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def metadata_add_endpoints(self):
""" Metadata: add endpoint to the group """
metadata = load_mpe_service_metadata(self.args.metadata_file)
group_name = metadata.get_group_name_nonetrick(self.args.group_name)
for endpoint in self.args.endpoints:
metadata.add_endpoint(group_name, endpoint)
metadata.save_pretty(self.args.metadata_file) | [
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def prepare_request(node):
"""
Prepare request to node's API route
:param Node node: the RAML node object
"""
if node.resource.method not in AVAILABLE_METHODS:
raise UnsupportedHTTPMethodError(node.resource.method)
def request(data=None, json=None, **kwargs):
"""
Make request to node's API route with the given keyword arguments
"""
# validate given query parameters
for key, value in kwargs.items():
param = next((p for p in node.resource.query_params if p.name == key), None)
if not param:
raise UnsupportedQueryParameter(node.resource.path, key)
if not match_type(value, param.type):
raise TypeError(
"Resource Query Parameter has type '{0}' but expected type '{1}'".format(
value.__class__.__name__, param.type))
response = requests.request(node.resource.method, node.resource.absolute_uri, params=kwargs,
data=data, json=json)
return response
return request | [
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def calc_filemap(atlas_properties, subject, atlas_version_tags, worklog,
output_path=None, overwrite=False, output_format='mgz', create_directory=False):
'''
calc_filemap is a calculator that converts the atlas properties nested-map into a single-depth
map whose keys are filenames and whose values are the interpolated property data.
Afferent parameters
@ output_path
The directory into which the atlas files should be written. If not provided or None then
uses the subject's surf directory. If this directory doesn't exist, then it uses the
subject's directory itself.
@ overwrite
Whether to overwrite existing atlas files. If True, then atlas files that already exist will
be overwritten. If False, then no files are overwritten.
@ create_directory
Whether to create the output path if it doesn't exist. This is False by default.
@ output_format
The desired output format of the files to be written. May be one of the following: 'mgz',
'mgh', or either 'curv' or 'morph'.
Efferent values:
@ filemap
A pimms lazy map whose keys are filenames and whose values are interpolated atlas
properties.
@ export_all_fn
A function of no arguments that, when called, exports all of the files in the filemap to the
output_path.
'''
if output_path is None:
output_path = os.path.join(subject.path, 'surf')
if not os.path.isdir(output_path): output_path = subject.path
output_format = 'mgz' if output_format is None else output_format.lower()
if output_format.startswith('.'): output_format = output_format[1:]
(fmt,ending) = (('mgh','.mgz') if output_format == 'mgz' else
('mgh','.mgh') if output_format == 'mgh' else
('freesurfer_morph',''))
# make the filemap...
worklog('Preparing Filemap...')
fm = AutoDict()
for (atl,atldat) in six.iteritems(atlas_properties):
for (ver,verdat) in six.iteritems(atldat):
vstr = atlas_version_tags[atl][ver]
for (h,hdat) in six.iteritems(verdat):
for m in six.iterkeys(hdat):
flnm = '%s.%s_%s%s%s' % (h, atl, m, vstr, ending)
flnm = os.path.join(output_path, flnm)
fm[flnm] = curry(lambda hdat,m: hdat[m], hdat, m)
# okay, make that a lazy map:
filemap = pimms.lazy_map(fm)
# the function for exporting all properties:
def export_all():
'''
This function will export all files from its associated filemap and return a list of the
filenames.
'''
if not os.path.isdir(output_path):
if not create_directory:
raise ValueError('No such path and create_direcotry is False: %s' % output_path)
os.makedirs(os.path.abspath(output_path), 0o755)
filenames = []
worklog('Extracting Files...')
wl = worklog.indent()
for flnm in six.iterkeys(filemap):
wl(flnm)
filenames.append(nyio.save(flnm, filemap[flnm], fmt))
return filenames
return {'filemap': filemap, 'export_all_fn': export_all} | [
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def get_initkwargs(cls, form_list, initial_dict=None,
instance_dict=None, condition_dict=None, *args, **kwargs):
"""
Creates a dict with all needed parameters for the form wizard instances.
* `form_list` - is a list of forms. The list entries can be single form
classes or tuples of (`step_name`, `form_class`). If you pass a list
of forms, the formwizard will convert the class list to
(`zero_based_counter`, `form_class`). This is needed to access the
form for a specific step.
* `initial_dict` - contains a dictionary of initial data dictionaries.
The key should be equal to the `step_name` in the `form_list` (or
the str of the zero based counter - if no step_names added in the
`form_list`)
* `instance_dict` - contains a dictionary of instance objects. This list
is only used when `ModelForm`s are used. The key should be equal to
the `step_name` in the `form_list`. Same rules as for `initial_dict`
apply.
* `condition_dict` - contains a dictionary of boolean values or
callables. If the value of for a specific `step_name` is callable it
will be called with the formwizard instance as the only argument.
If the return value is true, the step's form will be used.
"""
kwargs.update({
'initial_dict': initial_dict or {},
'instance_dict': instance_dict or {},
'condition_dict': condition_dict or {},
})
init_form_list = SortedDict()
assert len(form_list) > 0, 'at least one form is needed'
# walk through the passed form list
for i, form in enumerate(form_list):
if isinstance(form, (list, tuple)):
# if the element is a tuple, add the tuple to the new created
# sorted dictionary.
init_form_list[unicode(form[0])] = form[1]
else:
# if not, add the form with a zero based counter as unicode
init_form_list[unicode(i)] = form
# walk through the ne created list of forms
for form in init_form_list.itervalues():
if issubclass(form, formsets.BaseFormSet):
# if the element is based on BaseFormSet (FormSet/ModelFormSet)
# we need to override the form variable.
form = form.form
# check if any form contains a FileField, if yes, we need a
# file_storage added to the formwizard (by subclassing).
for field in form.base_fields.itervalues():
if (isinstance(field, forms.FileField) and
not hasattr(cls, 'file_storage')):
raise NoFileStorageConfigured
# build the kwargs for the formwizard instances
kwargs['form_list'] = init_form_list
return kwargs | [
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def echo_html_fenye_str(rec_num, fenye_num):
'''
生成分页的导航
'''
pagination_num = int(math.ceil(rec_num * 1.0 / 10))
if pagination_num == 1 or pagination_num == 0:
fenye_str = ''
elif pagination_num > 1:
pager_mid, pager_pre, pager_next, pager_last, pager_home = '', '', '', '', ''
fenye_str = '<ul class="pagination">'
if fenye_num > 1:
pager_home = '''<li class="{0}" name='fenye' onclick='change(this);'
value='{1}'><a>First Page</a></li>'''.format('', 1)
pager_pre = ''' <li class="{0}" name='fenye' onclick='change(this);'
value='{1}'><a>Previous Page</a></li>'''.format('', fenye_num - 1)
if fenye_num > 5:
cur_num = fenye_num - 4
else:
cur_num = 1
if pagination_num > 10 and cur_num < pagination_num - 10:
show_num = cur_num + 10
else:
show_num = pagination_num + 1
for num in range(cur_num, show_num):
if num == fenye_num:
checkstr = 'active'
else:
checkstr = ''
tmp_str_df = '''<li class="{0}" name='fenye' onclick='change(this);'
value='{1}'><a>{1}</a></li>'''.format(checkstr, num)
pager_mid += tmp_str_df
if fenye_num < pagination_num:
pager_next = '''<li class="{0}" name='fenye' onclick='change(this);'
value='{1}'><a>Next Page</a></li>'''.format('', fenye_num + 1)
pager_last = '''<li class="{0}" name='fenye' onclick='change(this);'
value='{1}'><a>End Page</a></li>'''.format('', pagination_num)
fenye_str += pager_home + pager_pre + pager_mid + pager_next + pager_last
fenye_str += '</ul>'
else:
return ''
return fenye_str | [
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def _ConvertMapFieldValue(self, value, message, field):
"""Convert map field value for a message map field.
Args:
value: A JSON object to convert the map field value.
message: A protocol message to record the converted data.
field: The descriptor of the map field to be converted.
Raises:
ParseError: In case of convert problems.
"""
if not isinstance(value, dict):
raise ParseError(
'Map field {0} must be in a dict which is {1}.'.format(
field.name, value))
key_field = field.message_type.fields_by_name['key']
value_field = field.message_type.fields_by_name['value']
for key in value:
key_value = _ConvertScalarFieldValue(key, key_field, True)
if value_field.cpp_type == descriptor.FieldDescriptor.CPPTYPE_MESSAGE:
self.ConvertMessage(value[key], getattr(
message, field.name)[key_value])
else:
getattr(message, field.name)[key_value] = _ConvertScalarFieldValue(
value[key], value_field) | [
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def buffer_to_value(self, obj, buffer, offset, default_endianness=DEFAULT_ENDIANNESS):
"""
Converts the bytes in ``buffer`` at ``offset`` to a native Python value. Returns that value and the number of
bytes consumed to create it.
:param obj: The parent :class:`.PebblePacket` of this field
:type obj: .PebblePacket
:param buffer: The buffer from which to extract a value.
:type buffer: bytes
:param offset: The offset in the buffer to start at.
:type offset: int
:param default_endianness: The default endianness of the value. Used if ``endianness`` was not passed to the
:class:`Field` constructor.
:type default_endianness: str
:return: (value, length)
:rtype: (:class:`object`, :any:`int`)
"""
try:
value, length = struct.unpack_from(str(self.endianness or default_endianness)
+ self.struct_format, buffer, offset)[0], struct.calcsize(self.struct_format)
if self._enum is not None:
try:
return self._enum(value), length
except ValueError as e:
raise PacketDecodeError("{}: {}".format(self.type, e))
else:
return value, length
except struct.error as e:
raise PacketDecodeError("{}: {}".format(self.type, e)) | [
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def append_func(self, func, *args, **kwargs):
'''
append func with given arguments and keywords.
'''
wraped_func = partial(func, *args, **kwargs)
self.append(wraped_func) | [
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def cloudshell_model_name(self):
"""Return the name of the CloudShell model"""
if self.shell_name:
return "{shell_name}.{resource_model}".format(shell_name=self.shell_name,
resource_model=self.RESOURCE_MODEL.replace(" ", ""))
else:
return self.RESOURCE_MODEL | [
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def b_fit_score(self, x, y):
""" Computes the cds statistic from variable 1 to variable 2
Args:
a (numpy.ndarray): Variable 1
b (numpy.ndarray): Variable 2
Returns:
float: BF fit score
"""
x = np.reshape(scale(x), (-1, 1))
y = np.reshape(scale(y), (-1, 1))
gp = GaussianProcessRegressor().fit(x, y)
y_predict = gp.predict(x)
error = mean_squared_error(y_predict, y)
return error | [
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def linkify_hostgroups_hosts(self, hosts):
"""We just search for each hostgroup the id of the hosts
and replace the names by the found identifiers
:param hosts: object Hosts
:type hosts: alignak.objects.host.Hosts
:return: None
"""
for hostgroup in self:
members = hostgroup.get_hosts()
# The new members identifiers list
new_members = []
for member in members:
# member is an host name
member = member.strip()
if not member: # void entry, skip this
continue
if member == '*':
# All the hosts identifiers list
new_members.extend(list(hosts.items.keys()))
else:
host = hosts.find_by_name(member)
if host is not None:
new_members.append(host.uuid)
if hostgroup.uuid not in host.hostgroups:
host.hostgroups.append(hostgroup.uuid)
else:
hostgroup.add_unknown_members(member)
# Make members unique
new_members = list(set(new_members))
# We find the id, we replace the names
hostgroup.replace_members(new_members) | [
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def get_request_data(self, var_name, full_data=False):
"""
:param var_name:
:param full_data: If you want `.to_array()` with this data, ready to be sent.
