text stringlengths 81 112k |
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Return avg room temperature for last session.
def last_room_temp(self):
"""Return avg room temperature for last session."""
try:
rmtemps = self.intervals[1]['timeseries']['tempRoomC']
except KeyError:
return None
tmp = 0
num_temps = len(rmtemps)
... |
Return avg heart rate for last session.
def last_heart_rate(self):
"""Return avg heart rate for last session."""
try:
rates = self.intervals[1]['timeseries']['heartRate']
except KeyError:
return None
tmp = 0
num_rates = len(rates)
if num_rates ==... |
Return a dict of all the 'last' parameters.
def last_values(self):
"""Return a dict of all the 'last' parameters."""
last_dict = {
'date': self.last_session_date,
'score': self.last_sleep_score,
'breakdown': self.last_sleep_breakdown,
'tnt': self.last_tnt... |
Calculate some heating data stats.
def heating_stats(self):
"""Calculate some heating data stats."""
local_5 = []
local_10 = []
for i in range(0, 10):
level = self.past_heating_level(i)
if level == 0:
_LOGGER.debug('Cant calculate stats yet...')
... |
Determine presence based on bed heating level and end presence
time reported by the api.
Idea originated from Alex Lee Yuk Cheung SmartThings Code.
def dynamic_presence(self):
"""
Determine presence based on bed heating level and end presence
time reported by the api.
... |
Update heating data json.
async def set_heating_level(self, level, duration=0):
"""Update heating data json."""
url = '{}/devices/{}'.format(API_URL, self.device.deviceid)
# Catch bad inputs
level = 10 if level < 10 else level
level = 100 if level > 100 else level
if s... |
Update trends data json for specified time period.
async def update_trend_data(self, startdate, enddate):
"""Update trends data json for specified time period."""
url = '{}/users/{}/trends'.format(API_URL, self.userid)
params = {
'tz': self.device.tzone,
'from': startdat... |
Update intervals data json for specified time period.
async def update_intervals_data(self):
"""Update intervals data json for specified time period."""
url = '{}/users/{}/intervals'.format(API_URL, self.userid)
intervals = await self.device.api_get(url)
if intervals is None:
... |
Saves a deserialized model object.
Uses save_base to avoid running code in model.save() and
to avoid triggering signals (if raw=True).
def save(obj=None, m2m_data=None):
"""Saves a deserialized model object.
Uses save_base to avoid running code in model.save() and
to avoid triggering signals (if ... |
Deserializes the encrypted serialized model
instances, tx, in a queryset of transactions.
Note: each transaction instance contains encrypted JSON text
that represents just ONE model instance.
def deserialize_transactions(self, transactions=None, deserialize_only=None):
"""Deserializes ... |
Runs json_text thru custom parsers.
def custom_parser(self, json_text=None):
"""Runs json_text thru custom parsers.
"""
app_config = django_apps.get_app_config("django_collect_offline")
for json_parser in app_config.custom_json_parsers:
json_text = json_parser(json_text)
... |
cli lazy property
def cli(self):
""" cli lazy property """
client = paramiko.SSHClient()
client.set_missing_host_key_policy(paramiko.AutoAddPolicy())
client.connect(hostname=self.private_hostname,
username=self.username,
key_filename=self.k... |
channel lazy property
def channel(self):
""" channel lazy property """
# start shell, non-blocking channel
chan = self.cli.invoke_shell(width=360, height=80)
chan.setblocking(0)
# set channel timeout
chan.settimeout(10)
# now waiting for shell prompt ('username@'... |
Plumbum lazy property
def pbm(self):
""" Plumbum lazy property """
if not self.disable_rpyc:
from plumbum import SshMachine
return SshMachine(host=self.private_hostname, user=self.username,
keyfile=self.key_filename,
ss... |
RPyC lazy property
def rpyc(self):
""" RPyC lazy property """
if not self.disable_rpyc:
try:
import rpyc
devnull_fd = open("/dev/null", "w")
rpyc_dirname = os.path.dirname(rpyc.__file__)
rnd_id = ''.join(random.choice(string.a... |
Close the connection
def disconnect(self):
"""
Close the connection
"""
if hasattr(self, '_lazy_sftp'):
if self.sftp is not None:
self.sftp.close()
delattr(self, '_lazy_sftp')
if hasattr(self, '_lazy_channel'):
if self.channel ... |
