Python pandas.util.testing.use_numexpr() Examples
The following are 15
code examples of pandas.util.testing.use_numexpr().
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Example #1
| Source File: test_expressions.py From recruit with Apache License 2.0 | 5 votes |
|
def test_boolean_ops(self):
def testit():
for f, f2 in [(self.frame, self.frame2),
(self.mixed, self.mixed2)]:
f11 = f
f12 = f + 1
f21 = f2
f22 = f2 + 1
for op, op_str in [('gt', '>'), ('lt', '<'), ('ge', '>='),
('le', '<='), ('eq', '=='), ('ne', '!=')]:
op = getattr(operator, op)
result = expr._can_use_numexpr(op, op_str, f11, f12,
'evaluate')
assert result != f11._is_mixed_type
result = expr.evaluate(op, op_str, f11, f12,
use_numexpr=True)
expected = expr.evaluate(op, op_str, f11, f12,
use_numexpr=False)
if isinstance(result, DataFrame):
tm.assert_frame_equal(result, expected)
else:
tm.assert_numpy_array_equal(result, expected.values)
result = expr._can_use_numexpr(op, op_str, f21, f22,
'evaluate')
assert not result
expr.set_use_numexpr(False)
testit()
expr.set_use_numexpr(True)
expr.set_numexpr_threads(1)
testit()
expr.set_numexpr_threads()
testit()
Example #2
| Source File: test_expressions.py From vnpy_crypto with MIT License | 5 votes |
|
def test_boolean_ops(self):
def testit():
for f, f2 in [(self.frame, self.frame2),
(self.mixed, self.mixed2)]:
f11 = f
f12 = f + 1
f21 = f2
f22 = f2 + 1
for op, op_str in [('gt', '>'), ('lt', '<'), ('ge', '>='),
('le', '<='), ('eq', '=='), ('ne', '!=')]:
op = getattr(operator, op)
result = expr._can_use_numexpr(op, op_str, f11, f12,
'evaluate')
assert result != f11._is_mixed_type
result = expr.evaluate(op, op_str, f11, f12,
use_numexpr=True)
expected = expr.evaluate(op, op_str, f11, f12,
use_numexpr=False)
if isinstance(result, DataFrame):
tm.assert_frame_equal(result, expected)
else:
tm.assert_numpy_array_equal(result, expected.values)
result = expr._can_use_numexpr(op, op_str, f21, f22,
'evaluate')
assert not result
expr.set_use_numexpr(False)
testit()
expr.set_use_numexpr(True)
expr.set_numexpr_threads(1)
testit()
expr.set_numexpr_threads()
testit()
Example #3
| Source File: test_expressions.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
|
def test_boolean_ops(self):
def testit():
for f, f2 in [(self.frame, self.frame2),
(self.mixed, self.mixed2)]:
f11 = f
f12 = f + 1
f21 = f2
f22 = f2 + 1
for op, op_str in [('gt', '>'), ('lt', '<'), ('ge', '>='),
('le', '<='), ('eq', '=='), ('ne', '!=')]:
op = getattr(operator, op)
result = expr._can_use_numexpr(op, op_str, f11, f12,
'evaluate')
assert result != f11._is_mixed_type
result = expr.evaluate(op, op_str, f11, f12,
use_numexpr=True)
expected = expr.evaluate(op, op_str, f11, f12,
use_numexpr=False)
if isinstance(result, DataFrame):
tm.assert_frame_equal(result, expected)
else:
tm.assert_numpy_array_equal(result, expected.values)
result = expr._can_use_numexpr(op, op_str, f21, f22,
'evaluate')
assert not result
expr.set_use_numexpr(False)
testit()
expr.set_use_numexpr(True)
expr.set_numexpr_threads(1)
testit()
expr.set_numexpr_threads()
testit()
Example #4
| Source File: test_expressions.py From elasticintel with GNU General Public License v3.0 | 5 votes |
|
def test_boolean_ops(self):
def testit():
for f, f2 in [(self.frame, self.frame2),
(self.mixed, self.mixed2)]:
f11 = f
f12 = f + 1
f21 = f2
f22 = f2 + 1
for op, op_str in [('gt', '>'), ('lt', '<'), ('ge', '>='),
('le', '<='), ('eq', '=='), ('ne', '!=')]:
