matplotlib-users Mailing List for matplotlib

Nelly,
I would like to compile libpng into matplotlib if possible, ie static.
Seems like thats not possible and I would like to would LD_LIBRARY_PATH as
much as possible. I much prefer -Wl, rpath or LD_PRELOAD.

Jouni,
for the pkg-config can I use the one with my OS, /usr/bin/pkg-config? and
also libpng comes with its own variation of pkg-config (not named that).
How can I include that? do I set PKG_CONFIG_PATH ?





On Sun, Sep 30, 2012 at 3:30 AM, Nelle Varoquaux
<nel...@gm...>wrote:

>
> On 30 Sep 2012 06:11, "Jouni K. Seppänen" <jk...@ik...> wrote:
> >
> > Rita <rmo...@gm...> writes:
> >
> > > i have a micro distribution setup. I am building python, numpy, scipy
> from
> > > scratch. I am building matplotlib from scratch also.
> > >
> > > I am doing a simple, /apps/bin/python setup.py build.
> > >
> > > I also compiled libpng and cairo in a location.
>
> When you build a shared library yourself, you always need to set the
> variable LD_LIBRARY_PATH. This is independant from the compilation. At
> runtime, the program merely tries to load the library if it has not been
> loaded previously.
>
> Usually, to avoid setting manually the path to the library, one adds this
> to its bashrc/zshrc.
>
> I hope this helps.
> Cheers,
> N.
>
> >
> > Have you set up pkg-config for your build of libpng? If you can't do
> > that for some reason, you can edit basedirlist in setup.cfg.
> >
> > --
> > Jouni K. Seppänen
> > http://www.iki.fi/jks
> >
> >
> >
> ------------------------------------------------------------------------------
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>
>
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-- 
--- Get your facts first, then you can distort them as you please.--

On 30 Sep 2012 06:11, "Jouni K. Seppänen" <jk...@ik...> wrote:
>
> Rita <rmo...@gm...> writes:
>
> > i have a micro distribution setup. I am building python, numpy, scipy
from
> > scratch. I am building matplotlib from scratch also.
> >
> > I am doing a simple, /apps/bin/python setup.py build.
> >
> > I also compiled libpng and cairo in a location.

When you build a shared library yourself, you always need to set the
variable LD_LIBRARY_PATH. This is independant from the compilation. At
runtime, the program merely tries to load the library if it has not been
loaded previously.

Usually, to avoid setting manually the path to the library, one adds this
to its bashrc/zshrc.

I hope this helps.
Cheers,
N.

>
> Have you set up pkg-config for your build of libpng? If you can't do
> that for some reason, you can edit basedirlist in setup.cfg.
>
> --
> Jouni K. Seppänen
> http://www.iki.fi/jks
>
>
>
------------------------------------------------------------------------------
> Everyone hates slow websites. So do we.
> Make your web apps faster with AppDynamics
> Download AppDynamics Lite for free today:
> http://ad.doubleclick.net/clk;258768047;13503038;j?
> http://info.appdynamics.com/FreeJavaPerformanceDownload.html
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users

Rita <rmo...@gm...> writes:

> i have a micro distribution setup. I am building python, numpy, scipy from
> scratch. I am building matplotlib from scratch also.
>
> I am doing a simple, /apps/bin/python setup.py build.
>
> I also compiled libpng and cairo in a location.

Have you set up pkg-config for your build of libpng? If you can't do
that for some reason, you can edit basedirlist in setup.cfg.

-- 
Jouni K. Seppänen
http://www.iki.fi/jks

i have a micro distribution setup. I am building python, numpy, scipy from
scratch. I am building matplotlib from scratch also.

I am doing a simple, /apps/bin/python setup.py build.

I also compiled libpng and cairo in a location.




On Fri, Sep 28, 2012 at 10:49 PM, Eric Firing <ef...@ha...> wrote:

> On 2012/09/28 3:40 PM, Rita wrote:
> > Whenever I use matplot lib its asking me for libpng and when I do
> > LD_LIBRARY_PATH it works. Is there a way I can compile matplotlib so I
> > can avoid doing an export LD_LIBRARY_PATH ?
>
> Normally one doesn't need it, so I don't know why you do need it.  You
> might get a useful response from someone who knows more about linking
> than I do if you provide some information about your platform and about
> how you are presently building matplotlib.
>
> Eric
>
>
>
> ------------------------------------------------------------------------------
> How fast is your code?
> 3 out of 4 devs don\\\'t know how their code performs in production.
> Find out how slow your code is with AppDynamics Lite.
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> http://info.appdynamics.com/FreeJavaPerformanceDownload.html
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>



-- 
--- Get your facts first, then you can distort them as you please.--

On 2012/09/28 3:40 PM, Rita wrote:
> Whenever I use matplot lib its asking me for libpng and when I do
> LD_LIBRARY_PATH it works. Is there a way I can compile matplotlib so I
> can avoid doing an export LD_LIBRARY_PATH ?

Normally one doesn't need it, so I don't know why you do need it.  You 
might get a useful response from someone who knows more about linking 
than I do if you provide some information about your platform and about 
how you are presently building matplotlib.

Eric

Whenever I use matplot lib its asking me for libpng and when I do
LD_LIBRARY_PATH it works. Is there a way I can compile matplotlib so I can
avoid doing an export LD_LIBRARY_PATH ?




-- 
--- Get your facts first, then you can distort them as you please.--

On 9/26/12 12:31 PM, Benjamin Root wrote:
>
>
> On Wed, Sep 26, 2012 at 12:10 PM, Paul Tremblay 
> <pau...@gm... <mailto:pau...@gm...>> wrote:
>
>     Thanks. I know when doing 8/9 in python 2.x you get 0. With python
>     3 you get a decimal (Hooray, Python 3!).
>
>     I ran the script I submitted with python 3. Do I need to change
>     the defects and totals from integers to floats to make my chart
>     work universally?
>
>     P.
>
>
Here is my latest version of the Pareto chart. If the developers feel it 
is worthy, then they can include it in the gallery. Otherwise, it will 
have to remain in these threads, useful when, needing such a chart, 
someone searches the web and ends up here.

import matplotlib.pyplot as plt
import numpy as np

# the data to plot
defects = [32.0, 22.0, 15.0, 5.0, 2.0]
labels = ['vertical', 'horizontal', 'behind', 'left area', 'other']
the_sum = sum(defects) # ie, 32 + 22 + 15 + 5 + 2
the_cumsum = np.cumsum(defects) #  32, 32 + 22, 32 + 22 + 15, 32 + 22 + 
15 + 5, 32 + 22, + 15 + 5 + 2
percent = (np.divide(the_cumsum, the_sum)) * 100
ind = np.arange(len(defects))  # the x locations for the groups
width = .98 # with do of the bars, where a width of 1 indidcates no 
space between bars
x = ind + .5 * width # find the middle of the bar
fig = plt.figure() # create a figure
ax1 = fig.add_subplot(111) # and a subplot
ax2 = ax1.twinx() # create a duplicate y axis
rects1 = ax1.bar(ind, defects, width=width) # draw the chart
line, = ax2.plot(x, percent) # draw the  line
ax1.set_ylim(ymax=the_sum) # without these limits, graphs will not work
ax2.set_ylim(0, 100)
ax1.set_xticks(x) # set ticks for middle of bars
ax1.set_xticklabels(labels) # create the labels for the bars
ax1.set_ylabel('Defects') # create the left y axis label
ax2.set_ylabel('Percentage') # create the right y axis label
plt.show()

