skopt.space.space
.Space¶

class
skopt.space.space.
Space
(dimensions)[source][source]¶ Initialize a search space from given specifications.
 Parameters
 dimensionslist, shape=(n_dims,)
List of search space dimensions. Each search dimension can be defined either as
a
(lower_bound, upper_bound)
tuple (forReal
orInteger
dimensions),a
(lower_bound, upper_bound, "prior")
tuple (forReal
dimensions),as a list of categories (for
Categorical
dimensions), oran instance of a
Dimension
object (Real
,Integer
orCategorical
).
Note
The upper and lower bounds are inclusive for
Integer
dimensions.
 Attributes
bounds
The dimension bounds, in the original space.
dimension_names
Names of all the dimensions in the searchspace.
is_categorical
Space contains exclusively categorical dimensions
is_partly_categorical
Space contains any categorical dimensions
is_real
Returns true if all dimensions are Real
n_constant_dimensions
Returns the number of constant dimensions which have zero degree of freedom, e.g.
n_dims
The dimensionality of the original space.
transformed_bounds
The dimension bounds, in the warped space.
transformed_n_dims
The dimensionality of the warped space.
Methods
distance
(point_a, point_b)Compute distance between two points in this space.
from_yaml
(yml_path[, namespace])Create Space from yaml configuration file
Returns all transformers as list
Inverse transform samples from the warped space back to the
rvs
([n_samples, random_state])Draw random samples.
set_transformer
(transform)Sets the transformer of all dimension objects to
transform
set_transformer_by_type
(transform, dim_type)Sets the transformer of
dim_type
objects totransform
transform
(X)Transform samples from the original space into a warped space.

property
bounds
¶ The dimension bounds, in the original space.

property
dimension_names
¶ Names of all the dimensions in the searchspace.

distance
(point_a, point_b)[source][source]¶ Compute distance between two points in this space.
 Parameters
 point_aarray
First point.
 point_barray
Second point.

classmethod
from_yaml
(yml_path, namespace=None)[source][source]¶ Create Space from yaml configuration file
 Parameters
 yml_pathstr
Full path to yaml configuration file, example YaML below: Space:
Integer: low: 5 high: 5
Categorical: categories:  a  b
Real: low: 1.0 high: 5.0 prior: loguniform
 namespacestr, default=None
Namespace within configuration file to use, will use first namespace if not provided
 Returns
 spaceSpace
Instantiated Space object

inverse_transform
(Xt)[source][source]¶  Inverse transform samples from the warped space back to the
original space.
 Parameters
 Xtarray of floats, shape=(n_samples, transformed_n_dims)
The samples to inverse transform.
 Returns
 Xlist of lists, shape=(n_samples, n_dims)
The original samples.

property
is_categorical
¶ Space contains exclusively categorical dimensions

property
is_partly_categorical
¶ Space contains any categorical dimensions

property
is_real
¶ Returns true if all dimensions are Real

property
n_constant_dimensions
¶ Returns the number of constant dimensions which have zero degree of freedom, e.g. an Integer dimensions with (0., 0.) as bounds.

property
n_dims
¶ The dimensionality of the original space.

rvs
(n_samples=1, random_state=None)[source][source]¶ Draw random samples.
The samples are in the original space. They need to be transformed before being passed to a model or minimizer by
space.transform()
. Parameters
 n_samplesint, default=1
Number of samples to be drawn from the space.
 random_stateint, RandomState instance, or None (default)
Set random state to something other than None for reproducible results.
 Returns
 pointslist of lists, shape=(n_points, n_dims)
Points sampled from the space.

set_transformer
(transform)[source][source]¶ Sets the transformer of all dimension objects to
transform
 Parameters
 transformstr or list of str
Sets all transformer,, when
transform
is a string. Otherwise, transform must be a list with strings with the same length asdimensions

set_transformer_by_type
(transform, dim_type)[source][source]¶ Sets the transformer of
dim_type
objects totransform
 Parameters
 transformstr
Sets all transformer of type
dim_type
totransform
 dim_typetype
 Can be
skopt.space.Real
,skopt.space.Integer
or skopt.space.Categorical
 Can be

transform
(X)[source][source]¶ Transform samples from the original space into a warped space.
 Note: this transformation is expected to be used to project samples
into a suitable space for numerical optimization.
 Parameters
 Xlist of lists, shape=(n_samples, n_dims)
The samples to transform.
 Returns
 Xtarray of floats, shape=(n_samples, transformed_n_dims)
The transformed samples.

property
transformed_bounds
¶ The dimension bounds, in the warped space.

property
transformed_n_dims
¶ The dimensionality of the warped space.