jjerphan/binary_tree.py

## binary_tree.py
import numpy as np

from sklearn.neighbors import KDTree, BallTree
from .common import Benchmark


class BinaryTreeBenchmark(Benchmark):
    """
    Base class for BinaryTree benchmarks.
    """

    param_names = ['BinaryTree', 'n', 'matrix_type', 'leaf_size']
    params = [
        [KDTree, BallTree],
        [1000, 10000],
        ['random', 'ordered', 'reverse_ordered', 'duplicated'],
        [1 , 20, 40, 100],
    ]

    test_cases = {
        "random": lambda n: np.random.rand(n),
        "ordered": lambda n: np.arange(n, dtype=float),
        "reverse_ordered": lambda n: np.arange(n, 0, -1, dtype=float),
        "duplicated": lambda n:  np.zeros([n], dtype=float)
    }


class BinaryTreeCreation(BinaryTreeBenchmark):
    """
    Benchmarks for BinaryTree creation.
    """

    def setup(self, BinaryTree, n, matrix_type, leaf_size):
        self.data = np.expand_dims(self.test_cases[matrix_type](n), -1)
        self.leaf_size = leaf_size
        self.BinaryTree = BinaryTree

    def time_creation(self, BinaryTree, n, matrix_type, leaf_size):
        self.BinaryTree(self.data, leaf_size=self.leaf_size)


class BinaryTreeQuery(BinaryTreeBenchmark):
    """
    Benchmarks for BinaryTree queries.
    """
    param_names = BinaryTreeBenchmark.param_names + ['breadth_first']
    params = BinaryTreeBenchmark.params + [[True, False]]

    def setup(self, BinaryTree, n, matrix_type, leaf_size, breadth_first):
        self.data = np.expand_dims(self.test_cases[matrix_type](n), -1)
        self.tree = BinaryTree(self.data, leaf_size=leaf_size)
        self.query_points = np.expand_dims(np.random.rand(10000), -1)

    def time_query(self, BinaryTree, n, matrix_type, leaf_size, breadth_first):
        self.tree.query(
            self.query_points,
            dualtree=False,
            breadth_first=breadth_first,
            sort_results=False)
	import numpy as np

	from sklearn.neighbors import KDTree, BallTree
	from .common import Benchmark


	class BinaryTreeBenchmark(Benchmark):
	"""
	Base class for BinaryTree benchmarks.
	"""

	param_names = ['BinaryTree', 'n', 'matrix_type', 'leaf_size']
	params = [
	[KDTree, BallTree],
	[1000, 10000],
	['random', 'ordered', 'reverse_ordered', 'duplicated'],
	[1 , 20, 40, 100],
	]

	test_cases = {
	"random": lambda n: np.random.rand(n),
	"ordered": lambda n: np.arange(n, dtype=float),
	"reverse_ordered": lambda n: np.arange(n, 0, -1, dtype=float),
	"duplicated": lambda n: np.zeros([n], dtype=float)
	}


	class BinaryTreeCreation(BinaryTreeBenchmark):
	"""
	Benchmarks for BinaryTree creation.
	"""

	def setup(self, BinaryTree, n, matrix_type, leaf_size):
	self.data = np.expand_dims(self.test_cases[matrix_type](n), -1)
	self.leaf_size = leaf_size
	self.BinaryTree = BinaryTree

	def time_creation(self, BinaryTree, n, matrix_type, leaf_size):
	self.BinaryTree(self.data, leaf_size=self.leaf_size)


	class BinaryTreeQuery(BinaryTreeBenchmark):
	"""
	Benchmarks for BinaryTree queries.
	"""
	param_names = BinaryTreeBenchmark.param_names + ['breadth_first']
	params = BinaryTreeBenchmark.params + [[True, False]]

	def setup(self, BinaryTree, n, matrix_type, leaf_size, breadth_first):
	self.data = np.expand_dims(self.test_cases[matrix_type](n), -1)
	self.tree = BinaryTree(self.data, leaf_size=leaf_size)
	self.query_points = np.expand_dims(np.random.rand(10000), -1)

	def time_query(self, BinaryTree, n, matrix_type, leaf_size, breadth_first):
	self.tree.query(
	self.query_points,
	dualtree=False,
	breadth_first=breadth_first,
	sort_results=False)