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JawboneHealth/jhhalchemy | jhhalchemy/model/__init__.py | Base.read_by | def read_by(cls, removed=False, **kwargs):
"""
filter_by query helper that handles soft delete logic. If your query conditions require expressions, use read.
:param removed: whether to include soft-deleted rows
:param kwargs: where clause mappings to pass to filter_by
:return: r... | python | def read_by(cls, removed=False, **kwargs):
"""
filter_by query helper that handles soft delete logic. If your query conditions require expressions, use read.
:param removed: whether to include soft-deleted rows
:param kwargs: where clause mappings to pass to filter_by
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JawboneHealth/jhhalchemy | jhhalchemy/model/__init__.py | Base.read | def read(cls, *criteria, **kwargs):
"""
filter query helper that handles soft delete logic. If your query conditions do not require expressions,
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:param criteria: where clause conditions
:param kwargs: set removed=True if you want soft-deleted rows
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"""
filter query helper that handles soft delete logic. If your query conditions do not require expressions,
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JawboneHealth/jhhalchemy | jhhalchemy/model/__init__.py | Base.delete | def delete(self, session, commit=True, soft=True):
"""
Delete a row from the DB.
:param session: flask_sqlalchemy session object
:param commit: whether to issue the commit
:param soft: whether this is a soft delete (i.e., update time_removed)
"""
if soft:
... | python | def delete(self, session, commit=True, soft=True):
"""
Delete a row from the DB.
:param session: flask_sqlalchemy session object
:param commit: whether to issue the commit
:param soft: whether this is a soft delete (i.e., update time_removed)
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gebn/wood | wood/entities.py | Entity.walk_paths | def walk_paths(self,
base: Optional[pathlib.PurePath] = pathlib.PurePath()) \
-> Iterator[pathlib.PurePath]:
"""
Recursively traverse all paths inside this entity, including the entity
itself.
:param base: The base path to prepend to the entity name.
... | python | def walk_paths(self,
base: Optional[pathlib.PurePath] = pathlib.PurePath()) \
-> Iterator[pathlib.PurePath]:
"""
Recursively traverse all paths inside this entity, including the entity
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gebn/wood | wood/entities.py | Entity._walk_paths | def _walk_paths(self, base: pathlib.PurePath) \
-> Iterator[pathlib.PurePath]:
"""
Internal helper for walking paths. This is required to exclude the name
of the root entity from the walk.
:param base: The base path to prepend to the entity name.
:return: An iterator... | python | def _walk_paths(self, base: pathlib.PurePath) \
-> Iterator[pathlib.PurePath]:
"""
Internal helper for walking paths. This is required to exclude the name
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gebn/wood | wood/entities.py | Entity.from_path | def from_path(cls, path: pathlib.Path) -> 'Entity':
"""
Create an entity from a local path.
:param path: The path to the entity, either a file or directory.
:return: An entity instance representing the path.
"""
if path.is_file():
return File.from_path(path)
... | python | def from_path(cls, path: pathlib.Path) -> 'Entity':
"""
Create an entity from a local path.
:param path: The path to the entity, either a file or directory.
:return: An entity instance representing the path.
"""
if path.is_file():
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gebn/wood | wood/entities.py | File._md5 | def _md5(path: pathlib.PurePath):
"""
Calculate the MD5 checksum of a file.
:param path: The path of the file whose checksum to calculate.
:return: The lowercase hex representation of the file's MD5
checksum, exactly 32 chars long.
"""
hash_ = hashlib... | python | def _md5(path: pathlib.PurePath):
"""
Calculate the MD5 checksum of a file.
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:return: The lowercase hex representation of the file's MD5
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gebn/wood | wood/entities.py | File.from_path | def from_path(cls, path: pathlib.Path) -> 'File':
"""
Create a file entity from a file path.
:param path: The path of the file.
:return: A file entity instance representing the file.
:raises ValueError: If the path does not point to a file.
"""
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"""
Create a file entity from a file path.
:param path: The path of the file.
:return: A file entity instance representing the file.
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gebn/wood | wood/entities.py | Directory.from_path | def from_path(cls, path: pathlib.Path) -> 'Directory':
"""
Create a directory entity from a directory path.
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:return: A directory entity instance representing the directory.
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rhayes777/PyAutoFit | autofit/optimize/grid_search.py | GridSearchResult.best_result | def best_result(self):
"""
The best result of the grid search. That is, the result output by the non linear search that had the highest
maximum figure of merit.
