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def is30(msg): """Check if a message is likely to be BDS code 2,0 Args: msg (String): 28 bytes hexadecimal message string Returns: bool: True or False """ if allzeros(msg): return False d = hex2bin(data(msg)) if d[0:8] != '00110000': return False # threat type 3 not assigned if d[28:30] == '11': return False # reserved for ACAS III, in far future if bin2int(d[15:22]) >= 48: return False return True
Check if a message is likely to be BDS code 2,0 Args: msg (String): 28 bytes hexadecimal message string Returns: bool: True or False
def atlas_get_peer( peer_hostport, peer_table=None ): """ Get the given peer's info """ ret = None with AtlasPeerTableLocked(peer_table) as ptbl: ret = ptbl.get(peer_hostport, None) return ret
Get the given peer's info
def set_cli_options(config, arguments=None): """Set any configuration options which have a CLI value set. Args: config (confpy.core.config.Configuration): A configuration object which has been initialized with options. arguments (iter of str): An iterable of strings which contains the CLI arguments passed. If nothing is give then sys.argv is used. Returns: confpy.core.config.Configuration: A configuration object with CLI values set. The pattern to follow when setting CLI values is: <section>_<option> Each value should be lower case and separated by underscores. """ arguments = arguments or sys.argv[1:] parser = argparse.ArgumentParser() for section_name, section in config: for option_name, _ in section: var_name = '{0}_{1}'.format( section_name.lower(), option_name.lower(), ) parser.add_argument('--{0}'.format(var_name)) args, _ = parser.parse_known_args(arguments) args = vars(args) for section_name, section in config: for option_name, _ in section: var_name = '{0}_{1}'.format( section_name.lower(), option_name.lower(), ) value = args.get(var_name) if value: setattr(section, option_name, value) return config
Set any configuration options which have a CLI value set. Args: config (confpy.core.config.Configuration): A configuration object which has been initialized with options. arguments (iter of str): An iterable of strings which contains the CLI arguments passed. If nothing is give then sys.argv is used. Returns: confpy.core.config.Configuration: A configuration object with CLI values set. The pattern to follow when setting CLI values is: <section>_<option> Each value should be lower case and separated by underscores.
def export_legacy_ldcoeffs(self, models, filename=None, photon_weighted=True): """ @models: the path (including the filename) of legacy's models.list @filename: output filename for storing the table Exports CK2004 limb darkening coefficients to a PHOEBE legacy compatible format. """ if photon_weighted: grid = self._ck2004_ld_photon_grid else: grid = self._ck2004_ld_energy_grid if filename is not None: import time f = open(filename, 'w') f.write('# PASS_SET %s\n' % self.pbset) f.write('# PASSBAND %s\n' % self.pbname) f.write('# VERSION 1.0\n\n') f.write('# Exported from PHOEBE-2 passband on %s\n' % (time.ctime())) f.write('# The coefficients are computed for the %s-weighted regime.\n\n' % ('photon' if photon_weighted else 'energy')) mods = np.loadtxt(models) for mod in mods: Tindex = np.argwhere(self._ck2004_intensity_axes[0] == mod[0])[0][0] lindex = np.argwhere(self._ck2004_intensity_axes[1] == mod[1]/10)[0][0] mindex = np.argwhere(self._ck2004_intensity_axes[2] == mod[2]/10)[0][0] if filename is None: print('%6.3f '*11 % tuple(grid[Tindex, lindex, mindex].tolist())) else: f.write(('%6.3f '*11+'\n') % tuple(self._ck2004_ld_photon_grid[Tindex, lindex, mindex].tolist())) if filename is not None: f.close()
@models: the path (including the filename) of legacy's models.list @filename: output filename for storing the table Exports CK2004 limb darkening coefficients to a PHOEBE legacy compatible format.
