SCA_RandomActuator(SCA_IActuator)#

base class — SCA_IActuator

class 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.