.. Copyright 2021 IRT Saint-Exupéry, https://www.irt-saintexupery.com This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by-sa/4.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA. .. _gen_doe_algos: DOE algorithms options ====================== A simple way to solve an :class:`.OptimizationProblem` is to use the API method :meth:`~gemseo.api.execute_algo`. E.g. .. code:: from gemseo.api import execute_algo from gemseo.problems.analytical.rosenbrock import Rosenbrock problem = Rosenbrock() sol = execute_algo(problem, "OT_LHS", n_samples=20) They are also used in all MDO and DOE scenarios in the dictionary passed to the :meth:`.MDODiscipline.execute` method. List of available algorithms : :ref:`CustomDOE_options` - :ref:`DiagonalDOE_options` - :ref:`OT_AXIAL_options` - :ref:`OT_COMPOSITE_options` - :ref:`OT_FACTORIAL_options` - :ref:`OT_FAURE_options` - :ref:`OT_FULLFACT_options` - :ref:`OT_HALTON_options` - :ref:`OT_HASELGROVE_options` - :ref:`OT_LHS_options` - :ref:`OT_LHSC_options` - :ref:`OT_MONTE_CARLO_options` - :ref:`OT_OPT_LHS_options` - :ref:`OT_RANDOM_options` - :ref:`OT_REVERSE_HALTON_options` - :ref:`OT_SOBOL_options` - :ref:`OT_SOBOL_INDICES_options` - :ref:`bbdesign_options` - :ref:`ccdesign_options` - :ref:`ff2n_options` - :ref:`fullfact_options` - :ref:`lhs_options` - :ref:`pbdesign_options` - .. _CustomDOE_options: CustomDOE --------- Description ~~~~~~~~~~~ This samples are provided either as a file in text or csv format or as a sequence of sequences of numbers. Options ~~~~~~~ - **comments**, :code:`str` - The characters or list of characters used to indicate the start of a comment. None implies no comments. - **delimiter**, :code:`str` - The string used to separate values. If None, use whitespace. - **doe_file**, :code:`str` - Either the file, the filename, or the generator to read. - **eval_jac**, :code:`bool` - evaluate jacobian - **max_time**, :code:`float` - maximum runtime in seconds, disabled if 0 (Default value = 0) - **n_processes**, :code:`int` - number of processes - **samples**, :code:`array` - The samples. - **skiprows**, :code:`int` - skip the first `skiprows` lines - **wait_time_between_samples**, :code:`float` - waiting time between two samples .. _DiagonalDOE_options: DiagonalDOE ----------- Description ~~~~~~~~~~~ Diagonal design of experiments Options ~~~~~~~ - **eval_jac**, :code:`bool` - evaluate jacobian - **max_time**, :code:`float` - maximum runtime in seconds, disabled if 0 (Default value = 0) - **n_processes**, :code:`int` - number of processes - **n_samples**, :code:`int` - number of samples - **reverse**, :code:`list(str)` - list of dimensions or variables to sample from their upper bounds to their lower bounds. Default: None. - **wait_time_between_samples**, :code:`float` - waiting time between two samples .. _OT_AXIAL_options: OT_AXIAL -------- Description ~~~~~~~~~~~ Axial design implemented in openTURNS library `External link `__ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Options ~~~~~~~ - **annealing**, :code:`bool` - if True, use simulated annealing to optimize LHS. Otherwise, use crude Monte Carlo. Default: True. - **centers**, :code:`array` - centers for axial, factorial and composite designs - **criterion**, :code:`str` - space-filling criterion, either "C2", "PhiP" or "MinDist". Default: "C2". - **distribution_name**, :code:`str` - distribution name - **end**, :code:`float` - level end for trapezoidal distribution - **eval_jac**, :code:`bool` - evaluate jacobian - **levels**, :code:`array` - levels for axial, factorial and composite designs - **max_time**, :code:`float` - maximum runtime in seconds, disabled if 0 (Default value = 0) - **mu**, :code:`float` - mean of a random variable for beta, normal and truncated normal distributions - **n_processes**, :code:`int` - number of processes - **n_replicates**, :code:`int` - number of Monte Carlo replicates to optimize LHS. Default: 1000. - **n_samples**, :code:`int` - number of samples - **seed**, :code:`int` - seed value. - **sigma**, :code:`float` - standard deviation for beta, normal and truncated normal distributions - **start**, :code:`float` - level start for trapezoidal distribution - **temperature**, :code:`string` - temperature profil