def set_index_edited(self, index, edited): """Set whether the conf was edited or not. Edited files will be displayed with a \'*\' :param index: the index that was edited :type index: QModelIndex :param edited: if the file was edited, set edited to True, else False :type edited: bool :returns: None :rtype: None :raises: None """ self.__edited[index.row()] = edited self.dataChanged.emit(index, index)
Set whether the conf was edited or not. Edited files will be displayed with a \'*\' :param index: the index that was edited :type index: QModelIndex :param edited: if the file was edited, set edited to True, else False :type edited: bool :returns: None :rtype: None :raises: None
def query(self, startTime=None, endTime=None, sinceServerStart=False, level="WARNING", services="*", machines="*", server="*", codes=[], processIds=[], export=False, exportType="CSV", #CSV or TAB out_path=None ): """ The query operation on the logs resource provides a way to aggregate, filter, and page through logs across the entire site. Inputs: """ allowed_levels = ("SEVERE", "WARNING", "INFO", "FINE", "VERBOSE", "DEBUG") qFilter = { "services": "*", "machines": "*", "server" : "*" } if len(processIds) > 0: qFilter['processIds'] = processIds if len(codes) > 0: qFilter['codes'] = codes params = { "f" : "json", "sinceServerStart" : sinceServerStart, "pageSize" : 10000 } if startTime is not None and \ isinstance(startTime, datetime): params['startTime'] = startTime.strftime("%Y-%m-%dT%H:%M:%S") if endTime is not None and \ isinstance(endTime, datetime): params['endTime'] = endTime.strftime("%Y-%m-%dT%H:%M:%S") if level.upper() in allowed_levels: params['level'] = level if server != "*": qFilter['server'] = server.split(',') if services != "*": qFilter['services'] = services.split(',') if machines != "*": qFilter['machines'] = machines.split(",") params['filter'] = qFilter if export == True and \ out_path is not None: messages = self._post(self._url + "/query", params, securityHandler=self._securityHandler, proxy_url=self._proxy_url, proxy_port=self._proxy_port) with open(name=out_path, mode='wb') as f: hasKeys = False if exportType == "TAB": csvwriter = csv.writer(f, delimiter='\t') else: csvwriter = csv.writer(f) for message in messages['logMessages']: if hasKeys == False: csvwriter.writerow(message.keys()) hasKeys = True csvwriter.writerow(message.values()) del message del messages return out_path else: return self._post(self._url + "/query", params, securityHandler=self._securityHandler, proxy_url=self._proxy_url, proxy_port=self._proxy_port)
The query operation on the logs resource provides a way to aggregate, filter, and page through logs across the entire site. Inputs:
def commit(self): """ Store metadata on this Job to the backend. """ logger.debug('Committing job {0}'.format(self.name)) self.backend.commit_job(self._serialize()) self.parent.commit()
Store metadata on this Job to the backend.
def mdr_mutual_information(X, Y, labels, base=2): """Calculates the MDR mutual information, I(XY;labels), in the given base MDR mutual information is calculated by combining variables X and Y into a single MDR model then calculating the mutual information between the resulting model's predictions and the labels. Parameters ---------- X: array-like (# samples) An array of values corresponding to one feature in the MDR model Y: array-like (# samples) An array of values corresponding to one feature in the MDR model labels: array-like (# samples) The class labels corresponding to features X and Y base: integer (default: 2) The base in which to calculate MDR mutual information Returns ---------- mdr_mutual_information: float The MDR mutual information calculated according to the equation I(XY;labels) = H(labels) - H(labels|XY) """ return mutual_information(_mdr_predict(X, Y, labels), labels, base=base)
Calculates the MDR mutual information, I(XY;labels), in the given base MDR mutual information is calculated by combining variables X and Y into a single MDR model then calculating the mutual information between the resulting model's predictions and the labels. Parameters ---------- X: array-like (# samples) An array of values corresponding to one feature in the MDR model Y: array-like (# samples) An array of values corresponding to one feature in the MDR model labels: array-like (# samples) The class labels corresponding to features X and Y base: integer (default: 2) The base in which to calculate MDR mutual information Returns ---------- mdr_mutual_information: float The MDR mutual information calculated according to the equation I(XY;labels) = H(labels) - H(labels|XY)
def _update_metadata(self, kwargs=None): '''Extract any additional attributes to hold with the instance from kwargs ''' # If not given metadata, use instance.list to get it for container if kwargs == None and hasattr(self, 'name'): kwargs = self._list(self.name, quiet=True, return_json=True) # Add acceptable arguments for arg in ['pid', 'name']: # Skip over non-iterables: if arg in kwargs: setattr(self, arg, kwargs[arg]) if "image" in kwargs: self._image = kwargs['image'] elif "container_image" in kwargs: self._image = kwargs['container_image']
