Mailman 3 November 2010 - Python-announce-list

ANN: Mahotas 0.5.3
by Luis Pedro Coelho Nov. 4, 2010

Nov. 4, 2010

Hi List, I'd like to announce the release of mahotas 0.5.3. Mahotas is an image processing library, which is mostly implemented in C++ for speed and complements scipy.ndimage and pymorph. Notable Algorithms ------------------ - watershed. - thresholding. - convex points calculations. - hit & miss. thinning. - Zernike & Haralick features. - freeimage based numpy image loading (requires freeimage libraries to be installed). New Features in 0.5.3 ---------------------- * Implement mahotas.thin() in C++ for speed * Add np.uint64 support to fullhistogram() * Drop GIL when possible * Add imresize() wrapper around ndimage.zoom Website: http://luispedro.org/software/mahotas Mailing List (for computer vision in Python stuff, including this library): http://groups.google.com/group/pythonvision Repository: http://github.com/luispedro/mahotas API Docs: http://packages.python.org/mahotas/ Thank you, -- Luis Pedro Coelho http://luispedro.org

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[ANN] guiqwt v2.0.4
by Pierre.RAYBAUT＠CEA.FR Nov. 3, 2010

Nov. 3, 2010

Hi all, I am pleased to announce that `guiqwt` v2.0.4 has been released. This is mostly a bug fix release. Based on PyQwt (plotting widgets for PyQt4 graphical user interfaces) and on the scientific modules NumPy and SciPy, guiqwt is a Python library providing efficient 2D data-plotting features (curve/image visualization and related tools) for interactive computing and signal/image processing application development. As you certainly know, the most popular Python module for data plotting is currently matplotlib, an open-source library providing a lot of plot types and an API (the pylab interface) which is very close to MATLAB's plotting interface. guiqwt plotting features are quite limited in terms of plot types compared to matplotlib. However the currently implemented plot types are much more efficient. For example, the guiqwt image showing function (imshow) do not make any copy of the displayed data, hence allowing to show images much larger than with its matplotlib's counterpart. In other terms, when showing a 30-MB image (16-bits unsigned integers for example) with guiqwt, no additional memory is wasted to display the image (except for the offscreen image of course which depends on the window size) whereas matplotlib takes more than 600-MB of additional memory (the original array is duplicated four times using 64-bits float data types). guiqwt also provides the following features: guiqwt.pyplot: equivalent to matplotlib's pyplot module (pylab) supported plot items: * curves, error bar curves and 1-D histograms * images (RGB images are not supported), images with non-linear x/y scales, images with specified pixel size (e.g. loaded from DICOM files), 2-D histograms, pseudo-color images (pcolor) * labels, curve plot legends * shapes: polygon, polylines, rectangle, circle, ellipse and segment * annotated shapes (shapes with labels showing position and dimensions): rectangle with center position and size, circle with center position and diameter, ellipse with center position and diameters (these items are very useful to measure things directly on displayed images) curves, images and shapes: * multiple object selection for moving objects or editing their properties through automatically generated dialog boxes (guidata) * item list panel: move objects from foreground to background, show/hide objects, remove objects, ... * customizable aspect ratio * a lot of ready-to-use tools: plot canvas export to image file, image snapshot, image rectangular filter, etc. curves: * interval selection tools with labels showing results of computing on selected area * curve fitting tool with automatic fit, manual fit with sliders, ... images: * contrast adjustment panel: select the LUT by moving a range selection object on the image levels histogram, eliminate outliers, ... * X-axis and Y-axis cross-sections: support for multiple images, average cross-section tool on a rectangular area, ... * apply any affine transform to displayed images in real-time (rotation, magnification, translation, horizontal/vertical flip, ...) application development helpers: * ready-to-use curve and image plot widgets and dialog boxes * load/save graphical objects (curves, images, shapes) * a lot of test scripts which demonstrate guiqwt features guiqwt has been successfully tested on GNU/Linux and Windows platforms. Python package index page: http://pypi.python.org/pypi/guiqwt/ Documentation, screenshots: http://packages.python.org/guiqwt/ Downloads (source + Python(x,y) plugin): http://sourceforge.net/projects/guiqwt/ Cheers, Pierre --- Dr. Pierre Raybaut CEA - Commissariat à l'Energie Atomique et aux Energies Alternatives

