The following are code examples for showing how to use . They are extracted from open source Python projects. You can vote up the examples you like or vote down the exmaples you don’t like. You can also save this page to your account.
Example 1
def _is_integer(x):
"""Determine whether some object ``x`` is an
integer type (int, long, etc). This is part of the
``fixes`` module, since Python 3 removes the long
datatype, we have to check the version major.
Parameters
----------
x : object
The item to assess whether is an integer.
Returns
-------
bool
True if ``x`` is an integer type
"""
return (not isinstance(x, (bool, np.bool))) and \
isinstance(x, (numbers.Integral, int, np.int, np.long, long)) # no long type in python 3 Example 2
def test_object_array_self_reference(self):
# Object arrays with references to themselves can cause problems
a = np.array(0, dtype=object)
a[()] = a
assert_raises(TypeError, int, a)
assert_raises(TypeError, long, a)
assert_raises(TypeError, float, a)
assert_raises(TypeError, oct, a)
assert_raises(TypeError, hex, a)
# Test the same for a circular reference.
b = np.array(a, dtype=object)
a[()] = b
assert_raises(TypeError, int, a)
# Numpy has no tp_traverse currently, so circular references
# cannot be detected. So resolve it:
a[()] = 0
# This was causing a to become like the above
a = np.array(0, dtype=object)
a[...] += 1
assert_equal(a, 1) Example 3
def test_attribute_wrapper():
def attribute_value_test(attribute_value):
node = make_node('Abs', ['X'], [], name='test_node', test_attribute=attribute_value)
model = make_model(make_graph([node], 'test_graph', [
make_tensor_value_info('X', onnx.TensorProto.FLOAT, [1, 2]),
], []), producer_name='ngraph')
wrapped_attribute = ModelWrapper(model).graph.node[0].get_attribute('test_attribute')
return wrapped_attribute.get_value()
tensor = make_tensor('test_tensor', onnx.TensorProto.FLOAT, [1], [1])
assert attribute_value_test(1) == 1
assert type(attribute_value_test(1)) == np.long
assert attribute_value_test(1.0) == 1.0
assert type(attribute_value_test(1.0)) == np.float
assert attribute_value_test('test') == 'test'
assert attribute_value_test(tensor)._proto == tensor
assert attribute_value_test([1, 2, 3]) == [1, 2, 3]
assert attribute_value_test([1.0, 2.0, 3.0]) == [1.0, 2.0, 3.0]
assert attribute_value_test(['test1', 'test2']) == ['test1', 'test2']
assert attribute_value_test([tensor, tensor])[1]._proto == tensor Example 4
def test_object_array_self_reference(self):
# Object arrays with references to themselves can cause problems
a = np.array(0, dtype=object)
a[()] = a
assert_raises(TypeError, int, a)
assert_raises(TypeError, long, a)
assert_raises(TypeError, float, a)
assert_raises(TypeError, oct, a)
assert_raises(TypeError, hex, a)
# Test the same for a circular reference.
b = np.array(a, dtype=object)
a[()] = b
assert_raises(TypeError, int, a)
# Numpy has no tp_traverse currently, so circular references
# cannot be detected. So resolve it:
a[()] = 0
# This was causing a to become like the above
a = np.array(0, dtype=object)
a[...] += 1
assert_equal(a, 1) Example 5
def test_object_array_self_reference(self):
# Object arrays with references to themselves can cause problems
a = np.array(0, dtype=object)
a[()] = a
assert_raises(TypeError, int, a)
assert_raises(TypeError, long, a)
assert_raises(TypeError, float, a)
assert_raises(TypeError, oct, a)
assert_raises(TypeError, hex, a)
