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PredixDev/predixpy | predix/security/uaa.py | UserAccountAuthentication.get_user_by_username | def get_user_by_username(self, username):
"""
Returns details for user of the given username.
If there is more than one match will only return the first. Use
get_users() for full result set.
"""
results = self.get_users(filter='username eq "%s"' % (username))
if... | python | def get_user_by_username(self, username):
"""
Returns details for user of the given username.
If there is more than one match will only return the first. Use
get_users() for full result set.
"""
results = self.get_users(filter='username eq "%s"' % (username))
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PredixDev/predixpy | predix/security/uaa.py | UserAccountAuthentication.get_user_by_email | def get_user_by_email(self, email):
"""
Returns details for user with the given email address.
If there is more than one match will only return the first. Use
get_users() for full result set.
"""
results = self.get_users(filter='email eq "%s"' % (email))
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"""
Returns details for user with the given email address.
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PredixDev/predixpy | predix/security/uaa.py | UserAccountAuthentication.get_user | def get_user(self, id):
"""
Returns details about the user for the given id.
Use get_user_by_email() or get_user_by_username() for help
identifiying the id.
"""
self.assert_has_permission('scim.read')
return self._get(self.uri + '/Users/%s' % (id)) | python | def get_user(self, id):
"""
Returns details about the user for the given id.
Use get_user_by_email() or get_user_by_username() for help
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PredixDev/predixpy | predix/admin/timeseries.py | TimeSeries.create | def create(self):
"""
Create an instance of the Time Series Service with the typical
starting settings.
"""
self.service.create()
predix.config.set_env_value(self.use_class, 'ingest_uri',
self.get_ingest_uri())
predix.config.set_env_value(self.use... | python | def create(self):
"""
Create an instance of the Time Series Service with the typical
starting settings.
"""
self.service.create()
predix.config.set_env_value(self.use_class, 'ingest_uri',
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PredixDev/predixpy | predix/admin/timeseries.py | TimeSeries.grant_client | def grant_client(self, client_id, read=True, write=True):
"""
Grant the given client id all the scopes and authorities
needed to work with the timeseries service.
"""
scopes = ['openid']
authorities = ['uaa.resource']
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for zone in self.servic... | python | def grant_client(self, client_id, read=True, write=True):
"""
Grant the given client id all the scopes and authorities
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"""
scopes = ['openid']
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PredixDev/predixpy | predix/admin/timeseries.py | TimeSeries.get_query_uri | def get_query_uri(self):
"""
Return the uri used for queries on time series data.
"""
# Query URI has extra path we don't want so strip it off here
query_uri = self.service.settings.data['query']['uri']
query_uri = urlparse(query_uri)
return query_uri.scheme + ':/... | python | def get_query_uri(self):
"""
Return the uri used for queries on time series data.
"""
# Query URI has extra path we don't want so strip it off here
query_uri = self.service.settings.data['query']['uri']
query_uri = urlparse(query_uri)
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PredixDev/predixpy | predix/admin/timeseries.py | TimeSeries.add_to_manifest | def add_to_manifest(self, manifest):
"""
Add useful details to the manifest about this service
so that it can be used in an application.
:param manifest: An predix.admin.app.Manifest object
instance that manages reading/writing manifest config
for a cloud foundry... | python | def add_to_manifest(self, manifest):
"""
Add useful details to the manifest about this service
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landscapeio/requirements-detector | requirements_detector/detect.py | find_requirements | def find_requirements(path):
"""
This method tries to determine the requirements of a particular project
by inspecting the possible places that they could be defined.
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1) to parse setup.py in the root for an install_requires value
2) to read a requirements.txt file or... | python | def find_requirements(path):
"""
This method tries to determine the requirements of a particular project
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1) to parse setup.py in the root for an install_requires value
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PredixDev/predixpy | predix/admin/cf/apps.py | App.get_app_guid | def get_app_guid(self, app_name):
"""
Returns the GUID for the app instance with
the given name.
"""
summary = self.space.get_space_summary()
for app in summary['apps']:
if app['name'] == app_name:
return app['guid'] | python | def get_app_guid(self, app_name):
"""
Returns the GUID for the app instance with
the given name.
"""
summary = self.space.get_space_summary()
for app in summary['apps']:
if app['name'] == app_name:
return app['guid'] | [
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PredixDev/predixpy | predix/admin/cf/apps.py | App.delete_app | def delete_app(self, app_name):
"""
Delete the given app.
Will fail intentionally if there are any service
bindings. You must delete those first.
"""
if app_name not in self.space.get_apps():
logging.warning("App not found so... succeeded?")
retu... | python | def delete_app(self, app_name):
"""
Delete the given app.
Will fail intentionally if there are any service
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"""
if app_name not in self.space.get_apps():
logging.warning("App not found so... succeeded?")