Extract any additional attributes to hold with the instance from kwargs
def sel_list_pres(ds_sfc_x): ''' select proper levels for model level data download ''' p_min, p_max = ds_sfc_x.sp.min().values, ds_sfc_x.sp.max().values list_pres_level = [ '1', '2', '3', '5', '7', '10', '20', '30', '50', '70', '100', '125', '150', '175', '200', '225', '250', '300', '350', '400', '450', '500', '550', '600', '650', '700', '750', '775', '800', '825', '850', '875', '900', '925', '950', '975', '1000', ] ser_pres_level = pd.Series(list_pres_level).map(int)*100 pos_lev_max, pos_lev_min = ( ser_pres_level[ser_pres_level > p_max].idxmin(), ser_pres_level[ser_pres_level < p_min].idxmax() ) list_pres_sel = ser_pres_level.loc[pos_lev_min:pos_lev_max]/100 list_pres_sel = list_pres_sel.map(int).map(str).to_list() return list_pres_sel
select proper levels for model level data download
def add_user(self, attrs): """add a user""" ldap_client = self._bind() # encoding crap attrs_srt = self.attrs_pretreatment(attrs) attrs_srt[self._byte_p2('objectClass')] = self.objectclasses # construct is DN dn = \ self._byte_p2(self.dn_user_attr) + \ self._byte_p2('=') + \ self._byte_p2(ldap.dn.escape_dn_chars( attrs[self.dn_user_attr] ) ) + \ self._byte_p2(',') + \ self._byte_p2(self.userdn) # gen the ldif first add_s and add the user ldif = modlist.addModlist(attrs_srt) try: ldap_client.add_s(dn, ldif) except ldap.ALREADY_EXISTS as e: raise UserAlreadyExists(attrs[self.key], self.backend_name) except Exception as e: ldap_client.unbind_s() self._exception_handler(e) ldap_client.unbind_s()
add a user
def approx_aic(self, ts): """ Calculates an approximation to the Akaike Information Criterion (AIC). This is an approximation as we use the conditional likelihood, rather than the exact likelihood. Please see [[https://en.wikipedia.org/wiki/Akaike_information_criterion]] for more information on this measure. Parameters ---------- ts: the timeseries to evaluate under current model Returns an approximation to the AIC under the current model as a double """ return self._jmodel.approxAIC(_py2java(self._ctx, Vectors.dense(ts)))
Calculates an approximation to the Akaike Information Criterion (AIC). This is an approximation as we use the conditional likelihood, rather than the exact likelihood. Please see [[https://en.wikipedia.org/wiki/Akaike_information_criterion]] for more information on this measure. Parameters ---------- ts: the timeseries to evaluate under current model Returns an approximation to the AIC under the current model as a double
def _interpret_regexp(self, string, flags): '''Perform sctring escape - for regexp literals''' self.index = 0 self.length = len(string) self.source = string self.lineNumber = 0 self.lineStart = 0 octal = False st = '' inside_square = 0 while (self.index < self.length): template = '[%s]' if not inside_square else '%s' ch = self.source[self.index] self.index += 1 if ch == '\\': ch = self.source[self.index] self.index += 1 if (not isLineTerminator(ch)): if ch == 'u': digs = self.source[self.index:self.index + 4] if len(digs) == 4 and all(isHexDigit(d) for d in digs): st += template % unichr(int(digs, 16)) self.index += 4 else: st += 'u' elif ch == 'x': digs = self.source[self.index:self.index + 2] if len(digs) == 2 and all(isHexDigit(d) for d in digs): st += template % unichr(int(digs, 16)) self.index += 2 else: st += 'x' # special meaning - single char. elif ch == '0': st += '\\0' elif ch == 'n': st += '\\n' elif ch == 'r': st += '\\r' elif ch == 't': st += '\\t' elif ch == 'f': st += '\\f' elif ch == 'v': st += '\\v' # unescape special single characters like . so that they are interpreted literally elif ch in REGEXP_SPECIAL_SINGLE: st += '\\' + ch # character groups elif ch == 'b': st += '\\b' elif ch == 'B': st += '\\B' elif ch == 'w': st += '\\w' elif ch == 'W': st += '\\W' elif ch == 'd': st += '\\d' elif ch == 'D': st += '\\D' elif ch == 's': st += template % u' \f\n\r\t\v\u00a0\u1680\u180e\u2000-\u200a\u2028\u2029\u202f\u205f\u3000\ufeff' elif ch == 'S': st += template % u'\u0000-\u0008\u000e-\u001f\u0021-\u009f\u00a1-\u167f\u1681-\u180d\u180f-\u1fff\u200b-\u2027\u202a-\u202e\u2030-\u205e\u2060-\u2fff\u3001-\ufefe\uff00-\uffff' else: if isDecimalDigit(ch): num = ch while self.index < self.length and isDecimalDigit( self.source[self.index]): num += self.source[self.index] self.index += 1 st += '\\' + num else: st += ch # DONT ESCAPE!!! else: self.lineNumber += 1 if (ch == '\r' and self.source[self.index] == '\n'): self.index += 1 self.lineStart = self.index else: if ch == '[': inside_square = True elif ch == ']': inside_square = False st += ch # print string, 'was transformed to', st return st
Perform sctring escape - for regexp literals
def returnDepositsWithdrawals(self, start=0, end=2**32-1): """Returns your deposit and withdrawal history within a range, specified by the "start" and "end" POST parameters, both of which should be given as UNIX timestamps.""" return self._private('returnDepositsWithdrawals', start=start, end=end)
Returns your deposit and withdrawal history within a range, specified by the "start" and "end" POST parameters, both of which should be given as UNIX timestamps.