Execute a command in the connection
@param command: command to execute
@type command: str
@param bufsize: buffer size
@type bufsize: int
@param get_pty: get pty
@type get_pty: bool
@return: the stdin, stdout, and stderr of the executing command
@rtype:... |
Execute a command and get its return value
@param command: command to execute
@type command: str
@param timeout: command execution timeout
@type timeout: int
@param get_pty: get pty
@type get_pty: bool
@return: the exit code of the process or None in case of t... |
(Helper) Set counter to value
def set(self, value):
"""(Helper) Set counter to value"""
self._elk.send(cx_encode(self._index, value)) |
Saves the provenance object to a JSON file, optionally including
checksums for inputs and outputs (which are initially produced mid-
run) to insert during the write
Parameters
----------
path : str
Path to save the generated JSON file
inputs : dict[str, str |... |
Loads a saved provenance object from a JSON file
Parameters
----------
path : str
Path to the provenance file
frequency : str
The frequency of the record
subject_id : str | None
The subject ID of the provenance record
visit_id : str | ... |
Compares information stored within provenance objects with the
exception of version information to see if they match. Matches are
constrained to the paths passed to the 'include' kwarg, with the
exception of sub-paths passed to the 'exclude' kwarg
Parameters
----------
o... |
A method for translating pipeline constructors from a sub-study to the
namespace of a multi-study. Returns a new method that calls the
sub-study pipeline constructor with appropriate keyword arguments
Parameters
----------
substudy_name : str
Name of the sub-study
... |
Data specs in the sub-study class that are not explicitly provided
in the name map
def auto_data_specs(self):
"""
Data specs in the sub-study class that are not explicitly provided
in the name map
"""
for spec in self.study_class.data_specs():
if spec.name no... |
Parameter pecs in the sub-study class that are not explicitly provided
in the name map
def auto_param_specs(self):
"""
Parameter pecs in the sub-study class that are not explicitly provided
in the name map
"""
for spec in self.study_class.parameter_specs():
i... |
Cast generated nodes to be Arcana nodes
def _make_nodes(self, cwd=None):
"""
Cast generated nodes to be Arcana nodes
"""
for i, node in NipypeMapNode._make_nodes(self, cwd=cwd):
# "Cast" NiPype node to a Arcana Node and set Arcana Node
# parameters
no... |
Find file matching query_name, read and return query object
def get_query(query_name):
"""Find file matching query_name, read and return query object
"""
query_file_match = list(
filter(lambda i: query_name == i.stem, FLAT_QUERIES))
if not query_file_match:
return None
# TODO: Log w... |
Call get_query, then submit query from file to resultset module
def get_result_set(query_name, **kwargs):
""" Call get_query, then submit query from file to resultset module
"""
query = get_query(query_name)
if not query:
query = SimpleNamespace()
query.error = f"No query found matching... |
Generate CSV from result data
def results_to_csv(query_name, **kwargs):
""" Generate CSV from result data
"""
query = get_result_set(query_name, **kwargs)
result = query.result
columns = list(result[0].keys())
data = [tuple(row.values()) for row in result]
frame = tablib.Dataset()
frame... |
Registers with app_label.modelname, wrapper_cls.
def register(self, models=None, wrapper_cls=None):
"""Registers with app_label.modelname, wrapper_cls.
"""
self.loaded = True
for model in models:
model = model.lower()
if model not in self.registry:
... |
Registers all models for this app_label.
def register_for_app(
self, app_label=None, exclude_models=None, exclude_model_classes=None
):
"""Registers all models for this app_label.
"""
models = []
exclude_models = exclude_models or []
app_config = django_apps.get_app_... |
Returns a wrapped model instance.
def get_wrapped_instance(self, instance=None):
"""Returns a wrapped model instance.
"""
if instance._meta.label_lower not in self.registry:
raise ModelNotRegistered(f"{repr(instance)} is not registered with {self}.")
wrapper_cls = self.regis... |
Returns a dictionary of registered models.
def site_models(self, app_label=None):
"""Returns a dictionary of registered models.
