text
stringlengths 67
7.88k
|
|---|
<|fim_prefix|>def <|fim_suffix|>(self, session):
pass<|fim_middle|>on_204<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(g):
g.cmd(b's', b'T05thread:01;')<|fim_middle|>gdb_step<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self):
self.check('/admin/default/shell')
ws_url = server.base_url.replace('http://', 'ws://') + '/admin/default/webshell-data'
ws = create_connection(ws_url)
# Python expressions are computed
ws.send('1 + 2')
eq_(ws.recv(), '3')
# Session state is maintained. Gramex can be imported
ws.send('import gramex')
eq_(ws.recv(), '')
ws.send('gramex.__version__')
eq_(ast.literal_eval(ws.recv()), gramex.__version__)
# handler is available for use
ws.send('handler.session')
result = ast.literal_eval(ws.recv())
ok_('_t' in result and 'id' in result)<|fim_middle|>test_shell<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self, x):
self.__buf.write(struct.pack('>L', x))<|fim_middle|>pack_uint<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self):
action = ChatJoinRequestHandler(self.callback)
for attr in action.__slots__:
assert getattr(action, attr, "err") != "err", f"got extra slot '{attr}'"
assert len(mro_slots(action)) == len(set(mro_slots(action))), "duplicate slot"<|fim_middle|>test_slot_behaviour<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self) -> str:
"""
Fully qualified resource ID for the resource. Ex - /subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName}
"""
return pulumi.get(self, "id")<|fim_middle|>id<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(path: Optional[Path] = None) -> Path:
if path is None:
path = Path.cwd()
here = path
while here.parent != here:
config = here / ".neuro.toml"
if config.exists():
return here
here = here.parent
raise ConfigError(f"Project root is not found for {path}")<|fim_middle|>find_project_root<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>():
parser = argparse.ArgumentParser(
description=USAGE,
prog="ddtrace-run",
usage="ddtrace-run <your usual python command>",
formatter_class=argparse.RawTextHelpFormatter,
)
parser.add_argument("command", nargs=argparse.REMAINDER, type=str, help="Command string to execute.")
parser.add_argument("-d", "--debug", help="enable debug mode (disabled by default)", action="store_true")
parser.add_argument(
"-i",
"--info",
help=(
"print library info useful for debugging. Only reflects configurations made via environment "
"variables, not those made in code."
),
action="store_true",
)
parser.add_argument("-p", "--profiling", help="enable profiling (disabled by default)", action="store_true")
parser.add_argument("-v", "--version", action="version", version="%(prog)s " + ddtrace.__version__)
parser.add_argument("-nc", "--colorless", help="print output of command without color", action="store_true")
args = parser.parse_args()
if args.profiling:
os.environ["DD_PROFILING_ENABLED"] = "true"
if args.debug or ddtrace.config._debug_mode:
logging.basicConfig(level=logging.DEBUG)
os.environ["DD_TRACE_DEBUG"] = "true"
if args.info:
# Inline imports for performance.
from ddtrace.internal.debug import pretty_collect
print(pretty_collect(ddtrace.tracer, color=not args.colorless))
sys.exit(0)
root_dir = os.path.dirname(ddtrace.__file__)
log.debug("ddtrace root: %s", root_dir)
bootstrap_dir = os.path.join(root_dir, "bootstrap")
log.debug("ddtrace bootstrap: %s", bootstrap_dir)
_add_bootstrap_to_pythonpath(bootstrap_dir)
log.debug("PYTHONPATH: %s", os.environ["PYTHONPATH"])
log.debug("sys.path: %s", sys.path)
if not args.command:
parser.print_help()
sys.exit(1)
# Find the executable path
executable = find_executable(args.command[0])
if executable is None:
print("ddtrace-run: failed to find executable '%s'.\n" % args.command[0])
parser.print_usage()
sys.exit(1)
log.debug("program executable: %s", executable)
if os.path.basename(executable) == "uwsgi":
print(
(
"ddtrace-run has known compatibility issues with uWSGI where the "
"tracer is not started properly in uWSGI workers which can cause "
"broken behavior. It is recommended you remove ddtrace-run and "
"update your uWSGI configuration following "
"https://ddtrace.readthedocs.io/en/stable/advanced_usage.html#uwsgi."
)
)
try:
os.execl(executable, executable, *args.command[1:])
except PermissionError:
print("ddtrace-run: permission error while launching '%s'" % executable)
print("Did you mean `ddtrace-run python %s`?" % executable)
sys.exit(1)
except Exception:
print("ddtrace-run: error launching '%s'" % executable)
raise
sys.exit(0)<|fim_middle|>main<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(iterable, n):
"""
Split a interable into chunks of length n with the final element
being the remainder len < n if n does not divide evenly
"""
len_iter = len(iterable)
return [iterable[i: min(i + n, len_iter)] for i in range(0, len_iter, n)]<|fim_middle|>take_n<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self):
log.debug("Loading live event")
res = self.request("GET", self.live_url)
for event in res.get("events", []):
return "event/{sportId}/{propertyId}/{tournamentId}/{id}".format(**event)<|fim_middle|>get_live_id<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(n_servers, i=None):
return server_n<|fim_middle|>dist_fcn_1_server<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self) -> 'outputs.PrivateEndpointConnectionPropertiesResponse':
"""
Resource properties.
"""
return pulumi.get(self, "properties")<|fim_middle|>properties<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self):
cli_params = ['application_name', 'config_file', 'eu-west-1', '--destinationTableAutoCreate', '--connection-pre-test', 'False']
config_reader = GlobalConfigParametersReader()
default_parameters = config_reader.get_config_key_values_updated_with_cli_args(cli_params)
expected_value = True
returned_value = default_parameters['destinationTableAutoCreate']
self.assertEqual(expected_value, returned_value)<|fim_middle|>test_global_config_reader_overwritten_default_value<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(
staff_api_client, permission_manage_shipping, shipping_method
):
# given
shipping_method.store_value_in_private_metadata({PUBLIC_KEY: PUBLIC_VALUE})
shipping_method.save(update_fields=["metadata"])
shipping_method_id = graphene.Node.to_global_id(
"ShippingMethodType", shipping_method.pk
)
# when
response = execute_clear_private_metadata_for_item(
staff_api_client,
permission_manage_shipping,
shipping_method_id,
"ShippingMethodType",
)
# then
assert item_without_private_metadata(
response["data"]["deletePrivateMetadata"]["item"],
shipping_method,
shipping_method_id,
)<|fim_middle|>test_delete_private_metadata_for_shipping_method<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self):
if not session.user:
