body
stringlengths 26
98.2k
| body_hash
int64 -9,222,864,604,528,158,000
9,221,803,474B
| docstring
stringlengths 1
16.8k
| path
stringlengths 5
230
| name
stringlengths 1
96
| repository_name
stringlengths 7
89
| lang
stringclasses 1
value | body_without_docstring
stringlengths 20
98.2k
|
|---|---|---|---|---|---|---|---|
def test_simple_grad():
'Test the use of jax.grad'
dev = qml.device('default.mixed', wires=2)
@qml.qnode(dev, interface='jax', diff_method='parameter-shift')
def circuit(weights):
qml.RX(weights[0], wires=0)
qml.RZ(weights[1], wires=1)
return qml.expval((qml.PauliZ(0) @ qml.PauliZ(1)))
weights = jnp.array([0.1, 0.2])
val = jax.grad(circuit)(weights)
assert ('DeviceArray' in val.__repr__()) | 8,963,306,386,412,158,000 | Test the use of jax.grad | tests/tape/interfaces/test_qnode_jax.py | test_simple_grad | PritishSehzpaul/pennylane | python | def test_simple_grad():
dev = qml.device('default.mixed', wires=2)
@qml.qnode(dev, interface='jax', diff_method='parameter-shift')
def circuit(weights):
qml.RX(weights[0], wires=0)
qml.RZ(weights[1], wires=1)
return qml.expval((qml.PauliZ(0) @ qml.PauliZ(1)))
weights = jnp.array([0.1, 0.2])
val = jax.grad(circuit)(weights)
assert ('DeviceArray' in val.__repr__()) |
@pytest.mark.parametrize('diff_method', ['parameter-shift', 'finite-diff'])
def test_differentiable_expand(diff_method):
'Test that operation and nested tapes expansion\n is differentiable'
class U3(qml.U3):
def expand(self):
(theta, phi, lam) = self.data
wires = self.wires
with JacobianTape() as tape:
qml.Rot(lam, theta, (- lam), wires=wires)
qml.PhaseShift((phi + lam), wires=wires)
return tape
dev = qml.device('default.mixed', wires=1)
a = jnp.array(0.1)
p = jnp.array([0.1, 0.2, 0.3])
@qnode(dev, diff_method=diff_method, interface='jax')
def circuit(a, p):
qml.RX(a, wires=0)
U3(p[0], p[1], p[2], wires=0)
return qml.expval(qml.PauliX(0))
res = circuit(a, p)
expected = (((np.cos(a) * np.cos(p[1])) * np.sin(p[0])) + (np.sin(a) * ((np.cos(p[2]) * np.sin(p[1])) + ((np.cos(p[0]) * np.cos(p[1])) * np.sin(p[2])))))
tol = 1e-05
assert np.allclose(res, expected, atol=tol, rtol=0)
res = jax.grad(circuit, argnums=1)(a, p)
expected = np.array([(np.cos(p[1]) * ((np.cos(a) * np.cos(p[0])) - ((np.sin(a) * np.sin(p[0])) * np.sin(p[2])))), (((np.cos(p[1]) * np.cos(p[2])) * np.sin(a)) - (np.sin(p[1]) * ((np.cos(a) * np.sin(p[0])) + ((np.cos(p[0]) * np.sin(a)) * np.sin(p[2]))))), (np.sin(a) * (((np.cos(p[0]) * np.cos(p[1])) * np.cos(p[2])) - (np.sin(p[1]) * np.sin(p[2]))))])
assert np.allclose(res, expected, atol=tol, rtol=0) | -6,303,920,968,199,098,000 | Test that operation and nested tapes expansion
is differentiable | tests/tape/interfaces/test_qnode_jax.py | test_differentiable_expand | PritishSehzpaul/pennylane | python | @pytest.mark.parametrize('diff_method', ['parameter-shift', 'finite-diff'])
def test_differentiable_expand(diff_method):
'Test that operation and nested tapes expansion\n is differentiable'
class U3(qml.U3):
def expand(self):
(theta, phi, lam) = self.data
wires = self.wires
with JacobianTape() as tape:
qml.Rot(lam, theta, (- lam), wires=wires)
qml.PhaseShift((phi + lam), wires=wires)
return tape
dev = qml.device('default.mixed', wires=1)
a = jnp.array(0.1)
p = jnp.array([0.1, 0.2, 0.3])
@qnode(dev, diff_method=diff_method, interface='jax')
def circuit(a, p):
qml.RX(a, wires=0)
U3(p[0], p[1], p[2], wires=0)
return qml.expval(qml.PauliX(0))
res = circuit(a, p)
expected = (((np.cos(a) * np.cos(p[1])) * np.sin(p[0])) + (np.sin(a) * ((np.cos(p[2]) * np.sin(p[1])) + ((np.cos(p[0]) * np.cos(p[1])) * np.sin(p[2])))))
tol = 1e-05
assert np.allclose(res, expected, atol=tol, rtol=0)
res = jax.grad(circuit, argnums=1)(a, p)
expected = np.array([(np.cos(p[1]) * ((np.cos(a) * np.cos(p[0])) - ((np.sin(a) * np.sin(p[0])) * np.sin(p[2])))), (((np.cos(p[1]) * np.cos(p[2])) * np.sin(a)) - (np.sin(p[1]) * ((np.cos(a) * np.sin(p[0])) + ((np.cos(p[0]) * np.sin(a)) * np.sin(p[2]))))), (np.sin(a) * (((np.cos(p[0]) * np.cos(p[1])) * np.cos(p[2])) - (np.sin(p[1]) * np.sin(p[2]))))])
assert np.allclose(res, expected, atol=tol, rtol=0) |
def qtransform(qnode, a, framework=jnp):
'Transforms every RY(y) gate in a circuit to RX(-a*cos(y))'
def construct(self, args, kwargs):
'New quantum tape construct method, that performs\n the transform on the tape in a define-by-run manner'
t_op = []
QNode.construct(self, args, kwargs)
new_ops = []
for o in self.qtape.operations:
if isinstance(o, qml.RY):
t_op.append(qml.RX(((- a) * framework.cos(o.data[0])), wires=o.wires))
new_ops.append(t_op[(- 1)])
else:
new_ops.append(o)
self.qtape._ops = new_ops
self.qtape._update()
import copy
new_qnode = copy.deepcopy(qnode)
new_qnode.construct = construct.__get__(new_qnode, QNode)
return new_qnode | 7,020,693,661,897,376,000 | Transforms every RY(y) gate in a circuit to RX(-a*cos(y)) | tests/tape/interfaces/test_qnode_jax.py | qtransform | PritishSehzpaul/pennylane | python | def qtransform(qnode, a, framework=jnp):
def construct(self, args, kwargs):
'New quantum tape construct method, that performs\n the transform on the tape in a define-by-run manner'
t_op = []
QNode.construct(self, args, kwargs)
new_ops = []
for o in self.qtape.operations:
if isinstance(o, qml.RY):
t_op.append(qml.RX(((- a) * framework.cos(o.data[0])), wires=o.wires))
new_ops.append(t_op[(- 1)])
else:
new_ops.append(o)
self.qtape._ops = new_ops
self.qtape._update()
import copy
new_qnode = copy.deepcopy(qnode)
new_qnode.construct = construct.__get__(new_qnode, QNode)
return new_qnode |
@pytest.mark.parametrize('dev_name,diff_method', [('default.mixed', 'finite-diff'), ('default.qubit.autograd', 'parameter-shift')])
def test_transform(dev_name, diff_method, monkeypatch, tol):
'Test an example transform'
monkeypatch.setattr(qml.operation.Operation, 'do_check_domain', False)
dev = qml.device(dev_name, wires=1)
@qnode(dev, interface='jax', diff_method=diff_method)
def circuit(weights):
op1 = qml.RY(weights[0], wires=0)
op2 = qml.RX(weights[1], wires=0)
return qml.expval(qml.PauliZ(wires=0))
weights = np.array([0.32, 0.543])
a = np.array(0.5)
def loss(weights, a):
new_circuit = qtransform(circuit, a)
res = new_circuit(weights)
res2 = circuit(jnp.sin(weights))
return (res + res2)
res = loss(weights, a)
grad = jax.grad(loss, argnums=[0, 1])(weights, a)
assert (len(grad) == 2)
assert (grad[0].shape == weights.shape)
assert (grad[1].shape == a.shape)
tol = 1e-05
assert np.allclose(res, 1.8244501889992706, atol=tol, rtol=0)
assert np.allclose(grad[0], [(- 0.26610258), (- 0.47053553)], atol=tol, rtol=0)
assert np.allclose(grad[1], 0.06486032, atol=tol, rtol=0) | 3,371,618,771,618,339,000 | Test an example transform | tests/tape/interfaces/test_qnode_jax.py | test_transform | PritishSehzpaul/pennylane | python | @pytest.mark.parametrize('dev_name,diff_method', [('default.mixed', 'finite-diff'), ('default.qubit.autograd', 'parameter-shift')])
def test_transform(dev_name, diff_method, monkeypatch, tol):
monkeypatch.setattr(qml.operation.Operation, 'do_check_domain', False)
dev = qml.device(dev_name, wires=1)
@qnode(dev, interface='jax', diff_method=diff_method)
def circuit(weights):
op1 = qml.RY(weights[0], wires=0)
op2 = qml.RX(weights[1], wires=0)
return qml.expval(qml.PauliZ(wires=0))
weights = np.array([0.32, 0.543])
a = np.array(0.5)
def loss(weights, a):
new_circuit = qtransform(circuit, a)
res = new_circuit(weights)
res2 = circuit(jnp.sin(weights))
return (res + res2)
res = loss(weights, a)
grad = jax.grad(loss, argnums=[0, 1])(weights, a)
assert (len(grad) == 2)
assert (grad[0].shape == weights.shape)
assert (grad[1].shape == a.shape)
tol = 1e-05
assert np.allclose(res, 1.8244501889992706, atol=tol, rtol=0)
assert np.allclose(grad[0], [(- 0.26610258), (- 0.47053553)], atol=tol, rtol=0)
assert np.allclose(grad[1], 0.06486032, atol=tol, rtol=0) |
def construct(self, args, kwargs):
'New quantum tape construct method, that performs\n the transform on the tape in a define-by-run manner'
t_op = []
QNode.construct(self, args, kwargs)
new_ops = []
for o in self.qtape.operations:
if isinstance(o, qml.RY):
t_op.append(qml.RX(((- a) * framework.cos(o.data[0])), wires=o.wires))
new_ops.append(t_op[(- 1)])
else:
new_ops.append(o)
self.qtape._ops = new_ops
self.qtape._update() | 5,238,125,990,119,009,000 | New quantum tape construct method, that performs
the transform on the tape in a define-by-run manner | tests/tape/interfaces/test_qnode_jax.py | construct | PritishSehzpaul/pennylane | python | def construct(self, args, kwargs):
'New quantum tape construct method, that performs\n the transform on the tape in a define-by-run manner'
t_op = []
QNode.construct(self, args, kwargs)
new_ops = []
for o in self.qtape.operations:
if isinstance(o, qml.RY):
t_op.append(qml.RX(((- a) * framework.cos(o.data[0])), wires=o.wires))
new_ops.append(t_op[(- 1)])
else:
new_ops.append(o)
self.qtape._ops = new_ops
self.qtape._update() |
def testDocxSetHeaderRequest(self):
'Test DocxSetHeaderRequest'
pass | -4,734,426,132,462,906,000 | Test DocxSetHeaderRequest | test/test_docx_set_header_request.py | testDocxSetHeaderRequest | Cloudmersive/Cloudmersive.APIClient.Python.Convert | python | def testDocxSetHeaderRequest(self):
pass |
@staticmethod
def updateCouplings(connection):
'\n The shape has changed, which means couplings might have to change, be added or removed.\n To be sure all couplings in this connection are deleted and then build up from scratch.\n '
'Remove all old couplings.'
for coupling in connection.couplings():
connection.Document.removeObject(coupling.Name)
'Add couplings for every shape.'
connection.addCouplings() | 1,902,094,766,423,032,800 | The shape has changed, which means couplings might have to change, be added or removed.
To be sure all couplings in this connection are deleted and then build up from scratch. | Sea/adapter/connections/Connection.py | updateCouplings | FRidh/Sea | python | @staticmethod
def updateCouplings(connection):
'\n The shape has changed, which means couplings might have to change, be added or removed.\n To be sure all couplings in this connection are deleted and then build up from scratch.\n '
'Remove all old couplings.'
for coupling in connection.couplings():
connection.Document.removeObject(coupling.Name)
'Add couplings for every shape.'
connection.addCouplings() |
@staticmethod
def addCouplings(connection):
'\n Add couplings to the :attr:`connection`.\n \n :param connection: an instance of :class:`Sea.adapter.baseclasses.Connection`\n '
for (comp_from, comp_to) in itertools.permutations(connection.Components, 2):
coupling_sort = Connection.determineCouplingType(connection.ClassName, comp_from, comp_to)
if (not coupling_sort):
App.Console.PrintWarning('Cannot add coupling.\n')
return
for (sub_from, sub_to) in itertools.product(comp_from.subsystems(), comp_to.subsystems()):
connection.makeCoupling(sub_from, sub_to, coupling_sort) | -1,349,375,267,989,642,800 | Add couplings to the :attr:`connection`.
:param connection: an instance of :class:`Sea.adapter.baseclasses.Connection` | Sea/adapter/connections/Connection.py | addCouplings | FRidh/Sea | python | @staticmethod
def addCouplings(connection):
'\n Add couplings to the :attr:`connection`.\n \n :param connection: an instance of :class:`Sea.adapter.baseclasses.Connection`\n '
for (comp_from, comp_to) in itertools.permutations(connection.Components, 2):
coupling_sort = Connection.determineCouplingType(connection.ClassName, comp_from, comp_to)
if (not coupling_sort):
App.Console.PrintWarning('Cannot add coupling.\n')
return
for (sub_from, sub_to) in itertools.product(comp_from.subsystems(), comp_to.subsystems()):
connection.makeCoupling(sub_from, sub_to, coupling_sort) |
@staticmethod
def determineCouplingType(connection_type, component_from, component_to):
'\n Determine the type of coupling. Detects what type of connection the components have.\n Based on the type of connection and on the types of components a coupling is returned.\n \n :param component_from: an instance of a child of :class:`Sea.adapter.baseclasses.Component`\n :param component_to: an instance of a child of :class:`Sea.adapter.baseclasses.Component`\n '
if connection_type:
item = (connection_type, component_from.ClassName, component_to.ClassName)
try:
return Connection.coupling_options[item]
except KeyError:
txt = (((((('Could not determine the type of coupling for ' + component_from.ClassName) + ' to ') + component_to.ClassName) + ' with ') + connection_type) + '.\n')
App.Console.PrintWarning(txt)
return None | -5,089,945,891,643,414,000 | Determine the type of coupling. Detects what type of connection the components have.
Based on the type of connection and on the types of components a coupling is returned.
:param component_from: an instance of a child of :class:`Sea.adapter.baseclasses.Component`
:param component_to: an instance of a child of :class:`Sea.adapter.baseclasses.Component` | Sea/adapter/connections/Connection.py | determineCouplingType | FRidh/Sea | python | @staticmethod
def determineCouplingType(connection_type, component_from, component_to):
'\n Determine the type of coupling. Detects what type of connection the components have.\n Based on the type of connection and on the types of components a coupling is returned.\n \n :param component_from: an instance of a child of :class:`Sea.adapter.baseclasses.Component`\n :param component_to: an instance of a child of :class:`Sea.adapter.baseclasses.Component`\n '
if connection_type:
item = (connection_type, component_from.ClassName, component_to.ClassName)
try:
return Connection.coupling_options[item]
except KeyError:
txt = (((((('Could not determine the type of coupling for ' + component_from.ClassName) + ' to ') + component_to.ClassName) + ' with ') + connection_type) + '.\n')
App.Console.PrintWarning(txt)
return None |
@staticmethod
def makeCoupling(connection, subsystem_from, subsystem_to, sort):
'\n Add a coupling to system.\n \n :param connection: an instance of :class:`Sea.adapter.baseclasses.Connection`\n :param component_from: an instance of a child of :class:`Sea.adapter.baseclasses.Component`\n :param subsystem_from: string representing the type of subsystem\n :param component_to: an instance of a child of :class:`Sea.adapter.baseclasses.Component`\n :param subsystem_to: string representing the type of subsystem\n :param sort: sort of coupling as specified in :class:`Sea.adapter.couplings.couplings_map`\n \n '
from Sea.adapter.object_maps import couplings_map
obj = connection.Document.addObject('App::FeaturePython', 'Coupling')
couplings_map[sort](obj, connection, subsystem_from, subsystem_to)
try:
Sea.adapter.couplings.ViewProviderCoupling(obj.ViewObject)
except AttributeError:
pass
obj.Label = ((((obj.ClassName + '_') + subsystem_from.ClassName.replace('Subsystem', '')) + '_to_') + subsystem_to.ClassName.replace('Subsystem', ''))
logging.info('Sea: Created %s.', obj.Name)
obj.Document.recompute()
return obj | -7,819,181,587,509,591,000 | Add a coupling to system.
:param connection: an instance of :class:`Sea.adapter.baseclasses.Connection`
:param component_from: an instance of a child of :class:`Sea.adapter.baseclasses.Component`
:param subsystem_from: string representing the type of subsystem
:param component_to: an instance of a child of :class:`Sea.adapter.baseclasses.Component`
:param subsystem_to: string representing the type of subsystem
:param sort: sort of coupling as specified in :class:`Sea.adapter.couplings.couplings_map` | Sea/adapter/connections/Connection.py | makeCoupling | FRidh/Sea | python | @staticmethod
def makeCoupling(connection, subsystem_from, subsystem_to, sort):
'\n Add a coupling to system.\n \n :param connection: an instance of :class:`Sea.adapter.baseclasses.Connection`\n :param component_from: an instance of a child of :class:`Sea.adapter.baseclasses.Component`\n :param subsystem_from: string representing the type of subsystem\n :param component_to: an instance of a child of :class:`Sea.adapter.baseclasses.Component`\n :param subsystem_to: string representing the type of subsystem\n :param sort: sort of coupling as specified in :class:`Sea.adapter.couplings.couplings_map`\n \n '
from Sea.adapter.object_maps import couplings_map
obj = connection.Document.addObject('App::FeaturePython', 'Coupling')
couplings_map[sort](obj, connection, subsystem_from, subsystem_to)
try:
Sea.adapter.couplings.ViewProviderCoupling(obj.ViewObject)
except AttributeError:
pass
obj.Label = ((((obj.ClassName + '_') + subsystem_from.ClassName.replace('Subsystem', )) + '_to_') + subsystem_to.ClassName.replace('Subsystem', ))
logging.info('Sea: Created %s.', obj.Name)
obj.Document.recompute()
return obj |
@test_util.run_v1_only('b/120545219')
def testControlFlowInitialization(self):
'Expects an error if an initializer is in a control-flow scope.'
