matplotlib-users Mailing List for matplotlib

Hi,

Well the first bit about wanting a specific column and the last bit about
not wanting to print all the data in and read it back, you get that from the
example I gave you. If you paste what I wrote for you line by line it should
become clearer for you, additionally it avoids you have to write your own
parsing code.

As far as your plotting goes, unless you actually post what you are entering
in the script (exactly as you have it), then it is impossible to say. For
example

plt.plot()
plt.show

there is no way that is all you have? if it is, then of course you will get
a fail as you are asking matplotlib to plot but are not providing it with
any data to plot!

Perhaps I am being particularly dense but "What I now need to do is have the
information in that column plotted as the number of rows vs. the mean value
of all of the rows." means nothing to me. Sorry. What do you want on the X
and Y... do you mean you want to plot your individual column (8 i think you
called it) against the mean of all the other rows? If so I would expect you
would have a dimensions issue

Martin


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Hi,

I create a collection item, add it to the current axis, and try to plot data
points over it but the points do not show up. Here is my code:

    fig = plt.figure(figsize=(10,10))
    ax = fig.gca()
    bb_collect = beachball.Beach([strike,dip,rake], linewidth=0.4,
facecolor='gray', bgcolor='w', edgecolor='k',alpha=1.0, xy=(0,0), width=2,
size=100, nofill=False,zorder=100)
    a = ax.add_collection(bb_collect)
    ax.autoscale_view(tight=False, scalex=True, scaley=True)
    plt.plot(x,y,linewidth=0,marker='+',ms=20,markeredgewidth=3)
    plt.xlim(-1,1)
    plt.ylim(-1,1)
    plt.savefig(evid[nm]+".png")

I can plot the collection by itself and the points by themselves, but can't
seem to plot the points on top of the collection object. Can anyone tell me
what I'm doing wrong?

Cheers!
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Hi Martin,

     Thank for the relpy.  What I have is a script that reads the data from
a large file then prints out the values listed in a particular column. What
I now need to do is have the information in that column plotted as the
number of rows vs. the mean value of all of the rows. What I have so far is 

import matplotlib.pyplot as plt

masses = []

f = open( 'myfile.txt','r')
f.readline()
for line in f:
 if line != ' ':      
    line = line.strip()          # Strips end of line character 
    columns = line.split()    # Splits into coloumn 
    mass = columns[8]      # Column which contains mass values
    mass = float(mass)
    masses.append(mass)
    print(mass)

plt.plot()
plt.show


I am thinking I can do something like 

'y runs fron 0 to n where n == len(masses) '
x = 'mass_avg = sum(masses)/len(masses)'

Problem is I don' tknow how to have matplotlib do it with out giving me an
error about dimentions. I would also like to do this with out having to
write and read from another file. I alos need to to be able to work on files
with ddifering numbers of rows.

Thanks





mdekauwe wrote:
> 
> I wasn't quite able to follow exactly what you wanted to do but maybe this
> will help. I am going to generate some "data" that I think sounds a bit
> like yours, write it to a file, clearly you already have this. Then I am
> going to read it back in and plot it, e.g.
> 
> import matplotlib.pyplot as plt
> import numpy as np
> 
> # Generate some data a little like yours, I think? 
> # print it to a file, i.e. I am making your myfile.txt
> numrows = 100
> numcols = 8
> mass = np.random.normal(0, 1, (numrows  * numcols)).reshape(numrows,
> numcols)
> f = open("myfile.txt", "w")
> for i in xrange(numrows):
>     for j in xrange(numcols):
>         print >>f,  mass[i,j],
>     print >> f
> f.close()    
> 
> # read the file back in
> mass = np.loadtxt("myfile.txt")
> 
> # plot the 8th column
> fig = plt.figure()
> ax = fig.add_subplot(111)
> ax.plot(mass[:,7], 'r-o')
> ax.set_xlabel("Time")
> ax.set_ylabel("Mass")
> plt.show()
> 
> 
> I wasn't clear on the mean bit, but that is easy to do with numpy, e.g. 
> 
> mean_mass = np.mean(mass[:,8])
> 
> etc.
> 
> Numpy et al is great for stuff like this.
> 
> Hope that helps,
> 
> Martin
> 
> 

