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<div><h1 id="a0000000235">A.3 Delivering Talks in PyXPlot</h1>
<p>Going one step further, PyXPlot can be used as a stand-alone tool for designing slides for talks; it has several advantages over other presentation tools. All of the text which is placed on slides is rendered neatly in L<sup style="font-variant:small-caps; margin-left:-0.3em">a</sup>T<sub style="text-transform:uppercase; margin-left:-0.2em">e</sub>X. Images can be placed on slides using the <tt class="tt">jpeg</tt><a name="a0000001657" id="a0000001657"></a> and <tt class="tt">eps</tt><a name="a0000001658" id="a0000001658"></a> commands, and placed at any arbitrary coordinate position on the slide. In comparison with programs such as Microsoft <i class="it">Powerpoint</i><a name="a0000001659" id="a0000001659"></a> and OpenOffice<a name="a0000001660" id="a0000001660"></a> <i class="it">Impress</i>, the text looks much neater, especially if equations or unusual characters are required. In comparison with T<sub style="text-transform:uppercase; margin-left:-0.2em">e</sub>X-based programs such as FoilT<sub style="text-transform:uppercase; margin-left:-0.2em">e</sub>X, it is much easier to incorporate images around text to create colourful slides which will keep an audience attentive. </p><p>As an additional advantage, graphs can be plotted within the scripts describing each slide, directly from datafiles in your local filesystem. If you receive new data shortly before giving a talk, it is a simple matter to re-run the PyXPlot scripts and your slides will automatically pick up the new datafiles. </p><p>Below, we outline our recipe for designing slides in PyXPlot. There are many steps, but they do not take much time; many simply involve pasting text into various files. Readers of the printed version of the manual may find it easier to copy these files from the HTML version of this manual on the PyXPlot website. </p></div>
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<li><a href="sect0235.html">A.3.1 Setting up Infrastructure</a>
</li><li><a href="sect0236.html">A.3.2 Writing A Short Example Talk</a>
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