text
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sequence | avg_line_len
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| score
float64 0
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def vcs_rbridge_context_input_rbridge_id(self, **kwargs):
"""Auto Generated Code
"""
config = ET.Element("config")
vcs_rbridge_context = ET.Element("vcs_rbridge_context")
config = vcs_rbridge_context
input = ET.SubElement(vcs_rbridge_context, "input")
rbridge_id = ET.SubElement(input, "rbridge-id")
rbridge_id.text = kwargs.pop('rbridge_id')
callback = kwargs.pop('callback', self._callback)
return callback(config) | [
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def only_owner(func):
"""
Only owner decorator
Restricts access to view ony to profile owner
"""
def decorated(*_, **kwargs):
id = kwargs['id']
if not current_user.is_authenticated:
abort(401)
elif current_user.id != id:
abort(403)
return func(**kwargs)
return decorated | [
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def run_samblaster(job, sam):
"""
Marks reads as PCR duplicates using SAMBLASTER
:param JobFunctionWrappingJob job: passed automatically by Toil
:param str sam: FileStoreID for SAM file
:return: FileStoreID for deduped SAM file
:rtype: str
"""
work_dir = job.fileStore.getLocalTempDir()
job.fileStore.readGlobalFile(sam, os.path.join(work_dir, 'input.sam'))
command = ['/usr/local/bin/samblaster',
'-i', '/data/input.sam',
'-o', '/data/output.sam',
'--ignoreUnmated']
start_time = time.time()
dockerCall(job=job, workDir=work_dir,
parameters=command,
tool='quay.io/biocontainers/samblaster:0.1.24--0')
end_time = time.time()
_log_runtime(job, start_time, end_time, "SAMBLASTER")
return job.fileStore.writeGlobalFile(os.path.join(work_dir, 'output.sam')) | [
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def _init_multicast_socket(self):
"""
Init multicast socket
:rtype: None
"""
self.debug("()")
# Create a UDP socket
self._multicast_socket = socket.socket(
socket.AF_INET,
socket.SOCK_DGRAM
)
# Allow reuse of addresses
self._multicast_socket.setsockopt(
socket.SOL_SOCKET,
socket.SO_REUSEADDR,
1
)
# Set multicast interface to local_ip
self._multicast_socket.setsockopt(
socket.IPPROTO_IP,
socket.IP_MULTICAST_IF,
socket.inet_aton(self._multicast_ip)
)
# Set multicast time-to-live
# Should keep our multicast packets from escaping the local network
self._multicast_socket.setsockopt(
socket.IPPROTO_IP,
socket.IP_MULTICAST_TTL,
self._multicast_ttl
)
self._add_membership_multicast_socket()
# Bind socket
if platform.system().lower() == "darwin":
self._multicast_socket.bind(("0.0.0.0", self._multicast_bind_port))
else:
self._multicast_socket.bind(
(self._multicast_ip, self._multicast_bind_port)
)
self._listening.append(self._multicast_socket) | [
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def generic_visit(self, node):
"""Called if no explicit visitor function exists for a node."""
for _, value in ast.iter_fields(node):
if isinstance(value, list):
self._handle_ast_list(value)
for item in value:
if isinstance(item, ast.AST):
self.visit(item)
elif isinstance(value, ast.AST):
self.visit(value) | [
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def parse_theme(self, xml):
""" Parses a theme from XML returned by Kuler.
Gets the theme's id, label and swatches.
All of the swatches are converted to RGB.
If we have a full description for a theme id in cache,
parse that to get tags associated with the theme.
"""
kt = KulerTheme()
kt.author = xml.getElementsByTagName("author")[0]
kt.author = kt.author.childNodes[1].childNodes[0].nodeValue
kt.id = int(self.parse_tag(xml, "id"))
kt.label = self.parse_tag(xml, "label")
mode = self.parse_tag(xml, "mode")
for swatch in xml.getElementsByTagName("swatch"):
c1 = float(self.parse_tag(swatch, "c1"))
c2 = float(self.parse_tag(swatch, "c2"))
c3 = float(self.parse_tag(swatch, "c3"))
c4 = float(self.parse_tag(swatch, "c4"))
if mode == "rgb":
kt.append((c1,c2,c3))
if mode == "cmyk":
kt.append(cmyk_to_rgb(c1,c2,c3,c4))
if mode == "hsv":
kt.append(colorsys.hsv_to_rgb(c1,c2,c3))
if mode == "hex":
kt.append(hex_to_rgb(c1))
if mode == "lab":
kt.append(lab_to_rgb(c1,c2,c3))
# If we have the full theme in cache,
# parse tags from it.
if self._cache.exists(self.id_string + str(kt.id)):
xml = self._cache.read(self.id_string + str(kt.id))
xml = minidom.parseString(xml)
for tags in xml.getElementsByTagName("tag"):
tags = self.parse_tag(tags, "label")
tags = tags.split(" ")
kt.tags.extend(tags)
return kt | [
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def _expand(self):
"""
Expand the free pool, if possible.
If out of capacity w.r.t. the defined ID value range, ValueError is
raised.
"""
assert not self._free # free pool is empty
expand_end = self._expand_start + self._expand_len
if expand_end > self._range_end:
# This happens if the size of the value range is not a multiple
# of the expansion chunk size.
expand_end = self._range_end
if self._expand_start == expand_end:
raise ValueError("Out of capacity in ID pool")
self._free = set(range(self._expand_start, expand_end))
self._expand_start = expand_end | [
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def item(self, infohash, prefetch=None, cache=False):
""" Fetch a single item by its info hash.
"""
return next(self.items(infohash, prefetch, cache)) | [
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def html_serialize(self, attributes, max_length=None):
"""Returns concatenated HTML code with SPAN tag.
Args:
attributes (dict): A map of name-value pairs for attributes of output
SPAN tags.
max_length (:obj:`int`, optional): Maximum length of span enclosed chunk.
Returns:
The organized HTML code. (str)
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doc = ET.Element('span')
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ele.text = chunk.word
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doc.getchildren()[-1].tail = chunk.word
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doc.getchildren()[-1].tail += chunk.word
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if doc.text is None:
doc.text = chunk.word
else:
doc.text += chunk.word
result = ET.tostring(doc, encoding='utf-8').decode('utf-8')
result = html5lib.serialize(
html5lib.parseFragment(result), sanitize=True,
quote_attr_values='always')
return result | [
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def SingleModeCombine(pupils,modeDiameter=None):
"""
Return the instantaneous coherent fluxes and photometric fluxes for a
multiway single-mode fibre combiner
"""
if modeDiameter is None:
modeDiameter=0.9*pupils.shape[-1]
amplitudes=FibreCouple(pupils,modeDiameter)
cc=np.conj(amplitudes)
fluxes=(amplitudes*cc).real
coherentFluxes=[amplitudes[i]*cc[j]
for i in range(1,len(amplitudes))
for j in range(i)]
return fluxes,coherentFluxes | [
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def dot(self, vec):
"""Dot product with another vector"""
if not isinstance(vec, self.__class__):
raise TypeError('Dot product operand must be a VectorArray')
if self.nV != 1 and vec.nV != 1 and self.nV != vec.nV:
raise ValueError('Dot product operands must have the same '
'number of elements.')
return np.sum((getattr(self, d)*getattr(vec, d) for d in self.dims), 1) | [
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def crt_prf_ftr_tc(aryMdlRsp, aryTmpExpInf, varNumVol, varTr, varTmpOvsmpl,
switchHrfSet, tplPngSize, varPar, dctPrm=None,
lgcPrint=True):
"""Create all spatial x feature prf time courses.
Parameters
----------
aryMdlRsp : 2d numpy array, shape [n_x_pos * n_y_pos * n_sd, n_cond]
Responses of 2D Gauss models to spatial conditions
aryTmpExpInf: 2d numpy array, shape [unknown, 4]
Temporal information about conditions
varNumVol : float, positive
Number of volumes of the (fMRI) data.
varTr : float, positive
Time to repeat (TR) of the (fMRI) experiment.
varTmpOvsmpl : int, positive
Factor by which the data hs been temporally upsampled.
switchHrfSet : int, (1, 2, 3)
Switch to determine which hrf basis functions are used
tplPngSize : tuple
Pixel dimensions of the visual space (width, height).
varPar : int, positive
Description of input 1.
dctPrm : dictionary, default None
Dictionary with customized hrf parameters. If this is None, default
hrf parameters will be used.
lgcPrint: boolean, default True
Should print messages be sent to user?
Returns
-------
aryNrlTcConv : 3d numpy array,
shape [nr of models, nr of unique feautures, varNumVol]
Prf time course models
"""
# Identify number of unique features
vecFeat = np.unique(aryTmpExpInf[:, 3])
vecFeat = vecFeat[np.nonzero(vecFeat)[0]]
# Preallocate the output array
aryPrfTc = np.zeros((aryMdlRsp.shape[0], 0, varNumVol),
dtype=np.float32)
# Loop over unique features
for indFtr, ftr in enumerate(vecFeat):
if lgcPrint:
print('---------Create prf time course model for feature ' +
str(ftr))
# Derive sptial conditions, onsets and durations for this specific
# feature
aryTmpCnd = aryTmpExpInf[aryTmpExpInf[:, 3] == ftr, 0]
aryTmpOns = aryTmpExpInf[aryTmpExpInf[:, 3] == ftr, 1]
aryTmpDrt = aryTmpExpInf[aryTmpExpInf[:, 3] == ftr, 2]
# Create temporally upsampled neural time courses.
aryNrlTcTmp = crt_nrl_tc(aryMdlRsp, aryTmpCnd, aryTmpOns, aryTmpDrt,
varTr, varNumVol, varTmpOvsmpl,
lgcPrint=lgcPrint)
# Convolve with hrf to create model pRF time courses.
aryPrfTcTmp = crt_prf_tc(aryNrlTcTmp, varNumVol, varTr, varTmpOvsmpl,
switchHrfSet, tplPngSize, varPar,
dctPrm=dctPrm, lgcPrint=lgcPrint)
# Add temporal time course to time course that will be returned
aryPrfTc = np.concatenate((aryPrfTc, aryPrfTcTmp), axis=1)
return aryPrfTc | [
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def _get_format_name_loader_mapping(self):
"""
:return: Mappings of format-name and loader class.
:rtype: dict
"""
loader_table = self._get_common_loader_mapping()
loader_table.update(
{
"excel": ExcelTableFileLoader,
"json_lines": JsonLinesTableTextLoader,
"markdown": MarkdownTableTextLoader,
"mediawiki": MediaWikiTableTextLoader,
"ssv": CsvTableFileLoader,
}
)
return loader_table | [
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async def jsk_vc_resume(self, ctx: commands.Context):
"""
Resumes a running audio source, if there is one.
