https://github.com/drvinceknight/testing_for_zd

Recognising zero determinant strategies: code for a paper under review (pre print: https://arxiv.org/abs/1904.00973).
https://github.com/drvinceknight/testing_for_zd

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Recognising zero determinant strategies: code for a paper under review (pre print: https://arxiv.org/abs/1904.00973).

• Host: GitHub
• URL: https://github.com/drvinceknight/testing_for_zd
• Owner: drvinceknight
• License: mit
• Created: 2018-06-04T16:43:46.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2024-03-18T15:55:26.000Z (9 months ago)
• Last Synced: 2024-06-20T00:44:32.452Z (6 months ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 50.9 MB
• Stars: 1
• Watchers: 5
• Forks: 1
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
## Software

All code for this work is in Python with all versions specified in

[`environment.yml`](./environment.yml).

### Create a conda environment with all required libraries

```

$ conda env create -f environment.yml

$ source activate testing-zd

```

To install specific software for this work:

```

$ python setup.py develop

```

To run tests:

```

$ pytest

```

## Reproducing the results

The raw data containing the specific interactions of all player interactions is

achieved at https://doi.org/10.5281/zenodo.1297075

**Having created and activated the conda environment**

### Download and unpack the archived data

```

$ invoke data

```

### Pre process the raw data

```

$ invoke process

```

### Create all assets

```

$ invoke assets --processdata

```

### Build the main pdf

```

$ invoke main

```

### Do all of the above

Note that you can simply run:

```

$ invoke data

$ invoke build

```

For more information about what you can do:

```

$ invoke -l

```