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import numpy as np
from Orange.data import DomainConversion, Domain, Table, \
ContinuousVariable, DiscreteVariable
from Orange.preprocess import Discretize, EqualFreq, Normalize
from .base import Benchmark, benchmark
class BenchConversion(Benchmark):
def setUp(self):
cols = 1000
rows = 100
cont = [ContinuousVariable(str(i)) for i in range(cols)]
disc = [DiscreteVariable("D" + str(i), values=("1", "2")) for i in range(cols)]
self.domain = Domain(cont + disc)
self.domain_x = Domain(list(self.domain.attributes) + [ContinuousVariable("x")])
self.single = Domain([ContinuousVariable("0")])
self.table = Table.from_numpy(
self.domain,
np.random.RandomState(0).randint(0, 2, (rows, len(self.domain.variables))))
self.discretized_domain = Discretize(EqualFreq(n=3))(self.table).domain
self.normalized_domain = Normalize()(self.table).domain
@benchmark(number=5)
def bench_full(self):
DomainConversion(self.domain, self.domain_x)
@benchmark(number=5)
def bench_selection(self):
DomainConversion(self.domain, self.single)
@benchmark(number=5)
def bench_transform_copy(self):
self.table.transform(self.domain_x)
@benchmark(number=5)
def bench_transform_discretize(self):
self.table.transform(self.discretized_domain)
@benchmark(number=5)
def bench_transform_normalize(self):
self.table.transform(self.normalized_domain)
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