"""
voice = ctx.guild.voice_client
if not voice.is_paused():
return await ctx.send("Audio is not paused.")
voice.resume()
await ctx.send(f"Resumed audio in {voice.channel.name}.") | [
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def _create_decoding_layers(self):
"""Create the decoding layers for reconstruction finetuning.
:return: output of the final encoding layer.
"""
next_decode = self.encode
for l, layer in reversed(list(enumerate(self.layers))):
with tf.name_scope("decode-{}".format(l)):
# Create decoding variables
if self.tied_weights:
dec_w = tf.transpose(self.encoding_w_[l])
else:
dec_w = tf.Variable(tf.transpose(
self.encoding_w_[l].initialized_value()))
dec_b = tf.Variable(tf.constant(
0.1, shape=[dec_w.get_shape().dims[1].value]))
self.decoding_w.append(dec_w)
self.decoding_b.append(dec_b)
y_act = tf.add(
tf.matmul(next_decode, dec_w),
dec_b
)
if self.finetune_dec_act_func[l] is not None:
layer_y = self.finetune_dec_act_func[l](y_act)
else:
layer_y = None
# the input to the next layer is the output of this layer
next_decode = tf.nn.dropout(layer_y, self.keep_prob)
self.layer_nodes.append(next_decode)
self.reconstruction = next_decode | [
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def get_port_from_port_server(portserver_address, pid=None):
"""Request a free a port from a system-wide portserver.
This follows a very simple portserver protocol:
The request consists of our pid (in ASCII) followed by a newline.
The response is a port number and a newline, 0 on failure.
This function is an implementation detail of pick_unused_port().
It should not normally be called by code outside of this module.
Args:
portserver_address: The address (path) of a unix domain socket
with which to connect to the portserver. A leading '@'
character indicates an address in the "abstract namespace."
On systems without socket.AF_UNIX, this is an AF_INET address.
pid: The PID to tell the portserver to associate the reservation with.
If None, the current process's PID is used.
Returns:
The port number on success or None on failure.
"""
if not portserver_address:
return None
# An AF_UNIX address may start with a zero byte, in which case it is in the
# "abstract namespace", and doesn't have any filesystem representation.
# See 'man 7 unix' for details.
# The convention is to write '@' in the address to represent this zero byte.
if portserver_address[0] == '@':
portserver_address = '\0' + portserver_address[1:]
if pid is None:
pid = os.getpid()
try:
# Create socket.
if hasattr(socket, 'AF_UNIX'):
sock = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM)
else:
# fallback to AF_INET if this is not unix
sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
try:
# Connect to portserver.
sock.connect(portserver_address)
# Write request.
sock.sendall(('%d\n' % pid).encode('ascii'))
# Read response.
# 1K should be ample buffer space.
buf = sock.recv(1024)
finally:
sock.close()
except socket.error as e:
print('Socket error when connecting to portserver:', e,
file=sys.stderr)
return None
try:
port = int(buf.split(b'\n')[0])
except ValueError:
print('Portserver failed to find a port.', file=sys.stderr)
return None
_owned_ports.add(port)
return port | [
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def format_currency(number, currency, format=None,
locale=LC_NUMERIC, currency_digits=True,
format_type='standard', decimal_quantization=True):
"""Return formatted currency value.
>>> format_currency(1099.98, 'USD', locale='en_US')
u'$1,099.98'
>>> format_currency(1099.98, 'USD', locale='es_CO')
u'US$\\xa01.099,98'
>>> format_currency(1099.98, 'EUR', locale='de_DE')
u'1.099,98\\xa0\\u20ac'
The format can also be specified explicitly. The currency is
placed with the '¤' sign. As the sign gets repeated the format
expands (¤ being the symbol, ¤¤ is the currency abbreviation and
¤¤¤ is the full name of the currency):
>>> format_currency(1099.98, 'EUR', u'\xa4\xa4 #,##0.00', locale='en_US')
u'EUR 1,099.98'
>>> format_currency(1099.98, 'EUR', u'#,##0.00 \xa4\xa4\xa4',
... locale='en_US')
u'1,099.98 euros'
Currencies usually have a specific number of decimal digits. This function
favours that information over the given format:
>>> format_currency(1099.98, 'JPY', locale='en_US')
u'\\xa51,100'
>>> format_currency(1099.98, 'COP', u'#,##0.00', locale='es_ES')
u'1.100'
However, the number of decimal digits can be overriden from the currency
information, by setting the last parameter to ``False``:
>>> format_currency(1099.98, 'JPY', locale='en_US', currency_digits=False)
u'\\xa51,099.98'
>>> format_currency(1099.98, 'COP', u'#,##0.00', locale='es_ES',
... currency_digits=False)
u'1.099,98'
If a format is not specified the type of currency format to use
from the locale can be specified:
>>> format_currency(1099.98, 'EUR', locale='en_US', format_type='standard')
u'\\u20ac1,099.98'
When the given currency format type is not available, an exception is
raised:
>>> format_currency('1099.98', 'EUR', locale='root', format_type='unknown')
Traceback (most recent call last):
...
UnknownCurrencyFormatError: "'unknown' is not a known currency format type"
By default the locale is allowed to truncate and round a high-precision
number by forcing its format pattern onto the decimal part. You can bypass
this behavior with the `decimal_quantization` parameter:
>>> format_currency(1099.9876, 'USD', locale='en_US')
u'$1,099.99'
>>> format_currency(1099.9876, 'USD', locale='en_US',
... decimal_quantization=False)
u'$1,099.9876'
:param number: the number to format
:param currency: the currency code
:param format: the format string to use
:param locale: the `Locale` object or locale identifier
:param currency_digits: use the currency's natural number of decimal digits
:param format_type: the currency format type to use
:param decimal_quantization: Truncate and round high-precision numbers to
the format pattern. Defaults to `True`.
"""
locale = Locale.parse(locale)
if format:
pattern = parse_pattern(format)
else:
try:
p = locale.currency_formats[format_type]
pattern = NumberPattern(
p.pattern, p.prefix, p.suffix, p.grouping, p.int_prec,
p.frac_prec, p.exp_prec, p.exp_plus)
except KeyError:
raise UnknownCurrencyFormatError(
"%r is not a known currency format type" % format_type)
return pattern.apply(
number, locale, currency=currency, currency_digits=currency_digits,
decimal_quantization=decimal_quantization) | [
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def data_url_scheme(self):
"""Get svg in Data URL Scheme format.
"""
# TODO: move to web.app or make it function
# remove #svg from dataframe
encoded = base64.b64encode(self.contents().encode())
return "data:image/svg+xml;base64," + encoded.decode() | [
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def name(self, name):
"""Set the member name.
Note that a member name cannot appear in other enums, or generally
anywhere else in the IDB.
"""
success = idaapi.set_enum_member_name(self.cid, name)
if not success:
raise exceptions.CantRenameEnumMember(
"Failed renaming {!r} to {!r}. Does the name exist somewhere else?".format(self.name, name)) | [
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def boll(self, n, dev, array=False):
"""布林通道"""
mid = self.sma(n, array)
std = self.std(n, array)
up = mid + std * dev
down = mid - std * dev
return up, down | [
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def create_proforma_invoice(sender, instance, created, **kwargs):
"""
For every Order if there are defined billing_data creates invoice proforma,
which is an order confirmation document
"""
if created:
Invoice.create(instance, Invoice.INVOICE_TYPES['PROFORMA']) | [
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def _check_cron_env(user,
name,
value=None):
'''
Return the environment changes
'''
if value is None:
value = "" # Matching value set in salt.modules.cron._render_tab
lst = __salt__['cron.list_tab'](user)
for env in lst['env']:
if name == env['name']:
if value != env['value']:
return 'update'
return 'present'
return 'absent' | [
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def p_literal_list(self, p):
"""literal_list : literal_list LITERAL
| LITERAL"""
if len(p) == 3:
p[0] = p[1] + [p[2][1:-1]]
else:
p[0] = [p[1][1:-1]] | [
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def get(self, agentml, user=None, key=None):
"""
Evaluate and return the current active topic
:param user: The active user object
:type user: agentml.User or None
:param agentml: The active AgentML instance
:type agentml: AgentML
:param key: The user id (defaults to the current user if None)
:type key: str
:return: Active topic of the user
:rtype : str or None
"""
user = agentml.get_user(key) if key else user
if not user:
return
return user.id | [
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def wrap_io_os_err(e):
'''Formats IO and OS error messages for wrapping in FSQExceptions'''
msg = ''
if e.strerror:
msg = e.strerror
if e.message:
msg = ' '.join([e.message, msg])
if e.filename:
msg = ': '.join([msg, e.filename])
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def list_cameras():
""" List all attached USB cameras that are supported by libgphoto2.
:return: All recognized cameras
:rtype: list of :py:class:`Camera`
"""
ctx = lib.gp_context_new()
camlist_p = new_gp_object("CameraList")
port_list_p = new_gp_object("GPPortInfoList")
lib.gp_port_info_list_load(port_list_p)
abilities_list_p = new_gp_object("CameraAbilitiesList")
lib.gp_abilities_list_load(abilities_list_p, ctx)
lib.gp_abilities_list_detect(abilities_list_p, port_list_p,
camlist_p, ctx)
out = []
for idx in range(lib.gp_list_count(camlist_p)):
name = get_string(lib.gp_list_get_name, camlist_p, idx)
value = get_string(lib.gp_list_get_value, camlist_p, idx)
# Skip iteration if no matches
matches = re.match(r"usb:(\d+),(\d+)", value)
if not matches:
continue
bus_no, device_no = (int(x) for x in matches.groups())
abilities = ffi.new("CameraAbilities*")
ability_idx = lib.gp_abilities_list_lookup_model(
abilities_list_p, name.encode())
lib.gp_abilities_list_get_abilities(abilities_list_p, ability_idx,
abilities)
if abilities.device_type == lib.GP_DEVICE_STILL_CAMERA:
out.append(Camera(bus_no, device_no, lazy=True,
_abilities=abilities))
lib.gp_list_free(camlist_p)
lib.gp_port_info_list_free(port_list_p)
lib.gp_abilities_list_free(abilities_list_p)
return out | [
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def hairball_files(self, paths, extensions):
"""Yield filepath to files with the proper extension within paths."""
def add_file(filename):
return os.path.splitext(filename)[1] in extensions
while paths:
arg_path = paths.pop(0)
if os.path.isdir(arg_path):
found = False
for path, dirs, files in os.walk(arg_path):
dirs.sort() # Traverse in sorted order
for filename in sorted(files):
if add_file(filename):
yield os.path.join(path, filename)
found = True
if not found:
if not self.options.quiet:
print('No files found in {}'.format(arg_path))
elif add_file(arg_path):
yield arg_path
elif not self.options.quiet:
print('Invalid file {}'.format(arg_path))
print('Did you forget to load a Kurt plugin (-k)?') | [
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")"
] | 44.695652 | 12.73913 |
def build(self, search, raw_query):
"""Build query.