"""
site_models = {}
app_configs = (
django_apps.get_app_configs()
if app_label is None
else [django_apps.get_app_config(ap... |
Set the path of the fileset from the repository
def get_fileset(self, fileset):
"""
Set the path of the fileset from the repository
"""
# Don't need to cache fileset as it is already local as long
# as the path is set
if fileset._path is None:
primary_path = ... |
Update the value of the field from the repository
def get_field(self, field):
"""
Update the value of the field from the repository
"""
# Load fields JSON, locking to prevent read/write conflicts
# Would be better if only checked if locked to allow
# concurrent reads but... |
Inserts or updates a fileset in the repository
def put_fileset(self, fileset):
"""
Inserts or updates a fileset in the repository
"""
target_path = self.fileset_path(fileset)
if op.isfile(fileset.path):
shutil.copyfile(fileset.path, target_path)
# Copy si... |
Inserts or updates a field in the repository
def put_field(self, field):
"""
Inserts or updates a field in the repository
"""
fpath = self.fields_json_path(field)
# Open fields JSON, locking to prevent other processes
# reading or writing
with InterProcessLock(fp... |
Find all data within a repository, registering filesets, fields and
provenance with the found_fileset, found_field and found_provenance
methods, respectively
Parameters
----------
subject_ids : list(str)
List of subject IDs with which to filter the tree with. If
... |
Try to guess the depth of a directory repository (i.e. whether it has
sub-folders for multiple subjects or visits, depending on where files
and/or derived label files are found in the hierarchy of
sub-directories under the root dir.
Parameters
----------
root_dir : str
... |
Get data source connection metadata based on config. Prefer, in order:
- Query file frontmatter
- `db.yaml` file in query subdirectory
- DATABASE_URL in environment
To allow for possible non-SQL sources to be contributed, we only
return a config value here, and leave connecting to concr... |
Returns a particular fileset|field in the collection corresponding to
the given subject and visit_ids. subject_id and visit_id must be
provided for relevant frequencies. Note that subject_id/visit_id can
also be provided for non-relevant frequencies, they will just be
ignored.
P... |
Used for duck typing Collection objects with Spec and Match
in source and sink initiation. Checks IDs match sessions in study.
def bind(self, study, **kwargs): # @UnusedVariable
"""
Used for duck typing Collection objects with Spec and Match
in source and sink initiation. Checks IDs ma... |
Gets the fileset named 'name' produced by the Study named 'study' if
provided. If a spec is passed instead of a str to the name argument,
then the study will be set from the spec iff it is derived
Parameters
----------
name : str | FilesetSpec
The name of the fileset... |
Gets the field named 'name' produced by the Study named 'study' if
provided. If a spec is passed instead of a str to the name argument,
then the study will be set from the spec iff it is derived
Parameters
----------
name : str | BaseField
The name of the field or a ... |
Returns the provenance record for a given pipeline
Parameters
----------
pipeline_name : str
The name of the pipeline that generated the record
from_study : str
The name of the study that the pipeline was generated from
Returns
-------
re... |
Highlights where two nodes differ in a human-readable form
Parameters
----------
other : TreeNode
The node to compare
indent : str
The white-space with which to indent output string
Returns
-------
mismatch : str
The human-rea... |
Returns an iterator over all nodes in the tree for the specified
frequency. If no frequency is specified then all nodes are returned
Parameters
----------
frequency : str | None
The frequency of the nodes to iterate over. If None all
frequencies are returned
... |
Used in debugging unittests
def find_mismatch(self, other, indent=''):
"""
Used in debugging unittests
"""
mismatch = super(Tree, self).find_mismatch(other, indent)
sub_indent = indent + ' '
if len(list(self.subjects)) != len(list(other.subjects)):
mismatch ... |
Fill in tree with additional empty subjects and/or visits to
allow the study to pull its inputs from external repositories
def _fill_empty_sessions(self, fill_subjects, fill_visits):
"""
Fill in tree with additional empty subjects and/or visits to
allow the study to pull its inputs from... |
Return the hierarchical tree of the filesets and fields stored in a
repository
Parameters
----------
respository : Repository
The repository that the tree comes from
filesets : list[Fileset]
List of all filesets in the tree
fields : list[Field]
... |
Returns all nodes of the specified frequency that are related to
the given Session
Parameters
----------
frequency : str | None
The frequency of the nodes to return
Returns
-------
nodes : iterable[TreeNode]
All nodes related to the Sessi... |
Write data on the asyncio Protocol
def write_data(self, data, response_required=None, timeout=5.0, raw=False):
"""Write data on the asyncio Protocol"""
if self._transport is None:
return
if self._paused:
return
if self._waiting_for_response:
LOG.deb... |
Convert responder querystring params, pulling values out of list
if there's only one.
