure, run the following in the command-line:
>>
>> python -c "import matplotlib; print matplotlib.__version__"
>>
>>
>> On Mon, Sep 22, 2014 at 11:42 AM, Gabriele Brambilla <
>> gb....@gm...> wrote:
>>
>>> If it returns this means that I have an older version?
>>>
>>> Traceback (most recent call last):
>>> File "dataMODEL.py", line 99, in <module>
>>> ax.scatter(np.log10(NP), np.log10(NB*10**12), np.log10(NL), c='b',
>>> marker='o
>>> ', depthshade=False)
>>> File "C:\Anaconda\lib\site-packages\mpl_toolkits\mplot3d\axes3d.py",
>>> line 2180
>>> , in scatter
>>> patches = Axes.scatter(self, xs, ys, s=s, c=c, *args, **kwargs)
>>> File "C:\Anaconda\lib\site-packages\matplotlib\axes.py", line 6312, in
>>> scatter
>>>
>>> collection.update(kwargs)
>>> File "C:\Anaconda\lib\site-packages\matplotlib\artist.py", line 739,
>>> in update
>>>
>>> raise AttributeError('Unknown property %s' % k)
>>> AttributeError: Unknown property depthshade
>>>
>>>
>>> 2014年09月22日 17:27 GMT+02:00 Benjamin Root <ben...@ou...>:
>>>
>>>> As of version 1.4.0, the 3d scatter plotting function gained the
>>>> "depthshade" argument that you can set to false.
>>>>
>>>> http://matplotlib.org/mpl_toolkits/mplot3d/tutorial.html#scatter-plots
>>>>
>>>> Cheers!
>>>> Ben Root
>>>>
>>>> On Mon, Sep 22, 2014 at 11:18 AM, Gabriele Brambilla <
>>>> gb....@gm...> wrote:
>>>>
>>>>> Hi I'm trying to use a 3d scatter plot.
>>>>>
>>>>> import matplotlib.pyplot as plt
>>>>> from mpl_toolkits.mplot3d import Axes3D
>>>>> import matplotlib.pyplot as plt
>>>>> from matplotlib import cm
>>>>>
>>>>> fig = plt.figure()
>>>>> ax = fig.add_subplot(111, projection='3d')
>>>>> ax.scatter(np.log10(NP), np.log10(NB*10**12), np.log10(NL), c='k')
>>>>> ax.scatter(np.log10(NPd), np.log10(NBd), np.log10(NLd), c='b')
>>>>>
>>>>> I would like that the dots that appear are all of the same color not
>>>>> in shades of black ('k') or shades of blue ('b') but I don't know how to do
>>>>> it.
>>>>>
>>>>> thanks
>>>>>
>>>>> Gabriele
>>>>>
>>>>>
>>>>> ------------------------------------------------------------------------------
>>>>> Meet PCI DSS 3.0 Compliance Requirements with EventLog Analyzer
>>>>> Achieve PCI DSS 3.0 Compliant Status with Out-of-the-box PCI DSS
>>>>> Reports
>>>>> Are you Audit-Ready for PCI DSS 3.0 Compliance? Download White paper
>>>>> Comply to PCI DSS 3.0 Requirement 10 and 11.5 with EventLog Analyzer
>>>>>
>>>>> http://pubads.g.doubleclick.net/gampad/clk?id=154622311&iu=/4140/ostg.clktrk
>>>>> _______________________________________________
>>>>> Matplotlib-users mailing list
>>>>> Mat...@li...
>>>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>>>
>>>>>
>>>>
>>>
>>
>

1.3.1
I'm using Anaconda...do you know if do a package exist of Anaconda with
1.4.0?
thanks
Gabriele
2014年09月22日 17:47 GMT+02:00 Benjamin Root <ben...@ou...>:
> quite likely. To know for sure, run the following in the command-line:
>
> python -c "import matplotlib; print matplotlib.__version__"
>
>
> On Mon, Sep 22, 2014 at 11:42 AM, Gabriele Brambilla <
> gb....@gm...> wrote:
>
>> If it returns this means that I have an older version?
>>
>> Traceback (most recent call last):
>> File "dataMODEL.py", line 99, in <module>
>> ax.scatter(np.log10(NP), np.log10(NB*10**12), np.log10(NL), c='b',
>> marker='o
>> ', depthshade=False)
>> File "C:\Anaconda\lib\site-packages\mpl_toolkits\mplot3d\axes3d.py",
>> line 2180
>> , in scatter
>> patches = Axes.scatter(self, xs, ys, s=s, c=c, *args, **kwargs)
>> File "C:\Anaconda\lib\site-packages\matplotlib\axes.py", line 6312, in
>> scatter
>>
>> collection.update(kwargs)
>> File "C:\Anaconda\lib\site-packages\matplotlib\artist.py", line 739, in
>> update
>>
>> raise AttributeError('Unknown property %s' % k)
>> AttributeError: Unknown property depthshade
>>
>>
>> 2014年09月22日 17:27 GMT+02:00 Benjamin Root <ben...@ou...>:
>>
>>> As of version 1.4.0, the 3d scatter plotting function gained the
>>> "depthshade" argument that you can set to false.
>>>
>>> http://matplotlib.org/mpl_toolkits/mplot3d/tutorial.html#scatter-plots
>>>
>>> Cheers!
>>> Ben Root
>>>
>>> On Mon, Sep 22, 2014 at 11:18 AM, Gabriele Brambilla <
>>> gb....@gm...> wrote:
>>>
>>>> Hi I'm trying to use a 3d scatter plot.