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PredixDev/predixpy | predix/admin/config.py | ServiceConfig._get_service_config | def _get_service_config(self):
"""
Reads in config file of UAA credential information
or generates one as a side-effect if not yet
initialized.
"""
# Should work for windows, osx, and linux environments
if not os.path.exists(self.config_path):
try:
... | python | def _get_service_config(self):
"""
Reads in config file of UAA credential information
or generates one as a side-effect if not yet
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"""
# Should work for windows, osx, and linux environments
if not os.path.exists(self.config_path):
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PredixDev/predixpy | predix/admin/config.py | ServiceConfig._write_service_config | def _write_service_config(self):
"""
Will write the config out to disk.
"""
with open(self.config_path, 'w') as output:
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Will write the config out to disk.
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PredixDev/predixpy | predix/admin/blobstore.py | BlobStore.create | def create(self, **kwargs):
"""
Create an instance of the Blob Store Service with the typical
starting settings.
"""
self.service.create(**kwargs)
predix.config.set_env_value(self.use_class, 'url',
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predix.config.... | python | def create(self, **kwargs):
"""
Create an instance of the Blob Store Service with the typical
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PredixDev/predixpy | predix/admin/blobstore.py | BlobStore.add_to_manifest | def add_to_manifest(self, manifest):
"""
Add useful details to the manifest about this service
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PredixDev/predixpy | predix/data/eventhub/subscriber.py | Subscriber.subscribe | def subscribe(self):
"""
return a generator for all subscribe messages
:return: None
"""
while self.run_subscribe_generator:
if len(self._rx_messages) != 0:
yield self._rx_messages.pop(0)
return | python | def subscribe(self):
"""
return a generator for all subscribe messages
:return: None
"""
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PredixDev/predixpy | predix/data/eventhub/subscriber.py | Subscriber.send_acks | def send_acks(self, message):
"""
send acks to the service
:param message: EventHub_pb2.Message
:return: None
"""
if isinstance(message, EventHub_pb2.Message):
ack = EventHub_pb2.Ack(partition=message.partition, offset=message.offset)
self.grpc_man... | python | def send_acks(self, message):
"""
send acks to the service
:param message: EventHub_pb2.Message
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PredixDev/predixpy | predix/data/eventhub/subscriber.py | Subscriber._generate_subscribe_headers | def _generate_subscribe_headers(self):
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generate the subscribe stub headers based on the supplied config
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PredixDev/predixpy | predix/ie/parking.py | ParkingPlanning._get_assets | def _get_assets(self, bbox, size=None, page=None, asset_type=None,
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PredixDev/predixpy | predix/ie/parking.py | ParkingPlanning.get_assets | def get_assets(self, bbox, **kwargs):
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PredixDev/predixpy | predix/ie/parking.py | ParkingPlanning._get_asset | def _get_asset(self, asset_uid):
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uri = self.uri + '/v2/assets/' + asset_uid
headers = self._get_headers()
return self.service._get(uri, headers=headers) | python | def _get_asset(self, asset_uid):
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Returns raw response for an given asset by its unique id.
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djgagne/hagelslag | hagelslag/processing/Hysteresis.py | Hysteresis.label | def label(self, input_grid):
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input_grid: 2D array of values.
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Label input grid with hysteresis method.
Args:
input_grid: 2D array of values.
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Labeled output grid.
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djgagne/hagelslag | hagelslag/processing/Hysteresis.py | Hysteresis.size_filter | def size_filter(labeled_grid, min_size):
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labeled_grid: 2D output from label method.
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labeled_grid: 2D output from label method.
