PyPlotSuite README File

PyPlotSuite is a set of graphical tools to quick visualize and explore/analyze monodimentional and bidimensional data. The plot created can be saved in a variety of image formats to produce publication quality graphs.

At the moment the project is composed by two little stand alone applications: ImageAnalyzer and Plotfile2. ImageAnalyzer is focused towards images (or any 2D data, such as arrays) visualization, analysis, and measurement. Plotfile2 focus is towards simple data series visualization, with the possibility to quick modify many plot characteristics. Both applications can save the result on a multitude of image file formats (png, eps, jpeg, pdf, and more).

PyPlotSuite is written in python, using the GTK gui toolkit (through the python binding pygtk, and using Glade-2 to layout the windows). All plots are created with the great Matplotlib python 2D graphic library. Matplotlib is such a good tool that the PyPlotSuite applications are only tiny wrapper around Matplotlib functionality. Also some Numpy functionality are used both through Matplotlib (which requires Numpy) and both directly.

0.1-alpha8

• Added multiplatform installer using distutils. Now to install the pyplotsuite system-wide just do "python setup.py install" form the source tree with administrative privileges.

• Various bug-fixes thanks to David Trémouilles' bug reports and patches (now the open dialog remebers the last dir).

• scipy.filters is now only optional to run ImageAnalyzer

• ImageAnalyzer: Allow to change aspect ratio for images in ImageAnalyzer (via the pixel dimesion dialog)

• ImageAnalyzer: Zemax file format loading fixes and autodetection improvements.

0.1-alpha7

Only Plotfile2 changes in this release. Various speed-up and code optimization, and the support for changing also the color for all line-plot elements.

0.1-alpha6

This is the first version of PyPlotSuite released as a single tarball. It includes both ImageAnalyzer and Plotfile2.

A new plot property dialog in Plotfile2 allows to change many plot parameters (line style and width, marker style and size). There's also the GUI for changing the colors of the various plot elements but this functions is not implemented in the underlying code yet.

Early versions of ImageAnalyzer and Plotfile2 were released in separated tarballs with separated version number. Now they are released together in the same tarball with the same version number (and I plan to integrate them more). However they retain separated changelogs, so you can keep track of each application separately.

You can decompress the archive where you want and then execute PyPloSuite in place, entering the directory and typing:

  python imageanalyzer

or

  python plotfile2

You can install PyPlotSuite system wide with this command:

  python setup.py install

The development version of PyPlotSuite is hosted on a git repository. To download the latest development version just install git and type:

  $ git clone git://repo.or.cz/pyplotsuite.git

Now you have a complete working tree of PyPlotSuite to test/hack on. If git and cogito does not work on your OS (I think only windows is affected) look at bazar that is multiplatform SCM with a git plugin too.

You must have this software installed in order to be able to run the program:

• Any recent version of Linux, Mac OSX or Windows

• Python 2.4 or newer (2.3 may still work, not tested): http://www.python.org

• PyGTK 2.x: http://www.pygtk.org/

• NumPy (1.0 or newer) http://numpy.scipy.org/

• MatPlotLib (0.87 or newer): http://matplotlib.sourceforge.net/

• SciPy (only the module scipy.ndimage.filters): http://www.scipy.org/

• Python Image Library (PIL): http://www.pythonware.com/products/pil/

Typically Numpy is a prerequisite for Matplotlib, so you may have installed it in bundle with Matplotlib.

The Scipy module and the PIL library are a requirement only if you want to run ImageAnalyzer. Plotfile2 does not requires them.

Description

ImageAnalyzer is a python[1] program written with the purpose to analyze scientific images to extract information such dimensions, and to reveal some subtle features. You can also create and save publication quality figures in a variety of hard-copy formats (using Matplotlib[5]).

To execute the program type:

  python imageanalyzer

Remeber to check the software requirement above.

Image formats supported

All format supported by the PIL[6] library, with the following pixel formats: - L (Luminance, aka black&white) 8 bit and 14 bit - RBG(A) with 8bit per channel

Features

The features currently implemented are:

• Load, zoom and navigate on any RBG(A) or L (Luminance, aka black&white) images.

• The possibility to choose one of the following 17 interpolation algorithms: Bessel, Bicubic, Bilinear, Blackman, Catrom, Gaussian, Hamming, Hanning, Hermite, Kaiser, Lanczos, Mitchell, Nearest, Quadric, Sinc, Spline16, Spline36. The default one is Nearest which is "no interpolation".

• Select one of the 14 color-maps (only for L images).