>>>>
>>>> import matplotlib.pyplot as plt
>>>> from mpl_toolkits.mplot3d import Axes3D
>>>> import matplotlib.pyplot as plt
>>>> from matplotlib import cm
>>>>
>>>> fig = plt.figure()
>>>> ax = fig.add_subplot(111, projection='3d')
>>>> ax.scatter(np.log10(NP), np.log10(NB*10**12), np.log10(NL), c='k')
>>>> ax.scatter(np.log10(NPd), np.log10(NBd), np.log10(NLd), c='b')
>>>>
>>>> I would like that the dots that appear are all of the same color not in
>>>> shades of black ('k') or shades of blue ('b') but I don't know how to do it.
>>>>
>>>> thanks
>>>>
>>>> Gabriele
>>>>
>>>>
>>>> ------------------------------------------------------------------------------
>>>> Meet PCI DSS 3.0 Compliance Requirements with EventLog Analyzer
>>>> Achieve PCI DSS 3.0 Compliant Status with Out-of-the-box PCI DSS Reports
>>>> Are you Audit-Ready for PCI DSS 3.0 Compliance? Download White paper
>>>> Comply to PCI DSS 3.0 Requirement 10 and 11.5 with EventLog Analyzer
>>>>
>>>> http://pubads.g.doubleclick.net/gampad/clk?id=154622311&iu=/4140/ostg.clktrk
>>>> _______________________________________________
>>>> Matplotlib-users mailing list
>>>> Mat...@li...
>>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>>
>>>>
>>>
>>
>

I guess I could change my API a bit to allow for data that would better fit
ax.plot3d. I suppose plot3d is really what I'm trying to make, where I'd
just pass 5 evenly spaced curves from my dataset.
If you think of a hacky solution even, can you shoot me a message?
Thanks for your help and the heads up about the graphics bugs.
On Mon, Sep 22, 2014 at 12:39 PM, Benjamin Root <ben...@ou...> wrote:
> Sorry, that isn't possible in the current design. Instead, I would suggest
> making a line plot on top of surface mimicking this. Although, depending on
> the shape of the surface, this may not work out well as mplot3d may not
> properly compose such a scene of mixed objects.
>
> Also, as a side note, be careful saving figures with zero linewidths as
> certain vector backends (e.g., pdf, ps) don't properly respect such
> linewidths. I think most of such bugs were fixed for v1.4.0, but there were
> a few additional bugs that are going into the upcoming v1.4.1 release.
>
> Cheers!
> Ben Root
>
> On Mon, Sep 22, 2014 at 12:29 PM, Adam Hughes <hug...@gm...>
> wrote:
>
>> Thanks benjamin. Not sure how I overlooked this!
>>
>> You wouldn't happen to know how to remove the cstrides while keeping the
>> rstrides in tact? By strides, I guess I don't mean strides per-se, but the
>> contour lines themselves that run over the surface.
>>
>> On Mon, Sep 22, 2014 at 9:55 AM, Benjamin Root <ben...@ou...> wrote:
>>
>>> I think you can just set the linewidth to zero like in these examples:
>>>
>>> http://matplotlib.org/examples/mplot3d/surface3d_demo.html
>>> http://matplotlib.org/examples/mplot3d/surface3d_demo3.html
>>>
>>> Cheers!
>>> Ben Root
>>>
>>> On Sat, Sep 20, 2014 at 7:44 PM, Adam Hughes <hug...@gm...>
>>> wrote:
>>>
>>>> Also, is it possible to change the stride color/opacity? Not for this
>>>> plot in particular, but for surface plots, I'd rather not have dense black
>>>> strides on my surface. Can't find the right keyword call through the 3d
>>>> API. Sorry if I'm overlooking something obvious in the docs
>>>>
>>>> On Sat, Sep 20, 2014 at 7:31 PM, Adam Hughes <hug...@gm...>
>>>> wrote:
>>>>
>>>>> Hi,
>>>>>
>>>>> I was using wireframe to plot my spectroscopy data, and noticed if I
>>>>> choose a large R-stride, I somewhat unexpectedly get this really helpful
>>>>> evenly spaced spectral plot (attached).
>>>>>
>>>>> The only issue is that there's still the cstride connecting some of
>>>>> the peaks. I'd like to get rid of this, but it seems that at least one
>>>>> cstride is necessary. Anyone have any hacking ideas on how to get rid of
>>>>> this?
>>>>>
>>>>
>>>>
>>>>
>>>> ------------------------------------------------------------------------------
>>>> Slashdot TV. Video for Nerds. Stuff that Matters.
>>>>
>>>> http://pubads.g.doubleclick.net/gampad/clk?id=160591471&iu=/4140/ostg.clktrk
>>>> _______________________________________________
>>>> Matplotlib-users mailing list
>>>> Mat...@li...
>>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>>
>>>>
>>>
>>
>

Sorry, that isn't possible in the current design. Instead, I would suggest
making a line plot on top of surface mimicking this. Although, depending on
the shape of the surface, this may not work out well as mplot3d may not
properly compose such a scene of mixed objects.
Also, as a side note, be careful saving figures with zero linewidths as
certain vector backends (e.g., pdf, ps) don't properly respect such
linewidths. I think most of such bugs were fixed for v1.4.0, but there were
a few additional bugs that are going into the upcoming v1.4.1 release.
Cheers!
Ben Root
On Mon, Sep 22, 2014 at 12:29 PM, Adam Hughes <hug...@gm...>
wrote:
> Thanks benjamin. Not sure how I overlooked this!
>
> You wouldn't happen to know how to remove the cstrides while keeping the
> rstrides in tact? By strides, I guess I don't mean strides per-se, but the
> contour lines themselves that run over the surface.
>
> On Mon, Sep 22, 2014 at 9:55 AM, Benjamin Root <ben...@ou...> wrote:
>
>> I think you can just set the linewidth to zero like in these examples:
>>
>> http://matplotlib.org/examples/mplot3d/surface3d_demo.html
>> http://matplotlib.org/examples/mplot3d/surface3d_demo3.html
>>
>> Cheers!