On 9/26/12 10:15 AM, Michael Droettboom wrote:
> On 09/26/2012 09:33 AM, Benjamin Root wrote:
>>
>>
>> On Wed, Sep 26, 2012 at 9:10 AM, Michael Droettboom <md...@st... 
>> <mailto:md...@st...>> wrote:
>>
>>     On 09/26/2012 12:28 AM, jos...@gm...
>>     <mailto:jos...@gm...> wrote:
>>     > On Wed, Sep 26, 2012 at 12:05 AM, Paul Tremblay
>>     <pau...@gm... <mailto:pau...@gm...>> wrote:
>>     >> In R, there are many default data sets one can use to both
>>     illustrate code
>>     >> and explore the scripting language. Instead of having to fake
>>     data, one can
>>     >> pull from meaningful data sets, created in the real world. For
>>     example, this
>>     >> one liner actually produces a plot:
>>     >>
>>     >> plot(mtcars$hp~mtcars$mpg)
>>     >>
>>     >> where mtcars refers to a built-in data set taken from Motor
>>     Trend Magazine.
>>     >> I don't believe matplotlib has anything similar. I have
>>     started to download
>>     >> some of the R data sets and store them as pickles for my own
>>     use. Does
>>     >> anyone else have any interest in creating a repository for
>>     these data sets
>>     >> or otherwise sharing them in some way?
>>     > Vincent converted several R datasets back to csv, that can be
>>     easily
>>     > loaded from the web with, for example, pandas.
>>     > http://vincentarelbundock.github.com/Rdatasets/
>>     > The collection is a bit random.
>>     >
>>     > statsmodels has some datasets that we use for examples and tests
>>     > http://statsmodels.sourceforge.net/devel/datasets/index.html
>>     > We were always a bit slow with adding datasets because we were too
>>     > cautious about licensing issues. But R seems to get away with
>>     > considering most datasets to be public domain.
>>     > We keep adding datasets to statsmodels as we need them for new
>>     models.
>>     >
>>     > The machine learning packages like sklearn have packaged the
>>     typical
>>     > machine learning datasets.
>>     >
>>     > If you are interested, you could join up with statsmodels or with
>>     > Vincent to expand on what's available.
>>     >
>>     It seems to me like contributing to (rather than duplicating) the
>>     work
>>     of one of these projects would be a great idea.  It would also be
>>     nice
>>     to add functionality in matplotlib to make it easier to download
>>     these
>>     things as a one-off -- obviously not exactly the same syntax as
>>     with R,
>>     but ideally with a single function call.
>>
>>     Mike
>>
>>
>> We did have such a thing. matplotlib.cbook.get_sample_data().  I 
>> think we got rid of it for 1.2.0?
> It was removed because the server side was a moving target and would 
> constantly break.  It was based on pulling files out of the svn (and 
> later git) repository, and sourceforge and github have had a habit of 
> changing the urls used to do so.  All of the data that was there was 
> moved into the main repository and is now installed alongside 
> matplotlib, so get_sample_data() still works.
>
> See this PR: https://github.com/matplotlib/matplotlib/pull/498
>
> I should have mentioned it earlier, that we do have a very small set 
> of standard data sets included there -- but these other projects 
> linked to above are much better and more extensive.  If we can rely on 
> them to have static urls over time, I think they are much better 
> options than anything matplotlib has had in the past.
>
> Mike
Drawing on other posts, it is conceivable to download both the R sets 
and the stats models sets and include them in 
site-packages/matplotlib/mpl-data/sample_data/? I understand that 
pulling data sets not in this directory creates problems because of 
moving URLs, but why even try to do a web pull when the data can exists 
in a reliable place?

I suppose one might raise reasonable objections to my suggestion, but at 
any rate, it doesn't seem I can add anything else to either project, 
since they both seem complete. I see only a small though significant 
problem with the R data sets in that it leaves out the header of the 
first column because of the structure of R data frames. Python needs 
this header.

Paul

>________________________________
> From: Benjamin Root <ben...@ou...>
>To: Michael Rawlins <raw...@ya...> 
>Cc: Matplotlib Users <mat...@li...> 
>Sent: Thursday, September 27, 2012 2:29 PM
>Subject: Re: [Matplotlib-users] error reading netcdf file
> 
>
>Michael,
>
>The .missing_value attribute is not used anymore (It is ._FillValue now).  Anyway, if your data had any value that matched ._FillValue, then, by default, netCDF4 will give you a masked array anyway.  You will only need to set the mask if the fill value doesn't exist or if it is different from what you were expecting.
>
>Ben Root
>
>
>

Thanks Ben. I'll play around with ._FillValue and masked arrays. Glad to have everything working again with this new OS.

Mike

Michael,

The .missing_value attribute is not used anymore (It is ._FillValue now).
Anyway, if your data had any value that matched ._FillValue, then, by
default, netCDF4 will give you a masked array anyway.  You will only need
to set the mask if the fill value doesn't exist or if it is different from
what you were expecting.

Ben Root

Hi,

trying to create a velocity plot for a 2d ode and superimposing it onto
a trajectory, I am encountering some issues with quiver.

Let ns1(x,t) be a vector function defining the ode, ready to be integrated with
scipy odeint and actually invariant with t. Here, x is a 1d state array with 2
entries.

I get the velocity field by first creating vectors of interesting points on the
two axis, say xg and yg. Then I make a grid with

xxg, yyg = np.meshgrid(xg, yg)

and I finally compute the velocity components as

vel = np.asarray(map(lambda x1, x2: ns1((x1,x2),0), xxg.flat, yyg.flat))
u=vel[:,0]
v=vel[:,1]

Now, I try to superimpose a trajectory with the velocity plot.
However, after having plotted the integrated trajectory, I cannot call

plt.quiver(xxg, yyg, u, v)

because the u and v components have very different ranges.

Trying to normalize as

plt.quiver(xxg, yyg, u/xrange, v/yrange)

looks (almost) right, but it is not nice to have to precompute the ranges.

I was expecting

plt.quiver(xxg, yyg, u, v, angles='xy')

to do the job automatically, but this is not the case.
For points with null x coordinate my arrows always have null length,
while this was not the case with the previous test.

any clue?

----- Original Message -----
> From: Michael Rawlins <raw...@ya...>
> To: Jeff Whitaker <jef...@no...>; Benjamin Root <ben...@ou...>; Matplotlib Users <mat...@li...>
> Cc: 
> Sent: Wednesday, September 26, 2012 6:23 PM
> Subject: Re: [Matplotlib-users] error reading netcdf file
> 
> 
> 
>> ________________________________
>>  From: Jeff Whitaker <jef...@no...>
>> To: Benjamin Root <ben...@ou...>; Michael Rawlins 
> <ra...@ge...>; Matplotlib Users 
> <mat...@li...> 
>> Sent: Wednesday, September 26, 2012 5:10 PM
>> Subject: Re: [Matplotlib-users] error reading netcdf file
>> 
>> 
>> Michael:  You can't change an attribute in a read-only dataset.  It 
> should never have worked.
>> 
>> -Jeff
>> 
>> 
> 
> 
> Thanks Jeff and Ben.
> 
> Below is a complete version of one such program I use. I was give the program by 
> a colleague and I do not know who wrote that code.  My previous post showed only 
> as far as the missing data statement.
> 


<snip>

I've gotten my script to work by setting the missing value another way. I'm showing lines commented out as well.