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Hi,

I create a collection item, add it to the current axis, and try to plot data
points over it but the points do not show up. Here is my code:

    fig = plt.figure(figsize=(10,10))
    ax = fig.gca()
    bb_collect = beachball.Beach([strike,dip,rake], linewidth=0.4,
facecolor='gray', bgcolor='w', edgecolor='k',alpha=1.0, xy=(0,0), width=2,
size=100, nofill=False,zorder=100)
    a = ax.add_collection(bb_collect)
    ax.autoscale_view(tight=False, scalex=True, scaley=True)
    plt.plot(x,y,linewidth=0,marker='+',ms=20,markeredgewidth=3)
    plt.xlim(-1,1)
    plt.ylim(-1,1)
    plt.savefig(evid[nm]+".png")

I can plot the collection by itself and the points by themselves, but can't
seem to plot the points on top of the collection object. Can anyone tell me
what I'm doing wrong?

Cheers!

OK, so it seems to be working if I use fig=plt.figure() instead of fig =
Figure() but I'm not sure why this is the case.

-Aman

On Thu, Aug 25, 2011 at 10:50 AM, Aman Thakral <ama...@gm...>wrote:

> Sorry about that.  I've attached a sample script.
> -Aman
>
>
> On Wed, Aug 24, 2011 at 9:05 PM, John Hunter <jd...@gm...> wrote:
>
>>
>>
>>
>>
>> On Aug 24, 2011, at 4:09 PM, Aman Thakral <ama...@gm...> wrote:
>>
>> > Hi,
>> >
>> > I've recently created a web application, using Django, to dynamically
>> create maps from weather data.  When I tried using FigCanvasAgg and
>> figure.Figure, the image that was responded by the web server (using
>> canvas.print_png and django.http.HttpResponse) did not show the map, just
>> the scatter points.  When I just saved the figure (that was created using a
>> matplotlib.pyplot.figure() instance) in folder that is statically available
>> on the web server, the image is perfect.  There is an advantage to using the
>> latter method as the saved images can be cached, but I'm curious as to why
>> the FigCanvasAgg method doesn't work.
>> >
>> > Is this a known issue?  If so, are there any workarounds?
>> >
>> > Any help on this issue would be greatly appreciated.
>> >
>>
>> You will need to post an example script.
>
>
>

I wasn't quite able to follow exactly what you wanted to do but maybe this
will help. I am going to generate some "data" that I think sounds a bit like
yours, write it to a file, clearly you already have this. Then I am going to
read it back in and plot it, e.g.

import matplotlib.pyplot as plt
import numpy as np

# Generate some data a little like yours, I think? 
# print it to a file, i.e. I am making your myfile.txt
numrows = 100
numcols = 8
mass = np.random.normal(0, 1, (numrows  * numcols)).reshape(numrows,
numcols)
f = open("myfile.txt", "w")
for i in xrange(numrows):
    for j in xrange(numcols):
        print >>f,  mass[i,j],
    print >> f
f.close()    

# read the file back in
mass = np.loadtxt("myfile.txt")

# plot the 8th column
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(mass[:,7], 'r-o')
ax.set_xlabel("Time")
ax.set_ylabel("Mass")
plt.show()


I wasn't clear on the mean bit, but that is easy to do with numpy, e.g. 

mean_mass = np.mean(mass[:,8])

etc.

Numpy et al is great for stuff like this.

Hope that helps,

Martin

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That does the trick. Didn't know where the clipping was occurring but 
couldn't find anything in plot so makes sense it was in the line. 
Assuming the comma just unpacks the tuple to get direct access to line.

