text stringlengths 75 104k | code_tokens list | avg_line_len float64 7.91 980 | score float64 0 0.18 |
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def visit_Capture(self, node: parsing.Capture) -> [ast.stmt] or ast.expr:
"""Generates python code to capture text consumed by a clause.
#If all clauses can be inlined
self.beginTag('tagname') and clause and self.endTag('tagname')
if not self.beginTag('tagname'):
return Fal... | [
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def get_pstats_print2list(fnames, filter_fnames=None, exclude_fnames=None,
sort=None, sort_reverse=None, limit=None):
"""Print stats with a filter or exclude filenames, sort index and limit.
:param list fnames: cProfile standard files to process.
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def mtf_transformer_lm_baseline():
"""Small language model to run on 1 TPU.
Run this on 2x2 on languagemodel_lm1b32k_packed for 272000 steps (10 epochs)
Results:
params/10^9 log-ppl(per-token)
0.14 3.202
Returns:
a hparams
"""
hparams = mtf_transformer_paper_lm(-1)
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def whois_list(request, format=None):
"""
Retrieve basic whois information related to a layer2 or layer3 network address.
"""
results = []
# layer3 results
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def load_modules(self, data=None, proxy=None):
'''
Load the modules into the state
'''
log.info('Loading fresh modules for state activity')
self.utils = salt.loader.utils(self.opts)
self.functions = salt.loader.minion_mods(self.opts, self.state_con,
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def handle_processing_packets():
"""handle_processing_packets
Replacement packet processing engine. This is not done.
"""
host = os.getenv(
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port = int(os.getenv(
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def price_dataframe(symbols='sp5002012',
start=datetime.datetime(2008, 1, 1),
end=datetime.datetime(2009, 12, 31),
price_type='actual_close',
cleaner=clean_dataframe,
):
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def disvec(self, x, y, aq=None):
'''Returns array of size (2, nparam, naq)'''
if aq is None: aq = self.model.aq.find_aquifer_data(x, y)
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def parse_localclasspath(self, tup_tree):
"""
Parse a LOCALCLASSPATH element and return the class path it represents
as a CIMClassName object.
::
<!ELEMENT LOCALCLASSPATH (LOCALNAMESPACEPATH, CLASSNAME)>
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self.check_node(tup_tree, 'LOCALCLASSPATH')
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def is_highlink_density(self, element):
"""
checks the density of links within a node,
is there not much text and most of it contains linky shit?
if so it's no good
"""
links = self.parser.getElementsByTag(element, tag='a')
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def random_link(self, dataset, state, backward=False):
"""Get a random link.
Parameters
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dataset : `object`
Dataset from `self.get_dataset()`.
state : `object`
Link source.
backward : `bool`, optional
Link direction.
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def copystat(self, target):
"""Copies the permissions, times and flags from this to the `target`.
The owner is not copied.
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def pb_for_delete(document_path, option):
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Args:
document_path (str): A fully-qualified document path.
option (optional[~.firestore_v1beta1.client.WriteOption]): A
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def _convert_filetime_to_timestamp(filetime):
"""
Windows returns times as 64-bit unsigned longs that are the number
of hundreds of nanoseconds since Jan 1 1601. This converts it to
a datetime object.
:param filetime:
A FILETIME struct object
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def modulename(cls, depth=1):
"""
get caller's __name__
"""
depth += cls.extra_depth
frame = sys._getframe(depth)
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def _synthesize_multiple_generic(self, helper_function, text_file, output_file_path, quit_after=None, backwards=False):
"""
Synthesize multiple fragments, generic function.
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def convertImages(self):
"""
run this to turn all folder1 TIFs and JPGs into folder2 data.
TIFs will be treated as micrographs and converted to JPG with enhanced
contrast. JPGs will simply be copied over.
"""
# copy over JPGs (and such)
exts=['.jpg','.png']
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def value_counts(self, dropna=True):
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Returns a Series containing counts of unique values.
Parameters
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dropna : boolean, default True
Don't include counts of NaN, even if NaN is in sp_values.
Returns
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def get_last(self):
"""
Get the last migration batch.
:rtype: list
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query = self.table().where('batch', self.get_last_batch_number())
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def refresh(self, token, timeout=None):
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def gradev(data, rate=1.0, data_type="phase", taus=None,
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""" gap resistant overlapping Allan deviation
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def U(self):
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def paga_adjacency(
adata,
adjacency='connectivities',
adjacency_tree='connectivities_tree',
as_heatmap=True,
color_map=None,
show=None,
save=None):
"""Connectivity of paga groups.