• Select a dynamic range either numerically and graphically through an histogram of the image (only for L images).

• Grid on/off, black/white (to match various color-maps).

• Calculate the distance between two points with the option to set the pixel dimension for the image (x and y separately).

• Plot the pixel-precise profile of an arbitrary number of sections of the image (only for L images).

ImageAnalyzer TODO

To-do list in no particular order:

• Allow to save modified images.

• Allow to save/load plot properties (colormap, interpolation, zoom). Handle this as explained in Plotfile2 TODO (below).

• Allow to choose font size for title and labels (separately).

• Fix axis apect ratio in histogram window.

• Better handling of failure on file load.

• Use Plotfile2 (instead of the current custom window) to show image sections.

• More image filtering options.

• Add pixel-value picker tool.

• Peak integration tool (2d integration on an elliptical area).

• Noise removal tools (dithering, noise shaping, 2D matched filter, you name it! :D)

Description

Plotfile2 is is a python[1] program written with the purpose to quick plot data series stored in standard ascii text files. Multiple data series can be plotted, compared and the resulting plot can be saved in a variety of image file formats with a customizable size and resolution. This feature come particularly handy if you want to embed your plot in a document and you what size the final image will have.

Plotfile2 is written using the GTK toolkit[2] and embeds Matplotlib[5] plot facility.

To execute the program, enter the Plotfile2 dir and type:

  python plotfile2

See also the software requirements above.

Features

At the moment Plotfile2 can:

• Load one or more data series from a two column (spaces or tab separated) ascii file. Blank lines (only spaces or tabs) are ignored.

• Detect if there is an header to automatically set axis labels. The header must be one line with two strings separated by spacing (or tabs). Blank lines before and after the header are ignored. More than two space-separated string results in an error.

• Controls to change the X and Y axis range, scale (linear or log) and toggle grid.

• Controls to toggle if plot shows points (markers), lines or both.

• Complete customization of plot elements through a dedicated dialog (line style, marker type, colors, etc…).

• Set the plot title and axis labels

• Set the figure size (both in inches or in cm) and resolution (in dpi). This is useful to export a plot to be included in a document with a know size.

• Navigate/explore plots (zoom, un-zoom, pan, etc) thanks to the Matplotlib NavigationToolbar2 (try to click on the crossed arrows icon and then click and dragg with the right mouse button).

• Save the plot in a multitude of image formats (png, jpeg, eps, pdf, … all the formats supported by Matplotlib). Just click on the floppy icon.

Plotfile2 TODO

• Possibility to customize plot line style, line color, line width, marker color, marker size, marker type for each series. [COMPLETED]

• Possibility to use spline interpolation (with various orders), and exponential-spline interpolation [Work in progress].

• Add dialogs to choose an arbitrary color for plot elements in the "Plot Properties" dialog.

• Allow font size (and if possible) font style change for labels and title.

• Save plots as data (two columns ascii file or csv). This is useful for new data generated by the interpolation.

• Allow to save and load plot properties associated with a set of data. This would allow to load a dataset with associated plot style. To maintain the data in a compatible format this metadata will be saved in a new file with same name but different extension (f.e. ".plot"). Maybe the file should be hidden… (in the same dir of the data of course).

• Add basic operators (spectrum, intergrate, differentiate: which make sense?).

• Embed an (optional) [i]python shell.

Plotfile2 Known Problems

• When you change figure size and resolution using the dedicated dialog, the main window may show a scrambled plot (or only an corner of the entire plot). This is only a visualization issue. Therefore, if you save the file (without resizing the window!) you will obtain the image file with the correct size and resolution ready to be included in your documents.

If you have any suggestion to solve this problem please contact me via mail.

1. Python: a dynamic object-oriented programming language.

   • http://www.python.org

2. PyGTK: Python binding for the GTK user interface library.

   • http://www.pygtk.org/

3. Numpy: The fundamental package needed for numerical computing with Python. It is the successor (and unifier) of all the old projects (Numeric and Numarray) for python numerical computing.

   • http://numpy.scipy.org/

4. SciPy: Many modules that were not specific to Numpy are gathered under the broader project SciPy:

   • http://numpy.scipy.org/

5. MatPlotLib: A python 2D plotting library which produces publication quality figures in a variety of hard-copy formats and interactive environments across platforms.

   • http://matplotlib.sourceforge.net/

6. Python Imaging Library (PIL).

   • http://www.pythonware.com/products/pil/

$ asciidoc -a toc -a icons -a badges README.txt