def unwrap_querystring_lists(obj):
"""Convert responder querystring params, pulling values out of list
if there's only one.
"""
new_dict = {
key: (obj[key][0]
if len(obj[key]) == 1 else obj[k... |
For duck-typing with *Spec types
def pipeline_getter(self):
"For duck-typing with *Spec types"
if not self.derivable:
raise ArcanaUsageError(
"There is no pipeline getter for {} because it doesn't "
"fallback to a derived spec".format(self))
return se... |
Iterates through the inputs of the pipelinen and determines the
all prerequisite pipelines
def prerequisites(self):
"""
Iterates through the inputs of the pipelinen and determines the
all prerequisite pipelines
"""
# Loop through the inputs to the pipeline and add the in... |
Returns all inputs of the study used by the pipeline, including inputs
of prerequisites (and their prerequisites recursively)
def study_inputs(self):
"""
Returns all inputs of the study used by the pipeline, including inputs
of prerequisites (and their prerequisites recursively)
... |
Adds a processing Node to the pipeline
Parameters
----------
name : str
Name for the node
interface : nipype.Interface
The interface to use for the node
inputs : dict[str, (str, FileFormat) | (Node, str)]
Connections from inputs of the pipelin... |
Connects a study fileset_spec as an input to the provided node
Parameters
----------
spec_name : str
Name of the study data spec (or one of the IDs from the iterator
nodes, 'subject_id' or 'visit_id') to connect to the node
node : arcana.Node
The node... |
Connects an output to a study fileset spec
Parameters
----------
spec_name : str
Name of the study fileset spec to connect to
node : arcana.Node
The node to connect the output from
node_output : str
Name of the output on the node to connect to... |
Maps a spec name to a new value based on the provided mapper
def _map_name(self, name, mapper):
"""
Maps a spec name to a new value based on the provided mapper
"""
if mapper is not None:
if isinstance(mapper, basestring):
name = mapper + name
try... |
Checks whether the fileset matches the requested file format
def requires_conversion(cls, fileset, file_format):
"""Checks whether the fileset matches the requested file format"""
if file_format is None:
return False
try:
filset_format = fileset.format
except Att... |
Saves a graph of the pipeline to file
Parameters
----------
fname : str
The filename for the saved graph
style : str
The style of the graph, can be one of can be one of
'orig', 'flat', 'exec', 'hierarchical'
plot : bool
Whether to ... |
Returns the iterators (i.e. subject_id, visit_id) that the pipeline
iterates over
Parameters
----------
frequency : str | None
A selected data frequency to use to determine which iterators are
required. If None, all input frequencies of the pipeline are
... |
Unwraps potentially nested name-mapping dictionaries to get values
for name, input_map, output_map and study. Unsed in __init__.
Parameters
----------
name_maps : dict
A dictionary containing the name_maps to apply to the values
name : str
Name passed fro... |
"Caps" the construction of the pipeline, signifying that no more inputs
and outputs are expected to be added and therefore the input and output
nodes can be created along with the provenance.
def cap(self):
"""
"Caps" the construction of the pipeline, signifying that no more inputs
... |
Generates an input node for the given frequency. It also adds implicit
file format conversion nodes to the pipeline.
Parameters
----------
frequency : str
The frequency (i.e. 'per_session', 'per_visit', 'per_subject' or
'per_study') of the input node to retrieve
... |
Generates an output node for the given frequency. It also adds implicit
file format conversion nodes to the pipeline.