>> Ben Root
>>
>> On Sat, Sep 20, 2014 at 7:44 PM, Adam Hughes <hug...@gm...>
>> wrote:
>>
>>> Also, is it possible to change the stride color/opacity? Not for this
>>> plot in particular, but for surface plots, I'd rather not have dense black
>>> strides on my surface. Can't find the right keyword call through the 3d
>>> API. Sorry if I'm overlooking something obvious in the docs
>>>
>>> On Sat, Sep 20, 2014 at 7:31 PM, Adam Hughes <hug...@gm...>
>>> wrote:
>>>
>>>> Hi,
>>>>
>>>> I was using wireframe to plot my spectroscopy data, and noticed if I
>>>> choose a large R-stride, I somewhat unexpectedly get this really helpful
>>>> evenly spaced spectral plot (attached).
>>>>
>>>> The only issue is that there's still the cstride connecting some of the
>>>> peaks. I'd like to get rid of this, but it seems that at least one cstride
>>>> is necessary. Anyone have any hacking ideas on how to get rid of this?
>>>>
>>>
>>>
>>>
>>> ------------------------------------------------------------------------------
>>> Slashdot TV. Video for Nerds. Stuff that Matters.
>>>
>>> http://pubads.g.doubleclick.net/gampad/clk?id=160591471&iu=/4140/ostg.clktrk
>>> _______________________________________________
>>> Matplotlib-users mailing list
>>> Mat...@li...
>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>
>>>
>>
>

Thanks benjamin. Not sure how I overlooked this!
You wouldn't happen to know how to remove the cstrides while keeping the
rstrides in tact? By strides, I guess I don't mean strides per-se, but the
contour lines themselves that run over the surface.
On Mon, Sep 22, 2014 at 9:55 AM, Benjamin Root <ben...@ou...> wrote:
> I think you can just set the linewidth to zero like in these examples:
>
> http://matplotlib.org/examples/mplot3d/surface3d_demo.html
> http://matplotlib.org/examples/mplot3d/surface3d_demo3.html
>
> Cheers!
> Ben Root
>
> On Sat, Sep 20, 2014 at 7:44 PM, Adam Hughes <hug...@gm...>
> wrote:
>
>> Also, is it possible to change the stride color/opacity? Not for this
>> plot in particular, but for surface plots, I'd rather not have dense black
>> strides on my surface. Can't find the right keyword call through the 3d
>> API. Sorry if I'm overlooking something obvious in the docs
>>
>> On Sat, Sep 20, 2014 at 7:31 PM, Adam Hughes <hug...@gm...>
>> wrote:
>>
>>> Hi,
>>>
>>> I was using wireframe to plot my spectroscopy data, and noticed if I
>>> choose a large R-stride, I somewhat unexpectedly get this really helpful
>>> evenly spaced spectral plot (attached).
>>>
>>> The only issue is that there's still the cstride connecting some of the
>>> peaks. I'd like to get rid of this, but it seems that at least one cstride
>>> is necessary. Anyone have any hacking ideas on how to get rid of this?
>>>
>>
>>
>>
>> ------------------------------------------------------------------------------
>> Slashdot TV. Video for Nerds. Stuff that Matters.
>>
>> http://pubads.g.doubleclick.net/gampad/clk?id=160591471&iu=/4140/ostg.clktrk
>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>>
>

Hi,
I want to show some points on a world map. But the color of a point is
linked to the value at the point. Any idea why the code below does not give
what I want (same color, no legend)?
Many thanks,
Tom
from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
import numpy as np
lats = [47.8, -54.85, 47.0544, 44.18, 47.42, 46.55]
lons = [11.02, -68.32, 12.9583, 10.7, 10.98, 7.99]
scores = [4.93657698397, -31.0626756529, 35.2049971001, 23.1060270438,
12.5139213403, 17.3946319493]
map = Basemap(projection = 'mill')
map.drawcoastlines()
map.drawmapboundary()
for lat, lon, score in zip(lats, lons, scores):
 print('Score at (%f, %f) is %f' % (lat, lon, score))
 x, y = map(lon, lat) # Notice x = lon, y = lat
 map.scatter(x, y, marker = 'o',
 s = 500,
 c = score,
 cmap = plt.get_cmap('rainbow'))
plt.legend()
plt.show()

quite likely. To know for sure, run the following in the command-line:
python -c "import matplotlib; print matplotlib.__version__"
On Mon, Sep 22, 2014 at 11:42 AM, Gabriele Brambilla <
gb....@gm...> wrote:
> If it returns this means that I have an older version?
>
> Traceback (most recent call last):
> File "dataMODEL.py", line 99, in <module>
> ax.scatter(np.log10(NP), np.log10(NB*10**12), np.log10(NL), c='b',
> marker='o
> ', depthshade=False)
> File "C:\Anaconda\lib\site-packages\mpl_toolkits\mplot3d\axes3d.py",
> line 2180
> , in scatter
> patches = Axes.scatter(self, xs, ys, s=s, c=c, *args, **kwargs)
> File "C:\Anaconda\lib\site-packages\matplotlib\axes.py", line 6312, in
> scatter
>
> collection.update(kwargs)
> File "C:\Anaconda\lib\site-packages\matplotlib\artist.py", line 739, in
> update
>
> raise AttributeError('Unknown property %s' % k)
> AttributeError: Unknown property depthshade
>
>
> 2014年09月22日 17:27 GMT+02:00 Benjamin Root <ben...@ou...>:
>
>> As of version 1.4.0, the 3d scatter plotting function gained the
>> "depthshade" argument that you can set to false.
>>
>> http://matplotlib.org/mpl_toolkits/mplot3d/tutorial.html#scatter-plots
>>
>> Cheers!
>> Ben Root
>>
>> On Mon, Sep 22, 2014 at 11:18 AM, Gabriele Brambilla <
>> gb....@gm...> wrote:
>>
>>> Hi I'm trying to use a 3d scatter plot.