#data.missing_value=-9.99
#try:
#    mval=data.missing_value
#    print " using specified missing value =",mval
#except:
    mval=-9.99
#    print " faking missing value=",mval
# make a masked array: using missing value(s) in mval
maskdat=ma.masked_values(slice,mval)


If I understand correctly, in previous versions the value of -9.99 was passed through the data.missing_value into mval. A mistake in coding that did not result in an error.  I will implement the change. Tomorrow I'll check that this solution is backward compatible.

Mike

On Thu, Sep 27, 2012 at 1:07 PM, Benjamin Root <ben...@ou...> wrote:
>
>
> On Thursday, September 27, 2012, Pierre Haessig wrote:
>>
>> Hi Paul,
>>
>> Le 26/09/2012 18:14, Paul Tremblay a écrit :
>> > I noticed today that when I create a bar graph with zero values that
>> > the labels don't align correctly:
>>
>> When I run your code with defects = [0, 0, 0, 5, 6, 7], I don't notice a
>> misalignment of xlabels, but rather a issue with xaxis scaling being
>> different (and not very good). So it would be more an issue of xaxis
>> autoscaling.
>>
>> Maybe you can send a link to your saved figure to check we are talking
>> of the same thing. I've attached my figures (manual 3 panels composition).
>>
>> Also, I've noticed that the xscaling issue doesn't come from zero values
>> in general, but from defects[0] being zero.
>>
>> Best,
>> Pierre
>
>
> This issue has been mentioned before.  The problem happens for a zero bar on
> either end.  Particularly, a bar with zero height does not register a bbox
> for determining the axis limits.  We will likely need a slightly different
> way of autoscaling for bar()
>
> Ben Root
>

As an epic hack/workaround. Could you set bars of zero height to
instead be of height, 10e-5. Or something small compared to whatever
the current scale on the y-axis is. Or call ax.set_xlim yourself after
plotting? It's not ideal, but does it help?

Like Ben said, the bbox should account for all possible bar locations,
regardless of height, for this to behave as expected.

-- 
Damon McDougall
http://www.damon-is-a-geek.com
B2.39
Mathematics Institute
University of Warwick
Coventry
West Midlands
CV4 7AL
United Kingdom

On Thursday, September 27, 2012, Pierre Haessig wrote:

> Hi Paul,
>
> Le 26/09/2012 18:14, Paul Tremblay a écrit :
> > I noticed today that when I create a bar graph with zero values that
> > the labels don't align correctly:
>
> When I run your code with defects = [0, 0, 0, 5, 6, 7], I don't notice a
> misalignment of xlabels, but rather a issue with xaxis scaling being
> different (and not very good). So it would be more an issue of xaxis
> autoscaling.
>
> Maybe you can send a link to your saved figure to check we are talking
> of the same thing. I've attached my figures (manual 3 panels composition).
>
> Also, I've noticed that the xscaling issue doesn't come from zero values
> in general, but from defects[0] being zero.
>
> Best,
> Pierre
>

This issue has been mentioned before.  The problem happens for a zero bar
on either end.  Particularly, a bar with zero height does not register a
bbox for determining the axis limits.  We will likely need a slightly
different way of autoscaling for bar()

Ben Root

Hi Paul,

Le 26/09/2012 18:14, Paul Tremblay a écrit :
> I noticed today that when I create a bar graph with zero values that
> the labels don't align correctly:

When I run your code with defects = [0, 0, 0, 5, 6, 7], I don't notice a
misalignment of xlabels, but rather a issue with xaxis scaling being
different (and not very good). So it would be more an issue of xaxis
autoscaling.

Maybe you can send a link to your saved figure to check we are talking
of the same thing. I've attached my figures (manual 3 panels composition).

Also, I've noticed that the xscaling issue doesn't come from zero values
in general, but from defects[0] being zero.

Best,
Pierre

>________________________________
> From: Jeff Whitaker <jef...@no...>
>To: Benjamin Root <ben...@ou...>; Michael Rawlins <ra...@ge...>; Matplotlib Users <mat...@li...> 
>Sent: Wednesday, September 26, 2012 5:10 PM
>Subject: Re: [Matplotlib-users] error reading netcdf file
> 
>
>Michael:  You can't change an attribute in a read-only dataset.  It should never have worked.
>
>-Jeff
>
>


Thanks Jeff and Ben.

Below is a complete version of one such program I use. I was give the program by a colleague and I do not know who wrote that code.  My previous post showed only as far as the missing data statement.


I'm relatively new to this software. It looks like the missing value goes into the maskdat array and maskdat is an input to pcolor function. Perhaps the best way is to get it working (shading a map) with just the array from the netCDF file read. Essentailly the missing value is to shade some grids outside the region white.  


Mike




#!/usr/bin/env python
# v0.5 19 June 2010
# General purpose plotter of 2-D gridded data from NetCDF files,
# plotted with map boundaries.
# NetCDF file should have data in either 2-D, 3-D or 4-D arrays.
# Works with the netCDF files in the tutorial, and also the
# files available for download at:
# http://www.cdc.noaa.gov/cdc/data.ncep.reanalysis.html 
# Adapted from the basemap example plotmap_pcolor.py,
# Some of the variable names from that example are retained.
#
# Uses basemap's pcolor function.  Pcolor accepts arrays
# of the longitude and latitude  points of the vertices on the pixels,
# as well as an array with the numerical value in the pixel. 

verbose=0 #verbose=2 says a bit more

import sys,getopt

from mpl_toolkits.basemap import Basemap, shiftgrid, cm 
#from netCDF3 import Dataset as NetCDFFile 
from mpl_toolkits.basemap import  NetCDFFile
from pylab import *

alloptions, otherargs= getopt.getopt(sys.argv[1:],'ro:p:X:Y:v:t:l:u:n:') # note 
the : after o and p
proj='lam'
#plotfile=None
#plotfile='testmap2.png'
usejetrev=False
colorbounds=[None,None]
extratext=""
xvar=None
yvar=None
thevar=None

thetitle='Bias - Winter Air Temperature'
#thetitle='Bias - Spring Air Temperature'
#thetitle='Bias - Summer Air Temperature'
#thetitle='Bias - Autumn Air Temperature'

therec=None
thelev=None
cbot=None
ctop=None
startlon=-180 #default assumption for starting longitude
for theopt,thearg in alloptions:
    print theopt,thearg
    if theopt=='-o': # -o needs filename after it, which is now thearg
        plotfile=thearg    
    elif theopt=='-p': 
        proj=thearg
    elif theopt=='-X': 
        xvar=thearg
    elif theopt=='-Y': 
        yvar=thearg
    elif theopt=='-v': 
        thevar=thearg
    elif theopt=='-t': 
        thetitle=thearg
    elif theopt=='-l': 
        cbot=thearg
    elif theopt=='-u': 
        ctop=thearg
    elif theopt=='-n': 
        therec=thearg
    elif theopt=='-m': 
        thelev=thearg
    elif theopt=='-r': 
        usejetrev=True
    else: #something went wrong
        print "hmm, what are these??? ", theopt, thearg
        sys.exit()


print otherargs
try:
    ncname=otherargs[0]
    ncfile = NetCDFFile(ncname, 'r')
except:
#    ncname = raw_input("\nenter NetCDF file name =>")
#    ncfile = NetCDFFile(ncname, 'r')
    ncfile = NetCDFFile('simple_xy.nc', 'r')   # Here's filename
    