:param search: Search query instance
:param raw_query: Raw query arguments dictionary
"""
unmatched_items = {}
for expression, value in raw_query.items():
# Parse query expression into tokens.
tokens = expression.split(TOKEN_SEPARATOR)
field = tokens[0]
tail = tokens[1:]
if field not in self.fields:
unmatched_items[expression] = value
continue
# Map field alias to final field.
field = self.fields_map.get(field, field)
# Parse lookup expression. Currently only no token or a single token is allowed.
if tail:
if len(tail) > 1:
raise NotImplementedError("Nested lookup expressions are not supported")
lookup = self.get_lookup(tail[0])
search = lookup.apply(search, field, value)
else:
# Default lookup.
custom_filter = getattr(self.custom_filter_object, 'custom_filter_{}'.format(field), None)
if custom_filter is not None:
search = custom_filter(value, search)
elif isinstance(value, list):
# Default is 'should' between matches. If you need anything else,
# a custom filter for this field should be implemented.
filters = [Q('match', **{field: item}) for item in value]
search = search.query('bool', should=filters)
else:
search = search.query('match', **{field: {'query': value, 'operator': 'and'}})
return (search, unmatched_items) | [
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def subscribe(self, topic, callback, ordered=True):
"""Subscribe to future messages in the given topic
The contents of topic should be in the format created by self.publish with a
sequence number of message type encoded as a json string.
Wildcard topics containing + and # are allowed and
Args:
topic (string): The MQTT topic to subscribe to
callback (callable): The callback to call when a new mesage is received
The signature of callback should be callback(sequence, topic, type, message)
ordered (bool): Whether messages on this topic have a sequence number that must
be checked and queued to ensure that packets are received in order
"""
if '+' in topic or '#' in topic:
regex = re.compile(topic.replace('+', '[^/]+').replace('#', '.*'))
self.wildcard_queues.append((topic, regex, callback, ordered))
else:
self.queues[topic] = PacketQueue(0, callback, ordered)
try:
self.client.subscribe(topic, 1, self._on_receive)
except operationError as exc:
raise InternalError("Could not subscribe to topic", topic=topic, message=exc.message) | [
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def _setup_resources():
"""Attempt to increase resource limits up to hard limits.
This allows us to avoid out of file handle limits where we can
move beyond the soft limit up to the hard limit.
"""
target_procs = 10240
cur_proc, max_proc = resource.getrlimit(resource.RLIMIT_NPROC)
target_proc = min(max_proc, target_procs) if max_proc > 0 else target_procs
resource.setrlimit(resource.RLIMIT_NPROC, (max(cur_proc, target_proc), max_proc))
cur_hdls, max_hdls = resource.getrlimit(resource.RLIMIT_NOFILE)
target_hdls = min(max_hdls, target_procs) if max_hdls > 0 else target_procs
resource.setrlimit(resource.RLIMIT_NOFILE, (max(cur_hdls, target_hdls), max_hdls)) | [
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def matches(self, desc):
"""Determines if a given label descriptor matches this enum instance
Args:
desc (:class:`endpoints_management.gen.servicemanagement_v1_messages.LabelDescriptor`):
the instance to test
Return:
`True` if desc is supported, otherwise `False`
"""
desc_value_type = desc.valueType or ValueType.STRING # default not parsed
return (self.label_name == desc.key and
self.value_type == desc_value_type) | [
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def regenerate_models(self, propnames=None, exclude=[], deep=False):
r"""
Re-runs the specified model or models.
Parameters
----------
propnames : string or list of strings
The list of property names to be regenerated. If None are given
then ALL models are re-run (except for those whose ``regen_mode``
is 'constant').
exclude : list of strings
Since the default behavior is to run ALL models, this can be used
to exclude specific models. It may be more convenient to supply
as list of 2 models to exclude than to specify 8 models to include.
deep : boolean
Specifies whether or not to regenerate models on all associated
objects. For instance, if ``True``, then all Physics models will
be regenerated when method is called on the corresponding Phase.
The default is ``False``. The method does not work in reverse,
so regenerating models on a Physics will not update a Phase.
"""
# If empty list of propnames was given, do nothing and return
if type(propnames) is list and len(propnames) == 0:
return
if type(propnames) is str: # Convert string to list if necessary
propnames = [propnames]
if propnames is None: # If no props given, then regenerate them all
propnames = self.models.dependency_list()
# If some props are to be excluded, remove them from list
if len(exclude) > 0:
propnames = [i for i in propnames if i not in exclude]
# Re-order given propnames according to dependency tree
self_models = self.models.dependency_list()
propnames = [i for i in self_models if i in propnames]
if deep:
other_models = None # Will trigger regen of ALL models
else:
# Make list of given propnames that are not in self
other_models = list(set(propnames).difference(set(self_models)))
# The following has some redundant lines, but is easier to understand
if self._isa('phase'):
# Start be regenerating models on self
for item in propnames:
self._regen(item)
# Then regen models on associated objects, if any in other_models
for phys in self.project.find_physics(phase=self):
phys.regenerate_models(propnames=other_models, deep=False)
elif self._isa('network'): # Repeat for other object types
for item in propnames:
self._regen(item)
for geom in self.project.geometries().values():
geom.regenerate_models(propnames=other_models, deep=False)
else:
for item in propnames:
self._regen(item) | [
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def _solve(self, x0, A, l, u, xmin, xmax):
""" Solves using Python Interior Point Solver (PIPS).
"""
s = pips(self._costfcn, x0, A, l, u, xmin, xmax,
self._consfcn, self._hessfcn, self.opt)
return s | [
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def write_config_file(self, f, comments):
"""This method write a sample file, with attributes, descriptions,
sample values, required flags, using the configuration object
properties.
"""
if comments:
f.write("#####################################\n")
f.write("# Section : ")
f.write("#".join(self.get_representation()) + "\n")
f.write("#####################################\n")
f.write("[" + self._name + "]\n")
if self._desc and comments:
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for i in self._desc.split('\n'):
f.write("# ")
f.write(i)
f.write("\n")
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def monitor_experiment(args):
'''monitor the experiment'''
if args.time <= 0:
print_error('please input a positive integer as time interval, the unit is second.')
exit(1)
while True:
try:
os.system('clear')
update_experiment()
show_experiment_info()
time.sleep(args.time)
except KeyboardInterrupt:
exit(0)
except Exception as exception:
print_error(exception)
exit(1) | [
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def _muck_w_date(record):
"""muck with the date because EPW starts counting from 1 and goes to 24."""
# minute 60 is actually minute 0?
temp_d = datetime.datetime(int(record['Year']), int(record['Month']),
int(record['Day']), int(record['Hour']) % 24,
int(record['Minute']) % 60)
d_off = int(record['Hour'])//24 # hour 24 is actually hour 0
if d_off > 0:
temp_d += datetime.timedelta(days=d_off)
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def _unpack_body(self):
"""Unpack `body` replace it by the result."""
obj = self._get_body_instance()
obj.unpack(self.body.value)
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def console_print_rect_ex(
con: tcod.console.Console,
x: int,
y: int,
w: int,
h: int,
flag: int,
alignment: int,
fmt: str,
) -> int:
"""Print a string constrained to a rectangle with blend and alignment.
Returns:
int: The number of lines of text once word-wrapped.
.. deprecated:: 8.5
Use :any:`Console.print_rect` instead.
"""
return int(
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def setupTable_VORG(self):
"""
Make the VORG table.
**This should not be called externally.** Subclasses
may override or supplement this method to handle the
table creation in a different way if desired.
"""
if "VORG" not in self.tables:
return
self.otf["VORG"] = vorg = newTable("VORG")
vorg.majorVersion = 1
vorg.minorVersion = 0
vorg.VOriginRecords = {}
# Find the most frequent verticalOrigin
vorg_count = Counter(_getVerticalOrigin(self.otf, glyph)
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def validate_rmq_cluster_running_nodes(self, sentry_units):
"""Check that all rmq unit hostnames are represented in the
cluster_status output of all units.
:param host_names: dict of juju unit names to host names
:param units: list of sentry unit pointers (all rmq units)
:returns: None if successful, otherwise return error message
"""
host_names = self.get_unit_hostnames(sentry_units)
errors = []
# Query every unit for cluster_status running nodes
for query_unit in sentry_units:
query_unit_name = query_unit.info['unit_name']
running_nodes = self.get_rmq_cluster_running_nodes(query_unit)
# Confirm that every unit is represented in the queried unit's
# cluster_status running nodes output.
for validate_unit in sentry_units:
val_host_name = host_names[validate_unit.info['unit_name']]
val_node_name = 'rabbit@{}'.format(val_host_name)
if val_node_name not in running_nodes:
errors.append('Cluster member check failed on {}: {} not '
'in {}\n'.format(query_unit_name,
val_node_name,
running_nodes))
if errors:
return ''.join(errors) | [
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] | 47.482759 | 22.034483 |
def teardown(self):
'''
cleanup the monitor data and
'''
self.monitor_thread.stop()
self.monitor_thread = None
super(BaseMonitor, self).teardown() | [
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def main():
"""Entrypoint for ``lander`` executable."""
args = parse_args()
config_logger(args)
logger = structlog.get_logger(__name__)
if args.show_version:
# only print the version
print_version()
sys.exit(0)
version = pkg_resources.get_distribution('lander').version
logger.info('Lander version {0}'.format(version))
config = Configuration(args=args)
# disable any build confirmed to be a PR with Travis
if config['is_travis_pull_request']:
logger.info('Skipping build from PR.')
sys.exit(0)
lander = Lander(config)
lander.build_site()
logger.info('Build complete')
if config['upload']:
lander.upload_site()
logger.info('Upload complete')
logger.info('Lander complete') | [
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def link_marked_atoms(self, atoms):
"""
Take a list of marked "interesting" atoms (heteroatoms, special carbons)
and attempt to connect them, returning a list of disjoint groups of
special atoms (and their connected hydrogens).
:param atoms: set of marked "interesting" atoms, presumably identified
using other functions in this class.
:return: list of sets of ints, representing groups of connected atoms
"""
# We will add hydrogens to functional groups
hydrogens = {n for n in self.molgraph.graph.nodes if
str(self.species[n]) == "H"}
# Graph representation of only marked atoms
subgraph = self.molgraph.graph.subgraph(list(atoms)).to_undirected()
func_grps_no_h = [x for x in nx.connected_components(subgraph)]
func_grps = []
for func_grp in func_grps_no_h:
grp_hs = set()
for node in func_grp:
neighbors = self.molgraph.graph[node]
for neighbor in neighbors.keys():
# Add all associated hydrogens into the functional group
if neighbor in hydrogens:
grp_hs.add(neighbor)
func_grp = func_grp.union(grp_hs)
func_grps.append(func_grp)
return func_grps | [
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def get(url, **kwargs):
"""
Wrapper for `request.get` function to set params.