for simulated annealing, either "Geometric" or "Linear". Default: "Geometric". - **wait_time_between_samples**, :code:`float` - waiting time between two samples .. _OT_COMPOSITE_options: OT_COMPOSITE ------------ Description ~~~~~~~~~~~ Composite design implemented in openTURNS library `External link `__ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Options ~~~~~~~ - **annealing**, :code:`bool` - if True, use simulated annealing to optimize LHS. Otherwise, use crude Monte Carlo. Default: True. - **centers**, :code:`array` - centers for axial, factorial and composite designs - **criterion**, :code:`str` - space-filling criterion, either "C2", "PhiP" or "MinDist". Default: "C2". - **distribution_name**, :code:`str` - distribution name - **end**, :code:`float` - level end for trapezoidal distribution - **eval_jac**, :code:`bool` - evaluate jacobian - **levels**, :code:`array` - levels for axial, factorial and composite designs - **max_time**, :code:`float` - maximum runtime in seconds, disabled if 0 (Default value = 0) - **mu**, :code:`float` - mean of a random variable for beta, normal and truncated normal distributions - **n_processes**, :code:`int` - number of processes - **n_replicates**, :code:`int` - number of Monte Carlo replicates to optimize LHS. Default: 1000. - **n_samples**, :code:`int` - number of samples - **seed**, :code:`int` - seed value. - **sigma**, :code:`float` - standard deviation for beta, normal and truncated normal distributions - **start**, :code:`float` - level start for trapezoidal distribution - **temperature**, :code:`string` - temperature profil for simulated annealing, either "Geometric" or "Linear". Default: "Geometric". - **wait_time_between_samples**, :code:`float` - waiting time between two samples .. _OT_FACTORIAL_options: OT_FACTORIAL ------------ Description ~~~~~~~~~~~ Factorial design implemented in openTURNS library `External link `__ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Options ~~~~~~~ - **annealing**, :code:`bool` - if True, use simulated annealing to optimize LHS. Otherwise, use crude Monte Carlo. Default: True. - **centers**, :code:`array` - centers for axial, factorial and composite designs - **criterion**, :code:`str` - space-filling criterion, either "C2", "PhiP" or "MinDist". Default: "C2". - **distribution_name**, :code:`str` - distribution name - **end**, :code:`float` - level end for trapezoidal distribution - **eval_jac**, :code:`bool` - evaluate jacobian - **levels**, :code:`array` - levels for axial, factorial and composite designs - **max_time**, :code:`float` - maximum runtime in seconds, disabled if 0 (Default value = 0) - **mu**, :code:`float` - mean of a random variable for beta, normal and truncated normal distributions - **n_processes**, :code:`int` - number of processes - **n_replicates**, :code:`int` - number of Monte Carlo replicates to optimize LHS. Default: 1000. - **n_samples**, :code:`int` - number of samples - **seed**, :code:`int` - seed value. - **sigma**, :code:`float` - standard deviation for beta, normal and truncated normal distributions - **start**, :code:`float` - level start for trapezoidal distribution - **temperature**, :code:`string` - temperature profil for simulated annealing, either "Geometric" or "Linear". Default: "Geometric". - **wait_time_between_samples**, :code:`float` - waiting time between two samples .. _OT_FAURE_options: OT_FAURE -------- Description ~~~~~~~~~~~ Faure sequence implemented in openTURNS library `External link `__ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Options ~~~~~~~ - **annealing**, :code:`bool` - if True, use simulated annealing to optimize LHS. Otherwise, use crude Monte Carlo. Default: True. - **centers**, :code:`array` - centers for axial, factorial and composite designs - **criterion**, :code:`str` - space-filling criterion, either "C2", "PhiP" or "MinDist". Default: "C2". - **distribution_name**, :code:`str` - distribution name - **end**, :code:`float` - level end for trapezoidal distribution - **eval_jac**, :code:`bool` - evaluate jacobian - **levels**, :code:`array` - levels for axial, factorial and composite designs - **max_time**, :code:`float` - maximum runtime in seconds, disabled if 0 (Default value = 