Thanks for the help

On 25/08/11 03:23, Eric Firing wrote:
> On 08/24/2011 06:53 AM, Jeffrey Spencer wrote:
>> I created this graph below but if I set the y axis upper limit to 100.
>> It cuts off the top half of the dots which are at 100. I wasn't sure how
>> to get the dots to show properly like now but set the y-axis upper limit
>> to 100 instead of like 102. It makes the data look misleading to have
>> that little tail above 100. Essentially a way to create the axis but
>> offset the actual axis grid to 95% of that or any other suggestions.
>>
>> Cheers
> Try the changes indicated below.
>
>>
>> Script used to create here:
>>
>> import matplotlib.pyplot as plt
>> import matplotlib.ticker as tick
>> from numpy import load, sqrt, shape, size, loadtxt, transpose
>>
>> def clear_spines(ax):
>> ax.spines['top'].set_color('none')
>> ax.spines['right'].set_color('none')
>> def set_spineLineWidth(ax, lineWidth):
>> for i in ax.spines.keys():
>> ax.spines[i].set_linewidth(lineWidth)
>> def showOnlySomeTicks(x, pos):
>> s = str(int(x))
>> if x == 5000:
>> return '5e3'#'%.0e' % x
>> return ''
>>
>>
>> plt.close('all')
>> golden_mean = (sqrt(5)-1.0)/2.0 # Aesthetic ratio
>> fig_width = fig_width_pt*inches_per_pt # width in inches
>> fig_height = fig_width*golden_mean # height in inches
>> fig_size = [fig_width,fig_height]
>> tick_size = 9
>> fontlabel_size = 10.5
>> params = {'backend': 'wxAgg', 'axes.labelsize': fontlabel_size,
>> 'text.fontsize': fontlabel_size, 'legend.fontsize': fontlabel_size,
>> 'xtick.labelsize': tick_size, 'ytick.labelsize': tick_size,
>> 'text.usetex': True, 'figure.figsize': fig_size}
>> plt.rcParams.update(params)
>> sizeX = storeMat[0].size
>> fig = plt.figure(1)
>> #figure(num=None, figsize=(8, 6), dpi=80, facecolor='w', edgecolor='k')
>> #fig.set_size_inches(fig_size)
>> plt.clf()
>> ax = plt.axes([0.145,0.18,0.95-0.155,0.95-0.2])
> pts, =
> plt.plot(storeMat[0][::2],storeMat[1][::2]/300.*100,'ko',markersize=3.5)
> # Note: the comma after "pts" is intentional.
> pts.set_clip_on(False)
>
>
>> #plt.plot(storeMat[0][::2],storeMat[1][::2]/300.*100,'k')
> plt.ylim(0,100)
>
>> plt.xlabel('Number of Channels')
>> plt.ylabel('Recognition Accuracy')
>> set_spineLineWidth(ax,spineLineWidth)
>> clear_spines(ax)
>> ax.yaxis.set_ticks_position('left')
>> ax.xaxis.set_ticks_position('bottom')
>> #ax.xaxis.set_minor_formatter(tick.FuncFormatter(showOnlySomeTicks))
>> #plt.legend()
>> for i in outExt:
>> plt.savefig('lineVersion/'+outFile+i, dpi = mydpi)
>>
>>
>>
>> ------------------------------------------------------------------------------
>> EMC VNX: the world's simplest storage, starting under $10K
>> The only unified storage solution that offers unified management
>> Up to 160% more powerful than alternatives and 25% more efficient.
>> Guaranteed. http://p.sf.net/sfu/emc-vnx-dev2dev
>>
>>
>>
>> _______________________________________________
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>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
> ------------------------------------------------------------------------------
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> The only unified storage solution that offers unified management
> Up to 160% more powerful than alternatives and 25% more efficient.
> Guaranteed. http://p.sf.net/sfu/emc-vnx-dev2dev
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users

On Aug 24, 2011, at 4:09 PM, Aman Thakral <ama...@gm...> wrote:

> Hi,
> 
> I've recently created a web application, using Django, to dynamically create maps from weather data.  When I tried using FigCanvasAgg and figure.Figure, the image that was responded by the web server (using canvas.print_png and django.http.HttpResponse) did not show the map, just the scatter points.  When I just saved the figure (that was created using a matplotlib.pyplot.figure() instance) in folder that is statically available on the web server, the image is perfect.  There is an advantage to using the latter method as the saved images can be cached, but I'm curious as to why the FigCanvasAgg method doesn't work.
> 
> Is this a known issue?  If so, are there any workarounds?
> 
> Any help on this issue would be greatly appreciated.
> 

You will need to post an example script. 