def get_destinations(self, ascii_listing): """ returns all line numbers that are used in a jump. """ self.destinations = set() def collect_destinations(matchobj): numbers = matchobj.group("no") if numbers: self.destinations.update(set( [n.strip() for n in numbers.split(",")] )) for line in self._iter_lines(ascii_listing): self.renum_regex.sub(collect_destinations, line) return sorted([int(no) for no in self.destinations if no])
returns all line numbers that are used in a jump.
def update_metadata_filters(metadata, jupyter_md, cell_metadata): """Update or set the notebook and cell metadata filters""" cell_metadata = [m for m in cell_metadata if m not in ['language', 'magic_args']] if 'cell_metadata_filter' in metadata.get('jupytext', {}): metadata_filter = metadata_filter_as_dict(metadata.get('jupytext', {})['cell_metadata_filter']) if isinstance(metadata_filter.get('excluded'), list): metadata_filter['excluded'] = [key for key in metadata_filter['excluded'] if key not in cell_metadata] metadata_filter.setdefault('additional', []) if isinstance(metadata_filter.get('additional'), list): for key in cell_metadata: if key not in metadata_filter['additional']: metadata_filter['additional'].append(key) metadata.setdefault('jupytext', {})['cell_metadata_filter'] = metadata_filter_as_string(metadata_filter) if not jupyter_md: # Set a metadata filter equal to the current metadata in script cell_metadata = {'additional': cell_metadata, 'excluded': 'all'} metadata.setdefault('jupytext', {})['notebook_metadata_filter'] = '-all' metadata.setdefault('jupytext', {})['cell_metadata_filter'] = metadata_filter_as_string(cell_metadata)
Update or set the notebook and cell metadata filters
def quick_summary(nml2_doc): ''' Or better just use nml2_doc.summary(show_includes=False) ''' info = 'Contents of NeuroML 2 document: %s\n'%nml2_doc.id membs = inspect.getmembers(nml2_doc) for memb in membs: if isinstance(memb[1], list) and len(memb[1])>0 \ and not memb[0].endswith('_'): info+=' %s:\n ['%memb[0] for entry in memb[1]: extra = '???' extra = entry.name if hasattr(entry,'name') else extra extra = entry.href if hasattr(entry,'href') else extra extra = entry.id if hasattr(entry,'id') else extra info+=" %s (%s),"%(entry, extra) info+=']\n' return info
Or better just use nml2_doc.summary(show_includes=False)
def set_extended_elements(self): """Parses and sets non required elements""" self.set_creative_commons() self.set_owner() self.set_subtitle() self.set_summary()
Parses and sets non required elements
def protect_libraries_from_patching(): """ In this function we delete some modules from `sys.modules` dictionary and import them again inside `_pydev_saved_modules` in order to save their original copies there. After that we can use these saved modules within the debugger to protect them from patching by external libraries (e.g. gevent). """ patched = ['threading', 'thread', '_thread', 'time', 'socket', 'Queue', 'queue', 'select', 'xmlrpclib', 'SimpleXMLRPCServer', 'BaseHTTPServer', 'SocketServer', 'xmlrpc.client', 'xmlrpc.server', 'http.server', 'socketserver'] for name in patched: try: __import__(name) except: pass patched_modules = dict([(k, v) for k, v in sys.modules.items() if k in patched]) for name in patched_modules: del sys.modules[name] # import for side effects import _pydev_imps._pydev_saved_modules for name in patched_modules: sys.modules[name] = patched_modules[name]
In this function we delete some modules from `sys.modules` dictionary and import them again inside `_pydev_saved_modules` in order to save their original copies there. After that we can use these saved modules within the debugger to protect them from patching by external libraries (e.g. gevent).