0) - **mu**, :code:`float` - mean of a random variable for beta, normal and truncated normal distributions - **n_processes**, :code:`int` - number of processes - **n_replicates**, :code:`int` - number of Monte Carlo replicates to optimize LHS. Default: 1000. - **n_samples**, :code:`int` - number of samples - **seed**, :code:`int` - seed value. - **sigma**, :code:`float` - standard deviation for beta, normal and truncated normal distributions - **start**, :code:`float` - level start for trapezoidal distribution - **temperature**, :code:`string` - temperature profil for simulated annealing, either "Geometric" or "Linear". Default: "Geometric". - **wait_time_between_samples**, :code:`float` - waiting time between two samples .. _OT_FULLFACT_options: OT_FULLFACT ----------- Description ~~~~~~~~~~~ Full factorial design implementedin openTURNS library `External link `__ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Options ~~~~~~~ - **annealing**, :code:`bool` - if True, use simulated annealing to optimize LHS. Otherwise, use crude Monte Carlo. Default: True. - **centers**, :code:`array` - centers for axial, factorial and composite designs - **criterion**, :code:`str` - space-filling criterion, either "C2", "PhiP" or "MinDist". Default: "C2". - **distribution_name**, :code:`str` - distribution name - **end**, :code:`float` - level end for trapezoidal distribution - **eval_jac**, :code:`bool` - evaluate jacobian - **levels**, :code:`array` - levels for axial, factorial and composite designs - **max_time**, :code:`float` - maximum runtime in seconds, disabled if 0 (Default value = 0) - **mu**, :code:`float` - mean of a random variable for beta, normal and truncated normal distributions - **n_processes**, :code:`int` - number of processes - **n_replicates**, :code:`int` - number of Monte Carlo replicates to optimize LHS. Default: 1000. - **n_samples**, :code:`int` - number of samples - **seed**, :code:`int` - seed value. - **sigma**, :code:`float` - standard deviation for beta, normal and truncated normal distributions - **start**, :code:`float` - level start for trapezoidal distribution - **temperature**, :code:`string` - temperature profil for simulated annealing, either "Geometric" or "Linear". Default: "Geometric". - **wait_time_between_samples**, :code:`float` - waiting time between two samples .. _OT_HALTON_options: OT_HALTON --------- Description ~~~~~~~~~~~ Halton sequence implemented in openTURNS library `External link `__ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Options ~~~~~~~ - **annealing**, :code:`bool` - if True, use simulated annealing to optimize LHS. Otherwise, use crude Monte Carlo. Default: True. - **centers**, :code:`array` - centers for axial, factorial and composite designs - **criterion**, :code:`str` - space-filling criterion, either "C2", "PhiP" or "MinDist". Default: "C2". - **distribution_name**, :code:`str` - distribution name - **end**, :code:`float` - level end for trapezoidal distribution - **eval_jac**, :code:`bool` - evaluate jacobian - **levels**, :code:`array` - levels for axial, factorial and composite designs - **max_time**, :code:`float` - maximum runtime in seconds, disabled if 0 (Default value = 0) - **mu**, :code:`float` - mean of a random variable for beta, normal and truncated normal distributions - **n_processes**, :code:`int` - number of processes - **n_replicates**, :code:`int` - number of Monte Carlo replicates to optimize LHS. Default: 1000. - **n_samples**, :code:`int` - number of samples - **seed**, :code:`int` - seed value. - **sigma**, :code:`float` - standard deviation for beta, normal and truncated normal distributions - **start**, :code:`float` - level start for trapezoidal distribution - **temperature**, :code:`string` - temperature profil for simulated annealing, either "Geometric" or "Linear". Default: "Geometric". - **wait_time_between_samples**, :code:`float` - waiting time between two samples .. _OT_HASELGROVE_options: OT_HASELGROVE ------------- Description ~~~~~~~~~~~ Haselgrove sequence implemented in openTURNS library `External link `__ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Options ~~~~~~~ - **annealing**, :code:`bool` - if True, use simulated annealing to optimize LHS. Otherwise, use