:return: A tuple of `to_array()` dict and the files (:py:func:`InputFile.get_request_files()`).
Files can be None, if no file was given, but an url or existing `file_id`.
If `self.media` is an `InputFile` however,
the first tuple element (either the string, or the dict's `['media']` if `full_data=True`),
will be set to `attach://{var_name}_media` automatically.
If `self.thumb` is an `InputFile` however, the first tuple element's `['thumb']`, will be set to `attach://{var_name}_thumb` automatically.
"""
if not full_data:
raise ArithmeticError('we have a thumbnail, please use `full_data=True`.')
# end if
file = {}
data, file_to_add = super(InputMediaWithThumb, self).get_request_data(var_name, full_data=True)
if file_to_add:
file.update(file_to_add)
# end if
data['thumb'], file_to_add = self.get_inputfile_data(self.thumb, var_name, suffix='_thumb')
if data['thumb'] is None:
del data['thumb'] # having `'thumb': null` in the json produces errors.
# end if
if file_to_add:
file.update(file_to_add)
# end if
return data, (file or None) | [
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def logo(symbol, token='', version=''):
'''This is a helper function, but the google APIs url is standardized.
https://iexcloud.io/docs/api/#logo
8am UTC daily
Args:
symbol (string); Ticker to request
token (string); Access token
version (string); API version
Returns:
dict: result
'''
_raiseIfNotStr(symbol)
return _getJson('stock/' + symbol + '/logo', token, version) | [
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def _to_kraus(rep, data, input_dim, output_dim):
"""Transform a QuantumChannel to the Kraus representation."""
if rep == 'Kraus':
return data
if rep == 'Stinespring':
return _stinespring_to_kraus(data, input_dim, output_dim)
if rep == 'Operator':
return _from_operator('Kraus', data, input_dim, output_dim)
# Convert via Choi and Kraus
if rep != 'Choi':
data = _to_choi(rep, data, input_dim, output_dim)
return _choi_to_kraus(data, input_dim, output_dim) | [
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def logit_px(self)->LogitTensorImage:
"Get logit(image.px)."
if self._logit_px is None: self._logit_px = logit_(self.px)
return self._logit_px | [
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def _parse(args):
"""Parse passed arguments from shell."""
ordered = []
opt_full = dict()
opt_abbrev = dict()
args = args + [''] # Avoid out of range
i = 0
while i < len(args) - 1:
arg = args[i]
arg_next = args[i+1]
if arg.startswith('--'):
if arg_next.startswith('-'):
raise ValueError('{} lacks value'.format(arg))
else:
opt_full[arg[2:]] = arg_next
i += 2
elif arg.startswith('-'):
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raise ValueError('{} lacks value'.format(arg))
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opt_abbrev[arg[1:]] = arg_next
i += 2
else:
ordered.append(arg)
i += 1
return ordered, opt_full, opt_abbrev | [
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def artist(self):
"""
:class:`Artist` object of album's artist
"""
if not self._artist:
self._artist = Artist(self._artist_id, self._artist_name, self._connection)
return self._artist | [
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def fmt_text(text):
""" convert characters that aren't printable to hex format
"""
PRINTABLE_CHAR = set(
list(range(ord(' '), ord('~') + 1)) + [ord('\r'), ord('\n')])
newtext = ("\\x{:02X}".format(
c) if c not in PRINTABLE_CHAR else chr(c) for c in text)
textlines = "\r\n".join(l.strip('\r')
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def extract(args):
"""
%prog extract idsfile sizesfile
Extract the lines containing only the given IDs.
"""
p = OptionParser(extract.__doc__)
opts, args = p.parse_args(args)
if len(args) != 2:
sys.exit(not p.print_help())
idsfile, sizesfile = args
sizes = Sizes(sizesfile).mapping
fp = open(idsfile)
for row in fp:
name = row.strip()
size = sizes[name]
print("\t".join(str(x) for x in (name, size))) | [
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def execute_notebook(self, name):
"""Loads and then runs a notebook file."""
warnings.filterwarnings("ignore", category=DeprecationWarning)
nb,f = self.load_notebook(name)
self.run_notebook(nb,f)
self.assertTrue(True) | [
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def async_command(self, command, raw=False, timeout_ms=None):
"""See shell_service.ShellService.async_command()."""
return self.shell_service.async_command(
str(command), raw=raw, timeout_ms=timeout_ms) | [
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def update_dashboards(modules, horizon_config, installed_apps):
"""Imports dashboard and panel configuration from modules and applies it.
The submodules from specified modules are imported, and the configuration
for the specific dashboards is merged, with the later modules overriding
settings from the former. Then the configuration is applied to
horizon_config and installed_apps, in alphabetical order of files from
which the configurations were imported.
For example, given this setup:
| foo/__init__.py
| foo/_10_baz.py
| foo/_20_qux.py
| bar/__init__.py
| bar/_30_baz_.py
and being called with ``modules=[foo, bar]``, we will first have the
configuration from ``_10_baz`` and ``_30_baz`` merged, then the
configurations will be applied in order ``qux``, ``baz`` (``baz`` is
second, because the most recent file which contributed to it, ``_30_baz``,
comes after ``_20_qux``).
Panel specific configurations are stored in horizon_config. Dashboards
from both plugin-based and openstack_dashboard must be registered before
the panel configuration can be applied. Making changes to the panel is
deferred until the horizon autodiscover is completed, configurations are
applied in alphabetical order of files where it was imported.
"""
config_dashboards = horizon_config.get('dashboards', [])
if config_dashboards or horizon_config.get('default_dashboard'):
logging.warning(
'"dashboards" and "default_dashboard" in (local_)settings is '
'DEPRECATED now and may be unsupported in some future release. '
'The preferred way to specify the order of dashboards and the '
'default dashboard is the pluggable dashboard mechanism (in %s).',
', '.join([os.path.abspath(module.__path__[0])
for module in modules])
)
enabled_dashboards = []
disabled_dashboards = []
exceptions = horizon_config.get('exceptions', {})
apps = []
angular_modules = []
js_files = []
js_spec_files = []
scss_files = []
xstatic_modules = []
panel_customization = []
header_sections = []
extra_tabs = collections.defaultdict(tuple)
extra_steps = collections.defaultdict(tuple)
update_horizon_config = {}
for key, config in import_dashboard_config(modules):
if config.get('DISABLED', False):
if config.get('DASHBOARD'):
disabled_dashboards.append(config.get('DASHBOARD'))
continue
_apps = config.get('ADD_INSTALLED_APPS', [])
apps.extend(_apps)
_header_sections = config.get('ADD_HEADER_SECTIONS', [])
header_sections.extend(_header_sections)
if config.get('AUTO_DISCOVER_STATIC_FILES', False):
for _app in _apps:
module = import_module(_app)
base_path = os.path.join(module.__path__[0], 'static/')
file_discovery.populate_horizon_config(horizon_config,
base_path)
add_exceptions = config.get('ADD_EXCEPTIONS', {}).items()
for category, exc_list in add_exceptions:
exceptions[category] = tuple(set(exceptions.get(category, ()) +
exc_list))
angular_modules.extend(config.get('ADD_ANGULAR_MODULES', []))
# avoid pulling in dashboard javascript dependencies multiple times
existing = set(js_files)
js_files.extend([f for f in config.get('ADD_JS_FILES', [])
if f not in existing])
js_spec_files.extend(config.get('ADD_JS_SPEC_FILES', []))
scss_files.extend(config.get('ADD_SCSS_FILES', []))
xstatic_modules.extend(config.get('ADD_XSTATIC_MODULES', []))
update_horizon_config.update(
config.get('UPDATE_HORIZON_CONFIG', {}))
if config.get('DASHBOARD'):
dashboard = key
enabled_dashboards.append(dashboard)
if config.get('DEFAULT', False):
horizon_config['default_dashboard'] = dashboard
elif config.get('PANEL') or config.get('PANEL_GROUP'):
config.pop("__builtins__", None)
panel_customization.append(config)
_extra_tabs = config.get('EXTRA_TABS', {})
for tab_key, tab_defs in _extra_tabs.items():
extra_tabs[tab_key] += tuple(tab_defs)
_extra_steps = config.get('EXTRA_STEPS', {})
for step_key, step_defs in _extra_steps.items():
extra_steps[step_key] += tuple(step_defs)
# Preserve the dashboard order specified in settings
dashboards = ([d for d in config_dashboards
if d not in disabled_dashboards] +
[d for d in enabled_dashboards
if d not in config_dashboards])
horizon_config['panel_customization'] = panel_customization
horizon_config['header_sections'] = header_sections
horizon_config['dashboards'] = tuple(dashboards)
horizon_config.setdefault('exceptions', {}).update(exceptions)
horizon_config.update(update_horizon_config)
horizon_config.setdefault('angular_modules', []).extend(angular_modules)
horizon_config.setdefault('js_files', []).extend(js_files)
horizon_config.setdefault('js_spec_files', []).extend(js_spec_files)
horizon_config.setdefault('scss_files', []).extend(scss_files)
horizon_config.setdefault('xstatic_modules', []).extend(xstatic_modules)
horizon_config['extra_tabs'] = extra_tabs
horizon_config['extra_steps'] = extra_steps
# apps contains reference to applications declared in the enabled folder
# basically a list of applications that are internal and external plugins
# installed_apps contains reference to applications declared in settings
# such as django.contribe.*, django_pyscss, compressor, horizon, etc...
# for translation, we are only interested in the list of external plugins
# so we save the reference to it before we append to installed_apps
horizon_config.setdefault('plugins', []).extend(apps)
installed_apps[0:0] = apps | [
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] | 46.661538 | 21.538462 |
def anonymous_login(services):
"""Initialize services without authenticating to Globus Auth.
Note:
Clients may have reduced functionality without authentication.
Arguments:
services (str or list of str): The services to initialize clients for.
Returns:
dict: The clients requested, indexed by service name.
"""
if isinstance(services, str):
services = [services]
clients = {}
# Initialize valid services
for serv in services:
try:
clients[serv] = KNOWN_CLIENTS[serv](http_timeout=STD_TIMEOUT)
except KeyError: # No known client
print("Error: No known client for '{}' service.".format(serv))
except Exception: # Other issue, probably auth
print("Error: Unable to create client for '{}' service.\n"
"Anonymous access may not be allowed.".format(serv))
return clients | [
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def Message(msg, id=260, ok=None):
"""Original doc: Display a MESSAGE string.
Return when the user clicks the OK button or presses Return.
The MESSAGE string can be at most 255 characters long.
"""
return psidialogs.message(message=msg, ok=ok) | [
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def do_state_tomography(preparation_program, nsamples, cxn, qubits=None, use_run=False):
"""
Method to perform both a QPU and QVM state tomography, and use the latter as
as reference to calculate the fidelity of the former.