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[ANN] guidata v1.2.2
by Pierre.RAYBAUT＠CEA.FR Nov. 3, 2010

Nov. 3, 2010

Hi all, I am pleased to announce that `guidata` v1.2.2 has been released. This is mostly a bug fix release. Based on the Qt Python binding module PyQt4, guidata is a Python library generating graphical user interfaces for easy dataset editing and display. It also provides helpers and application development tools for PyQt4. guidata also provides the following features: * guidata.qthelpers: PyQt4 helpers * guidata.disthelpers: py2exe helpers * guidata.userconfig: .ini configuration management helpers (based on Python standard module ConfigParser) * guidata.configtools: library/application data management * guidata.gettext_helpers: translation helpers (based on the GNU tool gettext) * guidata.guitest: automatic GUI-based test launcher * guidata.utils: miscelleneous utilities guidata has been successfully tested on GNU/Linux and Windows platforms. Python package index page: http://pypi.python.org/pypi/guidata/ Documentation, screenshots: http://packages.python.org/guidata/ Downloads (source + Python(x,y) plugin): http://sourceforge.net/projects/guidata/ Cheers, Pierre --- Dr. Pierre Raybaut CEA - Commissariat à l'Energie Atomique et aux Energies Alternatives

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ANN : svgplotlib 0.1
by Runar Tenfjord Nov. 3, 2010

Nov. 3, 2010

**svgplotlib** is a lightweight python package for creating SVG graphs and charts. The TEX package and freetype extension have been ported from matplotlib. Compared to matplotlib the dependency om numpy have been removed. Homepage : http://code.google.com/p/svgplotlib/ Download : http://pypi.python.org/pypi/svgplotlib/ **Highlights** * General SVG support * Support a subset of TEX syntax similar to matplotlib. * Inlines font glyps in SVG file for consistent results. * Pie chart * Bar chart * Gantt chart * XY plot * date plot <P><A HREF="http://pypi.python.org/pypi/svgplotlib/">svgplotlib 0.1</A>svgplotlib is a lightweight python package for creating SVG graphs and charts. (03-Nov-10)

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ANN: svg2rlg
by runar.tenfjord＠gmail.com Nov. 3, 2010

Nov. 3, 2010

svg2rlg is a python tool to convert SVG files to reportlab graphics. The tool can be used as a console application to convert SVG to PDF files. Homepage: http://code.google.com/p/svg2rlg/ Download : http://pypi.python.org/pypi/svg2rlg/ Known problems ( AKA todo list): * Missing support for elliptical arcs in paths. It is belived to be possible to convert arcs to quadratic beziers. * Text handling is limited. * Style sheets not supported. Note that some limitations are due to limitation in the reportlab graphics package: * No gradients * No text on path * No filling rules (only odd-even) A wxpython tool is included in the distribution which does a side by side comparison to the SVG test suite. Presently most of the official SVG 1.1 test suite is prefect. <P><A HREF="http://pypi.python.org/pypi/svg2rlg/">svg2rlg 0.3</A> svg2rlg is a python tool to convert SVG files to reportlab graphics (03-Nov-10)

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EPD 6.3 release
by Ilan Schnell Nov. 2, 2010

Nov. 2, 2010

Hello, I am pleased to announce that EPD (Enthought Python Distribution) version 6.3 has been released. Apart from the usual updates and bug fixes, many projects have been added into this EPD version including: numexpr (linked against the MKL's Vector Math Library), SimPy, h5py and pyzmq. Please find the complete list of additions, updates and bug fixes in the change log: http://www.enthought.com/EPDChangelog.html In addition, we now also provide a Python Package Index (PyPI) mirror for our customers which allows installing compiled PyPI packages using the native EPD install tool. To find more information about EPD, as well as download a 30 day free trial, visit this page: http://www.enthought.com/products/epd.php About EPD --------- The Enthought Python Distribution (EPD) is a "kitchen-sink-included" distribution of the Python Programming Language, including over 90 additional tools and libraries. The EPD bundle includes NumPy, SciPy, IPython, 2D and 3D visualization, and many other tools. http://www.enthought.com/products/epdlibraries.php It is currently available as a single-click installer for Windows XP, Vista and 7, MacOS (10.5 and 10.6), RedHat 3, 4 and 5, as well as Solaris 10 (x86 and x86_64/amd64 on all platforms). The 32-bit EPD is free for academic use. An annual subscription including installation support is available for individual and commercial use. Additional support options, including customization, bug fixes and training classes are also available: http://www.enthought.com/products/support_level_table.php - Ilan

