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copied!<p>You could try <a href="http://packages.python.org/guiqwt/" rel="nofollow"><code>guiqwt</code></a>. It's aimed for 2D graphs, but targets more specifically interactive plots (as opposed to Matplotlib, although it can handle some degree of interaction too). From the <em>guiqwt</em> documentation:</p> <blockquote> <p><strong>Overview</strong></p> <p>Based on PyQwt (plotting widgets for PyQt4 graphical user interfaces) and on the scientific modules NumPy and SciPy, guiqwt is a Python library providing efficient 2D data-plotting features (curve/image visualization and related tools) for interactive computing and signal/image processing application development.</p> <p><strong>Performances</strong></p> <p>The most popular Python module for data plotting is currently matplotlib, an open-source library providing a lot of plot types and an API (the pylab interface) which is very close to MATLAB’s plotting interface.</p> <p>guiqwt plotting features are quite limited in terms of plot types compared to matplotlib. However the currently implemented plot types are much more efficient. For example, the guiqwt image showing function (guiqwt.pyplot.imshow()) do not make any copy of the displayed data, hence allowing to show images which are much larger than with its matplotlib‘s counterpart. In other terms, when showing a 30-MB image (16-bits unsigned integers for example) with guiqwt, no additional memory is wasted to display the image (except for the offscreen image of course which depends on the window size) whereas matplotlib takes more than 600-MB of additional memory (the original array is duplicated four times using 64-bits float data types).</p> </blockquote> <p>(I haven't tried it, so I can't comment on these claims.)</p>

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