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.