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from itertools import count
import time
import os
import unittest
from unittest.mock import Mock, patch
import warnings
import numpy as np
import scipy.sparse as sp
from Orange.util import export_globals, flatten, deprecated, try_, deepgetattr, \
OrangeDeprecationWarning, nan_eq, nan_hash_stand, Registry, namegen
from Orange.data.util import vstack, hstack, array_equal
from Orange.statistics.util import stats
from Orange.tests.test_statistics import dense_sparse
from Orange.util import wrap_callback, get_entry_point, allot
SOMETHING = 0xf00babe
class TestUtil(unittest.TestCase):
def test_get_entry_point(self):
# pylint: disable=import-outside-toplevel
from Orange.canvas.__main__ import main as real_main
main = get_entry_point("Orange3", "gui_scripts", "orange-canvas")
self.assertIs(main, real_main)
def test_export_globals(self):
self.assertEqual(sorted(export_globals(globals(), __name__)),
['SOMETHING', 'TestAllot', 'TestUtil'])
def test_flatten(self):
self.assertEqual(list(flatten([[1, 2], [3]])), [1, 2, 3])
def test_deprecated(self):
@deprecated
def identity(x):
return x
with self.assertWarns(DeprecationWarning) as cm:
x = identity(10)
self.assertEqual(x, 10)
self.assertTrue('deprecated' in cm.warning.args[0])
self.assertTrue('identity' in cm.warning.args[0])
def test_try_(self):
self.assertTrue(try_(lambda: np.ones(3).any()))
self.assertFalse(try_(lambda: 1 / 0))
self.assertEqual(try_(len, default=SOMETHING), SOMETHING)
def test_reprable(self):
# pylint: disable=import-outside-toplevel
from Orange.data import ContinuousVariable
from Orange.preprocess.impute import ReplaceUnknownsRandom
from Orange.statistics.distribution import Continuous
from Orange.classification import LogisticRegressionLearner
var = ContinuousVariable('x')
transform = ReplaceUnknownsRandom(var, Continuous(1, var))
self.assertEqual(repr(transform).replace('\n', '').replace(' ', ''),
"ReplaceUnknownsRandom("
"variable=ContinuousVariable(name='x',number_of_decimals=3),"
"distribution=Continuous([[0.],[0.]]))")
# GH 2275
logit = LogisticRegressionLearner()
for _ in range(2):
self.assertEqual(repr(logit), 'LogisticRegressionLearner()')
def test_deepgetattr(self):
class a: # pylint: disable=invalid-name
l = []
self.assertTrue(deepgetattr(a, 'l.__len__.__call__'), a.l.__len__.__call__)
self.assertTrue(deepgetattr(a, 'l.__nx__.__x__', 42), 42)
self.assertRaises(AttributeError, lambda: deepgetattr(a, 'l.__nx__.__x__'))
def test_nan_eq(self):
self.assertTrue(nan_eq(float("nan"), float("nan")))
self.assertTrue(nan_eq(1, 1.0))
self.assertFalse(nan_eq(float("nan"), 1))
self.assertFalse(nan_eq(1, float("nan")))
self.assertFalse(nan_eq(float("inf"), float("nan")))
self.assertFalse(nan_eq(float("nan"), float("inf")))
self.assertFalse(nan_eq(1, 2))
self.assertFalse(nan_eq(None, 2))
self.assertFalse(nan_eq(2, None))
def test_nan_hash_stand(self):
self.assertEqual(hash(nan_hash_stand(float("nan"))),
hash(nan_hash_stand(float("nan"))))
def test_vstack(self):
numpy = np.array([[1., 2.], [3., 4.]])
csr = sp.csr_matrix(numpy)
csc = sp.csc_matrix(numpy)
self.assertCorrectArrayType(
vstack([numpy, numpy]),
shape=(4, 2), sparsity="dense")
self.assertCorrectArrayType(
vstack([csr, numpy]),
shape=(4, 2), sparsity="sparse")
self.assertCorrectArrayType(
vstack([numpy, csc]),
shape=(4, 2), sparsity="sparse")
self.assertCorrectArrayType(
vstack([csc, csr]),
shape=(4, 2), sparsity="sparse")
def test_hstack(self):
numpy = np.array([[1., 2.], [3., 4.]])
