remove only most current key-entry

defines self[key]

defines self[key]

initialize the best solution with `x`, `f`, and `evals`. Better solutions have smaller `f`-values.

Argument bounds can be `None` or ``bounds[0]`` and ``bounds[1]`` are lower and upper domain boundaries, each is either `None` or a

return `GenoPheno` instance with fixed dimension `dim`. Keyword Arguments ----------------- `scaling`

``xstart`` is a mandatory argument

see class `CMAEvolutionStrategy`

return an `Options` instance, either with the default options, if ``s is None``, or with all options whose name or description conta

Compute strategy parameters, mainly depending on dimension and population size, by calling `set`

initialize logging of data from a `CMAEvolutionStrategy` instance, default modulo expands to 1 == log with each call

initialize logging of data from a `CMAEvolutionStrategy` instance, default modulo expands to 1 == log with each call

parameters are `N` dimension `maxevals` maximal value for ``self.evaluations``, where

Parameters ---------- `func` objective function `x` point in search spa

defines self[key] = value

defines self[key] = value

not yet implemented

abstract method, add a "data point" from the state of `optim` into the logger, the argument `optim` can be omitted if it was `register()`-ed

abstract method, add a "data point" from the state of `optim` into the logger, the argument `optim` can be omitted if it was `register()`-ed

append some logging data from `CMAEvolutionStrategy` class instance `es`, if ``number_of_times_called % modulo`` equals to zero, never if ``m

Cigar test objective function

Cigtab test objective function

rank mu learning rate, disregarding the constrant cmu <= 1 - cone

used for computing separable learning rate

rank one update learning rate, ``df`` is disregarded and obsolete, reduce alphacov on noisy problems, say to 0.5

used for computing separable learning rate

Sphere (squared norm) test objective function constraint to the corner

return logged data in a dictionary (not implemented)

Diffpow test objective function

displays selected data from (files written by) the class `CMADataLogger`. The call ``cma.disp(name, idx)`` is a shortcut for ``cma.CMADataLogge

display some data trace (not implemented)

display some data trace (not implemented)

displays selected data from (files written by) the class `CMADataLogger`. Arguments --------- `idx` in

displays selected data from (files written by) the class `CMADataLogger`. Arguments --------- `idx` in

return C**-1/2 times mat, where mat can be a vector or matrix

generates, plots and saves function values ``func(y)``, where ``y`` is 'close' to `x` (see `__init__()`). The data are stored in the

rude downsampling of a `CMADataLogger` data file by `factor`, keeping also the first `first` entries. This function is a stump and

rude downsampling of a `CMADataLogger` data file by `factor`, keeping also the first `first` entries. This function is a stump and