Thank you Gary. I will definitely read the numpy doucs 

Gary Ruben-2 wrote:
> 
> As you show it, mass will be a string, so you'll need to convert it to
> a float first, then add it to a list. You can then manipulate the
> values in the list to compute your mean, or whatever, which matplotlib
> can use as input to its plot() function or whichever type of plot
> you're after. Alternatively, since the Python numpy module is made for
> manipulating data like this, it can probably read your data in a
> single function call and easily compute the things you want. However,
> if you are really that new to programming, you may struggle, so I'd
> suggest reading first going to scipy.org and reading up on numpy. When
> you understand the basics of numpy, matplotlib's documentation should
> make a lot more sense.
> 
> Gary
> 
> On Thu, Aug 25, 2011 at 6:48 AM, surfcast23 <sur...@gm...> wrote:
>>
>> I am fairly new to programing and have a question regarding matplotlib. I
>> wrote a python script that reads in data from the outfile of another
>> program
>> then prints out the data from one column.
>>
>> f = open( 'myfile.txt','r')
>> for line in f:
>> if line != ' ':
>>  line = line.strip()       # Strips end of line character
>>  columns = line.split() # Splits into coloumn
>>  mass = columns[8]    # Column which contains mass values
>>  print(mass)
>>
>> What I now need to do is have matplotlib take the values printed in
>> 'mass'
>> and plot number versus mean mass. I have read the documents on the
>> matplotlib website, but they don't really address how to get data from a
>> script(or I just did not see it) If anyone can point me to some
>> documentation that explains how I do this it would be really appreciated.
>>  Thanks in advance
>>
>> --
>> View this message in context:
>> http://old.nabble.com/How-do-you-Plot-data-generated-by-a-python-script--tp32328822p32328822.html
>> Sent from the matplotlib - users mailing list archive at Nabble.com.
>>
>>
>> ------------------------------------------------------------------------------
>> EMC VNX: the world's simplest storage, starting under $10K
>> The only unified storage solution that offers unified management
>> Up to 160% more powerful than alternatives and 25% more efficient.
>> Guaranteed. http://p.sf.net/sfu/emc-vnx-dev2dev
>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
> 
> ------------------------------------------------------------------------------
> EMC VNX: the world's simplest storage, starting under $10K
> The only unified storage solution that offers unified management 
> Up to 160% more powerful than alternatives and 25% more efficient. 
> Guaranteed. http://p.sf.net/sfu/emc-vnx-dev2dev
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> 
> 

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As you show it, mass will be a string, so you'll need to convert it to
a float first, then add it to a list. You can then manipulate the
values in the list to compute your mean, or whatever, which matplotlib
can use as input to its plot() function or whichever type of plot
you're after. Alternatively, since the Python numpy module is made for
manipulating data like this, it can probably read your data in a
single function call and easily compute the things you want. However,
if you are really that new to programming, you may struggle, so I'd
suggest reading first going to scipy.org and reading up on numpy. When
you understand the basics of numpy, matplotlib's documentation should
make a lot more sense.

Gary

On Thu, Aug 25, 2011 at 6:48 AM, surfcast23 <sur...@gm...> wrote:
>
> I am fairly new to programing and have a question regarding matplotlib. I
> wrote a python script that reads in data from the outfile of another program
> then prints out the data from one column.
>
> f = open( 'myfile.txt','r')
> for line in f:
> if line != ' ':
>  line = line.strip()       # Strips end of line character
>  columns = line.split() # Splits into coloumn
>  mass = columns[8]    # Column which contains mass values
>  print(mass)
>
> What I now need to do is have matplotlib take the values printed in 'mass'
> and plot number versus mean mass. I have read the documents on the
> matplotlib website, but they don't really address how to get data from a
> script(or I just did not see it) If anyone can point me to some
> documentation that explains how I do this it would be really appreciated.
>  Thanks in advance
>
> --
> View this message in context: http://old.nabble.com/How-do-you-Plot-data-generated-by-a-python-script--tp32328822p32328822.html
> Sent from the matplotlib - users mailing list archive at Nabble.com.
>
>
> ------------------------------------------------------------------------------
> EMC VNX: the world's simplest storage, starting under $10K
> The only unified storage solution that offers unified management
> Up to 160% more powerful than alternatives and 25% more efficient.
> Guaranteed. http://p.sf.net/sfu/emc-vnx-dev2dev
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>