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from functools import partial
import os
import numpy as np
import scipy.sparse
from Orange.data import Table, ContinuousVariable, Domain
from .base import Benchmark, benchmark
def save(table, fn):
try:
table.save(fn)
finally:
os.remove(fn)
class BenchSave(Benchmark):
def setup_dense(self, rows, cols, varkwargs=None):
if varkwargs is None:
varkwargs = {}
self.table = Table.from_numpy( # pylint: disable=W0201
Domain([ContinuousVariable(str(i), **varkwargs) for i in range(cols)]),
np.random.RandomState(0).rand(rows, cols))
def setup_sparse(self, rows, cols, varkwargs=None):
if varkwargs is None:
varkwargs = {}
sparse = scipy.sparse.rand(rows, cols, density=0.01, format='csr', random_state=0)
self.table = Table.from_numpy( # pylint: disable=W0201
Domain([ContinuousVariable(str(i), sparse=True, **varkwargs) for i in range(cols)]),
sparse)
@benchmark(setup=partial(setup_dense, rows=100, cols=10))
def bench_print_dense(self):
str(self.table)
@benchmark(setup=partial(setup_dense, rows=100, cols=10,
varkwargs={"number_of_decimals": 2}))
def bench_print_dense_decimals(self):
str(self.table)
@benchmark(setup=partial(setup_sparse, rows=100, cols=10), number=5)
def bench_print_sparse(self):
str(self.table)
@benchmark(setup=partial(setup_sparse, rows=100, cols=10,
varkwargs={"number_of_decimals": 2}),
number=5)
def bench_print_sparse_decimals(self):
str(self.table)
@benchmark(setup=partial(setup_dense, rows=100, cols=100))
def bench_save_tab(self):
save(self.table, "temp_save.tab")
@benchmark(setup=partial(setup_dense, rows=100, cols=100,
varkwargs={"number_of_decimals": 2}))
def bench_save_tab_decimals(self):
save(self.table, "temp_save.tab")
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