def cond(i, _):
return (i < 10)
def body(i, _):
zero = array_ops.zeros([], dtype=dtypes.int32)
v = variables.Variable(initial_value=zero)
return ((i + 1), v.read_value())
with self.assertRaisesRegex(ValueError, 'inside a control-flow'):
control_flow_ops.while_loop(cond, body, [0, 0]) | -3,174,679,683,478,967,000 | Expects an error if an initializer is in a control-flow scope. | tensorflow/python/kernel_tests/variables_test.py | testControlFlowInitialization | ArnovanHilten/tensorflow | python | @test_util.run_v1_only('b/120545219')
def testControlFlowInitialization(self):
def cond(i, _):
return (i < 10)
def body(i, _):
zero = array_ops.zeros([], dtype=dtypes.int32)
v = variables.Variable(initial_value=zero)
return ((i + 1), v.read_value())
with self.assertRaisesRegex(ValueError, 'inside a control-flow'):
control_flow_ops.while_loop(cond, body, [0, 0]) |
def search(taxonKey=None, repatriated=None, kingdomKey=None, phylumKey=None, classKey=None, orderKey=None, familyKey=None, genusKey=None, subgenusKey=None, scientificName=None, country=None, publishingCountry=None, hasCoordinate=None, typeStatus=None, recordNumber=None, lastInterpreted=None, continent=None, geometry=None, recordedBy=None, recordedByID=None, identifiedByID=None, basisOfRecord=None, datasetKey=None, eventDate=None, catalogNumber=None, year=None, month=None, decimalLatitude=None, decimalLongitude=None, elevation=None, depth=None, institutionCode=None, collectionCode=None, hasGeospatialIssue=None, issue=None, q=None, spellCheck=None, mediatype=None, limit=300, offset=0, establishmentMeans=None, facet=None, facetMincount=None, facetMultiselect=None, timeout=60, **kwargs):
'\n Search GBIF occurrences\n\n :param taxonKey: [int] A GBIF occurrence identifier\n :param q: [str] Simple search parameter. The value for this parameter can be a simple word or a phrase.\n :param spellCheck: [bool] If ``True`` ask GBIF to check your spelling of the value passed to the ``search`` parameter.\n IMPORTANT: This only checks the input to the ``search`` parameter, and no others. Default: ``False``\n :param repatriated: [str] Searches for records whose publishing country is different to the country where the record was recorded in\n :param kingdomKey: [int] Kingdom classification key\n :param phylumKey: [int] Phylum classification key\n :param classKey: [int] Class classification key\n :param orderKey: [int] Order classification key\n :param familyKey: [int] Family classification key\n :param genusKey: [int] Genus classification key\n :param subgenusKey: [int] Subgenus classification key\n :param scientificName: [str] A scientific name from the GBIF backbone. All included and synonym taxa are included in the search.\n :param datasetKey: [str] The occurrence dataset key (a uuid)\n :param catalogNumber: [str] An identifier of any form assigned by the source within a physical collection or digital dataset for the record which may not unique, but should be fairly unique in combination with the institution and collection code.\n :param recordedBy: [str] The person who recorded the occurrence.\n :param recordedByID: [str] Identifier (e.g. ORCID) for the person who recorded the occurrence\n :param identifiedByID: [str] Identifier (e.g. ORCID) for the person who provided the taxonomic identification of the occurrence.\n :param collectionCode: [str] An identifier of any form assigned by the source to identify the physical collection or digital dataset uniquely within the text of an institution.\n :param institutionCode: [str] An identifier of any form assigned by the source to identify the institution the record belongs to. Not guaranteed to be que.\n :param country: [str] The 2-letter country code (as per ISO-3166-1) of the country in which the occurrence was recorded. See here http://en.wikipedia.org/wiki/ISO_3166-1_alpha-2\n :param basisOfRecord: [str] Basis of record, as defined in our BasisOfRecord enum here http://gbif.github.io/gbif-api/apidocs/org/gbif/api/vocabulary/BasisOfRecord.html Acceptable values are:\n\n - ``FOSSIL_SPECIMEN`` An occurrence record describing a fossilized specimen.\n - ``HUMAN_OBSERVATION`` An occurrence record describing an observation made by one or more people.\n - ``LIVING_SPECIMEN`` An occurrence record describing a living specimen.\n - ``MACHINE_OBSERVATION`` An occurrence record describing an observation made by a machine.\n - ``MATERIAL_CITATION`` An occurrence record based on a reference to a scholarly publication.\n - ``OBSERVATION`` An occurrence record describing an observation.\n - ``OCCURRENCE`` An existence of an organism at a particular place and time. No more specific basis.\n - ``PRESERVED_SPECIMEN`` An occurrence record describing a preserved specimen.\n\n :param eventDate: [date] Occurrence date in ISO 8601 format: yyyy, yyyy-MM, yyyy-MM-dd, or\n MM-dd. Supports range queries, smaller,larger (e.g., ``1990,1991``, whereas ``1991,1990``\n wouldn\'t work)\n :param year: [int] The 4 digit year. A year of 98 will be interpreted as AD 98. Supports range queries,\n smaller,larger (e.g., ``1990,1991``, whereas ``1991,1990`` wouldn\'t work)\n :param month: [int] The month of the year, starting with 1 for January. Supports range queries,\n smaller,larger (e.g., ``1,2``, whereas ``2,1`` wouldn\'t work)\n :param decimalLatitude: [float] Latitude in decimals between -90 and 90 based on WGS 84.\n Supports range queries, smaller,larger (e.g., ``25,30``, whereas ``30,25`` wouldn\'t work)\n :param decimalLongitude: [float] Longitude in decimals between -180 and 180 based on WGS 84.\n Supports range queries (e.g., ``-0.4,-0.2``, whereas ``-0.2,-0.4`` wouldn\'t work).\n :param publishingCountry: [str] The 2-letter country code (as per ISO-3166-1) of the\n country in which the occurrence was recorded.\n :param elevation: [int/str] Elevation in meters above sea level. Supports range queries, smaller,larger\n (e.g., ``5,30``, whereas ``30,5`` wouldn\'t work)\n :param depth: [int/str] Depth in meters relative to elevation. For example 10 meters below a\n lake surface with given elevation. Supports range queries, smaller,larger (e.g., ``5,30``,\n whereas ``30,5`` wouldn\'t work)\n :param geometry: [str] Searches for occurrences inside a polygon described in Well Known\n Text (WKT) format. A WKT shape written as either POINT, LINESTRING, LINEARRING\n POLYGON, or MULTIPOLYGON. Example of a polygon: ``((30.1 10.1, 20, 20 40, 40 40, 30.1 10.1))`` would be queried as http://bit.ly/1BzNwDq.\n Polygons must have counter-clockwise ordering of points.\n :param hasGeospatialIssue: [bool] Includes/excludes occurrence records which contain spatial\n issues (as determined in our record interpretation), i.e. ``hasGeospatialIssue=TRUE``\n returns only those records with spatial issues while ``hasGeospatialIssue=FALSE`` includes\n only records without spatial issues. The absence of this parameter returns any\n record with or without spatial issues.\n :param issue: [str] One or more of many possible issues with each occurrence record. See\n Details. Issues passed to this parameter filter results by the issue.\n :param hasCoordinate: [bool] Return only occurence records with lat/long data (``True``) or\n all records (``False``, default).\n :param typeStatus: [str] Type status of the specimen. One of many options. See ?typestatus\n :param recordNumber: [int] Number recorded by collector of the data, different from GBIF record\n number. See http://rs.tdwg.org/dwc/terms/#recordNumber} for more info\n :param lastInterpreted: [date] Date the record was last modified in GBIF, in ISO 8601 format:\n yyyy, yyyy-MM, yyyy-MM-dd, or MM-dd. Supports range queries, smaller,larger (e.g.,\n ``1990,1991``, whereas ``1991,1990`` wouldn\'t work)\n :param continent: [str] Continent. One of ``africa``, ``antarctica``, ``asia``, ``europe``, ``north_america``\n (North America includes the Caribbean and reachies down and includes Panama), ``oceania``,\n or ``south_america``\n :param fields: [str] Default (``all``) returns all fields. ``minimal`` returns just taxon name,\n key, latitude, and longitude. Or specify each field you want returned by name, e.g.\n ``fields = c(\'name\',\'latitude\',\'elevation\')``.\n :param mediatype: [str] Media type. Default is ``NULL``, so no filtering on mediatype. Options:\n ``NULL``, ``MovingImage``, ``Sound``, and ``StillImage``\n :param limit: [int] Number of results to return. Default: ``300``\n :param offset: [int] Record to start at. Default: ``0``\n :param facet: [str] a character vector of length 1 or greater\n :param establishmentMeans: [str] EstablishmentMeans, possible values include: INTRODUCED,\n INVASIVE, MANAGED, NATIVE, NATURALISED, UNCERTAIN\n :param facetMincount: [int] minimum number of records to be included in the faceting results\n :param facetMultiselect: [bool] Set to ``True`` to still return counts for values that are not currently\n filtered. See examples. Default: ``False``\n\n :return: A dictionary\n\n Usage::\n\n from pygbif import occurrences\n occurrences.search(taxonKey = 3329049)\n\n # Return 2 results, this is the default by the way\n occurrences.search(taxonKey=3329049, limit=2)\n\n # Instead of getting a taxon key first, you can search for a name directly\n # However, note that using this approach (with `scientificName="..."`)\n # you are getting synonyms too. The results for using `scientifcName` and\n # `taxonKey` parameters are the same in this case, but I wouldn\'t be surprised if for some\n # names they return different results\n occurrences.search(scientificName = \'Ursus americanus\')\n from pygbif import species\n key = species.name_backbone(name = \'Ursus americanus\', rank=\'species\')[\'usageKey\']\n occurrences.search(taxonKey = key)\n\n # Search by dataset key\n occurrences.search(datasetKey=\'7b5d6a48-f762-11e1-a439-00145eb45e9a\', limit=20)\n\n # Search by catalog number\n occurrences.search(catalogNumber="49366", limit=20)\n # occurrences.search(catalogNumber=["49366","Bird.27847588"], limit=20)\n\n # Use paging parameters (limit and offset) to page. Note the different results\n # for the two queries below.\n occurrences.search(datasetKey=\'7b5d6a48-f762-11e1-a439-00145eb45e9a\', offset=10, limit=5)\n occurrences.search(datasetKey=\'7b5d6a48-f762-11e1-a439-00145eb45e9a\', offset=20, limit=5)\n\n # Many dataset keys\n # occurrences.search(datasetKey=["50c9509d-22c7-4a22-a47d-8c48425ef4a7", "7b5d6a48-f762-11e1-a439-00145eb45e9a"], limit=20)\n\n # Search by collector name\n res = occurrences.search(recordedBy="smith", limit=20)\n [ x[\'recordedBy\'] for x in res[\'results\'] ]\n\n # Many collector names\n # occurrences.search(recordedBy=["smith","BJ Stacey"], limit=20)\n \n # recordedByID\n occurrences.search(recordedByID="https://orcid.org/0000-0003-1691-239X", limit = 3)\n\n # identifiedByID\n occurrences.search(identifiedByID="https://orcid.org/0000-0003-1691-239X", limit = 3)\n\n # Search for many species\n splist = [\'Cyanocitta stelleri\', \'Junco hyemalis\', \'Aix sponsa\']\n keys = [ species.name_suggest(x)[0][\'key\'] for x in splist ]\n out = [ occurrences.search(taxonKey = x, limit=1) for x in keys ]\n [ x[\'results\'][0][\'speciesKey\'] for x in out ]\n\n # Search - q parameter\n occurrences.search(q = "kingfisher", limit=20)\n ## spell check - only works with the `search` parameter\n ### spelled correctly - same result as above call\n occurrences.search(q = "kingfisher", limit=20, spellCheck = True)\n ### spelled incorrectly - stops with suggested spelling\n occurrences.search(q = "kajsdkla", limit=20, spellCheck = True)\n ### spelled incorrectly - stops with many suggested spellings\n ### and number of results for each\n occurrences.search(q = "helir", limit=20, spellCheck = True)\n\n # Search on latitidue and longitude\n occurrences.search(decimalLatitude=50, decimalLongitude=10, limit=2)\n\n # Search on a bounding box\n ## in well known text format\n occurrences.search(geometry=\'POLYGON((30.1 10.1, 10 20, 20 40, 40 40, 30.1 10.1))\', limit=20)\n from pygbif import species\n key = species.name_suggest(q=\'Aesculus hippocastanum\')[0][\'key\']\n occurrences.search(taxonKey=key, geometry=\'POLYGON((30.1 10.1, 10 20, 20 40, 40 40, 30.1 10.1))\', limit=20)\n ## multipolygon\n wkt = \'MULTIPOLYGON(((-123 38, -123 43, -116 43, -116 38, -123 38)),((-97 41, -97 45, -93 45, -93 41, -97 41)))\'\n occurrences.search(geometry = wkt, limit = 20)\n\n # Search on country\n occurrences.search(country=\'US\', limit=20)\n occurrences.search(country=\'FR\', limit=20)\n occurrences.search(country=\'DE\', limit=20)\n\n # Get only occurrences with lat/long data\n occurrences.search(taxonKey=key, hasCoordinate=True, limit=20)\n\n # Get only occurrences that were recorded as living specimens\n occurrences.search(taxonKey=key, basisOfRecord="LIVING_SPECIMEN", hasCoordinate=True, limit=20)\n\n # Get occurrences for a particular eventDate\n occurrences.search(taxonKey=key, eventDate="2013", limit=20)\n occurrences.search(taxonKey=key, year="2013", limit=20)\n occurrences.search(taxonKey=key, month="6", limit=20)\n\n # Get occurrences based on depth\n key = species.name_backbone(name=\'Salmo salar\', kingdom=\'animals\')[\'usageKey\']\n occurrences.search(taxonKey=key, depth="5", limit=20)\n\n # Get occurrences based on elevation\n key = species.name_backbone(name=\'Puma concolor\', kingdom=\'animals\')[\'usageKey\']\n occurrences.search(taxonKey=key, elevation=50, hasCoordinate=True, limit=20)\n\n # Get occurrences based on institutionCode\n occurrences.search(institutionCode="TLMF", limit=20)\n\n # Get occurrences based on collectionCode\n occurrences.search(collectionCode="Floristic Databases MV - Higher Plants", limit=20)\n\n # Get only those occurrences with spatial issues\n occurrences.search(taxonKey=key, hasGeospatialIssue=True, limit=20)\n\n # Search using a query string\n occurrences.search(q="kingfisher", limit=20)\n\n # Range queries\n ## See Detail for parameters that support range queries\n ### this is a range depth, with lower/upper limits in character string\n occurrences.search(depth=\'50,100\')\n\n ## Range search with year\n occurrences.search(year=\'1999,2000\', limit=20)\n\n ## Range search with latitude\n occurrences.search(decimalLatitude=\'29.59,29.6\')\n\n # Search by specimen type status\n ## Look for possible values of the typeStatus parameter looking at the typestatus dataset\n occurrences.search(typeStatus = \'allotype\')\n\n # Search by specimen record number\n ## This is the record number of the person/group that submitted the data, not GBIF\'s numbers\n ## You can see that many different groups have record number 1, so not super helpful\n occurrences.search(recordNumber = 1)\n\n # Search by last time interpreted: Date the record was last modified in GBIF\n ## The lastInterpreted parameter accepts ISO 8601 format dates, including\n ## yyyy, yyyy-MM, yyyy-MM-dd, or MM-dd. Range queries are accepted for lastInterpreted\n occurrences.search(lastInterpreted = \'2014-04-01\')\n\n # Search by continent\n ## One of africa, antarctica, asia, europe, north_america, oceania, or south_america\n occurrences.search(continent = \'south_america\')\n occurrences.search(continent = \'africa\')\n occurrences.search(continent = \'oceania\')\n occurrences.search(continent = \'antarctica\')\n\n # Search for occurrences with images\n occurrences.search(mediatype = \'StillImage\')\n occurrences.search(mediatype = \'MovingImage\')\n x = occurrences.search(mediatype = \'Sound\')\n [z[\'media\'] for z in x[\'results\']]\n\n # Query based on issues\n occurrences.search(taxonKey=1, issue=\'DEPTH_UNLIKELY\')\n occurrences.search(taxonKey=1, issue=[\'DEPTH_UNLIKELY\',\'COORDINATE_ROUNDED\'])\n # Show all records in the Arizona State Lichen Collection that cant be matched to the GBIF\n # backbone properly:\n occurrences.search(datasetKey=\'84c0e1a0-f762-11e1-a439-00145eb45e9a\', issue=[\'TAXON_MATCH_NONE\',\'TAXON_MATCH_HIGHERRANK\'])\n\n # If you pass in an invalid polygon you get hopefully informative errors\n ### the WKT string is fine, but GBIF says bad polygon\n wkt = \'POLYGON((-178.59375 64.83258989321493,-165.9375 59.24622380205539,\n -147.3046875 59.065977905449806,-130.78125 51.04484764446178,-125.859375 36.70806354647625,\n -112.1484375 23.367471303759686,-105.1171875 16.093320185359257,-86.8359375 9.23767076398516,\n -82.96875 2.9485268155066175,-82.6171875 -14.812060061226388,-74.8828125 -18.849111862023985,\n -77.34375 -47.661687803329166,-84.375 -49.975955187343295,174.7265625 -50.649460483096114,\n 179.296875 -42.19189902447192,-176.8359375 -35.634976650677295,176.8359375 -31.835565983656227,\n 163.4765625 -6.528187613695323,152.578125 1.894796132058301,135.703125 4.702353722559447,\n 127.96875 15.077427674847987,127.96875 23.689804541429606,139.921875 32.06861069132688,\n 149.4140625 42.65416193033991,159.2578125 48.3160811030533,168.3984375 57.019804336633165,\n 178.2421875 59.95776046458139,-179.6484375 61.16708631440347,-178.59375 64.83258989321493))\'\n occurrences.search(geometry = wkt)\n\n # Faceting\n ## return no occurrence records with limit=0\n x = occurrences.search(facet = "country", limit = 0)\n x[\'facets\']\n\n ## also return occurrence records\n x = occurrences.search(facet = "establishmentMeans", limit = 10)\n x[\'facets\']\n x[\'results\']\n\n ## multiple facet variables\n x = occurrences.search(facet = ["country", "basisOfRecord"], limit = 10)\n x[\'results\']\n x[\'facets\']\n x[\'facets\'][\'country\']\n x[\'facets\'][\'basisOfRecord\']\n x[\'facets\'][\'basisOfRecord\'][\'count\']\n\n ## set a minimum facet count\n x = occurrences.search(facet = "country", facetMincount = 30000000L, limit = 0)\n x[\'facets\']\n\n ## paging per each faceted variable\n ### do so by passing in variables like "country" + "_facetLimit" = "country_facetLimit"\n ### or "country" + "_facetOffset" = "country_facetOffset"\n x = occurrences.search(\n facet = ["country", "basisOfRecord", "hasCoordinate"],\n country_facetLimit = 3,\n basisOfRecord_facetLimit = 6,\n limit = 0\n )\n x[\'facets\']\n\n # requests package options\n ## There\'s an acceptable set of requests options ([\'timeout\', \'cookies\', \'auth\',\n ## \'allow_redirects\', \'proxies\', \'verify\', \'stream\', \'cert\']) you can pass\n ## in via **kwargs, e.g., set a timeout. Default timeout set to 60 seconds.\n x = occurrences.search(timeout = 1)\n '
url = (gbif_baseurl + 'occurrence/search')
args = {'taxonKey': taxonKey, 'repatriated': repatriated, 'kingdomKey': kingdomKey, 'phylumKey': phylumKey, 'classKey': classKey, 'orderKey': orderKey, 'familyKey': familyKey, 'genusKey': genusKey, 'subgenusKey': subgenusKey, 'scientificName': scientificName, 'country': country, 'publishingCountry': publishingCountry, 'hasCoordinate': bool2str(hasCoordinate), 'typeStatus': typeStatus, 'recordNumber': recordNumber, 'lastInterpreted': lastInterpreted, 'continent': continent, 'geometry': geometry, 'recordedBy': recordedBy, 'recordedByID': recordedByID, 'identifiedByID': identifiedByID, 'basisOfRecord': basisOfRecord, 'datasetKey': datasetKey, 'eventDate': eventDate, 'catalogNumber': catalogNumber, 'year': year, 'month': month, 'decimalLatitude': decimalLatitude, 'decimalLongitude': decimalLongitude, 'elevation': elevation, 'depth': depth, 'institutionCode': institutionCode, 'collectionCode': collectionCode, 'hasGeospatialIssue': bool2str(hasGeospatialIssue), 'issue': issue, 'q': q, 'spellCheck': bool2str(spellCheck), 'mediatype': mediatype, 'limit': limit, 'offset': offset, 'establishmentMeans': establishmentMeans, 'facetMincount': facetMincount, 'facet': facet, 'facetMultiselect': bool2str(facetMultiselect)}
gbif_kwargs = {key: kwargs[key] for key in kwargs if (key not in requests_argset)}
if (gbif_kwargs is not None):
xx = dict(zip([re.sub('_', '.', x) for x in gbif_kwargs.keys()], gbif_kwargs.values()))
args.update(xx)
kwargs = {key: kwargs[key] for key in kwargs if (key in requests_argset)}
out = gbif_GET(url, args, **kwargs)
return out | 2,407,195,931,292,612,000 | Search GBIF occurrences
:param taxonKey: [int] A GBIF occurrence identifier
:param q: [str] Simple search parameter. The value for this parameter can be a simple word or a phrase.
:param spellCheck: [bool] If ``True`` ask GBIF to check your spelling of the value passed to the ``search`` parameter.
IMPORTANT: This only checks the input to the ``search`` parameter, and no others. Default: ``False``
:param repatriated: [str] Searches for records whose publishing country is different to the country where the record was recorded in
:param kingdomKey: [int] Kingdom classification key
:param phylumKey: [int] Phylum classification key
:param classKey: [int] Class classification key
:param orderKey: [int] Order classification key
:param familyKey: [int] Family classification key
:param genusKey: [int] Genus classification key
:param subgenusKey: [int] Subgenus classification key
:param scientificName: [str] A scientific name from the GBIF backbone. All included and synonym taxa are included in the search.
:param datasetKey: [str] The occurrence dataset key (a uuid)
:param catalogNumber: [str] An identifier of any form assigned by the source within a physical collection or digital dataset for the record which may not unique, but should be fairly unique in combination with the institution and collection code.
:param recordedBy: [str] The person who recorded the occurrence.
:param recordedByID: [str] Identifier (e.g. ORCID) for the person who recorded the occurrence
:param identifiedByID: [str] Identifier (e.g. ORCID) for the person who provided the taxonomic identification of the occurrence.
:param collectionCode: [str] An identifier of any form assigned by the source to identify the physical collection or digital dataset uniquely within the text of an institution.
:param institutionCode: [str] An identifier of any form assigned by the source to identify the institution the record belongs to. Not guaranteed to be que.
:param country: [str] The 2-letter country code (as per ISO-3166-1) of the country in which the occurrence was recorded. See here http://en.wikipedia.org/wiki/ISO_3166-1_alpha-2
:param basisOfRecord: [str] Basis of record, as defined in our BasisOfRecord enum here http://gbif.github.io/gbif-api/apidocs/org/gbif/api/vocabulary/BasisOfRecord.html Acceptable values are:
- ``FOSSIL_SPECIMEN`` An occurrence record describing a fossilized specimen.
- ``HUMAN_OBSERVATION`` An occurrence record describing an observation made by one or more people.
- ``LIVING_SPECIMEN`` An occurrence record describing a living specimen.
- ``MACHINE_OBSERVATION`` An occurrence record describing an observation made by a machine.
- ``MATERIAL_CITATION`` An occurrence record based on a reference to a scholarly publication.
- ``OBSERVATION`` An occurrence record describing an observation.
- ``OCCURRENCE`` An existence of an organism at a particular place and time. No more specific basis.
- ``PRESERVED_SPECIMEN`` An occurrence record describing a preserved specimen.
:param eventDate: [date] Occurrence date in ISO 8601 format: yyyy, yyyy-MM, yyyy-MM-dd, or
MM-dd. Supports range queries, smaller,larger (e.g., ``1990,1991``, whereas ``1991,1990``
wouldn't work)
:param year: [int] The 4 digit year. A year of 98 will be interpreted as AD 98. Supports range queries,
smaller,larger (e.g., ``1990,1991``, whereas ``1991,1990`` wouldn't work)
:param month: [int] The month of the year, starting with 1 for January. Supports range queries,
smaller,larger (e.g., ``1,2``, whereas ``2,1`` wouldn't work)
:param decimalLatitude: [float] Latitude in decimals between -90 and 90 based on WGS 84.
Supports range queries, smaller,larger (e.g., ``25,30``, whereas ``30,25`` wouldn't work)
:param decimalLongitude: [float] Longitude in decimals between -180 and 180 based on WGS 84.
Supports range queries (e.g., ``-0.4,-0.2``, whereas ``-0.2,-0.4`` wouldn't work).
:param publishingCountry: [str] The 2-letter country code (as per ISO-3166-1) of the
country in which the occurrence was recorded.
:param elevation: [int/str] Elevation in meters above sea level. Supports range queries, smaller,larger
(e.g., ``5,30``, whereas ``30,5`` wouldn't work)
:param depth: [int/str] Depth in meters relative to elevation. For example 10 meters below a
lake surface with given elevation. Supports range queries, smaller,larger (e.g., ``5,30``,
whereas ``30,5`` wouldn't work)
:param geometry: [str] Searches for occurrences inside a polygon described in Well Known
Text (WKT) format. A WKT shape written as either POINT, LINESTRING, LINEARRING
POLYGON, or MULTIPOLYGON. Example of a polygon: ``((30.1 10.1, 20, 20 40, 40 40, 30.1 10.1))`` would be queried as http://bit.ly/1BzNwDq.
Polygons must have counter-clockwise ordering of points.
:param hasGeospatialIssue: [bool] Includes/excludes occurrence records which contain spatial
issues (as determined in our record interpretation), i.e. ``hasGeospatialIssue=TRUE``
returns only those records with spatial issues while ``hasGeospatialIssue=FALSE`` includes
only records without spatial issues. The absence of this parameter returns any
record with or without spatial issues.
:param issue: [str] One or more of many possible issues with each occurrence record. See
Details. Issues passed to this parameter filter results by the issue.
:param hasCoordinate: [bool] Return only occurence records with lat/long data (``True``) or
all records (``False``, default).
:param typeStatus: [str] Type status of the specimen. One of many options. See ?typestatus
:param recordNumber: [int] Number recorded by collector of the data, different from GBIF record
number. See http://rs.tdwg.org/dwc/terms/#recordNumber} for more info
:param lastInterpreted: [date] Date the record was last modified in GBIF, in ISO 8601 format:
yyyy, yyyy-MM, yyyy-MM-dd, or MM-dd. Supports range queries, smaller,larger (e.g.,
``1990,1991``, whereas ``1991,1990`` wouldn't work)
:param continent: [str] Continent. One of ``africa``, ``antarctica``, ``asia``, ``europe``, ``north_america``
(North America includes the Caribbean and reachies down and includes Panama), ``oceania``,
or ``south_america``
:param fields: [str] Default (``all``) returns all fields. ``minimal`` returns just taxon name,
key, latitude, and longitude. Or specify each field you want returned by name, e.g.
``fields = c('name','latitude','elevation')``.
:param mediatype: [str] Media type. Default is ``NULL``, so no filtering on mediatype. Options:
``NULL``, ``MovingImage``, ``Sound``, and ``StillImage``
:param limit: [int] Number of results to return. Default: ``300``
:param offset: [int] Record to start at. Default: ``0``
:param facet: [str] a character vector of length 1 or greater
:param establishmentMeans: [str] EstablishmentMeans, possible values include: INTRODUCED,
INVASIVE, MANAGED, NATIVE, NATURALISED, UNCERTAIN
:param facetMincount: [int] minimum number of records to be included in the faceting results
:param facetMultiselect: [bool] Set to ``True`` to still return counts for values that are not currently
filtered. See examples. Default: ``False``
:return: A dictionary
Usage::
from pygbif import occurrences
occurrences.search(taxonKey = 3329049)
# Return 2 results, this is the default by the way
occurrences.search(taxonKey=3329049, limit=2)
# Instead of getting a taxon key first, you can search for a name directly
# However, note that using this approach (with `scientificName="..."`)
# you are getting synonyms too. The results for using `scientifcName` and
# `taxonKey` parameters are the same in this case, but I wouldn't be surprised if for some
# names they return different results
occurrences.search(scientificName = 'Ursus americanus')
from pygbif import species
key = species.name_backbone(name = 'Ursus americanus', rank='species')['usageKey']
occurrences.search(taxonKey = key)
# Search by dataset key
occurrences.search(datasetKey='7b5d6a48-f762-11e1-a439-00145eb45e9a', limit=20)
# Search by catalog number
occurrences.search(catalogNumber="49366", limit=20)
