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Refactor Python tests. (#3897)

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* Deprecate nose tests.
* Format python tests.
This commit is contained in:
Jiaming Yuan
2018-11-15 13:56:33 +13:00
committed by GitHub
parent c76d993681
commit 2ea0f887c1
23 changed files with 302 additions and 225 deletions
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36
tests/python/test_basic.py
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@@ -21,6 +21,8 @@ def captured_output():
"""
Reassign stdout temporarily in order to test printed statements
Taken from: https://stackoverflow.com/questions/4219717/how-to-assert-output-with-nosetest-unittest-in-python
Also works for pytest.
"""
new_out, new_err = StringIO(), StringIO()
old_out, old_err = sys.stdout, sys.stderr
@@ -36,7 +38,8 @@ class TestBasic(unittest.TestCase):
def test_basic(self):
dtrain = xgb.DMatrix(dpath + 'agaricus.txt.train')
dtest = xgb.DMatrix(dpath + 'agaricus.txt.test')
param = {'max_depth': 2, 'eta': 1, 'silent': 1, 'objective': 'binary:logistic'}
param = {'max_depth': 2, 'eta': 1, 'silent': 1,
'objective': 'binary:logistic'}
# specify validations set to watch performance
watchlist = [(dtest, 'eval'), (dtrain, 'train')]
num_round = 2
@@ -44,7 +47,8 @@ class TestBasic(unittest.TestCase):
# this is prediction
preds = bst.predict(dtest)
labels = dtest.get_label()
err = sum(1 for i in range(len(preds)) if int(preds[i] > 0.5) != labels[i]) / float(len(preds))
err = sum(1 for i in range(len(preds))
if int(preds[i] > 0.5) != labels[i]) / float(len(preds))
# error must be smaller than 10%
assert err < 0.1
@@ -62,7 +66,8 @@ class TestBasic(unittest.TestCase):
def test_record_results(self):
dtrain = xgb.DMatrix(dpath + 'agaricus.txt.train')
dtest = xgb.DMatrix(dpath + 'agaricus.txt.test')
param = {'max_depth': 2, 'eta': 1, 'silent': 1, 'objective': 'binary:logistic'}
param = {'max_depth': 2, 'eta': 1, 'silent': 1,
'objective': 'binary:logistic'}
# specify validations set to watch performance
watchlist = [(dtest, 'eval'), (dtrain, 'train')]
num_round = 2
@@ -86,7 +91,8 @@ class TestBasic(unittest.TestCase):
# this is prediction
preds = bst.predict(dtest)
labels = dtest.get_label()
err = sum(1 for i in range(len(preds)) if preds[i] != labels[i]) / float(len(preds))
err = sum(1 for i in range(len(preds))
if preds[i] != labels[i]) / float(len(preds))
# error must be smaller than 10%
assert err < 0.1
@@ -248,7 +254,8 @@ class TestBasic(unittest.TestCase):
def test_cv(self):
dm = xgb.DMatrix(dpath + 'agaricus.txt.train')
params = {'max_depth': 2, 'eta': 1, 'silent': 1, 'objective': 'binary:logistic'}
params = {'max_depth': 2, 'eta': 1, 'silent': 1,
'objective': 'binary:logistic'}
# return np.ndarray
cv = xgb.cv(params, dm, num_boost_round=10, nfold=10, as_pandas=False)
@@ -257,16 +264,19 @@ class TestBasic(unittest.TestCase):
def test_cv_no_shuffle(self):
dm = xgb.DMatrix(dpath + 'agaricus.txt.train')
params = {'max_depth': 2, 'eta': 1, 'silent': 1, 'objective': 'binary:logistic'}
params = {'max_depth': 2, 'eta': 1, 'silent': 1,
'objective': 'binary:logistic'}
# return np.ndarray
cv = xgb.cv(params, dm, num_boost_round=10, shuffle=False, nfold=10, as_pandas=False)
cv = xgb.cv(params, dm, num_boost_round=10, shuffle=False, nfold=10,
as_pandas=False)
assert isinstance(cv, dict)
assert len(cv) == (4)
def test_cv_explicit_fold_indices(self):
dm = xgb.DMatrix(dpath + 'agaricus.txt.train')
params = {'max_depth': 2, 'eta': 1, 'silent': 1, 'objective': 'binary:logistic'}
params = {'max_depth': 2, 'eta': 1, 'silent': 1, 'objective':
'binary:logistic'}
folds = [
# Train Test
([1, 3], [5, 8]),
@@ -274,12 +284,14 @@ class TestBasic(unittest.TestCase):
]
# return np.ndarray
cv = xgb.cv(params, dm, num_boost_round=10, folds=folds, as_pandas=False)
cv = xgb.cv(params, dm, num_boost_round=10, folds=folds,
as_pandas=False)
assert isinstance(cv, dict)
assert len(cv) == (4)
def test_cv_explicit_fold_indices_labels(self):
params = {'max_depth': 2, 'eta': 1, 'silent': 1, 'objective': 'reg:linear'}
params = {'max_depth': 2, 'eta': 1, 'silent': 1, 'objective':
'reg:linear'}
N = 100
F = 3
dm = xgb.DMatrix(data=np.random.randn(N, F), label=np.arange(N))
@@ -300,7 +312,9 @@ class TestBasic(unittest.TestCase):
as_pandas=False
)
output = out.getvalue().strip()
assert output == '[array([5., 8.], dtype=float32), array([23., 43., 11.], dtype=float32)]'
solution = ('[array([5., 8.], dtype=float32), array([23., 43., 11.],' +
' dtype=float32)]')
assert output == solution
def test_get_info(self):
dtrain = xgb.DMatrix(dpath + 'agaricus.txt.train')