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# $Id$
# Documentation for SCA_RandomActuator
from SCA_IActuator import *
class SCA_RandomActuator(SCA_IActuator):
"""
Random Actuator
"""
def setSeed(seed):
"""
Sets the seed of the random number generator.
Equal seeds produce equal series. If the seed is 0,
the generator will produce the same value on every call.
@type seed: integer
"""
def getSeed():
"""
Returns the initial seed of the generator.
@rtype: integer
"""
def getPara1():
"""
Returns the first parameter of the active distribution.
Refer to the documentation of the generator types for the meaning
of this value.
@rtype: float
"""
def getPara2():
"""
Returns the second parameter of the active distribution.
Refer to the documentation of the generator types for the meaning
of this value.
@rtype: float
"""
def getDistribution():
"""
Returns the type of random distribution.
@rtype: distribution type
@return: KX_RANDOMACT_BOOL_CONST, KX_RANDOMACT_BOOL_UNIFORM, KX_RANDOMACT_BOOL_BERNOUILLI,
KX_RANDOMACT_INT_CONST, KX_RANDOMACT_INT_UNIFORM, KX_RANDOMACT_INT_POISSON,
KX_RANDOMACT_FLOAT_CONST, KX_RANDOMACT_FLOAT_UNIFORM, KX_RANDOMACT_FLOAT_NORMAL,
KX_RANDOMACT_FLOAT_NEGATIVE_EXPONENTIAL
"""
def setProperty(property):
"""
Set the property to which the random value is assigned.
If the generator and property types do not match, the assignment is ignored.
@type property: string
@param property: The name of the property to set.
"""
def getProperty():
"""
Returns the name of the property to set.
@rtype: string
"""
def setBoolConst(value):
"""
Sets this generator to produce a constant boolean value.
@param value: The value to return.
@type value: boolean
"""
def setBoolUniform():
"""
Sets this generator to produce a uniform boolean distribution.
The generator will generate True or False with 50% chance.
"""
def setBoolBernouilli(value):
"""
Sets this generator to produce a Bernouilli distribution.
@param value: Specifies the proportion of False values to produce.
- 0.0: Always generate True
- 1.0: Always generate False
@type value: float
"""
def setIntConst(value):
"""
Sets this generator to always produce the given value.
@param value: the value this generator produces.
@type value: integer
"""
def setIntUniform(lower_bound, upper_bound):
"""
Sets this generator to produce a random value between the given lower and
upper bounds (inclusive).
@type lower_bound: integer
@type upper_bound: integer
"""
def 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.
@type value: float
"""
def setFloatConst(value):
"""
Always generate the given value.
@type value: float
"""
def setFloatUniform(lower_bound, upper_bound):
"""
Generates a random float between lower_bound and upper_bound with a
uniform distribution.
@type lower_bound: float
@type upper_bound: float
"""
def setFloatNormal(mean, standard_deviation):
"""
Generates a random float from the given normal distribution.
@type mean: float
@param mean: The mean (average) value of the generated numbers
@type standard_deviation: float
@param standard_deviation: The standard deviation of the generated numbers.
"""
def setFloatNegativeExponential(half_life):
"""
Generate negative-exponentially distributed numbers.
The half-life 'time' is characterized by half_life.
@type half_life: float
"""
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