# occurrences.search(catalogNumber=["49366","Bird.27847588"], limit=20)
# Use paging parameters (limit and offset) to page. Note the different results
# for the two queries below.
occurrences.search(datasetKey='7b5d6a48-f762-11e1-a439-00145eb45e9a', offset=10, limit=5)
occurrences.search(datasetKey='7b5d6a48-f762-11e1-a439-00145eb45e9a', offset=20, limit=5)
# Many dataset keys
# occurrences.search(datasetKey=["50c9509d-22c7-4a22-a47d-8c48425ef4a7", "7b5d6a48-f762-11e1-a439-00145eb45e9a"], limit=20)
# Search by collector name
res = occurrences.search(recordedBy="smith", limit=20)
[ x['recordedBy'] for x in res['results'] ]
# Many collector names
# occurrences.search(recordedBy=["smith","BJ Stacey"], limit=20)
# recordedByID
occurrences.search(recordedByID="https://orcid.org/0000-0003-1691-239X", limit = 3)
# identifiedByID
occurrences.search(identifiedByID="https://orcid.org/0000-0003-1691-239X", limit = 3)
# Search for many species
splist = ['Cyanocitta stelleri', 'Junco hyemalis', 'Aix sponsa']
keys = [ species.name_suggest(x)[0]['key'] for x in splist ]
out = [ occurrences.search(taxonKey = x, limit=1) for x in keys ]
[ x['results'][0]['speciesKey'] for x in out ]
# Search - q parameter
occurrences.search(q = "kingfisher", limit=20)
## spell check - only works with the `search` parameter
### spelled correctly - same result as above call
occurrences.search(q = "kingfisher", limit=20, spellCheck = True)
### spelled incorrectly - stops with suggested spelling
occurrences.search(q = "kajsdkla", limit=20, spellCheck = True)
### spelled incorrectly - stops with many suggested spellings
### and number of results for each
occurrences.search(q = "helir", limit=20, spellCheck = True)
# Search on latitidue and longitude
occurrences.search(decimalLatitude=50, decimalLongitude=10, limit=2)
# Search on a bounding box
## in well known text format
occurrences.search(geometry='POLYGON((30.1 10.1, 10 20, 20 40, 40 40, 30.1 10.1))', limit=20)
from pygbif import species
key = species.name_suggest(q='Aesculus hippocastanum')[0]['key']
occurrences.search(taxonKey=key, geometry='POLYGON((30.1 10.1, 10 20, 20 40, 40 40, 30.1 10.1))', limit=20)
## multipolygon
wkt = 'MULTIPOLYGON(((-123 38, -123 43, -116 43, -116 38, -123 38)),((-97 41, -97 45, -93 45, -93 41, -97 41)))'
occurrences.search(geometry = wkt, limit = 20)
# Search on country
occurrences.search(country='US', limit=20)
occurrences.search(country='FR', limit=20)
occurrences.search(country='DE', limit=20)
# Get only occurrences with lat/long data
occurrences.search(taxonKey=key, hasCoordinate=True, limit=20)
# Get only occurrences that were recorded as living specimens
occurrences.search(taxonKey=key, basisOfRecord="LIVING_SPECIMEN", hasCoordinate=True, limit=20)
# Get occurrences for a particular eventDate
occurrences.search(taxonKey=key, eventDate="2013", limit=20)
occurrences.search(taxonKey=key, year="2013", limit=20)
occurrences.search(taxonKey=key, month="6", limit=20)
# Get occurrences based on depth
key = species.name_backbone(name='Salmo salar', kingdom='animals')['usageKey']
occurrences.search(taxonKey=key, depth="5", limit=20)
# Get occurrences based on elevation
key = species.name_backbone(name='Puma concolor', kingdom='animals')['usageKey']
occurrences.search(taxonKey=key, elevation=50, hasCoordinate=True, limit=20)
# Get occurrences based on institutionCode
occurrences.search(institutionCode="TLMF", limit=20)
# Get occurrences based on collectionCode
occurrences.search(collectionCode="Floristic Databases MV - Higher Plants", limit=20)
# Get only those occurrences with spatial issues
occurrences.search(taxonKey=key, hasGeospatialIssue=True, limit=20)
# Search using a query string
occurrences.search(q="kingfisher", limit=20)
# Range queries
## See Detail for parameters that support range queries
### this is a range depth, with lower/upper limits in character string
occurrences.search(depth='50,100')
## Range search with year
occurrences.search(year='1999,2000', limit=20)
## Range search with latitude
occurrences.search(decimalLatitude='29.59,29.6')
# Search by specimen type status
## Look for possible values of the typeStatus parameter looking at the typestatus dataset
occurrences.search(typeStatus = 'allotype')
# Search by specimen record number
## This is the record number of the person/group that submitted the data, not GBIF's numbers
## You can see that many different groups have record number 1, so not super helpful
occurrences.search(recordNumber = 1)
# Search by last time interpreted: Date the record was last modified in GBIF
## The lastInterpreted parameter accepts ISO 8601 format dates, including
## yyyy, yyyy-MM, yyyy-MM-dd, or MM-dd. Range queries are accepted for lastInterpreted
occurrences.search(lastInterpreted = '2014-04-01')
# Search by continent
## One of africa, antarctica, asia, europe, north_america, oceania, or south_america
occurrences.search(continent = 'south_america')
occurrences.search(continent = 'africa')
occurrences.search(continent = 'oceania')
occurrences.search(continent = 'antarctica')
# Search for occurrences with images
occurrences.search(mediatype = 'StillImage')
occurrences.search(mediatype = 'MovingImage')
x = occurrences.search(mediatype = 'Sound')
[z['media'] for z in x['results']]
# Query based on issues
occurrences.search(taxonKey=1, issue='DEPTH_UNLIKELY')
occurrences.search(taxonKey=1, issue=['DEPTH_UNLIKELY','COORDINATE_ROUNDED'])
# Show all records in the Arizona State Lichen Collection that cant be matched to the GBIF
# backbone properly:
occurrences.search(datasetKey='84c0e1a0-f762-11e1-a439-00145eb45e9a', issue=['TAXON_MATCH_NONE','TAXON_MATCH_HIGHERRANK'])
# If you pass in an invalid polygon you get hopefully informative errors
### the WKT string is fine, but GBIF says bad polygon
wkt = 'POLYGON((-178.59375 64.83258989321493,-165.9375 59.24622380205539,
-147.3046875 59.065977905449806,-130.78125 51.04484764446178,-125.859375 36.70806354647625,
-112.1484375 23.367471303759686,-105.1171875 16.093320185359257,-86.8359375 9.23767076398516,
-82.96875 2.9485268155066175,-82.6171875 -14.812060061226388,-74.8828125 -18.849111862023985,
-77.34375 -47.661687803329166,-84.375 -49.975955187343295,174.7265625 -50.649460483096114,
179.296875 -42.19189902447192,-176.8359375 -35.634976650677295,176.8359375 -31.835565983656227,
163.4765625 -6.528187613695323,152.578125 1.894796132058301,135.703125 4.702353722559447,
127.96875 15.077427674847987,127.96875 23.689804541429606,139.921875 32.06861069132688,
149.4140625 42.65416193033991,159.2578125 48.3160811030533,168.3984375 57.019804336633165,
178.2421875 59.95776046458139,-179.6484375 61.16708631440347,-178.59375 64.83258989321493))'
occurrences.search(geometry = wkt)
# Faceting
## return no occurrence records with limit=0
x = occurrences.search(facet = "country", limit = 0)
x['facets']
## also return occurrence records
x = occurrences.search(facet = "establishmentMeans", limit = 10)
x['facets']
x['results']
## multiple facet variables
x = occurrences.search(facet = ["country", "basisOfRecord"], limit = 10)
x['results']
x['facets']
x['facets']['country']
x['facets']['basisOfRecord']
x['facets']['basisOfRecord']['count']
## set a minimum facet count
x = occurrences.search(facet = "country", facetMincount = 30000000L, limit = 0)
x['facets']
## paging per each faceted variable
### do so by passing in variables like "country" + "_facetLimit" = "country_facetLimit"
### or "country" + "_facetOffset" = "country_facetOffset"
x = occurrences.search(
facet = ["country", "basisOfRecord", "hasCoordinate"],
country_facetLimit = 3,
basisOfRecord_facetLimit = 6,
limit = 0
)
x['facets']
# requests package options
## There's an acceptable set of requests options (['timeout', 'cookies', 'auth',
## 'allow_redirects', 'proxies', 'verify', 'stream', 'cert']) you can pass
## in via **kwargs, e.g., set a timeout. Default timeout set to 60 seconds.
x = occurrences.search(timeout = 1) | pygbif/occurrences/search.py | search | livatras/pygbif | python | def search(taxonKey=None, repatriated=None, kingdomKey=None, phylumKey=None, classKey=None, orderKey=None, familyKey=None, genusKey=None, subgenusKey=None, scientificName=None, country=None, publishingCountry=None, hasCoordinate=None, typeStatus=None, recordNumber=None, lastInterpreted=None, continent=None, geometry=None, recordedBy=None, recordedByID=None, identifiedByID=None, basisOfRecord=None, datasetKey=None, eventDate=None, catalogNumber=None, year=None, month=None, decimalLatitude=None, decimalLongitude=None, elevation=None, depth=None, institutionCode=None, collectionCode=None, hasGeospatialIssue=None, issue=None, q=None, spellCheck=None, mediatype=None, limit=300, offset=0, establishmentMeans=None, facet=None, facetMincount=None, facetMultiselect=None, timeout=60, **kwargs):
'\n Search GBIF occurrences\n\n :param taxonKey: [int] A GBIF occurrence identifier\n :param q: [str] Simple search parameter. The value for this parameter can be a simple word or a phrase.\n :param spellCheck: [bool] If ``True`` ask GBIF to check your spelling of the value passed to the ``search`` parameter.\n IMPORTANT: This only checks the input to the ``search`` parameter, and no others. Default: ``False``\n :param repatriated: [str] Searches for records whose publishing country is different to the country where the record was recorded in\n :param kingdomKey: [int] Kingdom classification key\n :param phylumKey: [int] Phylum classification key\n :param classKey: [int] Class classification key\n :param orderKey: [int] Order classification key\n :param familyKey: [int] Family classification key\n :param genusKey: [int] Genus classification key\n :param subgenusKey: [int] Subgenus classification key\n :param scientificName: [str] A scientific name from the GBIF backbone. All included and synonym taxa are included in the search.\n :param datasetKey: [str] The occurrence dataset key (a uuid)\n :param catalogNumber: [str] An identifier of any form assigned by the source within a physical collection or digital dataset for the record which may not unique, but should be fairly unique in combination with the institution and collection code.\n :param recordedBy: [str] The person who recorded the occurrence.\n :param recordedByID: [str] Identifier (e.g. ORCID) for the person who recorded the occurrence\n :param identifiedByID: [str] Identifier (e.g. ORCID) for the person who provided the taxonomic identification of the occurrence.\n :param collectionCode: [str] An identifier of any form assigned by the source to identify the physical collection or digital dataset uniquely within the text of an institution.\n :param institutionCode: [str] An identifier of any form assigned by the source to identify the institution the record belongs to. Not guaranteed to be que.\n :param country: [str] The 2-letter country code (as per ISO-3166-1) of the country in which the occurrence was recorded. See here http://en.wikipedia.org/wiki/ISO_3166-1_alpha-2\n :param basisOfRecord: [str] Basis of record, as defined in our BasisOfRecord enum here http://gbif.github.io/gbif-api/apidocs/org/gbif/api/vocabulary/BasisOfRecord.html Acceptable values are:\n\n - ``FOSSIL_SPECIMEN`` An occurrence record describing a fossilized specimen.\n - ``HUMAN_OBSERVATION`` An occurrence record describing an observation made by one or more people.\n - ``LIVING_SPECIMEN`` An occurrence record describing a living specimen.\n - ``MACHINE_OBSERVATION`` An occurrence record describing an observation made by a machine.\n - ``MATERIAL_CITATION`` An occurrence record based on a reference to a scholarly publication.\n - ``OBSERVATION`` An occurrence record describing an observation.\n - ``OCCURRENCE`` An existence of an organism at a particular place and time. No more specific basis.\n - ``PRESERVED_SPECIMEN`` An occurrence record describing a preserved specimen.\n\n :param eventDate: [date] Occurrence date in ISO 8601 format: yyyy, yyyy-MM, yyyy-MM-dd, or\n MM-dd. Supports range queries, smaller,larger (e.g., ``1990,1991``, whereas ``1991,1990``\n wouldn\'t work)\n :param year: [int] The 4 digit year. A year of 98 will be interpreted as AD 98. Supports range queries,\n smaller,larger (e.g., ``1990,1991``, whereas ``1991,1990`` wouldn\'t work)\n :param month: [int] The month of the year, starting with 1 for January. Supports range queries,\n smaller,larger (e.g., ``1,2``, whereas ``2,1`` wouldn\'t work)\n :param decimalLatitude: [float] Latitude in decimals between -90 and 90 based on WGS 84.\n Supports range queries, smaller,larger (e.g., ``25,30``, whereas ``30,25`` wouldn\'t work)\n :param decimalLongitude: [float] Longitude in decimals between -180 and 180 based on WGS 84.\n Supports range queries (e.g., ``-0.4,-0.2``, whereas ``-0.2,-0.4`` wouldn\'t work).\n :param publishingCountry: [str] The 2-letter country code (as per ISO-3166-1) of the\n country in which the occurrence was recorded.\n :param elevation: [int/str] Elevation in meters above sea level. Supports range queries, smaller,larger\n (e.g., ``5,30``, whereas ``30,5`` wouldn\'t work)\n :param depth: [int/str] Depth in meters relative to elevation. For example 10 meters below a\n lake surface with given elevation. Supports range queries, smaller,larger (e.g., ``5,30``,\n whereas ``30,5`` wouldn\'t work)\n :param geometry: [str] Searches for occurrences inside a polygon described in Well Known\n Text (WKT) format. A WKT shape written as either POINT, LINESTRING, LINEARRING\n POLYGON, or MULTIPOLYGON. Example of a polygon: ``((30.1 10.1, 20, 20 40, 40 40, 30.1 10.1))`` would be queried as http://bit.ly/1BzNwDq.\n Polygons must have counter-clockwise ordering of points.\n :param hasGeospatialIssue: [bool] Includes/excludes occurrence records which contain spatial\n issues (as determined in our record interpretation), i.e. ``hasGeospatialIssue=TRUE``\n returns only those records with spatial issues while ``hasGeospatialIssue=FALSE`` includes\n only records without spatial issues. The absence of this parameter returns any\n record with or without spatial issues.\n :param issue: [str] One or more of many possible issues with each occurrence record. See\n Details. Issues passed to this parameter filter results by the issue.\n :param hasCoordinate: [bool] Return only occurence records with lat/long data (``True``) or\n all records (``False``, default).\n :param typeStatus: [str] Type status of the specimen. One of many options. See ?typestatus\n :param recordNumber: [int] Number recorded by collector of the data, different from GBIF record\n number. See http://rs.tdwg.org/dwc/terms/#recordNumber} for more info\n :param lastInterpreted: [date] Date the record was last modified in GBIF, in ISO 8601 format:\n yyyy, yyyy-MM, yyyy-MM-dd, or MM-dd. Supports range queries, smaller,larger (e.g.,\n ``1990,1991``, whereas ``1991,1990`` wouldn\'t work)\n :param continent: [str] Continent. One of ``africa``, ``antarctica``, ``asia``, ``europe``, ``north_america``\n (North America includes the Caribbean and reachies down and includes Panama), ``oceania``,\n or ``south_america``\n :param fields: [str] Default (``all``) returns all fields. ``minimal`` returns just taxon name,\n key, latitude, and longitude. Or specify each field you want returned by name, e.g.\n ``fields = c(\'name\',\'latitude\',\'elevation\')``.\n :param mediatype: [str] Media type. Default is ``NULL``, so no filtering on mediatype. Options:\n ``NULL``, ``MovingImage``, ``Sound``, and ``StillImage``\n :param limit: [int] Number of results to return. Default: ``300``\n :param offset: [int] Record to start at. Default: ``0``\n :param facet: [str] a character vector of length 1 or greater\n :param establishmentMeans: [str] EstablishmentMeans, possible values include: INTRODUCED,\n INVASIVE, MANAGED, NATIVE, NATURALISED, UNCERTAIN\n :param facetMincount: [int] minimum number of records to be included in the faceting results\n :param facetMultiselect: [bool] Set to ``True`` to still return counts for values that are not currently\n filtered. See examples. Default: ``False``\n\n :return: A dictionary\n\n Usage::\n\n from pygbif import occurrences\n occurrences.search(taxonKey = 3329049)\n\n # Return 2 results, this is the default by the way\n occurrences.search(taxonKey=3329049, limit=2)\n\n # Instead of getting a taxon key first, you can search for a name directly\n # However, note that using this approach (with `scientificName="..."`)\n # you are getting synonyms too. The results for using `scientifcName` and\n # `taxonKey` parameters are the same in this case, but I wouldn\'t be surprised if for some\n # names they return different results\n occurrences.search(scientificName = \'Ursus americanus\')\n from pygbif import species\n key = species.name_backbone(name = \'Ursus americanus\', rank=\'species\')[\'usageKey\']\n occurrences.search(taxonKey = key)\n\n # Search by dataset key\n occurrences.search(datasetKey=\'7b5d6a48-f762-11e1-a439-00145eb45e9a\', limit=20)\n\n # Search by catalog number\n occurrences.search(catalogNumber="49366", limit=20)\n # occurrences.search(catalogNumber=["49366","Bird.27847588"], limit=20)\n\n # Use paging parameters (limit and offset) to page. Note the different results\n # for the two queries below.\n occurrences.search(datasetKey=\'7b5d6a48-f762-11e1-a439-00145eb45e9a\', offset=10, limit=5)\n occurrences.search(datasetKey=\'7b5d6a48-f762-11e1-a439-00145eb45e9a\', offset=20, limit=5)\n\n # Many dataset keys\n # occurrences.search(datasetKey=["50c9509d-22c7-4a22-a47d-8c48425ef4a7", "7b5d6a48-f762-11e1-a439-00145eb45e9a"], limit=20)\n\n # Search by collector name\n res = occurrences.search(recordedBy="smith", limit=20)\n [ x[\'recordedBy\'] for x in res[\'results\'] ]\n\n # Many collector names\n # occurrences.search(recordedBy=["smith","BJ Stacey"], limit=20)\n \n # recordedByID\n occurrences.search(recordedByID="https://orcid.org/0000-0003-1691-239X", limit = 3)\n\n # identifiedByID\n occurrences.search(identifiedByID="https://orcid.org/0000-0003-1691-239X", limit = 3)\n\n # Search for many species\n splist = [\'Cyanocitta stelleri\', \'Junco hyemalis\', \'Aix sponsa\']\n keys = [ species.name_suggest(x)[0][\'key\'] for x in splist ]\n out = [ occurrences.search(taxonKey = x, limit=1) for x in keys ]\n [ x[\'results\'][0][\'speciesKey\'] for x in out ]\n\n # Search - q parameter\n occurrences.search(q = "kingfisher", limit=20)\n ## spell check - only works with the `search` parameter\n ### spelled correctly - same result as above call\n occurrences.search(q = "kingfisher", limit=20, spellCheck = True)\n ### spelled incorrectly - stops with suggested spelling\n occurrences.search(q = "kajsdkla", limit=20, spellCheck = True)\n ### spelled incorrectly - stops with many suggested spellings\n ### and number of results for each\n occurrences.search(q = "helir", limit=20, spellCheck = True)\n\n # Search on latitidue and longitude\n occurrences.search(decimalLatitude=50, decimalLongitude=10, limit=2)\n\n # Search on a bounding box\n ## in well known text format\n occurrences.search(geometry=\'POLYGON((30.1 10.1, 10 20, 20 40, 40 40, 30.1 10.1))\', limit=20)\n from pygbif import species\n key = species.name_suggest(q=\'Aesculus hippocastanum\')[0][\'key\']\n occurrences.search(taxonKey=key, geometry=\'POLYGON((30.1 10.1, 10 20, 20 40, 40 40, 30.1 10.1))\', limit=20)\n ## multipolygon\n wkt = \'MULTIPOLYGON(((-123 38, -123 43, -116 43, -116 38, -123 38)),((-97 41, -97 45, -93 45, -93 41, -97 41)))\'\n occurrences.search(geometry = wkt, limit = 20)\n\n # Search on country\n occurrences.search(country=\'US\', limit=20)\n occurrences.search(country=\'FR\', limit=20)\n occurrences.search(country=\'DE\', limit=20)\n\n # Get only occurrences with lat/long data\n occurrences.search(taxonKey=key, hasCoordinate=True, limit=20)\n\n # Get only occurrences that were recorded as living specimens\n occurrences.search(taxonKey=key, basisOfRecord="LIVING_SPECIMEN", hasCoordinate=True, limit=20)\n\n # Get occurrences for a particular eventDate\n occurrences.search(taxonKey=key, eventDate="2013", limit=20)\n occurrences.search(taxonKey=key, year="2013", limit=20)\n occurrences.search(taxonKey=key, month="6", limit=20)\n\n # Get occurrences based on depth\n key = species.name_backbone(name=\'Salmo salar\', kingdom=\'animals\')[\'usageKey\']\n occurrences.search(taxonKey=key, depth="5", limit=20)\n\n # Get occurrences based on elevation\n key = species.name_backbone(name=\'Puma concolor\', kingdom=\'animals\')[\'usageKey\']\n occurrences.search(taxonKey=key, elevation=50, hasCoordinate=True, limit=20)\n\n # Get occurrences based on institutionCode\n occurrences.search(institutionCode="TLMF", limit=20)\n\n # Get occurrences based on collectionCode\n occurrences.search(collectionCode="Floristic Databases MV - Higher Plants", limit=20)\n\n # Get only those occurrences with spatial issues\n occurrences.search(taxonKey=key, hasGeospatialIssue=True, limit=20)\n\n # Search using a query string\n occurrences.search(q="kingfisher", limit=20)\n\n # Range queries\n ## See Detail for parameters that support range queries\n ### this is a range depth, with lower/upper limits in character string\n occurrences.search(depth=\'50,100\')\n\n ## Range search with year\n occurrences.search(year=\'1999,2000\', limit=20)\n\n ## Range search with latitude\n occurrences.search(decimalLatitude=\'29.59,29.6\')\n\n # Search by specimen type status\n ## Look for possible values of the typeStatus parameter looking at the typestatus dataset\n occurrences.search(typeStatus = \'allotype\')\n\n # Search by specimen record number\n ## This is the record number of the person/group that submitted the data, not GBIF\'s numbers\n ## You can see that many different groups have record number 1, so not super helpful\n occurrences.search(recordNumber = 1)\n\n # Search by last time interpreted: Date the record was last modified in GBIF\n ## The lastInterpreted parameter accepts ISO 8601 format dates, including\n ## yyyy, yyyy-MM, yyyy-MM-dd, or MM-dd. Range queries are accepted for lastInterpreted\n occurrences.search(lastInterpreted = \'2014-04-01\')\n\n # Search by continent\n ## One of africa, antarctica, asia, europe, north_america, oceania, or south_america\n occurrences.search(continent = \'south_america\')\n occurrences.search(continent = \'africa\')\n occurrences.search(continent = \'oceania\')\n occurrences.search(continent = \'antarctica\')\n\n # Search for occurrences with images\n occurrences.search(mediatype = \'StillImage\')\n occurrences.search(mediatype = \'MovingImage\')\n x = occurrences.search(mediatype = \'Sound\')\n [z[\'media\'] for z in x[\'results\']]\n\n # Query based on issues\n occurrences.search(taxonKey=1, issue=\'DEPTH_UNLIKELY\')\n occurrences.search(taxonKey=1, issue=[\'DEPTH_UNLIKELY\',\'COORDINATE_ROUNDED\'])\n # Show all records in the Arizona State Lichen Collection that cant be matched to the GBIF\n # backbone properly:\n occurrences.search(datasetKey=\'84c0e1a0-f762-11e1-a439-00145eb45e9a\', issue=[\'TAXON_MATCH_NONE\',\'TAXON_MATCH_HIGHERRANK\'])\n\n # If you pass in an invalid polygon you get hopefully informative errors\n ### the WKT string is fine, but GBIF says bad polygon\n wkt = \'POLYGON((-178.59375 64.83258989321493,-165.9375 59.24622380205539,\n -147.3046875 59.065977905449806,-130.78125 51.04484764446178,-125.859375 36.70806354647625,\n -112.1484375 23.367471303759686,-105.1171875 16.093320185359257,-86.8359375 9.23767076398516,\n -82.96875 2.9485268155066175,-82.6171875 -14.812060061226388,-74.8828125 -18.849111862023985,\n -77.34375 -47.661687803329166,-84.375 -49.975955187343295,174.7265625 -50.649460483096114,\n 179.296875 -42.19189902447192,-176.8359375 -35.634976650677295,176.8359375 -31.835565983656227,\n 163.4765625 -6.528187613695323,152.578125 1.894796132058301,135.703125 4.702353722559447,\n 127.96875 15.077427674847987,127.96875 23.689804541429606,139.921875 32.06861069132688,\n 149.4140625 42.65416193033991,159.2578125 48.3160811030533,168.3984375 57.019804336633165,\n 178.2421875 59.95776046458139,-179.6484375 61.16708631440347,-178.59375 64.83258989321493))\'\n occurrences.search(geometry = wkt)\n\n # Faceting\n ## return no occurrence records with limit=0\n x = occurrences.search(facet = "country", limit = 0)\n x[\'facets\']\n\n ## also return occurrence records\n x = occurrences.search(facet = "establishmentMeans", limit = 10)\n x[\'facets\']\n x[\'results\']\n\n ## multiple facet variables\n x = occurrences.search(facet = ["country", "basisOfRecord"], limit = 10)\n x[\'results\']\n x[\'facets\']\n x[\'facets\'][\'country\']\n x[\'facets\'][\'basisOfRecord\']\n x[\'facets\'][\'basisOfRecord\'][\'count\']\n\n ## set a minimum facet count\n x = occurrences.search(facet = "country", facetMincount = 30000000L, limit = 0)\n x[\'facets\']\n\n ## paging per each faceted variable\n ### do so by passing in variables like "country" + "_facetLimit" = "country_facetLimit"\n ### or "country" + "_facetOffset" = "country_facetOffset"\n x = occurrences.search(\n facet = ["country", "basisOfRecord", "hasCoordinate"],\n country_facetLimit = 3,\n basisOfRecord_facetLimit = 6,\n limit = 0\n )\n x[\'facets\']\n\n # requests package options\n ## There\'s an acceptable set of requests options ([\'timeout\', \'cookies\', \'auth\',\n ## \'allow_redirects\', \'proxies\', \'verify\', \'stream\', \'cert\']) you can pass\n ## in via **kwargs, e.g., set a timeout. Default timeout set to 60 seconds.\n x = occurrences.search(timeout = 1)\n '
url = (gbif_baseurl + 'occurrence/search')
args = {'taxonKey': taxonKey, 'repatriated': repatriated, 'kingdomKey': kingdomKey, 'phylumKey': phylumKey, 'classKey': classKey, 'orderKey': orderKey, 'familyKey': familyKey, 'genusKey': genusKey, 'subgenusKey': subgenusKey, 'scientificName': scientificName, 'country': country, 'publishingCountry': publishingCountry, 'hasCoordinate': bool2str(hasCoordinate), 'typeStatus': typeStatus, 'recordNumber': recordNumber, 'lastInterpreted': lastInterpreted, 'continent': continent, 'geometry': geometry, 'recordedBy': recordedBy, 'recordedByID': recordedByID, 'identifiedByID': identifiedByID, 'basisOfRecord': basisOfRecord, 'datasetKey': datasetKey, 'eventDate': eventDate, 'catalogNumber': catalogNumber, 'year': year, 'month': month, 'decimalLatitude': decimalLatitude, 'decimalLongitude': decimalLongitude, 'elevation': elevation, 'depth': depth, 'institutionCode': institutionCode, 'collectionCode': collectionCode, 'hasGeospatialIssue': bool2str(hasGeospatialIssue), 'issue': issue, 'q': q, 'spellCheck': bool2str(spellCheck), 'mediatype': mediatype, 'limit': limit, 'offset': offset, 'establishmentMeans': establishmentMeans, 'facetMincount': facetMincount, 'facet': facet, 'facetMultiselect': bool2str(facetMultiselect)}
gbif_kwargs = {key: kwargs[key] for key in kwargs if (key not in requests_argset)}
if (gbif_kwargs is not None):
xx = dict(zip([re.sub('_', '.', x) for x in gbif_kwargs.keys()], gbif_kwargs.values()))
args.update(xx)
kwargs = {key: kwargs[key] for key in kwargs if (key in requests_argset)}
out = gbif_GET(url, args, **kwargs)
return out |
def __init__(self, id=None, data=None):
'\n DestinationIdSchema - a model defined in Swagger\n\n :param dict swaggerTypes: The key is attribute name\n and the value is attribute type.\n :param dict attributeMap: The key is attribute name\n and the value is json key in definition.\n '
self.swagger_types = {'id': 'str', 'data': 'DestinationSchema'}
self.attribute_map = {'id': 'id', 'data': 'data'}
self._id = id
self._data = data | -1,036,892,525,717,189,400 | DestinationIdSchema - a model defined in Swagger
:param dict swaggerTypes: The key is attribute name
and the value is attribute type.