if verbose>0:  #examine the NetCDF file
    print "GLOBAL ATTRIBUTES:"
    allattr=dir(ncfile)
    normalattr=dir(NetCDFFile('/tmp/throwaway.nc','w'))
    for item in allattr:
        if item not in normalattr: print item,': ',getattr(ncfile,item)
#    for name in ncfile.ncattrs():
#            print name,'=', getattr(ncfile,name)
#            if name=='Conventions' and getattr(ncfile,name)=='COARDS
':
#                nmcrean=True
#                startlon=0.
#                print "guessing this is an NMC reananalysis file
"
#            else:
#                nmcrean=False
    print "\n\nDIMENSIONS:"
    for name in ncfile.dimensions.keys():
        print "\nDIMENSION:",
        try:
            print name, ncfile.variables[name][:]
        except:
            print name, ncfile.dimensions[name]
        try:
            print '   ',ncfile.variables[name].units
        except:
            pass
        try:
            print '   ',ncfile.variables[name].gridtype
        except:
            pass
    print "\n'*****************'\nVARIABLES:"
    for name in ncfile.variables.keys():
        if name in ncfile.dimensions.keys(): continue
        print "\nVARIABLE:",
        print name, ncfile.variables[name].dimensions,
        try:
            print '   ',ncfile.variables[name].units
        except:
            pass
        try:
            print "   missing value=",ncfile.variables[name].missing
_value
        except:
            pass
#
print "********************\n"
#if not xvar: xvar=raw_input("\nenter X variable=>")
xvar='rlon'
print "shape of "+xvar+': ',ncfile.variables[xvar].shape
if ncfile.variables[xvar][:].ndim ==1:
    print "X is independent of Y"
    lon1d=ncfile.variables[xvar][:]
else:
    lon1d=False
    if  ncfile.variables[xvar][:].ndim ==2: lon2d=ncfile.variables[xvar][:]
    if  ncfile.variables[xvar][:].ndim ==3: lon2d=ncfile.variables[xvar][0,:
,:] #WRF
    print "shape of lond2d:", lon2d.shape


#print type(lon1d),lon1d,type(lon1d[1]),lon1d[1]
#
#if not yvar: yvar=raw_input("\nenter Y variable=>")
yvar='rlat'
print "shape of "+yvar+': ',ncfile.variables[yvar].shape
if ncfile.variables[yvar][:].ndim ==1:
    print "Y is independent of X"
    lat1d=ncfile.variables[yvar][:]
else:
    lat1d=False
    if  ncfile.variables[yvar][:].ndim ==2: lat2d=ncfile.variables[yvar][:]
    if  ncfile.variables[yvar][:].ndim ==3: lat2d=ncfile.variables[yvar][0,:
,:] #WRF
    print "shape of lat2d:", lat2d.shape
#
#if not thevar: thevar=raw_input("\nenter variable to plot=>")
#thevar='nseasondays'
thevar='diff'
#thevar='mean'
data=ncfile.variables[thevar]
dataa=data[:]
theshape=dataa.shape
try:
    add_offset=ncfile.variables[thevar].add_offset
    print "will use add_offset=",add_offset
except:
    add_offset=0.    
print "shape of "+thevar+': ',theshape
if len(theshape)>2:
    print "there are apparently",theshape[0],"records"
    if not therec: therec=raw_input("enter record number to plot=>")
    therec=int(therec)
    extratext=" rec=%d" %therec
if len(theshape)>3:
    print "there are apparently",theshape[1],"levels"
    if not thelev: thelev=raw_input("enter level number to plot=>")
    thelev=int(thelev)
    extratext=extratext+" lev=%d" %thelev
if len(theshape)>3: 
    slice=dataa[therec,thelev,:,:]+add_offset
elif len(theshape)>2: 
    slice=dataa[therec,:,:]+add_offset
else:
    slice=dataa+add_offset

#data.missing_value=0
#data.missing_value=-999
data.missing_value=-9.99
try:
    mval=data.missing_value
    print " using specified missing value =",mval
except:
    mval=1.e30
    print " faking missing value=",mval
# make a masked array: using missing value(s) in mval
maskdat=ma.masked_values(slice,mval)
datamax=max(maskdat.compressed().flat)
datamin=min(maskdat.compressed().flat)
print "\n"+thevar+" has maximum ", datamax,"  and minimum:", datamin

#colorbounds=[None,None]
#if not cbot: cbot=raw_input("enter lower bound on color scale =>")
#if cbot: colorbounds[0]=float(cbot)
#if not ctop: ctop=raw_input("enter upper bound on color scale =>")
#if ctop: colorbounds[1]=float(ctop)

colorbounds=[-3,3]            # for diff in C
print "using clim=",colorbounds


# shift lons and lats by 1/2 grid increment (so values represent the vertices
# of the grid box surrounding the data value, as pcolor expects).
if type(lon1d)!=type(False): #lon1d does exist
    delon = lon1d[1]-lon1d[0]
    delat = lat1d[1]-lat1d[0]
    lons = zeros(len(lon1d)+1,'d')
    lats = zeros(len(lat1d)+1,'d')
    lons[0:len(lon1d)] = lon1d-0.5*delon
    lons[-1] = lon1d[-1]+0.5*delon
    lats[0:len(lat1d)] = lat1d-0.5*delon
    lats[-1] = lat1d[-1]+0.5*delon
    lons, lats = meshgrid(lons, lats)
else:
    xdim,ydim=lon2d.shape
    lons=zeros([xdim+1,ydim+1],'d')
    lats=zeros([xdim+1,ydim+1],'d')
    for i in range(1,xdim):
        for j in range(1,ydim):
            lats[i,j]=.5*lat2d[i,j]+.5*lat2d[i-1,j-1]     
            lons[i,j]=.5*lon2d[i,j]+.5*lon2d[i-1,j-1]
    for i in range(1,xdim):
        lons[i,-1]=-lons[i,-3]+2*lons[i,-2]                    
        lats[i,-1]=-lats[i,-3]+2*lats[i,-2]                    
        lons[i,0]=-lons[i,2]+2*lons[i,1]                    
        lats[i,0]=-lats[i,2]+2*lats[i,1]                    
    for j in range(ydim+1):
        lons[-1,j]=-lons[-3,j]+2*lons[-2,j]                    
        lats[-1,j]=-lats[-3,j]+2*lats[-2,j]                    
        lons[0,j]=2*lons[1,j]-lons[2,j]                    
        lats[0,j]=2*lats[1,j]-lats[2,j]

#
# alter a matplotlib color table, 
# cm.jet is very useful scheme, but reversed colors are better for drought
cmap = cm.get_cmap('jet', 10)    # 10 discrete colors
#cmap = cm.get_cmap('summer_r', 10)    # 10 discrete colors

print "\nPlotting, please wait...maybe more than 10 seconds"
if proj=='lam': #Lambert Conformal
#    m = Basemap(llcrnrlon=-118.0,llcrnrlat=24.,urcrnrlon=-60.0,urcrnrlat=48.
0,\
#            resolution='l',area_thresh=1000.,projection='lcc',\
#            lat_1=70.,lon_0=-98.)
    m = Basemap(llcrnrlon=-80.6,llcrnrlat=38.4,urcrnrlon=-66.0,urcrnrlat=47.
7,\
            resolution='l',area_thresh=1000.,projection='lcc',\
            lat_1=65.,lon_0=-73.3)
    xtxt=200000. #offset for text
    ytxt=200000.
    parallels = arange(38.,48.,2.)
    meridians = arange(-80.,-66.,2.)
else: #cylindrical is default
#    m = Basemap(llcrnrlon=-180.,llcrnrlat=-90,urcrnrlon=180.,urcrnrlat=90.,\
#            resolution='c',area_thresh=10000.,projection='cyl')
    m = Basemap(llcrnrlon=startlon,llcrnrlat=-90,urcrnrlon=startlon+360.,urc
rnrlat=90.,\
            resolution='c',area_thresh=10000.,projection='cyl')
    xtxt=1.
    ytxt=0.
    parallels = arange(-90.,90.,30.)
    if startlon==-180:
        meridians = arange(-180.,180.,60.)
    else:
        meridians = arange(0.,360.,60.)