Returns
-------
best_result: Result
"""
best_result = None
for result in self.results:... | python | def best_result(self):
"""
The best result of the grid search. That is, the result output by the non linear search that had the highest
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Returns
-------
best_result: Result
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rhayes777/PyAutoFit | autofit/optimize/grid_search.py | GridSearch.make_lists | def make_lists(self, grid_priors):
"""
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Parameters
----------
grid_priors: [p.Prior]
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rhayes777/PyAutoFit | autofit/optimize/grid_search.py | GridSearch.fit | def fit(self, analysis, grid_priors):
"""
Fit an analysis with a set of grid priors. The grid priors are priors associated with the model mapper
of this instance that are replaced by uniform priors for each step of the grid search.
Parameters
----------
analysis: non_lin... | python | def fit(self, analysis, grid_priors):
"""
Fit an analysis with a set of grid priors. The grid priors are priors associated with the model mapper
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Nic30/hwtGraph | hwtGraph/elk/fromHwt/resolveSharedConnections.py | portTryReduce | def portTryReduce(root: LNode, port: LPort):
"""
Check if majority of children is connected to same port
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Nic30/hwtGraph | hwtGraph/elk/fromHwt/resolveSharedConnections.py | resolveSharedConnections | def resolveSharedConnections(root: LNode):
"""
Walk all ports on all nodes and group subinterface connections
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... | python | def resolveSharedConnections(root: LNode):
"""
Walk all ports on all nodes and group subinterface connections
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for ch in root.children:
resolveSharedConnections(ch)
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Nic30/hwtGraph | hwtGraph/elk/fromHwt/resolveSharedConnections.py | countDirectlyConnected | def countDirectlyConnected(port: LPort, result: dict) -> int:
"""
Count how many ports are directly connected to other nodes
:return: cumulative sum of port counts
"""
inEdges = port.incomingEdges
outEdges = port.outgoingEdges
if port.children:
ch_cnt = 0
# try:
# ... | python | def countDirectlyConnected(port: LPort, result: dict) -> int:
"""
Count how many ports are directly connected to other nodes
:return: cumulative sum of port counts
"""
inEdges = port.incomingEdges
outEdges = port.outgoingEdges
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ch_cnt = 0
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redhat-openstack/python-tripleo-helper | tripleohelper/ovb_baremetal.py | Baremetal.deploy | def deploy(self, image_name, ip, flavor='m1.small'):
"""Create the node.
This method should only be called by the BaremetalFactory.
"""
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"""Create the node.
This method should only be called by the BaremetalFactory.
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"""Specify which file ipxe should load during the netboot."""
new_port = {
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"""Specify which file ipxe should load during the netboot."""
new_port = {
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redhat-openstack/python-tripleo-helper | tripleohelper/ovb_baremetal.py | BaremetalFactory.initialize | def initialize(self, size=2):
"""Populate the node poll.
:param size: the number of node to create.
"""
# The IP should be in this range, this is the default DHCP range used by the introspection.
# inspection_iprange = 192.0.2.100,192.0.2.120
for i in range(0, size):
... | python | def initialize(self, size=2):
"""Populate the node poll.
:param size: the number of node to create.
"""
# The IP should be in this range, this is the default DHCP range used by the introspection.
# inspection_iprange = 192.0.2.100,192.0.2.120
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redhat-openstack/python-tripleo-helper | tripleohelper/ovb_baremetal.py | BaremetalFactory.create_bmc | def create_bmc(self, os_username, os_password, os_project_id, os_auth_url):
"""Deploy the BMC machine.
This machine hosts the ipmi servers, each ipmi server is associated to a baremetal
node and has its own IP.
"""
bmc = ovb_bmc.OvbBmc(
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"""Deploy the BMC machine.
This machine hosts the ipmi servers, each ipmi server is associated to a baremetal
node and has its own IP.
"""
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unt-libraries/pyuntl | pyuntl/untldoc.py | untlxml2py | def untlxml2py(untl_filename):
"""Parse a UNTL XML file object into a pyuntl element tree.
You can also pass this a string as file input like so:
import StringIO
untlxml2py(StringIO.StringIO(untl_string))
"""
# Create a stack to hold parents.
parent_stack = []
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"""Parse a UNTL XML file object into a pyuntl element tree.
You can also pass this a string as file input like so:
import StringIO
untlxml2py(StringIO.StringIO(untl_string))
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unt-libraries/pyuntl | pyuntl/untldoc.py | untldict2py | def untldict2py(untl_dict):
"""Convert a UNTL dictionary into a Python object."""
# Create the root element.
untl_root = PYUNTL_DISPATCH['metadata']()
untl_py_list = []
for element_name, element_list in untl_dict.items():
# Loop through the element dictionaries in the element list.
f... | python | def untldict2py(untl_dict):
"""Convert a UNTL dictionary into a Python object."""
