Python numpy.unsignedinteger() Examples
The following are 30
code examples of numpy.unsignedinteger().
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Example #1
| Source File: test_umath.py From recruit with Apache License 2.0 | 6 votes |
|
def _test_lcm_inner(self, dtype):
# basic use
a = np.array([12, 120], dtype=dtype)
b = np.array([20, 200], dtype=dtype)
assert_equal(np.lcm(a, b), [60, 600])
if not issubclass(dtype, np.unsignedinteger):
# negatives are ignored
a = np.array([12, -12, 12, -12], dtype=dtype)
b = np.array([20, 20, -20, -20], dtype=dtype)
assert_equal(np.lcm(a, b), [60]*4)
# reduce
a = np.array([3, 12, 20], dtype=dtype)
assert_equal(np.lcm.reduce([3, 12, 20]), 60)
# broadcasting, and a test including 0
a = np.arange(6).astype(dtype)
b = 20
assert_equal(np.lcm(a, b), [0, 20, 20, 60, 20, 20])
Example #2
| Source File: test_umath.py From twitter-stock-recommendation with MIT License | 6 votes |
|
def _test_gcd_inner(self, dtype):
# basic use
a = np.array([12, 120], dtype=dtype)
b = np.array([20, 200], dtype=dtype)
assert_equal(np.gcd(a, b), [4, 40])
if not issubclass(dtype, np.unsignedinteger):
# negatives are ignored
a = np.array([12, -12, 12, -12], dtype=dtype)
b = np.array([20, 20, -20, -20], dtype=dtype)
assert_equal(np.gcd(a, b), [4]*4)
# reduce
a = np.array([15, 25, 35], dtype=dtype)
assert_equal(np.gcd.reduce(a), 5)
# broadcasting, and a test including 0
a = np.arange(6).astype(dtype)
b = 20
assert_equal(np.gcd(a, b), [20, 1, 2, 1, 4, 5])
Example #3
| Source File: test_umath.py From twitter-stock-recommendation with MIT License | 6 votes |
|
def _test_lcm_inner(self, dtype):
# basic use
a = np.array([12, 120], dtype=dtype)
b = np.array([20, 200], dtype=dtype)
assert_equal(np.lcm(a, b), [60, 600])
if not issubclass(dtype, np.unsignedinteger):
# negatives are ignored
a = np.array([12, -12, 12, -12], dtype=dtype)
b = np.array([20, 20, -20, -20], dtype=dtype)
assert_equal(np.lcm(a, b), [60]*4)
# reduce
a = np.array([3, 12, 20], dtype=dtype)
assert_equal(np.lcm.reduce([3, 12, 20]), 60)
# broadcasting, and a test including 0
a = np.arange(6).astype(dtype)
b = 20
assert_equal(np.lcm(a, b), [0, 20, 20, 60, 20, 20])
Example #4
| Source File: test_umath.py From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License | 6 votes |
|
def _test_gcd_inner(self, dtype):
# basic use
a = np.array([12, 120], dtype=dtype)
b = np.array([20, 200], dtype=dtype)
assert_equal(np.gcd(a, b), [4, 40])
if not issubclass(dtype, np.unsignedinteger):
# negatives are ignored
a = np.array([12, -12, 12, -12], dtype=dtype)
b = np.array([20, 20, -20, -20], dtype=dtype)
assert_equal(np.gcd(a, b), [4]*4)
# reduce
a = np.array([15, 25, 35], dtype=dtype)
assert_equal(np.gcd.reduce(a), 5)
# broadcasting, and a test including 0
a = np.arange(6).astype(dtype)
b = 20
assert_equal(np.gcd(a, b), [20, 1, 2, 1, 4, 5])
Example #5
| Source File: test_umath.py From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License | 6 votes |
|
def _test_lcm_inner(self, dtype):
# basic use
a = np.array([12, 120], dtype=dtype)
