matplotlib-users — Discussion related to using matplotlib

Re: [Matplotlib-users] how to put colorbar label beside the handle?

[ChaoYue <cha...@gm...>]

I have a bit progress, but still not very well.

#to have a contourf plot
a = np.arange(100).reshape(10,10)
cbarlevel=np.arange(0,101,10)
contourf(a,levels=cbarlevel)
cbar = colorbar()
cbar.set_ticks(cbarlevel)

#to manipulate the range:
cbar_label = []
for i in range(len(cbarlevel)-1):
    cbar_label.append("{0}-{1}".format(cbarlevel[i],cbarlevel[i+1]))
cbar_label.append('')

In [54]: print cbar_label
['0-10', '10-20', '20-30', '30-40', '40-50', '50-60', '60-70', '70-80',
'80-90', '90-100', '']

#Then to apply on the colorbar:
cbar.set_ticklabels(cbar_label)

The generated figure is attached. But how can I put the labels a little bit
upward to make them parallel with the respective small rectangles in the
colorbar? <http://matplotlib.1069221.n5.nabble.com/file/n39786/fig.jpg> 





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Re: [Matplotlib-users] Why is pip not mentioned in the Installation Documentation?

[Mathew T. <mat...@ed...>]

The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336.

Re: [Matplotlib-users] Why is pip not mentioned in the Installation Documentation?

[Michael D. <md...@st...>]

One of the reasons (historically) is that the build scripts predate 
setuptools and ships copies of dependencies rather than using 
easy_install or pip to install them.  There is an open PR to address 
this here:

https://github.com/matplotlib/matplotlib/pull/1454

But you do make a good point that `pip` should be mentioned in the docs 
as part of that change.

Mike

On 11/16/2012 05:54 AM, Mathew Topper wrote:
> Hi,
>
> I'm interested to know why the pip package manager is not more widely 
> supported for installation of python packages like matplotlib? 
> Matplotlib seems to be particularly slowly updated in the Fedora 
> repositories, for example, so I often find that a source installation 
> is necessary. I know this isn't especially difficult for the 
> experienced user, but surely using something like pip would make this 
> process for accessible for all users of python packages, particularly 
> those that do not receive much attention from the big distribution 
> maintainers? Yet, pip doesn't get a mention on the installation 
> documentation of matplotlib or many other python packs.
>
> I would love to hear anyone's thoughts on this matter.
>
> Many Thanks,
>
> Mat
> -- 
> Dr. Mathew Topper
> Institute for Energy Systems
> School of Engineering
> The University of Edinburgh
> Faraday Building
> The King's Buildings
> Edinburgh EH9 3JL
> Tel: +44 (0)131 650 5570
> School fax: +44 (0)131 650 6554
> mat...@ed... <mailto:mat...@ed...>
> http://www.see.ed.ac.uk <http://www.see.ed.ac.uk/>
>
>
> The University of Edinburgh is a charitable body, registered in
> Scotland, with registration number SC005336.
>
>
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[Matplotlib-users] Why is pip not mentioned in the Installation Documentation?

[Mathew T. <mat...@ed...>]

The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336.

Re: [Matplotlib-users] Figure zoom crosshair color

[Paul I. <piv...@gm...>]

On Thu, Nov 15, 2012 at 3:24 PM, David Brunell <qua...@gm...> wrote:

> Hello Paul,
>
> Thanks so much for your carefully-crafted reply.  I had a hunch that it
> would not be a simple matter.  I'm using wxAgg for the backend.
>
> I ended up using a Matplotlib widget cursor like this:
> cursor = Cursor(ax, useblit=True, color='red', alpha = 0.5, linestyle =
> '-', linewidth=1)
>
> It does not do exactly what I want, but it's cleaner than hacking into the
> backend.
>

This is, of course, a perfectly legitimate solution, so I hope you don't
mind me forwarding the correspondence to the list for posterity.


