tornium-oc-graph 0.2.0

OC scenario graph for Torn

Tornium OC Graph

OC scenario graphs as generated C++ code.

[!IMPORTANT] This library was implemented by reversing Allenone's public OC graphs, generating C++ code from those graphs, and patching those generated files to resolve issues in Allenone's graphs. Therefore, there may be certain issues that were not caught or outdated data in the generated files.

If you need help using this library or encounter any bugs, please create a ticket on Tornium's Discord server.

Credit to Allenone for the original research into OC scenarios and for creating the original graphs for OC scenarios.

Supported Languages

• Elixir
• C++
• Python

Installation: Elixir

For installing for Elixir, the library can be installed through GitHub by adding tornium_oc_graph to your list of dependencies in mix.exs:

def deps do
  [
    {:tornium_oc_graph, github: "Tornium/tornium_oc_graph"}
  ]
end

Documentation can be generated with ExDoc and published on HexDocs.

Installation: Python

For installing for Python, the library can be installed through GitHub by installing the library through pip:

pip install tornium_oc_graph

or through GitHub:

pip install git+https://github.com/Tornium/tornium_oc_graph.git

Installation: Other Languages

Other languages that are not directly supported by the library can be made to work by linking the shared object generated when compiling this library to your application (depending on how your language's FFI works). This is not a supported use-case though.

Usage: Elixir

Once the library is installed, you can use Tornium.OC.graph.calculate_ev/2 and Tornium.OC.graph.calculate_probability/2 against a set of users' CPRs to calculate the expected probability and value of the OC.

Tornium.OC.Graph.calculate_ev("Leave No Trace", %{"imitator_1" => 87, "negotiator_1" => 87, "techie_1" => 87})
Tornium.OC.Graph.calculate_probability("Leave No Trace", %{"imitator_1" => 87, "negotiator_1" => 87, "techie_1" => 87})

Usage: Python

Once the library is installed, you can use tornium_oc_graph.calculate_ev and tornium_oc_graph.calculate_probability against a setof users' CPR to calculate the expected probability and value of the OC.

tornium_oc_graph.calculate_ev("Leave No Trace", {"imitator_1": 0.87, "negotiator_1": 0.87, "techie_1": 0.87})
tornium_oc_graph.calculate_probability("Leave No Trace", {"imitator_1": 0.87, "negotiator_1": 0.87, "techie_1": 0.87})

For a more comprehensive example, see this function in Tornium.

License

This library is licensed under the Apache v2 license.