def dispatch(self, req): """ Called by the Routes middleware to dispatch the request to the appropriate controller. If a webob exception is raised, it is returned; if some other exception is raised, the webob `HTTPInternalServerError` exception is raised. Otherwise, the return value of the controller is returned. """ # Grab the request parameters params = req.environ['wsgiorg.routing_args'][1] # What controller is authoritative? controller = params.pop('controller') # Determine its name cont_class = controller.__class__ cont_name = "%s:%s" % (cont_class.__module__, cont_class.__name__) # Determine the origin of the request origin = req.remote_addr if req.remote_addr else '[local]' if req.remote_user: origin = '%s (%s)' % (origin, req.remote_user) # Log that we're processing the request LOG.info("%s %s %s (controller %r)" % (origin, req.method, req.url, cont_name)) # Call into that controller try: return controller(req, params) except webob.exc.HTTPException as e: # Return the HTTP exception directly return e except exceptions.AppathyResponse as e: # Return the webob.Response directly return e.response except Exception as e: # Log the controller exception LOG.exception("Exception occurred in controller %r" % cont_name) # These exceptions result in a 500. Note we're # intentionally not including the exception message, since # it could contain sensitive data. return webob.exc.HTTPInternalServerError()
Called by the Routes middleware to dispatch the request to the appropriate controller. If a webob exception is raised, it is returned; if some other exception is raised, the webob `HTTPInternalServerError` exception is raised. Otherwise, the return value of the controller is returned.
def netconf_session_start_session_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") netconf_session_start = ET.SubElement(config, "netconf-session-start", xmlns="urn:ietf:params:xml:ns:yang:ietf-netconf-notifications") session_id = ET.SubElement(netconf_session_start, "session-id") session_id.text = kwargs.pop('session_id') callback = kwargs.pop('callback', self._callback) return callback(config)
Auto Generated Code
def _CreateAllTypes(self, enumTypes, dataTypes, managedTypes): """ Create pyVmomi types from pyVmomi type definitions """ # Create versions for typeInfo in managedTypes: name = typeInfo[0] version = typeInfo[3] VmomiSupport.AddVersion(version, '', '1.0', 0, name) VmomiSupport.AddVersionParent(version, 'vmodl.version.version0') VmomiSupport.AddVersionParent(version, 'vmodl.version.version1') VmomiSupport.AddVersionParent(version, version) # Create partial types for fn, infos in (VmomiSupport.CreateEnumType, enumTypes), \ (VmomiSupport.CreateDataType, dataTypes), \ (VmomiSupport.CreateManagedType, managedTypes): for typeInfo in infos: try: fn(*typeInfo) except Exception as err: #Ignore errors due to duplicate importing pass
Create pyVmomi types from pyVmomi type definitions
def search_globs(path, patterns): # type: (str, List[str]) -> bool """ Test whether the given *path* contains any patterns in *patterns* Args: path (str): A file path to test for matches. patterns (list[str]): A list of glob string patterns to test against. If *path* matches any of those patters, it will return True. Returns: bool: **True** if the ``path`` matches any pattern in *patterns*. """ for pattern in (p for p in patterns if p): if pattern.startswith('/'): # If pattern starts with root it means it match from root only regex = fnmatch.translate(pattern[1:]) regex = regex.replace('\\Z', '') temp_path = path[1:] if path.startswith('/') else path m = re.search(regex, temp_path) if m and m.start() == 0: return True else: regex = fnmatch.translate(pattern) regex = regex.replace('\\Z', '') if re.search(regex, path): return True return False
Test whether the given *path* contains any patterns in *patterns* Args: path (str): A file path to test for matches. patterns (list[str]): A list of glob string patterns to test against. If *path* matches any of those patters, it will return True. Returns: bool: **True** if the ``path`` matches any pattern in *patterns*.
def remove_listener(registry, listener): """ Removes a listener from the registry :param registry: A registry (a list) :param listener: The listener to remove :return: True if the listener was in the list """ if listener is not None and listener in registry: registry.remove(listener) return True return False
Removes a listener from the registry :param registry: A registry (a list) :param listener: The listener to remove :return: True if the listener was in the list
def parse_query(query): """ Given a simplified XPath query string, returns an array of normalized query parts. """ parts = query.split('/') norm = [] for p in parts: p = p.strip() if p: norm.append(p) elif '' not in norm: norm.append('') return norm
Given a simplified XPath query string, returns an array of normalized query parts.