> Again, thanks for your help.
>

Happy to be helpful,
-- 
Paul Ivanov
314 address only used for lists,  off-list direct email at:
http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7

Re: [Matplotlib-users] Plot multiple lines

[Paul H. <pmh...@gm...>]

On Thu, Nov 15, 2012 at 2:48 PM, Boris Vladimir Comi
<gl...@co...> wrote:
> Hi all:
>
> I have begun to learn about python / matplolib / basemap and really need some help.
>
>   My data is in an Excel workbook in format .xls or csv(see attached):
>
> 1. How to open excel file in python?
>
> 2. I would like to plot multiple line joining the positions of each of the events, it is possible to do this? Have any idea how to do it?
>
> The idea is to plot the trajectories on a particular region, for my case is Mexico.

Boris,

If you can, install pandas and openpyxl on your machine. Pandas and
read in the csv by itself. Openpyxl is only needed if you really want
to read the Excel file.

Sticking with the csv approach, all you'll have to do is this:

import matplotlib.pyplot
import pandas

fig, ax = plt.subplots()
data = pandas.read_csv("/path/to/Trayectorias-scm-2004.csv")
data.plot(ax=ax)

That will plot all of the non-index columns in your dataframe.

Hope that helps,
-paul

Re: [Matplotlib-users] Plot multiple lines

[Ethan G. <eth...@gm...>]

> 1. How to open excel file in python?

You can read excel files with the xlrd module : http://www.python-excel.org/ 
However, you may want to simply read your exported CSV files. 

> 2. I would like to plot multiple line joining the positions of each of the events, it is possible to do this? Have any idea how to do it?

I'm not quite sure what you are aiming for with this.  You should be able to just plot a series of lines, as long as they have common start and end points they will appear joined, but the lines can have different attributes (e.g. color).  Or you can plot all the points as a single line with multiple segments (all segments having the same attributes).  

> The idea is to plot the trajectories on a particular region, for my case is Mexico.
> <Trayectorias-scm-2004.csv><Trayectorias-scm-2004.xls>------------------------------------------------------------------------------

[Matplotlib-users] Plot multiple lines

[Boris V. C. <gl...@co...>]

________________________________________


Hi all:

I have begun to learn about python / matplolib / basemap and really need some help.

  My data is in an Excel workbook in format .xls or csv(see attached):



1. How to open excel file in python?

2. I would like to plot multiple line joining the positions of each of the events, it is possible to do this? Have any idea how to do it?

The idea is to plot the trajectories on a particular region, for my case is Mexico.

Re: [Matplotlib-users] discrete colors from colormap for plt.plot and plt.scatter

[Ryan N. <rne...@gm...>]

Claus,

I agree with Sterling that the colors api page has a great deal of useful
info. However, as another solution to your problem, keep in mind that the
predefined colormaps contained in matplotlib.pyplot.cm return color tuples
when called with a float between 0 and 1. To illustrate with an extension
of your example code, try the following:

import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0,10,25) # Your x values
# A list of parameters for generating the y values
p = np.linspace(1,10,5)
# An array of values between 0 and 1 with the same length as your parameter
list.
d = np.linspace(0, 1, 5)
for i,j in zip(p,d):
    y = np.sin(x*i)
    plt.scatter(x, y, color=plt.cm.copper(j))
    plt.plot(x, y, color=plt.cm.jet(j))
plt.show()

If you have a lot of parameters, hence a large number of plots, you might
want to start reading up on collections:
http://matplotlib.org/api/collections_api.html
My understanding is that collections plot faster than many repeated calls
to plt.plot or plt.scatter. I've used LineCollection to plot a large number
of lines: I don't know which collection to use for repeated scatter plots,
though.

Good luck

Ryan

On Thu, Nov 15, 2012 at 12:49 PM, Sterling Smith <sm...@fu...>wrote:

> Claus,
>
> I think you are looking for something in
> http://matplotlib.org/api/colors_api.html
>
> -Sterling
>
> On Nov 15, 2012, at 8:24AM, Claus wrote:
>
> > Hi,
> > I have this issue, schematically:
> >
> > import numpy as np
> > import matplotlib.pyplot as plt
> >
> > x = np.linspace(0.0, a, b)
> >
> > for i in range(d):
> >       y1 = f1(x, p1_i, p2_i)
> >       y2 = f2(x, p1_i, p2_i)
> >       plt.scatter(x, y1, c=color[i])
> >       plt.plot(x, y2, '-', c=color[i]
> >
> >
> > my question:
> > how can I setup color to be d colors from some colormap (like cm.copper
> or cm.jet), they should be somewhat "equally" spaced… maybe the loop is not
> ideal, but I don't know a better way (yet)…
> >
> > Thanks for your help,
> > Cheers,
> > Claus
> >
> >
> >
> >
> ------------------------------------------------------------------------------
> > Monitor your physical, virtual and cloud infrastructure from a single
> > web console. Get in-depth insight into apps, servers, databases, vmware,
> > SAP, cloud infrastructure, etc. Download 30-day Free Trial.
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>
>
>
> ------------------------------------------------------------------------------
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>

