Metadata-Version: 2.1
Name: treed
Version: 1.1.0
Summary: 3D Visualization of Branch-and-Cut Trees using PySCIPOpt
Home-page: https://github.com/mattmilten/TreeD
Author: Matthias Miltenberger
Author-email: matthias.miltenberger@gmail.com
License: UNKNOWN
Description: # TreeD
        
        [![TreeD on PyPI](https://img.shields.io/pypi/v/treed.svg)](https://pypi.python.org/pypi/treed)
        
        ### Visual representation of the branch-and-cut tree of SCIP using spatial dissimilarities of LP solutions -- [Interactive Example](http://www.zib.de/miltenberger/treed-showcase.html)
        
        [![Example](res/treed-example.png)](https://plot.ly/~mattmilten/103/)
        
        ## Installation
        
        ```
        python -m pip install treed
        ```
        
        ## Usage
        - run Python script `bin/treed` (will be installed into your PATH on Linux/macOS when using `pip install treed`) to get usage information or use this code snippet in a Jupyter notebook:
        
        ```
        from treed import TreeD
        
        treed = TreeD(
            probpath="model.mps",
            nodelimit=20,
            transformation='mds',
            showcuts=True
        )
        
        treed.solve()
        fig = treed.draw()
        fig.show(renderer='notebook')
        ```
        
        ## Dependencies
        - [PySCIPOpt](https://github.com/scipopt/PySCIPOpt) to solve the instance and generate the necessary tree data
        - [Plotly](https://plot.ly/) to draw the 3D visualization
        - [pandas](https://pandas.pydata.org/) to organize the collected data
        - [sklearn](http://scikit-learn.org/stable/) for multi-dimensional scaling
        - [pysal](https://github.com/pysal) to compute statistics based on spatial (dis)similarity; this is optional
        
        ## Export to [Amira](https://amira.zib.de/)
        - run `AmiraTreeD.py` to get usage information.
        
        `AmiraTreeD.py` generates the '.am' data files to be loaded by Amira software to draw the tree using LineRaycast.
        
        ### Settings
        
        ![Project View](res/ProjectView.png)
        
        - `DataTree.am`: SpatialGraph data file with tree nodes and edges.
        - `LineRaycast`: Module to display the SpatialGraph. Note that is needed to set the colormap according to py code output (For instance 'Color map from 1 to 70' in this picture).
        - `DataOpt.am`: SpatialGraph data file with optimun value.
        - `Opt Plane`: Display the optimal value as a plane.
        
        ### Preview
        
        ![Amira preview](res/AmiraTree.gif)
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