csr = sp.csr_matrix(numpy)
csc = sp.csc_matrix(numpy)
self.assertCorrectArrayType(
hstack([numpy, numpy]),
shape=(2, 4), sparsity="dense")
self.assertCorrectArrayType(
hstack([csr, numpy]),
shape=(2, 4), sparsity="sparse")
self.assertCorrectArrayType(
hstack([numpy, csc]),
shape=(2, 4), sparsity="sparse")
self.assertCorrectArrayType(
hstack([csc, csr]),
shape=(2, 4), sparsity="sparse")
def assertCorrectArrayType(self, array, shape, sparsity):
self.assertEqual(array.shape, shape)
self.assertEqual(["dense", "sparse"][sp.issparse(array)], sparsity)
@unittest.skipUnless(os.environ.get('ORANGE_DEPRECATIONS_ERROR'),
'ORANGE_DEPRECATIONS_ERROR not set')
def test_raise_deprecations(self):
with self.assertRaises(OrangeDeprecationWarning):
warnings.warn('foo', OrangeDeprecationWarning)
def test_stats_sparse(self):
# pylint: disable=import-outside-toplevel
from Orange.data import Table
data = Table("iris")
sparse_x = sp.csr_matrix(data.X)
self.assertTrue(stats(data.X).all() == stats(sparse_x).all())
@dense_sparse
def test_array_equal(self, array):
a1 = array([[0., 2.], [3., np.nan]])
a2 = array([[0., 2.], [3., np.nan]])
self.assertTrue(array_equal(a1, a2))
a3 = np.array([[0., 2.], [3., np.nan]])
self.assertTrue(array_equal(a1, a3))
self.assertTrue(array_equal(a3, a1))
@dense_sparse
def test_array_not_equal(self, array):
a1 = array([[0., 2.], [3., np.nan]])
a2 = array([[0., 2.], [4., np.nan]])
self.assertFalse(array_equal(a1, a2))
a3 = array([[0., 2.], [3., np.nan], [4., 5.]])
self.assertFalse(array_equal(a1, a3))
def test_csc_array_equal(self):
a1 = sp.csc_matrix(([1, 4, 5], ([0, 0, 1], [0, 2, 2])), shape=(2, 3))
a2 = sp.csc_matrix(([5, 1, 4], ([1, 0, 0], [2, 0, 2])), shape=(2, 3))
with warnings.catch_warnings():
# this is just inefficiency in tests, not the tested code
warnings.filterwarnings("ignore", ".*", sp.SparseEfficiencyWarning)
a2[0, 1] = 0 # explicitly setting to 0
self.assertTrue(array_equal(a1, a2))
def test_csc_scr_equal(self):
a1 = sp.csc_matrix(([1, 4, 5], ([0, 0, 1], [0, 2, 2])), shape=(2, 3))
a2 = sp.csr_matrix(([5, 1, 4], ([1, 0, 0], [2, 0, 2])), shape=(2, 3))
self.assertTrue(array_equal(a1, a2))
a1 = sp.csc_matrix(([1, 4, 5], ([0, 0, 1], [0, 2, 2])), shape=(2, 3))
a2 = sp.csr_matrix(([1, 4, 5], ([0, 0, 1], [0, 2, 2])), shape=(2, 3))
self.assertTrue(array_equal(a1, a2))
def test_csc_unordered_array_equal(self):
a1 = sp.csc_matrix(([1, 4, 5], [0, 0, 1], [0, 1, 1, 3]), shape=(2, 3))
a2 = sp.csc_matrix(([1, 5, 4], [0, 1, 0], [0, 1, 1, 3]), shape=(2, 3))
self.assertTrue(array_equal(a1, a2))
def test_wrap_callback(self):
def func(i):
return i
f = wrap_callback(func, start=0, end=0.8)
self.assertEqual(f(0), 0)
self.assertEqual(round(f(0.1), 2), 0.08)
self.assertEqual(f(1), 0.8)
f = wrap_callback(func, start=0.1, end=0.8)
self.assertEqual(f(0), 0.1)
self.assertEqual(f(0.1), 0.17)
self.assertEqual(f(1), 0.8)
def test_registry(self):
# pylint: disable=invalid-name, unused-variable
class A(metaclass=Registry):
pass
class BBB(A):
pass
class CC(A):
pass
class DDDD(BBB):
pass
self.assertEqual(set(A), {"BBB", "CC", "DDDD"})
self.assertEqual(str(A), "A({BBB, CC, DDDD})")
class D(metaclass=Registry):
pass
self.assertEqual(set(A), {"BBB", "CC", "DDDD"})
self.assertEqual(str(A), "A({BBB, CC, DDDD})")
self.assertEqual(set(D), set())
self.assertEqual(str(D), "D({})")
class E(D):
pass
self.assertEqual(set(A), {"BBB", "CC", "DDDD"})