Re: [Matplotlib-users] numpy.power vs pylab.power

[Benjamin R. <ben...@ou...>]

On Thu, Nov 15, 2012 at 12:06 PM, Paul Hobson <pmh...@gm...> wrote:

> Hey Will,
>
> As a user, all I can tell you is that pylab is there for convenience when:
> 1) quickly and interactively exploring some new data
> or
> 2) making the switch over from matlab or some other numerical analysis
> framework.
>
> In general, if you're doing some serious work -- especially work that
> you might revisit at any point -- explicitly import the packages you
> need into proper namespaces. As an example for me, this typically
> amounts to:
>
> import matplotlib.pyplot as plt
> import numpy as np
> import scipy.stats as stats
> import pandas #as pd
>
>
I still think Will's point is valid.  What likely happened (and this is me
completely guessing) is that np.random.power didn't always exist.  The
pylab module just blindly imports these namespaces.  Now, I do think that
instead of np.power(), one should probably be using the "**" operator
instead, but this does raise the issue of knowing when there are changes in
the flatten namespace.  Who's to say that something else won't collide in
the future?  We might need some sort of testing for this.

Ben Root

Re: [Matplotlib-users] discrete colors from colormap for plt.plot and plt.scatter

[Sterling S. <sm...@fu...>]

Claus,

I think you are looking for something in
http://matplotlib.org/api/colors_api.html

-Sterling

On Nov 15, 2012, at 8:24AM, Claus wrote:

> Hi,
> I have this issue, schematically:
> 
> import numpy as np
> import matplotlib.pyplot as plt 
> 
> x = np.linspace(0.0, a, b)
> 
> for i in range(d):
> 	y1 = f1(x, p1_i, p2_i)
> 	y2 = f2(x, p1_i, p2_i)
> 	plt.scatter(x, y1, c=color[i])
> 	plt.plot(x, y2, '-', c=color[i]
> 
> 
> my question:
> how can I setup color to be d colors from some colormap (like cm.copper or cm.jet), they should be somewhat "equally" spaced… maybe the loop is not ideal, but I don't know a better way (yet)…
> 
> Thanks for your help,
> Cheers,
> Claus
> 
> 
> 
> ------------------------------------------------------------------------------
> Monitor your physical, virtual and cloud infrastructure from a single
> web console. Get in-depth insight into apps, servers, databases, vmware,
> SAP, cloud infrastructure, etc. Download 30-day Free Trial.
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Re: [Matplotlib-users] numpy.power vs pylab.power

[Paul H. <pmh...@gm...>]

Hey Will,

As a user, all I can tell you is that pylab is there for convenience when:
1) quickly and interactively exploring some new data
or
2) making the switch over from matlab or some other numerical analysis
framework.

In general, if you're doing some serious work -- especially work that
you might revisit at any point -- explicitly import the packages you
need into proper namespaces. As an example for me, this typically
amounts to:

import matplotlib.pyplot as plt
import numpy as np
import scipy.stats as stats
import pandas #as pd



On Thu, Nov 15, 2012 at 8:22 AM, Will Furnass <wi...@th...> wrote:
> On my machine these are rather confusingly different functions, with the
> latter corresponding to numpy.random.power.  I appreciate that pylab
> imports everything from both the numpy and numpy.random modules but
> wouldn't it make sense if pylab.power were the oft-used power
> function rather than a means for sampling from the power distribution?
>
> Regards,
>
> Will Furnass
>
>
> ------------------------------------------------------------------------------
> Monitor your physical, virtual and cloud infrastructure from a single
> web console. Get in-depth insight into apps, servers, databases, vmware,
> SAP, cloud infrastructure, etc. Download 30-day Free Trial.
> Pricing starts from $795 for 25 servers or applications!
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[Matplotlib-users] discrete colors from colormap for plt.plot and plt.scatter

