Binaries are available for Linux x86, Mac OS X and Windows, and source allows it to be built for these and other platforms. It relies heavily on the Python numpy libraries for handling data. There are some small parts written in C and C++ to make the program faster. Veusz is multiplatform as it is written in Python and uses PyQt for user interface and plotting.
Unhide tool boxes veusz update#
These datasets update automatically if the underlying data is reloaded. A powerful feature is the ability to create new datasets in the program based on functions of other datasets. And if that’s not good enough, you can send numpy arrays to Veusz using the embedding interface, or define an import plugin, which is a simple Python script for reading the data. Importantly, it can load 1D and 2D data from FITS tables or images. It also supports CSV files (with an optional name for a dataset above each column). Its default format is a simple space-delimited text format which can contain a descriptor describing dataset names, columns and data types, or specified in the program. It supports 1D numeric, date and text datasets, and 2D numerical arrays. Veusz can read data in several different formats. Each graph can have as many axes as you like. Multiple graph widgets can be placed on a page and in a grid widget which arranges the graphs inside it. These plotting widgets are placed inside graph widgets. It also has a function-fitting widget for doing a chi-squared fit to data. It also supports plotting functions (which can be defined using numpy functions or in external python modules), histograms (which can be computed from data), contour plots (including sub-contour levels and labelled contours), automatic data keys, image plots (with different color maps), color bars, shapes (including arrows) and external image files. Veusz has scatter plots, with optional error bars (of several styles), joining-lines (stepped or beziers curves), fills and transparency, and allows for gaps in data.
Veusz can export several vector and bitmap formats, including PNG, EPS, PDF, SVG and EMF. Indeed, Veusz saved documents are simply Python scripts using the same set of commands and are easily modified. However, most of the functionality can also be accessed using a command interface, which can be used from Python command line console window, an embedding Python module or commands sent to it from stdin. The standard way to build up the plot is to use the GUI to add widgets to form a tree, reading data from external files. Veusz builds plots out of widgets, each of which has a set of properties and formatting options which can be modified. Although I initially found the command line interface to be the most important part of a plotting package, since developing Veusz, I now use its GUI almost exclusively as it’s rather powerful and easy to use. I wanted a free, easy to use and powerful package and so I started writing Veusz in 2004.
Unhide tool boxes veusz manuals#
Many were difficult to use, requiring libraries of other peoples’ code or a lot of work going through manuals (e.g. Several were not licensed freely (e.g., sm, idl). Some were fairly easy to use but old fashioned and/or limited (e.g., qdp, sm, grace, gnuplot). As an astronomer, I was dissatisfied with every plotting package I had used. Veusz (pronounced “views”) is a python-based GUI plotting package that I ( Jeremy Sanders) have developed. Jeremy is a postdoc working in the X-Ray Group at the Institute of Astronomy in the University of Cambridge in the UK. This is a guest post by Jeremy Sanders about the plotting package he’s developed.
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