pykoop.GridCenters
- class GridCenters(n_points_per_feature=2, symmetric_range=False)
Bases:
Centers
Centers generated on a uniform grid.
- centers_
Centers, shape (n_centers, n_features).
- Type:
np.ndarray
- range_max_
Maximum value of each feature used to generate grid.
- Type:
np.ndarray
- range_min_
Minimum value of each feature used to generate grid.
- Type:
np.ndarray
Examples
Generate centers on a grid
>>> grid = pykoop.GridCenters(n_points_per_feature=4) >>> grid.fit(X_msd[:, 1:]) # Remove episode feature GridCenters(n_points_per_feature=4) >>> grid.centers_ array([...])
- __init__(n_points_per_feature=2, symmetric_range=False)
Instantiate
GridCenters
.- Parameters:
n_points_per_feature (int) – Number of points in grid for each feature.
symmetric_range (bool) – If true, the grid range for a given feature is forced to be symmetric about zero (i.e.,
[-max(abs(x)), max(abs(x))]
). Otherwise, the grid range is taken directly on the data (i.e.,[min(x), max(x)]
). Default is false.
- Return type:
None
Methods
__init__
([n_points_per_feature, symmetric_range])Instantiate
GridCenters
.fit
(X[, y])Generate centers from data.
Get metadata routing of this object.
get_params
([deep])Get parameters for this estimator.
set_params
(**params)Set the parameters of this estimator.
- fit(X, y=None)
Generate centers from data.
- Parameters:
X (np.ndarray) – Data matrix.
y (Optional[np.ndarray]) – Ignored.
- Returns:
Instance of itself.
- Return type:
- Raises:
ValueError – If any of the constructor parameters are incorrect.
- get_metadata_routing()
Get metadata routing of this object.
Please check User Guide on how the routing mechanism works.
- Returns:
routing – A
MetadataRequest
encapsulating routing information.- Return type:
MetadataRequest
- get_params(deep=True)
Get parameters for this estimator.
- set_params(**params)
Set the parameters of this estimator.
The method works on simple estimators as well as on nested objects (such as
Pipeline
). The latter have parameters of the form<component>__<parameter>
so that it’s possible to update each component of a nested object.- Parameters:
**params (dict) – Estimator parameters.
- Returns:
self – Estimator instance.
- Return type:
estimator instance