'''
This file is part of PM4Py (More Info: https://pm4py.fit.fraunhofer.de).
PM4Py is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
PM4Py is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with PM4Py. If not, see <https://www.gnu.org/licenses/>.
'''
import sys
import numpy as np
from pm4py.objects.random_variables.basic_structure import BasicStructureRandomVariable
import warnings
[docs]class Gamma(BasicStructureRandomVariable):
"""
Describes a normal variable
"""
def __init__(self, a=1, loc=0, scale=1):
"""
Constructor
"""
self.a = a
self.loc = loc
self.scale = scale
BasicStructureRandomVariable.__init__(self)
[docs] def read_from_string(self, distribution_parameters):
"""
Initialize distribution parameters from string
Parameters
-----------
distribution_parameters
Current distribution parameters as exported on the Petri net
"""
self.a = float(distribution_parameters.split(";")[0])
self.loc = float(distribution_parameters.split(";")[1])
self.scale = float(distribution_parameters.split(";")[2])
[docs] def get_distribution_type(self):
"""
Get current distribution type
Returns
-----------
distribution_type
String representing the distribution type
"""
return "GAMMA"
[docs] def get_distribution_parameters(self):
"""
Get a string representing distribution parameters
Returns
-----------
distribution_parameters
String representing distribution parameters
"""
return str(self.a) + ";" + str(self.loc) + ";" + str(self.scale)
[docs] def calculate_loglikelihood(self, values):
"""
Calculate log likelihood
Parameters
------------
values
Empirical values to work on
Returns
------------
likelihood
Log likelihood that the values follows the distribution
"""
from scipy.stats import gamma
if len(values) > 1:
somma = 0
for value in values:
somma = somma + np.log(gamma.pdf(value, self.a, self.loc, self.scale))
return somma
return -sys.float_info.max
[docs] def calculate_parameters(self, values):
"""
Calculate parameters of the current distribution
Parameters
-----------
values
Empirical values to work on
"""
from scipy.stats import gamma
if len(values) > 1:
try:
self.a, self.loc, self.scale = gamma.fit(values)
except:
warnings.warn("Gamma fitting: Optimization converged to parameters that are outside the range allowed by the distribution")
[docs] def get_value(self):
"""
Get a random value following the distribution
Returns
-----------
value
Value obtained following the distribution
"""
from scipy.stats import gamma
return gamma.rvs(self.a, self.loc, self.scale)