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Distribution Conditions

Within each BetMode there is a set of Distribution Classes which determine the win-criteria within each bet-mode. Required fields are:

  1. Criteria
    • A shorthand name describing the win condition in a single word
  2. Quota
    • This is the amount of simulations (as a ratio of the total number of bet-mode simulation) which need to satisfy the corresponding criteria. The quota is normalised when assigning criteria to simulations, so the sum of all quotas does not need to be 1. There is a minimum of 1 simulation assigned per criteria.

  3. Conditions

    • Conditions can have an arbitary number of keys. Though the required keys are:
      • reel_weights
      • force_wincap
      • force_freegame

    Note that force_wincap and force_freegame are set to False by default and do not have to be explicitly added.

    The most common use for the Distribution Conditions is when drawing a random value using the BetMode's built-in method get_distribution_conditions(). i.e. 

        multiplplier = get_random_outcome(betmode.get_distribution_conditions()['mult_values'])
    Or to check if a board forcing the freegame should be drawn with: 
    if get_distribution_conditions()['force_freegame']:
    ...

  4. Win criteria (optional)

    There is also a win_criteria condition which incorporates a payout multiplier into the simulation acceptance. The two commonly used condtions are win_criteria = 0.0 and win_criteria = self.wincap. When calling self.check_repeat() at the end of a simulation, if win_criteria is not None (default), the final win amount must match the value passed.

    The intention behind betmode distribution conditions is to give the option to handle game actions in a way which depends on the (known) expected simulation. This is most clear if for example a simulation is known to correspond to a max-win scenario. Instead of repeatly drawing random outcomes which are most likely to be rejected, we can alter the probabilties of larger payouts occurring by biasing a particular reelset, weighting larger prize or multiplier values etc..