[Claus <cla...@gm...>]

Hi,
I have this issue, schematically:

import numpy as np
import matplotlib.pyplot as plt 

x = np.linspace(0.0, a, b)

for i in range(d):
	y1 = f1(x, p1_i, p2_i)
	y2 = f2(x, p1_i, p2_i)
	plt.scatter(x, y1, c=color[i])
	plt.plot(x, y2, '-', c=color[i]


my question:
how can I setup color to be d colors from some colormap (like cm.copper or cm.jet), they should be somewhat "equally" spaced… maybe the loop is not ideal, but I don't know a better way (yet)…

Thanks for your help,
Cheers,
Claus

[Matplotlib-users] numpy.power vs pylab.power

[Will F. <wi...@th...>]

On my machine these are rather confusingly different functions, with the
latter corresponding to numpy.random.power.  I appreciate that pylab
imports everything from both the numpy and numpy.random modules but
wouldn't it make sense if pylab.power were the oft-used power
function rather than a means for sampling from the power distribution?

Regards,

Will Furnass

Re: [Matplotlib-users] Gap when using contourf and nan's

[Ian T. <ian...@gm...>]

On 14 November 2012 21:05, Bror Jonsson <bro...@gm...> wrote:

> Dear all,
>
> I'm trying to to show where one set of values have NaN's on the contour
> plot of another set of values. I do this by creating a mask as such:
>
> fld = randn(4,4)
> fld[:2,:2] = np.nan
> mask[mask==0] = np.nan
> contourf(arange(4),arange(4),fld)
> contourf(arange(4),arange(4),mask)
>
> The problem is that the mask patch doesn't cover the empty space in the
> fld contour. Is there any way to make this happen?
>
> My ultimate goal is something like this:
>
> fld2 = randn(4,4)
> contourf(arange(4),arange(4),fld2)
> contourf(arange(4),arange(4),mask,[1,1], extend='both',
>          colors='w', alpha=0.5)
>
> to present where fld has NaN's on the fld2 plot.
>
>
> Many thanks in advance!
>
> Bror Jonsson
>


Hello Bror,

It is not clear from your code snippets exactly what you are asking for.
Please can you post a full runnable example?

Ian Thomas

Re: [Matplotlib-users] Documentation glitch on github

[Michael D. <md...@st...>]

Thanks for reporting.  It seems this file didn't make it over during the 
transition from Sourceforge to Github web hosting.  It's been restored.

Mike

On 11/14/2012 04:45 PM, william ratcliff wrote:
> Hi!   I was looking through the sample doc tutorial:
> http://matplotlib.org/sampledoc/
>
> and found that the link to the hard copy of the documentation is 
> missing.   Is there a more recent link?
>
>
> Best,
> William
>
>
> ------------------------------------------------------------------------------
> Monitor your physical, virtual and cloud infrastructure from a single
> web console. Get in-depth insight into apps, servers, databases, vmware,
> SAP, cloud infrastructure, etc. Download 30-day Free Trial.
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>
>
> _______________________________________________
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> Mat...@li...
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[Matplotlib-users] Documentation glitch on github

[william r. <wil...@gm...>]

Hi!   I was looking through the sample doc tutorial:
http://matplotlib.org/sampledoc/

and found that the link to the hard copy of the documentation is missing.
Is there a more recent link?


Best,
William

[Matplotlib-users] Gap when using contourf and nan's

[Bror J. <bro...@gm...>]

Dear all,

I'm trying to to show where one set of values have NaN's on the contour plot of another set of values. I do this by creating a mask as such:

fld = randn(4,4)
fld[:2,:2] = np.nan
mask[mask==0] = np.nan
contourf(arange(4),arange(4),fld)
contourf(arange(4),arange(4),mask)

The problem is that the mask patch doesn't cover the empty space in the fld contour. Is there any way to make this happen?