op = getattr(operator, op)
result = expr._can_use_numexpr(op, op_str, f11, f12,
'evaluate')
assert result != f11._is_mixed_type
result = expr.evaluate(op, op_str, f11, f12,
use_numexpr=True)
expected = expr.evaluate(op, op_str, f11, f12,
use_numexpr=False)
if isinstance(result, DataFrame):
tm.assert_frame_equal(result, expected)
else:
tm.assert_numpy_array_equal(result, expected.values)
result = expr._can_use_numexpr(op, op_str, f21, f22,
'evaluate')
assert not result
expr.set_use_numexpr(False)
testit()
expr.set_use_numexpr(True)
expr.set_numexpr_threads(1)
testit()
expr.set_numexpr_threads()
testit()
Example #5
| Source File: test_expressions.py From twitter-stock-recommendation with MIT License | 5 votes |
|
def test_boolean_ops(self):
def testit():
for f, f2 in [(self.frame, self.frame2),
(self.mixed, self.mixed2)]:
f11 = f
f12 = f + 1
f21 = f2
f22 = f2 + 1
for op, op_str in [('gt', '>'), ('lt', '<'), ('ge', '>='),
('le', '<='), ('eq', '=='), ('ne', '!=')]:
op = getattr(operator, op)
result = expr._can_use_numexpr(op, op_str, f11, f12,
'evaluate')
assert result != f11._is_mixed_type
result = expr.evaluate(op, op_str, f11, f12,
use_numexpr=True)
expected = expr.evaluate(op, op_str, f11, f12,
use_numexpr=False)
if isinstance(result, DataFrame):
tm.assert_frame_equal(result, expected)
else:
tm.assert_numpy_array_equal(result, expected.values)
result = expr._can_use_numexpr(op, op_str, f21, f22,
'evaluate')
assert not result
expr.set_use_numexpr(False)
testit()
expr.set_use_numexpr(True)
expr.set_numexpr_threads(1)
testit()
expr.set_numexpr_threads()
testit()
Example #6
| Source File: test_expressions.py From recruit with Apache License 2.0 | 4 votes |
|
def test_binary_ops(self):
def testit():
for f, f2 in [(self.frame, self.frame2),
(self.mixed, self.mixed2)]:
for op, op_str in [('add', '+'), ('sub', '-'), ('mul', '*'),
('div', '/'), ('pow', '**')]:
if op == 'pow':
continue
if op == 'div':
op = getattr(operator, 'truediv', None)
else:
op = getattr(operator, op, None)
if op is not None:
result = expr._can_use_numexpr(op, op_str, f, f,
'evaluate')
assert result != f._is_mixed_type
result = expr.evaluate(op, op_str, f, f,
use_numexpr=True)
expected = expr.evaluate(op, op_str, f, f,
use_numexpr=False)
if isinstance(result, DataFrame):
tm.assert_frame_equal(result, expected)
else:
tm.assert_numpy_array_equal(result,
expected.values)
result = expr._can_use_numexpr(op, op_str, f2, f2,
'evaluate')
assert not result
expr.set_use_numexpr(False)
testit()
expr.set_use_numexpr(True)
expr.set_numexpr_threads(1)
testit()
expr.set_numexpr_threads()
testit()
Example #7
| Source File: test_expressions.py From recruit with Apache License 2.0 | 4 votes |
|
def test_bool_ops_warn_on_arithmetic(self):
n = 10
df = DataFrame({'a': np.random.rand(n) > 0.5,
'b': np.random.rand(n) > 0.5})
names = 'add', 'mul', 'sub'
ops = '+', '*', '-'
subs = {'+': '|', '*': '&', '-': '^'}
sub_funcs = {'|': 'or_', '&': 'and_', '^': 'xor'}
for op, name in zip(ops, names):
f = getattr(operator, name)
fe = getattr(operator, sub_funcs[subs[op]])
# >= 1.13.0 these are now TypeErrors
if op == '-' and not _np_version_under1p13:
continue
with tm.use_numexpr(True, min_elements=5):
with tm.assert_produces_warning(check_stacklevel=False):
r = f(df, df)
e = fe(df, df)
tm.assert_frame_equal(r, e)
with tm.assert_produces_warning(check_stacklevel=False):
r = f(df.a, df.b)
e = fe(df.a, df.b)
tm.assert_series_equal(r, e)