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djgagne/hagelslag | hagelslag/evaluation/MetricPlotter.py | roc_curve | def roc_curve(roc_objs, obj_labels, colors, markers, filename, figsize=(8, 8),
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ylabel="Probability of Detection",
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ylabel="Probability of Detection",
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djgagne/hagelslag | hagelslag/evaluation/MetricPlotter.py | performance_diagram | def performance_diagram(roc_objs, obj_labels, colors, markers, filename, figsize=(8, 8),
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ylabel="Probability of Detection", ticks=np.arange(0, 1.1, 0.1),
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djgagne/hagelslag | hagelslag/evaluation/MetricPlotter.py | reliability_diagram | def reliability_diagram(rel_objs, obj_labels, colors, markers, filename, figsize=(8, 8), xlabel="Forecast Probability",
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djgagne/hagelslag | hagelslag/evaluation/MetricPlotter.py | attributes_diagram | def attributes_diagram(rel_objs, obj_labels, colors, markers, filename, figsize=(8, 8), xlabel="Forecast Probability",
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nion-software/nionswift | nion/swift/ScriptsDialog.py | RunScriptDialog.get_string | def get_string(self, prompt, default_str=None) -> str:
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nion-software/nionswift | nion/swift/ScriptsDialog.py | RunScriptDialog.__accept_reject | def __accept_reject(self, prompt, accepted_text, rejected_text, display_rejected):
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mgraffg/EvoDAG | EvoDAG/node.py | Variable.compute_weight | def compute_weight(self, r, ytr=None, mask=None):
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ytr = self._ytr if ytr is None else ytr
mask = self._mask if mask is None else mask
return compute_weight(r, ytr, mask) | python | def compute_weight(self, r, ytr=None, mask=None):
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mgraffg/EvoDAG | EvoDAG/node.py | Variable.isfinite | def isfinite(self):
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ajk8/hatchery | hatchery/helpers.py | value_of_named_argument_in_function | def value_of_named_argument_in_function(argument_name, function_name, search_str,
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ajk8/hatchery | hatchery/helpers.py | regex_in_file | def regex_in_file(regex, filepath, return_match=False):
""" Search for a regex in a file
If return_match is True, return the found object instead of a boolean
"""
file_content = get_file_content(filepath)
re_method = funcy.re_find if return_match else funcy.re_test
return re_method(regex, file_... | python | def regex_in_file(regex, filepath, return_match=False):
""" Search for a regex in a file
If return_match is True, return the found object instead of a boolean
"""
file_content = get_file_content(filepath)
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ajk8/hatchery | hatchery/helpers.py | regex_in_package_file | def regex_in_package_file(regex, filename, package_name, return_match=False):
""" Search for a regex in a file contained within the package directory
If return_match is True, return the found object instead of a boolean
"""
filepath = package_file_path(filename, package_name)
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""" Search for a regex in a file contained within the package directory
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"""
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ajk8/hatchery | hatchery/helpers.py | string_is_url | def string_is_url(test_str):
""" Test to see if a string is a URL or not, defined in this case as a string for which
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>>> string_is_url('somestring')
False
>>> string_is_url('https://some.domain.org/path')
True
"""
parsed = urlparse.urlparse(test_str)
... | python | def string_is_url(test_str):
""" Test to see if a string is a URL or not, defined in this case as a string for which
urlparse returns a scheme component
>>> string_is_url('somestring')
False
>>> string_is_url('https://some.domain.org/path')
True
"""
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nion-software/nionswift | nion/swift/model/DocumentModel.py | TransactionManager.item_transaction | def item_transaction(self, item) -> Transaction:
"""Begin transaction state for item.
A transaction state is exists to prevent writing out to disk, mainly for performance reasons.
All changes to the object are delayed until the transaction state exits.
This method is thread safe.
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"""Begin transaction state for item.
A transaction state is exists to prevent writing out to disk, mainly for performance reasons.
All changes to the object are delayed until the transaction state exits.
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nion-software/nionswift | nion/swift/model/DocumentModel.py | DocumentModel.insert_data_item | def insert_data_item(self, before_index, data_item, auto_display: bool = True) -> None:
"""Insert a new data item into document model.
This method is NOT threadsafe.
"""
assert data_item is not None
assert data_item not in self.data_items
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"""Insert a new data item into document model.
This method is NOT threadsafe.
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nion-software/nionswift | nion/swift/model/DocumentModel.py | DocumentModel.remove_data_item | def remove_data_item(self, data_item: DataItem.DataItem, *, safe: bool=False) -> typing.Optional[typing.Sequence]:
"""Remove data item from document model.
This method is NOT threadsafe.
"""
# remove data item from any computations
return self.__cascade_delete(data_item, safe=sa... | python | def remove_data_item(self, data_item: DataItem.DataItem, *, safe: bool=False) -> typing.Optional[typing.Sequence]:
"""Remove data item from document model.
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"""
# remove data item from any computations
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nion-software/nionswift | nion/swift/model/DocumentModel.py | DocumentModel.__cascade_delete_inner | def __cascade_delete_inner(self, master_item, safe: bool=False) -> typing.Optional[typing.Sequence]:
"""Cascade delete an item.
Returns an undelete log that can be used to undo the cascade deletion.
Builds a cascade of items to be deleted and dependencies to be removed when the passed item is ... | python | def __cascade_delete_inner(self, master_item, safe: bool=False) -> typing.Optional[typing.Sequence]:
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nion-software/nionswift | nion/swift/model/DocumentModel.py | DocumentModel.get_dependent_items | def get_dependent_items(self, item) -> typing.List:
"""Return the list of data items containing data that directly depends on data in this item."""
with self.__dependency_tree_lock:
return copy.copy(self.__dependency_tree_source_to_target_map.get(weakref.ref(item), list())) | python | def get_dependent_items(self, item) -> typing.List:
"""Return the list of data items containing data that directly depends on data in this item."""
with self.__dependency_tree_lock:
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nion-software/nionswift | nion/swift/model/DocumentModel.py | DocumentModel.__get_deep_dependent_item_set | def __get_deep_dependent_item_set(self, item, item_set) -> None:
"""Return the list of data items containing data that directly depends on data in this item."""
if not item in item_set:
item_set.add(item)
with self.__dependency_tree_lock:
for dependent in self.get... | python | def __get_deep_dependent_item_set(self, item, item_set) -> None:
"""Return the list of data items containing data that directly depends on data in this item."""
if not item in item_set:
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nion-software/nionswift | nion/swift/model/DocumentModel.py | DocumentModel.get_dependent_data_items | def get_dependent_data_items(self, data_item: DataItem.DataItem) -> typing.List[DataItem.DataItem]:
"""Return the list of data items containing data that directly depends on data in this item."""
with self.__dependency_tree_lock:
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"""Return the list of data items containing data that directly depends on data in this item."""