:param dict attributeMap: The key is attribute name
and the value is json key in definition. | rustici_software_cloud_v2/models/destination_id_schema.py | __init__ | ryanhope2/scormcloud-api-v2-client-python | python | def __init__(self, id=None, data=None):
'\n DestinationIdSchema - a model defined in Swagger\n\n :param dict swaggerTypes: The key is attribute name\n and the value is attribute type.\n :param dict attributeMap: The key is attribute name\n and the value is json key in definition.\n '
self.swagger_types = {'id': 'str', 'data': 'DestinationSchema'}
self.attribute_map = {'id': 'id', 'data': 'data'}
self._id = id
self._data = data |
@property
def id(self):
'\n Gets the id of this DestinationIdSchema.\n \n\n :return: The id of this DestinationIdSchema.\n :rtype: str\n '
return self._id | -4,756,714,808,268,342,000 | Gets the id of this DestinationIdSchema.
:return: The id of this DestinationIdSchema.
:rtype: str | rustici_software_cloud_v2/models/destination_id_schema.py | id | ryanhope2/scormcloud-api-v2-client-python | python | @property
def id(self):
'\n Gets the id of this DestinationIdSchema.\n \n\n :return: The id of this DestinationIdSchema.\n :rtype: str\n '
return self._id |
@id.setter
def id(self, id):
'\n Sets the id of this DestinationIdSchema.\n \n\n :param id: The id of this DestinationIdSchema.\n :type: str\n '
self._id = id | -2,075,493,263,701,627,100 | Sets the id of this DestinationIdSchema.
:param id: The id of this DestinationIdSchema.
:type: str | rustici_software_cloud_v2/models/destination_id_schema.py | id | ryanhope2/scormcloud-api-v2-client-python | python | @id.setter
def id(self, id):
'\n Sets the id of this DestinationIdSchema.\n \n\n :param id: The id of this DestinationIdSchema.\n :type: str\n '
self._id = id |
@property
def data(self):
'\n Gets the data of this DestinationIdSchema.\n\n :return: The data of this DestinationIdSchema.\n :rtype: DestinationSchema\n '
return self._data | 6,491,617,717,676,747,000 | Gets the data of this DestinationIdSchema.
:return: The data of this DestinationIdSchema.
:rtype: DestinationSchema | rustici_software_cloud_v2/models/destination_id_schema.py | data | ryanhope2/scormcloud-api-v2-client-python | python | @property
def data(self):
'\n Gets the data of this DestinationIdSchema.\n\n :return: The data of this DestinationIdSchema.\n :rtype: DestinationSchema\n '
return self._data |
@data.setter
def data(self, data):
'\n Sets the data of this DestinationIdSchema.\n\n :param data: The data of this DestinationIdSchema.\n :type: DestinationSchema\n '
self._data = data | -7,656,567,686,224,259,000 | Sets the data of this DestinationIdSchema.
:param data: The data of this DestinationIdSchema.
:type: DestinationSchema | rustici_software_cloud_v2/models/destination_id_schema.py | data | ryanhope2/scormcloud-api-v2-client-python | python | @data.setter
def data(self, data):
'\n Sets the data of this DestinationIdSchema.\n\n :param data: The data of this DestinationIdSchema.\n :type: DestinationSchema\n '
self._data = data |
def to_dict(self):
'\n Returns the model properties as a dict\n '
result = {}
for (attr, _) in iteritems(self.swagger_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map((lambda x: (x.to_dict() if hasattr(x, 'to_dict') else x)), value))
elif hasattr(value, 'to_dict'):
result[attr] = value.to_dict()
elif isinstance(value, dict):
result[attr] = dict(map((lambda item: ((item[0], item[1].to_dict()) if hasattr(item[1], 'to_dict') else item)), value.items()))
else:
result[attr] = value
return result | 2,191,974,537,531,847,000 | Returns the model properties as a dict | rustici_software_cloud_v2/models/destination_id_schema.py | to_dict | ryanhope2/scormcloud-api-v2-client-python | python | def to_dict(self):
'\n \n '
result = {}
for (attr, _) in iteritems(self.swagger_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map((lambda x: (x.to_dict() if hasattr(x, 'to_dict') else x)), value))
elif hasattr(value, 'to_dict'):
result[attr] = value.to_dict()
elif isinstance(value, dict):
result[attr] = dict(map((lambda item: ((item[0], item[1].to_dict()) if hasattr(item[1], 'to_dict') else item)), value.items()))
else:
result[attr] = value
return result |
def to_str(self):
'\n Returns the string representation of the model\n '
return pformat(self.to_dict()) | -3,531,024,894,346,511,000 | Returns the string representation of the model | rustici_software_cloud_v2/models/destination_id_schema.py | to_str | ryanhope2/scormcloud-api-v2-client-python | python | def to_str(self):
'\n \n '
return pformat(self.to_dict()) |
def __repr__(self):
'\n For `print` and `pprint`\n '
return self.to_str() | 5,853,962,500,611,353,000 | For `print` and `pprint` | rustici_software_cloud_v2/models/destination_id_schema.py | __repr__ | ryanhope2/scormcloud-api-v2-client-python | python | def __repr__(self):
'\n \n '
return self.to_str() |
def __eq__(self, other):
'\n Returns true if both objects are equal\n '
if (not isinstance(other, DestinationIdSchema)):
return False
return (self.__dict__ == other.__dict__) | 5,572,630,834,681,360,000 | Returns true if both objects are equal | rustici_software_cloud_v2/models/destination_id_schema.py | __eq__ | ryanhope2/scormcloud-api-v2-client-python | python | def __eq__(self, other):
'\n \n '
if (not isinstance(other, DestinationIdSchema)):
return False
return (self.__dict__ == other.__dict__) |
def __ne__(self, other):
'\n Returns true if both objects are not equal\n '
return (not (self == other)) | 3,600,423,175,817,510,400 | Returns true if both objects are not equal | rustici_software_cloud_v2/models/destination_id_schema.py | __ne__ | ryanhope2/scormcloud-api-v2-client-python | python | def __ne__(self, other):
'\n \n '
return (not (self == other)) |
def load_data(data_dir):
'Load the train/val data.'
data_transforms = {'train': transforms.Compose([transforms.RandomResizedCrop(224), transforms.RandomHorizontalFlip(), transforms.ToTensor(), transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])]), 'val': transforms.Compose([transforms.Resize(256), transforms.CenterCrop(224), transforms.ToTensor(), transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])])}
image_datasets = {x: datasets.ImageFolder(os.path.join(data_dir, x), data_transforms[x]) for x in ['train', 'val']}
dataloaders = {x: torch.utils.data.DataLoader(image_datasets[x], batch_size=4, shuffle=True, num_workers=4) for x in ['train', 'val']}
dataset_sizes = {x: len(image_datasets[x]) for x in ['train', 'val']}
class_names = image_datasets['train'].classes
return (dataloaders, dataset_sizes, class_names) | 2,688,968,184,329,373,000 | Load the train/val data. | azure-ml-pipelines/pytorch/training-folder/pytorch_train.py | load_data | hudua/azureml | python | def load_data(data_dir):
data_transforms = {'train': transforms.Compose([transforms.RandomResizedCrop(224), transforms.RandomHorizontalFlip(), transforms.ToTensor(), transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])]), 'val': transforms.Compose([transforms.Resize(256), transforms.CenterCrop(224), transforms.ToTensor(), transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])])}
image_datasets = {x: datasets.ImageFolder(os.path.join(data_dir, x), data_transforms[x]) for x in ['train', 'val']}
dataloaders = {x: torch.utils.data.DataLoader(image_datasets[x], batch_size=4, shuffle=True, num_workers=4) for x in ['train', 'val']}
dataset_sizes = {x: len(image_datasets[x]) for x in ['train', 'val']}
class_names = image_datasets['train'].classes
return (dataloaders, dataset_sizes, class_names) |
def train_model(model, criterion, optimizer, scheduler, num_epochs, data_dir):
'Train the model.'
(dataloaders, dataset_sizes, class_names) = load_data(data_dir)
device = torch.device(('cuda:0' if torch.cuda.is_available() else 'cpu'))
since = time.time()
best_model_wts = copy.deepcopy(model.state_dict())
best_acc = 0.0
for epoch in range(num_epochs):
print('Epoch {}/{}'.format(epoch, (num_epochs - 1)))
print(('-' * 10))
for phase in ['train', 'val']:
if (phase == 'train'):
scheduler.step()
model.train()
else:
model.eval()
running_loss = 0.0
running_corrects = 0
for (inputs, labels) in dataloaders[phase]:
inputs = inputs.to(device)
labels = labels.to(device)
optimizer.zero_grad()
with torch.set_grad_enabled((phase == 'train')):
outputs = model(inputs)
(_, preds) = torch.max(outputs, 1)
loss = criterion(outputs, labels)
if (phase == 'train'):
loss.backward()
optimizer.step()
running_loss += (loss.item() * inputs.size(0))
running_corrects += torch.sum((preds == labels.data))
epoch_loss = (running_loss / dataset_sizes[phase])
epoch_acc = (running_corrects.double() / dataset_sizes[phase])
print('{} Loss: {:.4f} Acc: {:.4f}'.format(phase, epoch_loss, epoch_acc))
if ((phase == 'val') and (epoch_acc > best_acc)):
best_acc = epoch_acc
best_model_wts = copy.deepcopy(model.state_dict())
run.log('best_val_acc', np.float(best_acc))
print()
time_elapsed = (time.time() - since)
print('Training complete in {:.0f}m {:.0f}s'.format((time_elapsed // 60), (time_elapsed % 60)))
print('Best val Acc: {:4f}'.format(best_acc))
model.load_state_dict(best_model_wts)
return model | -1,306,633,351,554,523,000 | Train the model. | azure-ml-pipelines/pytorch/training-folder/pytorch_train.py | train_model | hudua/azureml | python | def train_model(model, criterion, optimizer, scheduler, num_epochs, data_dir):
(dataloaders, dataset_sizes, class_names) = load_data(data_dir)
device = torch.device(('cuda:0' if torch.cuda.is_available() else 'cpu'))
since = time.time()
best_model_wts = copy.deepcopy(model.state_dict())
best_acc = 0.0
for epoch in range(num_epochs):
print('Epoch {}/{}'.format(epoch, (num_epochs - 1)))
print(('-' * 10))
for phase in ['train', 'val']:
if (phase == 'train'):
scheduler.step()
model.train()
else:
model.eval()
running_loss = 0.0
running_corrects = 0
for (inputs, labels) in dataloaders[phase]:
inputs = inputs.to(device)
labels = labels.to(device)
optimizer.zero_grad()
with torch.set_grad_enabled((phase == 'train')):
outputs = model(inputs)
(_, preds) = torch.max(outputs, 1)
loss = criterion(outputs, labels)
if (phase == 'train'):
loss.backward()
optimizer.step()
running_loss += (loss.item() * inputs.size(0))
running_corrects += torch.sum((preds == labels.data))
epoch_loss = (running_loss / dataset_sizes[phase])
epoch_acc = (running_corrects.double() / dataset_sizes[phase])
print('{} Loss: {:.4f} Acc: {:.4f}'.format(phase, epoch_loss, epoch_acc))
if ((phase == 'val') and (epoch_acc > best_acc)):
best_acc = epoch_acc
best_model_wts = copy.deepcopy(model.state_dict())
run.log('best_val_acc', np.float(best_acc))
print()
time_elapsed = (time.time() - since)
print('Training complete in {:.0f}m {:.0f}s'.format((time_elapsed // 60), (time_elapsed % 60)))
print('Best val Acc: {:4f}'.format(best_acc))
model.load_state_dict(best_model_wts)
return model |
def fine_tune_model(num_epochs, data_dir, learning_rate, momentum):
'Load a pretrained model and reset the final fully connected layer.'
run.log('lr', np.float(learning_rate))
run.log('momentum', np.float(momentum))
model_ft = models.resnet18(pretrained=True)
num_ftrs = model_ft.fc.in_features
model_ft.fc = nn.Linear(num_ftrs, 2)
device = torch.device(('cuda:0' if torch.cuda.is_available() else 'cpu'))
model_ft = model_ft.to(device)
criterion = nn.CrossEntropyLoss()
optimizer_ft = optim.SGD(model_ft.parameters(), lr=learning_rate, momentum=momentum)
exp_lr_scheduler = lr_scheduler.StepLR(optimizer_ft, step_size=7, gamma=0.1)
model = train_model(model_ft, criterion, optimizer_ft, exp_lr_scheduler, num_epochs, data_dir)
return model | 7,668,973,453,640,657,000 | Load a pretrained model and reset the final fully connected layer. | azure-ml-pipelines/pytorch/training-folder/pytorch_train.py | fine_tune_model | hudua/azureml | python | def fine_tune_model(num_epochs, data_dir, learning_rate, momentum):
run.log('lr', np.float(learning_rate))
run.log('momentum', np.float(momentum))
model_ft = models.resnet18(pretrained=True)
num_ftrs = model_ft.fc.in_features
model_ft.fc = nn.Linear(num_ftrs, 2)
device = torch.device(('cuda:0' if torch.cuda.is_available() else 'cpu'))
model_ft = model_ft.to(device)
criterion = nn.CrossEntropyLoss()
optimizer_ft = optim.SGD(model_ft.parameters(), lr=learning_rate, momentum=momentum)
exp_lr_scheduler = lr_scheduler.StepLR(optimizer_ft, step_size=7, gamma=0.1)
model = train_model(model_ft, criterion, optimizer_ft, exp_lr_scheduler, num_epochs, data_dir)
return model |
def load_model(model_path: str) -> None:
'\n 模型加载\n @param model_path: 模型文件夹路径\n @return:\n '
global kge_model, entity2id, id2entity, relation2id, all_true_triples, args
args = DotMap(json.load(codecs.open(os.path.join(model_path, 'config.json'), 'r', encoding='utf-8')))
(entity2id, id2entity, relation2id, id2relation, all_true_triples) = get_entity_relation_with_id(args.data_path)
kge_model = KGEModel(model_name=args.model, nentity=args.nentity, nrelation=args.nrelation, hidden_dim=args.hidden_dim, gamma=args.gamma, double_entity_embedding=args.double_entity_embedding, double_relation_embedding=args.double_relation_embedding)
if args.cuda:
kge_model = kge_model.cuda()
checkpoint = torch.load(os.path.join(args.init_checkpoint, 'checkpoint'))
kge_model.load_state_dict(checkpoint['model_state_dict']) | -1,381,956,851,112,199,000 | 模型加载
@param model_path: 模型文件夹路径
@return: | project/knowledge_graph_embedding/project_distmult_rotate_transe/service.py | load_model | Jianhan-Liu/solid_ai_waddle | python | def load_model(model_path: str) -> None:
'\n 模型加载\n @param model_path: 模型文件夹路径\n @return:\n '
global kge_model, entity2id, id2entity, relation2id, all_true_triples, args
args = DotMap(json.load(codecs.open(os.path.join(model_path, 'config.json'), 'r', encoding='utf-8')))
(entity2id, id2entity, relation2id, id2relation, all_true_triples) = get_entity_relation_with_id(args.data_path)
kge_model = KGEModel(model_name=args.model, nentity=args.nentity, nrelation=args.nrelation, hidden_dim=args.hidden_dim, gamma=args.gamma, double_entity_embedding=args.double_entity_embedding, double_relation_embedding=args.double_relation_embedding)
if args.cuda:
kge_model = kge_model.cuda()
checkpoint = torch.load(os.path.join(args.init_checkpoint, 'checkpoint'))
kge_model.load_state_dict(checkpoint['model_state_dict']) |
def inference(target_triple: str) -> Dict:
"\n 推理函数\n @param target_triple: 目标需预测三元组：'头实体 关系 尾实体'\n @return: 头尾实体的10个预测结果\n "
if (kge_model is None):
return {'预测结果': '提醒：模型未加载'}
try:
target_triple = target_triple.split()
head = entity2id[target_triple[0]]
tail = entity2id[target_triple[2]]
relation = relation2id[target_triple[1]]
target_triple = [(head, relation, tail)]
except KeyError as e:
return {'预测结果': f'实体或者关系 <{e}> 不存在，请确保输入的实体或者关系已存在。'}
prediction = kge_model.test_step(kge_model, target_triple, all_true_triples, args, True)
head_entity_prediction = [id2entity[str(idx)] for idx in prediction['head_predict']]
tail_entity_prediction = [id2entity[str(idx)] for idx in prediction['tail_predict']]
result = {'头实体预测结果': head_entity_prediction, '尾实体预测结果': tail_entity_prediction}
return result | -4,453,249,678,169,298,400 | 推理函数
@param target_triple: 目标需预测三元组：'头实体 关系 尾实体'
@return: 头尾实体的10个预测结果 | project/knowledge_graph_embedding/project_distmult_rotate_transe/service.py | inference | Jianhan-Liu/solid_ai_waddle | python | def inference(target_triple: str) -> Dict:
"\n 推理函数\n @param target_triple: 目标需预测三元组：'头实体 关系 尾实体'\n @return: 头尾实体的10个预测结果\n "
if (kge_model is None):
return {'预测结果': '提醒：模型未加载'}
try:
target_triple = target_triple.split()
head = entity2id[target_triple[0]]
tail = entity2id[target_triple[2]]
relation = relation2id[target_triple[1]]
target_triple = [(head, relation, tail)]
except KeyError as e:
return {'预测结果': f'实体或者关系 <{e}> 不存在，请确保输入的实体或者关系已存在。'}
prediction = kge_model.test_step(kge_model, target_triple, all_true_triples, args, True)
head_entity_prediction = [id2entity[str(idx)] for idx in prediction['head_predict']]
tail_entity_prediction = [id2entity[str(idx)] for idx in prediction['tail_predict']]
result = {'头实体预测结果': head_entity_prediction, '尾实体预测结果': tail_entity_prediction}
return result |
def _looks_like_asgi3(app):
'\n Try to figure out if an application object supports ASGI3.\n\n This is how uvicorn figures out the application version as well.\n '
if inspect.isclass(app):
return hasattr(app, '__await__')
elif inspect.isfunction(app):
return asyncio.iscoroutinefunction(app)
else:
call = getattr(app, '__call__', None)
return asyncio.iscoroutinefunction(call) | -1,719,280,184,835,323,600 | Try to figure out if an application object supports ASGI3.
This is how uvicorn figures out the application version as well. | sentry_sdk/integrations/asgi.py | _looks_like_asgi3 | cuenca-mx/sentry-python | python | def _looks_like_asgi3(app):
'\n Try to figure out if an application object supports ASGI3.\n\n This is how uvicorn figures out the application version as well.\n '
if inspect.isclass(app):
return hasattr(app, '__await__')
elif inspect.isfunction(app):
return asyncio.iscoroutinefunction(app)
else:
call = getattr(app, '__call__', None)
return asyncio.iscoroutinefunction(call) |
def __init__(self, app, unsafe_context_data=False):
'\n Instrument an ASGI application with Sentry. Provides HTTP/websocket\n data to sent events and basic handling for exceptions bubbling up\n through the middleware.\n\n :param unsafe_context_data: Disable errors when a proper contextvars installation could not be found. We do not recommend changing this from the default.\n '
if ((not unsafe_context_data) and (not HAS_REAL_CONTEXTVARS)):
raise RuntimeError(('The ASGI middleware for Sentry requires Python 3.7+ or the aiocontextvars package.' + CONTEXTVARS_ERROR_MESSAGE))
self.app = app
if _looks_like_asgi3(app):
self.__call__ = self._run_asgi3
else:
self.__call__ = self._run_asgi2 | 4,878,474,847,215,512,000 | Instrument an ASGI application with Sentry. Provides HTTP/websocket
data to sent events and basic handling for exceptions bubbling up
through the middleware.
:param unsafe_context_data: Disable errors when a proper contextvars installation could not be found. We do not recommend changing this from the default. | sentry_sdk/integrations/asgi.py | __init__ | cuenca-mx/sentry-python | python | def __init__(self, app, unsafe_context_data=False):
'\n Instrument an ASGI application with Sentry. Provides HTTP/websocket\n data to sent events and basic handling for exceptions bubbling up\n through the middleware.\n\n :param unsafe_context_data: Disable errors when a proper contextvars installation could not be found. We do not recommend changing this from the default.\n '
if ((not unsafe_context_data) and (not HAS_REAL_CONTEXTVARS)):
raise RuntimeError(('The ASGI middleware for Sentry requires Python 3.7+ or the aiocontextvars package.' + CONTEXTVARS_ERROR_MESSAGE))
self.app = app
if _looks_like_asgi3(app):
self.__call__ = self._run_asgi3
else:
self.__call__ = self._run_asgi2 |
def _get_url(self, scope, default_scheme, host):
'\n Extract URL from the ASGI scope, without also including the querystring.\n '
scheme = scope.get('scheme', default_scheme)
server = scope.get('server', None)
path = (scope.get('root_path', '') + scope.get('path', ''))
if host:
return ('%s://%s%s' % (scheme, host, path))
if (server is not None):
(host, port) = server
default_port = {'http': 80, 'https': 443, 'ws': 80, 'wss': 443}[scheme]
if (port != default_port):
return ('%s://%s:%s%s' % (scheme, host, port, path))
return ('%s://%s%s' % (scheme, host, path))
return path | 456,696,316,022,871,940 | Extract URL from the ASGI scope, without also including the querystring. | sentry_sdk/integrations/asgi.py | _get_url | cuenca-mx/sentry-python | python | def _get_url(self, scope, default_scheme, host):
'\n \n '
scheme = scope.get('scheme', default_scheme)
server = scope.get('server', None)
path = (scope.get('root_path', ) + scope.get('path', ))
if host:
return ('%s://%s%s' % (scheme, host, path))
if (server is not None):
(host, port) = server
default_port = {'http': 80, 'https': 443, 'ws': 80, 'wss': 443}[scheme]
if (port != default_port):
return ('%s://%s:%s%s' % (scheme, host, port, path))
return ('%s://%s%s' % (scheme, host, path))
return path |
def _get_query(self, scope):
'\n Extract querystring from the ASGI scope, in the format that the Sentry protocol expects.\n '
qs = scope.get('query_string')
if (not qs):
return None
return urllib.parse.unquote(qs.decode('latin-1')) | -3,749,750,348,190,675,000 | Extract querystring from the ASGI scope, in the format that the Sentry protocol expects. | sentry_sdk/integrations/asgi.py | _get_query | cuenca-mx/sentry-python | python | def _get_query(self, scope):
'\n \n '
qs = scope.get('query_string')
if (not qs):
return None
return urllib.parse.unquote(qs.decode('latin-1')) |
def _get_headers(self, scope):
'\n Extract headers from the ASGI scope, in the format that the Sentry protocol expects.\n '
headers = {}
for (raw_key, raw_value) in scope['headers']:
key = raw_key.decode('latin-1')
value = raw_value.decode('latin-1')
if (key in headers):
headers[key] = ((headers[key] + ', ') + value)
else:
headers[key] = value
return headers | -2,763,036,242,865,239,000 | Extract headers from the ASGI scope, in the format that the Sentry protocol expects. | sentry_sdk/integrations/asgi.py | _get_headers | cuenca-mx/sentry-python | python | def _get_headers(self, scope):
'\n \n '
headers = {}
for (raw_key, raw_value) in scope['headers']:
key = raw_key.decode('latin-1')
value = raw_value.decode('latin-1')
if (key in headers):
headers[key] = ((headers[key] + ', ') + value)
else:
headers[key] = value
return headers |
def text2phone(text, language):
'\n Convert graphemes to phonemes.\n '
seperator = phonemizer.separator.Separator(' |', '', '|')
punctuations = re.findall(PHONEME_PUNCTUATION_PATTERN, text)
if (version.parse(phonemizer.__version__) < version.parse('2.1')):
ph = phonemize(text, separator=seperator, strip=False, njobs=1, backend='espeak', language=language)
ph = ph[:(- 1)].strip()
if punctuations:
if (text[(- 1)] == punctuations[(- 1)]):
for punct in punctuations[:(- 1)]:
ph = ph.replace('| |\n', (('|' + punct) + '| |'), 1)
ph = (ph + punctuations[(- 1)])
else:
for punct in punctuations:
ph = ph.replace('| |\n', (('|' + punct) + '| |'), 1)
elif (version.parse(phonemizer.__version__) >= version.parse('2.1')):
ph = phonemize(text, separator=seperator, strip=False, njobs=1, backend='espeak', language=language, preserve_punctuation=True)
if punctuations:
for punctuation in punctuations:
ph = ph.replace(f'| |{punctuation} ', f'|{punctuation}| |').replace(f'| |{punctuation}', f'|{punctuation}| |')
ph = ph[:(- 3)]
else:
raise RuntimeError(" [!] Use 'phonemizer' version 2.1 or older.")
