# SCA_RandomActuator(SCA_IActuator)

base class — `SCA_IActuator`

class `bge.types.``SCA_RandomActuator`(SCA_IActuator)

  Random Actuator

  `seed`

    Seed of the random number generator.

    Type: | integer.

    Equal seeds produce equal series. If the seed is 0, the generator will produce the same value on every call.

  `para1`

    the first parameter of the active distribution.

    Type: | float, read-only.

    Refer to the documentation of the generator types for the meaning of this value.

  `para2`

    the second parameter of the active distribution.

    Type: | float, read-only

    Refer to the documentation of the generator types for the meaning of this value.

  `distribution`

    Distribution type. (read-only). Can be one of these constants

    Type: | integer

  `propName`

    the name of the property to set with the random value.

    Type: | string

    If the generator and property types do not match, the assignment is ignored.

  `setBoolConst`(value)

    Sets this generator to produce a constant boolean value.

    Parameters: | value (boolean) – The value to return.

  `setBoolUniform`()

    Sets this generator to produce a uniform boolean distribution.

    The generator will generate True or False with 50% chance.

  `setBoolBernouilli`(value)

    Sets this generator to produce a Bernouilli distribution.

    Parameters: | value (float) – Specifies the proportion of False values to produce. 0.0: Always generate True 1.0: Always generate False

  `setIntConst`(value)

    Sets this generator to always produce the given value.

    Parameters: | value (integer) – the value this generator produces.

  `setIntUniform`(lower_bound, upper_bound)

    Sets this generator to produce a random value between the given lower and upper bounds (inclusive).

  `setIntPoisson`(value)

    Generate a Poisson-distributed number.

    This performs a series of Bernouilli tests with parameter value. It returns the number of tries needed to achieve succes.

  `setFloatConst`(value)

    Always generate the given value.

  `setFloatUniform`(lower_bound, upper_bound)

    Generates a random float between lower_bound and upper_bound with a uniform distribution.

  `setFloatNormal`(mean, standard_deviation)

    Generates a random float from the given normal distribution.

    Parameters: | mean (float) – The mean (average) value of the generated numbers standard_deviation (float) – The standard deviation of the generated numbers.

  `setFloatNegativeExponential`(half_life)

    Generate negative-exponentially distributed numbers.

    The half-life ‘time’ is characterized by half_life.