My ultimate goal is something like this:

fld2 = randn(4,4)
contourf(arange(4),arange(4),fld2)
contourf(arange(4),arange(4),mask,[1,1], extend='both', 
         colors='w', alpha=0.5)

to present where fld has NaN's on the fld2 plot.


Many thanks in advance!

Bror Jonsson


"If you have a garden and a Library, You have everything you need." -Cicero
==============================================================

Associate Research Scholar
Princeton University
Department of Geosciences
113 Guyot Hall
Princeton, NJ  08544-1003
USA

AIM, Skype, gTalk:   brorfred
Phone:                      +1-617-818-1096

Re: [Matplotlib-users] Transparency issue with matplotlib and wxpython

[Sylvain L. <syl...@la...>]

Hello again

> expecting the transparency to "stop" at the layer below the plot and
> therefore see the.

Sorry, I meant "therefore see the panel".
-- 
Sylvain

[Matplotlib-users] Transparency issue with matplotlib and wxpython

[Sylvain L. <syl...@la...>]

Hello

I would like some help to understand a problem with matplotlib and 
wxpython.

I am developping a GUI where my plots are embedded on wxPanels on a 
wxNotebook (tabs). Under Windows, some themes don't use a single colour 
but a gradient as the tab background. Therefore, I'd like to make the 
background of my plots transparent.

Under Windows XP (whatever the theme), when I set the facecolor of the 
plot to 'none', the plot background becomes transparent, but the parts 
of the panel and of the notebook below as well, and I end up seeing 
other windows behind my GUI or the Windows desktop. I was expecting the 
transparency to "stop" at the layer below the plot and therefore see 
the.

I did a second experiment, where I overlayed two plots. The top one is 
larger than the one below. I make the top one partially transparent, to 
see the one below. The transparency is "stopped" in the area of the 
inferior plot, I see the desktop on the remaining parts, and where there 
is no plot the background of my panel.

I'm attaching the code for the second experiment.

I'm running XP 32bits with the Classic theme, python 2.7.3, matplotlib 
1.2.0 and wxpython 2.9.4-msw.

Thanks for your help
-- 
Sylvain

[Matplotlib-users] using draw_if_interactive in library plots?

[Skipper S. <jss...@gm...>]

Hi All,

Hoping someone can help me get a definitive answer to this question.
Is draw_if_interactive bad to have in library plotting code?

Based on this thread [1], we've been working under the assumption that
calling draw_if_interactive in plotting code is bad. Though I'm
skeptical that this is the takeaway that we should have. I also asked
this question on the IPython mailing list [2] since the recommendation
comes from their type of usage, but I'm still not clear.

I'll repeat the gist of the question here.

We have plotting functions that are designed to update a given axes. I
often work in interactive mode, and I'd like it if these functions
updated my axes in the way that I expect (and an R user doing plotting
in Python would expect). But now I'm forced to litter my user scripts
with draw_if_interactive after I call a function I expect to update a
plot - say updating a scatter plot with a regression line. Would be
harmful to just include these draw_if_interactive calls in our plot
functions. To be clear, I never have to call show or draw because I'm
working in interactive mode, so the recommendation to just call show()
at the end of a script is not what I want.

My understanding of the pitfalls is 1) there's a performance hit to
calling draw instead of just making one call. This is moot because
we're only calling draw_if_interactive - so we assume the user is
working interactively and actually wants to do the drawing and doesn't
care about the performance hit. And 2) we are assuming that the user
has imported and is using pyplot and there are possible side effects.
A user wouldn't be using pyplot in a GUI or in some sort of embedded
plotting framework. However, my intuition says that if this is the
case, draw_if_interactive won't do anything because interactive will
be False in these cases.

Can someone please help clear this up? Thanks,

Skipper


[1] https://groups.google.com/forum/#!msg/pystatsmodels/biNlCvJPNNY/BT7bQJmOa1cJ
[2] http://python.6.n6.nabble.com/IPython-User-using-matplotlib-draw-if-interactive-in-library-code-td4991275.html

Re: [Matplotlib-users] Figure zoom crosshair color

[Paul I. <piv...@gm...>]

On Tue, Nov 13, 2012 at 8:38 AM, David Brunell <qua...@gm...> wrote:

> Hello, I have what I hope is a simple question.  When producing a
> figure/plot, I have a window which pops up with the figure inside and a few
> tool buttons along the bottom, including "Zoom to rectangle."  Clicking the
> Zoom tool button, I'm presented with a black crosshair to select my zoom
> rectangle.  Many of the images I work with are predominantly black; is
> there any way to change the color of the crosshair so as to make it more
> visible?  Thanks.