if verbose>1: print m.__doc__ 
plt.rcParams['font.size'] = 20
xsize = rcParams['figure.figsize'][0]
fig=figure(figsize=(xsize,m.aspect*xsize))
#ax = fig.add_axes([0.08,0.1,0.7,0.7],axisbg='white')
ax = fig.add_axes([0.07,0.00,0.8,1.0],axisbg='white')
# make a pcolor plot.
x, y = m(lons, lats)
p = m.pcolor(x,y,maskdat,shading='flat',cmap=cmap)
clim(*colorbounds)

# axes units units are left, bottom, width, height
#cax = axes([0.85, 0.1, 0.05, 0.7])  #  colorbar axes for map w/ no graticule
cax = axes([0.88, 0.1, 0.06, 0.81])  #  colorbar axes for map w/ graticule
#if datamax>1000.:
#    colorbar(format='%7.1e', cax=cax) # draw colorbar
#elif datamax>5.:
#    colorbar(format='%d', cax=cax) # draw colorbar
#else:
#    colorbar(format='%5.2f', cax=cax) # draw colorbar
colorbar(format='%3.1f', cax=cax)
#text(0.7,1.02,'mm')
text(0.3,1.02,'$^{o}$C',fontsize=20)

axes(ax)  # make the original axes current again

# plot blue dot on Norman OK and label it as such.
#if startlon==-180:
#    xpt,ypt = m(-97.4836,35.2556) 
#else:
#    xpt,ypt = m(-97.4836+360.,35.2556) 
#m.plot([xpt],[ypt],'bo') 
#text(xpt+xtxt,ypt+ytxt,'Norman')

xpt,ypt = m(-70.7500,41.7500)
text(xpt,ypt,'N')

# draw coastlines and political boundaries.
m.drawcoastlines(linewidth=2.0)
m.drawcountries(linewidth=2.0)
m.drawstates(linewidth=2.0)
# draw parallels and meridians.
# label on left, right and bottom of map.
#m.drawparallels(parallels,labels=[1,0,0,0])
#m.drawmeridians(meridians,labels=[1,1,0,1])
if not thetitle:
    title(thevar+extratext,fontsize=20)
else:
    title(thetitle,fontsize=20)
    
#if plotfile:
#    savefig(plotfile, dpi=72, facecolor='w', bbox_inches='tight', edgecolor=
'w', orientation='portrait')
#else:
#    show()

plt.savefig('map.png')
plt.savefig('map.eps')
show()

On 9/26/12 1:41 PM, Benjamin Root wrote:
>
>
> On Wed, Sep 26, 2012 at 2:07 PM, Michael Rawlins <raw...@ya... 
> <mailto:raw...@ya...>> wrote:
>
>
>
>         ------------------------------------------------------------------------
>         *From:* Benjamin Root <ben...@ou... <mailto:ben...@ou...>>
>         *To:* Michael Rawlins <raw...@ya...
>         <mailto:raw...@ya...>>
>         *Cc:* "mat...@li...
>         <mailto:mat...@li...>"
>         <mat...@li...
>         <mailto:mat...@li...>>
>         *Sent:* Wednesday, September 26, 2012 10:33 AM
>         *Subject:* Re: [Matplotlib-users] error reading netcdf file
>
>
>
>         On Wed, Sep 26, 2012 at 10:27 AM, Michael Rawlins
>         <raw...@ya... <mailto:raw...@ya...>> wrote:
>
>             Recently built and installed netCDF4-1.0. I'm running a
>             script that has worked on two other linux OS systems. Error:
>
>             File "test.py <http://test.py/>", line 96, in <module>
>                 data.missing_value=-9.99
>               File "netCDF4.pyx", line 2570, in
>             netCDF4.Variable.__setattr__ (netCDF4.c:28242)
>               File "netCDF4.pyx", line 2392, in
>             netCDF4.Variable.setncattr (netCDF4.c:26309)
>               File "netCDF4.pyx", line 1013, in netCDF4._set_att
>             (netCDF4.c:12699)
>             AttributeError: NetCDF: Write to read only
>
>
>             The statement in the code triggers the error is:
>
>             data.missing_value=-9.99 .
>
>             MR
>
>
>
>
>         This typically happens when one opens a netCDF4 Dataset object
>         in 'r' mode, and/or if the file permissions for the file was
>         set to read-only.  When modifying an attribute, it is
>         technically trying to write to the file.
>
>         Ben Root
>
>
>
>         Here is the file open statement:
>
>         ncfile = NetCDFFile('statsPrcp_Uncertainty2_winter.nc', 'r')
>
>         This worked fine in earlier versions.  No where in the code do
>         I try to write to a netCDF file. So I'm confused as to why
>         specifying the read of the netCDF file would result in an
>         error when designating the missing data value.
>
>         Here's the code:
>
>         # Works with the netCDF files in the tutorial, and also the
>         # files available for download at:
>         # http://www.cdc.noaa.gov/cdc/data.ncep.reanalysis.html
>         # Adapted from the basemap example plotmap_pcolor.py,
>         # Some of the variable names from that example are retained.
>         #
>         # Uses basemap's pcolor function.  Pcolor accepts arrays
>         # of the longitude and latitude  points of the vertices on the
>         pixels,
>         # as well as an array with the numerical value in the pixel.
>
>         verbose=0 #verbose=2 says a bit more
>
>         import sys,getopt
>         from mpl_toolkits.basemap import Basemap, shiftgrid, cm
>         from netCDF4 import Dataset as NetCDFFile
>         #from mpl_toolkits.basemap import NetCDFFile
>         from pylab import *
>         import  matplotlib.pyplot as plt
>
>         alloptions, otherargs=
>         getopt.getopt(sys.argv[1:],'ro:p:X:Y:v:t:l:u:n:') # note the :
>         after o and p
>         proj='lam'
>
>         cmap = cm.get_cmap('jet_r', 10)    # 10 discrete colors
>
>         print "\nPlotting, please wait...maybe more than 10 seconds"
>         if proj=='lam': #Lambert Conformal
>             m =
>         Basemap(llcrnrlon=-80.6,llcrnrlat=38.4,urcrnrlon=-66.0,urcrnrlat=47.7,\
>         resolution='l',area_thresh=1000.,projection='lcc',\
>                     lat_1=65.,lon_0=-73.3)
>         xtxt=200000. #offset for text
>         ytxt=200000.
>         parallels = arange(38.,48.,2.)
>         meridians = arange(-80.,-64.,2.)
>
>         xsize = rcParams['figure.figsize'][0]
>         fig=figure(figsize=(xsize,m.aspect*xsize))
>         #cax = axes([0.88, 0.1, 0.06, 0.81])  # colorbar axes for map
>         w/ graticule
>
>         ############################################################################################
>         subplots_adjust(left=None, bottom=None, right=0.9, top=None,
>         wspace=0.05, hspace=0.03)
>         # Make the first map at upper left
>         plt.subplot(2,2,1)
>
>         ncfile = NetCDFFile('statsPrcp_Uncertainty2_winter.nc', 'r')
>
>         xvar='rlon'
>         print "shape of "+xvar+': ',ncfile.variables[xvar].shape
>         if ncfile.variables[xvar][:].ndim ==1:
>             print "X is independent of Y"
>             lon1d=ncfile.variables[xvar][:]
>         else:
>             lon1d=False
>             if  ncfile.variables[xvar][:].ndim ==2:
>         lon2d=ncfile.variables[xvar][:]
>             if  ncfile.variables[xvar][:].ndim ==3:
>         lon2d=ncfile.variables[xvar][0,:,:]
>             print "shape of lond2d:", lon2d.shape
>
>         yvar='rlat'
>         print "shape of "+yvar+': ',ncfile.variables[yvar].shape
>         if ncfile.variables[yvar][:].ndim ==1:
>             print "Y is independent of X"
>             lat1d=ncfile.variables[yvar][:]
>         else:
>             lat1d=False
>             if  ncfile.variables[yvar][:].ndim ==2:
>         lat2d=ncfile.variables[yvar][:]
>             if  ncfile.variables[yvar][:].ndim ==3:
>         lat2d=ncfile.variables[yvar][0,:,:]
>             print "shape of lat2d:", lat2d.shape
>
>         thevar='diff'
>         data=ncfile.variables[thevar]
>         dataa=data[:]
>         theshape=dataa.shape
>         try:
>         add_offset=ncfile.variables[thevar].add_offset
>             print "will use add_offset=",add_offset
>         except:
>             add_offset=0.
>         print "shape of "+thevar+': ',theshape
>         if len(theshape)>2:
>             print "there are apparently",theshape[0],"records"
>             if not therec: therec=raw_input("enter record number to
>         plot=>")
>             therec=int(therec)
>             extratext=" rec=%d" %therec
>         if len(theshape)>3:
>             print "there are apparently",theshape[1],"levels"
>             if not thelev: thelev=raw_input("enter level number to
>         plot=>")
>             thelev=int(thelev)
>             extratext=extratext+" lev=%d" %thelev
>         if len(theshape)>3:
>         slice=dataa[therec,thelev,:,:]+add_offset
>         elif len(theshape)>2:
>             slice=dataa[therec,:,:]+add_offset
>         else:
>             slice=dataa+add_offset
>
>         data.missing_value=-9.99
>
>
> I think I know why this used to work in the past.  I think netCDF4 
> used to recognize the "missing_value" attribute as a special value.  
> It is now ._FillValue.  But I am still not sure you can save a value 
> to that attribute in a read-only Dataset. You might have to perform 
> the mask after extracting the data.
>
> Note, setting the _FillValue *after* extracting the data to the 
> "dataa" variable won't change "dataa".  I don't see how setting 
> data.missing_value is supposed to actually help you.
>
> Ben Root

