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from Orange.data import Table
from Orange.preprocess import Discretize
from Orange.preprocess.discretize import EqualFreq
from .base import Benchmark, benchmark, pandas_only, non_pandas_only
# noinspection PyBroadException
try:
from Orange.data.filter import FilterContinuous, FilterDiscrete, Values
except: # pylint: disable=bare-except
# legacy only
pass
# noinspection PyStatementEffect
class BenchBasic(Benchmark):
def setUp(self):
self.iris = Table('iris')
self.adult = Table('adult')
self.discretizer = Discretize(EqualFreq(n=3))
@benchmark(number=100)
def bench_iris_read(self):
Table('iris')
@benchmark(number=5, warmup=1)
def bench_adult_read(self):
Table('adult')
@benchmark(number=100)
def bench_iris_create_X(self):
self.iris.X
@benchmark(number=50)
def bench_adult_create_X(self):
self.adult.X
@pandas_only
@benchmark(number=20)
def bench_adult_filter_pandas(self):
self.adult[(self.adult.age > 30) & (self.adult.workclass == 'Private')]
@non_pandas_only
@benchmark(number=20)
def bench_adult_filter_pre_pandas(self):
age_filter = FilterContinuous(self.adult.domain["age"], FilterContinuous.Greater, 30)
workclass_filter = FilterDiscrete(self.adult.domain["workclass"], [0])
combined = Values([age_filter, workclass_filter])
combined(self.adult)
@benchmark(number=50)
def bench_iris_basic_stats(self):
self.iris._compute_basic_stats()
@benchmark(number=20)
def bench_iris_distributions(self):
self.iris._compute_distributions()
@benchmark()
def bench_iris_contingency(self):
self.iris._compute_contingency()
@benchmark()
def bench_iris_discretize(self):
self.discretizer(self.iris)
@pandas_only
@benchmark()
def bench_iris_iteration_pandas(self):
for _, _ in self.iris.iterrows():
pass
@non_pandas_only
@benchmark()
def bench_iris_iteration_pre_pandas(self):
for _ in self.iris:
pass
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