"""
headers = kwargs.get('headers', {})
headers['User-Agent'] = config.USER_AGENT # overwrite
kwargs['headers'] = headers
timeout = kwargs.get('timeout', config.TIMEOUT)
kwargs['timeout'] = timeout
kwargs['verify'] = False # no SSLError
logger.debug("Getting: %s", url)
return requests.get(url, **kwargs) | [
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def insert(self, index: int, obj: Any) -> None:
""" Inserts an item to the list as long as it is not None """
if obj is not None:
super().insert(index, obj) | [
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def perform_initialization(self):
'''Initialize the harvesting for a given job'''
log.debug('Initializing backend')
factory = HarvestJob if self.dryrun else HarvestJob.objects.create
self.job = factory(status='initializing',
started=datetime.now(),
source=self.source)
before_harvest_job.send(self)
try:
self.initialize()
self.job.status = 'initialized'
if not self.dryrun:
self.job.save()
except HarvestValidationError as e:
log.info('Initialization failed for "%s" (%s)',
safe_unicode(self.source.name), self.source.backend)
error = HarvestError(message=safe_unicode(e))
self.job.errors.append(error)
self.job.status = 'failed'
self.end()
return
except Exception as e:
self.job.status = 'failed'
error = HarvestError(message=safe_unicode(e))
self.job.errors.append(error)
self.end()
msg = 'Initialization failed for "{0.name}" ({0.backend})'
log.exception(msg.format(self.source))
return
if self.max_items:
self.job.items = self.job.items[:self.max_items]
if self.job.items:
log.debug('Queued %s items', len(self.job.items))
return len(self.job.items) | [
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def simplify(self, options=None):
"""
returns a dict describing a simple snapshot of this change, and
its children if any.
"""
simple = {
"class": type(self).__name__,
"is_change": self.is_change(),
"description": self.get_description(),
"label": self.label,
}
if options:
simple["is_ignored"] = self.is_ignored(options)
if isinstance(self, Addition):
simple["is_addition"] = True
if isinstance(self, Removal):
simple["is_removal"] = True
if self.entry:
simple["entry"] = self.entry
return simple | [
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def index_complement(index_list, len_=None):
"""
Returns the other indicies in a list of length ``len_``
"""
mask1 = index_to_boolmask(index_list, len_)
mask2 = not_list(mask1)
index_list_bar = list_where(mask2)
return index_list_bar | [
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def list_connections(self, limit=500, offset=0):
"""List Points to which this Things is subscribed.
I.e. list all the Points this Thing is following and controls it's attached to
Returns subscription list e.g.
#!python
{
"<Subscription GUID 1>": {
"id": "<Control GUID>",
"entityId": "<Control's Thing GUID>",
"type": 3 # R_CONTROL from IoticAgent.Core.Const
},
"<Subscription GUID 2>": {
"id": "<Feed GUID>",
"entityId": "<Feed's Thing GUID>",
"type": 2 # R_FEED from IoticAgent.Core.Const
}
Raises [IOTException](./Exceptions.m.html#IoticAgent.IOT.Exceptions.IOTException)
containing the error if the infrastructure detects a problem
Raises [LinkException](../Core/AmqpLink.m.html#IoticAgent.Core.AmqpLink.LinkException)
if there is a communications problem between you and the infrastructure
Note: For Things following a Point see
[list_followers](./Point.m.html#IoticAgent.IOT.Point.Point.list_followers)
"""
evt = self._client._request_sub_list(self.__lid, limit=limit, offset=offset)
self._client._wait_and_except_if_failed(evt)
return evt.payload['subs'] | [
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def is_python_script(filename):
'''Checks a file to see if it's a python script of some sort.
'''
if filename.lower().endswith('.py'):
return True
if not os.path.isfile(filename):
return False
try:
with open(filename, 'rb') as fp:
if fp.read(2) != b'#!':
return False
return re.match(r'.*python', str_(fp.readline()))
except IOError:
pass
return False | [
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def calcMzFromMass(mass, charge):
"""Calculate the mz value of a peptide from its mass and charge.
:param mass: float, exact non protonated mass
:param charge: int, charge state
:returns: mass to charge ratio of the specified charge state
"""
mz = (mass + (maspy.constants.atomicMassProton * charge)) / charge
return mz | [
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def is_extension_type(arr):
"""
Check whether an array-like is of a pandas extension class instance.
Extension classes include categoricals, pandas sparse objects (i.e.
classes represented within the pandas library and not ones external
to it like scipy sparse matrices), and datetime-like arrays.
Parameters
----------
arr : array-like
The array-like to check.
Returns
-------
boolean
Whether or not the array-like is of a pandas extension class instance.
Examples
--------
>>> is_extension_type([1, 2, 3])
False
>>> is_extension_type(np.array([1, 2, 3]))
False
>>>
>>> cat = pd.Categorical([1, 2, 3])
>>>
>>> is_extension_type(cat)
True
>>> is_extension_type(pd.Series(cat))
True
>>> is_extension_type(pd.SparseArray([1, 2, 3]))
True
>>> is_extension_type(pd.SparseSeries([1, 2, 3]))
True
>>>
>>> from scipy.sparse import bsr_matrix
>>> is_extension_type(bsr_matrix([1, 2, 3]))
False
>>> is_extension_type(pd.DatetimeIndex([1, 2, 3]))
False
>>> is_extension_type(pd.DatetimeIndex([1, 2, 3], tz="US/Eastern"))
True
>>>
>>> dtype = DatetimeTZDtype("ns", tz="US/Eastern")
>>> s = pd.Series([], dtype=dtype)
>>> is_extension_type(s)
True
"""
if is_categorical(arr):
return True
elif is_sparse(arr):
return True
elif is_datetime64tz_dtype(arr):
return True
return False | [
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def delete_session(sid_s):
"""Delete entries in the data- and kvsessionstore with the given sid_s.
On a successful deletion, the flask-kvsession store returns 1 while the
sqlalchemy datastore returns None.
:param sid_s: The session ID.
:returns: ``1`` if deletion was successful.
"""
# Remove entries from sessionstore
_sessionstore.delete(sid_s)
# Find and remove the corresponding SessionActivity entry
with db.session.begin_nested():
SessionActivity.query.filter_by(sid_s=sid_s).delete()
return 1 | [
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def get_fieldset_index(fieldsets, index_or_name):
"""
Return the index of a fieldset in the ``fieldsets`` list.
Args:
fieldsets (list): The original ``fieldsets`` list.
index_or_name (int or str): The value of the reference element, or directly its numeric index.
Returns:
(int) The index of the fieldset in the ``fieldsets`` list.
"""
if isinstance(index_or_name, six.integer_types):
return index_or_name
for key, value in enumerate(fieldsets):
if value[0] == index_or_name:
return key
raise KeyError("Key not found: '{}'.".format(index_or_name)) | [
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def _ProcessImage(self, tag, wall_time, step, image):
"""Processes an image by adding it to accumulated state."""
event = ImageEvent(wall_time=wall_time,
step=step,
encoded_image_string=image.encoded_image_string,
width=image.width,
height=image.height)
self.images.AddItem(tag, event) | [
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def _read_para_echo_request_unsigned(self, code, cbit, clen, *, desc, length, version):
"""Read HIP ECHO_REQUEST_UNSIGNED parameter.
Structure of HIP ECHO_REQUEST_UNSIGNED parameter [RFC 7401]:
0 1 2 3
0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
| Type | Length |
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
| Opaque data (variable length) |
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
Octets Bits Name Description
0 0 echo_request_unsigned.type Parameter Type
1 15 echo_request_unsigned.critical Critical Bit
2 16 echo_request_unsigned.length Length of Contents
4 32 echo_request_unsigned.data Opaque Data
"""
_data = self._read_fileng(clen)
echo_request_unsigned = dict(
type=desc,
critical=cbit,
length=clen,
data=_data,
)
_plen = length - clen
if _plen:
self._read_fileng(_plen)
return echo_request_unsigned | [
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def get_best_electronegativity_anonymous_mapping(self, struct1, struct2):
"""
Performs an anonymous fitting, which allows distinct species in one
structure to map to another. E.g., to compare if the Li2O and Na2O
structures are similar. If multiple substitutions are within tolerance
this will return the one which minimizes the difference in
electronegativity between the matches species.
Args:
struct1 (Structure): 1st structure
struct2 (Structure): 2nd structure
Returns:
min_mapping (Dict): Mapping of struct1 species to struct2 species
"""
struct1, struct2 = self._process_species([struct1, struct2])
struct1, struct2, fu, s1_supercell = self._preprocess(struct1, struct2)
matches = self._anonymous_match(struct1, struct2, fu, s1_supercell,
use_rms=True, break_on_match=True)
if matches:
min_X_diff = np.inf
for m in matches:
X_diff = 0
for k, v in m[0].items():
X_diff += struct1.composition[k] * (k.X - v.X) ** 2
if X_diff < min_X_diff:
min_X_diff = X_diff
best = m[0]
return best | [
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def imbalance_metrics(data):
""" Computes imbalance metric for a given dataset.
Imbalance metric is equal to 0 when a dataset is perfectly balanced (i.e. number of in each class is exact).
:param data : pandas.DataFrame
A dataset in a panda's data frame
:returns int
A value of imbalance metric, where zero means that the dataset is perfectly balanced and the higher the value, the more imbalanced the dataset.
"""
if not data:
return 0
#imb - shows measure of inbalance within a dataset
imb = 0
num_classes=float(len(Counter(data)))
for x in Counter(data).values():
p_x = float(x)/len(data)
if p_x > 0:
imb += (p_x - 1/num_classes)*(p_x - 1/num_classes)
#worst case scenario: all but 1 examplars in 1st class, the remaining one in 2nd class
worst_case=(num_classes-1)*pow(1/num_classes,2) + pow(1-1/num_classes,2)
return (num_classes,imb/worst_case) | [
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def address_from_digest(digest):
# type: (Digest) -> Address
"""
Generates an address from a private key digest.
"""
address_trits = [0] * (Address.LEN * TRITS_PER_TRYTE) # type: List[int]
sponge = Kerl()
sponge.absorb(digest.as_trits())
sponge.squeeze(address_trits)
return Address.from_trits(
trits=address_trits,
key_index=digest.key_index,
security_level=digest.security_level,
) | [
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def wait_and_ignore(condition, timeout=WTF_TIMEOUT_MANAGER.NORMAL, sleep=0.5):
'''
Waits wrapper that'll wait for the condition to become true, but will
not error if the condition isn't met.
Args:
condition (lambda) - Lambda expression to wait for to evaluate to True.
Kwargs:
timeout (number) : Maximum number of seconds to wait.
sleep (number) : Sleep time to wait between iterations.