# Create the root element.
untl_root = PYUNTL_DISPATCH['metadata']()
untl_py_list = []
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unt-libraries/pyuntl | pyuntl/untldoc.py | post2pydict | def post2pydict(post, ignore_list):
"""Convert the UNTL posted data to a Python dictionary."""
root_element = PYUNTL_DISPATCH['metadata']()
untl_form_dict = {}
# Turn the posted data into usable data
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form_post = dict(post.copy())
# Loop through al... | python | def post2pydict(post, ignore_list):
"""Convert the UNTL posted data to a Python dictionary."""
root_element = PYUNTL_DISPATCH['metadata']()
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unt-libraries/pyuntl | pyuntl/untldoc.py | untlpy2dcpy | def untlpy2dcpy(untl_elements, **kwargs):
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ark: Takes an ark string and creates an identifier element out of it.
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"""Convert the UNTL elements structure into a DC structure.
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unt-libraries/pyuntl | pyuntl/untldoc.py | untlpy2highwirepy | def untlpy2highwirepy(untl_elements, **kwargs):
"""Convert a UNTL Python object to a highwire Python object."""
highwire_list = []
title = None
publisher = None
creation = None
escape = kwargs.get('escape', False)
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# If the UNTL element should be... | python | def untlpy2highwirepy(untl_elements, **kwargs):
"""Convert a UNTL Python object to a highwire Python object."""
highwire_list = []
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publisher = None
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escape = kwargs.get('escape', False)
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unt-libraries/pyuntl | pyuntl/untldoc.py | untlpydict2dcformatteddict | def untlpydict2dcformatteddict(untl_dict, **kwargs):
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ark = kwargs.get('ark', None)
domain_name = kwargs.get('domain_name', None)
scheme = kwargs.get('scheme', 'http')
resolve_values = kwargs.get('resolve_values', None)
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"""Convert a UNTL data dictionary to a formatted DC data dictionary."""
ark = kwargs.get('ark', None)
domain_name = kwargs.get('domain_name', None)
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unt-libraries/pyuntl | pyuntl/untldoc.py | formatted_dc_dict | def formatted_dc_dict(dc_dict):
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i.e. {'publisher': ['someone', 'someone else'], 'title': ['a title'],}
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unt-libraries/pyuntl | pyuntl/untldoc.py | generate_dc_xml | def generate_dc_xml(dc_dict):
"""Generate a DC XML string."""
# Define the root namespace.
root_namespace = '{%s}' % DC_NAMESPACES['oai_dc']
# Set the elements namespace URL.
elements_namespace = '{%s}' % DC_NAMESPACES['dc']
schema_location = ('http://www.openarchives.org/OAI/2.0/oai_dc/ '
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"""Generate a DC XML string."""
# Define the root namespace.
root_namespace = '{%s}' % DC_NAMESPACES['oai_dc']
# Set the elements namespace URL.
elements_namespace = '{%s}' % DC_NAMESPACES['dc']
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unt-libraries/pyuntl | pyuntl/untldoc.py | generate_dc_json | def generate_dc_json(dc_dict):
"""Generate DC JSON data.
Returns data as a JSON formatted string.
"""
formatted_dict = formatted_dc_dict(dc_dict)
return json.dumps(formatted_dict, sort_keys=True, indent=4) | python | def generate_dc_json(dc_dict):
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formatted_dict = formatted_dc_dict(dc_dict)
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unt-libraries/pyuntl | pyuntl/untldoc.py | highwirepy2dict | def highwirepy2dict(highwire_elements):
"""Convert a list of highwire elements into a dictionary.
The dictionary returned contains the elements in the
UNTL dict format.
"""
highwire_dict = {}
# Make a list of content dictionaries for each element name.
for element in highwire_elements:
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"""Convert a list of highwire elements into a dictionary.
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highwire_dict = {}
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unt-libraries/pyuntl | pyuntl/untldoc.py | generate_highwire_json | def generate_highwire_json(highwire_elements):
"""Convert highwire elements into a JSON structure.
Returns data as a JSON formatted string.
"""
highwire_dict = highwirepy2dict(highwire_elements)
return json.dumps(highwire_dict, sort_keys=True, indent=4) | python | def generate_highwire_json(highwire_elements):
"""Convert highwire elements into a JSON structure.
Returns data as a JSON formatted string.