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def _get_filehandler_with_formatter(logname, formatter=None):
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def _validate_frequency(cls, index, freq, **kwargs):
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def compute_screen_line_counts(
feed: "Feed", linestring: LineString, dates: List[str], geo_shapes=None
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"""
Find all the Feed trips active on the given dates
that intersect the given Shapely LineString (with WGS84
longitude-latitude coordinates).
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----------
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def pposition(hd, details=False):
"""Parse string into angular position.
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def get_command(self, command):
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def _normalizeImpurityMatrix(matrix):
"""Normalize each row of the matrix that the sum of the row equals 1.
:params matrix: a matrix (2d nested list) containing numbers, each isobaric
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:returns: a matrix containing normalized values
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def select_right(self):
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def _get_variable_value(defined_variables, name):
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def _parse_docstring(fh):
"""Parse the docstrings of a script to find marked dependencies."""
find_fades = re.compile(r'\b(fades)\b:').search
for line in fh:
if line.startswith("'"):
quote = "'"
break
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def segment_curvature(self, t, use_inf=False):
"""returns the curvature of the segment at t.
Notes
-----
If you receive a RuntimeWarning, run command
>>> old = np.seterr(invalid='raise')
This can be undone with
>>> np.seterr(**old)
"""
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def MAFFT(sequences, gap_open=1.53, gap_extension=0.0, retree=2):
'''A Coral wrapper for the MAFFT command line multiple sequence aligner.
:param sequences: A list of sequences to align.
:type sequences: List of homogeneous sequences (all DNA, or all RNA,
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def cmpToDataStore_uri(base, ds1, ds2):
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ret = difflib.get_close_matches(base.uri, [ds1.uri, ds2.uri], 1, cutoff=0.5)
if len(ret) <= 0:
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def get_pydoc_completions(modulename):
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Returns a list of possible values to be passed to pydoc.
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modulename = compat.ensure_not_unicode(modulename)
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def get_condition(self, service_id, version_number, name):
"""Gets a specified condition."""
content = self._fetch("/service/%s/version/%d/condition/%s" % (service_id, version_number, name))
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def Rank(a):
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Rank op.
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def process_connection(connection, my_socket):
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writefd = []
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def take(list_, index_list):
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Selects a subset of a list based on a list of indices.
This is similar to np.take, but pure python.
Args:
list_ (list): some indexable object
index_list (list, slice, int): some indexing object
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list or scalar: subset of the list
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def download_as_file(fn, data=None):
"""
Download given `data` as file `fn`. This service exists to allow frontend
present user with downloadable files.
"""
if data is None:
raise HTTPError(500, "This service require POST `data` parameter.")
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def _EncodeUnknownFields(message):
"""Remap unknown fields in message out of message.source."""
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if source is None:
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def process_from_file(signor_data_file, signor_complexes_file=None):
"""Process Signor interaction data from CSV files.
Parameters
----------
signor_data_file : str
Path to the Signor interaction data file in CSV format.
signor_complexes_file : str
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def lowstate_file_refs(chunks, extras=''):
'''
Create a list of file ref objects to reconcile
'''
refs = {}
for chunk in chunks:
if not isinstance(chunk, dict):
continue
saltenv = 'base'
crefs = []
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def ADDMOD(self, a, b, c):
"""Modulo addition operation"""
try:
result = Operators.ITEBV(256, c == 0, 0, (a + b) % c)
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result = 0
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def _process_dataset(name, directory, num_shards, labels_file):
"""Process a complete data set and save it as a TFRecord.
Args:
name: string, unique identifier specifying the data set.
directory: string, root path to the data set.
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def add_provide(self, provide):
""" Add a provide object if it does not already exist """
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def get_grp2codes(self):
"""Get dict of group name to namedtuples."""
grp2codes = cx.defaultdict(set)
for code, ntd in self.code2nt.items():
grp2codes[ntd.group].add(code)
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def add_bollinger_bands(self,periods=20,boll_std=2,fill=True,column=None,name='',
str='{name}({column},{period})',**kwargs):
"""
Add Bollinger Bands (BOLL) study to QuantFigure.studies
Parameters:
periods : int or list(int)
Number of periods
boll_std : int
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def from_analysis_period(cls, analysis_period, tau_b, tau_d,
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""""Initialize a RevisedClearSkyCondition from an analysis_period"""
_check_analysis_period(analysis_period)
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def init_defaults(self):
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The WARC-Record-ID header is set to a newly generated UUID.
