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visualization-python - Project Hosting on Google Code
By Anders Andreasen Motivation and outline A first step towards qualitative understanding and interpretation of scientific data is visualization of the data. Also, in order to reach a quantitative understanding, the data needs to be analyzed, e.g. by fitting a physical model to the data. The raw data may also require some initial processing in order to become useful, e.g. filtering, scaling, calibration etc. Python for scientific use. Part I: Data Visualization LG #114
matplotlib is a python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. matplotlib can be used in python scripts, the python and ipython shell (ala MATLAB®* or Mathematica®†), web application servers, and six graphical user interface toolkits. matplotlib tries to make easy things easy and hard things possible. You can generate plots, histograms, power spectra, bar charts, errorcharts, scatterplots, etc, with just a few lines of code.
Examples These are some simple examples showing the core functionality of the currently available pyvisi plotting objects. simplePlot This is a very simple example showing how one would produce a line plot using pyvisi. It shows a graph of y = x^2.
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