"""
highwire_dict = highwirepy2dict(highwire_elements)
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unt-libraries/pyuntl | pyuntl/untldoc.py | dcdict2rdfpy | def dcdict2rdfpy(dc_dict):
"""Convert a DC dictionary into an RDF Python object."""
ark_prefix = 'ark: ark:'
uri = URIRef('')
# Create the RDF Python object.
rdf_py = ConjunctiveGraph()
# Set DC namespace definition.
DC = Namespace('http://purl.org/dc/elements/1.1/')
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"""Convert a DC dictionary into an RDF Python object."""
ark_prefix = 'ark: ark:'
uri = URIRef('')
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rdf_py = ConjunctiveGraph()
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unt-libraries/pyuntl | pyuntl/untldoc.py | add_empty_fields | def add_empty_fields(untl_dict):
"""Add empty values if UNTL fields don't have values."""
# Iterate the ordered UNTL XML element list to determine
# which elements are missing from the untl_dict.
for element in UNTL_XML_ORDER:
if element not in untl_dict:
# Try to create an element w... | python | def add_empty_fields(untl_dict):
"""Add empty values if UNTL fields don't have values."""
# Iterate the ordered UNTL XML element list to determine
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unt-libraries/pyuntl | pyuntl/untldoc.py | add_empty_etd_ms_fields | def add_empty_etd_ms_fields(etd_ms_dict):
"""Add empty values for ETD_MS fields that don't have values."""
# Determine which ETD MS elements are missing from the etd_ms_dict.
for element in ETD_MS_ORDER:
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"""Add empty values for ETD_MS fields that don't have values."""
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unt-libraries/pyuntl | pyuntl/untldoc.py | find_untl_errors | def find_untl_errors(untl_dict, **kwargs):
"""Add empty required qualifiers to create valid UNTL."""
fix_errors = kwargs.get('fix_errors', False)
error_dict = {}
# Loop through all elements that require qualifiers.
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"""Add empty required qualifiers to create valid UNTL."""
fix_errors = kwargs.get('fix_errors', False)
error_dict = {}
# Loop through all elements that require qualifiers.
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unt-libraries/pyuntl | pyuntl/untldoc.py | untlpy2etd_ms | def untlpy2etd_ms(untl_elements, **kwargs):
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unt-libraries/pyuntl | pyuntl/untldoc.py | etd_ms_dict2xmlfile | def etd_ms_dict2xmlfile(filename, metadata_dict):
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f.write(generate_etd_ms_xml(metadata_dict).encode("utf-8"))
f.close()
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"""Create an ETD MS XML file."""
try:
f = open(filename, 'w')
f.write(generate_etd_ms_xml(metadata_dict).encode("utf-8"))
f.close()
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rhayes777/PyAutoFit | autofit/tools/fit.py | DataFit.signal_to_noise_map | def signal_to_noise_map(self):
"""The signal-to-noise_map of the data and noise-map which are fitted."""
signal_to_noise_map = np.divide(self.data, self.noise_map)
signal_to_noise_map[signal_to_noise_map < 0] = 0
return signal_to_noise_map | python | def signal_to_noise_map(self):
"""The signal-to-noise_map of the data and noise-map which are fitted."""
signal_to_noise_map = np.divide(self.data, self.noise_map)
signal_to_noise_map[signal_to_noise_map < 0] = 0
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althonos/moclo | moclo/moclo/core/parts.py | AbstractPart.structure | def structure(cls):
# type: () -> Text
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Warning:
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# type: () -> Text
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althonos/moclo | moclo/moclo/core/parts.py | AbstractPart.characterize | def characterize(cls, record):
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"""
classes = list(cls.__subclasses__())
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classes.append(cls)
for subclass in classes:
entity = subclass(record)
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"""Load the record in a concrete subclass of this type.
"""
classes = list(cls.__subclasses__())
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NikolayDachev/jadm | lib/paramiko-1.14.1/paramiko/transport.py | Transport.global_request | def global_request(self, kind, data=None, wait=True):
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:param str kind: name of the request.
:param tuple data:
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NikolayDachev/jadm | lib/paramiko-1.14.1/paramiko/transport.py | Transport._activate_inbound | def _activate_inbound(self):
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block_size = self._cipher_info[self.remote_cipher]['block-size']
if self.server_mode:
IV_in = self._compute_key('A', block_size)
key_in = self._compute_key('C', self._c... | python | def _activate_inbound(self):
"""switch on newly negotiated encryption parameters for inbound traffic"""
block_size = self._cipher_info[self.remote_cipher]['block-size']
if self.server_mode:
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redhat-openstack/python-tripleo-helper | tripleohelper/server.py | Server.enable_user | def enable_user(self, user):
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redhat-openstack/python-tripleo-helper | tripleohelper/server.py | Server.send_file | def send_file(self, local_path, remote_path, user='root', unix_mode=None):
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"""
self.enable_user(user)
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self.enable_user(user)
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redhat-openstack/python-tripleo-helper | tripleohelper/server.py | Server.send_dir | def send_dir(self, local_path, remote_path, user='root'):
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redhat-openstack/python-tripleo-helper | tripleohelper/server.py | Server.create_file | def create_file(self, path, content, mode='w', user='root'):
"""Create a file on the remote host.
