One nice thing is that the saved files are simply python commands to regenerate the plot, so it's easy for the user to automate making plots. The next release should support Python 3, too. #Veusz plot data codeThere's a bit of C++ code to handle the inner loops, but it's pretty responsive. Most of Veusz is written in Python with PyQt. When plotting, you can just enter expressions to investigate your data. There are a set of data manipulation plugins for filtering and so on (again you can write your own). You can easily write a plugin to load your own file format. Data is stored in named datasets, linked to external files or entered manually, or you can even capture it from sockets or external programs. It's now gained more data manipulation abilities. Each widget has a set of properties and formatting settings which can be changed. The widgets are arranged in a tree, a page holds a graph or a grid of graphs and a graph has axes and plotting widgets, and so on. I started with the idea that graphs should be built in an object-oriented fashion out of widgets. in veusz you might have to put your x variable in, as in if your x variable is called points, you'd use points y1. for example if you have two arrays, x and y, you can plot all x values for which y is 1 by using the expression x y1. Hopefully it's a good competitor to these (people tell me so), but I hadn't used them before embarking on Veusz! I mainly got annoyed with the state of command-line plotting facilities in astronomy and unix (like IDL, gnuplot, etc). hey, i think that what would help you is looking into slicing arrays numpy. I've been using xmgrace recently simply because it launches quickly, but it's (understandably) not retina and not native and just a pain really. matplotlib and its ilk are fine but require custom scripting. I personally find DataGraph's interface horrendous, even though its graphs are good, and Excel takes forever to make anything remotely decent. I usually use Plot ( ) which is great (scriptable, produces good looking graphs) but has a bit of a clunky interface. Though, sadly, it looks like this port doesn't replicate ggplot2's graphs pixel-for-pixel, which is a shame.Įdit: Incidentally if anyone has a recommendation for a good graphing app for OS X, I'd be all ears. A lot of thought has gone into ggplot2's default theme. It's more for creating good looking, publication-quality graphs. matplotlib which I suspect is more powerful overall. This is really exciting! I've always liked ggplot2 but sadly struggled with R syntax (the only time I ever used it was for ggplot2, and found it really confusing).įor anyone reading this, I don't think this is intended to replace e.g.
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