matplotlib-users Mailing List for matplotlib

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.

Thanks,
Aman

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

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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)
>
>
>
> ------------------------------------------------------------------------------
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>
>
>
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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


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])
plt.plot(storeMat[0][::2],storeMat[1][::2]/300.*100,'ko',markersize=3.5)
#plt.plot(storeMat[0][::2],storeMat[1][::2]/300.*100,'k')
plt.ylim(0,102)
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)

-- 
________________________
Jeffrey Spencer
jef...@gm...