Parameters
----------
frequency : str
The frequency (i.e. 'per_session', 'per_visit', 'per_subject' or
'per_study') of the output node to retriev... |
Extracts provenance information from the pipeline into a PipelineProv
object
Returns
-------
prov : dict[str, *]
A dictionary containing the provenance information to record
for the pipeline
def _gen_prov(self):
"""
Extracts provenance informatio... |
Constructs the provenance record that would be saved in the given node
if the pipeline was run on the current state of the repository
Parameters
----------
node : arcana.repository.tree.TreeNode
A node of the Tree representation of the study data stored in the
re... |
Adds the subjects/visits used to generate the derivatives iff there are
any joins over them in the pipeline
def _joined_ids(self):
"""
Adds the subjects/visits used to generate the derivatives iff there are
any joins over them in the pipeline
"""
joined_prov = {}
... |
Return the tree of subject and sessions information within a
project in the XNAT repository
Parameters
----------
subject_ids : list(str)
List of subject IDs with which to filter the tree with. If
None all are returned
visit_ids : list(str)
Li... |
Access the repository tree and caches it for subsequent
accesses
Parameters
----------
subject_ids : list(str)
List of subject IDs with which to filter the tree with. If
None all are returned
visit_ids : list(str)
List of visit IDs with which ... |
Names of resources used to store the format on a given repository type.
Defaults to the name of the name of the format
def resource_names(self, repo_type):
"""
Names of resources used to store the format on a given repository type.
Defaults to the name of the name of the format
... |
Get the default paths for auxiliary files relative to the path of the
primary file, i.e. the same name as the primary path with a different
extension
Parameters
----------
primary_path : str
Path to the primary file in the fileset
Returns
-------
... |
Assorts candidate files into primary and auxiliary (and ignored) files
corresponding to the format by their file extensions. Can be overridden
in specialised subclasses to assort files based on other
characteristics
Parameters
----------
candidates : list[str]
... |
Checks to see whether the format matches the given fileset
Parameters
----------
fileset : Fileset
The fileset to check
def matches(self, fileset):
"""
Checks to see whether the format matches the given fileset
Parameters
----------
fileset ... |
Register a Converter and the FileFormat that it is able to convert from
Parameters
----------
converter : Converter
The converter to register
file_format : FileFormat
The file format that can be converted into this format
def set_converter(self, file_format, con... |
Parse a Elk connection string
def parse_url(url):
"""Parse a Elk connection string """
scheme, dest = url.split('://')
host = None
ssl_context = None
if scheme == 'elk':
host, port = dest.split(':') if ':' in dest else (dest, 2101)
elif scheme == 'elks':
host, port = dest.split(... |
Make a constant pretty for printing in GUI
def pretty_const(value):
"""Make a constant pretty for printing in GUI"""
words = value.split('_')
pretty = words[0].capitalize()
for word in words[1:]:
pretty += ' ' + word.lower()
return pretty |
Return name of user.
def username(elk, user_number):
"""Return name of user."""
if user_number >= 0 and user_number < elk.users.max_elements:
return elk.users[user_number].name
if user_number == 201:
return "*Program*"
if user_number == 202:
return "*Elk RP*"
if user_number ... |
Asyncio connection to Elk.
async def _connect(self, connection_lost_callbk=None):
"""Asyncio connection to Elk."""
self.connection_lost_callbk = connection_lost_callbk
url = self._config['url']
LOG.info("Connecting to ElkM1 at %s", url)
scheme, dest, param, ssl_context = parse_u... |
Login and sync the ElkM1 panel to memory.
def _connected(self, transport, conn):
"""Login and sync the ElkM1 panel to memory."""
LOG.info("Connected to ElkM1")
self._conn = conn
self._transport = transport
self._connection_retry_timer = 1
if url_scheme_is_secure(self._co... |
Text description
def _sd_handler(self, desc_type, unit, desc, show_on_keypad):
"""Text description"""
if desc_type not in self._descriptions_in_progress:
LOG.debug("Text description response ignored for " + str(desc_type))
return
(max_units, results, callback) = self._d... |
Send a message to Elk panel.
def send(self, msg):
"""Send a message to Elk panel."""
if self._conn:
self._conn.write_data(msg.message, msg.response_command) |
Retrieve zones from ElkM1
def sync(self):
"""Retrieve zones from ElkM1"""
self.elk.send(az_encode())
self.elk.send(zd_encode())
self.elk.send(zp_encode())
self.elk.send(zs_encode())
self.get_descriptions(TextDescriptions.ZONE.value) |
Raises an exception if model uses a history manager and
historical model history_id is not a UUIDField.