# Test the same for a circular reference.
b = np.array(a, dtype=object)
a[()] = b
assert_raises(TypeError, int, a)
# Numpy has no tp_traverse currently, so circular references
# cannot be detected. So resolve it:
a[()] = 0
# This was causing a to become like the above
a = np.array(0, dtype=object)
a[...] += 1
assert_equal(a, 1) Example 6
def test_object_array_self_reference(self):
# Object arrays with references to themselves can cause problems
a = np.array(0, dtype=object)
a[()] = a
assert_raises(TypeError, int, a)
assert_raises(TypeError, long, a)
assert_raises(TypeError, float, a)
assert_raises(TypeError, oct, a)
assert_raises(TypeError, hex, a)
# Test the same for a circular reference.
b = np.array(a, dtype=object)
a[()] = b
assert_raises(TypeError, int, a)
# Numpy has no tp_traverse currently, so circular references
# cannot be detected. So resolve it:
a[()] = 0
# This was causing a to become like the above
a = np.array(0, dtype=object)
a[...] += 1
assert_equal(a, 1) Example 7
def test_respect_dtype_singleton(self):
# See gh-7203
for dt in self.itype:
lbnd = 0 if dt is np.bool_ else np.iinfo(dt).min
ubnd = 2 if dt is np.bool_ else np.iinfo(dt).max + 1
sample = self.rfunc(lbnd, ubnd, dtype=dt)
self.assertEqual(sample.dtype, np.dtype(dt))
for dt in (np.bool, np.int, np.long):
lbnd = 0 if dt is np.bool else np.iinfo(dt).min
ubnd = 2 if dt is np.bool else np.iinfo(dt).max + 1
# gh-7284: Ensure that we get Python data types
sample = self.rfunc(lbnd, ubnd, dtype=dt)
self.assertFalse(hasattr(sample, 'dtype'))
self.assertEqual(type(sample), dt) Example 8
def test_object_array_self_reference(self):
# Object arrays with references to themselves can cause problems
a = np.array(0, dtype=object)
a[()] = a
assert_raises(TypeError, int, a)
assert_raises(TypeError, long, a)
assert_raises(TypeError, float, a)
assert_raises(TypeError, oct, a)
assert_raises(TypeError, hex, a)
# Test the same for a circular reference.
b = np.array(a, dtype=object)
a[()] = b
assert_raises(TypeError, int, a)
# Numpy has no tp_traverse currently, so circular references
# cannot be detected. So resolve it:
a[()] = 0
# This was causing a to become like the above
a = np.array(0, dtype=object)
a[...] += 1
assert_equal(a, 1) Example 9
def test_object_array_self_reference(self):
# Object arrays with references to themselves can cause problems
a = np.array(0, dtype=object)
a[()] = a
assert_raises(TypeError, int, a)
assert_raises(TypeError, long, a)
assert_raises(TypeError, float, a)
assert_raises(TypeError, oct, a)
assert_raises(TypeError, hex, a)
# Test the same for a circular reference.
b = np.array(a, dtype=object)
a[()] = b
assert_raises(TypeError, int, a)
# NumPy has no tp_traverse currently, so circular references
# cannot be detected. So resolve it:
a[()] = 0
# This was causing a to become like the above
a = np.array(0, dtype=object)
a[...] += 1
assert_equal(a, 1) Example 10
def test_object_array_self_reference(self):
# Object arrays with references to themselves can cause problems
a = np.array(0, dtype=object)
a[()] = a
assert_raises(TypeError, int, a)
assert_raises(TypeError, long, a)
assert_raises(TypeError, float, a)
assert_raises(TypeError, oct, a)
assert_raises(TypeError, hex, a)
# Test the same for a circular reference.
b = np.array(a, dtype=object)
a[()] = b
assert_raises(TypeError, int, a)
# Numpy has no tp_traverse currently, so circular references
# cannot be detected. So resolve it:
a[()] = 0
# This was causing a to become like the above
a = np.array(0, dtype=object)
a[...] += 1
assert_equal(a, 1) Example 11
def _extract_field_names(self, event):
