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General Description
Liran Funaro edited this page May 11, 2017
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The Graph Generation System was designed to provide an interface for graph generation based on experiment data, using a client-server web interface.
Using this system, the user can connect to a website, select a specific data file, graph model and parameters, and plot a graph in the browser.
The graphs are generated using the Bokeh library in python and are interactive - allowing zoom pan and save operations.
The system also allows to save/load/delete presets plots for different data files, as well as an option to define your own plugin.
An interface for graph generation from given data file.
- Interactive file explorer for easier experiment selection
- Load preset: allows the user to load a preset per data file, selecting a preset from a list and generating a graph from it in a single click.
- Create preset: allows the user to create a new graph preset from available graph models (line, step, heatmap etc..).
- Save preset: allows the user to save the selected parameters as a preset for other users to use.
- Plugin system: allow the user to define their own graph model by writing their own plugin in python.
- Select-by-value: allows the user to define fields as "filter by value", which upon selection will display an additional input field to select by value. Select-by-value Fields can define a single or multiple selections.
- Export: Generated graph's data is also saved as a JSON (under the "exports" sub-directory) and the plot can be saved as an image (PNG) upon request.
- Zoom/Pan: Generated graphs are interactive in the browser, allowing zoom and pan.
- Portability: Database files (SQLite) holds the models and presets, and can be moved between machines to retain models/presets information.