>>>
>>> import matplotlib.pyplot as plt
>>> from mpl_toolkits.mplot3d import Axes3D
>>> import matplotlib.pyplot as plt
>>> from matplotlib import cm
>>>
>>> fig = plt.figure()
>>> ax = fig.add_subplot(111, projection='3d')
>>> ax.scatter(np.log10(NP), np.log10(NB*10**12), np.log10(NL), c='k')
>>> ax.scatter(np.log10(NPd), np.log10(NBd), np.log10(NLd), c='b')
>>>
>>> I would like that the dots that appear are all of the same color not in
>>> shades of black ('k') or shades of blue ('b') but I don't know how to do it.
>>>
>>> thanks
>>>
>>> Gabriele
>>>
>>>
>>> ------------------------------------------------------------------------------
>>> Meet PCI DSS 3.0 Compliance Requirements with EventLog Analyzer
>>> Achieve PCI DSS 3.0 Compliant Status with Out-of-the-box PCI DSS Reports
>>> Are you Audit-Ready for PCI DSS 3.0 Compliance? Download White paper
>>> Comply to PCI DSS 3.0 Requirement 10 and 11.5 with EventLog Analyzer
>>>
>>> http://pubads.g.doubleclick.net/gampad/clk?id=154622311&iu=/4140/ostg.clktrk
>>> _______________________________________________
>>> Matplotlib-users mailing list
>>> Mat...@li...
>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>>
>>>
>>
>

If it returns this means that I have an older version?
Traceback (most recent call last):
 File "dataMODEL.py", line 99, in <module>
 ax.scatter(np.log10(NP), np.log10(NB*10**12), np.log10(NL), c='b',
marker='o
', depthshade=False)
 File "C:\Anaconda\lib\site-packages\mpl_toolkits\mplot3d\axes3d.py", line
2180
, in scatter
 patches = Axes.scatter(self, xs, ys, s=s, c=c, *args, **kwargs)
 File "C:\Anaconda\lib\site-packages\matplotlib\axes.py", line 6312, in
scatter
 collection.update(kwargs)
 File "C:\Anaconda\lib\site-packages\matplotlib\artist.py", line 739, in
update
 raise AttributeError('Unknown property %s' % k)
AttributeError: Unknown property depthshade
2014年09月22日 17:27 GMT+02:00 Benjamin Root <ben...@ou...>:
> As of version 1.4.0, the 3d scatter plotting function gained the
> "depthshade" argument that you can set to false.
>
> http://matplotlib.org/mpl_toolkits/mplot3d/tutorial.html#scatter-plots
>
> Cheers!
> Ben Root
>
> On Mon, Sep 22, 2014 at 11:18 AM, Gabriele Brambilla <
> gb....@gm...> wrote:
>
>> Hi I'm trying to use a 3d scatter plot.
>>
>> import matplotlib.pyplot as plt
>> from mpl_toolkits.mplot3d import Axes3D
>> import matplotlib.pyplot as plt
>> from matplotlib import cm
>>
>> fig = plt.figure()
>> ax = fig.add_subplot(111, projection='3d')
>> ax.scatter(np.log10(NP), np.log10(NB*10**12), np.log10(NL), c='k')
>> ax.scatter(np.log10(NPd), np.log10(NBd), np.log10(NLd), c='b')
>>
>> I would like that the dots that appear are all of the same color not in
>> shades of black ('k') or shades of blue ('b') but I don't know how to do it.
>>
>> thanks
>>
>> Gabriele
>>
>>
>> ------------------------------------------------------------------------------
>> Meet PCI DSS 3.0 Compliance Requirements with EventLog Analyzer
>> Achieve PCI DSS 3.0 Compliant Status with Out-of-the-box PCI DSS Reports
>> Are you Audit-Ready for PCI DSS 3.0 Compliance? Download White paper
>> Comply to PCI DSS 3.0 Requirement 10 and 11.5 with EventLog Analyzer
>>
>> http://pubads.g.doubleclick.net/gampad/clk?id=154622311&iu=/4140/ostg.clktrk
>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>>
>

As of version 1.4.0, the 3d scatter plotting function gained the
"depthshade" argument that you can set to false.
http://matplotlib.org/mpl_toolkits/mplot3d/tutorial.html#scatter-plots
Cheers!
Ben Root
On Mon, Sep 22, 2014 at 11:18 AM, Gabriele Brambilla <
gb....@gm...> wrote:
> Hi I'm trying to use a 3d scatter plot.
>
> import matplotlib.pyplot as plt
> from mpl_toolkits.mplot3d import Axes3D
> import matplotlib.pyplot as plt
> from matplotlib import cm
>
> fig = plt.figure()
> ax = fig.add_subplot(111, projection='3d')
> ax.scatter(np.log10(NP), np.log10(NB*10**12), np.log10(NL), c='k')
> ax.scatter(np.log10(NPd), np.log10(NBd), np.log10(NLd), c='b')
>
> I would like that the dots that appear are all of the same color not in
> shades of black ('k') or shades of blue ('b') but I don't know how to do it.
>
> thanks
>
> Gabriele
>
>
> ------------------------------------------------------------------------------
> Meet PCI DSS 3.0 Compliance Requirements with EventLog Analyzer
> Achieve PCI DSS 3.0 Compliant Status with Out-of-the-box PCI DSS Reports
> Are you Audit-Ready for PCI DSS 3.0 Compliance? Download White paper
> Comply to PCI DSS 3.0 Requirement 10 and 11.5 with EventLog Analyzer
>
> http://pubads.g.doubleclick.net/gampad/clk?id=154622311&iu=/4140/ostg.clktrk
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>

Hi I'm trying to use a 3d scatter plot.