with tm.assert_produces_warning(check_stacklevel=False):
r = f(df.a, True)
e = fe(df.a, True)
tm.assert_series_equal(r, e)
with tm.assert_produces_warning(check_stacklevel=False):
r = f(False, df.a)
e = fe(False, df.a)
tm.assert_series_equal(r, e)
with tm.assert_produces_warning(check_stacklevel=False):
r = f(False, df)
e = fe(False, df)
tm.assert_frame_equal(r, e)
with tm.assert_produces_warning(check_stacklevel=False):
r = f(df, True)
e = fe(df, True)
tm.assert_frame_equal(r, e)
Example #8
| Source File: test_expressions.py From vnpy_crypto with MIT License | 4 votes |
|
def test_binary_ops(self):
def testit():
for f, f2 in [(self.frame, self.frame2),
(self.mixed, self.mixed2)]:
for op, op_str in [('add', '+'), ('sub', '-'), ('mul', '*'),
('div', '/'), ('pow', '**')]:
# numpy >= 1.11 doesn't handle integers
# raised to integer powers
# https://github.com/pandas-dev/pandas/issues/15363
if op == 'pow' and not _np_version_under1p11:
continue
if op == 'div':
op = getattr(operator, 'truediv', None)
else:
op = getattr(operator, op, None)
if op is not None:
result = expr._can_use_numexpr(op, op_str, f, f,
'evaluate')
assert result != f._is_mixed_type
result = expr.evaluate(op, op_str, f, f,
use_numexpr=True)
expected = expr.evaluate(op, op_str, f, f,
use_numexpr=False)
if isinstance(result, DataFrame):
tm.assert_frame_equal(result, expected)
else:
tm.assert_numpy_array_equal(result,
expected.values)
result = expr._can_use_numexpr(op, op_str, f2, f2,
'evaluate')
assert not result
expr.set_use_numexpr(False)
testit()
expr.set_use_numexpr(True)
expr.set_numexpr_threads(1)
testit()
expr.set_numexpr_threads()
testit()
Example #9
| Source File: test_expressions.py From vnpy_crypto with MIT License | 4 votes |
|
def test_bool_ops_warn_on_arithmetic(self):
n = 10
df = DataFrame({'a': np.random.rand(n) > 0.5,
'b': np.random.rand(n) > 0.5})
names = 'add', 'mul', 'sub'
ops = '+', '*', '-'
subs = {'+': '|', '*': '&', '-': '^'}
sub_funcs = {'|': 'or_', '&': 'and_', '^': 'xor'}
for op, name in zip(ops, names):
f = getattr(operator, name)
fe = getattr(operator, sub_funcs[subs[op]])
# >= 1.13.0 these are now TypeErrors
if op == '-' and not _np_version_under1p13:
continue
with tm.use_numexpr(True, min_elements=5):
with tm.assert_produces_warning(check_stacklevel=False):
r = f(df, df)
e = fe(df, df)
tm.assert_frame_equal(r, e)
with tm.assert_produces_warning(check_stacklevel=False):
r = f(df.a, df.b)
e = fe(df.a, df.b)
tm.assert_series_equal(r, e)
with tm.assert_produces_warning(check_stacklevel=False):
r = f(df.a, True)
e = fe(df.a, True)
tm.assert_series_equal(r, e)
with tm.assert_produces_warning(check_stacklevel=False):
r = f(False, df.a)
e = fe(False, df.a)
tm.assert_series_equal(r, e)
with tm.assert_produces_warning(check_stacklevel=False):
r = f(False, df)
e = fe(False, df)
tm.assert_frame_equal(r, e)
with tm.assert_produces_warning(check_stacklevel=False):
r = f(df, True)
e = fe(df, True)
tm.assert_frame_equal(r, e)
Example #10
| Source File: test_expressions.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 4 votes |
|
def test_binary_ops(self):
def testit():
for f, f2 in [(self.frame, self.frame2),
(self.mixed, self.mixed2)]:
for op, op_str in [('add', '+'), ('sub', '-'), ('mul', '*'),
('div', '/'), ('pow', '**')]:
if op == 'pow':
continue
if op == 'div':
op = getattr(operator, 'truediv', None)
else:
op = getattr(operator, op, None)
if op is not None:
result = expr._can_use_numexpr(op, op_str, f, f,