b = np.array([20, 200], dtype=dtype)
assert_equal(np.lcm(a, b), [60, 600])
if not issubclass(dtype, np.unsignedinteger):
# negatives are ignored
a = np.array([12, -12, 12, -12], dtype=dtype)
b = np.array([20, 20, -20, -20], dtype=dtype)
assert_equal(np.lcm(a, b), [60]*4)
# reduce
a = np.array([3, 12, 20], dtype=dtype)
assert_equal(np.lcm.reduce([3, 12, 20]), 60)
# broadcasting, and a test including 0
a = np.arange(6).astype(dtype)
b = 20
assert_equal(np.lcm(a, b), [0, 20, 20, 60, 20, 20])
Example #6
| Source File: test_umath.py From coffeegrindsize with MIT License | 6 votes |
|
def _test_gcd_inner(self, dtype):
# basic use
a = np.array([12, 120], dtype=dtype)
b = np.array([20, 200], dtype=dtype)
assert_equal(np.gcd(a, b), [4, 40])
if not issubclass(dtype, np.unsignedinteger):
# negatives are ignored
a = np.array([12, -12, 12, -12], dtype=dtype)
b = np.array([20, 20, -20, -20], dtype=dtype)
assert_equal(np.gcd(a, b), [4]*4)
# reduce
a = np.array([15, 25, 35], dtype=dtype)
assert_equal(np.gcd.reduce(a), 5)
# broadcasting, and a test including 0
a = np.arange(6).astype(dtype)
b = 20
assert_equal(np.gcd(a, b), [20, 1, 2, 1, 4, 5])
Example #7
| Source File: test_umath.py From coffeegrindsize with MIT License | 6 votes |
|
def _test_lcm_inner(self, dtype):
# basic use
a = np.array([12, 120], dtype=dtype)
b = np.array([20, 200], dtype=dtype)
assert_equal(np.lcm(a, b), [60, 600])
if not issubclass(dtype, np.unsignedinteger):
# negatives are ignored
a = np.array([12, -12, 12, -12], dtype=dtype)
b = np.array([20, 20, -20, -20], dtype=dtype)
assert_equal(np.lcm(a, b), [60]*4)
# reduce
a = np.array([3, 12, 20], dtype=dtype)
assert_equal(np.lcm.reduce([3, 12, 20]), 60)
# broadcasting, and a test including 0
a = np.arange(6).astype(dtype)
b = 20
assert_equal(np.lcm(a, b), [0, 20, 20, 60, 20, 20])
Example #8
| Source File: test_umath.py From pySINDy with MIT License | 6 votes |
|
def _test_gcd_inner(self, dtype):
# basic use
a = np.array([12, 120], dtype=dtype)
b = np.array([20, 200], dtype=dtype)
assert_equal(np.gcd(a, b), [4, 40])
if not issubclass(dtype, np.unsignedinteger):
# negatives are ignored
a = np.array([12, -12, 12, -12], dtype=dtype)
b = np.array([20, 20, -20, -20], dtype=dtype)
assert_equal(np.gcd(a, b), [4]*4)
# reduce
a = np.array([15, 25, 35], dtype=dtype)
assert_equal(np.gcd.reduce(a), 5)
# broadcasting, and a test including 0
a = np.arange(6).astype(dtype)
b = 20
assert_equal(np.gcd(a, b), [20, 1, 2, 1, 4, 5])
Example #9
| Source File: test_umath.py From pySINDy with MIT License | 6 votes |
|
def _test_lcm_inner(self, dtype):
# basic use
a = np.array([12, 120], dtype=dtype)
b = np.array([20, 200], dtype=dtype)
assert_equal(np.lcm(a, b), [60, 600])
if not issubclass(dtype, np.unsignedinteger):
# negatives are ignored
a = np.array([12, -12, 12, -12], dtype=dtype)
b = np.array([20, 20, -20, -20], dtype=dtype)
assert_equal(np.lcm(a, b), [60]*4)
# reduce
a = np.array([3, 12, 20], dtype=dtype)
assert_equal(np.lcm.reduce([3, 12, 20]), 60)
# broadcasting, and a test including 0
a = np.arange(6).astype(dtype)
b = 20
assert_equal(np.lcm(a, b), [0, 20, 20, 60, 20, 20])
Example #10
| Source File: test_umath.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
|
def _test_gcd_inner(self, dtype):
# basic use
a = np.array([12, 120], dtype=dtype)
b = np.array([20, 200], dtype=dtype)
assert_equal(np.gcd(a, b), [4, 40])
if not issubclass(dtype, np.unsignedinteger):
# negatives are ignored
a = np.array([12, -12, 12, -12], dtype=dtype)
b = np.array([20, 20, -20, -20], dtype=dtype)
assert_equal(np.gcd(a, b), [4]*4)
# reduce
a = np.array([15, 25, 35], dtype=dtype)
assert_equal(np.gcd.reduce(a), 5)
# broadcasting, and a test including 0
a = np.arange(6).astype(dtype)
b = 20
assert_equal(np.gcd(a, b), [20, 1, 2, 1, 4, 5])
Example #11
| Source File: test_umath.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
|
def _test_lcm_inner(self, dtype):
# basic use
a = np.array([12, 120], dtype=dtype)
b = np.array([20, 200], dtype=dtype)
assert_equal(np.lcm(a, b), [60, 600])
if not issubclass(dtype, np.unsignedinteger):
# negatives are ignored
a = np.array([12, -12, 12, -12], dtype=dtype)
b = np.array([20, 20, -20, -20], dtype=dtype)
assert_equal(np.lcm(a, b), [60]*4)
# reduce
a = np.array([3, 12, 20], dtype=dtype)
assert_equal(np.lcm.reduce([3, 12, 20]), 60)
# broadcasting, and a test including 0
a = np.arange(6).astype(dtype)
b = 20
assert_equal(np.lcm(a, b), [0, 20, 20, 60, 20, 20])
Example #12
| Source File: test_umath.py From GraphicDesignPatternByPython with MIT License | 6 votes |
|
def _test_gcd_inner(self, dtype):
# basic use
a = np.array([12, 120], dtype=dtype)
b = np.array([20, 200], dtype=dtype)
assert_equal(np.gcd(a, b), [4, 40])
if not issubclass(dtype, np.unsignedinteger):
# negatives are ignored
a = np.array([12, -12, 12, -12], dtype=dtype)
b = np.array([20, 20, -20, -20], dtype=dtype)
assert_equal(np.gcd(a, b), [4]*4)
# reduce
a = np.array([15, 25, 35], dtype=dtype)
assert_equal(np.gcd.reduce(a), 5)
# broadcasting, and a test including 0
a = np.arange(6).astype(dtype)
b = 20
assert_equal(np.gcd(a, b), [20, 1, 2, 1, 4, 5])
Example #13
| Source File: test_umath.py From GraphicDesignPatternByPython with MIT License | 6 votes |
|
def _test_lcm_inner(self, dtype):
# basic use
a = np.array([12, 120], dtype=dtype)
b = np.array([20, 200], dtype=dtype)
assert_equal(np.lcm(a, b), [60, 600])
if not issubclass(dtype, np.unsignedinteger):
# negatives are ignored
a = np.array([12, -12, 12, -12], dtype=dtype)
b = np.array([20, 20, -20, -20], dtype=dtype)
assert_equal(np.lcm(a, b), [60]*4)
# reduce
a = np.array([3, 12, 20], dtype=dtype)
assert_equal(np.lcm.reduce([3, 12, 20]), 60)
# broadcasting, and a test including 0
a = np.arange(6).astype(dtype)
b = 20
assert_equal(np.lcm(a, b), [0, 20, 20, 60, 20, 20])
Example #14
| Source File: test_umath.py From Mastering-Elasticsearch-7.0 with MIT License | 6 votes |
|
def _test_gcd_inner(self, dtype):
# basic use
a = np.array([12, 120], dtype=dtype)
b = np.array([20, 200], dtype=dtype)
assert_equal(np.gcd(a, b), [4, 40])
if not issubclass(dtype, np.unsignedinteger):
# negatives are ignored
a = np.array([12, -12, 12, -12], dtype=dtype)
b = np.array([20, 20, -20, -20], dtype=dtype)
assert_equal(np.gcd(a, b), [4]*4)
# reduce
a = np.array([15, 25, 35], dtype=dtype)
assert_equal(np.gcd.reduce(a), 5)
# broadcasting, and a test including 0
a = np.arange(6).astype(dtype)
b = 20
assert_equal(np.gcd(a, b), [20, 1, 2, 1, 4, 5])
Example #15
| Source File: test_umath.py From recruit with Apache License 2.0 | 6 votes |
|
def _test_gcd_inner(self, dtype):
# basic use
a = np.array([12, 120], dtype=dtype)
b = np.array([20, 200], dtype=dtype)
assert_equal(np.gcd(a, b), [4, 40])
if not issubclass(dtype, np.unsignedinteger):
# negatives are ignored
a = np.array([12, -12, 12, -12], dtype=dtype)
b = np.array([20, 20, -20, -20], dtype=dtype)
assert_equal(np.gcd(a, b), [4]*4)
# reduce
a = np.array([15, 25, 35], dtype=dtype)
assert_equal(np.gcd.reduce(a), 5)
# broadcasting, and a test including 0
a = np.arange(6).astype(dtype)
b = 20
assert_equal(np.gcd(a, b), [20, 1, 2, 1, 4, 5])
Example #16
| Source File: test_umath.py From Mastering-Elasticsearch-7.0 with MIT License | 6 votes |
|
def _test_lcm_inner(self, dtype):
# basic use
a = np.array([12, 120], dtype=dtype)
b = np.array([20, 200], dtype=dtype)
assert_equal(np.lcm(a, b), [60, 600])
if not issubclass(dtype, np.unsignedinteger):
# negatives are ignored
a = np.array([12, -12, 12, -12], dtype=dtype)
b = np.array([20, 20, -20, -20], dtype=dtype)
assert_equal(np.lcm(a, b), [60]*4)
# reduce
a = np.array([3, 12, 20], dtype=dtype)
assert_equal(np.lcm.reduce([3, 12, 20]), 60)
# broadcasting, and a test including 0
a = np.arange(6).astype(dtype)
b = 20
assert_equal(np.lcm(a, b), [0, 20, 20, 60, 20, 20])
Example #17
| Source File: file_checker.py From buzzard with Apache License 2.0 | 6 votes |
|
def _checksum(fname, buffer_size=512 * 1024, dtype='uint64'):
# https://github.com/airware/buzzard/pull/39/#discussion_r239071556
dtype = np.dtype(dtype)
dtypesize = dtype.itemsize
assert buffer_size % dtypesize == 0
assert np.issubdtype(dtype, np.unsignedinteger)
acc = dtype.type(0)
with open(fname, "rb") as f:
with np.warnings.catch_warnings():
np.warnings.filterwarnings('ignore', r'overflow encountered')
for chunk in iter(lambda: f.read(buffer_size), b""):
head = np.frombuffer(chunk, dtype, count=len(chunk) // dtypesize)
head = np.add.reduce(head, dtype=dtype, initial=acc)
acc += head
tailsize = len(chunk) % dtypesize
if tailsize > 0:
# This should only be needed for file's tail
tail = chunk[-tailsize:] + b'\0' * (dtypesize - tailsize)
tail = np.frombuffer(tail, dtype)
acc += tail
return '{:016x}'.format(acc.item())
Example #18
| Source File: writer.py From buzzard with Apache License 2.0 | 6 votes |
|
def _checksum(fname, buffer_size=512 * 1024, dtype='uint64'):
# https://github.com/airware/buzzard/pull/39/#discussion_r239071556
dtype = np.dtype(dtype)
dtypesize = dtype.itemsize
assert buffer_size % dtypesize == 0
assert np.issubdtype(dtype, np.unsignedinteger)
acc = dtype.type(0)
with open(fname, "rb") as f:
with np.warnings.catch_warnings():
np.warnings.filterwarnings('ignore', r'overflow encountered')
for chunk in iter(lambda: f.read(buffer_size), b""):
head = np.frombuffer(chunk, dtype, count=len(chunk) // dtypesize)
head = np.add.reduce(head, dtype=dtype, initial=acc)
acc += head
tailsize = len(chunk) % dtypesize
if tailsize > 0:
# This should only be needed for file's tail
tail = chunk[-tailsize:] + b'\0' * (dtypesize - tailsize)
tail = np.frombuffer(tail, dtype)
acc += tail
return '{:016x}'.format(acc.item())
Example #19
| Source File: test_abc.py From coffeegrindsize with MIT License | 5 votes |
|
def test_abstract(self):
assert_(issubclass(np.number, numbers.Number))
assert_(issubclass(np.inexact, numbers.Complex))
assert_(issubclass(np.complexfloating, numbers.Complex))
assert_(issubclass(np.floating, numbers.Real))
assert_(issubclass(np.integer, numbers.Integral))
assert_(issubclass(np.signedinteger, numbers.Integral))
assert_(issubclass(np.unsignedinteger, numbers.Integral))
Example #20
| Source File: data_schemas.py From lale with Apache License 2.0 | 5 votes |
|
def dtype_to_schema(typ):
result = None
if typ is bool or np.issubdtype(typ, np.bool_):
result = {'type': 'boolean'}
elif np.issubdtype(typ, np.unsignedinteger):
result = {'type': 'integer', 'minimum': 0}
elif np.issubdtype(typ, np.integer):
result = {'type': 'integer'}
elif np.issubdtype(typ, np.number):
result = {'type': 'number'}
elif np.issubdtype(typ, np.string_) or np.issubdtype(typ, np.unicode_):
result = {'type': 'string'}
elif isinstance(typ, np.dtype):
if typ.fields:
props = {k: dtype_to_schema(t) for k, t in typ.fields.items()}
result = {'type': 'object', 'properties': props}
elif typ.shape:
result = shape_and_dtype_to_schema(typ.shape, typ.subdtype)
elif np.issubdtype(typ, np.object_):
result = {'type': 'string'}
else:
assert False, f'unexpected dtype {typ}'
else:
assert False, f'unexpected non-dtype {typ}'
lale.type_checking.validate_is_schema(result)
return result
Example #21
| Source File: numeric.py From Splunking-Crime with GNU Affero General Public License v3.0 | 5 votes |
|
def _assert_safe_casting(cls, data, subarr):
"""
Ensure incoming data can be represented as uints.
"""
if not issubclass(data.dtype.type, np.unsignedinteger):
if not np.array_equal(data, subarr):
raise TypeError('Unsafe NumPy casting, you must '
'explicitly cast')
Example #22
| Source File: measurements.py From Splunking-Crime with GNU Affero General Public License v3.0 | 5 votes |
|
def _safely_castable_to_int(dt):
"""Test whether the numpy data type `dt` can be safely cast to an int."""
int_size = np.dtype(int).itemsize
safe = ((np.issubdtype(dt, int) and dt.itemsize <= int_size) or
(np.issubdtype(dt, np.unsignedinteger) and dt.itemsize < int_size))
return safe
Example #23
| Source File: numpngw.py From numpngw with BSD 2-Clause "Simplified" License | 5 votes |
|
def _validate_array(a):
if a.ndim != 2:
if a.ndim != 3 or a.shape[2] > 4 or a.shape[2] == 0:
raise ValueError("array must be 2D, or 3D with shape "
"(m, n, d) with 1 <= d <= 4.")