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from matplotlib import cm
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.scatter(np.log10(NP), np.log10(NB*10**12), np.log10(NL), c='k')
ax.scatter(np.log10(NPd), np.log10(NBd), np.log10(NLd), c='b')
I would like that the dots that appear are all of the same color not in
shades of black ('k') or shades of blue ('b') but I don't know how to do it.
thanks
Gabriele

In the example you provided, you tried to broadcase two 1D arrays against
each other, which isn't what you want because all you will get is another
1-D array. Broadcasting automatically repeats data for you along a
dimension. It is rare to actually call np.broadcast() as it usually happens
automatically. Perhaps you should take your questions about broadcasting
over to the numpy discussion mailing list where somebody there might be
able to better explain it than I.
Cheers!
Ben Root
On Mon, Sep 22, 2014 at 6:42 AM, Raffaele Quarta <raf...@li...
> wrote:
> Hi all,
>
> somebody can show me with an example how can I set the numpy's
> broadcasting feature?
>
> Actually, I'm using 'meshgrid' in the script but I knew that it takes a
> lot of time to have the plot.
>
> Thank you.
>
> Raf
>
>
>
> -----Original Message-----
> From: Raffaele Quarta [mailto:raf...@li...
> <raf...@li...>]
> Sent: Tue 9/9/2014 3:55 PM
> To: Benjamin Root; Ryan Nelson
> Cc: Matplotlib Users
> Subject: Re: [Matplotlib-users] Plotting large file (NetCDF)
>
> Hi Ben and Ryan,
>
> I will try to figure out as it works.
>
> Thank you.
>
> Regards,
>
> Raf
>
>
> -----Original Message-----
> From: ben...@gm... on behalf of Benjamin Root
> Sent: Tue 9/9/2014 3:25 PM
> To: Ryan Nelson
> Cc: Raffaele Quarta; Matplotlib Users
> Subject: Re: [Matplotlib-users] Plotting large file (NetCDF)
>
> Most of the time, you will not need to use meshgrid. Take advantage of
> numpy's broadcasting feature:
> http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html
> It saves *significantly* on memory and processing time. Most of
> Matplotlib's plotting functions work well with broadcastable inputs, so
> that is a great way to save on memory. NumPy's ogrid is also a neat tool
> for generating broadcastable grids.
>
> When I get a chance, I'll look through the script for any other obvious
> savers.
>
> Cheers!
> Ben Root
>
>
> On Tue, Sep 9, 2014 at 9:02 AM, Ryan Nelson <rne...@gm...> wrote:
>
> > Raffaele,
> >
> > As Ben pointed out, you might be creating a lot of in memory Numpy arrays
> > that you probably don't need/want.
> >
> > For example, I think (?) slicing all of the variable below:
> > lons = fh.variables['lon'][:]
> > is making a copy of all that (mmap'ed) data as a Numpy array in memory.
> > Get rid of the slice ([:]). Of course, these variables are not Numpy
> > arrays, so you'll have to change some of your code. For example:
> > lon_0 = lons.mean()
> > Will have to become:
> > lon_0 = np.mean( lons )
> >
> > If lats and lons are very large sets of data, then meshgrid will make two
> > very, very large arrays in memory.
> > For example, try this:
> > np.meshgrid(np.arange(5), np.arange(5))
> > The output is two much larger arrays:
> > [array([[0, 1, 2, 3, 4],
> > [0, 1, 2, 3, 4],
> > [0, 1, 2, 3, 4],
> > [0, 1, 2, 3, 4],
> > [0, 1, 2, 3, 4]]),
> > array([[0, 0, 0, 0, 0],
> > [1, 1, 1, 1, 1],
> > [2, 2, 2, 2, 2],
> > [3, 3, 3, 3, 3],
> > [4, 4, 4, 4, 4]])]
> > I don't know Basemap at all, so I don't know if this is necessary. You
> > might be able to force the meshgrid output into a memmap file, but I
> don't
> > know how to do that right now. Perhaps someone else has some suggestions.
> >
> > Hope that helps.
> >
> > Ryan
> >
> >
> >
> >
> > On Tue, Sep 9, 2014 at 4:07 AM, Raffaele Quarta <
> > raf...@li...> wrote:
> >
> >> Hi Jody and Ben,
> >>
> >> thanks for your answers.
> >> I tried to use pcolormesh instead of pcolor and the result is very good!
> >> For what concern with the memory system problem, I wasn't able to solve
> it.
> >> When I tried to use the bigger file, I got the same problem. Attached
> you
> >> will find the script that I'm using to make the plot. May be, I didn't
> >> understand very well how can I use the mmap function.
> >>
> >> Regards,
> >>
> >> Raffaele.
> >>
> >>
> >> -----Original Message-----
> >> From: Jody Klymak [mailto:jk...@uv... <jk...@uv...> <
> jk...@uv...>]
> >> Sent: Mon 9/8/2014 5:46 PM
> >> To: Benjamin Root
> >> Cc: Raffaele Quarta; Matplotlib Users
> >> Subject: Re: [Matplotlib-users] Plotting large file (NetCDF)
> >>
> >> It looks like you are calling `pcolor`. Can I suggest you try
> >> `pcolormesh`? ii
> >>
> >> 75 Mb is not a big file!
> >>
> >> Cheers, Jody
> >>
> >>
> >> On Sep 8, 2014, at 7:38 AM, Benjamin Root <ben...@ou...> wrote:
> >>
> >> > (Keeping this on the mailing list so that others can benefit)
> >> >
> >> > What might be happening is that you are keeping around too many numpy
> >> arrays in memory than you actually need. Take advantage of memmapping,
> >> which most netcdf tools provide by default. This keeps the data on disk
> >> rather than in RAM. Second, for very large images, I would suggest
> either
> >> pcolormesh() or just simply imshow() instead of pcolor() as they are
> more
> >> way more efficient than pcolor(). In addition, it sounds like you are
> >> dealing with re-sampled data ("at different zoom levels"). Does this
> mean
> >> that you are re-running contour on re-sampled data? I am not sure what
> the
> >> benefit of doing that is if one could just simply do the contour once at
> >> the highest resolution.
