J
Jeremy Sanders
I'm pleased to announce Veusz 1.0. Source, windows and linux i386 binaries
are available. Jeremy Sanders
Veusz 1.0
---------
Velvet Ember Under Sky Zenith
-----------------------------
http://home.gna.org/veusz/
Veusz is Copyright (C) 2003-2007 Jeremy Sanders <[email protected]>
Licenced under the GPL (version 2 or greater).
Veusz is a scientific plotting package 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
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.
Feature changes from 0.99.0:
* Import of Text datasets
* Labels can be plotted next to X-Y points
* Numbers can be directly plotted by entering into X-Y datasets as X and Y
* More line styles
* Loaded document and functions are checked for unsafe Python features
* Contours can be labelled with numbers
* 2D dataset creation to make 2D datasets from x, y, z 1D datasets
Bug and minor fixes from 0.99.0:
* Zooming into X-Y images works now
* Contour plots work on datasets with non equal X and Y sizes
* Various fixes for datasets including NaN or Inf
* Large changes to data import filter to support loading strings (and dates
later)
* Reduce number of undo levels for memory/speed
* Text renderer rewritten to be more simple
* Improved error dialogs
* Proper error dialog for invalid loading of documents
Features of package:
* X-Y plots (with errorbars)
* Line and function plots
* Contour plots
* Images (with colour mappings and colorbars)
* Stepped plots (for histograms)
* Fitting functions to data
* Stacked plots and arrays of plots
* Plot keys
* Plot labels
* LaTeX-like formatting for text
* EPS/PDF/PNG export
* Scripting interface
* Dataset creation/manipulation
* Embed Veusz within other programs
* Text, CSV and FITS importing
Requirements:
Python (2.3 or greater required)
http://www.python.org/
Qt >= 4.3 (free edition)
http://www.trolltech.com/products/qt/
PyQt >= 4.3 (SIP is required to be installed first)
http://www.riverbankcomputing.co.uk/pyqt/
http://www.riverbankcomputing.co.uk/sip/
numpy >= 1.0
http://numpy.scipy.org/
Microsoft Core Fonts (recommended for nice output)
http://corefonts.sourceforge.net/
PyFITS >= 1.1 (optional for FITS import)
http://www.stsci.edu/resources/software_hardware/pyfits
For documentation on using Veusz, see the "Documents" directory. The
manual is in pdf, html and text format (generated from docbook).
Issues:
* Reqires a rather new version of PyQt, otherwise dialogs don't work.
* Can be very slow to plot large datasets if antialiasing is enabled.
Right click on graph and disable antialias to speed up output.
* The embedding interface appears to crash on exiting.
If you enjoy using Veusz, I would love to hear from you. Please join
the mailing lists at
https://gna.org/mail/?group=veusz
to discuss new features or if you'd like to contribute code. The
latest code can always be found in the SVN repository.
are available. Jeremy Sanders
Veusz 1.0
---------
Velvet Ember Under Sky Zenith
-----------------------------
http://home.gna.org/veusz/
Veusz is Copyright (C) 2003-2007 Jeremy Sanders <[email protected]>
Licenced under the GPL (version 2 or greater).
Veusz is a scientific plotting package 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
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.
Feature changes from 0.99.0:
* Import of Text datasets
* Labels can be plotted next to X-Y points
* Numbers can be directly plotted by entering into X-Y datasets as X and Y
* More line styles
* Loaded document and functions are checked for unsafe Python features
* Contours can be labelled with numbers
* 2D dataset creation to make 2D datasets from x, y, z 1D datasets
Bug and minor fixes from 0.99.0:
* Zooming into X-Y images works now
* Contour plots work on datasets with non equal X and Y sizes
* Various fixes for datasets including NaN or Inf
* Large changes to data import filter to support loading strings (and dates
later)
* Reduce number of undo levels for memory/speed
* Text renderer rewritten to be more simple
* Improved error dialogs
* Proper error dialog for invalid loading of documents
Features of package:
* X-Y plots (with errorbars)
* Line and function plots
* Contour plots
* Images (with colour mappings and colorbars)
* Stepped plots (for histograms)
* Fitting functions to data
* Stacked plots and arrays of plots
* Plot keys
* Plot labels
* LaTeX-like formatting for text
* EPS/PDF/PNG export
* Scripting interface
* Dataset creation/manipulation
* Embed Veusz within other programs
* Text, CSV and FITS importing
Requirements:
Python (2.3 or greater required)
http://www.python.org/
Qt >= 4.3 (free edition)
http://www.trolltech.com/products/qt/
PyQt >= 4.3 (SIP is required to be installed first)
http://www.riverbankcomputing.co.uk/pyqt/
http://www.riverbankcomputing.co.uk/sip/
numpy >= 1.0
http://numpy.scipy.org/
Microsoft Core Fonts (recommended for nice output)
http://corefonts.sourceforge.net/
PyFITS >= 1.1 (optional for FITS import)
http://www.stsci.edu/resources/software_hardware/pyfits
For documentation on using Veusz, see the "Documents" directory. The
manual is in pdf, html and text format (generated from docbook).
Issues:
* Reqires a rather new version of PyQt, otherwise dialogs don't work.
* Can be very slow to plot large datasets if antialiasing is enabled.
Right click on graph and disable antialias to speed up output.
* The embedding interface appears to crash on exiting.
If you enjoy using Veusz, I would love to hear from you. Please join
the mailing lists at
https://gna.org/mail/?group=veusz
to discuss new features or if you'd like to contribute code. The
latest code can always be found in the SVN repository.