Example::
wait_and_ignore(lambda: driver.find_element_by_id("success").is_displayed(),
timeout=30,
sleep=0.5)
is equivalent to::
end_time = datetime.now() + timedelta(seconds=30)
while datetime.now() < end_time:
try:
if driver.find_element_by_id("success").is_displayed():
break;
except:
pass
time.sleep(0.5)
'''
try:
return wait_until(condition, timeout, sleep)
except:
pass | [
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def random_draw(self, size=None):
"""Draw random samples of the hyperparameters.
Parameters
----------
size : None, int or array-like, optional
The number/shape of samples to draw. If None, only one sample is
returned. Default is None.
"""
return scipy.asarray([scipy.stats.norm.rvs(loc=m, scale=s, size=size) for s, m in zip(self.sigma, self.mu)]) | [
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def get_output_jsonpath_with_name(self, sub_output=None):
"""If ExtractorProcessor has a name defined, return
a JSONPath that has a filter on that name"""
if self.name is None:
return None
output_jsonpath_field = self.get_output_jsonpath_field(sub_output)
extractor_filter = "name='{}'".format(self.name)
output_jsonpath = "{}[?{}].(result[*][value])".format(
output_jsonpath_field, extractor_filter)
return output_jsonpath | [
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def parse_argv(self, argv=None, location='Command line.'):
"""Parse command line arguments.
args <list str> or None:
The argument list to parse. None means use a copy of sys.argv. argv[0] is
ignored.
location = '' <str>:
A user friendly string describing where the parser got this
data from. '' means use "Command line." if args == None, and
"Builtin default." otherwise.
"""
if argv is None:
argv = list(sys.argv)
argv.pop(0)
self._parse_options(argv, location)
self._parse_positional_arguments(argv) | [
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def orthographic_u_umlaut(sound: str) -> str:
"""
>>> OldNorsePhonology.orthographic_u_umlaut("a")
'ö'
>>> OldNorsePhonology.orthographic_u_umlaut("e")
'e'
:param sound:
:return:
"""
if sound in OldNorsePhonology.U_UMLAUT:
return OldNorsePhonology.U_UMLAUT[sound]
else:
return sound | [
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def change_first_point_by_coords(self, x, y, max_distance=1e-4,
raise_if_too_far_away=True):
"""
Set the first point of the exterior to the given point based on its coordinates.
If multiple points are found, the closest one will be picked.
If no matching points are found, an exception is raised.
Note: This method does *not* work in-place.
Parameters
----------
x : number
X-coordinate of the point.
y : number
Y-coordinate of the point.
max_distance : None or number, optional
Maximum distance past which possible matches are ignored.
If ``None`` the distance limit is deactivated.
raise_if_too_far_away : bool, optional
Whether to raise an exception if the closest found point is too
far away (``True``) or simply return an unchanged copy if this
object (``False``).
Returns
-------
imgaug.Polygon
Copy of this polygon with the new point order.
"""
if len(self.exterior) == 0:
raise Exception("Cannot reorder polygon points, because it contains no points.")
closest_idx, closest_dist = self.find_closest_point_index(x=x, y=y, return_distance=True)
if max_distance is not None and closest_dist > max_distance:
if not raise_if_too_far_away:
return self.deepcopy()
closest_point = self.exterior[closest_idx, :]
raise Exception(
"Closest found point (%.9f, %.9f) exceeds max_distance of %.9f exceeded" % (
closest_point[0], closest_point[1], closest_dist)
)
return self.change_first_point_by_index(closest_idx) | [
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def getSelectedTab(tabs, forURL):
"""
Returns the tab that should be selected when the current
resource lives at C{forURL}. Call me after L{setTabURLs}
@param tabs: sequence of L{Tab} instances
@param forURL: L{nevow.url.URL}
@return: L{Tab} instance
"""
flatTabs = []
def flatten(tabs):
for t in tabs:
flatTabs.append(t)
flatten(t.children)
flatten(tabs)
forURL = '/' + forURL.path
for t in flatTabs:
if forURL == t.linkURL:
return t
flatTabs.sort(key=lambda t: len(t.linkURL), reverse=True)
for t in flatTabs:
if not t.linkURL.endswith('/'):
linkURL = t.linkURL + '/'
else:
linkURL = t.linkURL
if forURL.startswith(linkURL):
return t | [
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def __calculate_links(self, cluster1, cluster2):
"""!
@brief Returns number of link between two clusters.
@details Link between objects (points) exists only if distance between them less than connectivity radius.
@param[in] cluster1 (list): The first cluster.
@param[in] cluster2 (list): The second cluster.
@return (uint) Number of links between two clusters.
"""
number_links = 0;
for index1 in cluster1:
for index2 in cluster2:
number_links += self.__adjacency_matrix[index1][index2];
return number_links; | [
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"[",
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"]",
"return",
"number_links"
] | 35.736842 | 21.368421 |
def partition_dict(items, key):
"""
Given an ordered dictionary of items and a key in that dict,
return an ordered dict of items before, the keyed item, and
an ordered dict of items after.
>>> od = collections.OrderedDict(zip(range(5), 'abcde'))
>>> before, item, after = partition_dict(od, 3)
>>> before
OrderedDict([(0, 'a'), (1, 'b'), (2, 'c')])
>>> item
'd'
>>> after
OrderedDict([(4, 'e')])
Like string.partition, if the key is not found in the items,
the before will contain all items, item will be None, and
after will be an empty iterable.
>>> before, item, after = partition_dict(od, -1)
>>> before
OrderedDict([(0, 'a'), ..., (4, 'e')])
>>> item
>>> list(after)
[]
"""
def unmatched(pair):
test_key, item, = pair
return test_key != key
items_iter = iter(items.items())
item = items.get(key)
left = collections.OrderedDict(itertools.takewhile(unmatched, items_iter))
right = collections.OrderedDict(items_iter)
return left, item, right | [
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def _convert_nest_to_flat(self, params, _result=None, _prefix=None):
"""
Convert a data structure that looks like::
{"foo": {"bar": "baz", "shimmy": "sham"}}
to::
{"foo.bar": "baz",
"foo.shimmy": "sham"}
This is the inverse of L{_convert_flat_to_nest}.
"""
if _result is None:
_result = {}
for k, v in params.iteritems():
if _prefix is None:
path = k
else:
path = _prefix + '.' + k
if isinstance(v, dict):
self._convert_nest_to_flat(v, _result=_result, _prefix=path)
else:
_result[path] = v
return _result | [
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def set_value(self, treeiter, column, value):
"""
{{ all }}
`value` can also be a Python value and will be converted to a
:obj:`GObject.Value` using the corresponding column type (See
:obj:`Gtk.ListStore.set_column_types`\\()).
"""
value = self._convert_value(column, value)
Gtk.ListStore.set_value(self, treeiter, column, value) | [
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def new_cells_from_excel(
self,
book,
range_,
sheet=None,
names_row=None,
param_cols=None,
param_order=None,
transpose=False,
names_col=None,
param_rows=None,
):
"""Create multiple cells from an Excel range.
This method reads values from a range in an Excel file,
create cells and populate them with the values in the range.
To use this method, ``openpyxl`` package must be installed.
The Excel file to read data from is specified by ``book``
parameters. The ``range_`` can be a range address, such as "$G4:$K10",
or a named range. In case a range address is given,
``sheet`` must also be given.
By default, cells data are interpreted as being laid out side-by-side.
``names_row`` is a row index (starting from 0) to specify the
row that contains the names of cells and parameters.
Cells and parameter names must be contained in a single row.
``param_cols`` accepts a sequence (such as list or tuple) of
column indexes (starting from 0) that indicate columns that
contain cells arguments.
**2-dimensional cells definitions**
The optional ``names_col`` and ``param_rows`` parameters are used,
when data for one cells spans more than one column.
In such cases, the cells data is 2-dimensional, and
there must be parameter row(s) across the columns
that contain arguments of the parameters.
A sequence of row indexes that indicate parameter rows
is passed to ``param_rows``.
The names of those parameters must be contained in the
same rows as parameter values (arguments), and
``names_col`` is to indicate the column position at which
the parameter names are defined.
**Horizontal arrangement**
By default, cells data are interpreted as being placed
side-by-side, regardless of whether one cells corresponds
to a single column or multiple columns.
``transpose`` parameter is used to alter this orientation,
and if it is set to ``True``, cells values are
interpreted as being placed one above the other.
"row(s)" and "col(s)" in the parameter
names are interpreted inversely, i.e.
all indexes passed to "row(s)" parameters are interpreted
as column indexes,
and all indexes passed to "col(s)" parameters as row indexes.
Args:
book (str): Path to an Excel file.
range_ (str): Range expression, such as "A1", "$G4:$K10",
or named range "NamedRange1".
sheet (str): Sheet name (case ignored).
names_row (optional): an index number indicating
what row contains the names of cells and parameters.
Defaults to the top row (0).
param_cols (optional): a sequence of index numbers
indicating parameter columns.
Defaults to only the leftmost column ([0]).
names_col (optional): an index number, starting from 0,
indicating what column contains additional parameters.
param_rows (optional): a sequence of index numbers, starting from
0, indicating rows of additional parameters, in case cells are
defined in two dimensions.
transpose (optional): Defaults to ``False``.
If set to ``True``, "row(s)" and "col(s)" in the parameter
names are interpreted inversely, i.e.
all indexes passed to "row(s)" parameters are interpreted
as column indexes,
and all indexes passed to "col(s)" parameters as row indexes.
param_order (optional): a sequence to reorder the parameters.
The elements of the sequence are the indexes of ``param_cols``
elements, and optionally the index of ``param_rows`` elements
shifted by the length of ``param_cols``.
"""
return self._impl.new_cells_from_excel(
book,
range_,
sheet,
names_row,
param_cols,
param_order,
transpose,
names_col,
param_rows,
) | [
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def get_targets(conn=None):
"""
get_brain_targets function from Brain.Targets table.
:return: <generator> yields dict objects
"""
targets = RBT
results = targets.run(conn)
for item in results:
yield item | [
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def create_project_connection(self, create_connection_inputs, project):
"""CreateProjectConnection.
[Preview API] Creates a new Pipeline connection between the provider installation and the specified project. Returns the PipelineConnection object created.
:param :class:`<CreatePipelineConnectionInputs> <azure.devops.v5_1.cix.models.CreatePipelineConnectionInputs>` create_connection_inputs:
:param str project:
:rtype: :class:`<PipelineConnection> <azure.devops.v5_1.cix.models.PipelineConnection>`
"""
query_parameters = {}
if project is not None:
query_parameters['project'] = self._serialize.query('project', project, 'str')
content = self._serialize.body(create_connection_inputs, 'CreatePipelineConnectionInputs')
response = self._send(http_method='POST',
location_id='00df4879-9216-45d5-b38d-4a487b626b2c',
version='5.1-preview.1',
query_parameters=query_parameters,
content=content)
return self._deserialize('PipelineConnection', response) | [
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def main():
"""The main function.