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nion-software/nionswift | nion/swift/model/DocumentModel.py | DocumentModel.transaction_context | def transaction_context(self):
"""Return a context object for a document-wide transaction."""
class DocumentModelTransaction:
def __init__(self, document_model):
self.__document_model = document_model
def __enter__(self):
self.__document_model.per... | python | def transaction_context(self):
"""Return a context object for a document-wide transaction."""
class DocumentModelTransaction:
def __init__(self, document_model):
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nion-software/nionswift | nion/swift/model/DocumentModel.py | DocumentModel.data_item_live | def data_item_live(self, data_item):
""" Return a context manager to put the data item in a 'live state'. """
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def __init__(self, manager, object):
self.__manager = manager
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""" Return a context manager to put the data item in a 'live state'. """
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nion-software/nionswift | nion/swift/model/DocumentModel.py | DocumentModel.begin_data_item_live | def begin_data_item_live(self, data_item):
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"""
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nion-software/nionswift | nion/swift/model/DocumentModel.py | DocumentModel.end_data_item_live | def end_data_item_live(self, data_item):
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"""
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nion-software/nionswift | nion/swift/model/DocumentModel.py | DocumentModel.__construct_data_item_reference | def __construct_data_item_reference(self, hardware_source: HardwareSource.HardwareSource, data_channel: HardwareSource.DataChannel):
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nion-software/nionswift | nion/swift/model/DocumentModel.py | DocumentModel.__make_computation | def __make_computation(self, processing_id: str, inputs: typing.List[typing.Tuple[DisplayItem.DisplayItem, typing.Optional[Graphics.Graphic]]], region_list_map: typing.Mapping[str, typing.List[Graphics.Graphic]]=None, parameters: typing.Mapping[str, typing.Any]=None) -> DataItem.DataItem:
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nion-software/nionswift | nion/swift/model/ColorMaps.py | interpolate_colors | def interpolate_colors(array: numpy.ndarray, x: int) -> numpy.ndarray:
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:param x: number of colors
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:return: interpolated color map
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softvar/simplegist | simplegist/do.py | Do.star | def star(self, **args):
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self.gist_name = args['name']
self.gist_id = self.getMyID(self.gist_name)
elif 'id' in args:
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'''
star any gist by providing gistID or gistname(for authenticated user)
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self.gist_name = args['name']
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softvar/simplegist | simplegist/do.py | Do.checkifstar | def checkifstar(self, **args):
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base4sistemas/satcfe | satcfe/resposta/extrairlogs.py | RespostaExtrairLogs.salvar | def salvar(self, destino=None, prefix='tmp', suffix='-sat.log'):
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:param str destino: (Opcional) Caminho completo para o arquivo onde os
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"""Salva o arquivo de log decodificado.
:param str destino: (Opcional) Caminho completo para o arquivo onde os
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base4sistemas/satcfe | satcfe/resposta/extrairlogs.py | RespostaExtrairLogs.analisar | def analisar(retorno):
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informado.
:param unicode retorno: Retorno da função ``ExtrairLogs``.
"""
resposta = analisar_retorno(forcar_unicode(retorno),
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classe_res... | python | def analisar(retorno):
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djgagne/hagelslag | hagelslag/data/ModelGrid.py | ModelGrid.load_data_old | def load_data_old(self):
"""
Loads time series of 2D data grids from each opened file. The code
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from multiple files. Missing files are supported.
"""
units = ""
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djgagne/hagelslag | hagelslag/data/ModelGrid.py | ModelGrid.load_data | def load_data(self):
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Load data from netCDF file objects or list of netCDF file objects. Handles special variable name formats.
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djgagne/hagelslag | hagelslag/data/ModelGrid.py | ModelGrid.format_var_name | def format_var_name(variable, var_list):
"""
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variable (str): Variable being loaded
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variable (str): Variable being loaded
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djgagne/hagelslag | hagelslag/processing/TrackModeler.py | TrackModeler.load_data | def load_data(self, mode="train", format="csv"):
"""
Load data from flat data files containing total track information and information about each timestep.
