Inqbus.graphdemo ================ This package shows an example of how to use bokeh with large datasets. It uses flask as webframework and Hdf5-files to provide data. Installation and requirements ----------------------------- This package is written for Python3. For installing all requirements just run the setup.py. Make sure you have installed global requirements first. You can find them in docs/requirements. .. code:: python3 setup.py install Then you can start the flask process by running the main.py located in inqbus.graphdemo via python. .. code:: python3 main.py Examples included ----------------- The package includes 3 examples located in inqbus.graphdemo.bokeh_extension.layout. The first example is XYPlotJSLayout used for xy-plots based on JS and binary-transmitted data. The second one is XYPlotPythonLayout displaying the same plots. This can be used for performance comparison. The last example is ContourPlotLayout for 3D-Data. It is also based on binary-transmitted data. Features included ----------------- The main features are: * optimized performance due to reduced data: * First, data is filtered out of the given axis areas. Subsequently, the data is averaged so that only a reasonable number is transmitted. * For reducing the data fast libaries like numpy, pandas and dask are used. * data on request: * Instead of transmitting all data simultaneously, the data required data is calculated and transferred when the selection parameters or zoom operations have been changed. * easy-to-use * The layouts can be equipped with the required initial data via simple builder functions. * These functions are located in inqbus.graphdemo.bokeh_extension.builder
Inqbus/inqbus.graphdemo
A little demo showing how bokeh can work with large datasets
JavaScriptBSD-3-Clause