These are the steps performed for the data clean up:
1. Prints the version number.
2. Reads the configuration file (:py:func:`read_config_file`).
3. Creates a new directory with ``data_clean_up`` as prefix and the date
and time as suffix.
4. Check the input file type (``bfile``, ``tfile`` or ``file``).
5. Creates an intermediate directory with the section as prefix and the
script name as suffix (inside the previous directory).
6. Runs the required script in order (according to the configuration file
section).
.. note::
The main function is not responsible to check if the required files
exist. This should be done in the ``run`` functions.
"""
# Getting and checking the options
args = parse_args()
check_args(args)
# The directory name
dirname = "data_clean_up."
dirname += datetime.datetime.today().strftime("%Y-%m-%d_%H.%M.%S")
while os.path.isdir(dirname):
time.sleep(1)
dirname = "data_clean_up."
dirname += datetime.datetime.today().strftime("%Y-%m-%d_%H.%M.%S")
# Creating the output directory
os.mkdir(dirname)
# Configuring the root logger
add_file_handler_to_root(os.path.join(dirname, "pyGenClean.log"))
logger.info("pyGenClean version {}".format(__version__))
plink_version = get_plink_version()
logger.info("Using Plink version {}".format(plink_version))
# Reading the configuration file
logger.info("Reading configuration file [ {} ]".format(args.conf))
order, conf = read_config_file(args.conf)
# Executing the data clean up
current_in = None
current_in_type = None
suffixes = None
if args.tfile is not None:
current_in = args.tfile
current_in_type = "tfile"
suffixes = (".tped", ".tfam")
elif args.bfile is not None:
current_in = args.bfile
current_in_type = "bfile"
suffixes = (".bed", ".bim", ".fam")
else:
current_in = args.file
current_in_type = "file"
suffixes = (".ped", ".map")
# Creating the excluded files
try:
with open(os.path.join(dirname, "excluded_markers.txt"), "w") as o_f:
pass
with open(os.path.join(dirname, "excluded_samples.txt"), "w") as o_f:
pass
with open(os.path.join(dirname, "initial_files.txt"), "w") as o_file:
for s in suffixes:
print >>o_file, current_in + s
except IOError:
msg = "{}: cannot write summary".format(dirname)
raise ProgramError(msg)
# Counting the number of markers and samples in the datafile
logger.info("Counting initial number of samples and markers")
nb_markers, nb_samples = count_markers_samples(current_in,
current_in_type)
logger.info(" - {:,d} samples".format(nb_samples))
logger.info(" - {:,d} markers".format(nb_markers))
# Creating the result summary file containing the initial numbers
try:
with open(os.path.join(dirname, "results_summary.txt"), "w") as o_file:
print >>o_file, "# initial"
print >>o_file, ("Initial number of markers\t"
"{:,d}".format(nb_markers))
print >>o_file, ("Initial number of samples\t"
"{:,d}".format(nb_samples))
print >>o_file, "---"
except IOError:
msg = "{}: cannot write summary".format(dirname)
raise ProgramError(msg)
latex_summaries = []
steps = []
descriptions = []
long_descriptions = []
graphic_paths = set()
for number in order:
# Getting the script name and its options
script_name, options = conf[number]
# Getting the output prefix
output_prefix = os.path.join(dirname,
"{}_{}".format(number, script_name))
# Getting the function to use
function_to_use = available_functions[script_name]
# Executing the function
logger.info("Running {} {}".format(number, script_name))
logger.info(" - Using {} as prefix for input "
"files".format(current_in))
logger.info(" - Results will be in [ {} ]".format(output_prefix))
# Executing the function
step_results = function_to_use(
in_prefix=current_in,
in_type=current_in_type,
out_prefix=output_prefix,
base_dir=dirname,
options=options,
)
# Updating the input files and input file types
current_in = step_results.next_file
current_in_type = step_results.next_file_type
# Saving what's necessary for the LaTeX report
latex_summaries.append(step_results.latex_summary)
steps.append(script_name)
descriptions.append(step_results.description)
long_descriptions.append(step_results.long_description)
if step_results.graph_path is not None:
graphic_paths.update(step_results.graph_path)
# Counting the final number of samples and markers
logger.info("Counting final number of samples and markers")
nb_markers, nb_samples = count_markers_samples(current_in,
current_in_type)
logger.info(" - {:,d} samples".format(nb_samples))
logger.info(" - {:,d} markers".format(nb_markers))
# Getting the final suffixes
suffixes = None
if current_in_type == "tfile":
suffixes = ((".tped", nb_markers), (".tfam", nb_samples))
elif current_in_type == "bfile":
suffixes = ((".bed", None), (".bim", nb_markers), (".fam", nb_samples))
else:
suffixes = ((".ped", nb_samples), (".map", nb_markers))
with open(os.path.join(dirname, "final_files.txt"), "w") as o_file:
for s, nb in suffixes:
if nb:
print >>o_file, current_in + s + "\t{:,d}".format(nb)
else:
print >>o_file, current_in + s
# Generating the graphics paths file
graphic_paths_fn = None
if len(graphic_paths) > 0:
try:
graphic_paths_fn = os.path.join(dirname, "graphic_paths.txt")
with open(graphic_paths_fn, "w") as o_file:
for path in sorted(graphic_paths):
print >>o_file, path
except IOError:
msg = "{}: cannot write summary".format(dirname)
raise ProgramError(msg)
# We create the automatic report
logger.info("Generating automatic report")
report_name = os.path.join(dirname, "automatic_report.tex")
auto_report.create_report(
dirname,
report_name,
project_name=args.report_number,
steps=steps,
descriptions=descriptions,
graphic_paths_fn=graphic_paths_fn,
long_descriptions=long_descriptions,
summaries=latex_summaries,
background=args.report_background,
summary_fn=os.path.join(dirname, "results_summary.txt"),
report_title=args.report_title,
report_author=args.report_author,
initial_files=os.path.join(dirname, "initial_files.txt"),
final_files=os.path.join(dirname, "final_files.txt"),
final_nb_markers="{:,d}".format(nb_markers),
final_nb_samples="{:,d}".format(nb_samples),
plink_version=plink_version,
) | [
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",",
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] | 36.80203 | 19.106599 |
def calc_n_coarse_chan(self, chan_bw=None):
""" This makes an attempt to calculate the number of coarse channels in a given file.
Note:
This is unlikely to work on non-Breakthrough Listen data, as a-priori knowledge of
the digitizer system is required.
"""
nchans = int(self.header[b'nchans'])
# Do we have a file with enough channels that it has coarse channelization?
if chan_bw is not None:
bandwidth = abs(self.f_stop - self.f_start)
n_coarse_chan = int(bandwidth / chan_bw)
return n_coarse_chan
elif nchans >= 2**20:
# Does the common FFT length of 2^20 divide through without a remainder?
# This should work for most GBT and all Parkes hires data
if nchans % 2**20 == 0:
n_coarse_chan = nchans // 2**20
return n_coarse_chan
# Early GBT data has non-2^N FFT length, check if it is GBT data
elif self.header[b'telescope_id'] == 6:
coarse_chan_bw = 2.9296875
bandwidth = abs(self.f_stop - self.f_start)
n_coarse_chan = int(bandwidth / coarse_chan_bw)
return n_coarse_chan
else:
logger.warning("Couldn't figure out n_coarse_chan")
elif self.header[b'telescope_id'] == 6 and nchans < 2**20:
#For GBT non-hires data
coarse_chan_bw = 2.9296875
bandwidth = abs(self.f_stop - self.f_start)
n_coarse_chan = int(bandwidth / coarse_chan_bw)
return n_coarse_chan
else:
logger.warning("This function currently only works for hires BL Parkes or GBT data.") | [
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")"
] | 47.611111 | 18.555556 |
def do_alarm_definition_patch(mc, args):
'''Patch the alarm definition.'''
fields = {}
fields['alarm_id'] = args.id
if args.name:
fields['name'] = args.name
if args.description:
fields['description'] = args.description
if args.expression:
fields['expression'] = args.expression
if args.alarm_actions:
fields['alarm_actions'] = _arg_split_patch_update(args.alarm_actions, patch=True)
if args.ok_actions:
fields['ok_actions'] = _arg_split_patch_update(args.ok_actions, patch=True)
if args.undetermined_actions:
fields['undetermined_actions'] = _arg_split_patch_update(args.undetermined_actions,
patch=True)
if args.actions_enabled:
if args.actions_enabled not in enabled_types:
errmsg = ('Invalid value, not one of [' +
', '.join(enabled_types) + ']')
print(errmsg)
return
fields['actions_enabled'] = args.actions_enabled in ['true', 'True']
if args.severity:
if not _validate_severity(args.severity):
return
fields['severity'] = args.severity
try:
alarm = mc.alarm_definitions.patch(**fields)
except (osc_exc.ClientException, k_exc.HttpError) as he:
raise osc_exc.CommandError('%s\n%s' % (he.message, he.details))
else:
print(jsonutils.dumps(alarm, indent=2)) | [
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] | 41.764706 | 18.764706 |
def _pid_to_id(self, pid):
"""Converts a pid to a URI that can be used as an OAI-ORE identifier."""
return d1_common.url.joinPathElements(
self._base_url,
self._version_tag,
"resolve",
d1_common.url.encodePathElement(pid),
) | [
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async def import_aggregated(self, async_client, pid):
"""Import the SciObj at {pid}.
If the SciObj is a Resource Map, also recursively import the aggregated objects.
"""
self._logger.info('Importing: {}'.format(pid))
task_set = set()
object_info_pyxb = d1_common.types.dataoneTypes.ObjectInfo()
object_info_pyxb.identifier = pid
task_set.add(self.import_object(async_client, object_info_pyxb))
result_set, task_set = await asyncio.wait(task_set)
assert len(result_set) == 1
assert not task_set
sysmeta_pyxb = result_set.pop().result()
if not sysmeta_pyxb:
# Import was skipped
return
assert d1_common.xml.get_req_val(sysmeta_pyxb.identifier) == pid
if d1_gmn.app.did.is_resource_map_db(pid):
for member_pid in d1_gmn.app.resource_map.get_resource_map_members_by_map(
pid
):
self.progress_logger.event("Importing aggregated SciObj")
self._logger.info('Importing aggregated SciObj. pid="{}"'.format(pid))
await self.import_aggregated(async_client, member_pid) | [
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def generate_pseudo(strain_states, order=3):
"""
Generates the pseudoinverse for a given set of strains.