raise Forbidden
# If the user cannot manage the whole event see if anything gives them
# limited management access.
if not self.event.can_manage(session.user):
urls = sorted(values_from_signal(signals.event_management.management_url.send(self.event),
single_value=True))
response = redirect(urls[0]) if urls else None
raise Forbidden(response=response)
RHManageEventBase.METHOD_NAME(self) # mainly to trigger the legacy "event locked" check<|fim_middle|>check_access<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(cursor) -> List[Tuple[DbTableSchema, str]]:
schemas: Dict = {}
for row in cursor.fetchall():
table_schema_name: str = row[_TABLE_SCHEMA]
table_name: DbTableMeta = DbTableMeta(row[_TABLE_NAME])
table_column: DbColumn = DbColumn(
name=row[_COLUMN_NAME],
type=row[_UDT_NAME],
ordinal_position=row[_ORDINAL_POSITION],
)
try:
table_database = row[_TABLE_DATABASE]
except IndexError:
table_database = None
# Attempt to get table schema
table_key = ".".join(
filter(None, [table_database, table_schema_name, table_name.name])
)
# table_key: str = f"{table_schema_name}.{table_name}"
table_schema: Optional[DbTableSchema]
table_schema, _ = schemas.get(table_key) or (None, None)
if table_schema:
# Add column to existing table schema.
schemas[table_key][0].columns.append(table_column)
else:
# Create new table schema with column.
schemas[table_key] = (
DbTableSchema(
schema_name=table_schema_name,
table_name=table_name,
columns=[table_column],
),
table_database,
)
return list(schemas.values())<|fim_middle|>parse_query_result<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>():
# Try again with a target with a stretched y axis.
A_orig = np.array([[-3, 3], [-2, 3], [-2, 2], [-3, 2]], dtype=float)
B_orig = np.array([[3, 40], [1, 0], [3, -40], [5, 0]], dtype=float)
A, A_mu = _centered(A_orig)
B, B_mu = _centered(B_orig)
R, s = orthogonal_procrustes(A, B)
scale = s / np.square(norm(A))
B_approx = scale * np.dot(A, R) + B_mu
expected = np.array([[3, 21], [-18, 0], [3, -21], [24, 0]], dtype=float)
assert_allclose(B_approx, expected, atol=1e-8)
# Check disparity symmetry.
expected_disparity = 0.4501246882793018
AB_disparity = np.square(norm(B_approx - B_orig) / norm(B))
assert_allclose(AB_disparity, expected_disparity)
R, s = orthogonal_procrustes(B, A)
scale = s / np.square(norm(B))
A_approx = scale * np.dot(B, R) + A_mu
BA_disparity = np.square(norm(A_approx - A_orig) / norm(A))
assert_allclose(BA_disparity, expected_disparity)<|fim_middle|>test_orthogonal_procrustes_stretched_example<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(
mock_smb_client: SMBClient,
smb_remote_access_client: SMBRemoteAccessClient,
):
tags = EXPLOITER_TAGS.copy()
smb_remote_access_client.login(FULL_CREDENTIALS[0], set())
smb_remote_access_client.execute_agent(DESTINATION_PATH, tags)
assert tags == EXPLOITER_TAGS.union(EXECUTION_TAGS)<|fim_middle|>test_execute_succeeds<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self) -> str:
"""
Gets the workflow trigger callback URL relative path.
"""
return pulumi.get(self, "relative_path")<|fim_middle|>relative_path<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self):
form_data = {
"name": "Assunto 2",
"visible": True,
"init_date": datetime.now() + timedelta(days=2),
"end_date": datetime.now() + timedelta(days=3),
"subscribe_begin": datetime.now(),
"subscribe_end": datetime.now() + timedelta(days=1),
"category": self.category,
"tags": "teste,test,testando"
}
form = SubjectForm(data=form_data, initial={"category": self.category})
form.save()
subject = Subject.objects.latest("id")
tags = [str(t) for t in subject.tags.all()]
self.assertIn("teste", tags)
self.assertIn("test", tags)
self.assertIn("testando", tags)<|fim_middle|>test_form_tags<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self):
self.deployment_type = "AllAtOnce"
self.pre_traffic_hook = "pre_traffic_function_ref"
self.post_traffic_hook = "post_traffic_function_ref"
self.alarms = ["alarm1ref", "alarm2ref"]
self.role = {"Ref": "MyRole"}
self.trigger_configurations = {
"TriggerEvents": ["DeploymentSuccess", "DeploymentFailure"],
"TriggerTargetArn": {"Ref": "MySNSTopic"},
"TriggerName": "TestTrigger",
}
self.condition = "condition"<|fim_middle|>set_up<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(x, n):
c = 0.9
mu = (np.arange(1, n+1) - 0.5)/n
return x - 1/(1 - c/(2*n) * (mu[:,None]*x / (mu[:,None] + mu)).sum(axis=1))<|fim_middle|>f_6<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>():
args = argsparser()
config_parser = ConfigParser(args)
args = config_parser.parser()
random.seed(args.seed)
np.random.seed(args.seed)
paddle.seed(args.seed)
paddle.device.set_device(args.device)
class_name = args.category
assert class_name in mvtec.CLASS_NAMES
print("Testing model for {}".format(class_name))
# build model
model = get_model(args.method)(arch=args.backbone,
pretrained=False,
k=args.k,
method=args.method)
model.eval()
state = paddle.load(args.model_path)
model.model.set_dict(state["params"])
model.load(state["stats"])
model.eval()
# build data
MVTecDataset = mvtec.MVTecDataset(is_predict=True)
transform_x = MVTecDataset.get_transform_x()
x = Image.open(args.img_path).convert('RGB')
x = transform_x(x).unsqueeze(0)
predict(args, model, x)<|fim_middle|>main<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(api_dir, xml_dir):
import subprocess, sys
try:
# We don't generate groups since we create those manually
ret = subprocess.call('breathe-apidoc -m -o %s -p openucx %s -g struct,file' % (api_dir, xml_dir), shell=True)
if ret < 0:
sys.stderr.write('breathe-apidoc error code %s' % (-ret))
except OSError as e:
sys.stderr.write('breathe-apidoc execution failed: %s' % e)<|fim_middle|>run_apidoc<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(
tmp_path: Path,
filename: str,
fmt: str | None,
data: str,
expected: Any,
testing_metadata,
):
path = tmp_path / filename
path.write_text(data)
assert (
jinja_context.load_file_data(str(path), fmt, config=testing_metadata.config)
== expected
)<|fim_middle|>test_load_file_data<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self) -> int:
return hash(self)<|fim_middle|>hash_code<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self):
"""Open preferences dialog"""
widgets = gamewidget.getWidgets()
preferencesDialog.run(widgets)
notebook = widgets["preferences_notebook"]
self.assertIsNotNone(preferencesDialog.general_tab)
notebook.next_page()
self.assertIsNotNone(preferencesDialog.hint_tab)
notebook.next_page()
self.assertIsNotNone(preferencesDialog.theme_tab)
notebook.next_page()
self.assertIsNotNone(preferencesDialog.sound_tab)
notebook.next_page()
self.assertIsNotNone(preferencesDialog.save_tab)<|fim_middle|>test4<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(dataarray) -> None:
data_repr = fh.short_data_repr_html(dataarray)
assert data_repr.startswith("<pre>array")<|fim_middle|>test_short_data_repr_html<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self, fileno, new=False):
mask = 0
if self.listeners[self.READ].get(fileno):
mask |= self.READ_MASK | self.EXC_MASK
if self.listeners[self.WRITE].get(fileno):
mask |= self.WRITE_MASK | self.EXC_MASK
try:
if mask:
if new:
self.poll.METHOD_NAME(fileno, mask)
else:
try:
self.poll.modify(fileno, mask)
except (IOError, OSError):
self.poll.METHOD_NAME(fileno, mask)
else:
try:
self.poll.unregister(fileno)
except (KeyError, IOError, OSError):
# raised if we try to remove a fileno that was
# already removed/invalid
pass
except ValueError:
# fileno is bad, issue 74
self.remove_descriptor(fileno)
raise<|fim_middle|>register<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self):
# restart the collectd mapper to use recently set port
c8y_mapper_status = self.startProcess(
command=self.sudo,
arguments=["systemctl", "restart", "tedge-mapper-collectd.service"],
stdouterr="collectd_mapper_restart",
)
# check the status of the collectd mapper
c8y_mapper_status = self.startProcess(
command=self.sudo,
arguments=["systemctl", "status", "tedge-mapper-collectd.service"],
stdouterr="collectd_mapper_status",
)
self.assertGrep(
"collectd_mapper_status.out",
" MQTT connection error: I/O: Connection refused (os error 111)",
contains=False,
)<|fim_middle|>validate_collectd_mapper<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self, collection_name, vectors, top_k):
# Search vector in milvus collection
try:
self.set_collection(collection_name)
search_params = {
"metric_type": METRIC_TYPE,
"params": {
"nprobe": 16
}
}
res = self.collection.search(
vectors,
anns_field="embedding",
param=search_params,
limit=top_k)
LOGGER.debug(f"Successfully search in collection: {res}")
return res
except Exception as e:
LOGGER.error(f"Failed to search vectors in Milvus: {e}")
sys.exit(1)<|fim_middle|>search_vectors<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(q, t, q_len, t_len):
"""Compute the sliding dot products between a query and a time series.
Parameters
----------
q: numpy.array
Query.
t: numpy.array
Time series.
q_len: int
Length of the query.
t_len: int
Length of the time series.
Output
------
dot_prod: numpy.array
Sliding dot products between q and t.
"""
# Reversing query and padding both query and time series
t_padded = np.pad(t, (0, t_len))
q_reversed = np.flipud(q)
q_reversed_padded = np.pad(q_reversed, (0, 2 * t_len - q_len))
# Applying FFT to both query and time series
t_fft = np.fft.fft(t_padded)
q_fft = np.fft.fft(q_reversed_padded)
# Applying inverse FFT to obtain the convolution of the time series by
# the query
element_wise_mult = np.multiply(t_fft, q_fft)
inverse_fft = np.fft.ifft(element_wise_mult)
# Returns only the valid dot products from inverse_fft
dot_prod = inverse_fft[q_len - 1 : t_len].real
return dot_prod<|fim_middle|>sliding_dot_products<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(file_path, size=None):
"""
Turn given picture into a smaller version.
"""
im = Image.open(file_path)
if size is not None:
(width, height) = size
if height == 0:
size = get_full_size_from_width(im, width)
else:
size = im.size
im = make_im_bigger_if_needed(im, size)
im = fit_to_target_size(im, size)
im.thumbnail(size, Image.Resampling.LANCZOS)
if im.mode == "CMYK":
im = im.convert("RGBA")
final = Image.new("RGBA", size, (0, 0, 0, 0))
final.paste(
im, (int((size[0] - im.size[0]) / 2), int((size[1] - im.size[1]) / 2))
)
final.save(file_path, "PNG")
return file_path<|fim_middle|>turn_into_thumbnail<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self):
pass<|fim_middle|>test_future<|file_separator|> |
<|fim_prefix|> <|fim_suffix|>(self):<|fim_middle|>contents<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>():
group_delete_mock = MagicMock(return_value=True)
group_info_mock = MagicMock(return_value={"things": "stuff"})
with patch.dict(group.__salt__, {"group.delete": group_delete_mock}), patch.dict(
group.__salt__, {"group.info": group_info_mock}
):
ret = group.absent("salt", local=True)
assert ret == {
"changes": {"salt": ""},
"comment": "Removed group salt",
"name": "salt",
"result": True,
}
if salt.utils.platform.is_windows():
group_info_mock.assert_called_once_with("salt")
group_delete_mock.assert_called_once_with("salt")
else:
group_info_mock.assert_called_once_with("salt", root="/")
group_delete_mock.assert_called_once_with("salt", local=True)<|fim_middle|>test_absent_with_local<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(bin):
if type(bin) == type(bytes()):
try:
return bytes.decode(bin, encoding='utf-8', errors='strict')
except:
pass
# we want a hexdump in \xNN notation. bin.hex only takes a single char, so we replace that later.
return "\\x" + bin.hex(':').replace(':', "\\x")
return "ERROR: unknown type in bin_dumper(): " + str(type(bin))<|fim_middle|>bin_dumper<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>():
# One of these environment variables are guaranteed to exist
# from our official docker images.
# DISPATCH_VERSION is from a tagged release, and DISPATCH_BUILD is from a
# a git based image.
return "DISPATCH_VERSION" in os.environ or "DISPATCH_BUILD" in os.environ<|fim_middle|>is_docker<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(validate_event_schema):
def inner(message, **kwargs):
event = serialize({"logentry": {"message": message}}, **kwargs)
validate_event_schema(event)
return event["logentry"]["message"]
return inner<|fim_middle|>message_normalizer<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>():
s = vaex.string_column(["aap", None, "noot", "mies"])
o = ["aap", None, "noot", np.nan]
x = np.arange(4, dtype=np.float64)
x[2] = x[3] = np.nan
m = np.ma.array(x, mask=[0, 1, 0, 1])
df = vaex.from_arrays(x=x, m=m, s=s, o=o)
x = df.x.dropmissing().tolist()
assert (9 not in x)
assert np.any(np.isnan(x)), "nan is not a missing value"
m = df.m.dropmissing().tolist()
assert (m[:1] == [0])
assert np.isnan(m[1])
assert len(m) == 2
assert (df.s.dropmissing().tolist() == ["aap", "noot", "mies"])
assert (df.o.dropmissing().tolist()[:2] == ["aap", "noot"])
# this changed in vaex 4, since the np.nan is considered missing, the whole
# columns is seen as string
# assert np.isnan(df.o.dropmissing().tolist()[2])<|fim_middle|>test_dropmissing<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(A, node_features, k):
"""
Compute the k-hop adjacency matrix and aggregated features using message passing.
Parameters:
A (numpy array or scipy sparse matrix): The adjacency matrix of the graph.
node_features (numpy array or scipy sparse matrix): The feature matrix of the nodes.
k (int): The number of hops for message passing.
