pm4py.objects.random_variables 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

Subpackages

• pm4py.objects.random_variables.constant0 package
  • Submodules
  • pm4py.objects.random_variables.constant0.random_variable module
    • Constant0
      • Constant0.read_from_string()
      • Constant0.get_transition_type()
      • Constant0.get_distribution_type()
      • Constant0.get_distribution_parameters()
      • Constant0.get_value()
      • Constant0.get_values()
      • Constant0.calculate_loglikelihood()
• pm4py.objects.random_variables.deterministic package
  • Submodules
  • pm4py.objects.random_variables.deterministic.random_variable module
    • Deterministic
      • Deterministic.read_from_string()
      • Deterministic.get_transition_type()
      • Deterministic.get_distribution_type()
      • Deterministic.get_distribution_parameters()
      • Deterministic.get_value()
      • Deterministic.get_values()
      • Deterministic.calculate_loglikelihood()
• pm4py.objects.random_variables.exponential package
  • Submodules
  • pm4py.objects.random_variables.exponential.random_variable module
    • Exponential
      • Exponential.read_from_string()
      • Exponential.get_distribution_type()
      • Exponential.get_distribution_parameters()
      • Exponential.calculate_loglikelihood()
      • Exponential.calculate_parameters()
      • Exponential.get_value()
• pm4py.objects.random_variables.gamma package
  • Submodules
  • pm4py.objects.random_variables.gamma.random_variable module
    • Gamma
      • Gamma.read_from_string()
      • Gamma.get_distribution_type()
      • Gamma.get_distribution_parameters()
      • Gamma.calculate_loglikelihood()
      • Gamma.calculate_parameters()
      • Gamma.get_value()
• pm4py.objects.random_variables.lognormal package
  • Submodules
  • pm4py.objects.random_variables.lognormal.random_variable module
    • LogNormal
      • LogNormal.read_from_string()
      • LogNormal.get_distribution_type()
      • LogNormal.get_distribution_parameters()
      • LogNormal.calculate_loglikelihood()
      • LogNormal.calculate_parameters()
      • LogNormal.get_value()
• pm4py.objects.random_variables.normal package
  • Submodules
  • pm4py.objects.random_variables.normal.random_variable module
    • Normal
      • Normal.read_from_string()
      • Normal.get_distribution_type()
      • Normal.get_distribution_parameters()
      • Normal.calculate_loglikelihood()
      • Normal.calculate_parameters()
      • Normal.get_value()
• pm4py.objects.random_variables.uniform package
  • Submodules
  • pm4py.objects.random_variables.uniform.random_variable module
    • Uniform
      • Uniform.read_from_string()
      • Uniform.get_distribution_type()
      • Uniform.get_distribution_parameters()
      • Uniform.calculate_loglikelihood()
      • Uniform.calculate_parameters()
      • Uniform.get_value()

Submodules

pm4py.objects.random_variables.basic_structure 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.basic_structure.BasicStructureRandomVariable

Bases: object

get_weight()

Getter of weight

Returns

weight

Weight of the transition

set_weight(weight)

Setter of weight variable

Parameters

weight

Weight of the transition

get_priority()

Getter of the priority

Returns

priority

Priority of the transition

set_priority(priority)

Setter of the priority variable

Parameters

priority

Priority of the transition

get_transition_type()

Get the type of transition associated to the current distribution

Returns

transition_type

String representing the type of the transition

get_distribution_type()

Get current distribution type

Returns

distribution_type

String representing the distribution type

get_distribution_parameters()

Get a string representing distribution parameters

Returns

distribution_parameters

String representing distribution parameters

get_value()

Get a random value following the distribution

Returns

value

Value obtained following the distribution

get_values(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

pm4py.objects.random_variables.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.random_variable.RandomVariable

Bases: object

read_from_string(distribution_type, distribution_parameters)

Read the random variable from string

Parameters

distribution_type

Distribution type

distribution_parameters

Distribution parameters splitted by ;

get_distribution_type()

Get current distribution type

Returns

distribution_type

String representing the distribution type

get_transition_type()

Get the type of transition associated to the current distribution

Returns

transition_type

String representing the type of the transition

get_distribution_parameters()

Get a string representing distribution parameters

Returns

distribution_parameters

String representing distribution parameters

calculate_loglikelihood(values)

Calculate log likelihood

Parameters

values

Empirical values to work on

Returns

likelihood

Log likelihood that the values follows the distribution

calculate_parameters(values, parameters=None, force_distribution=None)

Calculate parameters of the current distribution

Parameters

values

Empirical values to work on

parameters

Possible parameters of the algorithm

force_distribution

If provided, distribution to force usage (e.g. EXPONENTIAL)

get_value()

Get a random value following the distribution

Returns

value

Value obtained following the distribution

get_values(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

get_weight()

Getter of weight

Returns

weight

Weight of the transition

set_weight(weight)

Setter of the weight

Parameters

weight

Weight of the transition

get_priority()

Getter of the priority

Returns

priority

Priority of the transition

set_priority(priority)

Setter of the priority variable

Parameters

priority

Priority of the transition