Args:
strain_states (6xN array like): a list of voigt-notation
"strain-states", i. e. perturbed indices of the strain
as a function of the smallest strain e. g. (0, 1, 0, 0, 1, 0)
order (int): order of pseudoinverse to calculate
Returns:
mis: pseudo inverses for each order tensor, these can
be multiplied by the central difference derivative
of the stress with respect to the strain state
absent_syms: symbols of the tensor absent from the PI
expression
"""
s = sp.Symbol('s')
nstates = len(strain_states)
ni = np.array(strain_states)*s
mis, absent_syms = [], []
for degree in range(2, order + 1):
cvec, carr = get_symbol_list(degree)
sarr = np.zeros((nstates, 6), dtype=object)
for n, strain_v in enumerate(ni):
# Get expressions
exps = carr.copy()
for i in range(degree - 1):
exps = np.dot(exps, strain_v)
exps /= np.math.factorial(degree - 1)
sarr[n] = [sp.diff(exp, s, degree - 1) for exp in exps]
svec = sarr.ravel()
present_syms = set.union(*[exp.atoms(sp.Symbol) for exp in svec])
absent_syms += [set(cvec) - present_syms]
m = np.zeros((6*nstates, len(cvec)))
for n, c in enumerate(cvec):
m[:, n] = v_diff(svec, c)
mis.append(np.linalg.pinv(m))
return mis, absent_syms | [
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def _pirls(self, X, Y, weights):
"""
Performs stable PIRLS iterations to estimate GAM coefficients
Parameters
---------
X : array-like of shape (n_samples, m_features)
containing input data
Y : array-like of shape (n,)
containing target data
weights : array-like of shape (n,)
containing sample weights
Returns
-------
None
"""
modelmat = self._modelmat(X) # build a basis matrix for the GLM
n, m = modelmat.shape
# initialize GLM coefficients if model is not yet fitted
if (not self._is_fitted
or len(self.coef_) != self.terms.n_coefs
or not np.isfinite(self.coef_).all()):
# initialize the model
self.coef_ = self._initial_estimate(Y, modelmat)
assert np.isfinite(self.coef_).all(), "coefficients should be well-behaved, but found: {}".format(self.coef_)
P = self._P()
S = sp.sparse.diags(np.ones(m) * np.sqrt(EPS)) # improve condition
# S += self._H # add any user-chosen minumum penalty to the diagonal
# if we dont have any constraints, then do cholesky now
if not self.terms.hasconstraint:
E = self._cholesky(S + P, sparse=False, verbose=self.verbose)
min_n_m = np.min([m,n])
Dinv = np.zeros((min_n_m + m, m)).T
for _ in range(self.max_iter):
# recompute cholesky if needed
if self.terms.hasconstraint:
P = self._P()
C = self._C()
E = self._cholesky(S + P + C, sparse=False, verbose=self.verbose)
# forward pass
y = deepcopy(Y) # for simplicity
lp = self._linear_predictor(modelmat=modelmat)
mu = self.link.mu(lp, self.distribution)
W = self._W(mu, weights, y) # create pirls weight matrix
# check for weghts == 0, nan, and update
mask = self._mask(W.diagonal())
y = y[mask] # update
lp = lp[mask] # update
mu = mu[mask] # update
W = sp.sparse.diags(W.diagonal()[mask]) # update
# PIRLS Wood pg 183
pseudo_data = W.dot(self._pseudo_data(y, lp, mu))
# log on-loop-start stats
self._on_loop_start(vars())
WB = W.dot(modelmat[mask,:]) # common matrix product
Q, R = np.linalg.qr(WB.A)
if not np.isfinite(Q).all() or not np.isfinite(R).all():
raise ValueError('QR decomposition produced NaN or Inf. '\
'Check X data.')
# need to recompute the number of singular values
min_n_m = np.min([m, n, mask.sum()])
Dinv = np.zeros((m, min_n_m))
# SVD
U, d, Vt = np.linalg.svd(np.vstack([R, E]))
svd_mask = d <= (d.max() * np.sqrt(EPS)) # mask out small singular values
np.fill_diagonal(Dinv, d**-1) # invert the singular values
U1 = U[:min_n_m,:min_n_m] # keep only top corner of U
# update coefficients
B = Vt.T.dot(Dinv).dot(U1.T).dot(Q.T)
coef_new = B.dot(pseudo_data).flatten()
diff = np.linalg.norm(self.coef_ - coef_new)/np.linalg.norm(coef_new)
self.coef_ = coef_new # update
# log on-loop-end stats
self._on_loop_end(vars())
# check convergence
if diff < self.tol:
break
# estimate statistics even if not converged
self._estimate_model_statistics(Y, modelmat, inner=None, BW=WB.T, B=B,
weights=weights, U1=U1)
if diff < self.tol:
return
print('did not converge')
return | [
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")",
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] | 34.831776 | 21.224299 |
def create_key_ring(
self,
parent,
key_ring_id,
key_ring,
retry=google.api_core.gapic_v1.method.DEFAULT,
timeout=google.api_core.gapic_v1.method.DEFAULT,
metadata=None,
):
"""
Create a new ``KeyRing`` in a given Project and Location.
Example:
>>> from google.cloud import kms_v1
>>>
>>> client = kms_v1.KeyManagementServiceClient()
>>>
>>> parent = client.location_path('[PROJECT]', '[LOCATION]')
>>>
>>> # TODO: Initialize `key_ring_id`:
>>> key_ring_id = ''
>>>
>>> # TODO: Initialize `key_ring`:
>>> key_ring = {}
>>>
>>> response = client.create_key_ring(parent, key_ring_id, key_ring)
Args:
parent (str): Required. The resource name of the location associated with the
``KeyRings``, in the format ``projects/*/locations/*``.
key_ring_id (str): Required. It must be unique within a location and match the regular
expression ``[a-zA-Z0-9_-]{1,63}``
key_ring (Union[dict, ~google.cloud.kms_v1.types.KeyRing]): A ``KeyRing`` with initial field values.
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.kms_v1.types.KeyRing`
retry (Optional[google.api_core.retry.Retry]): A retry object used
to retry requests. If ``None`` is specified, requests will not
be retried.
timeout (Optional[float]): The amount of time, in seconds, to wait
for the request to complete. Note that if ``retry`` is
specified, the timeout applies to each individual attempt.
metadata (Optional[Sequence[Tuple[str, str]]]): Additional metadata
that is provided to the method.
Returns:
A :class:`~google.cloud.kms_v1.types.KeyRing` instance.
Raises:
google.api_core.exceptions.GoogleAPICallError: If the request
failed for any reason.
google.api_core.exceptions.RetryError: If the request failed due
to a retryable error and retry attempts failed.
ValueError: If the parameters are invalid.
"""
# Wrap the transport method to add retry and timeout logic.
if "create_key_ring" not in self._inner_api_calls:
self._inner_api_calls[
"create_key_ring"
] = google.api_core.gapic_v1.method.wrap_method(
self.transport.create_key_ring,
default_retry=self._method_configs["CreateKeyRing"].retry,
default_timeout=self._method_configs["CreateKeyRing"].timeout,
client_info=self._client_info,
)
request = service_pb2.CreateKeyRingRequest(
parent=parent, key_ring_id=key_ring_id, key_ring=key_ring
)
if metadata is None:
metadata = []
metadata = list(metadata)
try:
routing_header = [("parent", parent)]
except AttributeError:
pass
else:
routing_metadata = google.api_core.gapic_v1.routing_header.to_grpc_metadata(
routing_header
)
metadata.append(routing_metadata)
return self._inner_api_calls["create_key_ring"](
request, retry=retry, timeout=timeout, metadata=metadata
) | [
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] | 41.105882 | 24.517647 |
def _extract_functions(resources):
"""
Extracts and returns function information from the given dictionary of SAM/CloudFormation resources. This
method supports functions defined with AWS::Serverless::Function and AWS::Lambda::Function
:param dict resources: Dictionary of SAM/CloudFormation resources
:return dict(string : samcli.commands.local.lib.provider.Function): Dictionary of function LogicalId to the
Function configuration object
"""
result = {}
for name, resource in resources.items():
resource_type = resource.get("Type")
resource_properties = resource.get("Properties", {})
if resource_type == SamFunctionProvider._SERVERLESS_FUNCTION:
layers = SamFunctionProvider._parse_layer_info(resource_properties.get("Layers", []), resources)
result[name] = SamFunctionProvider._convert_sam_function_resource(name, resource_properties, layers)
elif resource_type == SamFunctionProvider._LAMBDA_FUNCTION:
layers = SamFunctionProvider._parse_layer_info(resource_properties.get("Layers", []), resources)
result[name] = SamFunctionProvider._convert_lambda_function_resource(name, resource_properties, layers)
# We don't care about other resource types. Just ignore them
return result | [
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def check_overlap(current, hit, overlap = 200):
"""
determine if sequence has already hit the same part of the model,
indicating that this hit is for another 16S rRNA gene
"""
for prev in current:
p_coords = prev[2:4]
coords = hit[2:4]
if get_overlap(coords, p_coords) >= overlap:
return True
return False | [
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def _get_repo_file(self, repo_path):
"""
Lazy load RepoFile objects on demand.
:param repo_path:
:return:
"""
if repo_path not in self._repo_files:
self._repo_files[repo_path] = RepoFile(repo_path)
return self._repo_files[repo_path] | [
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def write_languages(f, l):
"""Write language information."""
f.write("Languages = {%s" % os.linesep)
for lang in sorted(l):
f.write(" %r: %r,%s" % (lang, l[lang], os.linesep))
f.write("}%s" % os.linesep) | [
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def get_icohp_dict_of_site(self, site, minsummedicohp=None, maxsummedicohp=None, minbondlength=0.0,
maxbondlength=8.0, only_bonds_to=None):
"""
get a dict of IcohpValue for a certain site (indicated by integer)
Args:
site: integer describing the site of interest, order as in Icohplist.lobster/Icooplist.lobster, starts at 0
minsummedicohp: float, minimal icohp/icoop of the bonds that are considered. It is the summed ICOHP value from both spin channels for spin polarized cases
maxsummedicohp: float, maximal icohp/icoop of the bonds that are considered. It is the summed ICOHP value from both spin channels for spin polarized cases
minbondlength: float, defines the minimum of the bond lengths of the bonds
maxbondlength: float, defines the maximum of the bond lengths of the bonds
only_bonds_to: list of strings describing the bonding partners that are allowed, e.g. ['O']
Returns:
dict of IcohpValues, the keys correspond to the values from the initial list_labels
"""
newicohp_dict = {}
for key, value in self._icohplist.items():
atomnumber1 = int(re.split(r'(\d+)', value._atom1)[1]) - 1
atomnumber2 = int(re.split(r'(\d+)', value._atom2)[1]) - 1
if site == atomnumber1 or site == atomnumber2:
# manipulate order of atoms so that searched one is always atom1
if site == atomnumber2:
save = value._atom1
value._atom1 = value._atom2
value._atom2 = save
if only_bonds_to is None:
second_test = True
else:
second_test = (re.split(r'(\d+)', value._atom2)[0] in only_bonds_to)
if value._length >= minbondlength and value._length <= maxbondlength and second_test:
if minsummedicohp is not None:
if value.summed_icohp >= minsummedicohp:
if maxsummedicohp is not None:
if value.summed_icohp <= maxsummedicohp:
newicohp_dict[key] = value
else:
newicohp_dict[key] = value
else:
if maxsummedicohp is not None:
if value.summed_icohp <= maxsummedicohp:
newicohp_dict[key] = value
else:
newicohp_dict[key] = value
return newicohp_dict | [
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def RSA_encrypt(public_key, message):
'''用RSA加密字符串.
public_key - 公钥
message - 要加密的信息, 使用UTF-8编码的字符串
@return - 使用base64编码的字符串
'''
# 如果没能成功导入RSA模块, 就直接返回空白字符串.
if not globals().get('RSA'):
return ''
rsakey = RSA.importKey(public_key)
rsakey = PKCS1_v1_5.new(rsakey)
encrypted = rsakey.encrypt(message.encode())
return base64.encodestring(encrypted).decode().replace('\n', '') | [
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def admin_tools_render_dashboard(context, location='index', dashboard=None):
"""
Template tag that renders the dashboard, it takes two optional arguments:
``location``
The location of the dashboard, it can be 'index' (for the admin index
dashboard) or 'app_index' (for the app index dashboard), the default
value is 'index'.
