Source code for pm4py.objects.random_variables.basic_structure
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class BasicStructureRandomVariable(object):
def __init__(self):
"""
Constructor
"""
self.priority = 0
self.weight = 0
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def get_weight(self):
"""
Getter of weight
Returns
----------
weight
Weight of the transition
"""
return self.weight
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def set_weight(self, weight):
"""
Setter of weight variable
Parameters
-----------
weight
Weight of the transition
"""
self.weight = weight
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def get_priority(self):
"""
Getter of the priority
Returns
-----------
priority
Priority of the transition
"""
return self.priority
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def set_priority(self, priority):
"""
Setter of the priority variable
Parameters
------------
priority
Priority of the transition
"""
self.priority = priority
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def get_transition_type(self):
"""
Get the type of transition associated to the current distribution
Returns
-----------
transition_type
String representing the type of the transition
"""
return "TIMED"
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def get_distribution_type(self):
"""
Get current distribution type
Returns
-----------
distribution_type
String representing the distribution type
"""
return "NORMAL"
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def get_distribution_parameters(self):
"""
Get a string representing distribution parameters
Returns
-----------
distribution_parameters
String representing distribution parameters
"""
return "UNDEFINED"
def __str__(self):
"""
Returns a representation of the current object
Returns
----------
repr
Representation of the current object
"""
return (
self.get_distribution_type()
+ " "
+ self.get_distribution_parameters()
)
def __repr__(self):
"""
Returns a representation of the current object
Returns
----------
repr
Representation of the current object
"""
return (
self.get_distribution_type()
+ " "
+ self.get_distribution_parameters()
)
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def get_value(self):
"""
Get a random value following the distribution
Returns
-----------
value
Value obtained following the distribution
"""
return None
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def get_values(self, no_values=400):
"""
Get some random values following the distribution
Parameters
-----------
no_values
Number of values to return
Returns
----------
values
Values extracted according to the probability distribution
"""
return [self.get_value() for i in range(no_values)]