Returns:
A_k (numpy array): The k-hop adjacency matrix.
agg_features (numpy array): The aggregated feature matrix for each node in the k-hop neighborhood.
"""
# Convert input matrices to sparse matrices if they are not already
if not sp.issparse(A):
A = sp.csr_matrix(A)
if not sp.issparse(node_features):
node_features = sp.csr_matrix(node_features)
# Compute the k-hop adjacency matrix and the aggregated features
A_k = A.copy()
agg_features = node_features.copy()
for i in tqdm(range(k)):
# Compute the message passing for the k-hop neighborhood
message = A_k.dot(node_features)
# Apply a GCN layer to aggregate the messages
agg_features = A_k.dot(agg_features) + message
# Update the k-hop adjacency matrix by adding new edges
A_k += A_k.dot(A)
return A_k.toarray(), agg_features.toarray()<|fim_middle|>k_hop_message_passing_sparse<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self):
if self.options.shared:
self.options.rm_safe("fPIC")
self.options["trantor"].shared = True
if not self.options.with_orm:
del self.options.with_postgres
del self.options.with_postgres_batch
del self.options.with_mysql
del self.options.with_sqlite
del self.options.with_redis
elif not self.options.with_postgres:
del self.options.with_postgres_batch<|fim_middle|>configure<|file_separator|> |
<|fim_prefix|>async def <|fim_suffix|>(self):
pass<|fim_middle|>async_tear_down<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(
self,
recipe: BaseRecipe,
recipe_conf: PerfRecipeConf,
results: List[PerfMeasurementResults],
) -> List[List[PerfMeasurementResults]]:
results_by_host = self._divide_results_by_host(results)
for host_results in results_by_host.values():
yield host_results<|fim_middle|>group_results<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>():
aq17 = ThermoFunDatabase("aq17")
T = 298.15
P = 1.0e5
#-------------------------------------------------------------------
# Testing attributes and thermodynamic properties of H2O@
#-------------------------------------------------------------------
species = aq17.species().get("H2O@")
assert species.formula().equivalent("H2O")
assert species.substance() == "Water HGK"
assert species.aggregateState() == AggregateState.Aqueous
assert species.charge() == 0
assert species.molarMass() == pytest.approx(0.0180153)
props = species.standardThermoProps(T, P)
assert props.G0[0] == pytest.approx(-2.371817e+05)
assert props.H0[0] == pytest.approx(-2.858310e+05)
assert props.V0[0] == pytest.approx( 1.806862e-05)
assert props.Cp0[0] == pytest.approx( 7.532758e+01)
#-------------------------------------------------------------------
# Testing attributes and thermodynamic properties of CO3-2
#-------------------------------------------------------------------
species = aq17.species().get("CO3-2")
assert species.formula().equivalent("CO3-2")
assert species.substance() == "CO3-2 carbonate ion"
assert species.aggregateState() == AggregateState.Aqueous
assert species.charge() == -2
assert species.molarMass() == pytest.approx(0.0600100979)
props = species.standardThermoProps(T, P)
assert props.G0[0] == pytest.approx(-5.279830e+05)
assert props.H0[0] == pytest.approx(-6.752359e+05)
assert props.V0[0] == pytest.approx(-6.063738e-06)
assert props.Cp0[0] == pytest.approx(-3.228612e+02)
#-------------------------------------------------------------------
# Testing attributes and thermodynamic properties of Ca+2
#-------------------------------------------------------------------
species = aq17.species().get("Ca+2")
assert species.formula().equivalent("Ca+2")
assert species.substance() == "Ca+2 ion"
assert species.aggregateState() == AggregateState.Aqueous
assert species.charge() == +2
assert species.molarMass() == pytest.approx(0.040076902)
props = species.standardThermoProps(T, P)
assert props.G0[0] == pytest.approx(-5.528210e+05)
assert props.H0[0] == pytest.approx(-5.431003e+05)
assert props.V0[0] == pytest.approx(-1.844093e-05)
assert props.Cp0[0] == pytest.approx(-3.099935e+01)
#-------------------------------------------------------------------
# Testing attributes and thermodynamic properties of CO2
#-------------------------------------------------------------------
species = aq17.species().get("CO2")
assert species.formula().equivalent("CO2")
assert species.substance() == "Carbon dioxide (CO2)"
assert species.aggregateState() == AggregateState.Gas
assert species.charge() == 0
assert species.molarMass() == pytest.approx(0.0440096006)
props = species.standardThermoProps(T, P)
assert props.G0[0] == pytest.approx(-3.943510e+05)
assert props.H0[0] == pytest.approx(-3.935472e+05)
assert props.V0[0] == pytest.approx( 0.0000000000)
assert props.Cp0[0] == pytest.approx( 3.710812e+01)
#-------------------------------------------------------------------
# Testing attributes and thermodynamic properties of Calcite
#-------------------------------------------------------------------
species = aq17.species().get("Calcite")
assert species.formula().equivalent("CaCO3")
assert species.substance() == "Calcite (cc)"
assert species.aggregateState() == AggregateState.CrystallineSolid
assert species.charge() == 0
assert species.molarMass() == pytest.approx(0.1000869999)
props = species.standardThermoProps(T, P)
assert props.G0[0] == pytest.approx(-1.129195e+06)
assert props.H0[0] == pytest.approx(-1.207470e+06)
assert props.V0[0] == pytest.approx( 3.689000e-05)
assert props.Cp0[0] == pytest.approx( 8.337073e+01)
with pytest.raises(RuntimeError):
assert ThermoFunDatabase("not-a-valid-file-name")
with pytest.raises(RuntimeError):
assert ThermoFunDatabase.withName("not-a-valid-file-name")
with pytest.raises(RuntimeError):
assert ThermoFunDatabase.fromFile("not-a-valid-file-name")<|fim_middle|>test_thermo_fun_database<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(next_link=None):
if not next_link:
request = build_list_request(
subscription_id=self._config.subscription_id,
api_version=api_version,
template_url=self.list.metadata["url"],
headers=_headers,
params=_params,
)
request = _convert_request(request)
request.url = self._client.format_url(request.url)
else:
# make call to next link with the client's api-version
_parsed_next_link = urllib.parse.urlparse(next_link)
_next_request_params = case_insensitive_dict(
{
key: [urllib.parse.quote(v) for v in value]
for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
}
)
_next_request_params["api-version"] = self._config.api_version
request = HttpRequest(
"GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