> >> >
> >> > Without seeing any code, though, I can only provide generic
> suggestions.
> >> >
> >> > Cheers!
> >> > Ben Root
> >> >
> >> >
> >> > On Mon, Sep 8, 2014 at 10:12 AM, Raffaele Quarta <
> >> raf...@li...> wrote:
> >> > Hi Ben,
> >> >
> >> > sorry for the few details that I gave to you. I'm trying to make a
> >> contour plot of a variable at different zoom levels by using high
> >> resolution data. The aim is to obtain .PNG output images. Actually, I'm
> >> working with big data (NetCDF file, dimension is about 75Mb). The
> current
> >> Matplotlib version on my UBUNTU 14.04 machine is the 1.3.1 one. My
> system
> >> has a RAM capacity of 8Gb.
> >> > Actually, I'm dealing with memory system problems when I try to make a
> >> plot. I got the error message as follow:
> >> >
> >> > --------------------------------------------
> >> > cs = m.pcolor(xi,yi,np.squeeze(t))
> >> > File
> "/usr/lib/pymodules/python2.7/mpl_toolkits/basemap/__init__.py",
> >> line 521, in with_transform
> >> > return plotfunc(self,x,y,data,*args,**kwargs)
> >> > File
> "/usr/lib/pymodules/python2.7/mpl_toolkits/basemap/__init__.py",
> >> line 3375, in pcolor
> >> > x = ma.masked_values(np.where(x > 1.e20,1.e20,x), 1.e20)
> >> > File "/usr/lib/python2.7/dist-packages/numpy/ma/core.py", line 2195,
> >> in masked_values
> >> > condition = umath.less_equal(mabs(xnew - value), atol + rtol *
> >> mabs(value))
> >> > MemoryError
> >> > --------------------------------------------
> >> >
> >> > Otherwise, when I try to make a plot of smaller file (such as 5Mb), it
> >> works very well. I believe that it's not something of wrong in the
> script.
> >> It might be a memory system problem.
> >> > I hope that my message is more clear now.
> >> >
> >> > Thanks for the help.
> >> >
> >> > Regards,
> >> >
> >> > Raffaele
> >> >
> >> > -----------------------------------------
> >> >
> >> > Sent: Mon 9/8/2014 3:19 PM
> >> > To: Raffaele Quarta
> >> > Cc: Matplotlib Users
> >> > Subject: Re: [Matplotlib-users] Plotting large file (NetCDF)
> >> >
> >> >
> >> >
> >> > You will need to be more specific... much more specific. What kind of
> >> plot
> >> > are you making? How big is your data? What version of matplotlib are
> you
> >> > using? How much RAM do you have available compared to the amount of
> data
> >> > (most slowdowns are actually due to swap-thrashing issues). Matplotlib
> >> can
> >> > be used for large data, but there exists some speciality tools for the
> >> > truly large datasets. The solution depends on the situation.
> >> >
> >> > Ben Root
> >> >
> >> > On Mon, Sep 8, 2014 at 7:45 AM, Raffaele Quarta <
> >> raf...@li...>
> >> > wrote:
> >> >
> >> > > Hi,
> >> > >
> >> > > I'm working with NetCDF format. When I try to make a plot of very
> >> large
> >> > > file, I have to wait for a long time for plotting. How can I solve
> >> this?
> >> > > Isn't there a solution for this problem?
> >> > >
> >> > > Raffaele
> >> > >
> >> > > --
> >> > > This email was Virus checked by Astaro Security Gateway.
> >> http://www.sophos.com
> >> > >
> >> > >
> >> > >
> >> > >
> >>
> ------------------------------------------------------------------------------
> >> > > Want excitement?
> >> > > Manually upgrade your production database.
> >> > > When you want reliability, choose Perforce
> >> > > Perforce version control. Predictably reliable.
> >> > >
> >> > >
> >>
> http://pubads.g.doubleclick.net/gampad/clk?id=157508191&iu=/4140/ostg.clktrk
> >> > > _______________________________________________
> >> > > Matplotlib-users mailing list
> >> > > Mat...@li...
> >> > > https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> >> > >
> >> > >
> >> >
> >> > --
> >> > This email was Virus checked by Astaro Security Gateway.
> >> http://www.sophos.com
> >> >
> >> >
> >> >
> >> >
> >>
> ------------------------------------------------------------------------------
> >> > Want excitement?
> >> > Manually upgrade your production database.
> >> > When you want reliability, choose Perforce
> >> > Perforce version control. Predictably reliable.
> >> >
> >>
> http://pubads.g.doubleclick.net/gampad/clk?id=157508191&iu=/4140/ostg.clktrk_______________________________________________
> >> > Matplotlib-users mailing list
> >> > Mat...@li...
> >> > https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> >>
> >> --
> >> Jody Klymak
> >> http://web.uvic.ca/~jklymak/
> >>
> >>
> >>
> >>
> >>
> >>
> >>
> >>
> >>
> >>
> ------------------------------------------------------------------------------
> >> Want excitement?
> >> Manually upgrade your production database.
> >> When you want reliability, choose Perforce.
> >> Perforce version control. Predictably reliable.
> >>
> >>
> http://pubads.g.doubleclick.net/gampad/clk?id=157508191&iu=/4140/ostg.clktrk
> >> _______________________________________________
> >> Matplotlib-users mailing list
> >> Mat...@li...
> >> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> >>
> >>
> >
> >
> >
> ------------------------------------------------------------------------------
> > Want excitement?
> > Manually upgrade your production database.
> > When you want reliability, choose Perforce.
> > Perforce version control. Predictably reliable.