:param Program preparation_program: Program to execute.
:param int nsamples: Number of samples to take for the program.
:param QVMConnection|QPUConnection cxn: Connection on which to run the program.
:param list qubits: List of qubits for the program.
to use in the tomography analysis.
:param bool use_run: If ``True``, use append measurements on all qubits and use ``cxn.run``
instead of ``cxn.run_and_measure``.
:return: The state tomogram.
:rtype: StateTomography
"""
return tomography._do_tomography(preparation_program, nsamples, cxn, qubits,
tomography.MAX_QUBITS_STATE_TOMO,
StateTomography, state_tomography_programs,
DEFAULT_STATE_TOMO_SETTINGS, use_run=use_run) | [
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def finalize(self) -> None:
''' split statement and task by last directive '''
self.wrap_script()
if not self.statements:
self.task = ''
return
# handle tasks
input_directive = [
idx for idx, statement in enumerate(self.statements)
if statement[0] == ':' and statement[1] == 'input'
]
task_directive = [
idx for idx, statement in enumerate(self.statements)
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]
if len(task_directive) > 1:
raise ValueError('Only one task statement is allowed in a step')
# handle parameter
for idx, statement in enumerate(self.statements):
if statement[0] == ':' and statement[1] == 'parameter':
if task_directive and task_directive[0] < idx:
raise ValueError(
'Parameter statement is not allowed in tasks.')
if '=' not in statement[2]:
if ':' in statement[2]:
if not is_type_hint(statement[2]):
raise ValueError(
f'Invalid type trait in parameter specification {statement[2]}'
)
name, value = statement[2].split(':')
else:
name = statement[2]
value = 'str'
else:
name, value = statement[2].split('=', 1)
# ignore type trait if a default value is specified
name = name.split(':')[0]
name = name.strip()
if name.startswith('_'):
raise ValueError(
f'Invalid parameter name {name}: names with leading underscore is not allowed.'
)
if not value.strip():
raise ValueError(
f'{self.step_name()}: Invalid parameter definition: {statement[2]}'
)
# there is a possibility that value contains # so sos_handle_parameter(name, val # aaa) will fail
self.statements[idx] = [
'!',
f'#begin_parameter {name}\n{name} = sos_handle_parameter_({name.strip()!r}, {value}\n) #end_parameter {name}\n',
statement[2].strip()
]
self.parameters[name] = (value, statement[3])
if input_directive and input_directive[0] < idx:
self.substep_parameters.add(name)
# handle tasks
if not task_directive:
self.task = ''
else:
start_task = task_directive[0] + 1
# convert statement to task
self.task = ''
for statement in self.statements[start_task:]:
if statement[0] == ':':
if statement[1] in ('input', 'output', 'depends'):
raise ValueError(
f'{self.step_name()}: Step task should be defined as the last item in a SoS step'
)
elif statement[1] == 'task':
raise ValueError(
f'{self.step_name()}: Only one task is allowed for a step'
)
elif statement[1] == 'parameter':
raise ValueError(
f'{self.step_name()}: Parameters should be defined before step task'
)
# ignore ...
self.task += '\n'
else:
self.task += statement[1]
self.task_params = self.statements[task_directive[0]][2]
self.statements = self.statements[:task_directive[0]]
# merge multiple statments at the end
if len(self.statements) > 1 and self.statements[-1][0] == '!':
starting = len(self.statements) - 1
for idx in range(starting - 1, -1, -1):
if self.statements[idx][0] == '!':
starting = idx
else:
break
# merge
for idx in range(starting + 1, len(self.statements)):
self.statements[starting][1] += self.statements[idx][1]
# remove the rest of the statements
self.statements = self.statements[:starting + 1]
#
# auto provides #859
if not any(opt in self.options for opt in ('provides', 'shared')) and \
len([x for x in self.statements if x[0] == ':' and x[1] == 'output']) == 1:
output_stmt = [
x for x in self.statements if x[0] == ':' and x[1] == 'output'
][0][2]
output_names = get_names_of_kwargs(output_stmt)
self.options['namedprovides'] = repr(output_names) | [
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] | 47 | 19.269231 |
def get_witness(self, work, siglum, text_class=WitnessText):
"""Returns a `WitnessText` representing the file associated with
`work` and `siglum`.
Combined, `work` and `siglum` form the basis of a filename for
retrieving the text.
:param work: name of work
:type work: `str`
:param siglum: siglum of witness
:type siglum: `str`
:rtype: `WitnessText`
"""
filename = os.path.join(work, siglum + '.txt')
self._logger.debug('Creating WitnessText object from {}'.format(
filename))
with open(os.path.join(self._path, filename), encoding='utf-8') \
as fh:
content = fh.read()
return text_class(work, siglum, content, self._tokenizer) | [
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def get_resource_ids(self):
"""
Get resource ids as a list.
:return: List of resource id:s or "unknown"
"""
resids = []
if self.dutinformations:
for info in self.dutinformations:
resids.append(info.resource_id)
return resids
return "unknown" | [
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def plot_covariance(
mean, cov=None, variance=1.0, std=None, interval=None,
ellipse=None, title=None, axis_equal=True,
show_semiaxis=False, show_center=True,
facecolor=None, edgecolor=None,
fc='none', ec='#004080',
alpha=1.0, xlim=None, ylim=None,
ls='solid'):
"""
Plots the covariance ellipse for the 2D normal defined by (mean, cov)
`variance` is the normal sigma^2 that we want to plot. If list-like,
ellipses for all ellipses will be ploted. E.g. [1,2] will plot the
sigma^2 = 1 and sigma^2 = 2 ellipses. Alternatively, use std for the
standard deviation, in which case `variance` will be ignored.
ellipse is a (angle,width,height) tuple containing the angle in radians,
and width and height radii.
You may provide either cov or ellipse, but not both.
Parameters
----------
mean : row vector like (2x1)
The mean of the normal
cov : ndarray-like
2x2 covariance matrix
variance : float, default 1, or iterable float, optional
Variance of the plotted ellipse. May specify std or interval instead.
If iterable, such as (1, 2**2, 3**2), then ellipses will be drawn
for all in the list.
std : float, or iterable float, optional
Standard deviation of the plotted ellipse. If specified, variance
is ignored, and interval must be `None`.
If iterable, such as (1, 2, 3), then ellipses will be drawn
for all in the list.
interval : float range [0,1), or iterable float, optional
Confidence interval for the plotted ellipse. For example, .68 (for
68%) gives roughly 1 standand deviation. If specified, variance
is ignored and `std` must be `None`
If iterable, such as (.68, .95), then ellipses will be drawn
for all in the list.
ellipse: (float, float, float)
Instead of a covariance, plots an ellipse described by (angle, width,
height), where angle is in radians, and the width and height are the
minor and major sub-axis radii. `cov` must be `None`.
title: str, optional
title for the plot
axis_equal: bool, default=True
Use the same scale for the x-axis and y-axis to ensure the aspect
ratio is correct.
show_semiaxis: bool, default=False
Draw the semiaxis of the ellipse
show_center: bool, default=True
Mark the center of the ellipse with a cross
facecolor, fc: color, default=None
If specified, fills the ellipse with the specified color. `fc` is an
allowed abbreviation
edgecolor, ec: color, default=None
If specified, overrides the default color sequence for the edge color
of the ellipse. `ec` is an allowed abbreviation
alpha: float range [0,1], default=1.
alpha value for the ellipse
xlim: float or (float,float), default=None
specifies the limits for the x-axis
ylim: float or (float,float), default=None
specifies the limits for the y-axis
ls: str, default='solid':
line style for the edge of the ellipse
"""
from matplotlib.patches import Ellipse
import matplotlib.pyplot as plt
if cov is not None and ellipse is not None:
raise ValueError('You cannot specify both cov and ellipse')
if cov is None and ellipse is None:
raise ValueError('Specify one of cov or ellipse')
if facecolor is None:
facecolor = fc
if edgecolor is None:
edgecolor = ec
if cov is not None:
ellipse = covariance_ellipse(cov)
if axis_equal:
plt.axis('equal')
if title is not None:
plt.title(title)
ax = plt.gca()
angle = np.degrees(ellipse[0])
width = ellipse[1] * 2.
height = ellipse[2] * 2.
std = _std_tuple_of(variance, std, interval)
for sd in std:
e = Ellipse(xy=mean, width=sd*width, height=sd*height, angle=angle,
facecolor=facecolor,
edgecolor=edgecolor,
alpha=alpha,
lw=2, ls=ls)
ax.add_patch(e)
x, y = mean
if show_center:
plt.scatter(x, y, marker='+', color=edgecolor)
if xlim is not None:
ax.set_xlim(xlim)
if ylim is not None:
ax.set_ylim(ylim)
if show_semiaxis:
a = ellipse[0]
h, w = height/4, width/4
plt.plot([x, x+ h*cos(a+np.pi/2)], [y, y + h*sin(a+np.pi/2)])
plt.plot([x, x+ w*cos(a)], [y, y + w*sin(a)]) | [
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] | 30.479167 | 21.868056 |
def abspath(cur_file, parent=0) -> str:
"""
Absolute path
Args:
cur_file: __file__ or file or path str
parent: level of parent to look for
Returns:
str
"""
file_path = os.path.abspath(cur_file).replace('\\', '/')
if os.path.isdir(file_path) and parent == 0: return file_path
adj = 1 - os.path.isdir(file_path)
return '/'.join(file_path.split('/')[:-(parent + adj)]) | [
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def inverted(values, input_min=0, input_max=1):
"""
Returns the inversion of the supplied values (*input_min* becomes
*input_max*, *input_max* becomes *input_min*, `input_min + 0.1` becomes
`input_max - 0.1`, etc.). All items in *values* are assumed to be between
*input_min* and *input_max* (which default to 0 and 1 respectively), and
the output will be in the same range. For example::
from gpiozero import MCP3008, PWMLED
from gpiozero.tools import inverted
from signal import pause
led = PWMLED(4)
pot = MCP3008(channel=0)
led.source = inverted(pot)
pause()
"""
values = _normalize(values)
if input_min >= input_max:
raise ValueError('input_min must be smaller than input_max')
for v in values:
yield input_min + input_max - v | [
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def export_avg_losses(ekey, dstore):
"""
:param ekey: export key, i.e. a pair (datastore key, fmt)
:param dstore: datastore object
"""
dskey = ekey[0]
oq = dstore['oqparam']
dt = oq.loss_dt()
name, value, tags = _get_data(dstore, dskey, oq.hazard_stats().items())
writer = writers.CsvWriter(fmt=writers.FIVEDIGITS)
assets = get_assets(dstore)
for tag, values in zip(tags, value.transpose(1, 0, 2)):
dest = dstore.build_fname(name, tag, 'csv')
array = numpy.zeros(len(values), dt)
for l, lt in enumerate(dt.names):
array[lt] = values[:, l]
writer.save(compose_arrays(assets, array), dest)
return writer.getsaved() | [
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def str(password,
opslimit=OPSLIMIT_INTERACTIVE,
memlimit=MEMLIMIT_INTERACTIVE):
"""
Hashes a password with a random salt, using the memory-hard
argon2i construct and returning an ascii string that has all
the needed info to check against a future password
The default settings for opslimit and memlimit are those deemed
correct for the interactive user login case.