)
request = _convert_request(request)
request.url = self._client.format_url(request.url)
request.method = "GET"
return request<|fim_middle|>prepare_request<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self, record: logging.LogRecord) -> str:
levelname = record.levelname
if self.use_color and levelname in self.COLORS:
levelname_with_color = (
self.COLOR_SEQ % (30 + self.COLORS[levelname])
+ levelname
+ self.RESET_SEQ
)
record.levelname = levelname_with_color
formated_record = logging.Formatter.METHOD_NAME(self, record)
record.levelname = (
levelname # Resetting levelname as `record` might be used elsewhere
)
return formated_record
else:
return logging.Formatter.METHOD_NAME(self, record)<|fim_middle|>format<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self):
section = self.doc_structure.add_new_section('mysection')
section.writeln('section contents')
self.doc_structure.hrefs['foo'] = 'www.foo.com'
section.hrefs['bar'] = 'www.bar.com'
contents = self.doc_structure.flush_structure()
self.assertIn(b'.. _foo: www.foo.com', contents)
self.assertIn(b'.. _bar: www.bar.com', contents)<|fim_middle|>test_flush_structure_hrefs<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>():
"""
"vendors" notary into docker by copying all of notary into the docker
vendor directory - also appending several lines into the Dockerfile because
it pulls down notary from github and builds the binaries
"""
docker_notary_relpath = "vendor/src/github.com/theupdateframework/notary"
docker_notary_abspath = os.path.join(DOCKER_DIR, docker_notary_relpath)
print("copying notary ({0}) into {1}".format(NOTARY_DIR, docker_notary_abspath))
def ignore_dirs(walked_dir, _):
"""
Don't vendor everything, particularly not the docker directory
recursively, if it happened to be in the notary directory
"""
if walked_dir == NOTARY_DIR:
return [".git", ".cover", "docs", "bin"]
elif walked_dir == os.path.join(NOTARY_DIR, "fixtures"):
return ["compatibility"]
return []
if os.path.exists(docker_notary_abspath):
shutil.rmtree(docker_notary_abspath)
shutil.copytree(
NOTARY_DIR, docker_notary_abspath, symlinks=True, ignore=ignore_dirs)
# hack this because docker/docker's Dockerfile checks out a particular version of notary
# based on a tag or SHA, and we want to build based on what was vendored in
dockerfile_addition = ("\n"
"RUN set -x && "
"export GO15VENDOREXPERIMENT=1 && "
"go build -o /usr/local/bin/notary-server github.com/theupdateframework/notary/cmd/notary-server &&"
"go build -o /usr/local/bin/notary github.com/theupdateframework/notary/cmd/notary")
with open(os.path.join(DOCKER_DIR, "Dockerfile")) as dockerfile:
text = dockerfile.read()
if not text.endswith(dockerfile_addition):
with open(os.path.join(DOCKER_DIR, "Dockerfile"), 'a+') as dockerfile:
dockerfile.write(dockerfile_addition)
# hack the makefile so that we tag the built image as something else so we
# don't interfere with any other docker test builds
with open(os.path.join(DOCKER_DIR, "Makefile"), 'r') as makefile:
makefiletext = makefile.read()
with open(os.path.join(DOCKER_DIR, "Makefile"), 'wb') as makefile:
image_name = os.getenv("DOCKER_TEST_IMAGE_NAME", "notary-docker-vendor-test")
text = re.sub("^DOCKER_IMAGE := .+$", "DOCKER_IMAGE := {0}".format(image_name),
makefiletext, 1, flags=re.M)
makefile.write(text)<|fim_middle|>fake_vendor<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(context, data_dict):
return {'success': False, 'msg': 'Not implemented yet in the auth refactor'}<|fim_middle|>revision_undelete<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>():
if not isRunningAsRoot():
return False
if not isMMapSupported():
return False
return True<|fim_middle|>is_timing_series_supported<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(filename, line):
"""
Append one line of text to filename.
:param filename: Path to the file.
:type filename: str
:param line: Line to be written.
:type line: str
"""
append_file(filename, line.rstrip("\n") + "\n")<|fim_middle|>append_one_line<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self, assembler):
"""
Create a list of functions to be tested and their reference values for the problem
"""
func_list = [
functions.StructuralMass(assembler),
functions.Compliance(assembler),
functions.KSDisplacement(
assembler, ksWeight=ksweight, direction=[0.0, 0.0, 1.0]
),
functions.KSFailure(assembler, ksWeight=ksweight, safetyFactor=1.5),
]
return func_list, FUNC_REFS<|fim_middle|>setup_funcs<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(request, kube_apis):
filtered_ns_1 = create_namespace_with_name_from_yaml(kube_apis.v1, f"filtered-ns-1", f"{TEST_DATA}/common/ns.yaml")
filtered_ns_2 = create_namespace_with_name_from_yaml(kube_apis.v1, f"filtered-ns-2", f"{TEST_DATA}/common/ns.yaml")
filtered_secret_1 = create_secret_from_yaml(
kube_apis.v1, filtered_ns_1, f"{TEST_DATA}/filter-secrets/filtered-secret-1.yaml"
)
filtered_secret_2 = create_secret_from_yaml(
kube_apis.v1, filtered_ns_2, f"{TEST_DATA}/filter-secrets/filtered-secret-2.yaml"
)
nginx_ingress_secret = create_secret_from_yaml(
kube_apis.v1, "nginx-ingress", f"{TEST_DATA}/filter-secrets/nginx-ingress-secret.yaml"
)
wait_before_test(1)
def fin():
if request.config.getoption("--skip-fixture-teardown") == "no":
print("Clean up:")
if is_secret_present(kube_apis.v1, filtered_secret_1, filtered_ns_1):
delete_secret(kube_apis.v1, filtered_secret_1, filtered_ns_1)
if is_secret_present(kube_apis.v1, filtered_secret_2, filtered_ns_2):
delete_secret(kube_apis.v1, filtered_secret_2, filtered_ns_2)
if is_secret_present(kube_apis.v1, nginx_ingress_secret, "nginx-ingress"):
delete_secret(kube_apis.v1, nginx_ingress_secret, "nginx-ingress")
delete_namespace(kube_apis.v1, filtered_ns_1)
delete_namespace(kube_apis.v1, filtered_ns_2)
request.addfinalizer(fin)<|fim_middle|>setup_multiple_ns_and_multiple_secrets<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(name: Optional[pulumi.Input[str]] = None,
resource_group_name: Optional[pulumi.Input[str]] = None,
version: Optional[pulumi.Input[str]] = None,
workspace_name: Optional[pulumi.Input[str]] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> pulumi.Output[GetDataVersionResult]:
"""
Azure Resource Manager resource envelope.
:param str name: Container name.
:param str resource_group_name: The name of the resource group. The name is case insensitive.
:param str version: Version identifier.
:param str workspace_name: Name of Azure Machine Learning workspace.
