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grid_search_sk   A

Complexity

Total Complexity 0

Size/Duplication

Total Lines 34
Duplicated Lines 0 %

Importance

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Metric Value
wmc 0
eloc 16
dl 0
loc 34
rs 10
c 0
b 0
f 0
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"""
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GridSearchSk Optimizer Example
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This example demonstrates how to use the GridSearchSk optimizer with
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loky backend for parallel execution.
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"""
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import numpy as np
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from hyperactive.opt import GridSearchSk
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from hyperactive.experiment.toy import Sphere
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# Define the optimization problem using a toy sphere function
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# The sphere function f(x,y) = x² + y² has its minimum at (0,0)
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sphere_experiment = Sphere(n_dim=2)
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# Define parameter grid - creates a 9x9 = 81 point grid
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param_grid = {
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    "x0": np.linspace(-2, 2, 9),
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    "x1": np.linspace(-2, 2, 9),
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}
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# Grid search with parallel execution using loky backend
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grid_search = GridSearchSk(
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    param_grid=param_grid,
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    backend="loky",  # Use loky backend for parallelization
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    backend_params={
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        "n_jobs": -1,  # Use all available CPU cores
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    },
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    experiment=sphere_experiment,
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)
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best_params = grid_search.run()
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print(f"Best params: {best_params}, Score: {grid_search.best_score_:.6f}")
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