"""
self.enable_user(user)
return self.ssh_pool.create_file(user, path, content, mode) | python | def create_file(self, path, content, mode='w', user='root'):
"""Create a file on the remote host.
"""
self.enable_user(user)
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redhat-openstack/python-tripleo-helper | tripleohelper/server.py | Server.yum_install | def yum_install(self, packages, ignore_error=False):
"""Install some packages on the remote host.
:param packages: ist of packages to install.
"""
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redhat-openstack/python-tripleo-helper | tripleohelper/server.py | Server.rhsm_register | def rhsm_register(self, rhsm):
"""Register the host on the RHSM.
:param rhsm: a dict of parameters (login, password, pool_id)
"""
# Get rhsm credentials
login = rhsm.get('login')
password = rhsm.get('password', os.environ.get('RHN_PW'))
pool_id = rhsm.get('pool_i... | python | def rhsm_register(self, rhsm):
"""Register the host on the RHSM.
:param rhsm: a dict of parameters (login, password, pool_id)
"""
# Get rhsm credentials
login = rhsm.get('login')
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redhat-openstack/python-tripleo-helper | tripleohelper/server.py | Server.enable_repositories | def enable_repositories(self, repositories):
"""Enable a list of RHSM repositories.
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[{'type': 'rhsm_channel', 'name': 'rhel-7-server-rpms'}]
"""
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con... | python | def enable_repositories(self, repositories):
"""Enable a list of RHSM repositories.
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"""
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redhat-openstack/python-tripleo-helper | tripleohelper/server.py | Server.create_stack_user | def create_stack_user(self):
"""Create the stack user on the machine.
"""
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"""Create the stack user on the machine.
"""
self.run('adduser -m stack', success_status=(0, 9))
self.create_file('/etc/sudoers.d/stack', 'stack ALL=(root) NOPASSWD:ALL\n')
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redhat-openstack/python-tripleo-helper | tripleohelper/server.py | Server.fetch_image | def fetch_image(self, path, dest, user='root'):
"""Store in the user home directory an image from a remote location.
"""
self.run('test -f %s || curl -L -s -o %s %s' % (dest, dest, path),
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"""Store in the user home directory an image from a remote location.
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redhat-openstack/python-tripleo-helper | tripleohelper/server.py | Server.clean_system | def clean_system(self):
"""Clean up unnecessary packages from the system.
"""
self.run('systemctl disable NetworkManager', success_status=(0, 1))
self.run('systemctl stop NetworkManager', success_status=(0, 5))
self.run('pkill -9 dhclient', success_status=(0, 1))
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"""Clean up unnecessary packages from the system.
"""
self.run('systemctl disable NetworkManager', success_status=(0, 1))
self.run('systemctl stop NetworkManager', success_status=(0, 5))
self.run('pkill -9 dhclient', success_status=(0, 1))
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redhat-openstack/python-tripleo-helper | tripleohelper/server.py | Server.yum_update | def yum_update(self, allow_reboot=False):
"""Do a yum update on the system.
:param allow_reboot: If True and if a new kernel has been installed,
the system will be rebooted
"""
self.run('yum clean all')
self.run('test -f /usr/bin/subscription-manager && subscription-mana... | python | def yum_update(self, allow_reboot=False):
"""Do a yum update on the system.
:param allow_reboot: If True and if a new kernel has been installed,
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"""
self.run('yum clean all')
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JawboneHealth/jhhalchemy | jhhalchemy/model/time_order.py | get_by_range | def get_by_range(model_cls, *args, **kwargs):
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Get ordered list of models for the specified time range.