"""
...<|fim_middle|>get_data_version_output<|file_separator|> |
<|fim_prefix|> <|fim_suffix|>( self ) :<|fim_middle|>test_copy<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(address: str) -> bytes32:
hrpgot, data = bech32_decode(address)
if data is None:
raise ValueError("Invalid Address")
decoded = convertbits(data, 5, 8, False)
decoded_bytes = bytes32(decoded)
return decoded_bytes<|fim_middle|>decode_puzzle_hash<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(en_vocab):
doc = Doc(en_vocab, words=["hello", "world"])
with make_tempdir() as d:
file_path = d / "doc"
doc.to_disk(file_path)
doc_d = Doc(en_vocab).from_disk(file_path)
assert doc.to_bytes() == doc_d.to_bytes()<|fim_middle|>test_serialize_doc_roundtrip_disk<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self):
with self.assertRaises(ValueError):
losses.regularization_penalty("l1_l2", 1e-4, [])<|fim_middle|>test_regulaization_missing_scale_value<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>():
"""Parse command line arguments using argparse.
"""
parser = argparse.ArgumentParser(description=DESCRIPTION)
parser.add_argument(
'-V', '--version',
action='version',
version='{0}: v{1} by {2}'.format('%(prog)s', __version__, __author__)
)
parser.add_argument(
'--always-ok',
help='Always returns OK.',
dest='ALWAYS_OK',
action='store_true',
default=False,
)
parser.add_argument(
'--defaults-file',
help='Specifies a cnf file to read parameters like user, host and password from '
'(instead of specifying them on the command line), '
'for example `/var/spool/icinga2/.my.cnf`. Default: %(default)s',
dest='DEFAULTS_FILE',
default=DEFAULT_DEFAULTS_FILE,
)
parser.add_argument(
'--defaults-group',
help='Group/section to read from in the cnf file. Default: %(default)s',
dest='DEFAULTS_GROUP',
default=DEFAULT_DEFAULTS_GROUP,
)
parser.add_argument(
'--timeout',
help='Network timeout in seconds. Default: %(default)s (seconds)',
dest='TIMEOUT',
type=int,
default=DEFAULT_TIMEOUT,
)
return parser.METHOD_NAME()<|fim_middle|>parse_args<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(
component: ComponentSpec,
cross_section: CrossSectionSpec = "strip",
port1: str = "o1",
port2: str = "o2",
straight_length: float | None = None,
**kwargs,
) -> ComponentSpec:
"""Returns double straight.
Args:
component: for cutback.
cross_section: specification (CrossSection, string or dict).
port1: name of first optical port.
port2: name of second optical port.
straight_length: length of straight.
kwargs: cross_section settings.
"""
xs = gf.get_cross_section(cross_section, **kwargs)
METHOD_NAME = gf.Component()
straight_component = straight(
length=straight_length or xs.radius * 2, cross_section=xs
)
straight_component2 = straight(
length=straight_length or xs.radius * 2, cross_section=xs
)
straight_r = METHOD_NAME << straight_component
straight_r2 = METHOD_NAME << straight_component2.mirror((1, 0))
straight_r2 = straight_r2.move(
origin=(0, 0),
destination=(0, -component.ports[port1].y + component.ports[port2].y),
)
METHOD_NAME.add_port("o1", port=straight_r.ports["o1"])
METHOD_NAME.add_port("o2", port=straight_r2.ports["o1"])
METHOD_NAME.add_port("o3", port=straight_r2.ports["o2"])
METHOD_NAME.add_port("o4", port=straight_r.ports["o2"])
return METHOD_NAME<|fim_middle|>straight_double<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self):
""" BaseDirectory with no existence check accepts any pathlib path.
"""
foo = SimpleBaseDirectory()
foo.path = pathlib.Path("!!!")
self.assertIsInstance(foo.path, str)<|fim_middle|>test_simple_accepts_any_pathlib<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>():
fmt = """
# comments are allowed
> # big endian (see documentation for struct)
# empty lines are allowed:
ashort: h
along: l
abyte: b # a byte
achar: c
astr: 5s
afloat: f; adouble: d # multiple "statements" are allowed
afixed: 16.16F
abool: ?
apad: x
"""
print("size:", calcsize(fmt))
class foo(object):
pass
i = foo()
i.ashort = 0x7FFF
i.along = 0x7FFFFFFF
i.abyte = 0x7F
i.achar = "a"
i.astr = "12345"
i.afloat = 0.5
i.adouble = 0.5
i.afixed = 1.5
i.abool = True
data = pack(fmt, i)
print("data:", repr(data))
print(unpack(fmt, data))
i2 = foo()
unpack(fmt, data, i2)
print(vars(i2))<|fim_middle|>test<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(tmp_path):
outfilename = tmp_path / "vu_tide_hourly_p0.dfs0"
ds = mikeio.read("tests/testdata/vu_tide_hourly.dfs1")
assert ds.n_elements > 1
ds_0 = ds.isel(0, axis="space")
assert ds_0.n_elements == 1
ds_0_0 = ds_0.isel(0)
assert ds_0_0.n_timesteps == 1
ds_0_0.to_dfs(outfilename)
dsnew = mikeio.read(outfilename)
assert dsnew.n_timesteps == 1<|fim_middle|>test_select_point_and_single_step_dfs1<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self):
self.window.show_all()
self.window.present()<|fim_middle|>show<|file_separator|> |
<|fim_prefix|>async def <|fim_suffix|>(
auth: AcaPyAuth = Depends(acapy_auth),<|fim_middle|>create_did<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>():
session = requests.Session()
make_session_public_only(session, 'demo_domain', src='testing')
return session<|fim_middle|>set_up_session<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self):
self.assertEqual(build_password("plain"), "plaintext:plain")<|fim_middle|>test_default_plaintext<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(
user_id: str
) -> List[learner_group_domain.LearnerGroup]:
"""Returns a list of learner groups of the given facilitator.
Args:
user_id: str. The id of the facilitator.
Returns:
list(LearnerGroup). A list of learner groups of the given facilitator.
"""
learner_grp_models = (
learner_group_models.LearnerGroupModel.get_by_facilitator_id(user_id))
if not learner_grp_models:
return []
return [
learner_group_services.get_learner_group_from_model(model)
for model in learner_grp_models
]<|fim_middle|>get_learner_groups_of_facilitator<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self, value: Optional[float]) -> None:
"""When not draining we pass thru to the socket,
since when draining we control the timeout.
