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<b class="current">2010 May 19: PyXPlot 0.8.0</b>
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<div><h2 id="a0000000251">2010 May 19: PyXPlot 0.8.0</h2>
<h3 id="a0000001711">Summary:</h3>
<p>This release is a major update, for which PyXPlot’s original python code has been completely rewritten in C with the addition of many new features. Because of the scale of this update, there is some minor syntax incompatibility with previous versions where features have undergone particularly heavy change. The most apparent change is the increase in speed and efficiency resultant from the use of a compiled language: especially when handling large datafiles, PyXPlot 0.8.0 can run more than an order-of-magnitude faster than previous versions. </p><h3 id="a0000001712">Details:</h3>
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<li><p>The handling of large datafiles has been streamlined to require around an order-of-magnitude less time and memory. </p></li><li><p>PyXPlot’s mathematical environment has been extended to handle complex numbers and quantities with physical units. </p></li><li><p>The range of mathematical functions built into PyXPlot has been massively extended. </p></li><li><p>The <tt class="tt">solve</tt> command has been added to allow the solution of systems of equations. </p></li><li><p>The <tt class="tt">maximise</tt> and <tt class="tt">minimise</tt> commands have been added to allow searches for local extrema of functions. </p></li><li><p>An <tt class="tt">fft</tt> command has been added for performing Fourier transforms on data. </p></li><li><p>New plot styles – <tt class="tt">filledregion</tt> and <tt class="tt">yerrorshaded</tt> – have been added for plotting filled error regions. </p></li><li><p>The configuration of linked axes has been entirely redesigned. </p></li><li><p>Parametric function plotting has been implemented. </p></li><li><p>Colours can now be specified by RGB, HSB or CMYK components, as well as by name. </p></li><li><p>Several commands, e.g. <tt class="tt">box</tt>, <tt class="tt">circle</tt>, <tt class="tt">ellipse</tt>, etc., have been added to allow vector graphics to be produced in PyXPlot’s multiplot environment. </p></li><li><p>The <tt class="tt">jpeg</tt> command has been generalised to allow the incorporation of not only <tt class="tt">jpeg</tt> images, but also <tt class="tt">bmp</tt>, <tt class="tt">gif</tt> and <tt class="tt">png</tt> images, onto multiplot canvases. The command has been renamed <tt class="tt">image</tt> in recognition of its wider applicability. Image transparency is now supported in <tt class="tt">gif</tt> and <tt class="tt">png</tt> images. </p></li><li><p>The <tt class="tt">spline</tt> command, now renamed the <tt class="tt">interpolate</tt> command, has been extended up provide many types of interpolation between datapoints. </p></li><li><p>A wide range of conditional and flow control structures have been added to PyXPlot’s command language – these are the <tt class="tt">do</tt>, <tt class="tt">for</tt>, <tt class="tt">foreach</tt>, <tt class="tt">if</tt> and <tt class="tt">while</tt> commands and the <tt class="tt">conditionalS</tt> and <tt class="tt">conditionalN</tt> mathematical functions. </p></li><li><p>Input filters have been introduced as a mechanism by which datafiles in arbitrary formats can be read. </p></li><li><p>PyXPlot’s commandline interface now supports tab completion. </p></li><li><p>The <tt class="tt">show</tt> command has been reworked to produce pastable output. </p></li><li><p>Many minor bugs have been fixed. </p></li>
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