crude Monte Carlo. Default: True. - **centers**, :code:`array` - centers for axial, factorial and composite designs - **criterion**, :code:`str` - space-filling criterion, either "C2", "PhiP" or "MinDist". Default: "C2". - **distribution_name**, :code:`str` - distribution name - **end**, :code:`float` - level end for trapezoidal distribution - **eval_jac**, :code:`bool` - evaluate jacobian - **levels**, :code:`array` - levels for axial, factorial and composite designs - **max_time**, :code:`float` - maximum runtime in seconds, disabled if 0 (Default value = 0) - **mu**, :code:`float` - mean of a random variable for beta, normal and truncated normal distributions - **n_processes**, :code:`int` - number of processes - **n_replicates**, :code:`int` - number of Monte Carlo replicates to optimize LHS. Default: 1000. - **n_samples**, :code:`int` - number of samples - **seed**, :code:`int` - seed value. - **sigma**, :code:`float` - standard deviation for beta, normal and truncated normal distributions - **start**, :code:`float` - level start for trapezoidal distribution - **temperature**, :code:`string` - temperature profil for simulated annealing, either "Geometric" or "Linear". Default: "Geometric". - **wait_time_between_samples**, :code:`float` - waiting time between two samples .. _OT_LHS_options: OT_LHS ------ Description ~~~~~~~~~~~ Latin Hypercube Sampling implemented in openTURNS library `External link `__ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Options ~~~~~~~ - **annealing**, :code:`bool` - if True, use simulated annealing to optimize LHS. Otherwise, use crude Monte Carlo. Default: True. - **centers**, :code:`array` - centers for axial, factorial and composite designs - **criterion**, :code:`str` - space-filling criterion, either "C2", "PhiP" or "MinDist". Default: "C2". - **distribution_name**, :code:`str` - distribution name - **end**, :code:`float` - level end for trapezoidal distribution - **eval_jac**, :code:`bool` - evaluate jacobian - **levels**, :code:`array` - levels for axial, factorial and composite designs - **max_time**, :code:`float` - maximum runtime in seconds, disabled if 0 (Default value = 0) - **mu**, :code:`float` - mean of a random variable for beta, normal and truncated normal distributions - **n_processes**, :code:`int` - number of processes - **n_replicates**, :code:`int` - number of Monte Carlo replicates to optimize LHS. Default: 1000. - **n_samples**, :code:`int` - number of samples - **seed**, :code:`int` - seed value. - **sigma**, :code:`float` - standard deviation for beta, normal and truncated normal distributions - **start**, :code:`float` - level start for trapezoidal distribution - **temperature**, :code:`string` - temperature profil for simulated annealing, either "Geometric" or "Linear". Default: "Geometric". - **wait_time_between_samples**, :code:`float` - waiting time between two samples .. _OT_LHSC_options: OT_LHSC ------- Description ~~~~~~~~~~~ Centered Latin Hypercube Sampling implemented in openTURNS library `External link `__ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Options ~~~~~~~ - **annealing**, :code:`bool` - if True, use simulated annealing to optimize LHS. Otherwise, use crude Monte Carlo. Default: True. - **centers**, :code:`array` - centers for axial, factorial and composite designs - **criterion**, :code:`str` - space-filling criterion, either "C2", "PhiP" or "MinDist". Default: "C2". - **distribution_name**, :code:`str` - distribution name - **end**, :code:`float` - level end for trapezoidal distribution - **eval_jac**, :code:`bool` - evaluate jacobian - **levels**, :code:`array` - levels for axial, factorial and composite designs - **max_time**, :code:`float` - maximum runtime in seconds, disabled if 0 (Default value = 0) - **mu**, :code:`float` - mean of a random variable for beta, normal and truncated normal distributions - **n_processes**, :code:`int` - number of processes - **n_replicates**, :code:`int` - number of Monte Carlo replicates to optimize LHS. Default: 1000. - **n_samples**, :code:`int` - number of samples - **seed**, :code:`int` - seed value. - **sigma**, :code:`float` - standard deviation for beta, normal and truncated normal distributions - **start**, :code:`float` - level