"""
if value is not None:
self._recv_timeout_sec = value
if self._drain_thread is None:
socket.socket.METHOD_NAME(self, value)<|fim_middle|>settimeout<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(
self,
description: str,
params: Mapping[str, Any],
url: bool | None = False,
provider: ExternalProviders | None = None,
) -> str:
if self.user:
name = self.user.name or self.user.email
else:
name = "Sentry"
issue_name = self.group.qualified_short_id or "an issue"
if url and self.group.qualified_short_id:
group_url = self.group.get_absolute_url(params={"referrer": "activity_notification"})
issue_name = f"{self.format_url(text=self.group.qualified_short_id, url=group_url, provider=provider)}"
context = {"author": name, "an issue": issue_name}
context.update(params)
return description.format(**context)<|fim_middle|>description_as_text<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self, native_face):
self._face = native_face
self._loops = [RhinoBrepLoop(loop) for loop in native_face.Loops]
self._surface = RhinoNurbsSurface.from_rhino(self._face.UnderlyingSurface().ToNurbsSurface())<|fim_middle|>set_face<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self, user):
return self.get_for_user(user, teammembership__role=TeamMembership.ROLE.OWNER)<|fim_middle|>get_owner_teams<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>():
column = BigqueryColumn(
name="date",
field_path="date",
ordinal_position=1,
data_type="TIMESTAMP",
is_partition_column=True,
cluster_column_position=None,
comment=None,
is_nullable=False,
)
partition_info = PartitionInfo(type="DAY", field="date", column=column)
profiler = BigqueryProfiler(config=BigQueryV2Config(), report=BigQueryV2Report())
test_table = BigqueryTable(
name="test_table",
comment="test_comment",
rows_count=1,
size_in_bytes=1,
last_altered=datetime.now(timezone.utc),
created=datetime.now(timezone.utc),
partition_info=partition_info,
max_partition_id="20200101",
)
query = profiler.generate_partition_profiler_query(
project="test_project",
schema="test_dataset",
table=test_table,
)
expected_query = """<|fim_middle|>test_generate_day_partitioned_partition_profiler_query<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self, inputs, metric, functional_metric, ref_metric, ignore_index):
"""Test functional implementation of metric."""
preds, target = inputs
if ignore_index is not None:
target = inject_ignore_index(target, ignore_index)
self.run_functional_metric_test(
preds=preds,
target=target,
metric_functional=functional_metric,
reference_metric=partial(_sklearn_ranking, fn=ref_metric, ignore_index=ignore_index),
metric_args={
"num_labels": NUM_CLASSES,
"ignore_index": ignore_index,
},
)<|fim_middle|>test_multilabel_ranking_functional<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self, positions: TensorType["bs":..., 3]) -> TensorType["bs":..., 1]:
"""Returns only the density. Used primarily with the density grid.
Args:
positions: the origin of the samples/frustums
"""
# Need to figure out a better way to descibe positions with a ray.
ray_samples = RaySamples(
frustums=Frustums(
origins=positions,
directions=torch.ones_like(positions),
starts=torch.zeros_like(positions[..., :1]),
ends=torch.zeros_like(positions[..., :1]),
pixel_area=torch.ones_like(positions[..., :1]),
)
)
density, _ = self.get_density(ray_samples)
return density<|fim_middle|>density_fn<|file_separator|> |
<|fim_prefix|> <|fim_suffix|>(self, old_name, new_name, merge=False):<|fim_middle|>after_rename<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>():
examinee = create_upgrade_pr(
from_ref=cm.ComponentReference(
name='c1',
componentName='c1',
version='1.2.3',
),
to_ref=cm.ComponentReference(
name='c1',
componentName='c1',
version='2.0.0',
),
)
cref = cm.ComponentReference(
name='c1',
componentName='c1',
version='6.0.0',
)
reference_component = cm.Component(
name='c1',
version='6.6.6',
repositoryContexts=(),
provider=None,
sources=(),
resources=(),
componentReferences=()
)
# test with reference component not declaring this dependency
assert not examinee.is_obsolete(reference_component=reference_component)
# add differently-named dependency with greater version
reference_component.componentReferences = (
dataclasses.replace(cref, componentName='other-name'),
)
assert not examinee.is_obsolete(reference_component=reference_component)
# add same-named web dependency with lesser version
reference_component.componentReferences = (
dataclasses.replace(cref, version='0.0.1'),
)
assert not examinee.is_obsolete(reference_component=reference_component)
# add same-named resource of greater version but different type
# todo: we should actually also test dependencies towards resources of two different types
reference_component.resources = (
cm.Resource(
name='c1',
version='6.0.0',
type=cm.ArtefactType.BLOB,
access=None,
),
)
assert not examinee.is_obsolete(reference_component=reference_component)
# finally, add greater dependency of matching type and name
reference_component.componentReferences = (
dataclasses.replace(cref, version='9.9.9'),
)
assert examinee.is_obsolete(reference_component=reference_component)<|fim_middle|>test_is_obsolete<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(testsystem_names, niterations=5):
"""
Run sampler stack on named test systems.
Parameters
----------
testsystem_names : list of str
Names of test systems to run
niterations : int, optional, default=5
Number of iterations to run
"""
for testsystem_name in testsystem_names:
import perses.tests.testsystems
testsystem_class = getattr(perses.tests.testsystems, testsystem_name)
# Instantiate test system.
testsystem = testsystem_class()
# Test MCMCSampler samplers.
for environment in testsystem.environments:
mcmc_sampler = testsystem.mcmc_samplers[environment]
f = partial(mcmc_sampler.run, niterations)
f.description = "Testing MCMC sampler with %s '%s'" % (testsystem_name, environment)
yield f
# Test ExpandedEnsembleSampler samplers.
for environment in testsystem.environments:
exen_sampler = testsystem.exen_samplers[environment]
f = partial(exen_sampler.run, niterations)
f.description = "Testing expanded ensemble sampler with %s '%s'" % (testsystem_name, environment)
yield f
# Test SAMSSampler samplers.
for environment in testsystem.environments:
sams_sampler = testsystem.sams_samplers[environment]
f = partial(sams_sampler.run, niterations)
f.description = "Testing SAMS sampler with %s '%s'" % (testsystem_name, environment)
yield f
# Test MultiTargetDesign sampler, if present.
if hasattr(testsystem, 'designer') and (testsystem.designer is not None):
f = partial(testsystem.designer.run, niterations)
f.description = "Testing MultiTargetDesign sampler with %s transfer free energy from vacuum -> %s" % (testsystem_name, environment)
yield f<|fim_middle|>run_samplers<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self) -> Response:
"""
Get a list with all of the tabels in TDEngine
"""
q = 'SHOW TABLES;'
return self.native_query(q)<|fim_middle|>get_tables<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(
self,
configs: List[Config[ModelConfig]],
performances: List[Performance],
) -> None:
super().METHOD_NAME(configs, performances)
# We need to sort by dataset to have the same ordering for each model config
ordering = np.argsort([c.dataset.name() for c in configs])
performance_df = Performance.to_dataframe(performances)
# Extract all metrics
metric_map = defaultdict(list)
for i in ordering:
metric_map[configs[i].model].append(
performance_df.iloc[i][self.objectives].to_numpy(), # type: ignore
)
# Build the properties
self.metrics = np.stack(list(metric_map.values()), axis=1)
self.model_indices = {model: i for i, model in enumerate(metric_map)}
# If we are in the multi-objective setting, we have to apply dataset-level quantile
# normalization of each objective. Otherwise, we perform standardization.
if not self.enforce_single_objective and len(self.objectives) > 1:
transformer = QuantileTransformer(
n_quantiles=min(1000, self.metrics.shape[0])
)
self.metrics = np.stack(
[
transformer.fit_transform(dataset_metrics)
for dataset_metrics in self.metrics
]
)
else:
transformer = StandardScaler()
self.metrics = np.stack(
[
transformer.fit_transform(dataset_metrics)
for dataset_metrics in self.metrics
]
)<|fim_middle|>fit<|file_separator|> |
<|fim_prefix|>async def <|fim_suffix|>(mock_iam_client):
group = await get_group(EXAMPLE_GROUPNAME, mock_iam_client)
assert group["GroupName"] == EXAMPLE_GROUPNAME<|fim_middle|>test_get_group<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self, Paramsmulticast):
# controle parameters multicast
return self.api.SetMulticastMultiSessionParameters(Paramsmulticast)<|fim_middle|>xmlrpc_set_multicast_multi_session_parameters<|file_separator|> |
<|fim_prefix|>f <|fim_suffix|>(self):<|fim_middle|>test_process_file<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(m):
opt = pyo.SolverFactory('gurobi')
res = opt.solve(m)
assert_optimal_termination(res)<|fim_middle|>solve_warehouse_location<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self) -> str:
"""
Resource ID.