:param bytes password:
:param int opslimit:
:param int memlimit:
:rtype: bytes
.. versionadded:: 1.2
"""
return nacl.bindings.crypto_pwhash_str_alg(password,
opslimit,
memlimit,
ALG) | [
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def _inputcooker_store(self, char):
"""Put the cooked data in the correct queue"""
if self.sb:
self.sbdataq = self.sbdataq + char
else:
self.inputcooker_store_queue(char) | [
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def gemini_writer(self, f_handle):
"""
Write out a GEMINI formated OT ephemeris. This is just a hack of SSD Horizons output.
"""
f_handle.write(GEMINI_HEADER)
# Date__(UT)__HR:MN Date_________JDUT R.A.___(ICRF/J2000.0)___DEC dRA*cosD d(DEC)/dt
# 1 2 3 4 5 6 7 8 9
# 123456789012345678901234567890123456789012345678901234567890123456789012345678901234567890
# ' 2019-Jan-30 00:00 01 46 56.46 +10 28 54.9 01 47 56.17 +10 34 27.6 3.520
for coordinate in self.coordinates:
date = coordinate.obstime.datetime.strftime('%Y-%b-%d %H:%M')[:17]
f_handle.write(" {:16} {:17.9f} {:27} {:+8.5f} {:+8.5f}\n".format(date,
coordinate.obstime.jd,
coordinate.to_string('hmsdms',
sep=' ',
precision=4,
pad=True)[:27],
float(coordinate.dra),
float(coordinate.ddec)),
)
f_handle.write(GEMINI_FOOTER)
return | [
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def _get_object_as_soft(self):
"""Return object as SOFT formatted string."""
soft = []
if self.database is not None:
soft.append(self.database._get_object_as_soft())
soft += ["^%s = %s" % (self.geotype, self.name),
self._get_metadata_as_string()]
for subset in self.subsets.values():
soft.append(subset._get_object_as_soft())
soft += ["^%s = %s" % (self.geotype, self.name),
self._get_columns_as_string(),
self._get_table_as_string()]
return "\n".join(soft) | [
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def __load_project(path):
'''
Load a docker-compose project from path
:param path:
:return:
'''
file_path = __get_docker_file_path(path)
if file_path is None:
msg = 'Could not find docker-compose file at {0}'.format(path)
return __standardize_result(False,
msg,
None, None)
return __load_project_from_file_path(file_path) | [
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def get_unique_families(hkls):
"""
Returns unique families of Miller indices. Families must be permutations
of each other.
Args:
hkls ([h, k, l]): List of Miller indices.
Returns:
{hkl: multiplicity}: A dict with unique hkl and multiplicity.
"""
# TODO: Definitely can be sped up.
def is_perm(hkl1, hkl2):
h1 = np.abs(hkl1)
h2 = np.abs(hkl2)
return all([i == j for i, j in zip(sorted(h1), sorted(h2))])
unique = collections.defaultdict(list)
for hkl1 in hkls:
found = False
for hkl2 in unique.keys():
if is_perm(hkl1, hkl2):
found = True
unique[hkl2].append(hkl1)
break
if not found:
unique[hkl1].append(hkl1)
pretty_unique = {}
for k, v in unique.items():
pretty_unique[sorted(v)[-1]] = len(v)
return pretty_unique | [
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def to_cartesian(r, theta, theta_units="radians"):
"""
Converts polar r, theta to cartesian x, y.
"""
assert theta_units in ['radians', 'degrees'],\
"kwarg theta_units must specified in radians or degrees"
# Convert to radians
if theta_units == "degrees":
theta = to_radians(theta)
theta = to_proper_radians(theta)
x = r * cos(theta)
y = r * sin(theta)
return x, y | [
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def vms(message, level=1):
"""Writes the specified message *only* if verbose output is enabled."""
if verbose is not None and verbose != False:
if isinstance(verbose, bool) or (isinstance(verbose, int) and level <= verbose):
std(message) | [
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def search(geo_coords, mode=2, verbose=True):
"""
Function to query for a list of coordinates
"""
if not isinstance(geo_coords, tuple) and not isinstance(geo_coords, list):
raise TypeError('Expecting a tuple or a tuple/list of tuples')
elif not isinstance(geo_coords[0], tuple):
geo_coords = [geo_coords]
_rg = RGeocoder(mode=mode, verbose=verbose)
return _rg.query(geo_coords) | [
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def handle_error(self, failure):
"""
Provides basic error information for bad requests.
If the error was an HttpError or DNSLookupError, it
prints more specific information.
"""
self.logger.error(repr(failure))
if failure.check(HttpError):
response = failure.value.response
self.logger.error(u'HttpError on %s', response.url)
self.logger.error(u'HttpError Code: %s', response.status)
if response.status in (401, 403):
# If the error is from invalid login, tell the user
self.logger.error(
"Credentials failed. Either add/update the current credentials "
"or remove them to enable auto auth"
)
elif failure.check(DNSLookupError):
request = failure.request
self.logger.error(u'DNSLookupError on %s', request.url) | [
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def hlen(key, host=None, port=None, db=None, password=None):
'''
Returns number of fields of a hash.
.. versionadded:: 2017.7.0
CLI Example:
.. code-block:: bash
salt '*' redis.hlen foo_hash
'''
server = _connect(host, port, db, password)
return server.hlen(key) | [
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def aboveAt(self, offset=0):
""" Returns point in the center of the region's top side (offset to the top
by negative ``offset``) """
return Location(self.getX() + (self.getW() / 2), self.getY() + offset) | [
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def create_apply_graph(self, signature, input_tensors, name):
"""See `ModuleImpl.create_apply_graph`."""
signature_def = self._meta_graph.signature_def.get(signature)
meta_graph = meta_graph_pb2.MetaGraphDef()
meta_graph.CopyFrom(self._meta_graph)
apply_graph = tf_v1.get_default_graph()
infeed_map = tensor_info.build_input_map(signature_def.inputs,
input_tensors)
# Build a input map to feed when importing the apply-graph by augmenting the
# state_map with the input args. This allows an input to override a tensor
# from the state-graph.
feed_map = dict(self._state_map)
# If we are applying the module in a function with a TPUReplicateContext, we
# must capture the state tensors in generating our feedmap and prune out
# assign ops. Function graph semantics are different in that all ops are
# executed regardless of dependency.
# TODO(b/112575006): The following adds functionality of function call
# within a TPU context. Work to generalize this for all function calls is
# ongoing.
if self._is_tpu_graph_function():
for k, v in self._state_map.items():
feed_map[k] = apply_graph.capture(v)
meta_graph_lib.prune_unused_nodes(meta_graph, signature_def)
# After we prune the metagraph def, we might need to prune away
# infeeds which no longer exist.
meta_graph_lib.prune_feed_map(meta_graph, infeed_map)
elif apply_graph.building_function:
raise NotImplementedError(
"Using TF-Hub module within a TensorFlow defined function "
"is currently not supported.")
# As state ops in the apply graph are unused, replace them with Placeholders
# so that in a heirarchical instantiation, apply_graph state ops are
# ignored.
replace_apply_state(meta_graph,
list_registered_stateful_ops_without_inputs(), feed_map)
feed_map.update(infeed_map)
# Make state tensors enter the current context. This way the Module can be
# applied inside a control flow structure such as a while_loop.
control_flow = apply_graph._get_control_flow_context() # pylint: disable=protected-access
if control_flow:
for key, value in sorted(feed_map.items()):
feed_map[key] = control_flow.AddValue(value)
# Don't mark the name as used at this point - import_scoped_meta_graph will
# start using it.
absolute_scope_name = apply_graph.unique_name(name, mark_as_used=False)
relative_scope_name = absolute_scope_name.split("/")[-1]
import_collections = [
# In most cases ASSET_FILEPATHS are only used for the TABLE_INITIALIZERS
# ops, however one could create a graph that uses an asset at any other
# time. As so everytime we bring the tensor with that has the asset
# filename we must annotate it as so, so later re-exports have that
# semantic information and can handle it.
tf_v1.GraphKeys.ASSET_FILEPATHS,
tf_v1.GraphKeys.COND_CONTEXT,
tf_v1.GraphKeys.WHILE_CONTEXT,
]
if self._trainable:
import_collections.extend([tf_v1.GraphKeys.UPDATE_OPS])
meta_graph_lib.filter_collections(meta_graph, import_collections)
meta_graph_lib.prefix_shared_name_attributes(meta_graph,
absolute_scope_name)
if len(meta_graph.collection_def) and self._is_tpu_graph_function():
raise NotImplementedError(
"Applying modules with collections inside TPU functions is not "
"supported.")
tf_v1.train.import_meta_graph(
meta_graph,
input_map=feed_map,
import_scope=relative_scope_name)
fix_colocation_after_import(input_map=feed_map,
absolute_import_scope=absolute_scope_name)
def get_tensor(name):
# When trying to output an input tensor there are no nodes created within
# the apply scope. So one must look into the input map.
try:
return feed_map[name]
except KeyError:
return apply_graph.get_tensor_by_name(
meta_graph_lib.prepend_name_scope(
name, import_scope=absolute_scope_name))
return tensor_info.build_output_map(signature_def.outputs, get_tensor) | [
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def expose_event(self, widget, event):
"""When an area of the window is exposed, we just copy out of the
server-side, off-screen surface to that area.
"""
x, y, width, height = event.area
self.logger.debug("surface is %s" % self.surface)
if self.surface is not None:
win = widget.get_window()
cr = win.cairo_create()
# set clip area for exposed region
cr.rectangle(x, y, width, height)
cr.clip()
# Paint from off-screen surface
cr.set_source_surface(self.surface, 0, 0)
cr.set_operator(cairo.OPERATOR_SOURCE)
cr.paint()
return False | [
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def _GetVSSStoreIdentifiers(self, scan_node):
"""Determines the VSS store identifiers.
Args:
scan_node (SourceScanNode): scan node.
Returns:
list[str]: VSS store identifiers.
Raises:
ScannerError: if the format the scan node is invalid or no mediator
is provided and VSS store identifiers are found.
UserAbort: if the user requested to abort.
"""
if not scan_node or not scan_node.path_spec:
raise errors.ScannerError('Invalid scan node.')
volume_system = vshadow_volume_system.VShadowVolumeSystem()
volume_system.Open(scan_node.path_spec)
volume_identifiers = self._source_scanner.GetVolumeIdentifiers(
volume_system)
if not volume_identifiers:
return []
if not self._mediator:
raise errors.ScannerError(
'Unable to proceed. VSS stores found but no mediator to determine '
'how they should be used.')
try:
volume_identifiers = self._mediator.GetVSSStoreIdentifiers(
volume_system, volume_identifiers)
except KeyboardInterrupt:
raise errors.UserAbort('File system scan aborted.')
return self._NormalizedVolumeIdentifiers(
volume_system, volume_identifiers, prefix='vss') | [
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def repeat_nd(a, repeats):
"""Return read-only view into input array with elements repeated.
Zoom nD image by integer factors using nearest neighbor interpolation
(box filter).
Parameters
----------
a : array_like
Input array.
repeats : sequence of int
The number of repetitions to apply along each dimension of input array.