``dashboard``
An instance of ``Dashboard``, if not given, the dashboard is retrieved
with the ``get_index_dashboard`` or ``get_app_index_dashboard``
functions, depending on the ``location`` argument.
"""
if dashboard is None:
dashboard = get_dashboard(context, location)
dashboard.init_with_context(context)
dashboard._prepare_children()
try:
preferences = DashboardPreferences.objects.get(
user=context['request'].user,
dashboard_id=dashboard.get_id()
).data
except DashboardPreferences.DoesNotExist:
preferences = '{}'
try:
DashboardPreferences(
user=context['request'].user,
dashboard_id=dashboard.get_id(),
data=preferences
).save()
except IntegrityError:
# dashboard already was saved for that (user, dashboard)
pass
context.update({
'template': dashboard.template,
'dashboard': dashboard,
'dashboard_preferences': preferences,
'split_at': math.ceil(
float(len(dashboard.children)) / float(dashboard.columns)
),
'has_disabled_modules': len(
[m for m in dashboard.children if not m.enabled]
) > 0,
'admin_url': reverse('%s:index' % get_admin_site_name(context)),
})
return context | [
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")",
",",
"}",
")",
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def _write_to_error(self, s, truncate=False):
"""Writes the given output to the error file, appending unless `truncate` is True."""
# if truncate is True, set write mode to truncate
with open(self._errorfile, 'w' if truncate else 'a') as fp:
fp.writelines((to_text(s)), ) | [
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def working_yesterday(self, date_from=None, date_format=None):
"""
Retourne la date d'hier depuis maintenant ou depuis une date fournie
seulement sur les jours ouvrableq.
Ainsi lundi devient samedi et samedi devient vendredi
:param: :date_from date de référence
:return datetime
"""
# date d'hier que sur les jours de week-end
return self.delta(days=-1, date_from=date_from, date_format=date_format, days_range=[1, 2, 3, 4, 5, 6]) | [
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def from_ros_pose_msg(pose_msg,
from_frame='unassigned',
to_frame='world'):
"""Creates a RigidTransform from a ROS pose msg.
Parameters
----------
pose_msg : :obj:`geometry_msgs.msg.Pose`
ROS pose message
"""
quaternion = np.array([pose_msg.orientation.w,
pose_msg.orientation.x,
pose_msg.orientation.y,
pose_msg.orientation.z])
position = np.array([pose_msg.position.x,
pose_msg.position.y,
pose_msg.position.z])
pose = RigidTransform(rotation=quaternion,
translation=position,
from_frame=from_frame,
to_frame=to_frame)
return pose | [
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def get_rtr_name(self, router_id):
"""Retrieve the router name. Incomplete. """
try:
body = {}
router = self.neutronclient.show_router(router_id, body=body)
return router.get('router').get('name')
except Exception as exc:
LOG.error("Failed to show router interface %(id)s "
"Exc %(exc)s", {'id': router_id, 'exc': str(exc)}) | [
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def isLoopback (self, ifname):
"""Check whether interface is a loopback device.
@param ifname: interface name
@type ifname: string
"""
# since not all systems have IFF_LOOPBACK as a flag defined,
# the ifname is tested first
if ifname.startswith('lo'):
return True
return (self.getFlags(ifname) & self.IFF_LOOPBACK) != 0 | [
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def inject(self, request, response):
"""
Inject the debug toolbar iframe into an HTML response.
"""
# called in host app
if not isinstance(response, Response):
return
settings = request.app[APP_KEY]['settings']
response_html = response.body
route = request.app.router['debugtoolbar.request']
toolbar_url = route.url_for(request_id=request['id'])
button_style = settings['button_style']
css_path = request.app.router[STATIC_ROUTE_NAME].url_for(
filename='css/toolbar_button.css')
toolbar_css = toolbar_css_template % {'css_path': css_path}
toolbar_html = toolbar_html_template % {
'button_style': button_style,
'css_path': css_path,
'toolbar_url': toolbar_url}
toolbar_html = toolbar_html.encode(response.charset or 'utf-8')
toolbar_css = toolbar_css.encode(response.charset or 'utf-8')
response_html = replace_insensitive(
response_html, b'</head>', toolbar_css + b'</head>')
response.body = replace_insensitive(
response_html, b'</body>',
toolbar_html + b'</body>') | [
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def parse_oxide(self):
"""
Determines if an oxide is a peroxide/superoxide/ozonide/normal oxide.
Returns:
oxide_type (str): Type of oxide
ozonide/peroxide/superoxide/hydroxide/None.
nbonds (int): Number of peroxide/superoxide/hydroxide bonds in
structure.
"""
structure = self.structure
relative_cutoff = self.relative_cutoff
o_sites_frac_coords = []
h_sites_frac_coords = []
lattice = structure.lattice
if isinstance(structure.composition.elements[0], Element):
comp = structure.composition
elif isinstance(structure.composition.elements[0], Specie):
elmap = collections.defaultdict(float)
for site in structure:
for species, occu in site.species.items():
elmap[species.element] += occu
comp = Composition(elmap)
if Element("O") not in comp or comp.is_element:
return "None", 0
for site in structure:
syms = [sp.symbol for sp in site.species.keys()]
if "O" in syms:
o_sites_frac_coords.append(site.frac_coords)
if "H" in syms:
h_sites_frac_coords.append(site.frac_coords)
if h_sites_frac_coords:
dist_matrix = lattice.get_all_distances(o_sites_frac_coords,
h_sites_frac_coords)
if np.any(dist_matrix < relative_cutoff * 0.93):
return "hydroxide", len(
np.where(dist_matrix < relative_cutoff * 0.93)[0]) / 2.0
dist_matrix = lattice.get_all_distances(o_sites_frac_coords,
o_sites_frac_coords)
np.fill_diagonal(dist_matrix, 1000)
is_superoxide = False
is_peroxide = False
is_ozonide = False
if np.any(dist_matrix < relative_cutoff * 1.35):
bond_atoms = np.where(dist_matrix < relative_cutoff * 1.35)[0]
is_superoxide = True
elif np.any(dist_matrix < relative_cutoff * 1.49):
is_peroxide = True
bond_atoms = np.where(dist_matrix < relative_cutoff * 1.49)[0]
if is_superoxide:
if len(bond_atoms) > len(set(bond_atoms)):
is_superoxide = False
is_ozonide = True
try:
nbonds = len(set(bond_atoms))
except UnboundLocalError:
nbonds = 0.0
if is_ozonide:
str_oxide = "ozonide"
elif is_superoxide:
str_oxide = "superoxide"
elif is_peroxide:
str_oxide = "peroxide"
else:
str_oxide = "oxide"
if str_oxide == "oxide":
nbonds = comp["O"]
return str_oxide, nbonds | [
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] | 39 | 15.873239 |
def get_extensions_assigned_to_user(self, user_id):
"""GetExtensionsAssignedToUser.
[Preview API] Returns extensions that are currently assigned to the user in the account
:param str user_id: The user's identity id.
:rtype: {LicensingSource}
"""
route_values = {}
if user_id is not None:
route_values['userId'] = self._serialize.url('user_id', user_id, 'str')
response = self._send(http_method='GET',
location_id='8cec75ea-044f-4245-ab0d-a82dafcc85ea',
version='5.0-preview.1',
route_values=route_values)
return self._deserialize('{LicensingSource}', self._unwrap_collection(response)) | [
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] | 53.285714 | 19.857143 |
def get_unverified_claims(token):
"""Returns the decoded claims without verification of any kind.
Args:
token (str): A signed JWT to decode the headers from.
Returns:
dict: The dict representation of the token claims.
Raises:
JWTError: If there is an exception decoding the token.
"""
try:
claims = jws.get_unverified_claims(token)
except:
raise JWTError('Error decoding token claims.')
try:
claims = json.loads(claims.decode('utf-8'))
except ValueError as e:
raise JWTError('Invalid claims string: %s' % e)
if not isinstance(claims, Mapping):
raise JWTError('Invalid claims string: must be a json object')
return claims | [
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def _chooseBestSegmentPerCell(cls,
connections,
cells,
allMatchingSegments,
potentialOverlaps):
"""
For each specified cell, choose its matching segment with largest number
of active potential synapses. When there's a tie, the first segment wins.
@param connections (SparseMatrixConnections)
@param cells (numpy array)
@param allMatchingSegments (numpy array)
@param potentialOverlaps (numpy array)
@return (numpy array)
One segment per cell
"""
candidateSegments = connections.filterSegmentsByCell(allMatchingSegments,
cells)
# Narrow it down to one pair per cell.
onePerCellFilter = np2.argmaxMulti(potentialOverlaps[candidateSegments],
connections.mapSegmentsToCells(
candidateSegments))
learningSegments = candidateSegments[onePerCellFilter]
return learningSegments | [
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def render_template(template_name_or_list, **context):
"""Renders a template from the template folder with the given
context.
:param template_name_or_list: the name of the template to be
rendered, or an iterable with template names
the first one existing will be rendered
:param context: the variables that should be available in the
context of the template.
"""
ctx = _app_ctx_stack.top
ctx.app.update_template_context(context)
return _render(ctx.app.jinja_env.get_or_select_template(template_name_or_list),
context, ctx.app) | [
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def set_title(self,table=None,title=None,verbose=None):
"""
Changes the visible identifier of a single table.
:param table (string, optional): Specifies a table by table name. If the pr
efix SUID: is used, the table corresponding the SUID will be returne
d.
:param title (string, optional): The name of the table used in the current
network
"""
PARAMS=set_param(['table','title'],[table,title])
response=api(url=self.__url+"/set title", PARAMS=PARAMS, method="POST", verbose=verbose)
return response | [
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