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geophysics-ubonn/crtomo_tools | lib/crtomo/parManager.py | ParMan.add_data | def add_data(self, data, metadata=None):
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Parameters
----------
data: numpy.ndarray
one or more parameter sets. It must either be 1D or 2D, with the
first dimension the number of parameter sets (K), and the second
the n... | python | def add_data(self, data, metadata=None):
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filename : string, file path
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pid : int
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filename : string, file path
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filename: string
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filename of sensitivity file
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geophysics-ubonn/crtomo_tools | lib/crtomo/parManager.py | ParMan.save_to_rho_file | def save_to_rho_file(self, filename, cid_mag, cid_pha=None):
"""Save one or two parameter sets in the rho.dat forward model format
Parameters
----------
filename: string (file path)
output filename
cid_mag: int
ID of magnitude parameter set
cid_ph... | python | def save_to_rho_file(self, filename, cid_mag, cid_pha=None):
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filename: string (file path)
output filename
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geophysics-ubonn/crtomo_tools | lib/crtomo/parManager.py | ParMan._clean_pid | def _clean_pid(self, pid):
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geophysics-ubonn/crtomo_tools | lib/crtomo/parManager.py | ParMan.extract_along_line | def extract_along_line(self, pid, xy0, xy1, N=10):
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geophysics-ubonn/crtomo_tools | lib/crtomo/parManager.py | ParMan.extract_polygon_area | def extract_polygon_area(self, pid, polygon_points):
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geophysics-ubonn/crtomo_tools | src/grid_homogenize.py | rotate_point | def rotate_point(xorigin, yorigin, x, y, angle):
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geophysics-ubonn/crtomo_tools | src/cr_get_modelling_errors.py | get_R_mod | def get_R_mod(options, rho0):
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rhayes777/PyAutoFit | autofit/tools/path_util.py | make_and_return_path_from_path_and_folder_names | def make_and_return_path_from_path_and_folder_names(path, folder_names):
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redhat-openstack/python-tripleo-helper | tripleohelper/ovb_bmc.py | OvbBmc.register_host | def register_host(self, bm_instance):
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gofed/gofedlib | gofedlib/go/snapshot.py | Snapshot.Godeps | def Godeps(self):
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rhayes777/PyAutoFit | autofit/optimize/non_linear.py | NonLinearOptimizer.backup_path | def backup_path(self) -> str:
"""
The path to the backed up optimizer folder.
"""
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"""
The path to the backed up optimizer folder.
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rhayes777/PyAutoFit | autofit/optimize/non_linear.py | NonLinearOptimizer.backup | def backup(self):
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rhayes777/PyAutoFit | autofit/optimize/non_linear.py | NonLinearOptimizer.restore | def restore(self):
"""
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Copy files from the backup folder to the sym-linked optimizer folder.
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rhayes777/PyAutoFit | autofit/optimize/non_linear.py | NonLinearOptimizer.config | def config(self, attribute_name, attribute_type=str):
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"""
Get a config field from this optimizer's section in non_linear.ini by a key and value type.
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attribute_name: str
The analysis_path of the field
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rhayes777/PyAutoFit | autofit/optimize/non_linear.py | MultiNest.weighted_sample_instance_from_weighted_samples | def weighted_sample_instance_from_weighted_samples(self, index):
"""Setup a model instance of a weighted sample, including its weight and likelihood.
Parameters
-----------
index : int
The index of the weighted sample to return.
"""
model, weight, likelihood ... | python | def weighted_sample_instance_from_weighted_samples(self, index):
"""Setup a model instance of a weighted sample, including its weight and likelihood.
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The index of the weighted sample to return.
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rhayes777/PyAutoFit | autofit/optimize/non_linear.py | MultiNest.weighted_sample_model_from_weighted_samples | def weighted_sample_model_from_weighted_samples(self, index):
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Riminder/python-riminder-api | riminder/hmacutils.py | compare_digest | def compare_digest(a, b):
"""Compare 2 hash digest."""
py_version = sys.version_info[0]
if py_version >= 3:
return _compare_digest_py3(a, b)
return _compare_digest_py2(a, b) | python | def compare_digest(a, b):
"""Compare 2 hash digest."""
py_version = sys.version_info[0]
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thiagopbueno/tf-rddlsim | tfrddlsim/viz/generic_visualizer.py | GenericVisualizer._render_trajectories | def _render_trajectories(self,
trajectories: Tuple[NonFluents, Fluents, Fluents, Fluents, np.array]) -> None:
'''Prints the first batch of simulated `trajectories`.
Args:
trajectories: NonFluents, states, actions, interms and rewards.
'''
if self._verbose:
... | python | def _render_trajectories(self,
trajectories: Tuple[NonFluents, Fluents, Fluents, Fluents, np.array]) -> None:
'''Prints the first batch of simulated `trajectories`.
Args:
trajectories: NonFluents, states, actions, interms and rewards.
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thiagopbueno/tf-rddlsim | tfrddlsim/viz/generic_visualizer.py | GenericVisualizer._render_batch | def _render_batch(self,
non_fluents: NonFluents,
states: Fluents, actions: Fluents, interms: Fluents,
rewards: np.array,
horizon: Optional[int] = None) -> None:
'''Prints `non_fluents`, `states`, `actions`, `interms` and `rewards`
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... | python | def _render_batch(self,
non_fluents: NonFluents,
states: Fluents, actions: Fluents, interms: Fluents,
rewards: np.array,
horizon: Optional[int] = None) -> None:
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thiagopbueno/tf-rddlsim | tfrddlsim/viz/generic_visualizer.py | GenericVisualizer._render_timestep | def _render_timestep(self,
t: int,
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r: np.float32) -> None:
'''Prints fluents and rewards for the given timestep `t`.