Examples
--------
>>> repeat_nd([[1, 2], [3, 4]], (2, 2))
array([[1, 1, 2, 2],
[1, 1, 2, 2],
[3, 3, 4, 4],
[3, 3, 4, 4]])
"""
a = numpy.asarray(a)
reshape = []
shape = []
strides = []
for i, j, k in zip(a.strides, a.shape, repeats):
shape.extend((j, k))
strides.extend((i, 0))
reshape.append(j * k)
return numpy.lib.stride_tricks.as_strided(
a, shape, strides, writeable=False).reshape(reshape) | [
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def oauth2(self):
"""
returns the oauth2 class
"""
if self._url.endswith("/oauth2"):
url = self._url
else:
url = self._url + "/oauth2"
return _oauth2.oauth2(oauth_url=url,
securityHandler=self._securityHandler,
proxy_url=self._proxy_url,
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def _format_list(self, extracted_list):
"""Format a list of traceback entry tuples for printing.
Given a list of tuples as returned by extract_tb() or
extract_stack(), return a list of strings ready for printing.
Each string in the resulting list corresponds to the item with the
same index in the argument list. Each string ends in a newline;
the strings may contain internal newlines as well, for those items
whose source text line is not None.
Lifted almost verbatim from traceback.py
"""
Colors = self.Colors
list = []
for filename, lineno, name, line in extracted_list[:-1]:
item = ' File %s"%s"%s, line %s%d%s, in %s%s%s\n' % \
(Colors.filename, filename, Colors.Normal,
Colors.lineno, lineno, Colors.Normal,
Colors.name, name, Colors.Normal)
if line:
item += ' %s\n' % line.strip()
list.append(item)
# Emphasize the last entry
filename, lineno, name, line = extracted_list[-1]
item = '%s File %s"%s"%s, line %s%d%s, in %s%s%s%s\n' % \
(Colors.normalEm,
Colors.filenameEm, filename, Colors.normalEm,
Colors.linenoEm, lineno, Colors.normalEm,
Colors.nameEm, name, Colors.normalEm,
Colors.Normal)
if line:
item += '%s %s%s\n' % (Colors.line, line.strip(),
Colors.Normal)
list.append(item)
#from pprint import pformat; print 'LISTTB', pformat(list) # dbg
return list | [
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"#from pprint import pformat; print 'LISTTB', pformat(list) # dbg",
"return",
"list"
] | 44.621622 | 19.297297 |
def delete_db_instance(self, dbid):
''' Delete DB '''
if not self.connect_to_aws_rds():
return False
try:
database = self.rdsc.delete_dbinstance(dbid,
skip_final_snapshot=True)
print database
except:
return False
else:
return True | [
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def is_bridge(self):
"""bool: Is this zone a bridge?"""
# Since this does not change over time (?) check whether we already
# know the answer. If so, there is no need to go further
if self._is_bridge is not None:
return self._is_bridge
# if not, we have to get it from the zone topology. This will set
# self._is_bridge for us for next time, so we won't have to do this
# again
self._parse_zone_group_state()
return self._is_bridge | [
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def register_column(self,
column,
expr,
deltas=None,
checkpoints=None,
odo_kwargs=None):
"""Explicitly map a single bound column to a collection of blaze
expressions. The expressions need to have ``timestamp`` and ``as_of``
columns.
Parameters
----------
column : BoundColumn
The pipeline dataset to map to the given expressions.
expr : Expr
The baseline values.
deltas : Expr, optional
The deltas for the data.
checkpoints : Expr, optional
The forward fill checkpoints for the data.
odo_kwargs : dict, optional
The keyword arguments to forward to the odo calls internally.
See Also
--------
:func:`zipline.pipeline.loaders.blaze.from_blaze`
"""
self._table_expressions[column] = ExprData(
expr,
deltas,
checkpoints,
odo_kwargs,
) | [
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async def _redirect(self, response_obj):
'''
Calls the _check_redirect method of the supplied response object
in order to determine if the http status code indicates a redirect.
Returns:
Response: May or may not be the result of recursive calls due
to redirects!
Notes:
If it does redirect, it calls the appropriate method with the
redirect location, returning the response object. Furthermore,
if there is a redirect, this function is recursive in a roundabout
way, storing the previous response object in `.history_objects`.
'''
redirect, force_get, location = False, None, None
if 300 <= response_obj.status_code < 400:
if response_obj.status_code == 303:
self.data, self.json, self.files = None, None, None
if response_obj.status_code in [301, 305]:
# redirect / force GET / location
redirect = True
force_get = False
else:
redirect = True
force_get = True
location = response_obj.headers['Location']
if redirect:
allow_redirect = True
redirect_uri = urlparse(location.strip())
# relative redirect
if not redirect_uri.netloc:
self.uri = urlunparse(
(self.scheme, self.host, *redirect_uri[2:]))
# absolute-redirect
else:
location = location.strip()
if self.auth is not None:
if not self.auth_off_domain:
allow_redirect = self._location_auth_protect(location)
self.uri = location
l_scheme, l_netloc, *_ = urlparse(location)
if l_scheme != self.scheme or l_netloc != self.host:
await self._get_new_sock()
# follow redirect with correct http method type
if force_get:
self.history_objects.append(response_obj)
self.method = 'GET'
else:
self.history_objects.append(response_obj)
self.max_redirects -= 1
try:
if response_obj.headers['connection'].lower() == 'close':
await self._get_new_sock()
except KeyError:
pass
if allow_redirect:
_, response_obj = await self.make_request()
return response_obj | [
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] | 39.492063 | 19.238095 |
def reread(self):
"""
Read and parse credentials file.
If something goes wrong, log exception and continue.
"""
logger.debug("Loading credentials from %s",
os.path.abspath(self.creds_filename))
creds = {}
try:
with self.open_creds() as fp:
creds = yaml.safe_load(fp)
except IOError:
logger.info("No credentials file found at %s",
os.path.abspath(self.creds_filename))
except:
logger.exception("Error loading credentials file")
if creds != self.creds:
self.creds = creds
return True
return False | [
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] | 34.2 | 14.2 |
def fullversion():
'''
Return all server information from catalina.sh version
CLI Example:
.. code-block:: bash
salt '*' tomcat.fullversion
'''
cmd = __catalina_home() + '/bin/catalina.sh version'
ret = {}
out = __salt__['cmd.run'](cmd).splitlines()
for line in out:
if not line:
continue
if ': ' in line:
comps = line.split(': ')
ret[comps[0]] = comps[1].lstrip()
return ret | [
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] | 22.95 | 21.65 |
def serialize(obj):
"""JSON serializer that accepts datetime & date"""
from datetime import datetime, date, time
if isinstance(obj, date) and not isinstance(obj, datetime):
obj = datetime.combine(obj, time.min)
if isinstance(obj, datetime):
return obj.isoformat() | [
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def formatter_help(cls):
""" Return a list of format specifiers and their documentation.
"""
result = [("raw", "Switch off the default field formatter.")]
for name, method in globals().items():
if name.startswith("fmt_"):
result.append((name[4:], method.__doc__.strip()))
return result | [
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def illumg(method, target, ilusrc, et, fixref, abcorr, obsrvr, spoint):
"""
Find the illumination angles (phase, incidence, and
emission) at a specified surface point of a target body.
The surface of the target body may be represented by a triaxial
ellipsoid or by topographic data provided by DSK files.
The illumination source is a specified ephemeris object.
param method: Computation method.
https://naif.jpl.nasa.gov/pub/naif/toolkit_docs/C/cspice/illumg_c.html
:type method: str
:param target: Name of target body.
:type target: str
:param ilusrc: Name of illumination source.
:type ilusrc: str
:param et: Epoch in ephemeris seconds past J2000.
:type et: float
:param fixref: Body-fixed, body-centered target body frame.
:type fixref: str
:param abcorr: Desired aberration correction.
:type abcorr: str
:param obsrvr: Name of observing body.
:type obsrvr: str
:param spoint: Body-fixed coordinates of a target surface point.
:type spoint: 3-Element Array of floats
:return: Target surface point epoch, Vector from observer to target
surface point, Phase angle at the surface point, Source incidence
angle at the surface point, Emission angle at the surface point,
:rtype: tuple
"""
method = stypes.stringToCharP(method)
target = stypes.stringToCharP(target)
ilusrc = stypes.stringToCharP(ilusrc)
et = ctypes.c_double(et)
fixref = stypes.stringToCharP(fixref)
abcorr = stypes.stringToCharP(abcorr)
obsrvr = stypes.stringToCharP(obsrvr)
spoint = stypes.toDoubleVector(spoint)
trgepc = ctypes.c_double(0)
srfvec = stypes.emptyDoubleVector(3)
phase = ctypes.c_double(0)
incdnc = ctypes.c_double(0)
emissn = ctypes.c_double(0)
libspice.illumg_c(method, target, ilusrc, et, fixref, abcorr, obsrvr, spoint,
ctypes.byref(trgepc), srfvec, ctypes.byref(phase),
ctypes.byref(incdnc), ctypes.byref(emissn))
return trgepc.value, stypes.cVectorToPython(srfvec), \
phase.value, incdnc.value, emissn.value | [
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",",
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"value"
] | 41.176471 | 16.392157 |
def _get_model_parameters_estimations(self, error_model):
"""
Infer model estimation method from the 'error_model'. Return an object
of type ModelParametersEstimation.
"""
if error_model.dependance == NIDM_INDEPEDENT_ERROR:
if error_model.variance_homo:
estimation_method = STATO_OLS
else:
estimation_method = STATO_WLS
else:
estimation_method = STATO_GLS
mpe = ModelParametersEstimation(estimation_method, self.software.id)
return mpe | [
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def _process_flux_param(self, pval, wave):
"""Process individual model parameter representing flux."""
if isinstance(pval, u.Quantity):
self._validate_flux_unit(pval.unit)
outval = units.convert_flux(self._redshift_model(wave), pval,
self._internal_flux_unit).value
else: # Assume already in internal unit
outval = pval
return outval | [
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"return",
"outval"
] | 48.222222 | 12.777778 |
def str_append_hash(*args):
""" Convert each argument to a lower case string, appended, then hash """
ret_hash = ""
for i in args:
ret_hash += str(i).lower()
return hash(ret_hash) | [
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def new_method_call(celf, destination, path, iface, method) :
"creates a new DBUS.MESSAGE_TYPE_METHOD_CALL message."
result = dbus.dbus_message_new_method_call \
(
(lambda : None, lambda : destination.encode())[destination != None](),
path.encode(),
(lambda : None, lambda : iface.encode())[iface != None](),
method.encode(),
)
if result == None :
raise CallFailed("dbus_message_new_method_call")
#end if
return \
celf(result) | [
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def _path_to_objs(path, include=['*', '.*'], exclude=['.*', '_*']):
"""Turn path with opt. globbing into valid list of files respecting
include and exclude patterns.
Parameters
----------
path : str
Path to process. Can be location of a file, folder or glob.
Can be in uri-notation, can be relative or absolute or start with ~.
include : list, optional
Globbing patterns to require in result, defaults to ['*', '.*'].
exclude : list, optional
Globbing patterns to exclude from result, defaults to ['.*', '_*'].
Returns
-------
objs : list
List of valid files
Notes
-----
- Doesn't show hidden files starting with '.' by default. To enable hidden files, make sure '.*' is in `include` and '.*' is not in `exclude`.
- Doesn't show files starting with '_' by default. To enable these files, make sure '_*' is not in `exclude`.