return ph | -8,971,153,413,979,716,000 | Convert graphemes to phonemes. | utils/text/__init__.py | text2phone | DanBmh/TTS | python | def text2phone(text, language):
'\n \n '
seperator = phonemizer.separator.Separator(' |', , '|')
punctuations = re.findall(PHONEME_PUNCTUATION_PATTERN, text)
if (version.parse(phonemizer.__version__) < version.parse('2.1')):
ph = phonemize(text, separator=seperator, strip=False, njobs=1, backend='espeak', language=language)
ph = ph[:(- 1)].strip()
if punctuations:
if (text[(- 1)] == punctuations[(- 1)]):
for punct in punctuations[:(- 1)]:
ph = ph.replace('| |\n', (('|' + punct) + '| |'), 1)
ph = (ph + punctuations[(- 1)])
else:
for punct in punctuations:
ph = ph.replace('| |\n', (('|' + punct) + '| |'), 1)
elif (version.parse(phonemizer.__version__) >= version.parse('2.1')):
ph = phonemize(text, separator=seperator, strip=False, njobs=1, backend='espeak', language=language, preserve_punctuation=True)
if punctuations:
for punctuation in punctuations:
ph = ph.replace(f'| |{punctuation} ', f'|{punctuation}| |').replace(f'| |{punctuation}', f'|{punctuation}| |')
ph = ph[:(- 3)]
else:
raise RuntimeError(" [!] Use 'phonemizer' version 2.1 or older.")
return ph |
def sequence_to_phoneme(sequence, tp=None):
'Converts a sequence of IDs back to a string'
global _id_to_phonemes
result = ''
if tp:
(_, _phonemes) = make_symbols(**tp)
_id_to_phonemes = {i: s for (i, s) in enumerate(_phonemes)}
for symbol_id in sequence:
if (symbol_id in _id_to_phonemes):
s = _id_to_phonemes[symbol_id]
result += s
return result.replace('}{', ' ') | 6,434,912,201,758,388,000 | Converts a sequence of IDs back to a string | utils/text/__init__.py | sequence_to_phoneme | DanBmh/TTS | python | def sequence_to_phoneme(sequence, tp=None):
global _id_to_phonemes
result =
if tp:
(_, _phonemes) = make_symbols(**tp)
_id_to_phonemes = {i: s for (i, s) in enumerate(_phonemes)}
for symbol_id in sequence:
if (symbol_id in _id_to_phonemes):
s = _id_to_phonemes[symbol_id]
result += s
return result.replace('}{', ' ') |
def text_to_sequence(text, cleaner_names, tp=None):
'Converts a string of text to a sequence of IDs corresponding to the symbols in the text.\n\n The text can optionally have ARPAbet sequences enclosed in curly braces embedded\n in it. For example, "Turn left on {HH AW1 S S T AH0 N} Street."\n\n Args:\n text: string to convert to a sequence\n cleaner_names: names of the cleaner functions to run the text through\n\n Returns:\n List of integers corresponding to the symbols in the text\n '
global _symbol_to_id
if tp:
(_symbols, _) = make_symbols(**tp)
_symbol_to_id = {s: i for (i, s) in enumerate(_symbols)}
sequence = []
while text:
m = _CURLY_RE.match(text)
if (not m):
sequence += _symbols_to_sequence(_clean_text(text, cleaner_names))
break
sequence += _symbols_to_sequence(_clean_text(m.group(1), cleaner_names))
sequence += _arpabet_to_sequence(m.group(2))
text = m.group(3)
return sequence | -863,534,234,504,303,600 | Converts a string of text to a sequence of IDs corresponding to the symbols in the text.
The text can optionally have ARPAbet sequences enclosed in curly braces embedded
in it. For example, "Turn left on {HH AW1 S S T AH0 N} Street."
Args:
text: string to convert to a sequence
cleaner_names: names of the cleaner functions to run the text through
Returns:
List of integers corresponding to the symbols in the text | utils/text/__init__.py | text_to_sequence | DanBmh/TTS | python | def text_to_sequence(text, cleaner_names, tp=None):
'Converts a string of text to a sequence of IDs corresponding to the symbols in the text.\n\n The text can optionally have ARPAbet sequences enclosed in curly braces embedded\n in it. For example, "Turn left on {HH AW1 S S T AH0 N} Street."\n\n Args:\n text: string to convert to a sequence\n cleaner_names: names of the cleaner functions to run the text through\n\n Returns:\n List of integers corresponding to the symbols in the text\n '
global _symbol_to_id
if tp:
(_symbols, _) = make_symbols(**tp)
_symbol_to_id = {s: i for (i, s) in enumerate(_symbols)}
sequence = []
while text:
m = _CURLY_RE.match(text)
if (not m):
sequence += _symbols_to_sequence(_clean_text(text, cleaner_names))
break
sequence += _symbols_to_sequence(_clean_text(m.group(1), cleaner_names))
sequence += _arpabet_to_sequence(m.group(2))
text = m.group(3)
return sequence |
def sequence_to_text(sequence, tp=None):
'Converts a sequence of IDs back to a string'
global _id_to_symbol
if tp:
(_symbols, _) = make_symbols(**tp)
_id_to_symbol = {i: s for (i, s) in enumerate(_symbols)}
result = ''
for symbol_id in sequence:
if (symbol_id in _id_to_symbol):
s = _id_to_symbol[symbol_id]
if ((len(s) > 1) and (s[0] == '@')):
s = ('{%s}' % s[1:])
result += s
return result.replace('}{', ' ') | -3,614,943,435,538,793,500 | Converts a sequence of IDs back to a string | utils/text/__init__.py | sequence_to_text | DanBmh/TTS | python | def sequence_to_text(sequence, tp=None):
global _id_to_symbol
if tp:
(_symbols, _) = make_symbols(**tp)
_id_to_symbol = {i: s for (i, s) in enumerate(_symbols)}
result =
for symbol_id in sequence:
if (symbol_id in _id_to_symbol):
s = _id_to_symbol[symbol_id]
if ((len(s) > 1) and (s[0] == '@')):
s = ('{%s}' % s[1:])
result += s
return result.replace('}{', ' ') |
def validate_subdirectory_string(subdirectory_str):
' Validate subdirectory string '
if (not subdirectory_str.isascii()):
raise argparse.ArgumentTypeError(('%s contains non ascii characters' % subdirectory_str))
if subdirectory_str.startswith('/'):
subdirectory_str = subdirectory_str[1:]
if subdirectory_str.endswith('/'):
subdirectory_str = subdirectory_str[:(- 1)]
site_config.set_subdirectory(subdirectory_str)
return subdirectory_str | 9,133,025,839,659,418,000 | Validate subdirectory string | update-attack.py | validate_subdirectory_string | Alexander-RB/attack-website | python | def validate_subdirectory_string(subdirectory_str):
' '
if (not subdirectory_str.isascii()):
raise argparse.ArgumentTypeError(('%s contains non ascii characters' % subdirectory_str))
if subdirectory_str.startswith('/'):
subdirectory_str = subdirectory_str[1:]
if subdirectory_str.endswith('/'):
subdirectory_str = subdirectory_str[:(- 1)]
site_config.set_subdirectory(subdirectory_str)
return subdirectory_str |
def get_parsed_args():
'Create argument parser and parse arguments'
parser = argparse.ArgumentParser(description='Build the ATT&CK website.\nAll flags are optional. If you run the build without flags, the modules that pertain to the ATT&CK dataset will be ran. If you would like to run extra modules, opt-in these modules with the--extras flag.')
parser.add_argument('--refresh', '-r', action='store_true', help='Pull down the current STIX data from the MITRE/CTI GitHub respository')
parser.add_argument('--no-stix-link-replacement', action='store_true', help='If this flag is absent, links to attack.mitre.org/[page] in the STIX data will be replaced with /[page]. Add this flag to preserve links to attack.mitre.org.')
parser.add_argument('--modules', '-m', nargs='+', type=str, choices=module_choices, help="Run specific modules by selecting from the list and leaving one space in between them. For example: '-m clean techniques tactics'.Will run all the modules if flag is not called, or selected without arguments.")
parser.add_argument('--extras', '-e', nargs='*', type=str, choices=extras, help="Run extra modules that do not pertain to the ATT&CK dataset. Select from the list and leaving one space in between them. For example: '-m resources blog'.\nThese modules will only run if the user adds this flag. Calling this flag without arguments will select all the extra modules.")
parser.add_argument('--test', '-t', nargs='+', choices=test_choices, dest='tests', help="Run specific tests by selecting from the list and leaving one space in between them. For example: '-t output links'. Tests: size (size of output directory against github pages limit); links (dead internal hyperlinks and relative hyperlinks); external_links (dead external hyperlinks); citations (unparsed citation text).")
parser.add_argument('--attack-brand', action='store_true', help='Applies ATT&CK brand colors. See also the --extras flag.')
parser.add_argument('--proxy', help='set proxy')
parser.add_argument('--subdirectory', help='If you intend to host the site from a sub-directory, specify the directory using this flag.', type=validate_subdirectory_string)
parser.add_argument('--print-tests', dest='print_tests', action='store_true', help='Force test output to print to stdout even if the results are very long.')
parser.add_argument('--no-test-exitstatus', dest='override_exit_status', action='store_true', help='Forces application to exit with success status codes even if tests fail.')
args = parser.parse_args()
if (not args.modules):
args.modules = module_choices
if ((not args.extras) and isinstance(args.extras, list)):
args.extras = extras
site_config.args = args
return args | 3,227,462,813,491,606,500 | Create argument parser and parse arguments | update-attack.py | get_parsed_args | Alexander-RB/attack-website | python | def get_parsed_args():
parser = argparse.ArgumentParser(description='Build the ATT&CK website.\nAll flags are optional. If you run the build without flags, the modules that pertain to the ATT&CK dataset will be ran. If you would like to run extra modules, opt-in these modules with the--extras flag.')
parser.add_argument('--refresh', '-r', action='store_true', help='Pull down the current STIX data from the MITRE/CTI GitHub respository')
parser.add_argument('--no-stix-link-replacement', action='store_true', help='If this flag is absent, links to attack.mitre.org/[page] in the STIX data will be replaced with /[page]. Add this flag to preserve links to attack.mitre.org.')
parser.add_argument('--modules', '-m', nargs='+', type=str, choices=module_choices, help="Run specific modules by selecting from the list and leaving one space in between them. For example: '-m clean techniques tactics'.Will run all the modules if flag is not called, or selected without arguments.")
parser.add_argument('--extras', '-e', nargs='*', type=str, choices=extras, help="Run extra modules that do not pertain to the ATT&CK dataset. Select from the list and leaving one space in between them. For example: '-m resources blog'.\nThese modules will only run if the user adds this flag. Calling this flag without arguments will select all the extra modules.")
parser.add_argument('--test', '-t', nargs='+', choices=test_choices, dest='tests', help="Run specific tests by selecting from the list and leaving one space in between them. For example: '-t output links'. Tests: size (size of output directory against github pages limit); links (dead internal hyperlinks and relative hyperlinks); external_links (dead external hyperlinks); citations (unparsed citation text).")
parser.add_argument('--attack-brand', action='store_true', help='Applies ATT&CK brand colors. See also the --extras flag.')
parser.add_argument('--proxy', help='set proxy')
parser.add_argument('--subdirectory', help='If you intend to host the site from a sub-directory, specify the directory using this flag.', type=validate_subdirectory_string)
parser.add_argument('--print-tests', dest='print_tests', action='store_true', help='Force test output to print to stdout even if the results are very long.')
parser.add_argument('--no-test-exitstatus', dest='override_exit_status', action='store_true', help='Forces application to exit with success status codes even if tests fail.')
args = parser.parse_args()
if (not args.modules):
args.modules = module_choices
if ((not args.extras) and isinstance(args.extras, list)):
args.extras = extras
site_config.args = args
return args |
def remove_from_build(arg_modules, arg_extras):
' Given a list of modules from command line, remove modules that appear in module\n directory that are not in list.\n '
def remove_from_running_pool():
' Remove modules from running pool if they are not in modules list from argument '
copy_of_modules = []
for module in modules.run_ptr:
if (module['name'].lower() in arg_modules):
copy_of_modules.append(module)
modules.run_ptr = copy_of_modules
def remove_from_menu():
' Remove modules from menu if they are not in modules list from argument '
copy_of_menu = []
for module in modules.menu_ptr:
if (module['name'].lower() in arg_modules):
copy_of_menu.append(module)
modules.menu_ptr = copy_of_menu
if arg_extras:
arg_modules = (arg_modules + arg_extras)
remove_from_running_pool()
remove_from_menu() | -4,698,552,695,145,996,000 | Given a list of modules from command line, remove modules that appear in module
directory that are not in list. | update-attack.py | remove_from_build | Alexander-RB/attack-website | python | def remove_from_build(arg_modules, arg_extras):
' Given a list of modules from command line, remove modules that appear in module\n directory that are not in list.\n '
def remove_from_running_pool():
' Remove modules from running pool if they are not in modules list from argument '
copy_of_modules = []
for module in modules.run_ptr:
if (module['name'].lower() in arg_modules):
copy_of_modules.append(module)
modules.run_ptr = copy_of_modules
def remove_from_menu():
' Remove modules from menu if they are not in modules list from argument '
copy_of_menu = []
for module in modules.menu_ptr:
if (module['name'].lower() in arg_modules):
copy_of_menu.append(module)
modules.menu_ptr = copy_of_menu
if arg_extras:
arg_modules = (arg_modules + arg_extras)
remove_from_running_pool()
remove_from_menu() |
def remove_from_running_pool():
' Remove modules from running pool if they are not in modules list from argument '
copy_of_modules = []
for module in modules.run_ptr:
if (module['name'].lower() in arg_modules):
copy_of_modules.append(module)
modules.run_ptr = copy_of_modules | -6,515,811,293,937,717,000 | Remove modules from running pool if they are not in modules list from argument | update-attack.py | remove_from_running_pool | Alexander-RB/attack-website | python | def remove_from_running_pool():
' '
copy_of_modules = []
for module in modules.run_ptr:
if (module['name'].lower() in arg_modules):
copy_of_modules.append(module)
modules.run_ptr = copy_of_modules |
def remove_from_menu():
' Remove modules from menu if they are not in modules list from argument '
copy_of_menu = []
for module in modules.menu_ptr:
if (module['name'].lower() in arg_modules):
copy_of_menu.append(module)
modules.menu_ptr = copy_of_menu | -6,787,491,815,310,537,000 | Remove modules from menu if they are not in modules list from argument | update-attack.py | remove_from_menu | Alexander-RB/attack-website | python | def remove_from_menu():
' '
copy_of_menu = []
for module in modules.menu_ptr:
if (module['name'].lower() in arg_modules):
copy_of_menu.append(module)
modules.menu_ptr = copy_of_menu |
def run_command(command, display_cmd=False, ignore_error=False, print_to_console=True):
'Run bash command and print output to stdout\n '
if (display_cmd == True):
click.echo((click.style('Running command: ', fg='cyan') + click.style(command, fg='green')))
proc = subprocess.Popen(command, shell=True, text=True, stdout=subprocess.PIPE)
(out, err) = proc.communicate()
if ((len(out) > 0) and print_to_console):
click.echo(out)
if ((proc.returncode != 0) and (not ignore_error)):
sys.exit(proc.returncode)
return (out, err) | 3,621,573,615,239,375,400 | Run bash command and print output to stdout | show/plugins/mlnx.py | run_command | AshokDaparthi/sonic-utilities | python | def run_command(command, display_cmd=False, ignore_error=False, print_to_console=True):
'\n '
if (display_cmd == True):
click.echo((click.style('Running command: ', fg='cyan') + click.style(command, fg='green')))
proc = subprocess.Popen(command, shell=True, text=True, stdout=subprocess.PIPE)
(out, err) = proc.communicate()
if ((len(out) > 0) and print_to_console):
click.echo(out)
if ((proc.returncode != 0) and (not ignore_error)):
sys.exit(proc.returncode)
return (out, err) |
@click.group()
def mlnx():
' Show Mellanox platform information '
pass | -8,046,836,575,544,220,000 | Show Mellanox platform information | show/plugins/mlnx.py | mlnx | AshokDaparthi/sonic-utilities | python | @click.group()
def mlnx():
' '
pass |
def is_issu_status_enabled():
' This function parses the SAI XML profile used for mlnx to\n get whether ISSU is enabled or disabled\n @return: True/False\n '
issu_enabled = False
sai_profile_path = '/{}/sai.profile'.format(HWSKU_PATH)
DOCKER_CAT_COMMAND = 'docker exec {container_name} cat {path}'
command = DOCKER_CAT_COMMAND.format(container_name=CONTAINER_NAME, path=sai_profile_path)
(sai_profile_content, _) = run_command(command, print_to_console=False)
sai_profile_kvs = {}
for line in sai_profile_content.split('\n'):
if (not (SAI_PROFILE_DELIMITER in line)):
continue
(key, value) = line.split(SAI_PROFILE_DELIMITER)
sai_profile_kvs[key] = value.strip()
try:
sai_xml_path = sai_profile_kvs['SAI_INIT_CONFIG_FILE']
except KeyError:
click.echo('Failed to get SAI XML from sai profile', err=True)
sys.exit(1)
command = DOCKER_CAT_COMMAND.format(container_name=CONTAINER_NAME, path=sai_xml_path)
(sai_xml_content, _) = run_command(command, print_to_console=False)
try:
root = ET.fromstring(sai_xml_content)
except ET.ParseError:
click.echo('Failed to parse SAI xml', err=True)
sys.exit(1)
el = root.find('platform_info').find('issu-enabled')
if (el is not None):
issu_enabled = (int(el.text) == 1)
return issu_enabled | 8,463,833,370,658,066,000 | This function parses the SAI XML profile used for mlnx to
get whether ISSU is enabled or disabled
@return: True/False | show/plugins/mlnx.py | is_issu_status_enabled | AshokDaparthi/sonic-utilities | python | def is_issu_status_enabled():
' This function parses the SAI XML profile used for mlnx to\n get whether ISSU is enabled or disabled\n @return: True/False\n '
issu_enabled = False
sai_profile_path = '/{}/sai.profile'.format(HWSKU_PATH)
DOCKER_CAT_COMMAND = 'docker exec {container_name} cat {path}'
command = DOCKER_CAT_COMMAND.format(container_name=CONTAINER_NAME, path=sai_profile_path)
(sai_profile_content, _) = run_command(command, print_to_console=False)
sai_profile_kvs = {}
for line in sai_profile_content.split('\n'):
if (not (SAI_PROFILE_DELIMITER in line)):
continue
(key, value) = line.split(SAI_PROFILE_DELIMITER)
sai_profile_kvs[key] = value.strip()
try:
sai_xml_path = sai_profile_kvs['SAI_INIT_CONFIG_FILE']
except KeyError:
click.echo('Failed to get SAI XML from sai profile', err=True)
sys.exit(1)
command = DOCKER_CAT_COMMAND.format(container_name=CONTAINER_NAME, path=sai_xml_path)
(sai_xml_content, _) = run_command(command, print_to_console=False)
try:
root = ET.fromstring(sai_xml_content)
except ET.ParseError:
click.echo('Failed to parse SAI xml', err=True)
sys.exit(1)
el = root.find('platform_info').find('issu-enabled')
if (el is not None):
issu_enabled = (int(el.text) == 1)
return issu_enabled |
@mlnx.command('sniffer')
def sniffer_status():
' Show sniffer status '
components = ['sdk']
env_variable_strings = [ENV_VARIABLE_SX_SNIFFER]
for index in range(len(components)):
enabled = sniffer_status_get(env_variable_strings[index])
if (enabled is True):
click.echo((components[index] + ' sniffer is enabled'))
else:
click.echo((components[index] + ' sniffer is disabled')) | 131,115,497,342,275,740 | Show sniffer status | show/plugins/mlnx.py | sniffer_status | AshokDaparthi/sonic-utilities | python | @mlnx.command('sniffer')
def sniffer_status():
' '
components = ['sdk']
env_variable_strings = [ENV_VARIABLE_SX_SNIFFER]
for index in range(len(components)):
enabled = sniffer_status_get(env_variable_strings[index])
if (enabled is True):
click.echo((components[index] + ' sniffer is enabled'))
else:
click.echo((components[index] + ' sniffer is disabled')) |
@mlnx.command('issu')
def issu_status():
' Show ISSU status '
res = is_issu_status_enabled()
click.echo(('ISSU is enabled' if res else 'ISSU is disabled')) | -331,031,383,470,014,140 | Show ISSU status | show/plugins/mlnx.py | issu_status | AshokDaparthi/sonic-utilities | python | @mlnx.command('issu')
def issu_status():
' '
res = is_issu_status_enabled()
click.echo(('ISSU is enabled' if res else 'ISSU is disabled')) |
def make_meshgrid(x, y, h=0.02):
'Create a mesh of points to plot in\n\n Parameters\n ----------\n x: data to base x-axis meshgrid on\n y: data to base y-axis meshgrid on\n h: stepsize for meshgrid, optional\n\n Returns\n -------\n xx, yy : ndarray\n '
(x_min, x_max) = ((x.min() - 1), (x.max() + 1))
(y_min, y_max) = ((y.min() - 1), (y.max() + 1))
(xx, yy) = np.meshgrid(np.arange(x_min, x_max, h), np.arange(y_min, y_max, h))
return (xx, yy) | -4,317,779,463,543,041,500 | Create a mesh of points to plot in
Parameters
----------
x: data to base x-axis meshgrid on
y: data to base y-axis meshgrid on
h: stepsize for meshgrid, optional
Returns
-------
xx, yy : ndarray | main.py | make_meshgrid | MartimChaves/ret_detect | python | def make_meshgrid(x, y, h=0.02):
'Create a mesh of points to plot in\n\n Parameters\n ----------\n x: data to base x-axis meshgrid on\n y: data to base y-axis meshgrid on\n h: stepsize for meshgrid, optional\n\n Returns\n -------\n xx, yy : ndarray\n '
(x_min, x_max) = ((x.min() - 1), (x.max() + 1))
(y_min, y_max) = ((y.min() - 1), (y.max() + 1))
(xx, yy) = np.meshgrid(np.arange(x_min, x_max, h), np.arange(y_min, y_max, h))
return (xx, yy) |
def plot_contours(ax, clf, xx, yy, proba=False, **params):
'Plot the decision boundaries for a classifier.\n\n Parameters\n ----------\n ax: matplotlib axes object\n clf: a classifier\n xx: meshgrid ndarray\n yy: meshgrid ndarray\n params: dictionary of params to pass to contourf, optional\n '
if proba:
Z = clf.predict_proba(np.c_[(xx.ravel(), yy.ravel())])[:, (- 1)]
else:
Z = clf.predict(np.c_[(xx.ravel(), yy.ravel())])
Z = Z.reshape(xx.shape)
out = ax.contourf(xx, yy, Z, 20, **params)
return out | -8,037,834,054,018,846,000 | Plot the decision boundaries for a classifier.