# extract field names from sids (price, volume etc), make sure
# every sid has the same fields.
sid_keys = []
for sid in itervalues(event.data):
keys = set([name for name, value in sid.items()
if isinstance(value,
(int,
float,
numpy.integer,
numpy.float,
numpy.long))
])
sid_keys.append(keys)
# with CUSTOM data events, there may be different fields
# per sid. So the allowable keys are the union of all events.
union = set.union(*sid_keys)
unwanted_fields = {
'portfolio',
'sid',
'dt',
'type',
'source_id',
'_initial_len',
}
return union - unwanted_fields Example 12
def fit(self, X):
_X = self.__aggregate_dataset(X)
self.polynomial = np.polyfit(_X['expenses'].astype(np.long),
_X['distance_traveled'].astype(np.long),
3)
self._polynomial_fn = np.poly1d(self.polynomial)
return self Example 13
def test_is_numeric():
assert is_numeric(1)
assert is_numeric(1.)
assert is_numeric(np.long(1))
assert is_numeric(np.int(1.0))
assert is_numeric(np.float(1))
assert is_numeric(1e-12)
assert not is_numeric('a')
assert not is_numeric(True) Example 14
def score(self, X, y=None):
"""Returns the score on the given data, if the estimator has been refit.
This uses the score defined by ``scoring`` where provided, and the
``best_estimator_.score`` method otherwise.
Parameters
----------
X : array-like or pandas DataFrame, shape = [n_samples, n_features]
Input data, where n_samples is the number of samples and
n_features is the number of features.
y : array-like, shape = [n_samples] or [n_samples, n_output], optional
Target relative to X for classification or regression;
None for unsupervised learning.
Returns
-------
score : float
Notes
-----
* The long-standing behavior of this method changed in version 0.16.
* It no longer uses the metric provided by ``estimator.score`` if the
``scoring`` parameter was set when fitting.
"""
X = _validate_X(X)
y = _validate_y(y)
if not hasattr(self, 'scorer_') or self.scorer_ is None:
raise ValueError("No score function explicitly defined, "
"and the estimator doesn't provide one %s"
% self.best_estimator_)
# we've already fit, and we have a scorer
if self.scoring is not None and hasattr(self.best_estimator_, 'score'):
warnings.warn("The long-standing behavior to use the estimator's "
"score function in {0}.score has changed. The "
"scoring parameter is now used."
"".format(self.__class__.__name__),
UserWarning)
return self.scorer_(self.best_estimator_, X, y) Example 15
def is_integer(x):
"""Determine whether some object ``x`` is an
integer type (int, long, etc).
Parameters
----------
x : object
The item to assess
Returns
-------
bool
True if ``x`` is an integer type
"""
try:
python_major_version = sys.version_info.major
assert(python_major_version == 2 or python_major_version == 3)
if python_major_version == 2:
return (not isinstance(x, (bool, np.bool))) and \
isinstance(x, (numbers.Integral, int, long, np.int, np.long))
elif python_major_version == 3:
return (not isinstance(x, (bool, np.bool))) and \
isinstance(x, (numbers.Integral, int, np.int, np.long))
except AssertionError:
_, _, tb = sys.exc_info()
traceback.print_tb(tb) # Fixed format
tb_info = traceback.extract_tb(tb)
filename, line, func, text = tb_info[-1]
print('An error occurred on line {} in statement {}'.format(line, text))
exit(1)
return _is_integer(x) Example 16
def __init__(self, weights=None, size_average=None):
super(ClassNLLCriterion, self).__init__()
if size_average:
self.size_average = size_average
else:
self.size_average = True
if weights:
# assert(weights:dim() == 1, "weights input should be 1-D Tensor")
self.weights = weights
self.output_tensor = np.zeros(1)
self.total_weight_tensor = np.ones(1)
self.target = np.zeros(1) # , dtype=np.long) Example 17
def test_signed_integer_division_overflow(self):