"""
if '://' in path:
# don't modify when path is in uri-notation, except for local files
if path.startswith('file://'):
path = path[7:]
else:
return [path]
path = os.path.abspath(os.path.expanduser(path))
if os.path.isfile(path):
if not path.lower().endswith(('.xlsx', '.xls')) and zipfile.is_zipfile(path):
# zipfile misidentifies xlsx as archive of xml files
with zipfile.ZipFile(path) as myzip:
zipped = []
for z in myzip.namelist():
z_fn = os.path.basename(z)
if z_fn != '' and any([fnmatch(z_fn, i) for i in include]) and \
not any([fnmatch(z_fn, e) for e in exclude]):
zipped.append(z)
return [myzip.open(z) for z in zipped]
else:
return [path]
elif os.path.isdir(path):
cands = [os.path.abspath(os.path.join(path, p)) for p in os.listdir(path)]
dirname = path
else:
cands = []
dirname = os.path.dirname(path)
include = list(chain.from_iterable(glob(os.path.join(dirname, i)) for i in include))
exclude = list(chain.from_iterable(glob(os.path.join(dirname, e)) for e in exclude))
objs = []
if cands == []:
cands = glob(path)
for p in cands:
if os.path.isfile(p) and p in include and not p in exclude:
objs.append(p)
zipped = [zipfile.is_zipfile(o) and not o.lower().endswith(('.xlsx', '.xls')) \
for o in objs]
toappend = []
todelete = []
for ix, o in enumerate(objs):
# if zipfile in objs replace zipfile with its contents
if zipped[ix]:
for new_o in _path_to_objs(o):
toappend.append(new_o)
todelete.append(ix)
shiftindex = 0
for d in todelete:
del objs[d - shiftindex]
shiftindex += 1
for new_o in toappend:
objs.append(new_o)
return objs | [
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def create(self, model):
""" Given a model object instance create it """
signals.pre_create.send(model.__class__, model=model)
signals.pre_save.send(model.__class__, model=model)
param = self.to_pg(model)
query = """
INSERT INTO {table} ({dirty_cols})
VALUES ({dirty_vals})
RETURNING {cols};
"""
query = query.format(
cols=self.field_cols(model),
dirty_cols=self.dirty_cols(model),
dirty_vals=self.dirty_vals(model),
table=model.rtype,
)
result = self.query(query, param=param)
signals.post_create.send(model.__class__, model=model)
signals.post_save.send(model.__class__, model=model)
return model.merge(result[0], clean=True) | [
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def _pretrained_initializer(varname, weight_file, embedding_weight_file=None):
"""
We'll stub out all the initializers in the pretrained LM with
a function that loads the weights from the file
"""
weight_name_map = {}
for i in range(2):
for j in range(8): # if we decide to add more layers
root = 'RNN_{}/RNN/MultiRNNCell/Cell{}'.format(i, j)
weight_name_map[root + '/rnn/lstm_cell/kernel'] = \
root + '/LSTMCell/W_0'
weight_name_map[root + '/rnn/lstm_cell/bias'] = \
root + '/LSTMCell/B'
weight_name_map[root + '/rnn/lstm_cell/projection/kernel'] = \
root + '/LSTMCell/W_P_0'
# convert the graph name to that in the checkpoint
varname_in_file = varname[5:]
if varname_in_file.startswith('RNN'):
varname_in_file = weight_name_map[varname_in_file]
if varname_in_file == 'embedding':
with h5py.File(embedding_weight_file, 'r') as fin:
# Have added a special 0 index for padding not present
# in the original model.
embed_weights = fin[varname_in_file][...]
weights = np.zeros(
(embed_weights.shape[0] + 1, embed_weights.shape[1]),
dtype=DTYPE
)
weights[1:, :] = embed_weights
else:
with h5py.File(weight_file, 'r') as fin:
if varname_in_file == 'char_embed':
# Have added a special 0 index for padding not present
# in the original model.
char_embed_weights = fin[varname_in_file][...]
weights = np.zeros(
(char_embed_weights.shape[0] + 1,
char_embed_weights.shape[1]),
dtype=DTYPE
)
weights[1:, :] = char_embed_weights
else:
weights = fin[varname_in_file][...]
# Tensorflow initializers are callables that accept a shape parameter
# and some optional kwargs
def ret(shape, **kwargs):
if list(shape) != list(weights.shape):
raise ValueError(
"Invalid shape initializing {0}, got {1}, expected {2}".format(
varname_in_file, shape, weights.shape)
)
return weights
return ret | [
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def post(self, request, *args, **kwargs):
"""
Returns a token identifying the user in Centrifugo.
"""
current_timestamp = "%.0f" % time.time()
user_id_str = u"{0}".format(request.user.id)
token = generate_token(settings.CENTRIFUGE_SECRET, user_id_str, "{0}".format(current_timestamp), info="")
# we get all the channels to which the user can subscribe
participant = Participant.objects.get(id=request.user.id)
# we use the threads as channels ids
channels = []
for thread in Thread.managers.get_threads_where_participant_is_active(participant_id=participant.id):
channels.append(
build_channel(settings.CENTRIFUGO_MESSAGE_NAMESPACE, thread.id, thread.participants.all())
)
# we also have a channel to alert us about new threads
threads_channel = build_channel(settings.CENTRIFUGO_THREAD_NAMESPACE, request.user.id, [request.user.id]) # he is the only one to have access to the channel
channels.append(threads_channel)
# we return the information
to_return = {
'user': user_id_str,
'timestamp': current_timestamp,
'token': token,
'connection_url': "{0}connection/".format(settings.CENTRIFUGE_ADDRESS),
'channels': channels,
'debug': settings.DEBUG,
}
return HttpResponse(json.dumps(to_return), content_type='application/json; charset=utf-8') | [
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] | 43.235294 | 27.588235 |
def execute(args):
"""
Executes the *index* subprogram with parsed commandline *args*.
"""
index_file = Config.instance().get_expanded("core", "index_file")
# just print the file location?
if args.location:
print(index_file)
return
# just remove the index file?
if args.remove:
if os.path.exists(index_file):
os.remove(index_file)
print("removed index file {}".format(index_file))
return
# get modules to lookup
lookup = [m.strip() for m in Config.instance().keys("modules")]
if args.modules:
lookup += args.modules
print("loading tasks from {} module(s)".format(len(lookup)))
# loop through modules, import everything to load tasks
for modid in lookup:
if not modid:
continue
if args.verbose:
sys.stdout.write("loading module '{}'".format(modid))
try:
import_module(modid)
except Exception as e:
if not args.verbose:
print("Error in module '{}': {}".format(colored(modid, "red"), str(e)))
else:
print("\n\nError in module '{}':".format(colored(modid, "red")))
traceback.print_exc()
continue
if args.verbose:
print(", {}".format(colored("done", style="bright")))
# determine tasks to write into the index file
seen_families = []
task_classes = []
lookup = [Task]
while lookup:
cls = lookup.pop(0)
lookup.extend(cls.__subclasses__())
# skip already seen task families
if cls.task_family in seen_families:
continue
seen_families.append(cls.task_family)
# skip when explicitly excluded
if cls.exclude_index:
continue
# skip external tasks
is_external_task = issubclass(cls, ExternalTask)
if args.no_externals and is_external_task:
continue
# skip non-external tasks without run implementation
run_is_callable = callable(getattr(cls, "run", None))
run_is_abstract = getattr(cls.run, "__isabstractmethod__", False)
if not is_external_task and (not run_is_callable or run_is_abstract):
continue
task_classes.append(cls)
def get_task_params(cls):
params = []
for attr in dir(cls):
member = getattr(cls, attr)
if isinstance(member, luigi.Parameter):
exclude = getattr(cls, "exclude_params_index", set())
if not multi_match(attr, exclude, any):
params.append(attr.replace("_", "-"))
return params
def index_line(cls, params):
# format: "module_id:task_family:param param ..."
return "{}:{}:{}".format(cls.__module__, cls.task_family, " ".join(params))
stats = OrderedDict()
# write the index file
if not os.path.exists(os.path.dirname(index_file)):
os.makedirs(os.path.dirname(index_file))
with open(index_file, "w") as f:
for cls in task_classes:
# get prams
params = get_task_params(cls)
# fill stats
if cls.__module__ not in stats:
stats[cls.__module__] = []
stats[cls.__module__].append((cls.task_family, params))
f.write(index_line(cls, params) + "\n")
# print stats
if args.verbose:
for mod, data in six.iteritems(stats):
print("\nmodule '{}', {} task(s):".format(colored(mod, style="bright"), len(data)))
for task_family, _ in data:
print(" - {}".format(colored(task_family, "green")))
print("")
print("written {} task(s) to index file '{}'".format(len(task_classes), index_file)) | [
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")"
] | 31.452991 | 21.367521 |
def compute_pointwise_distances(self, other, default=None):
"""
Compute the minimal distance between each point on self and other.
Parameters
----------
other : tuple of number \
or imgaug.augmentables.kps.Keypoint \
or imgaug.augmentables.LineString
Other object to which to compute the distances.
default
Value to return if `other` contains no points.
Returns
-------
list of float
Distances to `other` or `default` if not distance could be computed.
"""
import shapely.geometry
from .kps import Keypoint
if isinstance(other, Keypoint):
other = shapely.geometry.Point((other.x, other.y))
elif isinstance(other, LineString):
if len(other.coords) == 0:
return default
elif len(other.coords) == 1:
other = shapely.geometry.Point(other.coords[0, :])
else:
other = shapely.geometry.LineString(other.coords)
elif isinstance(other, tuple):
assert len(other) == 2
other = shapely.geometry.Point(other)
else:
raise ValueError(
("Expected Keypoint or LineString or tuple (x,y), "
+ "got type %s.") % (type(other),))
return [shapely.geometry.Point(point).distance(other)
for point in self.coords] | [
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def get_alerts_summary(self, **kwargs): # noqa: E501
"""Count alerts of various statuses for a customer # noqa: E501
# noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.get_alerts_summary(async_req=True)
>>> result = thread.get()
:param async_req bool
:return: ResponseContainerMapStringInteger
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.get_alerts_summary_with_http_info(**kwargs) # noqa: E501
else:
(data) = self.get_alerts_summary_with_http_info(**kwargs) # noqa: E501
return data | [
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def _events(self, using_url, filters=None, limit=None):
""" A long-polling method that queries Syncthing for events..
Args:
using_url (str): REST HTTP endpoint
filters (List[str]): Creates an "event group" in Syncthing to
only receive events that have been subscribed to.
limit (int): The number of events to query in the history
to catch up to the current state.