The WARC-Date header is set to the current datetime.
The Content-Type is set based on the WARC-Type header.
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def branches(self):
""" #TODO: description
"""
for branch in self._grid.graph_edges():
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def build_job(name=None, parameters=None):
'''
Initiate a build for the provided job.
:param name: The name of the job is check if it exists.
:param parameters: Parameters to send to the job.
:return: True is successful, otherwise raise an exception.
CLI Example:
.. code-block:: bash
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def sca_intensity(scatterer, h_pol=True):
"""Scattering intensity (phase function) for the current setup.
Args:
scatterer: a Scatterer instance.
h_pol: If True (default), use horizontal polarization.
If False, use vertical polarization.
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def _instantiate_target(self, target_adaptor):
"""Given a TargetAdaptor struct previously parsed from a BUILD file, instantiate a Target."""
target_cls = self._target_types[target_adaptor.type_alias]
try:
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def nnz_obs_names(self):
""" wrapper around pyemu.Pst.nnz_obs_names for listing non-zero
observation names
Returns
-------
nnz_obs_names : list
pyemu.Pst.nnz_obs_names
"""
if self.__pst is not None:
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def _pre_request(self, url, method = u"get", data = None, headers=None, **kwargs):
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hook for manipulating the _pre request data
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def _gpdfit(x):
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Empirical Bayes estimate for the parameters of the generalized Pareto
distribution given the data.
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x : array
sorted 1D data array
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def get_conn(self):
"""Returns a Google Cloud Dataproc service object."""
http_authorized = self._authorize()
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def create_logger(name, formatter=None, handler=None, level=None):
"""
Returns a new logger for the specified name.
"""
logger = logging.getLogger(name)
#: remove existing handlers
logger.handlers = []
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def get_row_by_fsid(self, fs_id):
'''确认在Liststore中是否存在这条任务. 如果存在, 返回TreeModelRow,
否则就返回None'''
for row in self.liststore:
if row[FSID_COL] == fs_id:
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def register_preprocessed_file(self, infile, pmid, extra_annotations):
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This is essentially a mock function to "register" already preprocessed
files and get an IsiPreprocessor object that can be passed to
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def serialize_to_xml(root, block):
"""
Serialize the Peer Instruction XBlock's content to XML.
Args:
block (PeerInstructionXBlock): The peer instruction block to serialize.
root (etree.Element): The XML root node to update.
Returns:
etree.Element
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def tplot_options(option, value):
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def stripe_to_db(self, data):
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def update_limits(self, change_source_lower_limit=None, change_source_upper_limit=None):
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def validate_capacity(capacity):
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def project_status():
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def addai(argname, condition=None):
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Add an "AI" exception in the global exception handler.
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def spawn(func, *args, **kwargs):
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def get_overlapping_ranges(self, collection_link, partition_key_ranges):
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def protocols(self):
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def layout(self):
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def ui_label(self):
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def user(name, id='', user='', priv='', password='', status='active'):
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def get_account_tokens(self, address):
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Get the list of tokens that this address owns
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cur = self.db.cursor()
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def toJSONFilters(actions):
"""Generate a JSON-to-JSON filter from stdin to stdout
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def getCalculationDependencies(self, flat=False, deps=None):
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"... | 32.846154 | 0.002275 |
def _sub16(ins):
''' Pops last 2 words from the stack and subtract them.
Then push the result onto the stack. Top of the stack is
subtracted Top -1
Optimizations:
* If 2nd op is ZERO,
then do NOTHING: A - 0 = A
* If any of the operands is < 4, then
DEC is used
* If a... | [
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"op1"... | 24.117647 | 0.000781 |
def connectivity_map(dset,prefix,x,y,z,radius=2):
'''Will perform connectivity analysis on ``dset`` using seed point ``(x,y,z)`` (in RAI order) with a sphere of radius ``radius``.
Does not perform any preprocessing of ``dset``. This should be already motion corrected, noise-regressed, residualized, etc.'''
... | [
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def reset(self):
"""Resets the iterator to the beginning of the data."""
self.curr_idx = 0
random.shuffle(self.idx)
for buck in self.data:
np.random.shuffle(buck) | [
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def set_position(self, x, y, speed=None):
''' Move chuck to absolute position in um'''
if speed:
self._intf.write('MoveChuckSubsite %1.1f %1.1f R Y %d' % (x, y, speed))
else:
self._intf.write('MoveChuckSubsite %1.1f %1.1f R Y' % (x, y)) | [
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"else"... | 46.5 | 0.010563 |
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