# Ticket #1317.
def test_type(t):
min = np.array([np.iinfo(t).min])
min //= -1
with np.errstate(divide="ignore"):
for t in (np.int8, np.int16, np.int32, np.int64, np.int, np.long):
test_type(t) Example 18
def test_array_side_effect(self):
# The second use of itemsize was throwing an exception because in
# ctors.c, discover_itemsize was calling PyObject_Length without
# checking the return code. This failed to get the length of the
# number 2, and the exception hung around until something checked
# PyErr_Occurred() and returned an error.
assert_equal(np.dtype('S10').itemsize, 10)
np.array([['abc', 2], ['long ', '0123456789']], dtype=np.string_)
assert_equal(np.dtype('S10').itemsize, 10) Example 19
def test_sequence_long(self):
assert_equal(np.array([long(4), long(4)]).dtype, np.long)
assert_equal(np.array([long(4), 2**80]).dtype, np.object)
assert_equal(np.array([long(4), 2**80, long(4)]).dtype, np.object)
assert_equal(np.array([2**80, long(4)]).dtype, np.object) Example 20
def test_matrix_multiply(self):
self.compare_matrix_multiply_results(np.long)
self.compare_matrix_multiply_results(np.double) Example 21
def test_random_integers_max_int(self):
# Tests whether random_integers can generate the
# maximum allowed Python int that can be converted
# into a C long. Previous implementations of this
# method have thrown an OverflowError when attempting
# to generate this integer.
actual = np.random.random_integers(np.iinfo('l').max,
np.iinfo('l').max)
desired = np.iinfo('l').max
np.testing.assert_equal(actual, desired) Example 22
def test_signed_integer_division_overflow(self):
# Ticket #1317.
def test_type(t):
min = np.array([np.iinfo(t).min])
min //= -1
with np.errstate(divide="ignore"):
for t in (np.int8, np.int16, np.int32, np.int64, np.int, np.long):
test_type(t) Example 23
def test_array_side_effect(self):
# The second use of itemsize was throwing an exception because in
# ctors.c, discover_itemsize was calling PyObject_Length without
# checking the return code. This failed to get the length of the
# number 2, and the exception hung around until something checked
# PyErr_Occurred() and returned an error.
assert_equal(np.dtype('S10').itemsize, 10)
np.array([['abc', 2], ['long ', '0123456789']], dtype=np.string_)
assert_equal(np.dtype('S10').itemsize, 10) Example 24
def test_sequence_long(self):
assert_equal(np.array([long(4), long(4)]).dtype, np.long)
assert_equal(np.array([long(4), 2**80]).dtype, np.object)
assert_equal(np.array([long(4), 2**80, long(4)]).dtype, np.object)
assert_equal(np.array([2**80, long(4)]).dtype, np.object) Example 25
def test_matrix_multiply(self):
self.compare_matrix_multiply_results(np.long)
self.compare_matrix_multiply_results(np.double) Example 26
def test_random_integers_max_int(self):
# Tests whether random_integers can generate the
# maximum allowed Python int that can be converted
# into a C long. Previous implementations of this
# method have thrown an OverflowError when attempting
# to generate this integer.
actual = np.random.random_integers(np.iinfo('l').max,
np.iinfo('l').max)
desired = np.iinfo('l').max
np.testing.assert_equal(actual, desired) Example 27
def get_landmarks(self,img,box=None,left=None,top=None,right=None,bottom=None): if box is not None: left,top,right,bottom = box left = np.long(left) top = np.long(top) right = np.long(right) bottom = np.long(bottom) bb = dlib.rectangle(left,top,right,bottom) landmarks = self.align_tool.findLandmarks(img,bb) npLandmarks = np.float32(landmarks) npLandmarkIndices = np.array(self.landmarkIndices) return npLandmarks[npLandmarkIndices]
Example 28
def test_signed_integer_division_overflow(self):
# Ticket #1317.
def test_type(t):
min = np.array([np.iinfo(t).min])
min //= -1
with np.errstate(divide="ignore"):
for t in (np.int8, np.int16, np.int32, np.int64, np.int, np.long):
test_type(t) Example 29
def test_array_side_effect(self):
