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| ''' | |
| 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 | |
| from pm4py.objects.random_variables.basic_structure import BasicStructureRandomVariable | |
| class Deterministic(BasicStructureRandomVariable): | |
| """ | |
| Describes a deterministic random variable | |
| """ | |
| def __init__(self, value=0): | |
| """ | |
| Constructor | |
| Parameters | |
| ---------- | |
| value | |
| Constant value of the distribution | |
| """ | |
| BasicStructureRandomVariable.__init__(self) | |
| self.value = value | |
| self.priority = 1 | |
| 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.value = distribution_parameters | |
| 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 "DETERMINISTIC" | |
| def get_distribution_type(self): | |
| """ | |
| Get current distribution type | |
| Returns | |
| ----------- | |
| distribution_type | |
| String representing the distribution type | |
| """ | |
| return "DETERMINISTIC" | |
| def get_distribution_parameters(self): | |
| """ | |
| Get a string representing distribution parameters | |
| Returns | |
| ----------- | |
| distribution_parameters | |
| String representing distribution parameters | |
| """ | |
| return str(self.value) | |
| def get_value(self): | |
| """ | |
| Get a random value following the distribution | |
| Returns | |
| ----------- | |
| value | |
| Value obtained following the distribution | |
| """ | |
| return self.value | |
| 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)] | |
| def calculate_loglikelihood(self, values, tol=0.0001): | |
| """ | |
| Calculate log likelihood | |
| Parameters | |
| ------------ | |
| values | |
| Empirical values to work on | |
| tol | |
| Tolerance about float values (consider them 0?) | |
| Returns | |
| ------------ | |
| likelihood | |
| Log likelihood that the values follows the distribution | |
| """ | |
| values_0 = [x for x in values if abs(x-self.value) < tol] | |
| if len(values) == len(values_0): | |
| return sys.float_info.max | |
| return -sys.float_info.max | |