Parameters
----------
ax: matplotlib axes object
clf: a classifier
xx: meshgrid ndarray
yy: meshgrid ndarray
params: dictionary of params to pass to contourf, optional | main.py | plot_contours | MartimChaves/ret_detect | python | def plot_contours(ax, clf, xx, yy, proba=False, **params):
'Plot the decision boundaries for a classifier.\n\n Parameters\n ----------\n ax: matplotlib axes object\n clf: a classifier\n xx: meshgrid ndarray\n yy: meshgrid ndarray\n params: dictionary of params to pass to contourf, optional\n '
if proba:
Z = clf.predict_proba(np.c_[(xx.ravel(), yy.ravel())])[:, (- 1)]
else:
Z = clf.predict(np.c_[(xx.ravel(), yy.ravel())])
Z = Z.reshape(xx.shape)
out = ax.contourf(xx, yy, Z, 20, **params)
return out |
def apply(self, context, clear, split, check_for_existing=True, **kwargs):
'Extract Candidates from a Context'
if (not isinstance(context, Sentence)):
raise NotImplementedError(('%s is currently only implemented for Sentence contexts.' % self.__name__))
entity_idxs = dict(((et, defaultdict(list)) for et in set(self.entity_types)))
L = len(context.words)
for i in range(L):
if (context.entity_types[i] is not None):
ets = context.entity_types[i].split(self.entity_sep)
cids = context.entity_cids[i].split(self.entity_sep)
for (et, cid) in zip(ets, cids):
if (et in entity_idxs):
entity_idxs[et][cid].append(i)
entity_spans = defaultdict(list)
entity_cids = {}
for (et, cid_idxs) in iteritems(entity_idxs):
for (cid, idxs) in iteritems(entity_idxs[et]):
while (len(idxs) > 0):
i = idxs.pop(0)
char_start = context.char_offsets[i]
char_end = ((char_start + len(context.words[i])) - 1)
while ((len(idxs) > 0) and (idxs[0] == (i + 1))):
i = idxs.pop(0)
char_end = ((context.char_offsets[i] + len(context.words[i])) - 1)
tc = TemporarySpan(char_start=char_start, char_end=char_end, sentence=context)
tc.load_id_or_insert(self.session)
entity_cids[tc.id] = cid
entity_spans[et].append(tc)
candidate_args = {'split': split}
for args in product(*[enumerate(entity_spans[et]) for et in self.entity_types]):
if (self.arity == 2):
(ai, a) = args[0]
(bi, b) = args[1]
if ((not self.self_relations) and (a == b)):
continue
elif ((not self.nested_relations) and ((a in b) or (b in a))):
continue
elif ((not self.symmetric_relations) and (ai > bi)):
continue
for (i, arg_name) in enumerate(self.candidate_class.__argnames__):
candidate_args[(arg_name + '_id')] = args[i][1].id
candidate_args[(arg_name + '_cid')] = entity_cids[args[i][1].id]
if check_for_existing:
q = select([self.candidate_class.id])
for (key, value) in iteritems(candidate_args):
q = q.where((getattr(self.candidate_class, key) == value))
candidate_id = self.session.execute(q).first()
if (candidate_id is not None):
continue
(yield self.candidate_class(**candidate_args)) | 7,479,512,621,843,678,000 | Extract Candidates from a Context | snorkel/candidates.py | apply | ailabx/snorkel | python | def apply(self, context, clear, split, check_for_existing=True, **kwargs):
if (not isinstance(context, Sentence)):
raise NotImplementedError(('%s is currently only implemented for Sentence contexts.' % self.__name__))
entity_idxs = dict(((et, defaultdict(list)) for et in set(self.entity_types)))
L = len(context.words)
for i in range(L):
if (context.entity_types[i] is not None):
ets = context.entity_types[i].split(self.entity_sep)
cids = context.entity_cids[i].split(self.entity_sep)
for (et, cid) in zip(ets, cids):
if (et in entity_idxs):
entity_idxs[et][cid].append(i)
entity_spans = defaultdict(list)
entity_cids = {}
for (et, cid_idxs) in iteritems(entity_idxs):
for (cid, idxs) in iteritems(entity_idxs[et]):
while (len(idxs) > 0):
i = idxs.pop(0)
char_start = context.char_offsets[i]
char_end = ((char_start + len(context.words[i])) - 1)
while ((len(idxs) > 0) and (idxs[0] == (i + 1))):
i = idxs.pop(0)
char_end = ((context.char_offsets[i] + len(context.words[i])) - 1)
tc = TemporarySpan(char_start=char_start, char_end=char_end, sentence=context)
tc.load_id_or_insert(self.session)
entity_cids[tc.id] = cid
entity_spans[et].append(tc)
candidate_args = {'split': split}
for args in product(*[enumerate(entity_spans[et]) for et in self.entity_types]):
if (self.arity == 2):
(ai, a) = args[0]
(bi, b) = args[1]
if ((not self.self_relations) and (a == b)):
continue
elif ((not self.nested_relations) and ((a in b) or (b in a))):
continue
elif ((not self.symmetric_relations) and (ai > bi)):
continue
for (i, arg_name) in enumerate(self.candidate_class.__argnames__):
candidate_args[(arg_name + '_id')] = args[i][1].id
candidate_args[(arg_name + '_cid')] = entity_cids[args[i][1].id]
if check_for_existing:
q = select([self.candidate_class.id])
for (key, value) in iteritems(candidate_args):
q = q.where((getattr(self.candidate_class, key) == value))
candidate_id = self.session.execute(q).first()
if (candidate_id is not None):
continue
(yield self.candidate_class(**candidate_args)) |
def read_inputs(self, name: str):
'\n read circuit graphs\n '
top_ports = []
ports_weight = {}
for (node, attr) in self.G.nodes(data=True):
if ('source' in attr['inst_type']):
for source_nets in self.G.neighbors(node):
top_ports.append(source_nets)
elif ('net_type' in attr):
if (attr['net_type'] == 'external'):
top_ports.append(node)
ports_weight[node] = []
for nbr in list(self.G.neighbors(node)):
ports_weight[node].append(self.G.get_edge_data(node, nbr)['weight'])
logger.debug('Merging nested graph hierarchies to dictionary: ')
const = self.const_parse.read_user_const(name)
self.hier_graph_dict[name] = {'graph': self.G, 'ports': top_ports, 'ports_weight': ports_weight, 'const': const}
self._traverse_hier_in_graph(self.G)
logger.debug(f'read graph {self.hier_graph_dict}')
return self.hier_graph_dict | -3,506,295,908,788,865,500 | read circuit graphs | align/compiler/create_database.py | read_inputs | mabrains/ALIGN-public | python | def read_inputs(self, name: str):
'\n \n '
top_ports = []
ports_weight = {}
for (node, attr) in self.G.nodes(data=True):
if ('source' in attr['inst_type']):
for source_nets in self.G.neighbors(node):
top_ports.append(source_nets)
elif ('net_type' in attr):
if (attr['net_type'] == 'external'):
top_ports.append(node)
ports_weight[node] = []
for nbr in list(self.G.neighbors(node)):
ports_weight[node].append(self.G.get_edge_data(node, nbr)['weight'])
logger.debug('Merging nested graph hierarchies to dictionary: ')
const = self.const_parse.read_user_const(name)
self.hier_graph_dict[name] = {'graph': self.G, 'ports': top_ports, 'ports_weight': ports_weight, 'const': const}
self._traverse_hier_in_graph(self.G)
logger.debug(f'read graph {self.hier_graph_dict}')
return self.hier_graph_dict |
def _traverse_hier_in_graph(self, G):
'\n Recusively reads all hierachies in the graph and convert them to dictionary\n '
for (node, attr) in G.nodes(data=True):
if (('sub_graph' in attr) and attr['sub_graph']):
logger.debug(f"Traversing sub graph: {node} {attr['inst_type']} {attr['ports']}")
sub_ports = []
ports_weight = {}
for (sub_node, sub_attr) in attr['sub_graph'].nodes(data=True):
if ('net_type' in sub_attr):
if (sub_attr['net_type'] == 'external'):
sub_ports.append(sub_node)
ports_weight[sub_node] = []
for nbr in list(attr['sub_graph'].neighbors(sub_node)):
ports_weight[sub_node].append(attr['sub_graph'].get_edge_data(sub_node, nbr)['weight'])
logger.debug(f"external ports: {sub_ports}, {attr['connection']}, {ports_weight}")
const = self.const_parse.read_user_const(attr['inst_type'])
self.hier_graph_dict[attr['inst_type']] = {'graph': attr['sub_graph'], 'ports': sub_ports, 'const': const, 'ports_weight': ports_weight}
self._traverse_hier_in_graph(attr['sub_graph']) | 66,405,325,679,430,640 | Recusively reads all hierachies in the graph and convert them to dictionary | align/compiler/create_database.py | _traverse_hier_in_graph | mabrains/ALIGN-public | python | def _traverse_hier_in_graph(self, G):
'\n \n '
for (node, attr) in G.nodes(data=True):
if (('sub_graph' in attr) and attr['sub_graph']):
logger.debug(f"Traversing sub graph: {node} {attr['inst_type']} {attr['ports']}")
sub_ports = []
ports_weight = {}
for (sub_node, sub_attr) in attr['sub_graph'].nodes(data=True):
if ('net_type' in sub_attr):
if (sub_attr['net_type'] == 'external'):
sub_ports.append(sub_node)
ports_weight[sub_node] = []
for nbr in list(attr['sub_graph'].neighbors(sub_node)):
ports_weight[sub_node].append(attr['sub_graph'].get_edge_data(sub_node, nbr)['weight'])
logger.debug(f"external ports: {sub_ports}, {attr['connection']}, {ports_weight}")
const = self.const_parse.read_user_const(attr['inst_type'])
self.hier_graph_dict[attr['inst_type']] = {'graph': attr['sub_graph'], 'ports': sub_ports, 'const': const, 'ports_weight': ports_weight}
self._traverse_hier_in_graph(attr['sub_graph']) |
def run(self, loaderFunc):
'Called when execution of a feeder element is desired.'
if (loaderFunc == Type.kIntake):
if ((self.xboxMap.getDriveLeftTrig() > 0) and (self.xboxMap.getDriveRightTrig() == 0)):
self.intakeMotor.runIntake(self.intakeMotorSpeed, Direction.kForwards)
log.debug('right trig intake', self.xboxMap.getMechRightTrig())
elif ((self.xboxMap.getDriveRightTrig() > 0) and (self.xboxMap.getDriveLeftTrig() == 0)):
self.intakeMotor.runIntake(self.intakeMotorSpeed, Direction.kBackwards)
log.debug('left trig intake', self.xboxMap.getMechLeftTrig())
else:
self.intakeMotor.runIntake(0, Direction.kForwards)
if (loaderFunc == Type.kHopper):
if ((self.xboxMap.getDriveLeftTrig() > 0) and (self.xboxMap.getDriveRightTrig() == 0)):
self.hopperMotor.runHopperMotorForeside(self.loaderMotorSpeed, Direction.kForwards)
self.hopperMotor.runHopperMotorBackside(self.loaderMotorSpeed, Direction.kForwards)
log.debug('right trig manual', self.xboxMap.getMechRightTrig())
elif ((self.xboxMap.getDriveRightTrig() > 0) and (self.xboxMap.getDriveLeftTrig() == 0)):
self.hopperMotor.runHopperMotorForeside(self.loaderMotorSpeed, Direction.kBackwards)
self.hopperMotor.runHopperMotorBackside(self.loaderMotorSpeed, Direction.kBackwards)
log.debug('left trig manual', self.xboxMap.getMechLeftTrig())
else:
self.hopperMotor.stopHopperMotorBackside()
self.hopperMotor.stopHopperMotorForeside() | 4,227,365,644,385,983,500 | Called when execution of a feeder element is desired. | components/Actuators/HighLevel/feederMap.py | run | Raptacon/Robot-2022 | python | def run(self, loaderFunc):
if (loaderFunc == Type.kIntake):
if ((self.xboxMap.getDriveLeftTrig() > 0) and (self.xboxMap.getDriveRightTrig() == 0)):
self.intakeMotor.runIntake(self.intakeMotorSpeed, Direction.kForwards)
log.debug('right trig intake', self.xboxMap.getMechRightTrig())
elif ((self.xboxMap.getDriveRightTrig() > 0) and (self.xboxMap.getDriveLeftTrig() == 0)):
self.intakeMotor.runIntake(self.intakeMotorSpeed, Direction.kBackwards)
log.debug('left trig intake', self.xboxMap.getMechLeftTrig())
else:
self.intakeMotor.runIntake(0, Direction.kForwards)
if (loaderFunc == Type.kHopper):
if ((self.xboxMap.getDriveLeftTrig() > 0) and (self.xboxMap.getDriveRightTrig() == 0)):
self.hopperMotor.runHopperMotorForeside(self.loaderMotorSpeed, Direction.kForwards)
self.hopperMotor.runHopperMotorBackside(self.loaderMotorSpeed, Direction.kForwards)
log.debug('right trig manual', self.xboxMap.getMechRightTrig())
elif ((self.xboxMap.getDriveRightTrig() > 0) and (self.xboxMap.getDriveLeftTrig() == 0)):
self.hopperMotor.runHopperMotorForeside(self.loaderMotorSpeed, Direction.kBackwards)
self.hopperMotor.runHopperMotorBackside(self.loaderMotorSpeed, Direction.kBackwards)
log.debug('left trig manual', self.xboxMap.getMechLeftTrig())
else:
self.hopperMotor.stopHopperMotorBackside()
self.hopperMotor.stopHopperMotorForeside() |
def __init__(self, graph=None):
'\n Initializes the CASE document.\n Args:\n graph: The graph to populate (instance of rdflib.Graph)\n If not provided, a graph in memory will be used.\n '
if (not graph):
graph = rdflib.Graph()
graph.namespace_manager.bind('case', CASE)
self.graph = graph | -570,383,764,642,344,300 | Initializes the CASE document.
Args:
graph: The graph to populate (instance of rdflib.Graph)
If not provided, a graph in memory will be used. | example/case_example.py | __init__ | casework/CASE-API-Python | python | def __init__(self, graph=None):
'\n Initializes the CASE document.\n Args:\n graph: The graph to populate (instance of rdflib.Graph)\n If not provided, a graph in memory will be used.\n '
if (not graph):
graph = rdflib.Graph()
graph.namespace_manager.bind('case', CASE)
self.graph = graph |
def _sanitize_triple(self, triple):
'Santizes the triple to contains pure rdflib terms.'
(s, p, o) = triple
if isinstance(s, Node):
s = s._node
if isinstance(o, Node):
o = o._node
elif ((o is not None) and (not isinstance(o, rdflib.term.Node))):
o = rdflib.Literal(o)
if ((p is not None) and (not isinstance(p, rdflib.term.Node))):
p = CASE[p]
return (s, p, o) | -2,340,009,076,956,215,300 | Santizes the triple to contains pure rdflib terms. | example/case_example.py | _sanitize_triple | casework/CASE-API-Python | python | def _sanitize_triple(self, triple):
(s, p, o) = triple
if isinstance(s, Node):
s = s._node
if isinstance(o, Node):
o = o._node
elif ((o is not None) and (not isinstance(o, rdflib.term.Node))):
o = rdflib.Literal(o)
if ((p is not None) and (not isinstance(p, rdflib.term.Node))):
p = CASE[p]
return (s, p, o) |
def __iter__(self):
'Wrapper for iterating over all triples in the graph'
return iter(self.graph) | 3,017,913,809,145,363,000 | Wrapper for iterating over all triples in the graph | example/case_example.py | __iter__ | casework/CASE-API-Python | python | def __iter__(self):
return iter(self.graph) |
def __contains__(self, triple):
'Wrapper for checking if triple is contained in the graph.'
return (self._sanitize_triple(triple) in self.graph) | -3,107,036,654,600,936,000 | Wrapper for checking if triple is contained in the graph. | example/case_example.py | __contains__ | casework/CASE-API-Python | python | def __contains__(self, triple):
return (self._sanitize_triple(triple) in self.graph) |
def triples(self, triple):
'Generator over the triple store in graph.'
return self.graph.triples(self._sanitize_triple(triple)) | 1,302,646,430,989,216,500 | Generator over the triple store in graph. | example/case_example.py | triples | casework/CASE-API-Python | python | def triples(self, triple):
return self.graph.triples(self._sanitize_triple(triple)) |
def serialize(self, format='json-ld', **kwargs):
"Serializes the document's graph to a destination.\n (Follows same arguments as rdflib.Graph().serialize())"
if (format == 'json-ld'):
if ('context' not in kwargs):
kwargs['context'] = self._json_ld_context()
if ('auto_compact' not in kwargs):
kwargs['auto_compact'] = True
return self.graph.serialize(format=format, **kwargs) | -4,027,732,136,207,101,400 | Serializes the document's graph to a destination.
(Follows same arguments as rdflib.Graph().serialize()) | example/case_example.py | serialize | casework/CASE-API-Python | python | def serialize(self, format='json-ld', **kwargs):
"Serializes the document's graph to a destination.\n (Follows same arguments as rdflib.Graph().serialize())"
if (format == 'json-ld'):
if ('context' not in kwargs):
kwargs['context'] = self._json_ld_context()
if ('auto_compact' not in kwargs):
kwargs['auto_compact'] = True
return self.graph.serialize(format=format, **kwargs) |
def create_CoreObject(self, _type=None, **kwargs):
'\n Creates and returns a CoreObject.\n '
return CoreObject(self.graph, rdf_type=_type, **kwargs) | -7,912,393,568,977,087,000 | Creates and returns a CoreObject. | example/case_example.py | create_CoreObject | casework/CASE-API-Python | python | def create_CoreObject(self, _type=None, **kwargs):
'\n \n '
return CoreObject(self.graph, rdf_type=_type, **kwargs) |
def create_ContextObject(self, _type=None, **kwargs):
'\n Creates and returns a Context.\n This class may not have PropertyBundles.\n '
return ContextObject(self.graph, rdf_type=_type, **kwargs) | -7,159,098,150,300,702,000 | Creates and returns a Context.
This class may not have PropertyBundles. | example/case_example.py | create_ContextObject | casework/CASE-API-Python | python | def create_ContextObject(self, _type=None, **kwargs):
'\n Creates and returns a Context.\n This class may not have PropertyBundles.\n '
return ContextObject(self.graph, rdf_type=_type, **kwargs) |
def create_SubObject(self, _type=None, **kwargs):
'\n Creates and returns a Sub.\n This class is for children of one of the above CASE classes.\n This class may not have PropertyBundles.\n '
return SubObject(self.graph, rdf_type=_type, **kwargs) | 6,910,321,356,426,898,000 | Creates and returns a Sub.
This class is for children of one of the above CASE classes.
This class may not have PropertyBundles. | example/case_example.py | create_SubObject | casework/CASE-API-Python | python | def create_SubObject(self, _type=None, **kwargs):
'\n Creates and returns a Sub.\n This class is for children of one of the above CASE classes.\n This class may not have PropertyBundles.\n '
return SubObject(self.graph, rdf_type=_type, **kwargs) |
def create_DuckObject(self, _type=None, **kwargs):
'\n Creates and returns a Duck.\n These lonely Ducks have no parents and are fully duck-typed.\n This class may not have PropertyBundles.\n '
return DuckObject(self.graph, rdf_type=_type, **kwargs) | 4,973,963,120,371,535,000 | Creates and returns a Duck.
These lonely Ducks have no parents and are fully duck-typed.
This class may not have PropertyBundles. | example/case_example.py | create_DuckObject | casework/CASE-API-Python | python | def create_DuckObject(self, _type=None, **kwargs):
'\n Creates and returns a Duck.\n These lonely Ducks have no parents and are fully duck-typed.\n This class may not have PropertyBundles.\n '
return DuckObject(self.graph, rdf_type=_type, **kwargs) |
def __init__(self, graph, uri=None, bnode=False, rdf_type=None, **kwargs):
'Initializes and adds a node to the graph.\n\n NOTE: At least the type or a property must be supplied for the Node\n to exist in the graph.\n\n Args:\n graph: The graph to add this node to. (instance of rdflib.Graph)\n uri: Optional string to set th URI to. (If not provided a UUID will be generated.)\n bnode: Whether to create a blank node or a uri reference.\n rdf_type: The RDF type to set this node to.\n properties: Extra properties to add to this node.\n (More properties can be set after initialization by using the add() function.)\n '
super(Node, self).__init__()
if uri:
self.uri = uri
else:
self.uri = str(uuid.uuid4())
if bnode:
self._node = rdflib.BNode(self.uri)
else:
self._node = rdflib.URIRef(self.uri)
self._graph = graph
if (not rdf_type):
rdf_type = self.RDF_TYPE
if (not isinstance(rdf_type, rdflib.term.Node)):
rdf_type = self.NAMESPACE[rdf_type]
self.add(RDF.type, rdf_type)
for (key, value) in iter(kwargs.items()):
self.add(key, value) | 8,967,509,059,899,799,000 | Initializes and adds a node to the graph.
NOTE: At least the type or a property must be supplied for the Node
to exist in the graph.
Args:
graph: The graph to add this node to. (instance of rdflib.Graph)
uri: Optional string to set th URI to. (If not provided a UUID will be generated.)
bnode: Whether to create a blank node or a uri reference.
rdf_type: The RDF type to set this node to.
properties: Extra properties to add to this node.
(More properties can be set after initialization by using the add() function.) | example/case_example.py | __init__ | casework/CASE-API-Python | python | def __init__(self, graph, uri=None, bnode=False, rdf_type=None, **kwargs):
'Initializes and adds a node to the graph.\n\n NOTE: At least the type or a property must be supplied for the Node\n to exist in the graph.\n\n Args:\n graph: The graph to add this node to. (instance of rdflib.Graph)\n uri: Optional string to set th URI to. (If not provided a UUID will be generated.)\n bnode: Whether to create a blank node or a uri reference.\n rdf_type: The RDF type to set this node to.\n properties: Extra properties to add to this node.\n (More properties can be set after initialization by using the add() function.)\n '
super(Node, self).__init__()
if uri:
self.uri = uri
else:
self.uri = str(uuid.uuid4())
if bnode:
self._node = rdflib.BNode(self.uri)
else:
self._node = rdflib.URIRef(self.uri)
self._graph = graph
if (not rdf_type):
rdf_type = self.RDF_TYPE
if (not isinstance(rdf_type, rdflib.term.Node)):
rdf_type = self.NAMESPACE[rdf_type]
self.add(RDF.type, rdf_type)
for (key, value) in iter(kwargs.items()):
self.add(key, value) |
def add(self, property, value):
'Adds a property and its value to the node.'
if (value is None):
return
if isinstance(value, (list, tuple, set)):
for item in value:
self.add(property, item)
return
if isinstance(value, Node):
value = value._node
elif (not isinstance(value, rdflib.term.Node)):
value = rdflib.Literal(value)
if (not isinstance(property, rdflib.term.Node)):
property = self.NAMESPACE[property]
self._graph.add((self._node, property, value)) | 4,964,973,318,960,611,000 | Adds a property and its value to the node. | example/case_example.py | add | casework/CASE-API-Python | python | def add(self, property, value):
if (value is None):
return
if isinstance(value, (list, tuple, set)):
for item in value:
self.add(property, item)
return
if isinstance(value, Node):
value = value._node
elif (not isinstance(value, rdflib.term.Node)):
value = rdflib.Literal(value)
if (not isinstance(property, rdflib.term.Node)):
property = self.NAMESPACE[property]
self._graph.add((self._node, property, value)) |
def __init__(self, graph, rdf_type=None, **kwargs):
'Initializes and adds a node to the graph.\n NOTE: At least the type or a property must be supplied for the Node\n to exist in the graph.\n\n Args:\n graph: The graph to add this node to. (instance of rdflib.Graph)\n rdf_type: The RDF type to set this node to.\n properties: Extra properties to add to this node.\n (More properties can be set after initialization by using the add() function.)\n '
self.type = rdf_type
super(CoreObject, self).__init__(graph, rdf_type=rdf_type, **kwargs)
self.add('CoreObjectCreationTime', datetime.datetime.utcnow())
self.pb = '' | 7,103,185,099,151,627,000 | Initializes and adds a node to the graph.
NOTE: At least the type or a property must be supplied for the Node
to exist in the graph.
Args:
graph: The graph to add this node to. (instance of rdflib.Graph)
rdf_type: The RDF type to set this node to.
properties: Extra properties to add to this node.
(More properties can be set after initialization by using the add() function.) | example/case_example.py | __init__ | casework/CASE-API-Python | python | def __init__(self, graph, rdf_type=None, **kwargs):
'Initializes and adds a node to the graph.\n NOTE: At least the type or a property must be supplied for the Node\n to exist in the graph.\n\n Args:\n graph: The graph to add this node to. (instance of rdflib.Graph)\n rdf_type: The RDF type to set this node to.\n properties: Extra properties to add to this node.\n (More properties can be set after initialization by using the add() function.)\n '
self.type = rdf_type
super(CoreObject, self).__init__(graph, rdf_type=rdf_type, **kwargs)
self.add('CoreObjectCreationTime', datetime.datetime.utcnow())
self.pb = |
def create_PropertyBundle(self, prop_type=None, **kwargs):
'Convenience function for adding property bundles to this Trace.\n\n Args:\n type: The @type of property bundle (can be of type rdflib.URIRef or string).\n properties: Properties to add to the created property bundle.\n\n Returns:\n The property bundle created (instance of PropertyBundle).\n '
self.pb = PropertyBundle(self._graph, rdf_type=prop_type, **kwargs)
self.add(CASE.propertyBundle, self.pb)
return self.pb | 8,454,463,926,833,009,000 | Convenience function for adding property bundles to this Trace.
Args:
type: The @type of property bundle (can be of type rdflib.URIRef or string).
properties: Properties to add to the created property bundle.
Returns:
The property bundle created (instance of PropertyBundle). | example/case_example.py | create_PropertyBundle | casework/CASE-API-Python | python | def create_PropertyBundle(self, prop_type=None, **kwargs):
'Convenience function for adding property bundles to this Trace.\n\n Args:\n type: The @type of property bundle (can be of type rdflib.URIRef or string).\n properties: Properties to add to the created property bundle.\n\n Returns:\n The property bundle created (instance of PropertyBundle).\n '
self.pb = PropertyBundle(self._graph, rdf_type=prop_type, **kwargs)
self.add(CASE.propertyBundle, self.pb)
return self.pb |
def __init__(self, graph, rdf_type=None, **kwargs):
'Initializes and adds a node to the graph.\n NOTE: At least the type or a property must be supplied for the Node\n to exist in the graph.\n\n Args:\n graph: The graph to add this node to. (instance of rdflib.Graph)\n rdf_type: The RDF type to set this node to.\n properties: Extra properties to add to this node.\n (More properties can be set after initialization by using the add() function.)\n '
self.type = rdf_type
self.propObj = kwargs
super(PropertyBundle, self).__init__(graph, bnode=True, rdf_type=rdf_type, **kwargs) | 26,501,929,538,819,850 | Initializes and adds a node to the graph.
