文件列表:

code (0, 2018-12-02)
code\0_test_environment.py (333, 2018-12-02)
code\1_vscode_jupyter.py (4599, 2018-12-02)
code\2_pathpy.ipynb (18024, 2018-12-02)
code\2_pathpy.py (13964, 2018-12-02)
code\2_pathpy_code.py (2416, 2018-12-02)
code\3_higher_order.ipynb (23944, 2018-12-02)
code\3_higher_order.py (19886, 2018-12-02)
code\3_higher_order_code.py (2785, 2018-12-02)
code\4_temporal_networks.ipynb (39638, 2018-12-02)
code\4_temporal_networks.py (33262, 2018-12-02)
code\4_temporal_networks_code.py (5701, 2018-12-02)
code\5_exploration.ipynb (3137, 2018-12-02)
code\5_exploration.py (2413, 2018-12-02)
code\5_exploration_code.py (609, 2018-12-02)
code\6_multi_order.ipynb (26006, 2018-12-02)
code\6_multi_order.py (21581, 2018-12-02)
code\6_multi_order_code.py (3416, 2018-12-02)
code\7_generate_gt.py (1966, 2018-12-02)
code\7_optimal_analysis.ipynb (21465, 2018-12-02)
code\7_optimal_analysis.py (18013, 2018-12-02)
code\7_optimal_analysis_code.py (4380, 2018-12-02)
code\8_exploration.ipynb (3895, 2018-12-02)
code\8_exploration.py (2940, 2018-12-02)
code\8_exploration_code.py (632, 2018-12-02)
data (0, 2018-12-02)
data\US_flights.ngram (4806832, 2018-12-02)
data\US_flights_gt.json (5169, 2018-12-02)
data\US_flights_train.ngram (2404040, 2018-12-02)
data\US_flights_validate.ngram (2402792, 2018-12-02)
data\custom_template.html (13319, 2018-12-02)
data\haggle_gt.json (3986, 2018-12-02)
data\lotr_chapters.json (4184, 2018-12-02)
data\lotr_characters.json (2977, 2018-12-02)
data\manufacturing_email_gt.json (4286, 2018-12-02)
data\temporal_clusters.state (193968, 2018-12-02)
... ...

# Higher-Order Data Analytics for Temporal Network Data In this repository, wou will find all material needed to complete the hands-on tutorial on Higher-Order Data Analytics for Temporal Network Data. A detailed [tutorial schedule](https://IngoScholtes.github.io/csh2018-tutorial/) as well as [step-by-step setup instructions](https://IngoScholtes.github.io/csh2018-tutorial/setup) can be found on the [tutorial website](https://IngoScholtes.github.io/csh2018-tutorial/). While you can manually download all necessary files, we strongly recommend to clone this repository to obtain a local, sychronised copy of all material via `git`. Assuming you have a local `git` installation, you can do this as follows: `git clone https://github.com/IngoScholtes/csh2018-tutorial` If you don't have `git` installed already, here you can find information on [how to set up git](https://help.github.com/articles/set-up-git/). Prior to the hands-on tutorial, you will get access to skeleton `python` files, that we will complete together throughout the tutorial sessions. At specific *synchronisation points, we will push a commit of the current solution to this `gitHub` repository. You can thus simply execute the terminal command `git pull` in the directory of your local copy to receive a *sample solution* that is growing as the tutorial advances.

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