Michael:  You can't change an attribute in a read-only dataset.  It 
should never have worked.

-Jeff

-- 
Jeffrey S. Whitaker         Phone  : (303)497-6313
Meteorologist               FAX    : (303)497-6449
NOAA/OAR/PSD  R/PSD1        Email  : Jef...@no...
325 Broadway                Office : Skaggs Research Cntr 1D-113
Boulder, CO, USA 80303-3328 Web    : http://tinyurl.com/5telg

On Wed, Sep 26, 2012 at 2:07 PM, Michael Rawlins <raw...@ya...>wrote:

>
>
>   ------------------------------
> *From:* Benjamin Root <ben...@ou...>
> *To:* Michael Rawlins <raw...@ya...>
> *Cc:* "mat...@li..." <
> mat...@li...>
> *Sent:* Wednesday, September 26, 2012 10:33 AM
> *Subject:* Re: [Matplotlib-users] error reading netcdf file
>
>
>
> On Wed, Sep 26, 2012 at 10:27 AM, Michael Rawlins <raw...@ya...>wrote:
>
> Recently built and installed netCDF4-1.0.  I'm running a script that has
> worked on two other linux OS systems. Error:
>
> File "test.py", line 96, in <module>
>     data.missing_value=-9.99
>   File "netCDF4.pyx", line 2570, in netCDF4.Variable.__setattr__
> (netCDF4.c:28242)
>   File "netCDF4.pyx", line 2392, in netCDF4.Variable.setncattr
> (netCDF4.c:26309)
>   File "netCDF4.pyx", line 1013, in netCDF4._set_att (netCDF4.c:12699)
> AttributeError: NetCDF: Write to read only
>
>
> The statement in the code triggers the error is:
>
> data.missing_value=-9.99 .
>
> MR
>
>
>
>
> This typically happens when one opens a netCDF4 Dataset object in 'r'
> mode, and/or if the file permissions for the file was set to read-only.
> When modifying an attribute, it is technically trying to write to the file.
>
> Ben Root
>
>
>
> Here is the file open statement:
>
> ncfile = NetCDFFile('statsPrcp_Uncertainty2_winter.nc', 'r')
>
> This worked fine in earlier versions.  No where in the code do I try to
> write to a netCDF file. So I'm confused as to why specifying the read of
> the netCDF file would result in an error when designating the missing data
> value.
>
> Here's the code:
>
> # Works with the netCDF files in the tutorial, and also the
> # files available for download at:
> # http://www.cdc.noaa.gov/cdc/data.ncep.reanalysis.html
> # Adapted from the basemap example plotmap_pcolor.py,
> # Some of the variable names from that example are retained.
> #
> # Uses basemap's pcolor function.  Pcolor accepts arrays
> # of the longitude and latitude  points of the vertices on the pixels,
> # as well as an array with the numerical value in the pixel.
>
> verbose=0 #verbose=2 says a bit more
>
> import sys,getopt
> from mpl_toolkits.basemap import Basemap, shiftgrid, cm
> from netCDF4 import Dataset as NetCDFFile
> #from mpl_toolkits.basemap import  NetCDFFile
> from pylab import *
> import  matplotlib.pyplot as plt
>
> alloptions, otherargs= getopt.getopt(sys.argv[1:],'ro:p:X:Y:v:t:l:u:n:') #
> note the : after o and p
> proj='lam'
>
> cmap = cm.get_cmap('jet_r', 10)    # 10 discrete colors
>
> print "\nPlotting, please wait...maybe more than 10 seconds"
> if proj=='lam': #Lambert Conformal
>     m =
> Basemap(llcrnrlon=-80.6,llcrnrlat=38.4,urcrnrlon=-66.0,urcrnrlat=47.7,\
>             resolution='l',area_thresh=1000.,projection='lcc',\
>             lat_1=65.,lon_0=-73.3)
> xtxt=200000. #offset for text
> ytxt=200000.
> parallels = arange(38.,48.,2.)
> meridians = arange(-80.,-64.,2.)
>
> xsize = rcParams['figure.figsize'][0]
> fig=figure(figsize=(xsize,m.aspect*xsize))
> #cax = axes([0.88, 0.1, 0.06, 0.81])  #  colorbar axes for map w/ graticule
>
>
> ############################################################################################
> subplots_adjust(left=None, bottom=None, right=0.9, top=None, wspace=0.05,
> hspace=0.03)
> # Make the first map at upper left
> plt.subplot(2,2,1)
>
> ncfile = NetCDFFile('statsPrcp_Uncertainty2_winter.nc', 'r')
>
> xvar='rlon'
> print "shape of "+xvar+': ',ncfile.variables[xvar].shape
> if ncfile.variables[xvar][:].ndim ==1:
>     print "X is independent of Y"
>     lon1d=ncfile.variables[xvar][:]
> else:
>     lon1d=False
>     if  ncfile.variables[xvar][:].ndim ==2: lon2d=ncfile.variables[xvar][:]
>     if  ncfile.variables[xvar][:].ndim ==3:
> lon2d=ncfile.variables[xvar][0,:,:]
>     print "shape of lond2d:", lon2d.shape
>
> yvar='rlat'
> print "shape of "+yvar+': ',ncfile.variables[yvar].shape
> if ncfile.variables[yvar][:].ndim ==1:
>     print "Y is independent of X"
>     lat1d=ncfile.variables[yvar][:]
> else:
>     lat1d=False
>     if  ncfile.variables[yvar][:].ndim ==2: lat2d=ncfile.variables[yvar][:]
>     if  ncfile.variables[yvar][:].ndim ==3:
> lat2d=ncfile.variables[yvar][0,:,:]
>     print "shape of lat2d:", lat2d.shape
>
> thevar='diff'
> data=ncfile.variables[thevar]
> dataa=data[:]
> theshape=dataa.shape
> try:
>     add_offset=ncfile.variables[thevar].add_offset
>     print "will use add_offset=",add_offset
> except:
>     add_offset=0.
> print "shape of "+thevar+': ',theshape
> if len(theshape)>2:
>     print "there are apparently",theshape[0],"records"
>     if not therec: therec=raw_input("enter record number to plot=>")
>     therec=int(therec)
>     extratext=" rec=%d" %therec
> if len(theshape)>3:
>     print "there are apparently",theshape[1],"levels"
>     if not thelev: thelev=raw_input("enter level number to plot=>")
>     thelev=int(thelev)
>     extratext=extratext+" lev=%d" %thelev
> if len(theshape)>3:
>     slice=dataa[therec,thelev,:,:]+add_offset
> elif len(theshape)>2:
>     slice=dataa[therec,:,:]+add_offset
> else:
>     slice=dataa+add_offset
>
> data.missing_value=-9.99
>
>
> I think I know why this used to work in the past.  I think netCDF4 used to
recognize the "missing_value" attribute as a special value.  It is now
._FillValue.  But I am still not sure you can save a value to that
attribute in a read-only Dataset.  You might have to perform the mask after
extracting the data.

