Created
April 15, 2021 08:45
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Simple Benchmark for `sklearn.neighbours.BinaryTree`
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| import numpy as np | |
| from sklearn.neighbors import KDTree, BallTree | |
| from .common import Benchmark | |
| class BinaryTreeStatsBenchmark(Benchmark): | |
| """ | |
| Base class for BinaryTree benchmarks for removing statistics. | |
| """ | |
| param_names = ['BinaryTree', 'n', 'd', 'leaf_size'] | |
| params = ( | |
| [KDTree, BallTree], | |
| [100, 1000, 10000], | |
| [10, 100, 1000], | |
| [10, 100] | |
| ) | |
| class BinaryTreeStatsCreation(BinaryTreeStatsBenchmark): | |
| """ | |
| Benchmarks for BinaryTree creation. | |
| """ | |
| def setup(self, BinaryTree, n, d, leaf_size): | |
| self.samples = np.random.rand(n, d) | |
| self.leaf_size = leaf_size | |
| self.BinaryTree = BinaryTree | |
| def time_creation(self, BinaryTree, n, d, leaf_size): | |
| self.BinaryTree(self.samples, leaf_size=self.leaf_size) | |
| class BinaryTreeStatsQuery(BinaryTreeStatsBenchmark): | |
| """ | |
| Benchmarks for BinaryTree queries. | |
| """ | |
| def setup(self, BinaryTree, n, d, leaf_size): | |
| self.tree = BinaryTree(np.random.rand(n, d), leaf_size=leaf_size) | |
| self.query_points = np.random.rand(n, d) | |
| def time_query(self, BinaryTree, n, d, leaf_size): | |
| self.tree.query( | |
| self.query_points, | |
| dualtree=False, | |
| breadth_first=False, | |
| sort_results=False) |
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Raw results for scikit-learn/scikit-learn#19893: