Here are the examples of the python api numpy.array.dtype taken from open source projects. By voting up you can indicate which examples are most useful and appropriate.
31 Examples
3
View Complete Implementation : test_numeric.py
Copyright MIT License
Author : alvarob96
Copyright MIT License
Author : alvarob96
def full_like(array, value):
"""Compatibility for numpy<1.8.0
"""
ret = np.empty(array.shape, dtype=np.array(value).dtype)
ret.fill(value)
return ret
3
View Complete Implementation : utils.py
Copyright Apache License 2.0
Author : google
Copyright Apache License 2.0
Author : google
def astype(array, y):
"""A functional form of the `astype` method.
Args:
array: The array or number to cast.
y: An array or number, as the input, whose type should be that of array.
Returns:
An array or number with the same dtype as `y`.
"""
if isinstance(y, autograd.core.Node):
return array.astype(numpy.array(y.value).dtype)
return array.astype(numpy.array(y).dtype)
3
View Complete Implementation : test_block.py
Copyright BSD 3-Clause "New" or "Revised" License
Author : ledatelescope
Copyright BSD 3-Clause "New" or "Revised" License
Author : ledatelescope
def tearDown(self):
"""Run the pipeline and test the output against the expectation"""
Pipeline(self.blocks).main()
if np.array(self.expected_result).dtype == 'complex128':
result = np.loadtxt('.log.txt', dtype=np.float64).view(np.complex128)
else:
result = np.loadtxt('.log.txt').astype(np.float32)
np.testing.astert_almost_equal(result, self.expected_result)
3
View Complete Implementation : test_numpy_array.py
Copyright Apache License 2.0
Author : mlperf
Copyright Apache License 2.0
Author : mlperf
def test_constructors():
defaults = m.default_constructors()
for a in defaults.values():
astert a.size == 0
astert defaults["array"].dtype == np.array([]).dtype
astert defaults["array_t<int32>"].dtype == np.int32
astert defaults["array_t<double>"].dtype == np.float64
results = m.converting_constructors([1, 2, 3])
for a in results.values():
np.testing.astert_array_equal(a, [1, 2, 3])
astert results["array"].dtype == np.int_
astert results["array_t<int32>"].dtype == np.int32
astert results["array_t<double>"].dtype == np.float64
3
View Complete Implementation : catalogue_errors.py
Copyright Mozilla Public License 2.0
Author : nanoporetech
Copyright Mozilla Public License 2.0
Author : nanoporetech
def rle(it):
"""Calculate a run length encoding (rle), of an input vector.
:param it: iterable.
:returns: structured array with fields `start`, `length`, and `value`.
"""
val_dtype = np.array(it[0]).dtype
dtype = [('length', int), ('start', int), ('value', val_dtype)]
def _gen():
start = 0
for key, group in itertools.groupby(it):
length = sum(1 for x in group)
yield length, start, key
start += length
return np.fromiter(_gen(), dtype=dtype)
3
View Complete Implementation : value.py
Copyright MIT License
Author : pfnet-research
Copyright MIT License
Author : pfnet-research
def get_attribute(self, key: str, env: 'utils.Env') -> 'Value':
if not self.is_py:
raise TypeError('Unsupported attribute %s for an ONNX value' % key)
value = Value(getattr(self.value, key))
if (value.is_py and
(value.value is None or
not isinstance(value.value, type) and
# TODO(hamaji): We probably need to create a ValueInfo
# for Variable.
not isinstance(value.value, chainer.Variable) and
np.array(value.value).dtype != np.object)):
value.to_value_info(env.root())
setattr(self.value, key, value)
if not value.is_py:
env.read_attrs.append((self, key, value))
return value
3
View Complete Implementation : functions_ndarray.py
Copyright MIT License
Author : pfnet-research
Copyright MIT License
Author : pfnet-research
def vcall(self, module: 'values.Field', graph: 'graphs.Graph', inst: 'values.Object', args: 'functions.FunctionArgInput',
context: 'functions.VEvalContext' = None, line=-1):
args = functions.FunctionArgInput()
args.inputs.append(inst)
args.keywords['self'] = inst
node = nodes.NodeCall(self, args, line)
value = values.NumberValue(None)
value.dtype = np.array(0).dtype
value.name = '@F.{}.{}'.format(line, self.name)
node.set_outputs([value])
graph.add_node(node)
return values.Object(value)
3
View Complete Implementation : values.py
Copyright MIT License
Author : pfnet-research
Copyright MIT License
Author : pfnet-research
def __init__(self, number):
super().__init__()
self.internal_value = number
self.dtype = None
if self.internal_value is not None:
self.dtype = np.array(self.internal_value).dtype
if not config.float_restrict and self.dtype == np.float64:
self.dtype = np.float32
3
View Complete Implementation : values.py
Copyright MIT License
Author : pfnet-research
Copyright MIT License
Author : pfnet-research
def __init__(self, value = None):
super().__init__()
self.shape = ()
self.internal_value = value
self.value = None # not used?
self.dtype = None
if self.internal_value is not None:
self.dtype = np.array(self.internal_value).dtype
if not config.float_restrict and self.dtype == np.float64:
self.dtype = np.float32
3
View Complete Implementation : test_datasets.py
Copyright MIT License
Author : PhasesResearchLab
Copyright MIT License
Author : PhasesResearchLab
def test_datasets_convert_thermochemical_string_values_producing_correct_value(datasets_db):
"""Strings where floats are expected should give correct answers for thermochemical datasets"""
ds = clean_dataset(CU_MG_DATASET_THERMOCHEMICAL_STRING_VALUES)
astert np.issubdtype(np.array(ds['values']).dtype, np.number)
astert np.issubdtype(np.array(ds['conditions']['T']).dtype, np.number)
astert np.issubdtype(np.array(ds['conditions']['P']).dtype, np.number)