> >
> >
> http://pubads.g.doubleclick.net/gampad/clk?id=157508191&iu=/4140/ostg.clktrk
> > _______________________________________________
> > Matplotlib-users mailing list
> > Mat...@li...
> > https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> >
> >
>
>
> --
> This email was Virus checked by Astaro Security Gateway.
> http://www.sophos.com
>
>
>
>
>
>
>
>
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>

I think you can just set the linewidth to zero like in these examples:
http://matplotlib.org/examples/mplot3d/surface3d_demo.html
http://matplotlib.org/examples/mplot3d/surface3d_demo3.html
Cheers!
Ben Root
On Sat, Sep 20, 2014 at 7:44 PM, Adam Hughes <hug...@gm...> wrote:
> Also, is it possible to change the stride color/opacity? Not for this
> plot in particular, but for surface plots, I'd rather not have dense black
> strides on my surface. Can't find the right keyword call through the 3d
> API. Sorry if I'm overlooking something obvious in the docs
>
> On Sat, Sep 20, 2014 at 7:31 PM, Adam Hughes <hug...@gm...>
> wrote:
>
>> Hi,
>>
>> I was using wireframe to plot my spectroscopy data, and noticed if I
>> choose a large R-stride, I somewhat unexpectedly get this really helpful
>> evenly spaced spectral plot (attached).
>>
>> The only issue is that there's still the cstride connecting some of the
>> peaks. I'd like to get rid of this, but it seems that at least one cstride
>> is necessary. Anyone have any hacking ideas on how to get rid of this?
>>
>
>
>
> ------------------------------------------------------------------------------
> Slashdot TV. Video for Nerds. Stuff that Matters.
>
> http://pubads.g.doubleclick.net/gampad/clk?id=160591471&iu=/4140/ostg.clktrk
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>

Hi all,
somebody can show me with an example how can I set the numpy's broadcasting feature?
Actually, I'm using 'meshgrid' in the script but I knew that it takes a lot of time to have the plot.
Thank you.
Raf
-----Original Message-----
From: Raffaele Quarta [mailto:raf...@li...]
Sent: Tue 9/9/2014 3:55 PM
To: Benjamin Root; Ryan Nelson
Cc: Matplotlib Users
Subject: Re: [Matplotlib-users] Plotting large file (NetCDF)
 
Hi Ben and Ryan,
I will try to figure out as it works. 
Thank you.
Regards, 
Raf
-----Original Message-----
From: ben...@gm... on behalf of Benjamin Root
Sent: Tue 9/9/2014 3:25 PM
To: Ryan Nelson
Cc: Raffaele Quarta; Matplotlib Users
Subject: Re: [Matplotlib-users] Plotting large file (NetCDF)
 
Most of the time, you will not need to use meshgrid. Take advantage of
numpy's broadcasting feature:
http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html
It saves *significantly* on memory and processing time. Most of
Matplotlib's plotting functions work well with broadcastable inputs, so
that is a great way to save on memory. NumPy's ogrid is also a neat tool
for generating broadcastable grids.
When I get a chance, I'll look through the script for any other obvious
savers.
Cheers!
Ben Root
On Tue, Sep 9, 2014 at 9:02 AM, Ryan Nelson <rne...@gm...> wrote:
> Raffaele,
>
> As Ben pointed out, you might be creating a lot of in memory Numpy arrays
> that you probably don't need/want.
>
> For example, I think (?) slicing all of the variable below:
> lons = fh.variables['lon'][:]
> is making a copy of all that (mmap'ed) data as a Numpy array in memory.
> Get rid of the slice ([:]). Of course, these variables are not Numpy
> arrays, so you'll have to change some of your code. For example:
> lon_0 = lons.mean()
> Will have to become:
> lon_0 = np.mean( lons )
>
> If lats and lons are very large sets of data, then meshgrid will make two
> very, very large arrays in memory.
> For example, try this:
> np.meshgrid(np.arange(5), np.arange(5))
> The output is two much larger arrays:
> [array([[0, 1, 2, 3, 4],
> [0, 1, 2, 3, 4],
> [0, 1, 2, 3, 4],
> [0, 1, 2, 3, 4],
> [0, 1, 2, 3, 4]]),
> array([[0, 0, 0, 0, 0],
> [1, 1, 1, 1, 1],
> [2, 2, 2, 2, 2],
> [3, 3, 3, 3, 3],
> [4, 4, 4, 4, 4]])]
> I don't know Basemap at all, so I don't know if this is necessary. You
> might be able to force the meshgrid output into a memmap file, but I don't
> know how to do that right now. Perhaps someone else has some suggestions.
>
> Hope that helps.
>
> Ryan
>
>
>
>
> On Tue, Sep 9, 2014 at 4:07 AM, Raffaele Quarta <
> raf...@li...> wrote:
>
>> Hi Jody and Ben,
>>
>> thanks for your answers.
>> I tried to use pcolormesh instead of pcolor and the result is very good!
>> For what concern with the memory system problem, I wasn't able to solve it.
>> When I tried to use the bigger file, I got the same problem. Attached you
>> will find the script that I'm using to make the plot. May be, I didn't
>> understand very well how can I use the mmap function.
>>
>> Regards,
>>
>> Raffaele.
>>
>>
>> -----Original Message-----
>> From: Jody Klymak [mailto:jk...@uv... <jk...@uv...>]
>> Sent: Mon 9/8/2014 5:46 PM
>> To: Benjamin Root
>> Cc: Raffaele Quarta; Matplotlib Users
>> Subject: Re: [Matplotlib-users] Plotting large file (NetCDF)
>>
>> It looks like you are calling `pcolor`. Can I suggest you try
>> `pcolormesh`? ii
>>
>> 75 Mb is not a big file!
