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# $Id$
# Documentation for SCA_RandomActuator
from SCA_IActuator import *
class SCA_RandomActuator(SCA_IActuator):
"""
Random Actuator
Properties:
@ivar seed: 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
@ivar para1: the first parameter of the active distribution.
Refer to the documentation of the generator types for the meaning
of this value.
@type para1: float, read-only
@ivar para2: the second parameter of the active distribution.
Refer to the documentation of the generator types for the meaning
of this value.
@type para2: float, read-only
@ivar distribution: distribution type:
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
@type distribution: integer, read-only
@ivar property: the name of the property to set with the random value.
If the generator and property types do not match, the assignment is ignored.
@type property: string
"""
def setSeed(seed):
"""
DEPRECATED: use the seed property
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():
"""
DEPRECATED: use the seed property
Returns the initial seed of the generator.
@rtype: integer
"""
def getPara1():
"""
DEPRECATED: use the para1 property
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():
"""
DEPRECATED: use the para2 property
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():
"""
DEPRECATED: use the distribution property
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):
"""
DEPRECATED: use the property 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():
"""
DEPRECATED: use the property property
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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