start for trapezoidal distribution - **temperature**, :code:`string` - temperature profil for simulated annealing, either "Geometric" or "Linear". Default: "Geometric". - **wait_time_between_samples**, :code:`float` - waiting time between two samples .. _OT_MONTE_CARLO_options: OT_MONTE_CARLO -------------- Description ~~~~~~~~~~~ Monte Carlo sequence implemented in openTURNS library `External link `__ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Options ~~~~~~~ - **annealing**, :code:`bool` - if True, use simulated annealing to optimize LHS. Otherwise, use crude Monte Carlo. Default: True. - **centers**, :code:`array` - centers for axial, factorial and composite designs - **criterion**, :code:`str` - space-filling criterion, either "C2", "PhiP" or "MinDist". Default: "C2". - **distribution_name**, :code:`str` - distribution name - **end**, :code:`float` - level end for trapezoidal distribution - **eval_jac**, :code:`bool` - evaluate jacobian - **levels**, :code:`array` - levels for axial, factorial and composite designs - **max_time**, :code:`float` - maximum runtime in seconds, disabled if 0 (Default value = 0) - **mu**, :code:`float` - mean of a random variable for beta, normal and truncated normal distributions - **n_processes**, :code:`int` - number of processes - **n_replicates**, :code:`int` - number of Monte Carlo replicates to optimize LHS. Default: 1000. - **n_samples**, :code:`int` - number of samples - **seed**, :code:`int` - seed value. - **sigma**, :code:`float` - standard deviation for beta, normal and truncated normal distributions - **start**, :code:`float` - level start for trapezoidal distribution - **temperature**, :code:`string` - temperature profil for simulated annealing, either "Geometric" or "Linear". Default: "Geometric". - **wait_time_between_samples**, :code:`float` - waiting time between two samples .. _OT_OPT_LHS_options: OT_OPT_LHS ---------- Description ~~~~~~~~~~~ Optimal Latin Hypercube Sampling implemented in openTURNS library `External link `__ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Options ~~~~~~~ - **annealing**, :code:`bool` - if True, use simulated annealing to optimize LHS. Otherwise, use crude Monte Carlo. Default: True. - **centers**, :code:`array` - centers for axial, factorial and composite designs - **criterion**, :code:`str` - space-filling criterion, either "C2", "PhiP" or "MinDist". Default: "C2". - **distribution_name**, :code:`str` - distribution name - **end**, :code:`float` - level end for trapezoidal distribution - **eval_jac**, :code:`bool` - evaluate jacobian - **levels**, :code:`array` - levels for axial, factorial and composite designs - **max_time**, :code:`float` - maximum runtime in seconds, disabled if 0 (Default value = 0) - **mu**, :code:`float` - mean of a random variable for beta, normal and truncated normal distributions - **n_processes**, :code:`int` - number of processes - **n_replicates**, :code:`int` - number of Monte Carlo replicates to optimize LHS. Default: 1000. - **n_samples**, :code:`int` - number of samples - **seed**, :code:`int` - seed value. - **sigma**, :code:`float` - standard deviation for beta, normal and truncated normal distributions - **start**, :code:`float` - level start for trapezoidal distribution - **temperature**, :code:`string` - temperature profil for simulated annealing, either "Geometric" or "Linear". Default: "Geometric". - **wait_time_between_samples**, :code:`float` - waiting time between two samples .. _OT_RANDOM_options: OT_RANDOM --------- Description ~~~~~~~~~~~ Random sampling implemented in openTURNS library `External link `__ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Options ~~~~~~~ - **annealing**, :code:`bool` - if True, use simulated annealing to optimize LHS. Otherwise, use crude Monte Carlo. Default: True. - **centers**, :code:`array` - centers for axial, factorial and composite designs - **criterion**, :code:`str` - space-filling criterion, either "C2", "PhiP" or "MinDist". Default: "C2". - **distribution_name**, :code:`str` - distribution name - **end**, :code:`float` - level end for trapezoidal distribution - **eval_jac**, :code:`bool` - evaluate jacobian - **levels**, :code:`array` - levels for