self.assertEqual(str(A), "A({BBB, CC, DDDD})")
self.assertEqual(set(D), set("E"))
self.assertEqual(str(D), "D({E})")
def test_namegen(self):
self.assertEqual([name for name, _ in zip(namegen(), range(3))],
["_0", "_1", "_2"])
self.assertEqual([name for name, _ in zip(namegen("foo "), range(3))],
["foo 0", "foo 1", "foo 2"])
self.assertEqual([name for name, _ in zip(namegen("foo ", 2, spec_count=count), range(3))],
["foo 2", "foo 3", "foo 4"])
class TestAllot(unittest.TestCase):
# names of functions within tests don't matter, pylint: disable=invalid-name
def setUp(self):
# patch the object to user perf_counter, which will include the time
# when tests `sleep`
patcher = patch.object(allot, "_allot__timer", new=time.perf_counter)
patcher.start()
self.addCleanup(patcher.stop)
def test_duration(self):
@allot
def f(x, y):
self.assertEqual(x, 5)
self.assertEqual(y, 6)
time.sleep(0.2)
f(5, y=6)
self.assertGreaterEqual(f.last_call_duration, 0.2)
class A:
def __init__(self):
self.x = self.y = 0
@allot
def f(self, x, y):
self.x = x
self.y = y
time.sleep(0.2)
a = A()
a.f(5, y=6)
self.assertEqual(a.x, 5)
self.assertEqual(a.y, 6)
self.assertGreaterEqual(f.last_call_duration, 0.2)
def test_skipping(self):
uf = Mock()
@allot(0.5)
def f(x, y):
uf()
self.assertEqual(x, 5)
self.assertEqual(y, 6)
time.sleep(0.2)
f(5, y=6)
uf.assert_called_once()
uf.reset_mock()
self.assertGreaterEqual(f.last_call_duration, 0.2)
f(5, y=6)
uf.assert_not_called()
self.assertGreaterEqual(f.last_call_duration, 0.2)
time.sleep(0.35)
f(5, y=6)
uf.assert_called_once()
self.assertGreaterEqual(f.last_call_duration, 0.2)
class A:
def __init__(self):
self.x = self.y = 0
@allot(0.5)
def f(self, x, y):
self.x = x
self.y = y
time.sleep(0.2)
a = A()
a2 = A()
a.f(5, y=6)
self.assertEqual(a.x, 5)
self.assertEqual(a.y, 6)
self.assertGreaterEqual(f.last_call_duration, 0.2)
a.f(7, y=8)
self.assertEqual(a.x, 5) # no call, `a` is unchanged
self.assertGreaterEqual(f.last_call_duration, 0.2)
time.sleep(0.35)
a.f(9, y=10)
a2.f(11, y=12)
self.assertEqual(a.x, 9)
self.assertGreaterEqual(f.last_call_duration, 0.2)
# a2.f is not being skipped because of a.f - bound methods for different
# instance are separate
self.assertEqual(a2.x, 11)
# forced calls work
a.f.call(11, 12)
self.assertEqual(a.x, 11)
# forced calls block later non-forced calls
a = A()
a.f.call(13, y=14)
self.assertEqual(a.x, 13)
a.f(15, y=16)
self.assertEqual(a.x, 13)
def test_overflow(self):
uf = Mock()
of = Mock(return_value=13)
@allot(0.1, overflow=of)
def f(*_, **__):
uf()
time.sleep(0.1)
return 42
self.assertEqual(f(5, y=6), 42)
uf.assert_called()
uf.reset_mock()
of.assert_not_called()
self.assertEqual(f(7, y=8), 13)
uf.assert_not_called()
of.assert_called_with(7, y=8)
def test_assert_no_result(self):
# pylint: disable=function-redefined
@allot(0.1)
def f():
return 42
self.assertRaises(AssertionError, f)
@allot(0.05, overflow=lambda x: 3 * x)
def f(x):
time.sleep(0.6)
return 2 * x
self.assertEqual(f(3), 6)
self.assertEqual(f(3), 9)
@allot
def f():
return 42
self.assertEqual(f(), 42)
def test_assertion(self):
self.assertRaises(AssertionError, allot, "foo")
self.assertRaises(AssertionError, allot, 0.0)
self.assertRaises(AssertionError, allot, -1.0)
def test_getter(self):
class A:
@allot
def f(self):
pass
# getter for class must not do anything with the method
self.assertIs(A.f, A.__dict__["f"])
if __name__ == "__main__":
unittest.main()
|