"""
return pulumi.get(self, "id")<|fim_middle|>id<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self):
return self.event.METHOD_NAME + f"/session/{self.id}"<|fim_middle|>site_link<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(colorer, s, i):
return colorer.match_seq_regexp(s, i, kind="label", regexp="`[A-z0-9]+[^`]+`_{1,2}")<|fim_middle|>rest_rule17<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self):
for pos in self:
seq = pos.l10n_es_simplified_invoice_sequence_id
pos.l10n_es_simplified_invoice_number = (
seq._get_current_sequence().number_next_actual
)
pos.l10n_es_simplified_invoice_prefix = seq._get_prefix_suffix()[0]
pos.l10n_es_simplified_invoice_padding = seq.padding<|fim_middle|>compute_simplified_invoice_sequence<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self):
x = tensor.Tensor(np.array([1, 2, 3]))
self.assertEqual(x.rank, 1)<|fim_middle|>test_rank_is_one_for_vector<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>():
assert not np.isnan(atmosphere.get_relative_airmass(10))<|fim_middle|>test_airmass_scalar<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>():
"""Return the default filters (all available filters)."""
return dict((name, set(PlayerIter(name))) for name in PlayerIter.filters)<|fim_middle|>get_default_filters<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self, token_ids: Sequence[bytes]) -> Sequence[KlerosToken]:
queries = []
for token_id in token_ids:
queries.append(self.kleros_contract.functions.getTokenInfo(token_id))
# name string, ticker string, addr address, symbolMultihash string, status uint8, numberOfRequests uint256
token_infos = self.ethereum_client.batch_call(queries)
return [KlerosToken(*token_info) for token_info in token_infos]<|fim_middle|>get_token_info<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(
self, aligned_segment_starting_times: List[List[float]], stub_test: bool = False
):
"""
Align the individual starting time for each video in this interface relative to the common session start time.
Must be in units seconds relative to the common 'session_start_time'.
Parameters
----------
aligned_segment_starting_times : list of list of floats
The relative starting times of each video.
Outer list is over file paths (readers).
Inner list is over segments of each recording.
"""
number_of_files_from_starting_times = len(aligned_segment_starting_times)
assert number_of_files_from_starting_times == len(self.readers_list), (
f"The length of the outer list of 'starting_times' ({number_of_files_from_starting_times}) "
"does not match the number of files ({len(self.readers_list)})!"
)
for file_index, (reader, aligned_segment_starting_times_by_file) in enumerate(
zip(self.readers_list, aligned_segment_starting_times)
):
number_of_segments = reader.header["nb_segment"][0]
assert number_of_segments == len(
aligned_segment_starting_times_by_file
), f"The length of starting times index {file_index} does not match the number of segments of that reader!"
reader._t_starts = aligned_segment_starting_times_by_file<|fim_middle|>set_aligned_segment_starting_times<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self, msg):
pass<|fim_middle|>on_inv<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(self, output, identifier):
return self._wrapped.METHOD_NAME(output._lines, identifier)<|fim_middle|>get_value_from_output<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>():
x = np.zeros((5, 5), dtype=int)
array_2d_view_assign(x[::, ::], 9)
array_2d_view_assign(x[:2:2, :2:3], 10)
array_2d_view_assign(x[3::2, 3::3], 11)
array_2d_view_assign(x[1:2, 2:3], 12)
array_1d_view_assign(x[0, :], 1)
array_1d_view_assign(x[1, ::2], 2)
array_1d_view_assign(x[2, 1:4:2], 3)
array_1d_view_assign(x[3, 3:4], 4)
array_1d_view_assign(x[:, 0], 5)
array_1d_view_assign(x[::2, 1], 6)
array_1d_view_assign(x[1:4:2, 2], 7)
array_1d_view_assign(x[3:4, 3], 8)
for i in range(np.shape(x)[0]):
for j in range(np.shape(x)[1]):
print(x[i][j])<|fim_middle|>array_2d_view<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(iterable):
"""Test whether visitors properly set the type constraint of the a For node representing for/else statement
iterating over a heterogeneous list.
"""
assume(type(iterable[0]) != type(iterable[1]))
val_types = [type(val) for val in iterable]
if int in val_types:
assume(bool not in val_types)
if bool in val_types:
assume(int not in val_types)
program = f"for elt in {iterable}:\n" f" x = elt\n"
module, TypeInferrer = cs._parse_text(program)
for_node = list(module.nodes_of_class(nodes.For))[0]
local_type_var = module.type_environment.lookup_in_env("x")
inferred_type = TypeInferrer.type_constraints.resolve(local_type_var).getValue()
assert inferred_type == Any<|fim_middle|>test_for_heterogeneous_list<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(plistpath, content):
"""A test utility to create a plist file with known content.
Ensures that the directory for the file exists, and writes an XML plist with
specific content.
:param plistpath: The path for the plist file to create.
:param content: A dictionary of content that plistlib can use to create the plist
file.
:returns: The path to the file that was created.
"""
plistpath.parent.mkdir(parents=True, exist_ok=True)
with plistpath.open("wb") as f:
plistlib.dump(content, f)
return plistpath<|fim_middle|>create_plist_file<|file_separator|> |
<|fim_prefix|>def <|fim_suffix|>(instance, check, aggregator):
del instance['custom_queries']
with mock.patch(
'datadog_checks.ibm_was.IbmWasCheck.make_request', return_value=mock_data('perfservlet-multiple-nodes.xml')
):
check = check(instance)
check.check(instance)
node = 'node:cmhqlvij2a04'
for metric_name, metrics in aggregator._metrics.items():
for metric in metrics:
if 'server:IJ2Server02' in metric.tags:
assert node in metric.tags, "Expected '{}' tag in '{}' tags, found {}".format(
node, metric_name, metric.tags
)<|fim_middle|>test_right_server_tag<|file_separator|> |
End of preview. Expand
in Dataset Viewer.
README.md exists but content is empty.
Use the Edit dataset card button to edit it.
- Downloads last month
- 38