>>
>> Cheers, Jody
>>
>>
>> On Sep 8, 2014, at 7:38 AM, Benjamin Root <ben...@ou...> wrote:
>>
>> > (Keeping this on the mailing list so that others can benefit)
>> >
>> > What might be happening is that you are keeping around too many numpy
>> arrays in memory than you actually need. Take advantage of memmapping,
>> which most netcdf tools provide by default. This keeps the data on disk
>> rather than in RAM. Second, for very large images, I would suggest either
>> pcolormesh() or just simply imshow() instead of pcolor() as they are more
>> way more efficient than pcolor(). In addition, it sounds like you are
>> dealing with re-sampled data ("at different zoom levels"). Does this mean
>> that you are re-running contour on re-sampled data? I am not sure what the
>> benefit of doing that is if one could just simply do the contour once at
>> the highest resolution.
>> >
>> > Without seeing any code, though, I can only provide generic suggestions.
>> >
>> > Cheers!
>> > Ben Root
>> >
>> >
>> > On Mon, Sep 8, 2014 at 10:12 AM, Raffaele Quarta <
>> raf...@li...> wrote:
>> > Hi Ben,
>> >
>> > sorry for the few details that I gave to you. I'm trying to make a
>> contour plot of a variable at different zoom levels by using high
>> resolution data. The aim is to obtain .PNG output images. Actually, I'm
>> working with big data (NetCDF file, dimension is about 75Mb). The current
>> Matplotlib version on my UBUNTU 14.04 machine is the 1.3.1 one. My system
>> has a RAM capacity of 8Gb.
>> > Actually, I'm dealing with memory system problems when I try to make a
>> plot. I got the error message as follow:
>> >
>> > --------------------------------------------
>> > cs = m.pcolor(xi,yi,np.squeeze(t))
>> > File "/usr/lib/pymodules/python2.7/mpl_toolkits/basemap/__init__.py",
>> line 521, in with_transform
>> > return plotfunc(self,x,y,data,*args,**kwargs)
>> > File "/usr/lib/pymodules/python2.7/mpl_toolkits/basemap/__init__.py",
>> line 3375, in pcolor
>> > x = ma.masked_values(np.where(x > 1.e20,1.e20,x), 1.e20)
>> > File "/usr/lib/python2.7/dist-packages/numpy/ma/core.py", line 2195,
>> in masked_values
>> > condition = umath.less_equal(mabs(xnew - value), atol + rtol *
>> mabs(value))
>> > MemoryError
>> > --------------------------------------------
>> >
>> > Otherwise, when I try to make a plot of smaller file (such as 5Mb), it
>> works very well. I believe that it's not something of wrong in the script.
>> It might be a memory system problem.
>> > I hope that my message is more clear now.
>> >
>> > Thanks for the help.
>> >
>> > Regards,
>> >
>> > Raffaele
>> >
>> > -----------------------------------------
>> >
>> > Sent: Mon 9/8/2014 3:19 PM
>> > To: Raffaele Quarta
>> > Cc: Matplotlib Users
>> > Subject: Re: [Matplotlib-users] Plotting large file (NetCDF)
>> >
>> >
>> >
>> > You will need to be more specific... much more specific. What kind of
>> plot
>> > are you making? How big is your data? What version of matplotlib are you
>> > using? How much RAM do you have available compared to the amount of data
>> > (most slowdowns are actually due to swap-thrashing issues). Matplotlib
>> can
>> > be used for large data, but there exists some speciality tools for the
>> > truly large datasets. The solution depends on the situation.
>> >
>> > Ben Root
>> >
>> > On Mon, Sep 8, 2014 at 7:45 AM, Raffaele Quarta <
>> raf...@li...>
>> > wrote:
>> >
>> > > Hi,
>> > >
>> > > I'm working with NetCDF format. When I try to make a plot of very
>> large
>> > > file, I have to wait for a long time for plotting. How can I solve
>> this?
>> > > Isn't there a solution for this problem?
>> > >
>> > > Raffaele
>> > >
>> > > --
>> > > This email was Virus checked by Astaro Security Gateway.
>> http://www.sophos.com
>> > >
>> > >
>> > >
>> > >
>> ------------------------------------------------------------------------------
>> > > Want excitement?
>> > > Manually upgrade your production database.
>> > > When you want reliability, choose Perforce
>> > > Perforce version control. Predictably reliable.
>> > >
>> > >
>> http://pubads.g.doubleclick.net/gampad/clk?id=157508191&iu=/4140/ostg.clktrk
>> > > _______________________________________________
>> > > Matplotlib-users mailing list
>> > > Mat...@li...
>> > > https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>> > >
>> > >
>> >
>> > --
>> > This email was Virus checked by Astaro Security Gateway.
>> http://www.sophos.com
>> >
>> >
>> >
>> >
>> ------------------------------------------------------------------------------
>> > Want excitement?
>> > Manually upgrade your production database.
>> > When you want reliability, choose Perforce
>> > Perforce version control. Predictably reliable.
>> >
>> http://pubads.g.doubleclick.net/gampad/clk?id=157508191&iu=/4140/ostg.clktrk_______________________________________________
>> > Matplotlib-users mailing list
>> > Mat...@li...
>> > https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>> --
>> Jody Klymak
>> http://web.uvic.ca/~jklymak/
>>
>>
>>
>>
>>
>>
>>
>>
>>
>> ------------------------------------------------------------------------------
>> Want excitement?
>> Manually upgrade your production database.
>> When you want reliability, choose Perforce.
>> Perforce version control. Predictably reliable.
>>
>> http://pubads.g.doubleclick.net/gampad/clk?id=157508191&iu=/4140/ostg.clktrk
>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>>
>
>
> ------------------------------------------------------------------------------
> Want excitement?
> Manually upgrade your production database.
> When you want reliability, choose Perforce.
> Perforce version control. Predictably reliable.
>
> http://pubads.g.doubleclick.net/gampad/clk?id=157508191&iu=/4140/ostg.clktrk
> _______________________________________________
> Matplotlib-users mailing list
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> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>
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