axial, factorial and composite designs - **max_time**, :code:`float` - maximum runtime in seconds, disabled if 0 (Default value = 0) - **mu**, :code:`float` - mean of a random variable for beta, normal and truncated normal distributions - **n_processes**, :code:`int` - number of processes - **n_replicates**, :code:`int` - number of Monte Carlo replicates to optimize LHS. Default: 1000. - **n_samples**, :code:`int` - number of samples - **seed**, :code:`int` - seed value. - **sigma**, :code:`float` - standard deviation for beta, normal and truncated normal distributions - **start**, :code:`float` - level start for trapezoidal distribution - **temperature**, :code:`string` - temperature profil for simulated annealing, either "Geometric" or "Linear". Default: "Geometric". - **wait_time_between_samples**, :code:`float` - waiting time between two samples .. _OT_REVERSE_HALTON_options: OT_REVERSE_HALTON ----------------- Description ~~~~~~~~~~~ Reverse Halton sequence implemented in openTURNS library `External link `__ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Options ~~~~~~~ - **annealing**, :code:`bool` - if True, use simulated annealing to optimize LHS. Otherwise, use crude Monte Carlo. Default: True. - **centers**, :code:`array` - centers for axial, factorial and composite designs - **criterion**, :code:`str` - space-filling criterion, either "C2", "PhiP" or "MinDist". Default: "C2". - **distribution_name**, :code:`str` - distribution name - **end**, :code:`float` - level end for trapezoidal distribution - **eval_jac**, :code:`bool` - evaluate jacobian - **levels**, :code:`array` - levels for axial, factorial and composite designs - **max_time**, :code:`float` - maximum runtime in seconds, disabled if 0 (Default value = 0) - **mu**, :code:`float` - mean of a random variable for beta, normal and truncated normal distributions - **n_processes**, :code:`int` - number of processes - **n_replicates**, :code:`int` - number of Monte Carlo replicates to optimize LHS. Default: 1000. - **n_samples**, :code:`int` - number of samples - **seed**, :code:`int` - seed value. - **sigma**, :code:`float` - standard deviation for beta, normal and truncated normal distributions - **start**, :code:`float` - level start for trapezoidal distribution - **temperature**, :code:`string` - temperature profil for simulated annealing, either "Geometric" or "Linear". Default: "Geometric". - **wait_time_between_samples**, :code:`float` - waiting time between two samples .. _OT_SOBOL_options: OT_SOBOL -------- Description ~~~~~~~~~~~ Sobol sequence implemented in openTURNS library `External link `__ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Options ~~~~~~~ - **annealing**, :code:`bool` - if True, use simulated annealing to optimize LHS. Otherwise, use crude Monte Carlo. Default: True. - **centers**, :code:`array` - centers for axial, factorial and composite designs - **criterion**, :code:`str` - space-filling criterion, either "C2", "PhiP" or "MinDist". Default: "C2". - **distribution_name**, :code:`str` - distribution name - **end**, :code:`float` - level end for trapezoidal distribution - **eval_jac**, :code:`bool` - evaluate jacobian - **levels**, :code:`array` - levels for axial, factorial and composite designs - **max_time**, :code:`float` - maximum runtime in seconds, disabled if 0 (Default value = 0) - **mu**, :code:`float` - mean of a random variable for beta, normal and truncated normal distributions - **n_processes**, :code:`int` - number of processes - **n_replicates**, :code:`int` - number of Monte Carlo replicates to optimize LHS. Default: 1000. - **n_samples**, :code:`int` - number of samples - **seed**, :code:`int` - seed value. - **sigma**, :code:`float` - standard deviation for beta, normal and truncated normal distributions - **start**, :code:`float` - level start for trapezoidal distribution - **temperature**, :code:`string` - temperature profil for simulated annealing, either "Geometric" or "Linear". Default: "Geometric". - **wait_time_between_samples**, :code:`float` - waiting time between two samples .. _OT_SOBOL_INDICES_options: OT_SOBOL_INDICES ---------------- Description ~~~~~~~~~~~ Sobol indices `External link `__ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Options ~~~~~~~ - **annealing**, :code:`bool` - if True, use simulated annealing to optimize LHS. Otherwise, use crude Monte Carlo. Default: True. - **centers**, :code:`array` - centers for axial, factorial and composite designs - **criterion**, :code:`str` - space-filling criterion, either "C2", "PhiP" or "MinDist". Default: "C2". - **distribution_name**, :code:`str` - distribution name - **end**, :code:`float` - level end for trapezoidal distribution - **eval_jac**, :code:`bool` - evaluate jacobian - **levels**, :code:`array` - levels for axial, factorial and composite designs - **max_time**, :code:`float` - maximum runtime in seconds, disabled if 0 (Default value = 0) - **mu**, :code:`float` - mean of a random variable for beta, normal and truncated normal distributions - **n_processes**, :code:`int` - number of processes - **n_replicates**, :code:`int` - number of Monte Carlo replicates to optimize LHS. Default: 1000. - **n_samples**, :code:`int` - number of samples - **seed**, :code:`int` - seed value. - **sigma**, :code:`float` - standard deviation for beta, normal and truncated normal distributions - **start**, :code:`float` - level start for trapezoidal distribution - **temperature**, :code:`string` - temperature profil for simulated annealing, either "Geometric" or "Linear". Default: "Geometric". - **wait_time_between_samples**, :code:`float` - waiting time between two samples .. _bbdesign_options: bbdesign -------- Description ~~~~~~~~~~~ Box-Behnken design implemented in pyDOE `External link `__ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Options ~~~~~~~ - **alpha**, :code:`str` - effect the variance, either "orthogonal" or "rotatable" - **center_bb**, :code:`int` - number of center points for Box-Behnken design - **center_cc**, :code:`tuple` - 2-tuple of center points for the central composite design - **criterion**, :code:`string` - Default value = None) :type criterion: - **eval_jac**, :code:`bool` - evaluate jacobian - **face**, :code:`str` - The relation between the start points and the corner (factorial) points, either "circumscribed", "inscribed" or "faced" - **iterations**, :code:`integer` - Default value = 5) :type iterations: - **levels**, :code:`array` - levels for axial, factorial and composite designs - **max_time**, :code:`float` - maximum runtime in seconds, disabled if 0 (Default value = 0) - **n_processes**, :code:`int` - number of processes - **n_samples**, :code:`int` - number of samples - **seed**, :code:`int` - seed value. - **wait_time_between_samples**, :code:`float` - waiting time between two samples .. _ccdesign_options: ccdesign -------- Description ~~~~~~~~~~~ Central Composite implemented in pyDOE `External link `__ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Options ~~~~~~~ - **alpha**, :code:`str` - effect the variance, either "orthogonal" or "rotatable" - **center_bb**, :code:`int` - number of center points for Box-Behnken design - **center_cc**, :code:`tuple` - 2-tuple of center points for the central composite design - **criterion**, :code:`string` - Default value = None) :type criterion: - **eval_jac**, :code:`bool` - evaluate jacobian - **face**, :code:`str` - The relation between the start points and the corner (factorial) points, either "circumscribed", "inscribed" or "faced" - **iterations**, :code:`integer` - Default value = 5) :type iterations: - **levels**, :code:`array` - levels for axial, factorial and composite designs - **max_time**, :code:`float` - maximum runtime in seconds, disabled if 0 (Default value = 0) - **n_processes**, :code:`int` - number of processes - **n_samples**, :code:`int` - number of samples - **seed**, :code:`int` - seed value. - **wait_time_between_samples**, :code:`float` - waiting time between two samples .. _ff2n_options: ff2n ---- Description ~~~~~~~~~~~ 2-Level Full-Factorial implemented in pyDOE `External link `__ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Options ~~~~~~~ - **alpha**, :code:`str` - effect the variance, either "orthogonal" or "rotatable" - **center_bb**, :code:`int` - number of center points for Box-Behnken design - **center_cc**, :code:`tuple` - 2-tuple of center points for the central composite design - **criterion**, :code:`string` - Default