The two sets are combined using merge operations on the Track IDs. Additional member information is gathered
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djgagne/hagelslag | hagelslag/processing/TrackModeler.py | TrackModeler.calc_copulas | def calc_copulas(self,
output_file,
model_names=("start-time", "translation-x", "translation-y"),
label_columns=("Start_Time_Error", "Translation_Error_X", "Translation_Error_Y")):
"""
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output_file,
model_names=("start-time", "translation-x", "translation-y"),
label_columns=("Start_Time_Error", "Translation_Error_X", "Translation_Error_Y")):
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djgagne/hagelslag | hagelslag/processing/TrackModeler.py | TrackModeler.fit_condition_models | def fit_condition_models(self, model_names,
model_objs,
input_columns,
output_column="Matched",
output_threshold=0.0):
"""
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model_objs,
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djgagne/hagelslag | hagelslag/processing/TrackModeler.py | TrackModeler.fit_condition_threshold_models | def fit_condition_threshold_models(self, model_names, model_objs, input_columns, output_column="Matched",
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input_columns,
metadata_cols,
data_mode="forecast",
):
"""
Apply condition modelsto forecast data.
Args:
... | python | def predict_condition_models(self, model_names,
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Apply condition modelsto forecast data.
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djgagne/hagelslag | hagelslag/processing/TrackModeler.py | TrackModeler.fit_size_distribution_models | def fit_size_distribution_models(self, model_names, model_objs, input_columns,
output_columns=None, calibrate=False):
"""
Fits multitask machine learning models to predict the parameters of a size distribution
Args:
model_names: List of machine le... | python | def fit_size_distribution_models(self, model_names, model_objs, input_columns,
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Fits multitask machine learning models to predict the parameters of a size distribution
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djgagne/hagelslag | hagelslag/processing/TrackModeler.py | TrackModeler.fit_size_distribution_component_models | def fit_size_distribution_component_models(self, model_names, model_objs, input_columns, output_columns):
"""
This calculates 2 principal components for the hail size distribution between the shape and scale parameters.
Separate machine learning models are fit to predict each component.
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djgagne/hagelslag | hagelslag/processing/TrackModeler.py | TrackModeler.predict_size_distribution_models | def predict_size_distribution_models(self, model_names, input_columns, metadata_cols,
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"""
Make predictions using fitted size distribution models.
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model_names: Name of the models for pre... | python | def predict_size_distribution_models(self, model_names, input_columns, metadata_cols,
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Make predictions using fitted size distribution models.
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djgagne/hagelslag | hagelslag/processing/TrackModeler.py | TrackModeler.fit_size_models | def fit_size_models(self, model_names,
model_objs,
input_columns,
output_column="Hail_Size",
output_start=5,
output_step=5,
output_stop=100):
"""
Fit size model... | python | def fit_size_models(self, model_names,
model_objs,
input_columns,
output_column="Hail_Size",
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output_step=5,
output_stop=100):
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input_columns,
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Apply size models to forecast data.
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djgagne/hagelslag | hagelslag/processing/TrackModeler.py | TrackModeler.fit_track_models | def fit_track_models(self,
model_names,
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output_ranges,
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djgagne/hagelslag | hagelslag/processing/TrackModeler.py | TrackModeler.save_models | def save_models(self, model_path):
"""
Save machine learning models to pickle files.
"""
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"""
Save machine learning models to pickle files.
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for group, condition_model_set in self.condition_models.items():
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djgagne/hagelslag | hagelslag/processing/TrackModeler.py | TrackModeler.load_models | def load_models(self, model_path):
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Load models from pickle files.
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djgagne/hagelslag | hagelslag/processing/TrackModeler.py | TrackModeler.output_forecasts_csv | def output_forecasts_csv(self, forecasts, mode, csv_path, run_date_format="%Y%m%d-%H%M"):
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Output hail forecast values to csv files by run date and ensemble member.
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base4sistemas/satcfe | satcfe/base.py | BibliotecaSAT._carregar | def _carregar(self):
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base4sistemas/satcfe | satcfe/base.py | FuncoesSAT.ativar_sat | def ativar_sat(self, tipo_certificado, cnpj, codigo_uf):
"""Função ``AtivarSAT`` conforme ER SAT, item 6.1.1.
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"""Função ``AtivarSAT`` conforme ER SAT, item 6.1.1.
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"... | Função ``AtivarSAT`` conforme ER SAT, item 6.1.1.
Ativação do equipamento SAT. Dependendo do tipo do certificado, o
procedimento de ativação é complementado enviando-se o certificado
emitido pela ICP-Brasil (:meth:`comunicar_certificado_icpbrasil`).
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base4sistemas/satcfe | satcfe/base.py | FuncoesSAT.comunicar_certificado_icpbrasil | def comunicar_certificado_icpbrasil(self, certificado):
"""Função ``ComunicarCertificadoICPBRASIL`` conforme ER SAT, item 6.1.2.
Envio do certificado criado pela ICP-Brasil.
