skopt.space.space
.Integer¶
-
class
skopt.space.space.
Integer
(low, high, prior='uniform', base=10, transform=None, name=None, dtype=<class 'numpy.int64'>)[source][source]¶ Search space dimension that can take on integer values.
- Parameters
- lowint
Lower bound (inclusive).
- highint
Upper bound (inclusive).
- prior“uniform” or “log-uniform”, default=”uniform”
Distribution to use when sampling random integers for this dimension. - If
"uniform"
, intgers are sampled uniformly between the lowerand upper bounds.
If
"log-uniform"
, intgers are sampled uniformly betweenlog(lower, base)
andlog(upper, base)
where log has basebase
.
- baseint
The logarithmic base to use for a log-uniform prior. - Default 10, otherwise commonly 2.
- transform“identity”, “normalize”, optional
The following transformations are supported.
“identity”, (default) the transformed space is the same as the original space.
“normalize”, the transformed space is scaled to be between 0 and 1.
- namestr or None
Name associated with dimension, e.g., “number of trees”.
- dtypestr or dtype, default=np.int64
integer type which will be used in inverse_transform, can be int, np.int16, np.uint32, np.int32, np.int64 (default). When set to int,
inverse_transform
returns a list instead of a numpy array
- Attributes
- bounds
- name
- prior
- size
- transformed_bounds
- transformed_size
Methods
distance
(self, a, b)Compute distance between point
a
andb
.inverse_transform
(self, Xt)Inverse transform samples from the warped space back into the original space.
rvs
(self[, n_samples, random_state])Draw random samples.
transform
(self, X)Transform samples form the original space to a warped space.
-
__init__
(self, low, high, prior='uniform', base=10, transform=None, name=None, dtype=<class 'numpy.int64'>)[source][source]¶ Initialize self. See help(type(self)) for accurate signature.
-
distance
(self, a, b)[source][source]¶ Compute distance between point
a
andb
.- Parameters
- aint
First point.
- bint
Second point.
-
inverse_transform
(self, Xt)[source][source]¶ Inverse transform samples from the warped space back into the original space.