itemsize = a.dtype.itemsize
if not _np.issubdtype(a.dtype, _np.unsignedinteger) or itemsize > 2:
raise ValueError("array must be an array of 8- or 16-bit "
"unsigned integers")
# Notes on color_type:
#
# color_type meaning tRNS chunk contents (optional)
# ---------- ------------------------ --------------------------------
# 0 grayscale Single gray level value, 2 bytes
# 2 RGB Single RGB, 2 bytes per channel
# 3 8 bit indexed RGB or RGBA Series of 1 byte alpha values
# 4 Grayscale and alpha
# 6 RGBA
#
#
# from http://www.w3.org/TR/PNG/:
# Table 11.1 - Allowed combinations of colour type and bit depth
#
# Color Allowed
# PNG image type type bit depths Interpretation
# Greyscale 0 1, 2, 4, 8, 16 Each pixel is a greyscale
# sample
# Truecolour 2 8, 16 Each pixel is an RGB triple
# Indexed-colour 3 1, 2, 4, 8 Each pixel is a palette index;
# a PLTE chunk shall appear.
# Greyscale with alpha 4 8, 16 Each pixel is a greyscale
# sample followed by an alpha
# sample.
# Truecolour with alpha 6 8, 16 Each pixel is an RGB triple
# followed by an alpha sample.
Example #24
| Source File: numeric.py From elasticintel with GNU General Public License v3.0 | 5 votes |
|
def _assert_safe_casting(cls, data, subarr):
"""
Ensure incoming data can be represented as uints.
"""
if not issubclass(data.dtype.type, np.unsignedinteger):
if not np.array_equal(data, subarr):
raise TypeError('Unsafe NumPy casting, you must '
'explicitly cast')
Example #25
| Source File: common.py From elasticintel with GNU General Public License v3.0 | 5 votes |
|
def is_unsigned_integer_dtype(arr_or_dtype):
"""
Check whether the provided array or dtype is of an unsigned integer dtype.
Parameters
----------
arr_or_dtype : array-like
The array or dtype to check.
Returns
-------
boolean : Whether or not the array or dtype is of an
unsigned integer dtype.
Examples
--------
>>> is_unsigned_integer_dtype(str)
False
>>> is_unsigned_integer_dtype(int) # signed
False
>>> is_unsigned_integer_dtype(float)
False
>>> is_unsigned_integer_dtype(np.uint64)
True
>>> is_unsigned_integer_dtype(np.array(['a', 'b']))
False
>>> is_unsigned_integer_dtype(pd.Series([1, 2])) # signed
False
>>> is_unsigned_integer_dtype(pd.Index([1, 2.])) # float
False
>>> is_unsigned_integer_dtype(np.array([1, 2], dtype=np.uint32))
True
"""
if arr_or_dtype is None:
return False
tipo = _get_dtype_type(arr_or_dtype)
return (issubclass(tipo, np.unsignedinteger) and
not issubclass(tipo, (np.datetime64, np.timedelta64)))
Example #26
| Source File: _parse.py From sklearn-onnx with MIT License | 5 votes |
|
def _parse_sklearn_classifier(scope, model, inputs, custom_parsers=None):
probability_tensor = _parse_sklearn_simple_model(
scope, model, inputs, custom_parsers=custom_parsers)
if model.__class__ in [NuSVC, SVC] and not model.probability:
return probability_tensor
options = scope.get_options(model, dict(zipmap=True))
if not options['zipmap']:
return probability_tensor
this_operator = scope.declare_local_operator('SklearnZipMap')
this_operator.inputs = probability_tensor
label_type = Int64TensorType([None])
classes = get_label_classes(scope, model)
if (isinstance(model.classes_, list) and
isinstance(model.classes_[0], np.ndarray)):
# multi-label problem
pass
elif np.issubdtype(classes.dtype, np.floating):
classes = np.array(list(map(lambda x: int(x), classes)))
if set(map(lambda x: float(x), classes)) != set(model.classes_):
raise RuntimeError("skl2onnx implicitly converts float class "
"labels into integers but at least one label "
"is not an integer. Class labels should "
"be integers or strings.")