Returns:
generator[dict]
"""
# coerce
if not isinstance(limit, (int, NoneType)):
limit = None
# coerce
if filters is None:
filters = []
# format our list into the correct expectation of string with commas
if isinstance(filters, string_types):
filters = filters.split(',')
# reset the state if the loop was broken with `stop`
if not self.blocking:
self.blocking = True
# block/long-poll for updates to the events api
while self.blocking:
params = {
'since': self._last_seen_id,
'limit': limit,
}
if filters:
params['events'] = ','.join(map(str, filters))
try:
data = self.get(using_url, params=params, raw_exceptions=True)
except (ConnectTimeout, ConnectionError) as e:
# swallow timeout errors for long polling
data = None
except Exception as e:
reraise('', e)
if data:
# update our last_seen_id to move our event counter forward
self._last_seen_id = data[-1]['id']
for event in data:
# handle potentially multiple events returned in a list
self._count += 1
yield event | [
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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 end(self) -> "GameNode":
"""Follows the main variation to the end and returns the last node."""
node = self
while node.variations:
node = node.variations[0]
return node | [
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def json2value(json_string, params=Null, flexible=False, leaves=False):
"""
:param json_string: THE JSON
:param params: STANDARD JSON PARAMS
:param flexible: REMOVE COMMENTS
:param leaves: ASSUME JSON KEYS ARE DOT-DELIMITED
:return: Python value
"""
if not is_text(json_string):
Log.error("only unicode json accepted")
try:
if flexible:
# REMOVE """COMMENTS""", # COMMENTS, //COMMENTS, AND \n \r
# DERIVED FROM https://github.com/jeads/datasource/blob/master/datasource/bases/BaseHub.py# L58
json_string = re.sub(r"\"\"\".*?\"\"\"", r"\n", json_string, flags=re.MULTILINE)
json_string = "\n".join(remove_line_comment(l) for l in json_string.split("\n"))
# ALLOW DICTIONARY'S NAME:VALUE LIST TO END WITH COMMA
json_string = re.sub(r",\s*\}", r"}", json_string)
# ALLOW LISTS TO END WITH COMMA
json_string = re.sub(r",\s*\]", r"]", json_string)
if params:
# LOOKUP REFERENCES
json_string = expand_template(json_string, params)
try:
value = wrap(json_decoder(text_type(json_string)))
except Exception as e:
Log.error("can not decode\n{{content}}", content=json_string, cause=e)
if leaves:
value = wrap_leaves(value)
return value
except Exception as e:
e = Except.wrap(e)
if not json_string.strip():
Log.error("JSON string is only whitespace")
c = e
while "Expecting '" in c.cause and "' delimiter: line" in c.cause:
c = c.cause
if "Expecting '" in c and "' delimiter: line" in c:
line_index = int(strings.between(c.message, " line ", " column ")) - 1
column = int(strings.between(c.message, " column ", " ")) - 1
line = json_string.split("\n")[line_index].replace("\t", " ")
if column > 20:
sample = "..." + line[column - 20:]
pointer = " " + (" " * 20) + "^"
else:
sample = line
pointer = (" " * column) + "^"
if len(sample) > 43:
sample = sample[:43] + "..."
Log.error(CAN_NOT_DECODE_JSON + " at:\n\t{{sample}}\n\t{{pointer}}\n", sample=sample, pointer=pointer)
base_str = strings.limit(json_string, 1000).encode('utf8')
hexx_str = bytes2hex(base_str, " ")
try:
char_str = " " + " ".join((c.decode("latin1") if ord(c) >= 32 else ".") for c in base_str)
except Exception:
char_str = " "
Log.error(CAN_NOT_DECODE_JSON + ":\n{{char_str}}\n{{hexx_str}}\n", char_str=char_str, hexx_str=hexx_str, cause=e) | [
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def global_closeness_centrality(g, node=None, normalize=True):
"""
Calculates global closeness centrality for one or all nodes in the network.
See :func:`.node_global_closeness_centrality` for more information.
Parameters
----------
g : networkx.Graph
normalize : boolean
If True, normalizes centrality based on the average shortest path
length. Default is True.
Returns
-------
C : dict
Dictionary of results, with node identifiers as keys and gcc as values.
"""
if not node:
C = {}
for node in g.nodes():
C[node] = global_closeness_centrality(g, node, normalize=normalize)
return C
values = nx.shortest_path_length(g, node).values()
c = sum([1./pl for pl in values if pl != 0.]) / len(g)
if normalize:
ac = 0
for sg in nx.connected_component_subgraphs(g):
if len(sg.nodes()) > 1:
aspl = nx.average_shortest_path_length(sg)
ac += (1./aspl) * (float(len(sg)) / float(len(g))**2 )
c = c/ac
return c | [
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def terminate(self, include_watchman=True):
"""Terminates pantsd and watchman.
N.B. This should always be called under care of the `lifecycle_lock`.
"""
super(PantsDaemon, self).terminate()
if include_watchman:
self.watchman_launcher.terminate() | [
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def get_queryset(self):
"""
Optionally restricts the queryset by filtering against
query parameters in the URL.
"""
query_params = self.request.query_params
url_params = self.kwargs
# get queryset_filters from FilterMixin
queryset_filters = self.get_db_filters(url_params, query_params)
# This dict will hold filter kwargs to pass in to Django ORM calls.
db_filters = queryset_filters['db_filters']
# This dict will hold exclude kwargs to pass in to Django ORM calls.
db_excludes = queryset_filters['db_excludes']
queryset = Team.objects.prefetch_related(
'players'
).all()
return queryset.filter(**db_filters).exclude(**db_excludes) | [
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def start_api_and_rpc_workers(self):
"""Initializes eventlet and starts wait for workers to exit.
Spawns the workers returned from serve_rpc
"""
pool = eventlet.GreenPool()
quark_rpc = self.serve_rpc()
pool.spawn(quark_rpc.wait)
pool.waitall() | [
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def error(msg, exit_code):
"""
Print `msg` error and exit with status `exit_code`
"""
sys.stderr.write("%s\ntry 'mongotail --help' for more information\n" % msg)
sys.stderr.flush()
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def predict(self, x):
"""
This function make forward pass through MLP (no update).
**Args:**
* `x` : input vector (1-dimensional array)
**Returns:**
* `y` : output of MLP (float or 1-diemnsional array).
Size depends on number of MLP outputs.
"""
# forward pass to hidden layers
for l in self.layers:
x = l.predict(x)
self.x[1:] = x
# forward pass to output layer
if self.outputs == 1:
self.y = np.dot(self.w, self.x)
else:
self.y = np.sum(self.w*self.x, axis=1)
return self.y | [
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def fetch_weighted_complexity(self, recalculate_metrics=False):
"""
Calculates indicator value according to metrics weights
Uses metrics in database
args:
recalculate_metrics: If true metrics values are updated before
using weights
"""
# TODO: implment metrics recalculation
max_total = sum(
[self.metrics_weights[metric_name] for metric_name in self.metrics_weights]
)
total = 0
if recalculate_metrics:
self.calculate_indicator_metrics()
for metric in self.metrics.all():
if metric.name in self.metrics_weights and metric.is_outlier:
total += self.metrics_weights[metric.name]
value = total / max_total
final_value = "{:.1f}".format(value * 10)
if final_value[-1] == "0":
final_value = "{:.0f}".format(value * 10)
final_value = int(final_value)
else:
final_value = float(final_value)
self.value = float(final_value)
self.is_valid = True
self.updated_at = datetime.datetime.now()
self.save()
return final_value | [
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def encode_arg(arg):
"""
Encode argument to be sent in a valid GuacamoleInstruction.
example:
>> arg = encode_arg('size')
>> arg == '4.size'
>> True
:param arg: arg string.
:return: str
"""
arg_utf8 = utf8(arg)
return ELEM_SEP.join([str(len(str(arg_utf8))), str(arg_utf8)]) | [
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def iteration(self, node_status=True):
"""
Execute a single model iteration
:return: Iteration_id, Incremental node status (dictionary node->status)
"""
self.clean_initial_status(self.available_statuses.values())
actual_status = {node: nstatus for node, nstatus in future.utils.iteritems(self.status)}
if self.actual_iteration == 0:
if min(actual_status.values()) == 0:
number_node_blocked = int(float(self.graph.number_of_nodes()) *
float(self.params['model']['percentage_blocked']))
i = 0
while i < number_node_blocked:
# select a random node
node = list(self.graph.nodes())[np.random.randint(0, self.graph.number_of_nodes())]
# node not infected
if actual_status[node] == 0:
# node blocked
actual_status[node] = -1
self.status[node] = -1
i += 1
self.actual_iteration += 1
delta, node_count, status_delta = self.status_delta(actual_status)
if node_status:
return {"iteration": 0, "status": actual_status.copy(),
"node_count": node_count.copy(), "status_delta": status_delta.copy()}
else:
return {"iteration": 0, "status": {},
"node_count": node_count.copy(), "status_delta": status_delta.copy()}
for node in self.graph.nodes():
if self.status[node] == 0:
if self.params['model']['adopter_rate'] > 0:
xk = (0, 1)
pk = (1-self.params['model']['adopter_rate'], self.params['model']['adopter_rate'])
probability = stats.rv_discrete(name='probability', values=(xk, pk))
number_probability = probability.rvs()
if number_probability == 1:
actual_status[node] = 1
continue
neighbors = list(self.graph.neighbors(node))
if len(neighbors) == 0:
continue
if isinstance(self.graph, nx.DiGraph):
neighbors = self.graph.predecessors(node)
infected = 0
for v in neighbors:
if self.status[v] != -1:
infected += self.status[v]
infected_ratio = float(infected)/len(neighbors)
if infected_ratio >= self.params['nodes']['threshold'][node]:
actual_status[node] = 1
delta, node_count, status_delta = self.status_delta(actual_status)
self.status = actual_status
self.actual_iteration += 1
if node_status:
return {"iteration": self.actual_iteration - 1, "status": delta.copy(),
"node_count": node_count.copy(), "status_delta": status_delta.copy()}
else:
return {"iteration": self.actual_iteration - 1, "status": {},
"node_count": node_count.copy(), "status_delta": status_delta.copy()} | [
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] | 42.253333 | 23.8 |
def saveAs( self, filename = '' ):
"""
Saves the current document to the inputed filename. If no filename \
is supplied, then the user will be prompted to supply a filename.
:param filename | <str>
:return <bool> | success
"""
if ( not (filename and isinstance(filename, basestring)) ):
langTypes = XLanguage.pluginFileTypes()
filename = QFileDialog.getSaveFileName( None,
'Save File As...',
QDir.currentPath(),
langTypes)
if type(filename) == tuple:
filename = nativestring(filename[0])
if ( not filename ):
return False
docfile = QFile(filename)
if ( not docfile.open(QFile.WriteOnly) ):
logger.warning('Could not open %s for writing.' % filename)
return False
success = self.write(docfile)
docfile.close()
if success:
filename = nativestring(filename)
self._filename = filename
self.setModified(False)
# set the language
lang = XLanguage.byFileType(os.path.splitext(filename)[1])
if ( lang != self.language() ):
self.setLanguage(lang)
return success | [
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def do_pot(self):
"""
Sync the template with the python code.