# The second use of itemsize was throwing an exception because in
# ctors.c, discover_itemsize was calling PyObject_Length without
# checking the return code. This failed to get the length of the
# number 2, and the exception hung around until something checked
# PyErr_Occurred() and returned an error.
assert_equal(np.dtype('S10').itemsize, 10)
np.array([['abc', 2], ['long ', '0123456789']], dtype=np.string_)
assert_equal(np.dtype('S10').itemsize, 10) Example 30
def test_sequence_long(self):
assert_equal(np.array([long(4), long(4)]).dtype, np.long)
assert_equal(np.array([long(4), 2**80]).dtype, np.object)
assert_equal(np.array([long(4), 2**80, long(4)]).dtype, np.object)
assert_equal(np.array([2**80, long(4)]).dtype, np.object) Example 31
def test_matrix_multiply(self):
self.compare_matrix_multiply_results(np.long)
self.compare_matrix_multiply_results(np.double) Example 32
def test_signed_integer_division_overflow(self):
# Ticket #1317.
def test_type(t):
min = np.array([np.iinfo(t).min])
min //= -1
with np.errstate(divide="ignore"):
for t in (np.int8, np.int16, np.int32, np.int64, np.int, np.long):
test_type(t) Example 33
def test_array_side_effect(self):
# The second use of itemsize was throwing an exception because in
# ctors.c, discover_itemsize was calling PyObject_Length without
# checking the return code. This failed to get the length of the
# number 2, and the exception hung around until something checked
# PyErr_Occurred() and returned an error.
assert_equal(np.dtype('S10').itemsize, 10)
np.array([['abc', 2], ['long ', '0123456789']], dtype=np.string_)
assert_equal(np.dtype('S10').itemsize, 10) Example 34
def test_sequence_long(self):
assert_equal(np.array([long(4), long(4)]).dtype, np.long)
assert_equal(np.array([long(4), 2**80]).dtype, np.object)
assert_equal(np.array([long(4), 2**80, long(4)]).dtype, np.object)
assert_equal(np.array([2**80, long(4)]).dtype, np.object) Example 35
def test_matrix_multiply(self):
self.compare_matrix_multiply_results(np.long)
self.compare_matrix_multiply_results(np.double) Example 36
def test_random_integers_max_int(self):
# Tests whether random_integers can generate the
# maximum allowed Python int that can be converted
# into a C long. Previous implementations of this
# method have thrown an OverflowError when attempting
# to generate this integer.
with suppress_warnings() as sup:
w = sup.record(DeprecationWarning)
actual = mt19937.random_integers(np.iinfo('l').max,
np.iinfo('l').max)
assert_(len(w) == 1)
desired = np.iinfo('l').max
assert_equal(actual, desired) Example 37
def test_signed_integer_division_overflow(self):
# Ticket #1317.
def test_type(t):
min = np.array([np.iinfo(t).min])
min //= -1
with np.errstate(divide="ignore"):
for t in (np.int8, np.int16, np.int32, np.int64, np.int, np.long):
test_type(t) Example 38
def test_array_side_effect(self):
# The second use of itemsize was throwing an exception because in
# ctors.c, discover_itemsize was calling PyObject_Length without
# checking the return code. This failed to get the length of the
# number 2, and the exception hung around until something checked
# PyErr_Occurred() and returned an error.
assert_equal(np.dtype('S10').itemsize, 10)
np.array([['abc', 2], ['long ', '0123456789']], dtype=np.string_)
assert_equal(np.dtype('S10').itemsize, 10) Example 39
def test_sequence_long(self):
assert_equal(np.array([long(4), long(4)]).dtype, np.long)
assert_equal(np.array([long(4), 2**80]).dtype, np.object)
assert_equal(np.array([long(4), 2**80, long(4)]).dtype, np.object)
assert_equal(np.array([2**80, long(4)]).dtype, np.object) Example 40
def test_matrix_multiply(self):
self.compare_matrix_multiply_results(np.long)
self.compare_matrix_multiply_results(np.double) Example 41
def test_random_integers_max_int(self):