Args:
t (int): timestep
s (Sequence[Tuple[str], np.array]: State fluents.
a (S... | python | def _render_timestep(self,
t: int,
s: Fluents, a: Fluents, f: Fluents,
r: np.float32) -> None:
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thiagopbueno/tf-rddlsim | tfrddlsim/viz/generic_visualizer.py | GenericVisualizer._render_fluent_timestep | def _render_fluent_timestep(self,
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fluent_variables: Sequence[Tuple[str, List[str]]]) -> None:
'''Prints `fluents` of given `fluent_type` as list of instantiated variables
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Ar... | python | def _render_fluent_timestep(self,
fluent_type: str,
fluents: Sequence[Tuple[str, np.array]],
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thiagopbueno/tf-rddlsim | tfrddlsim/viz/generic_visualizer.py | GenericVisualizer._render_reward | def _render_reward(self, r: np.float32) -> None:
'''Prints reward `r`.'''
print("reward = {:.4f}".format(float(r)))
print() | python | def _render_reward(self, r: np.float32) -> None:
'''Prints reward `r`.'''
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thiagopbueno/tf-rddlsim | tfrddlsim/viz/generic_visualizer.py | GenericVisualizer._render_round_init | def _render_round_init(self, horizon: int, non_fluents: NonFluents) -> None:
'''Prints round init information about `horizon` and `non_fluents`.'''
print('*********************************************************')
print('>>> ROUND INIT, horizon = {}'.format(horizon))
print('************... | python | def _render_round_init(self, horizon: int, non_fluents: NonFluents) -> None:
'''Prints round init information about `horizon` and `non_fluents`.'''
print('*********************************************************')
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thiagopbueno/tf-rddlsim | tfrddlsim/viz/generic_visualizer.py | GenericVisualizer._render_round_end | def _render_round_end(self, rewards: np.array) -> None:
'''Prints round end information about `rewards`.'''
print("*********************************************************")
print(">>> ROUND END")
print("*********************************************************")
total_reward = ... | python | def _render_round_end(self, rewards: np.array) -> None:
'''Prints round end information about `rewards`.'''
print("*********************************************************")
print(">>> ROUND END")
print("*********************************************************")
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edx/edx-celeryutils | celery_utils/persist_on_failure.py | _truncate_to_field | def _truncate_to_field(model, field_name, value):
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Shorten data to fit in the specified model field.
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Shorten data to fit in the specified model field.
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edx/edx-celeryutils | celery_utils/persist_on_failure.py | PersistOnFailureTask.on_failure | def on_failure(self, exc, task_id, args, kwargs, einfo):
"""
If the task fails, persist a record of the task.
"""
if not FailedTask.objects.filter(task_id=task_id, datetime_resolved=None).exists():
FailedTask.objects.create(
task_name=_truncate_to_field(Failed... | python | def on_failure(self, exc, task_id, args, kwargs, einfo):
"""
If the task fails, persist a record of the task.
"""
if not FailedTask.objects.filter(task_id=task_id, datetime_resolved=None).exists():
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thiagopbueno/tf-rddlsim | tfrddlsim/viz/abstract_visualizer.py | Visualizer.render | def render(self,
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batch: Optional[int] = None) -> None:
'''Renders the simulated `trajectories` for the given `batch`.
Args:
trajectories: NonFluents, states, actions, interms and rewards.
... | python | def render(self,
trajectories: Tuple[NonFluents, Fluents, Fluents, Fluents, np.array],
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grundprinzip/pyxplorer | pyxplorer/types.py | Column.distribution | def distribution(self, limit=1024):
"""
Build the distribution of distinct values
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"""
Build the distribution of distinct values
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res = self._qexec("%s, count(*) as __cnt" % self.name(), group="%s" % self.name(),
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gofed/gofedlib | gofedlib/distribution/distributionnameparser.py | DistributionNameParser.parse | def parse(self, name):
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:param name: distribution string, e.g. "Fedora 23"
:type name: string
"""
name = name.strip()
groups = self._parseFedora(name)
if groups:
self._signature = DistributionNameSignature("Fedora", groups.group(1))
return self
raise ValueError("Dist... | python | def parse(self, name):
"""Parse distribution string
:param name: distribution string, e.g. "Fedora 23"
:type name: string
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name = name.strip()
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zalando-stups/lizzy-client | lizzy_client/token.py | get_token | def get_token(url: str, scopes: str, credentials_dir: str) -> dict:
"""
Get access token info.