Note, setting the _FillValue *after* extracting the data to the "dataa"
variable won't change "dataa".  I don't see how setting data.missing_value
is supposed to actually help you.

Ben Root

>________________________________
> From: Benjamin Root <ben...@ou...>
>To: Michael Rawlins <raw...@ya...> 
>Cc: "mat...@li..." <mat...@li...> 
>Sent: Wednesday, September 26, 2012 10:33 AM
>Subject: Re: [Matplotlib-users] error reading netcdf file
> 
>
>
>
>
>On Wed, Sep 26, 2012 at 10:27 AM, Michael Rawlins <raw...@ya...> wrote:
>
>Recently built and installed netCDF4-1.0.  I'm running a script that has worked on two other linux OS systems. Error:
>>
>>File "test.py", line 96, in <module>
>>    data.missing_value=-9.99
>>  File "netCDF4.pyx", line 2570, in netCDF4.Variable.__setattr__ (netCDF4.c:28242)
>>  File "netCDF4.pyx", line 2392, in netCDF4.Variable.setncattr (netCDF4.c:26309)
>>  File "netCDF4.pyx", line 1013, in netCDF4._set_att (netCDF4.c:12699)
>>AttributeError: NetCDF: Write to read only
>>
>>
>>The statement in the code triggers the error is:
>>
>>data.missing_value=-9.99 .
>>
>>MR
>>
>>
>
>
>This typically happens when one opens a netCDF4 Dataset object in 'r' mode, and/or if the file permissions for the file was set to read-only.  When modifying an attribute, it is technically trying to write to the file.
>
>Ben Root
>
>
>
>Here is the file open statement:
>
>ncfile = NetCDFFile('statsPrcp_Uncertainty2_winter.nc', 'r')
>
>This worked fine in earlier versions.  No where in the code do I try to write to a netCDF file. So I'm confused as to why specifying the read of the netCDF file would result in an error when designating the missing data value.
>
>Here's the code:
>
># Works with the netCDF files in the tutorial, and also the
># files available for download at:
># http://www.cdc.noaa.gov/cdc/data.ncep.reanalysis.html 
># Adapted from the basemap example plotmap_pcolor.py,
># Some of the variable names from that example are retained.
>#
># Uses basemap's pcolor function.  Pcolor accepts arrays
># of the longitude and latitude  points of the vertices on the pixels,
># as well as an array with the numerical value in the pixel. 
>
>verbose=0 #verbose=2 says a bit more
>
>import sys,getopt
>from mpl_toolkits.basemap import Basemap, shiftgrid, cm 
>from netCDF4 import Dataset as NetCDFFile 
>#from mpl_toolkits.basemap import  NetCDFFile
>from pylab import *
>import  matplotlib.pyplot as plt
>
>alloptions, otherargs= getopt.getopt(sys.argv[1:],'ro:p:X:Y:v:t:l:u:n:') # note the : after o and p
>proj='lam'
>
>cmap = cm.get_cmap('jet_r', 10)    # 10 discrete colors
>
>print "\nPlotting, please wait...maybe more than 10 seconds"
>if proj=='lam': #Lambert Conformal
>    m = Basemap(llcrnrlon=-80.6,llcrnrlat=38.4,urcrnrlon=-66.0,urcrnrlat=47.7,\
>            resolution='l',area_thresh=1000.,projection='lcc',\
>            lat_1=65.,lon_0=-73.3)
>xtxt=200000. #offset for text
>ytxt=200000.
>parallels = arange(38.,48.,2.)
>meridians = arange(-80.,-64.,2.)
>
>xsize = rcParams['figure.figsize'][0]
>fig=figure(figsize=(xsize,m.aspect*xsize))
>#cax = axes([0.88, 0.1, 0.06, 0.81])  #  colorbar axes for map w/ graticule
>
>############################################################################################
>subplots_adjust(left=None, bottom=None, right=0.9, top=None, wspace=0.05, hspace=0.03)
># Make the first map at upper left
>plt.subplot(2,2,1)
>
>ncfile = NetCDFFile('statsPrcp_Uncertainty2_winter.nc', 'r')
>
>xvar='rlon'
>print "shape of "+xvar+': ',ncfile.variables[xvar].shape
>if ncfile.variables[xvar][:].ndim ==1:
>    print "X is independent of Y"
>    lon1d=ncfile.variables[xvar][:]
>else:
>    lon1d=False
>    if  ncfile.variables[xvar][:].ndim ==2: lon2d=ncfile.variables[xvar][:]
>    if  ncfile.variables[xvar][:].ndim ==3: lon2d=ncfile.variables[xvar][0,:,:]
>    print "shape of lond2d:", lon2d.shape
>
>yvar='rlat'
>print "shape of "+yvar+': ',ncfile.variables[yvar].shape
>if ncfile.variables[yvar][:].ndim ==1:
>    print "Y is independent of X"
>    lat1d=ncfile.variables[yvar][:]
>else:
>    lat1d=False
>    if  ncfile.variables[yvar][:].ndim ==2: lat2d=ncfile.variables[yvar][:]
>    if  ncfile.variables[yvar][:].ndim ==3: lat2d=ncfile.variables[yvar][0,:,:] 
>    print "shape of lat2d:", lat2d.shape
>
>thevar='diff'
>data=ncfile.variables[thevar]
>dataa=data[:]
>theshape=dataa.shape
>try:
>    add_offset=ncfile.variables[thevar].add_offset
>    print "will use add_offset=",add_offset
>except:
>    add_offset=0.    
>print "shape of "+thevar+': ',theshape
>if len(theshape)>2:
>    print "there are apparently",theshape[0],"records"
>    if not therec: therec=raw_input("enter record number to plot=>")
>    therec=int(therec)
>    extratext=" rec=%d" %therec
>if len(theshape)>3:
>    print "there are apparently",theshape[1],"levels"
>    if not thelev: thelev=raw_input("enter level number to plot=>")
>    thelev=int(thelev)
>    extratext=extratext+" lev=%d" %thelev
>if len(theshape)>3: 
>    slice=dataa[therec,thelev,:,:]+add_offset
>elif len(theshape)>2: 
>    slice=dataa[therec,:,:]+add_offset
>else:
>    slice=dataa+add_offset
>
>data.missing_value=-9.99
>
>
>
>
>
>