# Tests whether random_integers can generate the
# maximum allowed Python int that can be converted
# into a C long. Previous implementations of this
# method have thrown an OverflowError when attempting
# to generate this integer.
actual = np.random.random_integers(np.iinfo('l').max,
np.iinfo('l').max)
desired = np.iinfo('l').max
np.testing.assert_equal(actual, desired) Example 42
def test_signed_integer_division_overflow(self):
# Ticket #1317.
def test_type(t):
min = np.array([np.iinfo(t).min])
min //= -1
with np.errstate(divide="ignore"):
for t in (np.int8, np.int16, np.int32, np.int64, np.int, np.long):
test_type(t) Example 43
def test_array_side_effect(self):
# The second use of itemsize was throwing an exception because in
# ctors.c, discover_itemsize was calling PyObject_Length without
# checking the return code. This failed to get the length of the
# number 2, and the exception hung around until something checked
# PyErr_Occurred() and returned an error.
assert_equal(np.dtype('S10').itemsize, 10)
np.array([['abc', 2], ['long ', '0123456789']], dtype=np.string_)
assert_equal(np.dtype('S10').itemsize, 10) Example 44
def test_sequence_long(self):
assert_equal(np.array([long(4), long(4)]).dtype, np.long)
assert_equal(np.array([long(4), 2**80]).dtype, np.object)
assert_equal(np.array([long(4), 2**80, long(4)]).dtype, np.object)
assert_equal(np.array([2**80, long(4)]).dtype, np.object) Example 45
def test_matrix_multiply(self):
self.compare_matrix_multiply_results(np.long)
self.compare_matrix_multiply_results(np.double) Example 46
def test_random_integers_max_int(self):
# Tests whether random_integers can generate the
# maximum allowed Python int that can be converted
# into a C long. Previous implementations of this
# method have thrown an OverflowError when attempting
# to generate this integer.
with suppress_warnings() as sup:
w = sup.record(DeprecationWarning)
actual = np.random.random_integers(np.iinfo('l').max,
np.iinfo('l').max)
assert_(len(w) == 1)
desired = np.iinfo('l').max
assert_equal(actual, desired) Example 47
def assert_valid_percent(x, eq_lower=False, eq_upper=False):
# these are all castable to float
assert_is_type(x, (float, np.float, np.int, int, long, np.long))
x = float(x)
# test lower bound:
if not ((eq_lower and 0. <= x) or ((not eq_lower) and 0. < x)):
raise ValueError('Expected 0. %s x, but got x=%r'
% ('<=' if eq_lower else '<', x))
if not ((eq_upper and x <= 1.) or ((not eq_upper) and x < 1.)):
raise ValueError('Expected x %s 1., but got x=%r'
% ('<=' if eq_upper else '<', x))
return x Example 48
def get_random_state(random_state):
# if it's a seed, return a new seeded RandomState
if isinstance(random_state, (int, np.int, long, np.long, NoneType)):
return RandomState(random_state)
# if it's a RandomState, it's been initialized
elif isinstance(random_state, RandomState):
return random_state
else:
raise TypeError('cannot seed new RandomState with type=%s'
% type(random_state)) Example 49
def test_signed_integer_division_overflow(self):
# Ticket #1317.
def test_type(t):
min = np.array([np.iinfo(t).min])
min //= -1
with np.errstate(divide="ignore"):
for t in (np.int8, np.int16, np.int32, np.int64, np.int, np.long):
test_type(t) Example 50
def test_array_side_effect(self):
# The second use of itemsize was throwing an exception because in
# ctors.c, discover_itemsize was calling PyObject_Length without
# checking the return code. This failed to get the length of the
# number 2, and the exception hung around until something checked
# PyErr_Occurred() and returned an error.
assert_equal(np.dtype('S10').itemsize, 10)
np.array([['abc', 2], ['long ', '0123456789']], dtype=np.string_)
assert_equal(np.dtype('S10').itemsize, 10) 