NOTE: At least the type or a property must be supplied for the Node
to exist in the graph.
Args:
graph: The graph to add this node to. (instance of rdflib.Graph)
rdf_type: The RDF type to set this node to.
properties: Extra properties to add to this node.
(More properties can be set after initialization by using the add() function.) | example/case_example.py | __init__ | casework/CASE-API-Python | python | def __init__(self, graph, rdf_type=None, **kwargs):
'Initializes and adds a node to the graph.\n NOTE: At least the type or a property must be supplied for the Node\n to exist in the graph.\n\n Args:\n graph: The graph to add this node to. (instance of rdflib.Graph)\n rdf_type: The RDF type to set this node to.\n properties: Extra properties to add to this node.\n (More properties can be set after initialization by using the add() function.)\n '
self.type = rdf_type
self.propObj = kwargs
super(PropertyBundle, self).__init__(graph, bnode=True, rdf_type=rdf_type, **kwargs) |
def __init__(self, graph, rdf_type=None, **kwargs):
'Initializes and adds a node to the graph.\n NOTE: At least the type must be supplied for the Node\n to exist in the graph.\n\n Args:\n graph: The graph to add this node to. (instance of rdflib.Graph)\n rdf_type: The RDF type to set this node to.\n properties: Extra properties to add to this node.\n (More properties can be set after initialization by using the add() function.)\n '
self.type = rdf_type
super(ContextObject, self).__init__(graph, rdf_type=rdf_type, **kwargs)
self.add('ContextObjectCreationTime', datetime.datetime.utcnow()) | -5,985,738,002,460,461,000 | Initializes and adds a node to the graph.
NOTE: At least the type must be supplied for the Node
to exist in the graph.
Args:
graph: The graph to add this node to. (instance of rdflib.Graph)
rdf_type: The RDF type to set this node to.
properties: Extra properties to add to this node.
(More properties can be set after initialization by using the add() function.) | example/case_example.py | __init__ | casework/CASE-API-Python | python | def __init__(self, graph, rdf_type=None, **kwargs):
'Initializes and adds a node to the graph.\n NOTE: At least the type must be supplied for the Node\n to exist in the graph.\n\n Args:\n graph: The graph to add this node to. (instance of rdflib.Graph)\n rdf_type: The RDF type to set this node to.\n properties: Extra properties to add to this node.\n (More properties can be set after initialization by using the add() function.)\n '
self.type = rdf_type
super(ContextObject, self).__init__(graph, rdf_type=rdf_type, **kwargs)
self.add('ContextObjectCreationTime', datetime.datetime.utcnow()) |
def __init__(self, graph, rdf_type=None, **kwargs):
'Initializes and adds a node to the graph.\n NOTE: At least the type must be supplied for the Node\n to exist in the graph.\n\n Args:\n graph: The graph to add this node to. (instance of rdflib.Graph)\n rdf_type: The RDF type to set this node to.\n properties: Extra properties to add to this node.\n (More properties can be set after initialization by using the add() function.)\n '
self.type = rdf_type
super(SubObject, self).__init__(graph, rdf_type=rdf_type, **kwargs)
self.add('SubObjectCreationTime', datetime.datetime.utcnow()) | 3,458,609,786,989,587,000 | Initializes and adds a node to the graph.
NOTE: At least the type must be supplied for the Node
to exist in the graph.
Args:
graph: The graph to add this node to. (instance of rdflib.Graph)
rdf_type: The RDF type to set this node to.
properties: Extra properties to add to this node.
(More properties can be set after initialization by using the add() function.) | example/case_example.py | __init__ | casework/CASE-API-Python | python | def __init__(self, graph, rdf_type=None, **kwargs):
'Initializes and adds a node to the graph.\n NOTE: At least the type must be supplied for the Node\n to exist in the graph.\n\n Args:\n graph: The graph to add this node to. (instance of rdflib.Graph)\n rdf_type: The RDF type to set this node to.\n properties: Extra properties to add to this node.\n (More properties can be set after initialization by using the add() function.)\n '
self.type = rdf_type
super(SubObject, self).__init__(graph, rdf_type=rdf_type, **kwargs)
self.add('SubObjectCreationTime', datetime.datetime.utcnow()) |
def __init__(self, graph, rdf_type=None, **kwargs):
'Initializes and adds a node to the graph.\n NOTE: At least the type must be supplied for the Node\n to exist in the graph.\n\n Args:\n graph: The graph to add this node to. (instance of rdflib.Graph)\n rdf_type: The RDF type to set this node to.\n properties: Extra properties to add to this node.\n (More properties can be set after initialization by using the add() function.)\n '
self.type = rdf_type
super(DuckObject, self).__init__(graph, rdf_type=rdf_type, **kwargs)
self.add('DuckObjectCreationTime', datetime.datetime.utcnow()) | 458,313,680,131,040,830 | Initializes and adds a node to the graph.
NOTE: At least the type must be supplied for the Node
to exist in the graph.
Args:
graph: The graph to add this node to. (instance of rdflib.Graph)
rdf_type: The RDF type to set this node to.
properties: Extra properties to add to this node.
(More properties can be set after initialization by using the add() function.) | example/case_example.py | __init__ | casework/CASE-API-Python | python | def __init__(self, graph, rdf_type=None, **kwargs):
'Initializes and adds a node to the graph.\n NOTE: At least the type must be supplied for the Node\n to exist in the graph.\n\n Args:\n graph: The graph to add this node to. (instance of rdflib.Graph)\n rdf_type: The RDF type to set this node to.\n properties: Extra properties to add to this node.\n (More properties can be set after initialization by using the add() function.)\n '
self.type = rdf_type
super(DuckObject, self).__init__(graph, rdf_type=rdf_type, **kwargs)
self.add('DuckObjectCreationTime', datetime.datetime.utcnow()) |
def create_map_job(config, internal_storage, executor_id, job_id, map_function, iterdata, runtime_meta, runtime_memory, extra_env, include_modules, exclude_modules, execution_timeout, extra_args=None, obj_chunk_size=None, obj_chunk_number=None, invoke_pool_threads=128):
'\n Wrapper to create a map job. It integrates COS logic to process objects.\n '
host_job_meta = {'host_job_create_tstamp': time.time()}
map_iterdata = utils.verify_args(map_function, iterdata, extra_args)
if config['lithops'].get('rabbitmq_monitor', False):
rabbit_amqp_url = config['rabbitmq'].get('amqp_url')
utils.create_rabbitmq_resources(rabbit_amqp_url, executor_id, job_id)
parts_per_object = None
if is_object_processing_function(map_function):
create_partitions_start = time.time()
logger.debug('ExecutorID {} | JobID {} - Calling map on partitions from object storage flow'.format(executor_id, job_id))
(map_iterdata, parts_per_object) = create_partitions(config, internal_storage, map_iterdata, obj_chunk_size, obj_chunk_number)
host_job_meta['host_job_create_partitions_time'] = round((time.time() - create_partitions_start), 6)
job = _create_job(config=config, internal_storage=internal_storage, executor_id=executor_id, job_id=job_id, func=map_function, iterdata=map_iterdata, runtime_meta=runtime_meta, runtime_memory=runtime_memory, extra_env=extra_env, include_modules=include_modules, exclude_modules=exclude_modules, execution_timeout=execution_timeout, host_job_meta=host_job_meta, invoke_pool_threads=invoke_pool_threads)
if parts_per_object:
job.parts_per_object = parts_per_object
return job | -4,410,323,720,239,119,000 | Wrapper to create a map job. It integrates COS logic to process objects. | lithops/job/job.py | create_map_job | pablogs98/lithops | python | def create_map_job(config, internal_storage, executor_id, job_id, map_function, iterdata, runtime_meta, runtime_memory, extra_env, include_modules, exclude_modules, execution_timeout, extra_args=None, obj_chunk_size=None, obj_chunk_number=None, invoke_pool_threads=128):
'\n \n '
host_job_meta = {'host_job_create_tstamp': time.time()}
map_iterdata = utils.verify_args(map_function, iterdata, extra_args)
if config['lithops'].get('rabbitmq_monitor', False):
rabbit_amqp_url = config['rabbitmq'].get('amqp_url')
utils.create_rabbitmq_resources(rabbit_amqp_url, executor_id, job_id)
parts_per_object = None
if is_object_processing_function(map_function):
create_partitions_start = time.time()
logger.debug('ExecutorID {} | JobID {} - Calling map on partitions from object storage flow'.format(executor_id, job_id))
(map_iterdata, parts_per_object) = create_partitions(config, internal_storage, map_iterdata, obj_chunk_size, obj_chunk_number)
host_job_meta['host_job_create_partitions_time'] = round((time.time() - create_partitions_start), 6)
job = _create_job(config=config, internal_storage=internal_storage, executor_id=executor_id, job_id=job_id, func=map_function, iterdata=map_iterdata, runtime_meta=runtime_meta, runtime_memory=runtime_memory, extra_env=extra_env, include_modules=include_modules, exclude_modules=exclude_modules, execution_timeout=execution_timeout, host_job_meta=host_job_meta, invoke_pool_threads=invoke_pool_threads)
if parts_per_object:
job.parts_per_object = parts_per_object
return job |
def create_reduce_job(config, internal_storage, executor_id, reduce_job_id, reduce_function, map_job, map_futures, runtime_meta, runtime_memory, reducer_one_per_object, extra_env, include_modules, exclude_modules, execution_timeout=None):
'\n Wrapper to create a reduce job. Apply a function across all map futures.\n '
host_job_meta = {'host_job_create_tstamp': time.time()}
iterdata = [(map_futures,)]
if (hasattr(map_job, 'parts_per_object') and reducer_one_per_object):
prev_total_partitons = 0
iterdata = []
for total_partitions in map_job.parts_per_object:
iterdata.append((map_futures[prev_total_partitons:(prev_total_partitons + total_partitions)],))
prev_total_partitons += total_partitions
reduce_job_env = {'__LITHOPS_REDUCE_JOB': True}
if (extra_env is None):
ext_env = reduce_job_env
else:
ext_env = extra_env.copy()
ext_env.update(reduce_job_env)
iterdata = utils.verify_args(reduce_function, iterdata, None)
return _create_job(config=config, internal_storage=internal_storage, executor_id=executor_id, job_id=reduce_job_id, func=reduce_function, iterdata=iterdata, runtime_meta=runtime_meta, runtime_memory=runtime_memory, extra_env=ext_env, include_modules=include_modules, exclude_modules=exclude_modules, execution_timeout=execution_timeout, host_job_meta=host_job_meta) | 266,928,933,511,763,460 | Wrapper to create a reduce job. Apply a function across all map futures. | lithops/job/job.py | create_reduce_job | pablogs98/lithops | python | def create_reduce_job(config, internal_storage, executor_id, reduce_job_id, reduce_function, map_job, map_futures, runtime_meta, runtime_memory, reducer_one_per_object, extra_env, include_modules, exclude_modules, execution_timeout=None):
'\n \n '
host_job_meta = {'host_job_create_tstamp': time.time()}
iterdata = [(map_futures,)]
if (hasattr(map_job, 'parts_per_object') and reducer_one_per_object):
prev_total_partitons = 0
iterdata = []
for total_partitions in map_job.parts_per_object:
iterdata.append((map_futures[prev_total_partitons:(prev_total_partitons + total_partitions)],))
prev_total_partitons += total_partitions
reduce_job_env = {'__LITHOPS_REDUCE_JOB': True}
if (extra_env is None):
ext_env = reduce_job_env
else:
ext_env = extra_env.copy()
ext_env.update(reduce_job_env)
iterdata = utils.verify_args(reduce_function, iterdata, None)
return _create_job(config=config, internal_storage=internal_storage, executor_id=executor_id, job_id=reduce_job_id, func=reduce_function, iterdata=iterdata, runtime_meta=runtime_meta, runtime_memory=runtime_memory, extra_env=ext_env, include_modules=include_modules, exclude_modules=exclude_modules, execution_timeout=execution_timeout, host_job_meta=host_job_meta) |
def _create_job(config, internal_storage, executor_id, job_id, func, iterdata, runtime_meta, runtime_memory, extra_env, include_modules, exclude_modules, execution_timeout, host_job_meta, invoke_pool_threads=128):
'\n :param func: the function to map over the data\n :param iterdata: An iterable of input data\n :param extra_env: Additional environment variables for CF environment. Default None.\n :param extra_meta: Additional metadata to pass to CF. Default None.\n :param remote_invocation: Enable remote invocation. Default False.\n :param invoke_pool_threads: Number of threads to use to invoke.\n :param data_all_as_one: upload the data as a single object. Default True\n :param overwrite_invoke_args: Overwrite other args. Mainly used for testing.\n :param exclude_modules: Explicitly keep these modules from pickled dependencies.\n :return: A list with size `len(iterdata)` of futures for each job\n :rtype: list of futures.\n '
ext_env = ({} if (extra_env is None) else extra_env.copy())
if ext_env:
ext_env = utils.convert_bools_to_string(ext_env)
logger.debug('Extra environment vars {}'.format(ext_env))
job = SimpleNamespace()
job.executor_id = executor_id
job.job_id = job_id
job.extra_env = ext_env
job.execution_timeout = (execution_timeout or config['lithops']['execution_timeout'])
job.function_name = func.__name__
job.total_calls = len(iterdata)
mode = config['lithops']['mode']
if (mode == SERVERLESS):
job.invoke_pool_threads = invoke_pool_threads
job.runtime_memory = (runtime_memory or config['serverless']['runtime_memory'])
job.runtime_timeout = config['serverless']['runtime_timeout']
if (job.execution_timeout >= job.runtime_timeout):
job.execution_timeout = (job.runtime_timeout - 5)
elif (mode == STANDALONE):
job.runtime_memory = None
runtime_timeout = config['standalone']['hard_dismantle_timeout']
if (job.execution_timeout >= runtime_timeout):
job.execution_timeout = (runtime_timeout - 10)
elif (mode == LOCALHOST):
job.runtime_memory = None
job.runtime_timeout = execution_timeout
exclude_modules_cfg = config['lithops'].get('exclude_modules', [])
include_modules_cfg = config['lithops'].get('include_modules', [])
exc_modules = set()
inc_modules = set()
if exclude_modules_cfg:
exc_modules.update(exclude_modules_cfg)
if exclude_modules:
exc_modules.update(exclude_modules)
if (include_modules_cfg is not None):
inc_modules.update(include_modules_cfg)
if ((include_modules_cfg is None) and (not include_modules)):
inc_modules = None
if ((include_modules is not None) and include_modules):
inc_modules.update(include_modules)
if (include_modules is None):
inc_modules = None
logger.debug('ExecutorID {} | JobID {} - Serializing function and data'.format(executor_id, job_id))
job_serialize_start = time.time()
serializer = SerializeIndependent(runtime_meta['preinstalls'])
(func_and_data_ser, mod_paths) = serializer(([func] + iterdata), inc_modules, exc_modules)
data_strs = func_and_data_ser[1:]
data_size_bytes = sum((len(x) for x in data_strs))
module_data = create_module_data(mod_paths)
func_str = func_and_data_ser[0]
func_module_str = pickle.dumps({'func': func_str, 'module_data': module_data}, (- 1))
func_module_size_bytes = len(func_module_str)
total_size = utils.sizeof_fmt((data_size_bytes + func_module_size_bytes))
host_job_meta['host_job_serialize_time'] = round((time.time() - job_serialize_start), 6)
host_job_meta['data_size_bytes'] = data_size_bytes
host_job_meta['func_module_size_bytes'] = func_module_size_bytes
if ('data_limit' in config['lithops']):
data_limit = config['lithops']['data_limit']
else:
data_limit = MAX_AGG_DATA_SIZE
if (data_limit and (data_size_bytes > (data_limit * (1024 ** 2)))):
log_msg = 'ExecutorID {} | JobID {} - Total data exceeded maximum size of {}'.format(executor_id, job_id, sizeof_fmt((data_limit * (1024 ** 2))))
raise Exception(log_msg)
logger.info('ExecutorID {} | JobID {} - Uploading function and data - Total: {}'.format(executor_id, job_id, total_size))
data_key = create_agg_data_key(JOBS_PREFIX, executor_id, job_id)
job.data_key = data_key
(data_bytes, data_ranges) = utils.agg_data(data_strs)
job.data_ranges = data_ranges
data_upload_start = time.time()
internal_storage.put_data(data_key, data_bytes)
data_upload_end = time.time()
host_job_meta['host_data_upload_time'] = round((data_upload_end - data_upload_start), 6)
func_upload_start = time.time()
if config[mode].get('customized_runtime'):
function_file = func.__code__.co_filename
function_hash = hashlib.md5(open(function_file, 'rb').read()).hexdigest()[:16]
mod_hash = hashlib.md5(repr(sorted(mod_paths)).encode('utf-8')).hexdigest()[:16]
uuid = f'{function_hash}{mod_hash}'
func_key = create_func_key(JOBS_PREFIX, uuid, '')
_store_func_and_modules(func_key, func_str, module_data)
job.ext_runtime_uuid = uuid
else:
func_key = create_func_key(JOBS_PREFIX, executor_id, job_id)
internal_storage.put_func(func_key, func_module_str)
job.func_key = func_key
func_upload_end = time.time()
host_job_meta['host_func_upload_time'] = round((func_upload_end - func_upload_start), 6)
host_job_meta['host_job_created_time'] = round((time.time() - host_job_meta['host_job_create_tstamp']), 6)
job.metadata = host_job_meta
return job | 5,071,671,900,706,446,000 | :param func: the function to map over the data
:param iterdata: An iterable of input data
:param extra_env: Additional environment variables for CF environment. Default None.
:param extra_meta: Additional metadata to pass to CF. Default None.
:param remote_invocation: Enable remote invocation. Default False.
:param invoke_pool_threads: Number of threads to use to invoke.
:param data_all_as_one: upload the data as a single object. Default True
:param overwrite_invoke_args: Overwrite other args. Mainly used for testing.
:param exclude_modules: Explicitly keep these modules from pickled dependencies.
:return: A list with size `len(iterdata)` of futures for each job
:rtype: list of futures. | lithops/job/job.py | _create_job | pablogs98/lithops | python | def _create_job(config, internal_storage, executor_id, job_id, func, iterdata, runtime_meta, runtime_memory, extra_env, include_modules, exclude_modules, execution_timeout, host_job_meta, invoke_pool_threads=128):
'\n :param func: the function to map over the data\n :param iterdata: An iterable of input data\n :param extra_env: Additional environment variables for CF environment. Default None.\n :param extra_meta: Additional metadata to pass to CF. Default None.\n :param remote_invocation: Enable remote invocation. Default False.\n :param invoke_pool_threads: Number of threads to use to invoke.\n :param data_all_as_one: upload the data as a single object. Default True\n :param overwrite_invoke_args: Overwrite other args. Mainly used for testing.\n :param exclude_modules: Explicitly keep these modules from pickled dependencies.\n :return: A list with size `len(iterdata)` of futures for each job\n :rtype: list of futures.\n '
ext_env = ({} if (extra_env is None) else extra_env.copy())
if ext_env:
ext_env = utils.convert_bools_to_string(ext_env)
logger.debug('Extra environment vars {}'.format(ext_env))
job = SimpleNamespace()
job.executor_id = executor_id
job.job_id = job_id
job.extra_env = ext_env
job.execution_timeout = (execution_timeout or config['lithops']['execution_timeout'])
job.function_name = func.__name__
job.total_calls = len(iterdata)
mode = config['lithops']['mode']
if (mode == SERVERLESS):
job.invoke_pool_threads = invoke_pool_threads
job.runtime_memory = (runtime_memory or config['serverless']['runtime_memory'])
job.runtime_timeout = config['serverless']['runtime_timeout']
if (job.execution_timeout >= job.runtime_timeout):
job.execution_timeout = (job.runtime_timeout - 5)
elif (mode == STANDALONE):
job.runtime_memory = None
runtime_timeout = config['standalone']['hard_dismantle_timeout']
if (job.execution_timeout >= runtime_timeout):
job.execution_timeout = (runtime_timeout - 10)
elif (mode == LOCALHOST):
job.runtime_memory = None
job.runtime_timeout = execution_timeout
exclude_modules_cfg = config['lithops'].get('exclude_modules', [])
include_modules_cfg = config['lithops'].get('include_modules', [])
exc_modules = set()
inc_modules = set()
if exclude_modules_cfg:
exc_modules.update(exclude_modules_cfg)
if exclude_modules:
exc_modules.update(exclude_modules)
if (include_modules_cfg is not None):
inc_modules.update(include_modules_cfg)
if ((include_modules_cfg is None) and (not include_modules)):
inc_modules = None
if ((include_modules is not None) and include_modules):
inc_modules.update(include_modules)
if (include_modules is None):
inc_modules = None
logger.debug('ExecutorID {} | JobID {} - Serializing function and data'.format(executor_id, job_id))
job_serialize_start = time.time()
serializer = SerializeIndependent(runtime_meta['preinstalls'])
(func_and_data_ser, mod_paths) = serializer(([func] + iterdata), inc_modules, exc_modules)
data_strs = func_and_data_ser[1:]
data_size_bytes = sum((len(x) for x in data_strs))
module_data = create_module_data(mod_paths)
func_str = func_and_data_ser[0]
func_module_str = pickle.dumps({'func': func_str, 'module_data': module_data}, (- 1))
func_module_size_bytes = len(func_module_str)
total_size = utils.sizeof_fmt((data_size_bytes + func_module_size_bytes))
host_job_meta['host_job_serialize_time'] = round((time.time() - job_serialize_start), 6)
host_job_meta['data_size_bytes'] = data_size_bytes
host_job_meta['func_module_size_bytes'] = func_module_size_bytes
if ('data_limit' in config['lithops']):
data_limit = config['lithops']['data_limit']
else:
data_limit = MAX_AGG_DATA_SIZE
if (data_limit and (data_size_bytes > (data_limit * (1024 ** 2)))):
log_msg = 'ExecutorID {} | JobID {} - Total data exceeded maximum size of {}'.format(executor_id, job_id, sizeof_fmt((data_limit * (1024 ** 2))))
raise Exception(log_msg)
logger.info('ExecutorID {} | JobID {} - Uploading function and data - Total: {}'.format(executor_id, job_id, total_size))
data_key = create_agg_data_key(JOBS_PREFIX, executor_id, job_id)
job.data_key = data_key
(data_bytes, data_ranges) = utils.agg_data(data_strs)
job.data_ranges = data_ranges
data_upload_start = time.time()
internal_storage.put_data(data_key, data_bytes)
data_upload_end = time.time()
host_job_meta['host_data_upload_time'] = round((data_upload_end - data_upload_start), 6)
func_upload_start = time.time()
if config[mode].get('customized_runtime'):
function_file = func.__code__.co_filename
function_hash = hashlib.md5(open(function_file, 'rb').read()).hexdigest()[:16]
mod_hash = hashlib.md5(repr(sorted(mod_paths)).encode('utf-8')).hexdigest()[:16]
uuid = f'{function_hash}{mod_hash}'
func_key = create_func_key(JOBS_PREFIX, uuid, )
_store_func_and_modules(func_key, func_str, module_data)
job.ext_runtime_uuid = uuid
else:
func_key = create_func_key(JOBS_PREFIX, executor_id, job_id)
internal_storage.put_func(func_key, func_module_str)
job.func_key = func_key
func_upload_end = time.time()
host_job_meta['host_func_upload_time'] = round((func_upload_end - func_upload_start), 6)
host_job_meta['host_job_created_time'] = round((time.time() - host_job_meta['host_job_create_tstamp']), 6)
job.metadata = host_job_meta
return job |
def untar(path, fname, deleteTar=True):
'\n Unpacks the given archive file to the same directory, then (by default)\n deletes the archive file.\n '
print(('unpacking ' + fname))
fullpath = os.path.join(path, fname)
shutil.unpack_archive(fullpath, path)
if deleteTar:
os.remove(fullpath) | -8,229,018,165,018,037,000 | Unpacks the given archive file to the same directory, then (by default)
deletes the archive file. | cogdl/datasets/gtn_data.py | untar | AlvinWen428/cogdl | python | def untar(path, fname, deleteTar=True):
'\n Unpacks the given archive file to the same directory, then (by default)\n deletes the archive file.\n '
print(('unpacking ' + fname))
fullpath = os.path.join(path, fname)
shutil.unpack_archive(fullpath, path)
if deleteTar:
os.remove(fullpath) |
@property
@abc.abstractmethod
def uuid(self) -> Optional[str]:
'Return the unique identifier of the repository.' | 4,545,748,468,575,769,000 | Return the unique identifier of the repository. | aiida/repository/backend/abstract.py | uuid | azadoks/aiida-core | python | @property
@abc.abstractmethod
def uuid(self) -> Optional[str]:
|
@property
@abc.abstractmethod
def key_format(self) -> Optional[str]:
'Return the format for the keys of the repository.\n\n Important for when migrating between backends (e.g. archive -> main), as if they are not equal then it is\n necessary to re-compute all the `Node.repository_metadata` before importing (otherwise they will not match\n with the repository).\n ' | -7,728,492,979,033,497,000 | Return the format for the keys of the repository.