Note: expected to use edc_model.HistoricalRecords instead of
simple_history.HistoricalRecords.
def has_offline_historical_manager_or_raise(self):
"""Raises an exception if model uses... |
Return the primary key field.
Is `id` in most cases. Is `history_id` for Historical models.
def primary_key_field(self):
"""Return the primary key field.
Is `id` in most cases. Is `history_id` for Historical models.
"""
return [field for field in self.instance._meta.fields if ... |
Serialize the model instance to an AES encrypted json object
and saves the json object to the OutgoingTransaction model.
def to_outgoing_transaction(self, using, created=None, deleted=None):
""" Serialize the model instance to an AES encrypted json object
and saves the json object to the Outgoi... |
Returns an encrypted json serialized from self.
def encrypted_json(self):
"""Returns an encrypted json serialized from self.
"""
json = serialize(objects=[self.instance])
encrypted_json = Cryptor().aes_encrypt(json, LOCAL_MODE)
return encrypted_json |
Maps the name of an Requirement class to the name of the corresponding
module in the environment
Parameters
----------
requirement : Requirement
The requirement to map to the name of a module on the system
def map_req(self, requirement):
"""
Maps the name of... |
Maps a local version name to one recognised by the Requirement class
Parameters
----------
requirement : str
Name of the requirement
version : str
version string
def map_version(self, requirement, local_version):
"""
Maps a local version name to ... |
Register the TagProcessors that are bundled with doxytag2zealdb.
def init_tag_processors(self):
'''Register the TagProcessors that are bundled with doxytag2zealdb.'''
register = self.register_tag_processor
register('class', classTagProcessor(**self.opts))
register('file', fileTagProces... |
Run all tag processors.
def process(self):
'''Run all tag processors.'''
for tag_proc in self.tag_procs:
before_count = self.entry_count
self.run_tag_processor(tag_proc)
after_count = self.entry_count
if self.verbose:
print('Inserted %d e... |
Run a tag processor.
Args:
tag_proc_name: A string key that maps to the TagProcessor to run.
def run_tag_processor(self, tag_proc_name):
'''Run a tag processor.
Args:
tag_proc_name: A string key that maps to the TagProcessor to run.
'''
tag_processor = ... |
Process a tag with a tag processor and insert a DB entry.
Args:
tag_proc_name: A string key that maps to the TagProcessor to use.
tag: A BeautifulSoup Tag to process.
def process_tag(self, tag_proc_name, tag):
'''Process a tag with a tag processor and insert a DB entry.
... |
wrapper to itertools.groupby that returns a list of each group, rather
than a generator and accepts integers or strings as the key and
automatically converts them to callables with itemgetter(key)
Arguments:
iterable: iterable
key: string, int or callable that tells how to group
Return... |
>>> groups_of(2, range(5))
def groups_of(n, iterable):
"""
>>> groups_of(2, range(5))
"""
args = [iter(iterable)] * n
for x in izip_longest(*args):
yield [v for v in x if v is not None] |
Connects all pipelines to that study's repository and runs them
in the same NiPype workflow
Parameters
----------
pipeline(s) : Pipeline, ...
The pipeline to connect to repository
required_outputs : list[set[str]]
A set of required outputs for each pipeli... |
Connects a pipeline to a overarching workflow that sets up iterators
over subjects|visits present in the repository (if required) and
repository source and sink nodes
Parameters
----------
pipeline : Pipeline
The pipeline to connect
required_outputs : set[str... |
Generate nodes that iterate over subjects and visits in the study that
need to be processed by the pipeline
Parameters
----------
pipeline : Pipeline
The pipeline to add iter_nodes for
to_process_array : 2-D numpy.array[bool]
A two-dimensional boolean arr... |
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