2011/2/9 Curiouslearn <curiousle...@gmail.com>
>
> Can you please see the code below and let me know why the png figure
> comes out empty (it only contains the x-axis, does not contain the
> scatterplot). The pdf file has no such problems.
Seems like mpl is getting confused because of the rect argument of
add_axes. Note that bottom is 0.3 and height is 0.9 so bottom + heigt
> 1. Maybe different backends differs handling the overflow.
Does this change in line 12 fix your issue?:
ax1 = fig1.add_axes([0.1, 0.3, 0.8, 0.6])
Goyo
>
> I have tried saving another usual line plot in .png format and I had
> no problems. Does this have to do with scatter plot and .png format?
>
> Thank you.
>
> The code
>
> import matplotlib.pyplot as plt
> import numpy
>
> differences = numpy.random.uniform(-2,2,190)
>
> bin_values = numpy.arange(-2,2.6,0.1)
> hist, bins = numpy.histogram(differences, bins = bin_values)
>
> fig1 = plt.figure()
> fig1.set_figwidth(6)
> fig1.set_figheight(3)
> ax1 = fig1.add_axes([0.1, 0.3, 0.8, 0.9])
> ax1.patch.set_facecolor('Linen')
>
> for left, hist_val in zip(bins[:-1], hist):
> xvec = [left]*hist_val
> yvec = 0.05*numpy.arange(hist_val) + 0.1
> if len(xvec) > 0:
> ax1.scatter(xvec,yvec)
>
> ax1.axvline(1.3, ymax=0.6, color='DarkGreen')
>
> # The frame of the axes is referred to as
> # spines in matplotlib
> for i in ax1.spines.iteritems():
> if i[0] in ['top','right', 'left']:
> i[1].set_visible(False)
> print i
>
>
> # Ticks only in bottom
> ax1.xaxis.set_ticks_position('bottom')
> ax1.yaxis.set_ticks_position('none')
> ax1.set_ylim(bottom=0,top=1.5)
>
>
>
> fig1.savefig('trial_figure.png', facecolor='Linen')
> fig1.savefig('trial_figure.pdf', facecolor='Linen')
>
> ------------------------------------------------------------------------------
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------------------------------------------------------------------------------
The ultimate all-in-one performance toolkit: Intel(R) Parallel Studio XE:
Pinpoint memory and threading errors before they happen.
Find and fix more than 250 security defects in the development cycle.
Locate bottlenecks in serial and parallel code that limit performance.
http://p.sf.net/sfu/intel-dev2devfeb
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