MySimulation

Overview

The mysimulation is a library that supports simulating the player's playing results when participating in a slot game. This library helps game designers predict whether the game's RTP is as expected or not, helping to come up with an accurate solution.

Functionality:

• Manage all of simulations for a game such as
  • Create new simulation.
  • List simulations.
  • Download the simulation reports.
• And together with internal interface
  • Used as a library for a game to run their own logic.
  • Start & stop worker to run these simulations.

How to use MySimulation in Debug Tools

Access the debug tool at: Debug Tool.

The MySimulation Site

This is the MySimulation site, from here you can take the following actions:

• Auto Refresh Button: When the Auto Refresh Button is on, you can see the current progress of the simulation. [1]
• Create New Simulation: Using to create a new simulation. [2]
• View List of Simulation [3]: In one of the row, you can take two actions:
  • Download Report: Return a simulation report file and will auto download on your device.
  • Recreate Simulation: Create a new simulation that like the simulation want to recreate.

Read the Simulation Report

Here is a simulation report example.

In a simulation report, we have six fix columns and some optional extra columns.

• Six fix columns: Except rtp column, the remain columns is created from the AWP algorithm.

  • payout_min: The AWP result will return a payout range, such as [0,1], [1,5]... Payout_min is a min of payout range, example:

    • With payout range [0,1], payout_min is 0.

  • payout_max: The same payout_min, payout_max is a max of payout range, example:

    • With payout range [0,1], payout_max is 1.

  Developers will choose randomly target_rtp between payout_min and payout_max. Then choose the result that has rtp equal target_rtp or smaller and nearest to target_rtp.

  • rtp: Is a actual rtp that player get from current spin, example:

    • Player bet $1 and player win $10 that mean rtp is 10

  • final_hit_rate: Is a ratio chosen based on calculation from the AWP algorithm.

  • normal_game_hit_rate: Is a randomly selected ratio from 0 to 1 before get payout. The normal_game_hit_rate will be compared with max_hit_rate of bet_experience at awp_setting. If normal_game_hit_rate is greater than max_hit_rate, the AWP result will return a payout range [0,0].

  • volatility: Is the payout volatility over each spin. That is calculated based on the formula:

    $sumOfSquare=sumOfSquare+gamePayout^2$

    $volatility=\sqrt{\frac{sumOfSquare}{spin*betStake^2}-(\frac{totalPayout}{totalBet})^2}$

    In there:

    • gamePayout: current game payout

    • spin: current number of spin at the time

    • totalPayout:total Payout for all of the spins already done

    • totalBet: total bet amount for all of the spins already done

• Optional Extra columns: Each game will have difference option extra columns.

How to integrate MySimulation library in backend service

At internal/server/serve.go file, need to call New mysimulation and register mysimulation server, example:

package server

import (
    ...

    mysimulationcli "gitlab.nautilusgames.tech/marketplace/mysimulation"
    mysimpkg "gitlab.nautilusgames.tech/marketplace/mysimulation/pkg"

    ...
)

func Serve(cfg *config.Config) {
    ...

    mySimulation, err := mysimulationcli.New(entDriver, func(ctx context.Context, ssr mysimpkg.SimulationSpinRequest) (mysimpkg.SimulationSpinResult, error) {
        // TODO: handle simulationSpinResult
        return mysimpkg.SimulationSpinResult{}, nil
    })
    if err != nil {
        logger.Fatal("init my simulation failed", zap.Error(err))
    }
    mySimulation.RegisterGrpcServer(server)
    mySimulation.RegisterHttpServer(ctx, service.HttpServeMux())
    mySimulation.StartRunner()
    defer mySimulation.StopRunner()

    ...
}