this_operator.classlabels_int64s = classes
elif np.issubdtype(classes.dtype, np.signedinteger):
this_operator.classlabels_int64s = classes
elif np.issubdtype(classes.dtype, np.unsignedinteger):
this_operator.classlabels_int64s = classes
else:
classes = np.array([s.encode('utf-8') for s in classes])
this_operator.classlabels_strings = classes
label_type = StringTensorType([None])
output_label = scope.declare_local_variable('output_label', label_type)
output_probability = scope.declare_local_variable(
'output_probability',
SequenceType(DictionaryType(label_type, scope.tensor_type())))
this_operator.outputs.append(output_label)
this_operator.outputs.append(output_probability)
return this_operator.outputs
Example #27
| Source File: common.py From Splunking-Crime with GNU Affero General Public License v3.0 | 5 votes |
|
def is_unsigned_integer_dtype(arr_or_dtype):
"""
Check whether the provided array or dtype is of an unsigned integer dtype.
Parameters
----------
arr_or_dtype : array-like
The array or dtype to check.
Returns
-------
boolean : Whether or not the array or dtype is of an
unsigned integer dtype.
Examples
--------
>>> is_unsigned_integer_dtype(str)
False
>>> is_unsigned_integer_dtype(int) # signed
False
>>> is_unsigned_integer_dtype(float)
False
>>> is_unsigned_integer_dtype(np.uint64)
True
>>> is_unsigned_integer_dtype(np.array(['a', 'b']))
False
>>> is_unsigned_integer_dtype(pd.Series([1, 2])) # signed
False
>>> is_unsigned_integer_dtype(pd.Index([1, 2.])) # float
False
>>> is_unsigned_integer_dtype(np.array([1, 2], dtype=np.uint32))
True
"""
if arr_or_dtype is None:
return False
tipo = _get_dtype_type(arr_or_dtype)
return (issubclass(tipo, np.unsignedinteger) and
not issubclass(tipo, (np.datetime64, np.timedelta64)))
Example #28
| Source File: test_abc.py From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License | 5 votes |
|
def test_abstract(self):
assert_(issubclass(np.number, numbers.Number))
assert_(issubclass(np.inexact, numbers.Complex))
assert_(issubclass(np.complexfloating, numbers.Complex))
assert_(issubclass(np.floating, numbers.Real))
assert_(issubclass(np.integer, numbers.Integral))
assert_(issubclass(np.signedinteger, numbers.Integral))
assert_(issubclass(np.unsignedinteger, numbers.Integral))
Example #29
| Source File: numeric.py From recruit with Apache License 2.0 | 5 votes |
|
def _assert_safe_casting(cls, data, subarr):
"""
Ensure incoming data can be represented as uints.
"""
if not issubclass(data.dtype.type, np.unsignedinteger):
if not np.array_equal(data, subarr):
raise TypeError('Unsafe NumPy casting, you must '
'explicitly cast')
Example #30
| Source File: test_abc.py From twitter-stock-recommendation with MIT License | 5 votes |
|
def test_abstract(self):
assert_(issubclass(np.number, numbers.Number))
assert_(issubclass(np.inexact, numbers.Complex))
assert_(issubclass(np.complexfloating, numbers.Complex))
assert_(issubclass(np.floating, numbers.Real))
assert_(issubclass(np.integer, numbers.Integral))
assert_(issubclass(np.signedinteger, numbers.Integral))
assert_(issubclass(np.unsignedinteger, numbers.Integral))