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ANN: Milk 0.3.4
by Luis Pedro Coelho Nov. 1, 2010

Nov. 1, 2010

Milk is a machine learning toolkit in Python. It's focus is on supervised classification with several classifiers available: SVMs (based on libsvm), k-NN, random forests, decision trees. It also performs feature selection. These classifiers can be combined in many ways to form different classification systems. For unsupervised learning, milk supports k-means clustering and affinity propagation. New in Version 0.3.4: * Random forest learners were added. * Decision trees were sped up by 20 times. * Gridsearch is much faster since it finds an optimum without computing all folds. Homepage: http://luispedro.org/software/milk API Docs: http://packages.python.org/milk/ Github: http://github.com/luispedro/milk Freshmeat: http://freshmeat.net/projects/milk -- Luis Pedro Coelho http://luispedro.org

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ANN: PyQt v4.8.1 Released
by Phil Thompson Nov. 1, 2010

Nov. 1, 2010

PyQt v4.8.1 has been released and is available from http://www.riverbankcomputing.com/software/pyqt/. PyQt is a comprehensive set of bindings for the Qt application and UI framework from Nokia. It supports the same platforms as Qt (Windows, Linux and MacOS/X). PyQt supports Python v3 and Python v2.3 and later. The highlight of this release is full support for Qt v4.7.0 including the ability to integrate Python with QML, the new declarative markup language for building highly dynamic user interfaces. Windows installers are provided for the GPL version of PyQt which contains everything needed for PyQt development (including Qt, Qt Designer, QScintilla, and MySQL, PostgreSQL, SQLite and ODBC drivers) except Python itself. PyQt v4 is implemented as a set of 19 extension modules containing over 400 classes and over 6,000 functions and methods. QtCore The non-GUI infrastructure including event loops, threads, i18n, Unicode, signals and slots, user and application settings, mapped files and shared memory. QtDeclarative A set of classes that implement a framework for building highly dynamic user interfaces using the QML declarative language that can be integrated with Python. QtDesigner A set of classes that allow the Qt Designer GUI design tool to be extended with PyQt. QtGui A rich collection of GUI widgets. QtHelp A set of classes for creating and viewing searchable documentation and being able to integrate online help with PyQt applications. It includes the C++ port of the Lucene text search engine. QtNetwork A set of classes to support TCP and UDP socket programming and higher level protocols (eg. HTTP, SSL). QtOpenGL A set of classes that allows PyOpenGL to render onto Qt widgets. QtScript A set of classes that implements a JavaScript interpreter. Python objects may be exposed in the interpreter as JavaScript objects. QtScriptTools A debugger for the JavaScript interpreter. QtSql A set of classes that implement SQL data models and interfaces to industry standard databases. The Windows installers include support for SQLite, MySQL, PostgreSQL and ODBC. QtSvg A set of classes to render SVG files onto Qt widgets. QtTest A set of classes to automate unit testing of PyQt applications and GUIs. QtWebKit This implements a web browser engine based on the WebKit engine used by Apple's Safari browser. It allows the methods and properties of Python objects to be published and appear as JavaScript objects to scripts embedded in HTML pages. QtXML A set of classes that implement DOM and SAX parsers. QtXMLPatterns A set of classes that implement XQuery and XPath support for XML and custom data models. QAxContainer A set of classes for Windows that allows the integration of ActiveX controls and COM objects. phonon A cross-platform multimedia framework that enables the use of audio and video content in PyQt applications. DirectX is used as the Windows backend, QuickTime as the MacOS/X backend, and GStreamer as the Linux backend. QtMultimedia A set of classes that provide low-level multimedia functions. Application developers would normally use the phonon module. DBus PyQt includes dbus.mainloop.qt that allows the Qt event loop to be used with the standard DBus Python bindings. PyQt includes the pyuic4 utility which generates Python code to implement user interfaces created with Qt Designer in the same way that the uic utility generates C++ code. It is also able to load Designer XML files dynamically. PyQt is available under the GPL and a commercial license. Unlike Qt, PyQt is not available under the LGPL. The commercial PyQt license allows GPL applications to be relicensed at any time.

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