:param str certificado: Conteúdo do certificado digital criado pela
autoridade certificadora ICP-Brasil.
... | python | def comunicar_certificado_icpbrasil(self, certificado):
"""Função ``ComunicarCertificadoICPBRASIL`` conforme ER SAT, item 6.1.2.
Envio do certificado criado pela ICP-Brasil.
:param str certificado: Conteúdo do certificado digital criado pela
autoridade certificadora ICP-Brasil.
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base4sistemas/satcfe | satcfe/base.py | FuncoesSAT.enviar_dados_venda | def enviar_dados_venda(self, dados_venda):
"""Função ``EnviarDadosVenda`` conforme ER SAT, item 6.1.3. Envia o
CF-e de venda para o equipamento SAT, que o enviará para autorização
pela SEFAZ.
:param dados_venda: Uma instância de :class:`~satcfe.entidades.CFeVenda`
ou uma str... | python | def enviar_dados_venda(self, dados_venda):
"""Função ``EnviarDadosVenda`` conforme ER SAT, item 6.1.3. Envia o
CF-e de venda para o equipamento SAT, que o enviará para autorização
pela SEFAZ.
:param dados_venda: Uma instância de :class:`~satcfe.entidades.CFeVenda`
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base4sistemas/satcfe | satcfe/base.py | FuncoesSAT.cancelar_ultima_venda | def cancelar_ultima_venda(self, chave_cfe, dados_cancelamento):
"""Função ``CancelarUltimaVenda`` conforme ER SAT, item 6.1.4. Envia o
CF-e de cancelamento para o equipamento SAT, que o enviará para
autorização e cancelamento do CF-e pela SEFAZ.
:param chave_cfe: String contendo a chave... | python | def cancelar_ultima_venda(self, chave_cfe, dados_cancelamento):
"""Função ``CancelarUltimaVenda`` conforme ER SAT, item 6.1.4. Envia o
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base4sistemas/satcfe | satcfe/base.py | FuncoesSAT.consultar_numero_sessao | def consultar_numero_sessao(self, numero_sessao):
"""Função ``ConsultarNumeroSessao`` conforme ER SAT, item 6.1.8.
Consulta o equipamento SAT por um número de sessão específico.
:param int numero_sessao: Número da sessão que se quer consultar.
:return: Retorna *verbatim* a resposta da ... | python | def consultar_numero_sessao(self, numero_sessao):
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Consulta o equipamento SAT por um número de sessão específico.
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:param int numero_sessao: Número da sessão que se quer consultar.
:return: Retorna *verbatim* a resposta da função SAT.
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base4sistemas/satcfe | satcfe/base.py | FuncoesSAT.configurar_interface_de_rede | def configurar_interface_de_rede(self, configuracao):
"""Função ``ConfigurarInterfaceDeRede`` conforme ER SAT, item 6.1.9.
Configurção da interface de comunicação do equipamento SAT.
:param configuracao: Instância de :class:`~satcfe.rede.ConfiguracaoRede`
ou uma string contendo o XM... | python | def configurar_interface_de_rede(self, configuracao):
"""Função ``ConfigurarInterfaceDeRede`` conforme ER SAT, item 6.1.9.
Configurção da interface de comunicação do equipamento SAT.
:param configuracao: Instância de :class:`~satcfe.rede.ConfiguracaoRede`
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base4sistemas/satcfe | satcfe/base.py | FuncoesSAT.associar_assinatura | def associar_assinatura(self, sequencia_cnpj, assinatura_ac):
"""Função ``AssociarAssinatura`` conforme ER SAT, item 6.1.10.
Associação da assinatura do aplicativo comercial.
:param sequencia_cnpj: Sequência string de 28 dígitos composta do CNPJ
do desenvolvedor da AC e do CNPJ do e... | python | def associar_assinatura(self, sequencia_cnpj, assinatura_ac):
"""Função ``AssociarAssinatura`` conforme ER SAT, item 6.1.10.
Associação da assinatura do aplicativo comercial.
:param sequencia_cnpj: Sequência string de 28 dígitos composta do CNPJ
do desenvolvedor da AC e do CNPJ do e... | [
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Associação da assinatura do aplicativo comercial.
:param sequencia_cnpj: Sequência string de 28 dígitos composta do CNPJ
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base4sistemas/satcfe | satcfe/base.py | FuncoesSAT.trocar_codigo_de_ativacao | def trocar_codigo_de_ativacao(self, novo_codigo_ativacao,
opcao=constantes.CODIGO_ATIVACAO_REGULAR,
codigo_emergencia=None):
"""Função ``TrocarCodigoDeAtivacao`` conforme ER SAT, item 6.1.15.
Troca do código de ativação do equipamento SAT.
