pm4py.objects.random_variables.uniform package#

PM4Py – A Process Mining Library for Python

Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)

This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or any later version.

This program 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 Affero General Public License for more details.

You should have received a copy of the GNU Affero General Public License along with this program. If not, see this software project’s root or visit <https://www.gnu.org/licenses/>.

Website: https://processintelligence.solutions Contact: info@processintelligence.solutions

Submodules#

pm4py.objects.random_variables.uniform.random_variable module#

PM4Py – A Process Mining Library for Python

Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)

This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or any later version.

This program 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 Affero General Public License for more details.

You should have received a copy of the GNU Affero General Public License along with this program. If not, see this software project’s root or visit <https://www.gnu.org/licenses/>.

Website: https://processintelligence.solutions Contact: info@processintelligence.solutions

class pm4py.objects.random_variables.uniform.random_variable.Uniform(loc=0, scale=1)[source]#

Bases: BasicStructureRandomVariable

Describes an uniform variable

read_from_string(distribution_parameters)[source]#

Initialize distribution parameters from string

Parameters#

distribution_parameters

Current distribution parameters as exported on the Petri net

get_distribution_type()[source]#

Get current distribution type

Returns#

distribution_type

String representing the distribution type

get_distribution_parameters()[source]#

Get a string representing distribution parameters

Returns#

distribution_parameters

String representing distribution parameters

calculate_loglikelihood(values)[source]#

Calculate log likelihood

Parameters#

values

Empirical values to work on

Returns#

likelihood

Log likelihood that the values follows the distribution

calculate_parameters(values)[source]#

Calculate parameters of the current distribution

Parameters#

values

Empirical values to work on

get_value()[source]#

Get a random value following the distribution

Returns#

value

Value obtained following the distribution