[SciPy-User] ANN: Veusz 1.8

Jeremy Sanders jeremy@jeremysanders....
Mon Jun 21 07:57:36 CDT 2010

Veusz 1.8
Velvet Ember Under Sky Zenith

Veusz is Copyright (C) 2003-2010 Jeremy Sanders <jeremy@jeremysanders.net>
Licenced under the GPL (version 2 or greater).

Veusz is a Qt4 based scientific plotting package. It is written in
Python, using PyQt4 for display and user-interfaces, and numpy for
handling the numeric data. Veusz is designed to produce
publication-ready Postscript/PDF/SVG output. The user interface aims
to be simple, consistent and powerful.

Veusz provides a GUI, command line, embedding and scripting interface
(based on Python) to its plotting facilities. It also allows for
manipulation and editing of datasets. Data can be captured from
external sources such as internet sockets or other programs.

Changes in 1.8:
 * Rewritten several inner loops in C++ giving speedups for large datasets
 * Lines, points and shapes are clipped before plotting, which speeds up
   plotting with some Qt backends and reduces file sizes
 * Data histogram feature added for calculating histograms of datasets,
   including cumulative histograms
 * Data import plugins allow the user to add support for importing any 
   file type - see Veusz wiki for details
 * Experimental Bezier curve option for joining data points

Minor changes in 1.8:
 * Fix zoom button default action
 * Speed up user interface when handling large numbers of datasets
 * Reset buttons added to several dialog boxes
 * Add engineering number formatting for axes: %VE giving e.g. 1k or 50m
 * Add drop down list of number formatting option to axis tick labels
 * Force Qt dialog boxes to be used instead of KDE ones, as KDE ones are
   currently broken
 * Use miter joins for plotting data points for sharper appearance
 * Add SetAntiAliasing command to command interface to toggle anti aliasing
 * Fix highlighting of errors when entering settings
 * Fix conversion of numpy to QVariants for new versions of PyQt
 * New point styles added for showing limits
 * Reworked internals of import dialog substantially
 * Several other minor bug fixes

Note for people building from source and package builders:
 * Veusz now contains C++ code, dependent for building on the development
   libraries of SIP, PyQt4 and Qt4. Note that Veusz will still work (but
   more slowly) without this helper library.

Features of package:
 * X-Y plots (with errorbars)
 * Line and function plots
 * Contour plots
 * Images (with colour mappings and colorbars)
 * Stepped plots (for histograms)
 * Bar graphs
 * Plotting dates
 * Fitting functions to data
 * Stacked plots and arrays of plots
 * Plot keys
 * Plot labels
 * Shapes and arrows on plots
 * LaTeX-like formatting for text
 * Scripting interface
 * Dataset creation/manipulation
 * Embed Veusz within other programs
 * Text, CSV, FITS and user-plugin importing
 * Data can be captured from external sources
 * User defined functions, constants and can import external Python 

Requirements for source install:
 Python (2.4 or greater required)
 Qt >= 4.3 (free edition)
 PyQt >= 4.3 (SIP is required to be installed first)
 numpy >= 1.0

 Microsoft Core Fonts (recommended for nice output)
 PyFITS >= 1.1 (optional for FITS import)
 pyemf >= 2.0.0 (optional for EMF export)
 For EMF and better SVG export, PyQt >= 4.6 or better is
   required, to fix a bug in the C++ wrapping

For documentation on using Veusz, see the "Documents" directory. The
manual is in PDF, HTML and text format (generated from docbook). The
examples are also useful documentation. Please also see and contribute
to the Veusz wiki: http://barmag.net/veusz-wiki/

Issues with the current version:

 * Plots can sometimes be slow using antialiasing. Go to the
   preferences dialog or right click on the plot to disable

 * Some recent versions of PyQt/SIP will causes crashes when exporting
   SVG files. Update to 4.7.4 (if released) or a recent snapshot to
   solve this problem.

If you enjoy using Veusz, I would love to hear from you. Please join
the mailing lists at


to discuss new features or if you'd like to contribute code. The
latest code can always be found in the SVN repository.

Jeremy Sanders

More information about the SciPy-User mailing list