:param str novo_codigo_ativacao... | python | def trocar_codigo_de_ativacao(self, novo_codigo_ativacao,
opcao=constantes.CODIGO_ATIVACAO_REGULAR,
codigo_emergencia=None):
"""Função ``TrocarCodigoDeAtivacao`` conforme ER SAT, item 6.1.15.
Troca do código de ativação do equipamento SAT.
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djgagne/hagelslag | hagelslag/evaluation/ObjectEvaluator.py | ObjectEvaluator.load_forecasts | def load_forecasts(self):
"""
Loads the forecast files and gathers the forecast information into pandas DataFrames.
"""
forecast_path = self.forecast_json_path + "/{0}/{1}/".format(self.run_date.strftime("%Y%m%d"),
self... | python | def load_forecasts(self):
"""
Loads the forecast files and gathers the forecast information into pandas DataFrames.
"""
forecast_path = self.forecast_json_path + "/{0}/{1}/".format(self.run_date.strftime("%Y%m%d"),
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djgagne/hagelslag | hagelslag/evaluation/ObjectEvaluator.py | ObjectEvaluator.load_obs | def load_obs(self):
"""
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"""
track_total_file = self.track_data_csv_path + \
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self... | python | def load_obs(self):
"""
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djgagne/hagelslag | hagelslag/evaluation/ObjectEvaluator.py | ObjectEvaluator.merge_obs | def merge_obs(self):
"""
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"""
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self.matched_forecasts[model_type] = {}
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"""
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"""
for model_type in self.model_types:
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djgagne/hagelslag | hagelslag/evaluation/ObjectEvaluator.py | ObjectEvaluator.crps | def crps(self, model_type, model_name, condition_model_name, condition_threshold, query=None):
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Calculates the cumulative ranked probability score (CRPS) on the forecast data.
Args:
model_type: model type being evaluated.
model_name: machine learning model being evalu... | python | def crps(self, model_type, model_name, condition_model_name, condition_threshold, query=None):
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djgagne/hagelslag | hagelslag/evaluation/ObjectEvaluator.py | ObjectEvaluator.roc | def roc(self, model_type, model_name, intensity_threshold, prob_thresholds, query=None):
"""
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Args:
model_type: type of model being evaluated (e.g. size).
model_name: machine learning model being evaluated
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model_type: type of model being evaluated (e.g. size).
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djgagne/hagelslag | hagelslag/evaluation/ObjectEvaluator.py | ObjectEvaluator.sample_forecast_max_hail | def sample_forecast_max_hail(self, dist_model_name, condition_model_name,
num_samples, condition_threshold=0.5, query=None):
"""
Samples every forecast hail object and returns an empirical distribution of possible maximum hail sizes.
Hail sizes are sampled from ... | python | def sample_forecast_max_hail(self, dist_model_name, condition_model_name,
num_samples, condition_threshold=0.5, query=None):
"""
Samples every forecast hail object and returns an empirical distribution of possible maximum hail sizes.
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paymentwall/paymentwall-python | paymentwall/widget.py | Widget.get_params | def get_params(self):
"""Get signature and params
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products_number = len(self.products)
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"""Get signature and params
"""
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base4sistemas/satcfe | satcfe/util.py | hms | def hms(segundos): # TODO: mover para util.py
"""
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.. sourcecode:: python
>>> hms(1)
(0, 0, 1)
>>> hms(60)
(0, 1, 0)
>>> hms(3600)
(1, 0, 0)
>>> hms(3601)
... | python | def hms(segundos): # TODO: mover para util.py
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>>> hms(1)
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>>> hms(60)
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>>> hms(3600)
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>>> hms(3601)
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base4sistemas/satcfe | satcfe/util.py | hms_humanizado | def hms_humanizado(segundos): # TODO: mover para util.py
"""
Retorna um texto legível que descreve o total de horas, minutos e segundos
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.. sourcecode:: python
>>> hms_humanizado(0)
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>>> hms_humanizado(1)
... | python | def hms_humanizado(segundos): # TODO: mover para util.py
"""
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>>> hms_humanizado(0)
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djgagne/hagelslag | hagelslag/data/HREFv2ModelGrid.py | ModelGrid.format_grib_name | def format_grib_name(self, selected_variable):
"""
Assigns name to grib2 message number with name 'unknown'. Names based on NOAA grib2 abbreviations.
Args:
selected_variable(str): name of selected variable for loading
Names:
3: LCDC: Low Cloud Cover
4:... | python | def format_grib_name(self, selected_variable):
"""
Assigns name to grib2 message number with name 'unknown'. Names based on NOAA grib2 abbreviations.
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selected_variable(str): name of selected variable for loading
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djgagne/hagelslag | hagelslag/data/HREFv2ModelGrid.py | ModelGrid.load_data | def load_data(self):
"""
Loads data from grib2 file objects or list of grib2 file objects. Handles specific grib2 variable names
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Returns:
Array of data loaded from files in (time, y, x) dimensions, Units
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"""
Loads data from grib2 file objects or list of grib2 file objects. Handles specific grib2 variable names
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djgagne/hagelslag | hagelslag/evaluation/GridEvaluator.py | GridEvaluator.load_forecasts | def load_forecasts(self):
"""
Load the forecast files into memory.