On Wed, Sep 26, 2012 at 12:10 PM, Paul Tremblay <pau...@gm...>wrote:

> Thanks. I know when doing 8/9 in python 2.x you get 0. With python 3 you
> get a decimal (Hooray, Python 3!).
>
> I ran the script I submitted with python 3. Do I need to change the
> defects and totals from integers to floats to make my chart work
> universally?
>
> P.
>
>
That or just one of the two.  Either way would work.

Ben Root

So I rebuilt Python so that I would have Tkinter support, and using
TkAgg I get the behavior I want, so it's not mission critical to me to
figure this out anymore. But if anyone is interested in tracking it
down I will be glad to help.

On Wed, Sep 26, 2012 at 8:06 AM, Craig the Demolishor
<des...@gm...> wrote:
> Hi all,
>   I've been having some trouble getting interactive mode to work
> correctly with the WxAgg backend. I have these versions:
>
> [craigb@xxxxxx hists]$ python
> Python 2.7.3 (default, Aug 13 2012, 16:13:38)
> [GCC 4.1.2 20080704 (Red Hat 4.1.2-52)] on linux2
> Type "help", "copyright", "credits" or "license" for more information.
>>>> import matplotlib
>>>> matplotlib.__version__
> '1.1.1rc'
>>>> import wx
>>>> wx.__version__
> '2.8.12.1'
>>>>
>
>
> When I do something like this,
>
>>>> from matplotlib import pyplot
>>>> import numpy
>>>> pyplot.plot(numpy.arange(10), numpy.arange(10), 'r.')
> [<matplotlib.lines.Line2D object at 0x5561750>]
>>>> pyplot.show()
>
> I get a good-looking window with my plot. I can mouse over the window
> and get coordinates, there are buttons on the bottom of the window
> that I can push, etc. However, if I turn on interactive mode (I read
> somewhere that it's bad to turn on interactive mode after you've
> already made a plot, so below I've exited and started a new
> interactive session),
>
>>>> from matplotlib import pyplot
>>>> import numpy
>>>> pyplot.ion()
>>>> pyplot.plot(numpy.arange(10), numpy.arange(10), 'r.')
> [<matplotlib.lines.Line2D object at 0x153e2ad0>]
>
> Nothing shows at this point. If I continue,
>
>>>> pyplot.show()
>
> Still nothing shows. If I exit right now, I get a brief glimpse of my
> plot before python exits completely. I can get the plot to show by
> doing
>
>>>> pyplot.draw()
>
> But it's only the top half of the plot, and if I drag another window
> on top of it, it doesn't automatically redraw. No buttons, no
> mouse-over niceness. Issuing pyplot.draw() again gets me the full
> plot, but no mouse-overs, no buttons, and no redraw.
>
> Both MPL and wxPython were built from source on a RHEL5.8 machine, so
> maybe it's the libraries I am linking against...? Anyway, I've
> attached two screenshots of what my plots look like when they finally
> are drawn. Many many thanks in advance!
>
> --cb

I noticed today that when I create a bar graph with zero values that the
labels don't align correctly:

import matplotlib.pyplot as plt
import numpy as np

fig = plt.figure()
names = ['name a', 'name b', 'name c', 'named', 'name e', 'name f']
defects = [0, 0, 0, 5, 6, 7]
ax = fig.add_subplot(111)
widths=.75
ind = np.arange(len(defects))  # the x locations for the groups
ind = ind +  widths
bar = ax.bar(ind, defects, width=widths)
plt.xticks(ind + widths/2.0 , names, rotation=90)
ax.set_xlabel('Sorter')
ax.set_ylabel('Percentage (Average)')
plt.subplots_adjust( bottom=0.30)
ax.yaxis.grid(True, linestyle='-', which='major', color='lightgrey',
alpha=0.5)
ax.set_axisbelow(True)
plt.savefig('temp.png')

defects = [1, 2, 3, 5, 6, 7]
# same code...

When run with the defects with non zero values, the labels appear as I
expect; with zero values, the left label aligns incorrectly with the y axis.

Thanks

P.

Thanks. I know when doing 8/9 in python 2.x you get 0. With python 3 you
get a decimal (Hooray, Python 3!).

I ran the script I submitted with python 3. Do I need to change the defects
and totals from integers to floats to make my chart work universally?

P.

On Wed, Sep 26, 2012 at 4:31 AM, Pierre Haessig <pie...@cr...>wrote:

>  Hi,
>
> Just a detail :
>
> Le 26/09/2012 04:29, Paul Tremblay a écrit :
>
> percent = (np.divide(the_cumsum, the_sum)) * 100
>
> This lines doesn't work on my computer (numpy 1.6.2)
>
> Indeed, there is a casting issue :
> In [2]: percent
> Out[2]: array([  0,   0,   0,   0, 100])
>
> However, using the regular "/" operator instead of np.divide gives the
> proper result:
> In [8]: the_cumsum/the_sum*100
> Out[8]: array([  42.10526316,   71.05263158,   90.78947368,   97.36842105,
> 100.        ])
>
> Best,
> Pierre
>
>
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>
>

On Wed, Sep 26, 2012 at 11:07 AM, Pierre Haessig
<pie...@cr...>wrote:

> Le 26/09/2012 15:30, Benjamin Root a écrit :
> >
> > Probably could have the two axes listen for an "xlim_changed" event,
> > check to see if it belongs to its twin, and update itself accordingly
> > (without emitting).
> I guess you mean "ylim_changed" event ?
>
> (Maybe my description was not very clear, but the issue I'm having is
> with respective placement of yticks on left and right sides.
> xticks are the same, so no problem with these.)
>
> Best,
> Pierre
>
> Correct... twinx should have them listen to each other's ylim_changed,
twiny should have them listen to each other's xlim_changed.  Thanks for
catching that...

Ben Root

Le 26/09/2012 15:30, Benjamin Root a écrit :
>
> Probably could have the two axes listen for an "xlim_changed" event,
> check to see if it belongs to its twin, and update itself accordingly
> (without emitting).
I guess you mean "ylim_changed" event ?

(Maybe my description was not very clear, but the issue I'm having is
with respective placement of yticks on left and right sides.
xticks are the same, so no problem with these.)

Best,
Pierre