'evaluate')
assert result != f._is_mixed_type
result = expr.evaluate(op, op_str, f, f,
use_numexpr=True)
expected = expr.evaluate(op, op_str, f, f,
use_numexpr=False)
if isinstance(result, DataFrame):
tm.assert_frame_equal(result, expected)
else:
tm.assert_numpy_array_equal(result,
expected.values)
result = expr._can_use_numexpr(op, op_str, f2, f2,
'evaluate')
assert not result
expr.set_use_numexpr(False)
testit()
expr.set_use_numexpr(True)
expr.set_numexpr_threads(1)
testit()
expr.set_numexpr_threads()
testit()
Example #11
| Source File: test_expressions.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 4 votes |
|
def test_bool_ops_warn_on_arithmetic(self):
n = 10
df = DataFrame({'a': np.random.rand(n) > 0.5,
'b': np.random.rand(n) > 0.5})
names = 'add', 'mul', 'sub'
ops = '+', '*', '-'
subs = {'+': '|', '*': '&', '-': '^'}
sub_funcs = {'|': 'or_', '&': 'and_', '^': 'xor'}
for op, name in zip(ops, names):
f = getattr(operator, name)
fe = getattr(operator, sub_funcs[subs[op]])
# >= 1.13.0 these are now TypeErrors
if op == '-' and not _np_version_under1p13:
continue
with tm.use_numexpr(True, min_elements=5):
with tm.assert_produces_warning(check_stacklevel=False):
r = f(df, df)
e = fe(df, df)
tm.assert_frame_equal(r, e)
with tm.assert_produces_warning(check_stacklevel=False):
r = f(df.a, df.b)
e = fe(df.a, df.b)
tm.assert_series_equal(r, e)
with tm.assert_produces_warning(check_stacklevel=False):
r = f(df.a, True)
e = fe(df.a, True)
tm.assert_series_equal(r, e)
with tm.assert_produces_warning(check_stacklevel=False):
r = f(False, df.a)
e = fe(False, df.a)
tm.assert_series_equal(r, e)
with tm.assert_produces_warning(check_stacklevel=False):
r = f(False, df)
e = fe(False, df)
tm.assert_frame_equal(r, e)
with tm.assert_produces_warning(check_stacklevel=False):
r = f(df, True)
e = fe(df, True)
tm.assert_frame_equal(r, e)
Example #12
| Source File: test_expressions.py From elasticintel with GNU General Public License v3.0 | 4 votes |
|
def test_binary_ops(self):
def testit():
for f, f2 in [(self.frame, self.frame2),
(self.mixed, self.mixed2)]:
for op, op_str in [('add', '+'), ('sub', '-'), ('mul', '*'),
('div', '/'), ('pow', '**')]:
# numpy >= 1.11 doesn't handle integers
# raised to integer powers
# https://github.com/pandas-dev/pandas/issues/15363
if op == 'pow' and not _np_version_under1p11:
continue
if op == 'div':
op = getattr(operator, 'truediv', None)
else:
op = getattr(operator, op, None)
if op is not None:
result = expr._can_use_numexpr(op, op_str, f, f,
'evaluate')
assert result != f._is_mixed_type
result = expr.evaluate(op, op_str, f, f,
use_numexpr=True)
expected = expr.evaluate(op, op_str, f, f,
use_numexpr=False)
if isinstance(result, DataFrame):
tm.assert_frame_equal(result, expected)
else:
tm.assert_numpy_array_equal(result,
expected.values)
result = expr._can_use_numexpr(op, op_str, f2, f2,
'evaluate')
assert not result
expr.set_use_numexpr(False)
testit()
expr.set_use_numexpr(True)
expr.set_numexpr_threads(1)
testit()
expr.set_numexpr_threads()
testit()
Example #13
| Source File: test_expressions.py From elasticintel with GNU General Public License v3.0 | 4 votes |
|
def test_bool_ops_warn_on_arithmetic(self):
n = 10
df = DataFrame({'a': np.random.rand(n) > 0.5,
'b': np.random.rand(n) > 0.5})
names = 'add', 'mul', 'sub'
ops = '+', '*', '-'
subs = {'+': '|', '*': '&', '-': '^'}
sub_funcs = {'|': 'or_', '&': 'and_', '^': 'xor'}
for op, name in zip(ops, names):