value = None) :type criterion: - **eval_jac**, :code:`bool` - evaluate jacobian - **face**, :code:`str` - The relation between the start points and the corner (factorial) points, either "circumscribed", "inscribed" or "faced" - **iterations**, :code:`integer` - Default value = 5) :type iterations: - **levels**, :code:`array` - levels for axial, factorial and composite designs - **max_time**, :code:`float` - maximum runtime in seconds, disabled if 0 (Default value = 0) - **n_processes**, :code:`int` - number of processes - **n_samples**, :code:`int` - number of samples - **seed**, :code:`int` - seed value. - **wait_time_between_samples**, :code:`float` - waiting time between two samples .. _fullfact_options: fullfact -------- Description ~~~~~~~~~~~ Full-Factorial implemented in pyDOE `External link `__ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Options ~~~~~~~ - **alpha**, :code:`str` - effect the variance, either "orthogonal" or "rotatable" - **center_bb**, :code:`int` - number of center points for Box-Behnken design - **center_cc**, :code:`tuple` - 2-tuple of center points for the central composite design - **criterion**, :code:`string` - Default value = None) :type criterion: - **eval_jac**, :code:`bool` - evaluate jacobian - **face**, :code:`str` - The relation between the start points and the corner (factorial) points, either "circumscribed", "inscribed" or "faced" - **iterations**, :code:`integer` - Default value = 5) :type iterations: - **levels**, :code:`array` - levels for axial, factorial and composite designs - **max_time**, :code:`float` - maximum runtime in seconds, disabled if 0 (Default value = 0) - **n_processes**, :code:`int` - number of processes - **n_samples**, :code:`int` - number of samples - **seed**, :code:`int` - seed value. - **wait_time_between_samples**, :code:`float` - waiting time between two samples .. _lhs_options: lhs --- Description ~~~~~~~~~~~ Latin Hypercube Sampling implemented in pyDOE `External link `__ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Options ~~~~~~~ - **alpha**, :code:`str` - effect the variance, either "orthogonal" or "rotatable" - **center_bb**, :code:`int` - number of center points for Box-Behnken design - **center_cc**, :code:`tuple` - 2-tuple of center points for the central composite design - **criterion**, :code:`string` - Default value = None) :type criterion: - **eval_jac**, :code:`bool` - evaluate jacobian - **face**, :code:`str` - The relation between the start points and the corner (factorial) points, either "circumscribed", "inscribed" or "faced" - **iterations**, :code:`integer` - Default value = 5) :type iterations: - **levels**, :code:`array` - levels for axial, factorial and composite designs - **max_time**, :code:`float` - maximum runtime in seconds, disabled if 0 (Default value = 0) - **n_processes**, :code:`int` - number of processes - **n_samples**, :code:`int` - number of samples - **seed**, :code:`int` - seed value. - **wait_time_between_samples**, :code:`float` - waiting time between two samples .. _pbdesign_options: pbdesign -------- Description ~~~~~~~~~~~ Plackett-Burman design implemented in pyDOE `External link `__ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Options ~~~~~~~ - **alpha**, :code:`str` - effect the variance, either "orthogonal" or "rotatable" - **center_bb**, :code:`int` - number of center points for Box-Behnken design - **center_cc**, :code:`tuple` - 2-tuple of center points for the central composite design - **criterion**, :code:`string` - Default value = None) :type criterion: - **eval_jac**, :code:`bool` - evaluate jacobian - **face**, :code:`str` - The relation between the start points and the corner (factorial) points, either "circumscribed", "inscribed" or "faced" - **iterations**, :code:`integer` - Default value = 5) :type iterations: - **levels**, :code:`array` - levels for axial, factorial and composite designs - **max_time**, :code:`float` - maximum runtime in seconds, disabled if 0 (Default value = 0) - **n_processes**, :code:`int` - number of processes - **n_samples**, :code:`int` - number of samples - **seed**, :code:`int` - seed value. - **wait_time_between_samples**, :code:`float` - waiting time between two samples