Important for when migrating between backends (e.g. archive -> main), as if they are not equal then it is
necessary to re-compute all the `Node.repository_metadata` before importing (otherwise they will not match
with the repository). | aiida/repository/backend/abstract.py | key_format | azadoks/aiida-core | python | @property
@abc.abstractmethod
def key_format(self) -> Optional[str]:
'Return the format for the keys of the repository.\n\n Important for when migrating between backends (e.g. archive -> main), as if they are not equal then it is\n necessary to re-compute all the `Node.repository_metadata` before importing (otherwise they will not match\n with the repository).\n ' |
@abc.abstractmethod
def initialise(self, **kwargs) -> None:
"Initialise the repository if it hasn't already been initialised.\n\n :param kwargs: parameters for the initialisation.\n " | -6,842,518,518,233,794,000 | Initialise the repository if it hasn't already been initialised.
:param kwargs: parameters for the initialisation. | aiida/repository/backend/abstract.py | initialise | azadoks/aiida-core | python | @abc.abstractmethod
def initialise(self, **kwargs) -> None:
"Initialise the repository if it hasn't already been initialised.\n\n :param kwargs: parameters for the initialisation.\n " |
@property
@abc.abstractmethod
def is_initialised(self) -> bool:
'Return whether the repository has been initialised.' | -8,991,978,196,976,154,000 | Return whether the repository has been initialised. | aiida/repository/backend/abstract.py | is_initialised | azadoks/aiida-core | python | @property
@abc.abstractmethod
def is_initialised(self) -> bool:
|
@abc.abstractmethod
def erase(self) -> None:
'Delete the repository itself and all its contents.\n\n .. note:: This should not merely delete the contents of the repository but any resources it created. For\n example, if the repository is essentially a folder on disk, the folder itself should also be deleted, not\n just its contents.\n ' | 8,501,606,104,825,531,000 | Delete the repository itself and all its contents.
.. note:: This should not merely delete the contents of the repository but any resources it created. For
example, if the repository is essentially a folder on disk, the folder itself should also be deleted, not
just its contents. | aiida/repository/backend/abstract.py | erase | azadoks/aiida-core | python | @abc.abstractmethod
def erase(self) -> None:
'Delete the repository itself and all its contents.\n\n .. note:: This should not merely delete the contents of the repository but any resources it created. For\n example, if the repository is essentially a folder on disk, the folder itself should also be deleted, not\n just its contents.\n ' |
def put_object_from_filelike(self, handle: BinaryIO) -> str:
'Store the byte contents of a file in the repository.\n\n :param handle: filelike object with the byte content to be stored.\n :return: the generated fully qualified identifier for the object within the repository.\n :raises TypeError: if the handle is not a byte stream.\n '
if ((not isinstance(handle, io.BufferedIOBase)) and (not self.is_readable_byte_stream(handle))):
raise TypeError(f'handle does not seem to be a byte stream: {type(handle)}.')
return self._put_object_from_filelike(handle) | 9,115,440,169,624,832,000 | Store the byte contents of a file in the repository.
:param handle: filelike object with the byte content to be stored.
:return: the generated fully qualified identifier for the object within the repository.
:raises TypeError: if the handle is not a byte stream. | aiida/repository/backend/abstract.py | put_object_from_filelike | azadoks/aiida-core | python | def put_object_from_filelike(self, handle: BinaryIO) -> str:
'Store the byte contents of a file in the repository.\n\n :param handle: filelike object with the byte content to be stored.\n :return: the generated fully qualified identifier for the object within the repository.\n :raises TypeError: if the handle is not a byte stream.\n '
if ((not isinstance(handle, io.BufferedIOBase)) and (not self.is_readable_byte_stream(handle))):
raise TypeError(f'handle does not seem to be a byte stream: {type(handle)}.')
return self._put_object_from_filelike(handle) |
def put_object_from_file(self, filepath: Union[(str, pathlib.Path)]) -> str:
'Store a new object with contents of the file located at `filepath` on this file system.\n\n :param filepath: absolute path of file whose contents to copy to the repository.\n :return: the generated fully qualified identifier for the object within the repository.\n :raises TypeError: if the handle is not a byte stream.\n '
with open(filepath, mode='rb') as handle:
return self.put_object_from_filelike(handle) | -7,005,207,975,189,346,000 | Store a new object with contents of the file located at `filepath` on this file system.
:param filepath: absolute path of file whose contents to copy to the repository.
:return: the generated fully qualified identifier for the object within the repository.
:raises TypeError: if the handle is not a byte stream. | aiida/repository/backend/abstract.py | put_object_from_file | azadoks/aiida-core | python | def put_object_from_file(self, filepath: Union[(str, pathlib.Path)]) -> str:
'Store a new object with contents of the file located at `filepath` on this file system.\n\n :param filepath: absolute path of file whose contents to copy to the repository.\n :return: the generated fully qualified identifier for the object within the repository.\n :raises TypeError: if the handle is not a byte stream.\n '
with open(filepath, mode='rb') as handle:
return self.put_object_from_filelike(handle) |
@abc.abstractmethod
def has_objects(self, keys: List[str]) -> List[bool]:
'Return whether the repository has an object with the given key.\n\n :param keys:\n list of fully qualified identifiers for objects within the repository.\n :return:\n list of logicals, in the same order as the keys provided, with value True if the respective\n object exists and False otherwise.\n ' | -506,592,450,390,231,200 | Return whether the repository has an object with the given key.
:param keys:
list of fully qualified identifiers for objects within the repository.
:return:
list of logicals, in the same order as the keys provided, with value True if the respective
object exists and False otherwise. | aiida/repository/backend/abstract.py | has_objects | azadoks/aiida-core | python | @abc.abstractmethod
def has_objects(self, keys: List[str]) -> List[bool]:
'Return whether the repository has an object with the given key.\n\n :param keys:\n list of fully qualified identifiers for objects within the repository.\n :return:\n list of logicals, in the same order as the keys provided, with value True if the respective\n object exists and False otherwise.\n ' |
def has_object(self, key: str) -> bool:
'Return whether the repository has an object with the given key.\n\n :param key: fully qualified identifier for the object within the repository.\n :return: True if the object exists, False otherwise.\n '
return self.has_objects([key])[0] | 8,852,391,107,573,442,000 | Return whether the repository has an object with the given key.
:param key: fully qualified identifier for the object within the repository.
:return: True if the object exists, False otherwise. | aiida/repository/backend/abstract.py | has_object | azadoks/aiida-core | python | def has_object(self, key: str) -> bool:
'Return whether the repository has an object with the given key.\n\n :param key: fully qualified identifier for the object within the repository.\n :return: True if the object exists, False otherwise.\n '
return self.has_objects([key])[0] |
@abc.abstractmethod
def list_objects(self) -> Iterable[str]:
'Return iterable that yields all available objects by key.\n\n :return: An iterable for all the available object keys.\n ' | -939,318,421,040,364,300 | Return iterable that yields all available objects by key.
:return: An iterable for all the available object keys. | aiida/repository/backend/abstract.py | list_objects | azadoks/aiida-core | python | @abc.abstractmethod
def list_objects(self) -> Iterable[str]:
'Return iterable that yields all available objects by key.\n\n :return: An iterable for all the available object keys.\n ' |
@contextlib.contextmanager
def open(self, key: str) -> Iterator[BinaryIO]:
'Open a file handle to an object stored under the given key.\n\n .. note:: this should only be used to open a handle to read an existing file. To write a new file use the method\n ``put_object_from_filelike`` instead.\n\n :param key: fully qualified identifier for the object within the repository.\n :return: yield a byte stream object.\n :raise FileNotFoundError: if the file does not exist.\n :raise OSError: if the file could not be opened.\n '
if (not self.has_object(key)):
raise FileNotFoundError(f'object with key `{key}` does not exist.') | 3,297,650,485,873,668,000 | Open a file handle to an object stored under the given key.
.. note:: this should only be used to open a handle to read an existing file. To write a new file use the method
``put_object_from_filelike`` instead.
:param key: fully qualified identifier for the object within the repository.
:return: yield a byte stream object.
:raise FileNotFoundError: if the file does not exist.
:raise OSError: if the file could not be opened. | aiida/repository/backend/abstract.py | open | azadoks/aiida-core | python | @contextlib.contextmanager
def open(self, key: str) -> Iterator[BinaryIO]:
'Open a file handle to an object stored under the given key.\n\n .. note:: this should only be used to open a handle to read an existing file. To write a new file use the method\n ``put_object_from_filelike`` instead.\n\n :param key: fully qualified identifier for the object within the repository.\n :return: yield a byte stream object.\n :raise FileNotFoundError: if the file does not exist.\n :raise OSError: if the file could not be opened.\n '
if (not self.has_object(key)):
raise FileNotFoundError(f'object with key `{key}` does not exist.') |
def get_object_content(self, key: str) -> bytes:
'Return the content of a object identified by key.\n\n :param key: fully qualified identifier for the object within the repository.\n :raise FileNotFoundError: if the file does not exist.\n :raise OSError: if the file could not be opened.\n '
with self.open(key) as handle:
return handle.read() | 8,643,959,129,101,297,000 | Return the content of a object identified by key.
:param key: fully qualified identifier for the object within the repository.
:raise FileNotFoundError: if the file does not exist.
:raise OSError: if the file could not be opened. | aiida/repository/backend/abstract.py | get_object_content | azadoks/aiida-core | python | def get_object_content(self, key: str) -> bytes:
'Return the content of a object identified by key.\n\n :param key: fully qualified identifier for the object within the repository.\n :raise FileNotFoundError: if the file does not exist.\n :raise OSError: if the file could not be opened.\n '
with self.open(key) as handle:
return handle.read() |
@abc.abstractmethod
def iter_object_streams(self, keys: List[str]) -> Iterator[Tuple[(str, BinaryIO)]]:
'Return an iterator over the (read-only) byte streams of objects identified by key.\n\n .. note:: handles should only be read within the context of this iterator.\n\n :param keys: fully qualified identifiers for the objects within the repository.\n :return: an iterator over the object byte streams.\n :raise FileNotFoundError: if the file does not exist.\n :raise OSError: if a file could not be opened.\n ' | -8,532,632,070,989,044,000 | Return an iterator over the (read-only) byte streams of objects identified by key.
.. note:: handles should only be read within the context of this iterator.
:param keys: fully qualified identifiers for the objects within the repository.
:return: an iterator over the object byte streams.
:raise FileNotFoundError: if the file does not exist.
:raise OSError: if a file could not be opened. | aiida/repository/backend/abstract.py | iter_object_streams | azadoks/aiida-core | python | @abc.abstractmethod
def iter_object_streams(self, keys: List[str]) -> Iterator[Tuple[(str, BinaryIO)]]:
'Return an iterator over the (read-only) byte streams of objects identified by key.\n\n .. note:: handles should only be read within the context of this iterator.\n\n :param keys: fully qualified identifiers for the objects within the repository.\n :return: an iterator over the object byte streams.\n :raise FileNotFoundError: if the file does not exist.\n :raise OSError: if a file could not be opened.\n ' |
def get_object_hash(self, key: str) -> str:
'Return the SHA-256 hash of an object stored under the given key.\n\n .. important::\n A SHA-256 hash should always be returned,\n to ensure consistency across different repository implementations.\n\n :param key: fully qualified identifier for the object within the repository.\n :raise FileNotFoundError: if the file does not exist.\n :raise OSError: if the file could not be opened.\n '
with self.open(key) as handle:
return chunked_file_hash(handle, hashlib.sha256) | -5,363,301,719,493,803,000 | Return the SHA-256 hash of an object stored under the given key.
.. important::
A SHA-256 hash should always be returned,
to ensure consistency across different repository implementations.
:param key: fully qualified identifier for the object within the repository.
:raise FileNotFoundError: if the file does not exist.
:raise OSError: if the file could not be opened. | aiida/repository/backend/abstract.py | get_object_hash | azadoks/aiida-core | python | def get_object_hash(self, key: str) -> str:
'Return the SHA-256 hash of an object stored under the given key.\n\n .. important::\n A SHA-256 hash should always be returned,\n to ensure consistency across different repository implementations.\n\n :param key: fully qualified identifier for the object within the repository.\n :raise FileNotFoundError: if the file does not exist.\n :raise OSError: if the file could not be opened.\n '
with self.open(key) as handle:
return chunked_file_hash(handle, hashlib.sha256) |
@abc.abstractmethod
def delete_objects(self, keys: List[str]) -> None:
'Delete the objects from the repository.\n\n :param keys: list of fully qualified identifiers for the objects within the repository.\n :raise FileNotFoundError: if any of the files does not exist.\n :raise OSError: if any of the files could not be deleted.\n '
keys_exist = self.has_objects(keys)
if (not all(keys_exist)):
error_message = 'some of the keys provided do not correspond to any object in the repository:\n'
for (indx, key_exists) in enumerate(keys_exist):
if (not key_exists):
error_message += f''' > object with key `{keys[indx]}` does not exist.
'''
raise FileNotFoundError(error_message) | 6,488,864,614,444,447,000 | Delete the objects from the repository.
:param keys: list of fully qualified identifiers for the objects within the repository.
:raise FileNotFoundError: if any of the files does not exist.
:raise OSError: if any of the files could not be deleted. | aiida/repository/backend/abstract.py | delete_objects | azadoks/aiida-core | python | @abc.abstractmethod
def delete_objects(self, keys: List[str]) -> None:
'Delete the objects from the repository.\n\n :param keys: list of fully qualified identifiers for the objects within the repository.\n :raise FileNotFoundError: if any of the files does not exist.\n :raise OSError: if any of the files could not be deleted.\n '
keys_exist = self.has_objects(keys)
if (not all(keys_exist)):
error_message = 'some of the keys provided do not correspond to any object in the repository:\n'
for (indx, key_exists) in enumerate(keys_exist):
if (not key_exists):
error_message += f' > object with key `{keys[indx]}` does not exist.
'
raise FileNotFoundError(error_message) |
def delete_object(self, key: str) -> None:
'Delete the object from the repository.\n\n :param key: fully qualified identifier for the object within the repository.\n :raise FileNotFoundError: if the file does not exist.\n :raise OSError: if the file could not be deleted.\n '
return self.delete_objects([key]) | 2,549,091,568,805,183,000 | Delete the object from the repository.
:param key: fully qualified identifier for the object within the repository.
:raise FileNotFoundError: if the file does not exist.
:raise OSError: if the file could not be deleted. | aiida/repository/backend/abstract.py | delete_object | azadoks/aiida-core | python | def delete_object(self, key: str) -> None:
'Delete the object from the repository.\n\n :param key: fully qualified identifier for the object within the repository.\n :raise FileNotFoundError: if the file does not exist.\n :raise OSError: if the file could not be deleted.\n '
return self.delete_objects([key]) |
@classmethod
def setUpClass(cls):
'Launch the webdriver of choice with selected options(see browserconfig.py).\n Then login using pickled cookies(see tests/pickledlogin.py).'
if (browserconfig.current_browser in ['chrome', 'firefox']):
cls.driver = browserconfig.driver_runner(executable_path=browserconfig.driver_path, desired_capabilities=browserconfig.capabilities)
elif (browserconfig.current_browser == 'edge'):
cls.driver = browserconfig.driver_runner(executable_path=browserconfig.driver_path, capabilities=browserconfig.capabilities)
tests.pickledlogin.pickled_login(cls.driver) | 547,812,806,824,385,660 | Launch the webdriver of choice with selected options(see browserconfig.py).
Then login using pickled cookies(see tests/pickledlogin.py). | tests/test_headerpage.py | setUpClass | BradleyPelton/NetflixSelenium | python | @classmethod
def setUpClass(cls):
'Launch the webdriver of choice with selected options(see browserconfig.py).\n Then login using pickled cookies(see tests/pickledlogin.py).'
if (browserconfig.current_browser in ['chrome', 'firefox']):
cls.driver = browserconfig.driver_runner(executable_path=browserconfig.driver_path, desired_capabilities=browserconfig.capabilities)
elif (browserconfig.current_browser == 'edge'):
cls.driver = browserconfig.driver_runner(executable_path=browserconfig.driver_path, capabilities=browserconfig.capabilities)
tests.pickledlogin.pickled_login(cls.driver) |
@classmethod
def tearDownClass(cls):
'Closes the browser and shuts down the driver executable.'
cls.driver.quit() | 1,645,581,262,967,605,800 | Closes the browser and shuts down the driver executable. | tests/test_headerpage.py | tearDownClass | BradleyPelton/NetflixSelenium | python | @classmethod
def tearDownClass(cls):
cls.driver.quit() |
def setUp(self):
'Return to the home page, netflix.com/browse, the staging place for header tests.'
self.driver.get('https://netflix.com/browse') | 3,288,124,154,217,542,700 | Return to the home page, netflix.com/browse, the staging place for header tests. | tests/test_headerpage.py | setUp | BradleyPelton/NetflixSelenium | python | def setUp(self):
self.driver.get('https://netflix.com/browse') |
def test_logout_from_header(self):
'Logout from the header.'
header_page = pagemodels.headerpage.HeaderPage(self.driver)
header_page.logout()
self.assertIn('logout', self.driver.current_url)
tests.pickledlogin.pickled_login(self.driver) | 2,353,134,763,560,939,000 | Logout from the header. | tests/test_headerpage.py | test_logout_from_header | BradleyPelton/NetflixSelenium | python | def test_logout_from_header(self):
header_page = pagemodels.headerpage.HeaderPage(self.driver)
header_page.logout()
self.assertIn('logout', self.driver.current_url)
tests.pickledlogin.pickled_login(self.driver) |
def test_navigate_home_from_my_list(self):
'Using the giant Netflix logo in the top left, navigate to the home page /browse/\n from the my-list page.'
self.driver.get('https://www.netflix.com/browse/my-list')
header_page = pagemodels.headerpage.HeaderPage(self.driver)
header_page.navigate_to_home()
self.assertEqual('https://www.netflix.com/browse', self.driver.current_url) | -5,558,719,885,448,803,000 | Using the giant Netflix logo in the top left, navigate to the home page /browse/
from the my-list page. | tests/test_headerpage.py | test_navigate_home_from_my_list | BradleyPelton/NetflixSelenium | python | def test_navigate_home_from_my_list(self):
'Using the giant Netflix logo in the top left, navigate to the home page /browse/\n from the my-list page.'
self.driver.get('https://www.netflix.com/browse/my-list')
header_page = pagemodels.headerpage.HeaderPage(self.driver)
header_page.navigate_to_home()
self.assertEqual('https://www.netflix.com/browse', self.driver.current_url) |
def test_navigate_to_manage_profile(self):
'Using the header account dropdown, navigate to the manage profile page.'
header_page = pagemodels.headerpage.HeaderPage(self.driver)
header_page.navigate_to_manage_profile()
self.assertIn('profiles/manage', self.driver.current_url) | -6,285,243,719,116,505,000 | Using the header account dropdown, navigate to the manage profile page. | tests/test_headerpage.py | test_navigate_to_manage_profile | BradleyPelton/NetflixSelenium | python | def test_navigate_to_manage_profile(self):
header_page = pagemodels.headerpage.HeaderPage(self.driver)
header_page.navigate_to_manage_profile()
self.assertIn('profiles/manage', self.driver.current_url) |
def test_search_for_shawshank(self):
"Using the search field, search for 'shawshank' and assert that shawshank was found."
header_page = pagemodels.headerpage.HeaderPage(self.driver)
header_page.search('shawshank')
self.assertIn('The Shawshank Redemption', self.driver.page_source) | 428,388,069,566,930,800 | Using the search field, search for 'shawshank' and assert that shawshank was found. | tests/test_headerpage.py | test_search_for_shawshank | BradleyPelton/NetflixSelenium | python | def test_search_for_shawshank(self):
header_page = pagemodels.headerpage.HeaderPage(self.driver)
header_page.search('shawshank')
self.assertIn('The Shawshank Redemption', self.driver.page_source) |
def test_click_top_notification(self):
'Click the top notification and assert that the page has changed.'
header_page = pagemodels.headerpage.HeaderPage(self.driver)
header_page.click_top_notification()
self.assertTrue((('title' in self.driver.current_url) or ('notification' in self.driver.current_url))) | -6,941,320,859,743,506,000 | Click the top notification and assert that the page has changed. | tests/test_headerpage.py | test_click_top_notification | BradleyPelton/NetflixSelenium | python | def test_click_top_notification(self):
header_page = pagemodels.headerpage.HeaderPage(self.driver)
header_page.click_top_notification()
self.assertTrue((('title' in self.driver.current_url) or ('notification' in self.driver.current_url))) |
def dnn(tensor_in, hidden_units, activation=nn.relu, dropout=None):
'Creates fully connected deep neural network subgraph.\n\n Args:\n tensor_in: tensor or placeholder for input features.\n hidden_units: list of counts of hidden units in each layer.\n activation: activation function between layers. Can be None.\n dropout: if not None, will add a dropout layer with given probability.\n\n Returns:\n A tensor which would be a deep neural network.\n '
with vs.variable_scope('dnn'):
for (i, n_units) in enumerate(hidden_units):
with vs.variable_scope(('layer%d' % i)):
tensor_in = rnn_cell.linear(tensor_in, n_units, True)
if (activation is not None):
tensor_in = activation(tensor_in)
if (dropout is not None):
tensor_in = dropout_ops.dropout(tensor_in, prob=(1.0 - dropout))
return tensor_in | -8,516,419,455,471,346,000 | Creates fully connected deep neural network subgraph.
Args:
tensor_in: tensor or placeholder for input features.
hidden_units: list of counts of hidden units in each layer.
activation: activation function between layers. Can be None.
dropout: if not None, will add a dropout layer with given probability.
Returns:
A tensor which would be a deep neural network. | tensorflow/contrib/learn/python/learn/ops/dnn_ops.py | dnn | InfoPrice/tensorflow | python | def dnn(tensor_in, hidden_units, activation=nn.relu, dropout=None):
'Creates fully connected deep neural network subgraph.\n\n Args:\n tensor_in: tensor or placeholder for input features.\n hidden_units: list of counts of hidden units in each layer.\n activation: activation function between layers. Can be None.\n dropout: if not None, will add a dropout layer with given probability.\n\n Returns:\n A tensor which would be a deep neural network.\n '
with vs.variable_scope('dnn'):
for (i, n_units) in enumerate(hidden_units):
with vs.variable_scope(('layer%d' % i)):
tensor_in = rnn_cell.linear(tensor_in, n_units, True)
if (activation is not None):
tensor_in = activation(tensor_in)
if (dropout is not None):
tensor_in = dropout_ops.dropout(tensor_in, prob=(1.0 - dropout))
return tensor_in |
def __init__(self, parent=None, orientation='bottom', *args, **kargs):
"\n The *orientation* argument may be 'bottom', 'top', 'left', or 'right' \n indicating whether the gradient is displayed horizontally (top, bottom)\n or vertically (left, right) and on what side of the gradient the editable \n ticks will appear.\n \n All other arguments are passed to \n :func:`GradientEditorItem.__init__ <pyqtgraph.GradientEditorItem.__init__>`.\n \n Note: For convenience, this class wraps methods from \n :class:`GradientEditorItem <pyqtgraph.GradientEditorItem>`.\n "
GraphicsView.__init__(self, parent, useOpenGL=False, background=None)
self.maxDim = 31
kargs['tickPen'] = 'k'
self.item = GradientEditorItem(*args, **kargs)
self.item.sigGradientChanged.connect(self.sigGradientChanged)
self.item.sigGradientChangeFinished.connect(self.sigGradientChangeFinished)
self.setCentralItem(self.item)
self.setOrientation(orientation)
self.setCacheMode(self.CacheNone)
self.setRenderHints((QtGui.QPainter.Antialiasing | QtGui.QPainter.TextAntialiasing))
self.setFrameStyle((QtGui.QFrame.NoFrame | QtGui.QFrame.Plain)) | 3,786,569,015,888,706,600 | The *orientation* argument may be 'bottom', 'top', 'left', or 'right'
indicating whether the gradient is displayed horizontally (top, bottom)
or vertically (left, right) and on what side of the gradient the editable
ticks will appear.
All other arguments are passed to
:func:`GradientEditorItem.__init__ <pyqtgraph.GradientEditorItem.__init__>`.
Note: For convenience, this class wraps methods from
:class:`GradientEditorItem <pyqtgraph.GradientEditorItem>`. | scripts/pyqtgraph-develop/pyqtgraph/widgets/GradientWidget.py | __init__ | kuldeepaman/tf-pose | python | def __init__(self, parent=None, orientation='bottom', *args, **kargs):
"\n The *orientation* argument may be 'bottom', 'top', 'left', or 'right' \n indicating whether the gradient is displayed horizontally (top, bottom)\n or vertically (left, right) and on what side of the gradient the editable \n ticks will appear.\n \n All other arguments are passed to \n :func:`GradientEditorItem.__init__ <pyqtgraph.GradientEditorItem.__init__>`.\n \n Note: For convenience, this class wraps methods from \n :class:`GradientEditorItem <pyqtgraph.GradientEditorItem>`.\n "
GraphicsView.__init__(self, parent, useOpenGL=False, background=None)
self.maxDim = 31
kargs['tickPen'] = 'k'
self.item = GradientEditorItem(*args, **kargs)
self.item.sigGradientChanged.connect(self.sigGradientChanged)
self.item.sigGradientChangeFinished.connect(self.sigGradientChangeFinished)
self.setCentralItem(self.item)
self.setOrientation(orientation)
self.setCacheMode(self.CacheNone)
self.setRenderHints((QtGui.QPainter.Antialiasing | QtGui.QPainter.TextAntialiasing))
self.setFrameStyle((QtGui.QFrame.NoFrame | QtGui.QFrame.Plain)) |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.