"""
tokens.configure(url=url, dir=credentials_dir)
tokens.manage('lizzy', [scopes])
tokens.start()
return tokens.get('lizzy') | python | def get_token(url: str, scopes: str, credentials_dir: str) -> dict:
"""
Get access token info.
"""
tokens.configure(url=url, dir=credentials_dir)
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peterbe/gg | gg/builtins/config.py | config | def config(config, fork_name="", origin_name=""):
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state = read(config.configfile)
any_set = False
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any_set = True
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"""Setting various configuration options"""
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geophysics-ubonn/crtomo_tools | lib/crtomo/eitManager.py | eitMan.set_area_to_sip_signature | def set_area_to_sip_signature(self, xmin, xmax, zmin, zmax, spectrum):
"""Parameterize the eit instance by supplying one
SIP spectrum and the area to apply to.
Parameters
----------
xmin : float
Minimum x coordinate of the area
xmax : float
Maximu... | python | def set_area_to_sip_signature(self, xmin, xmax, zmin, zmax, spectrum):
"""Parameterize the eit instance by supplying one
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xmin : float
Minimum x coordinate of the area
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geophysics-ubonn/crtomo_tools | lib/crtomo/eitManager.py | eitMan.add_homogeneous_model | def add_homogeneous_model(self, magnitude, phase=0, frequency=None):
"""Add homogeneous models to one or all tomodirs. Register those as
forward models
Parameters
----------
magnitude : float
Value of homogeneous magnitude model
phase : float, optional
... | python | def add_homogeneous_model(self, magnitude, phase=0, frequency=None):
"""Add homogeneous models to one or all tomodirs. Register those as
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Parameters
----------
magnitude : float
Value of homogeneous magnitude model
phase : float, optional
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geophysics-ubonn/crtomo_tools | lib/crtomo/eitManager.py | eitMan.apply_crtomo_cfg | def apply_crtomo_cfg(self):
"""Set the global crtomo_cfg for all frequencies
"""
for key in sorted(self.tds.keys()):
self.tds[key].crtomo_cfg = self.crtomo_cfg.copy() | python | def apply_crtomo_cfg(self):
"""Set the global crtomo_cfg for all frequencies
"""
for key in sorted(self.tds.keys()):
self.tds[key].crtomo_cfg = self.crtomo_cfg.copy() | [
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geophysics-ubonn/crtomo_tools | lib/crtomo/eitManager.py | eitMan.apply_noise_models | def apply_noise_models(self):
"""Set the global noise_model for all frequencies
"""
for key in sorted(self.tds.keys()):
self.tds[key].noise_model = self.noise_model | python | def apply_noise_models(self):
"""Set the global noise_model for all frequencies
"""
for key in sorted(self.tds.keys()):
self.tds[key].noise_model = self.noise_model | [
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geophysics-ubonn/crtomo_tools | lib/crtomo/eitManager.py | eitMan.load_inversion_results | def load_inversion_results(self, sipdir):
"""Given an sEIT inversion directory, load inversion results and store
the corresponding parameter ids in self.assignments
Note that all previous data stored in this instance of the eitManager
will be overwritten, if required!
"""
... | python | def load_inversion_results(self, sipdir):
"""Given an sEIT inversion directory, load inversion results and store
the corresponding parameter ids in self.assignments
Note that all previous data stored in this instance of the eitManager
will be overwritten, if required!
"""
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geophysics-ubonn/crtomo_tools | lib/crtomo/eitManager.py | eitMan.plot_forward_models | def plot_forward_models(self, maglim=None, phalim=None, **kwargs):
"""Create plots of the forward models
Returns
-------
mag_fig: dict
Dictionary containing the figure and axes objects of the magnitude
plots
"""
return_dict = {}
N = len(... | python | def plot_forward_models(self, maglim=None, phalim=None, **kwargs):
"""Create plots of the forward models
Returns
-------
mag_fig: dict
Dictionary containing the figure and axes objects of the magnitude
plots
"""
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geophysics-ubonn/crtomo_tools | lib/crtomo/eitManager.py | eitMan.add_to_configs | def add_to_configs(self, configs):
"""Add configurations to all tomodirs
Parameters
----------
configs : :class:`numpy.ndarray`
Nx4 numpy array with abmn configurations
"""
for f, td in self.tds.items():
td.configs.add_to_configs(configs) | python | def add_to_configs(self, configs):
"""Add configurations to all tomodirs
Parameters
----------
configs : :class:`numpy.ndarray`
Nx4 numpy array with abmn configurations
"""
for f, td in self.tds.items():
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