Hi David,

Unfortunately, those widgets are backend specific, so changing them is not
trivial in general, since each toolkit has its own way of specifying the
cursor. With that said, you can try to figure out if there's a way to do it
for your backend `import matplotlib as mpl; mpl.get_backend()` will tell
you which backend you're using, and then you'll need to look in the
relevant source code for where the cursor is define.

If you don't know where your matplotlib code lives, you can the path of the
relevant files using this:

  import matplotlib.backends as b
  import os
  os.path.dirname(b.__file__)

There, you'll find files for all of the backends, and the `cursord`
dictionary in most of them is what specifies how the widgets look. I'm not
sure which toolkits allow one to change the color of the default cursors,
but some of them allow you to even specify your own color images, so it
should be possible.

An alternative, of course, would be to change the colormap you're plotting
with, or add an alpha value to the images you're plotting so that the black
widgets can be seen. Maybe it's inelegant, but looks like the path of least
resistance...

best,
-- 
Paul Ivanov
314 address only used for lists,  off-list direct email at:
http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7

Re: [Matplotlib-users] matplotlib 1.2.0 (OS X 10.6 binary) "requires System Python 2.7"

[Russell E. O. <ro...@uw...>]

In article 
<CAJ...@ma...>,
 Alexey Shamrin <sh...@gm...> 
 wrote:

> Thank you for 1.2.0 release!
> 
> Could you please make it clear that matplotlib requires
> python.org-Python sourceforge.net-NumPy? Telling about it during
> installation would be great.

This is described in three places:
- The description of the file on the download page
- The name of the file on the download page
- The ReadMe file in the binary installer

Note that the official binary installers for numpy and scipy are also 
for python.org python, and as far as I know they do no more than the 
matplotlib installer as far as informing the user of this fact.

It is bdist_mpkg that makes these installers, and it could be better 
about checking compatibility. But that is a known issue.

I don't know about messages about "system python", though that vaguely 
rings a bell as a bdist_mpkg issue.

I'll add information about numpy to the ReadMe for future binary 
installers. Aside from that, I believe I've done everything I reasonably 
can to clarify the requirements for the binary installer.

-- Russell

[Matplotlib-users] Basemap - pcolormesh outside of projected area

[Jay L. <jl...@as...>]

All,

I am attempting to plot a base map with extents which are outside of the
figure using the following code:

#Map
lon_min = -101.5
lon_max = -94.5
lat_min = -32.5
lat_max = -27.5

m = Basemap(projection='aeqd',llcrnrlat=lat_min,urcrnrlat=lat_max,
            llcrnrlon=lon_min,urcrnrlon=lon_max,lon_0=-97.7328,
lat_0=-30.0906,resolution=None, rsphere=(1737400.0,1737400.0))

        #Read the input image
input_basemap = gdal.Open('Mare_Orientale_Volc_AzEqui.png')
input_band = input_basemap.GetRasterBand(1)
bmap = input_band.ReadAsArray()
        #The bounds of the input image using gdalinfo
LL = (-204690.290, -162184.543)
UR = (200909.710,  176915.457)


I know that I need to use pcolormesh() to get my map visualized.  I also
believe that I need to use the transform_scalar function to get from pixel
space to map projected space.  My input image is not in Lat/Lon, but in
pixel space.  Any suggestions on getting my image to display in projected
space?

Best,
Jay

[Matplotlib-users] Figure zoom crosshair color

[David B. <qua...@gm...>]

Hello, I have what I hope is a simple question.  When producing a
figure/plot, I have a window which pops up with the figure inside and a few
tool buttons along the bottom, including "Zoom to rectangle."  Clicking the
Zoom tool button, I'm presented with a black crosshair to select my zoom
rectangle.  Many of the images I work with are predominantly black; is
there any way to change the color of the crosshair so as to make it more
visible?  Thanks.