"""
files_to_translate = []
log.debug("Collecting python sources for pot ...")
for source_path in self._source_paths:
for source_path in self._iter_suffix(path=source_path, suffix=".py"):
log.debug("... add to pot: {source}".format(source=str(source_path)))
files_to_translate.append(str(source_path))
for system_file in self.SYSTEM_SOURCE_FILES:
files_to_translate.append(str(self._system_path / system_file))
# FIXME: use separate domain for system source translations? Nerge them when generating mo's?
log.debug("Finished collection sources.")
pot_path = (self._po_path / self._basename).with_suffix(".pot")
command = ["xgettext", "--keyword=_", "--keyword=_translate",
"--output={output}".format(output=str(pot_path))]
command.extend(files_to_translate)
check_call(command)
log.debug("pot file \"{pot}\" created!".format(pot=str(pot_path)))
pot_copy_path = self._mo_path / pot_path.name
log.debug("Copying pot file to mo path: {pot_copy_path}".format(pot_copy_path=str(pot_copy_path)))
shutil.copy(str(pot_path), str(pot_copy_path)) | [
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] | 53.791667 | 23.291667 |
def get_upstream_paths(self, port):
"""Retrieve a dictionary containing the full URLs of the upstream apps
:param int port: The port used by the replay and cdx servers
:return: A dictionary containing the upstream paths (replay, cdx-server, record [if enabled])
:rtype: dict[str, str]
"""
base_paths = {
'replay': self.REPLAY_API % port,
'cdx-server': self.CDX_API % port,
}
if self.recorder_path:
base_paths['record'] = self.recorder_path
return base_paths | [
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def top_directory(self):
"""Return the name of the archive topmost directory."""
if self.handle:
return os.path.commonprefix(self.handle.getnames()).rstrip('/') | [
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def _new_conn(self):
"""
Return a fresh :class:`HTTPConnection`.
"""
self.num_connections += 1
log.debug("Starting new HTTP connection (%d): %s",
self.num_connections, self.host)
conn = self.ConnectionCls(host=self.host, port=self.port,
timeout=self.timeout.connect_timeout,
strict=self.strict, **self.conn_kw)
return conn | [
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def schedule_contact_downtime(self, contact, start_time, end_time, author, comment):
"""Schedule contact downtime
Format of the line that triggers function call::
SCHEDULE_CONTACT_DOWNTIME;<contact_name>;<start_time>;<end_time>;<author>;<comment>
:param contact: contact to put in downtime
:type contact: alignak.objects.contact.Contact
:param start_time: downtime start time
:type start_time: int
:param end_time: downtime end time
:type end_time: int
:param author: downtime author
:type author: str
:param comment: text comment
:type comment: str
:return: None
"""
data = {'ref': contact.uuid, 'start_time': start_time,
'end_time': end_time, 'author': author, 'comment': comment}
cdt = ContactDowntime(data)
contact.add_downtime(cdt)
self.send_an_element(contact.get_update_status_brok()) | [
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def common(self, other):
"""
Return two objects with the same dimensions if they lie in the same orthogonal plane.
::
>>> l = Location(pop=1, snap=2)
>>> m = Location(crackle=1, snap=3)
>>> l.common(m)
(<Location snap:2 >, <Location snap:3 >)
"""
selfDim = set(self.keys())
otherDim = set(other.keys())
dims = selfDim | otherDim
newSelf = None
newOther = None
for dim in dims:
sd = self.get(dim, None)
od = other.get(dim, None)
if sd is None or od is None:
# axis is missing in one or the other
continue
if -_EPSILON < sd < _EPSILON and -_EPSILON < od < _EPSILON:
# values are both zero
continue
if newSelf is None:
newSelf = self.__class__()
if newOther is None:
newOther = self.__class__()
newSelf[dim] = self[dim]
newOther[dim] = other[dim]
return newSelf, newOther | [
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def extend(self, tasks):
'''Add tasks to this particular shovel'''
self._tasks.extend(tasks)
for task in tasks:
# We'll now go through all of our tasks and group them into
# sub-shovels
current = self.map
modules = task.fullname.split('.')
for module in modules[:-1]:
if not isinstance(current[module], Shovel):
logger.warn('Overriding task %s with a module' %
current[module].file)
shovel = Shovel()
shovel.overrides = current[module]
current[module] = shovel
current = current[module].map
# Now we'll put the task in this particular sub-shovel
name = modules[-1]
if name in current:
logger.warn('Overriding %s with %s' % (
'.'.join(modules), task.file))
task.overrides = current[name]
current[name] = task | [
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def set(self, client_id, code, request, *args, **kwargs):
"""Creates Grant object with the given params
:param client_id: ID of the client
:param code:
:param request: OAuthlib request object
"""
expires = datetime.utcnow() + timedelta(seconds=100)
grant = self.model(
client_id=request.client.client_id,
code=code['code'],
redirect_uri=request.redirect_uri,
scope=' '.join(request.scopes),
user=self.current_user(),
expires=expires
)
self.session.add(grant)
self.session.commit() | [
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def runGenomeSGE(bfile, freqFile, nbJob, outPrefix, options):
"""Runs the genome command from plink, on SGE.
:param bfile: the prefix of the input file.
:param freqFile: the name of the frequency file (from Plink).
:param nbJob: the number of jobs to launch.
:param outPrefix: the prefix of all the output files.
:param options: the options.
:type bfile: str
:type freqFile: str
:type nbJob: int
:type outPrefix: str
:type options: argparse.Namespace
Runs Plink with the ``genome`` options on the cluster (using SGE).
"""
# Add the environment variable for DRMAA package
if "DRMAA_LIBRARY_PATH" not in os.environ:
msg = "could not load drmaa: set DRMAA_LIBRARY_PATH"
raise ProgramError(msg)
# Import the python drmaa library
try:
import drmaa
except ImportError:
raise ProgramError("drmaa is not install, install drmaa")
# Initializing a session
s = drmaa.Session()
s.initialize()
# Run for each sub task...
jobIDs = []
jobTemplates = []
for i in xrange(1, nbJob + 1):
for j in xrange(i, nbJob + 1):
# The command to run
plinkCommand = ["plink", "--noweb", "--bfile", bfile,
"--read-freq", freqFile, "--genome",
"--genome-full", "--genome-lists",
"{}_tmp.list{}".format(outPrefix, i),
"{}_tmp.list{}".format(outPrefix, j), "--out",
"{}_output.sub.{}.{}".format(outPrefix, i, j)]
# Creating the job template
jt = s.createJobTemplate()
jt.remoteCommand = plinkCommand[0]
jt.workingDirectory = os.getcwd()
jt.jobEnvironment = os.environ
jt.args = plinkCommand[1:]
jt.jobName = "_plink_genome_{}_{}".format(i, j)
# Cluster specifics
if options.sge_walltime is not None:
jt.hardWallclockTimeLimit = options.sge_walltime
if options.sge_nodes is not None:
native_spec = "-l nodes={}:ppn={}".format(options.sge_nodes[0],
options.sge_nodes[1])
jt.nativeSpecification = native_spec
jobIDs.append(s.runJob(jt))
jobTemplates.append(jt)
# Waiting for the jobs to finish
hadProblems = []
for jobID in jobIDs:
retVal = s.wait(jobID, drmaa.Session.TIMEOUT_WAIT_FOREVER)
hadProblems.append(retVal.exitStatus == 0)
# Deleting the jobs
for jt in jobTemplates:
s.deleteJobTemplate(jt)
# Closing the session
s.exit()
# Checking for problems
for hadProblem in hadProblems:
if not hadProblem:
msg = "Some SGE jobs had errors..."
raise ProgramError(msg) | [
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def get_all_context(self):
"""
Retrieves Plan and Pricing for current order creation
"""
self.plan_pricing = get_object_or_404(PlanPricing.objects.all().select_related('plan', 'pricing'),
Q(pk=self.kwargs['pk']) & Q(plan__available=True) & (
Q(plan__customized=self.request.user) | Q(
plan__customized__isnull=True)))
# User is not allowed to create new order for Plan when he has different Plan
# He should use Plan Change View for this kind of action
if not self.request.user.userplan.is_expired() and self.request.user.userplan.plan != self.plan_pricing.plan:
raise Http404
self.plan = self.plan_pricing.plan
self.pricing = self.plan_pricing.pricing | [
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def is_downloadable(self, response):
'''
Checks whether the response object is a html page
or a likely downloadable file.
Intended to detect error pages or prompts
such as kaggle's competition rules acceptance prompt.
Returns True if the response is a html page. False otherwise.
'''
content_type = response.headers.get('Content-Type', '')
content_disp = response.headers.get('Content-Disposition', '')
if 'text/html' in content_type and 'attachment' not in content_disp:
# This response is a html file
# which is not marked as an attachment,
# so we likely hit a rules acceptance prompt
return False
return True | [
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def fourier_ratios(phase_shifted_coeffs):
r"""
Returns the :math:`R_{j1}` and :math:`\phi_{j1}` values for the given
phase-shifted coefficients.
.. math::
R_{j1} = A_j / A_1
.. math::
\phi_{j1} = \phi_j - j \phi_1
**Parameters**
phase_shifted_coeffs : array-like, shape = [:math:`2n+1`]
Fourier sine or cosine series coefficients.
:math:`[ A_0, A_1, \Phi_1, \ldots, A_n, \Phi_n ]`.
**Returns**
out : array-like, shape = [:math:`2n+1`]
Fourier ratios
:math:`[ R_{21}, \phi_{21}, \ldots, R_{n1}, \phi_{n1} ]`.
"""
n_coeff = phase_shifted_coeffs.size
# n_coeff = 2*degree + 1 => degree = (n_coeff-1)/2
degree = (n_coeff - 1) / 2
amplitudes = phase_shifted_coeffs[1::2]
phases = phase_shifted_coeffs[2::2]
# there are degree-1 amplitude ratios, and degree-1 phase deltas,
# so altogether there are 2*(degree-1) values
ratios = numpy.empty(2*(degree-1), dtype=float)
amplitude_ratios = ratios[::2]
phase_deltas = ratios[1::2]
# amplitudes may be zero, so suppress division by zero warnings
with numpy.errstate(divide="ignore"):
amplitude_ratios[:] = amplitudes[1:]
amplitude_ratios /= amplitudes[0]
# indices for phase deltas
i = numpy.arange(2, degree+1)
phase_deltas[:] = phases[1:]
phase_deltas -= i*phases[0]
# constrain phase_deltas between 0 and 2*pi
phase_deltas %= 2*pi
return ratios | [
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def extend_back(self, dag, edge_map=None):
"""Add `dag` at the end of `self`, using `edge_map`.
"""
edge_map = edge_map or {}
for qreg in dag.qregs.values():
if qreg.name not in self.qregs:
self.add_qreg(QuantumRegister(qreg.size, qreg.name))
edge_map.update([(qbit, qbit) for qbit in qreg if qbit not in edge_map])
for creg in dag.cregs.values():
if creg.name not in self.cregs:
self.add_creg(ClassicalRegister(creg.size, creg.name))
edge_map.update([(cbit, cbit) for cbit in creg if cbit not in edge_map])
self.compose_back(dag, edge_map) | [
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def from_ordered_sequence(cls, iseq):
"""
Return the root of a balanced binary search tree populated with the
values in iterable *iseq*.
"""
seq = list(iseq)
# optimize for usually all fits by making longest first
bst = cls(seq.pop())
bst._insert_from_ordered_sequence(seq)
return bst | [
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def set_unicode(self, quoted_text=False):
"""Converts the context's ``value`` to a sequence of unicode code points for holding text tokens, indicating
whether the text is quoted.
"""
if isinstance(self.value, CodePointArray):
assert self.quoted_text == quoted_text
return self
self.value = CodePointArray(self.value)
self.quoted_text = quoted_text
self.line_comment = False
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def ppj(json_data):
"""ppj
:param json_data: dictionary to print
"""
return str(json.dumps(
json_data,
sort_keys=True,
indent=4,
separators=(',', ': '))) | [
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