"""
run_date_str = self.run_date.strftime("%Y%m%d")
for model_name in self.model_names:
self.raw_forecasts[model_name] = {}
forecast_file = self.forecast_path + run_date_str + "/" + \
... | python | def load_forecasts(self):
"""
Load the forecast files into memory.
"""
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djgagne/hagelslag | hagelslag/evaluation/GridEvaluator.py | GridEvaluator.get_window_forecasts | def get_window_forecasts(self):
"""
Aggregate the forecasts within the specified time windows.
"""
for model_name in self.model_names:
self.window_forecasts[model_name] = {}
for size_threshold in self.size_thresholds:
self.window_forecasts[model_na... | python | def get_window_forecasts(self):
"""
Aggregate the forecasts within the specified time windows.
"""
for model_name in self.model_names:
self.window_forecasts[model_name] = {}
for size_threshold in self.size_thresholds:
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djgagne/hagelslag | hagelslag/evaluation/GridEvaluator.py | GridEvaluator.load_obs | def load_obs(self, mask_threshold=0.5):
"""
Loads observations and masking grid (if needed).
:param mask_threshold: Values greater than the threshold are kept, others are masked.
:return:
"""
start_date = self.run_date + timedelta(hours=self.start_hour)
end_date... | python | def load_obs(self, mask_threshold=0.5):
"""
Loads observations and masking grid (if needed).
:param mask_threshold: Values greater than the threshold are kept, others are masked.
:return:
"""
start_date = self.run_date + timedelta(hours=self.start_hour)
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djgagne/hagelslag | hagelslag/evaluation/GridEvaluator.py | GridEvaluator.dilate_obs | def dilate_obs(self, dilation_radius):
"""
Use a dilation filter to grow positive observation areas by a specified number of grid points
:param dilation_radius: Number of times to dilate the grid.
:return:
"""
for s in self.size_thresholds:
self.dilated_obs[s... | python | def dilate_obs(self, dilation_radius):
"""
Use a dilation filter to grow positive observation areas by a specified number of grid points
:param dilation_radius: Number of times to dilate the grid.
:return:
"""
for s in self.size_thresholds:
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djgagne/hagelslag | hagelslag/evaluation/GridEvaluator.py | GridEvaluator.roc_curves | def roc_curves(self, prob_thresholds):
"""
Generate ROC Curve objects for each machine learning model, size threshold, and time window.
:param prob_thresholds: Probability thresholds for the ROC Curve
:param dilation_radius: Number of times to dilate the observation grid.
:retur... | python | def roc_curves(self, prob_thresholds):
"""
Generate ROC Curve objects for each machine learning model, size threshold, and time window.
:param prob_thresholds: Probability thresholds for the ROC Curve
:param dilation_radius: Number of times to dilate the observation grid.
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djgagne/hagelslag | hagelslag/evaluation/GridEvaluator.py | GridEvaluator.reliability_curves | def reliability_curves(self, prob_thresholds):
"""
Output reliability curves for each machine learning model, size threshold, and time window.
:param prob_thresholds:
:param dilation_radius:
:return:
"""
all_rel_curves = {}
for model_name in self.model_na... | python | def reliability_curves(self, prob_thresholds):
"""
Output reliability curves for each machine learning model, size threshold, and time window.
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djgagne/hagelslag | hagelslag/util/convert_mrms_grids.py | load_map_coordinates | def load_map_coordinates(map_file):
"""
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Args:
map_file: Filename for the file containing coordinate information.
Returns:
Latitude and longitude grids as numpy arrays.
"""
if map_file[-4:] == ".pkl":... | python | def load_map_coordinates(map_file):
"""
Loads map coordinates from netCDF or pickle file created by util.makeMapGrids.
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map_file: Filename for the file containing coordinate information.
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Latitude and longitude grids as numpy arrays.
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djgagne/hagelslag | hagelslag/util/convert_mrms_grids.py | interpolate_mrms_day | def interpolate_mrms_day(start_date, variable, interp_type, mrms_path, map_filename, out_path):
"""
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start_date (datet... | python | def interpolate_mrms_day(start_date, variable, interp_type, mrms_path, map_filename, out_path):
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longitude grid, and saves the interpolated grids to CF-compliant netCDF4 files.
Args:
start_date (datetime.datetime): Date of data being interpolated
variable (str): MRMS variable
interp_type (st... | [
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"Ar... | train | https://github.com/djgagne/hagelslag/blob/6fb6c3df90bf4867e13a97d3460b14471d107df1/hagelslag/util/convert_mrms_grids.py#L81-L113 |
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