f = getattr(operator, name)
fe = getattr(operator, sub_funcs[subs[op]])
# >= 1.13.0 these are now TypeErrors
if op == '-' and not _np_version_under1p13:
continue
with tm.use_numexpr(True, min_elements=5):
with tm.assert_produces_warning(check_stacklevel=False):
r = f(df, df)
e = fe(df, df)
tm.assert_frame_equal(r, e)
with tm.assert_produces_warning(check_stacklevel=False):
r = f(df.a, df.b)
e = fe(df.a, df.b)
tm.assert_series_equal(r, e)
with tm.assert_produces_warning(check_stacklevel=False):
r = f(df.a, True)
e = fe(df.a, True)
tm.assert_series_equal(r, e)
with tm.assert_produces_warning(check_stacklevel=False):
r = f(False, df.a)
e = fe(False, df.a)
tm.assert_series_equal(r, e)
with tm.assert_produces_warning(check_stacklevel=False):
r = f(False, df)
e = fe(False, df)
tm.assert_frame_equal(r, e)
with tm.assert_produces_warning(check_stacklevel=False):
r = f(df, True)
e = fe(df, True)
tm.assert_frame_equal(r, e)
Example #14
| Source File: test_expressions.py From twitter-stock-recommendation with MIT License | 4 votes |
|
def test_binary_ops(self):
def testit():
for f, f2 in [(self.frame, self.frame2),
(self.mixed, self.mixed2)]:
for op, op_str in [('add', '+'), ('sub', '-'), ('mul', '*'),
('div', '/'), ('pow', '**')]:
# numpy >= 1.11 doesn't handle integers
# raised to integer powers
# https://github.com/pandas-dev/pandas/issues/15363
if op == 'pow' and not _np_version_under1p11:
continue
if op == 'div':
op = getattr(operator, 'truediv', None)
else:
op = getattr(operator, op, None)
if op is not None:
result = expr._can_use_numexpr(op, op_str, f, f,
'evaluate')
assert result != f._is_mixed_type
result = expr.evaluate(op, op_str, f, f,
use_numexpr=True)
expected = expr.evaluate(op, op_str, f, f,
use_numexpr=False)
if isinstance(result, DataFrame):
tm.assert_frame_equal(result, expected)
else:
tm.assert_numpy_array_equal(result,
expected.values)
result = expr._can_use_numexpr(op, op_str, f2, f2,
'evaluate')
assert not result
expr.set_use_numexpr(False)
testit()
expr.set_use_numexpr(True)
expr.set_numexpr_threads(1)
testit()
expr.set_numexpr_threads()
testit()
Example #15
| Source File: test_expressions.py From twitter-stock-recommendation with MIT License | 4 votes |
|
def test_bool_ops_warn_on_arithmetic(self):
n = 10
df = DataFrame({'a': np.random.rand(n) > 0.5,
'b': np.random.rand(n) > 0.5})
names = 'add', 'mul', 'sub'
ops = '+', '*', '-'
subs = {'+': '|', '*': '&', '-': '^'}
sub_funcs = {'|': 'or_', '&': 'and_', '^': 'xor'}
for op, name in zip(ops, names):
f = getattr(operator, name)
fe = getattr(operator, sub_funcs[subs[op]])
# >= 1.13.0 these are now TypeErrors
if op == '-' and not _np_version_under1p13:
continue
with tm.use_numexpr(True, min_elements=5):
with tm.assert_produces_warning(check_stacklevel=False):
r = f(df, df)
e = fe(df, df)
tm.assert_frame_equal(r, e)
with tm.assert_produces_warning(check_stacklevel=False):
r = f(df.a, df.b)
e = fe(df.a, df.b)
tm.assert_series_equal(r, e)
with tm.assert_produces_warning(check_stacklevel=False):
r = f(df.a, True)
e = fe(df.a, True)
tm.assert_series_equal(r, e)
with tm.assert_produces_warning(check_stacklevel=False):
r = f(False, df.a)
e = fe(False, df.a)
tm.assert_series_equal(r, e)
with tm.assert_produces_warning(check_stacklevel=False):
r = f(False, df)
e = fe(False, df)
tm.assert_frame_equal(r, e)
with tm.assert_produces_warning(check_stacklevel=False):
r = f(df, True)
e = fe(df, True)
tm.assert_frame_equal(r, e)
