r"""The function1 peak function to be used with scenario 1. :math:`f(\mathbf{x}) = \\frac{h}{1 + w \sqrt{\sum_{i=1}^N (x_i - p_i)^2}}`

Generate an expression where each leaf has the same depth between *min* and *max*. :param pset: Primitive set from which primitives are selec

Generate an expression where each leaf might have a different depth between *min* and *max*. :param pset: Primitive set from which primitives

.. deprecated:: 1.0 The function has been renamed. Use :func:`~deap.gp.genHalfAndHalf` instead.

r"""Generate a population of :math:`\lambda` individuals of type *ind_init* from the current strategy. :param ind_init: A function ob

r"""Generate a population of :math:`\lambda` individuals of type *ind_init* from the current strategy. :param ind_init: A function ob

Generate a population of :math:`\lambda` individuals of type *ind_init* from the current strategy. :param ind_init: A function object

Provide the genealogy tree of an *individual*. The individual must have an attribute :attr:`history_index` as defined by :func:`~deap.

Returns the length of the i-th list.

Construct the graph of a tree expression. The tree expression must be valid. It returns in order a node list, an edge list, and a dictionary of

r"""Griewank test objective function. .. list-table:: :widths: 10 50 :stub-columns: 1 * - Type - minimization

r""" Simple two-dimensional function containing several local maxima. From: The Merits of a Parallel Genetic Algorithm in Solving Hard Optimiz

Implement bloat control on a GP evolution using HARM-GP, as defined in [Gardner2015]. It is implemented in the form of an evolution algorithm

r"""The Himmelblau's function is multimodal with 4 defined minimums in :math:`[-6, 6]^2`. .. list-table:: :widths: 10 50 :stub-

Return the hypervolume of a *front*. If the *ref* point is not given, the worst value for each objective +1 is used. :param front: The popula

Returns directly the argument *obj*.

Returns directly the argument *obj*.

Call the function *container* with a generator function corresponding to the calling *n* times the functions present in *seq_func*. :param co

Call the function *container* with an iterable as its only argument. The iterable must be returned by the method or the object *generator*.

Call the function *func* *n* times and return the results in a container type `container` :param container: The type to put in the data from

Initialize a target set with noisy string to match based on the schematas provided.

Replace the __init__ function of the new type, in order to add attributes that were defined with **kargs to the instance.

r"""Kotanchek benchmark function. .. list-table:: :widths: 10 50 :stub-columns: 1 * - Range - :math:`\mathbf{x} \i

r"""Kursawe multiobjective function. :math:`f_{\text{Kursawe}1}(\mathbf{x}) = \sum_{i=1}^{N-1} -10 e^{-0.2 \sqrt{x_i^2 + x_{i+1}^2} }` :math

Return the number of comparison-swap used.

Return the number of comparison-swap used.

Compute the contribution of the string at *index* in the match set.

Compute the match strength of a set of strings on the target set of strings. The strength is the maximum of all match string on each target.

Compute the match strength of a set of strings on the target set of strings. The strength is the maximum of all match string on each target ex

Migration using pipes between initialized processes. It first selects *k* individuals from the *deme* and writes them in *pipeout*. Then it re

Perform a ring migration between the *populations*. The migration first select *k* emigrants from each population using the specified *selection*

Adds or remove an item from an individual

r"""Mutate an evolution strategy according to its :attr:`strategy` attribute as described in [Beyer2002]_. First the strategy is mutated accor

This operator works on the constants of the tree *individual*. In *mode* ``"one"``, it will change the value of one of the individual ephemera

Flip the value of the attributes of the input individual and return the mutant. The *individual* is expected to be a :term:`sequence` and the valu

This function applies a gaussian mutation of mean *mu* and standard deviation *sigma* on the input individual. This mutation expects a :term:`

Inserts a new branch at a random position in *individual*. The subtree at the chosen position is used as child node of the created subtree, in

Replaces a randomly chosen primitive from *individual* by a randomly chosen primitive with the same number of arguments from the :attr:`pset`

Polynomial mutation as implemented in original NSGA-II algorithm in C by Deb. :param individual: :term:`Sequence <sequence>` individual to be

Implementation of the Semantic Mutation operator. [Geometric semantic genetic programming, Moraglio et al., 2012] mutated_individual = indivi

Mutation that pops or add an element.

This operator shrinks the *individual* by choosing randomly a branch and replacing it with one of the branch's arguments (also randomly chosen).

Shuffle the attributes of the input individual and return the mutant. The *individual* is expected to be a :term:`sequence`. The *indpb* argument

Randomly select a point in the tree *individual*, then replace the subtree at that point as a root by the expression generated using method :f

Mutate an individual by replacing attributes, with probability *indpb*, by a integer uniformly drawn between *low* and *up* inclusively. :par

Set the current noise to *noise*. After decorating the evaluation function, this function will be available directly from the function

r"""Plane test objective function. .. list-table:: :widths: 10 50 :stub-columns: 1 * - Type - minimization

r"""Poloni's multiobjective function on a two attribute *individual*. From: C. Poloni, "Hybrid GA for multi objective aerodynamic shape optimizati