def setHoverIcon( self, column, icon ): """ Returns the icon to use when coloring when the user hovers over the item for the given column. :param column | <int> icon | <QtGui.QIcon) """ self._hoverIcon[column] = QtGui.QIcon(icon)
Returns the icon to use when coloring when the user hovers over the item for the given column. :param column | <int> icon | <QtGui.QIcon)
def integrateFullOrbit_c(pot,yo,t,int_method,rtol=None,atol=None,dt=None): """ NAME: integrateFullOrbit_c PURPOSE: C integrate an ode for a FullOrbit INPUT: pot - Potential or list of such instances yo - initial condition [q,p] t - set of times at which one wants the result int_method= 'leapfrog_c', 'rk4_c', 'rk6_c', 'symplec4_c' rtol, atol dt= (None) force integrator to use this stepsize (default is to automatically determine one)) OUTPUT: (y,err) y : array, shape (len(y0), len(t)) Array containing the value of y for each desired time in t, \ with the initial value y0 in the first row. err: error message, if not zero: 1 means maximum step reduction happened for adaptive integrators HISTORY: 2011-11-13 - Written - Bovy (IAS) """ rtol, atol= _parse_tol(rtol,atol) npot, pot_type, pot_args= _parse_pot(pot) int_method_c= _parse_integrator(int_method) if dt is None: dt= -9999.99 #Set up result array result= nu.empty((len(t),6)) err= ctypes.c_int(0) #Set up the C code ndarrayFlags= ('C_CONTIGUOUS','WRITEABLE') integrationFunc= _lib.integrateFullOrbit integrationFunc.argtypes= [ndpointer(dtype=nu.float64,flags=ndarrayFlags), ctypes.c_int, ndpointer(dtype=nu.float64,flags=ndarrayFlags), ctypes.c_int, ndpointer(dtype=nu.int32,flags=ndarrayFlags), ndpointer(dtype=nu.float64,flags=ndarrayFlags), ctypes.c_double, ctypes.c_double, ctypes.c_double, ndpointer(dtype=nu.float64,flags=ndarrayFlags), ctypes.POINTER(ctypes.c_int), ctypes.c_int] #Array requirements, first store old order f_cont= [yo.flags['F_CONTIGUOUS'], t.flags['F_CONTIGUOUS']] yo= nu.require(yo,dtype=nu.float64,requirements=['C','W']) t= nu.require(t,dtype=nu.float64,requirements=['C','W']) result= nu.require(result,dtype=nu.float64,requirements=['C','W']) #Run the C code integrationFunc(yo, ctypes.c_int(len(t)), t, ctypes.c_int(npot), pot_type, pot_args, ctypes.c_double(dt), ctypes.c_double(rtol),ctypes.c_double(atol), result, ctypes.byref(err), ctypes.c_int(int_method_c)) if int(err.value) == -10: #pragma: no cover raise KeyboardInterrupt("Orbit integration interrupted by CTRL-C (SIGINT)") #Reset input arrays if f_cont[0]: yo= nu.asfortranarray(yo) if f_cont[1]: t= nu.asfortranarray(t) return (result,err.value)
NAME: integrateFullOrbit_c PURPOSE: C integrate an ode for a FullOrbit INPUT: pot - Potential or list of such instances yo - initial condition [q,p] t - set of times at which one wants the result int_method= 'leapfrog_c', 'rk4_c', 'rk6_c', 'symplec4_c' rtol, atol dt= (None) force integrator to use this stepsize (default is to automatically determine one)) OUTPUT: (y,err) y : array, shape (len(y0), len(t)) Array containing the value of y for each desired time in t, \ with the initial value y0 in the first row. err: error message, if not zero: 1 means maximum step reduction happened for adaptive integrators HISTORY: 2011-11-13 - Written - Bovy (IAS)
def get_meta(meta, name): """Retrieves the metadata variable 'name' from the 'meta' dict.""" assert name in meta data = meta[name] if data['t'] in ['MetaString', 'MetaBool']: return data['c'] elif data['t'] == 'MetaInlines': # Handle bug in pandoc 2.2.3 and 2.2.3.1: Return boolean value rather # than strings, as appropriate. if len(data['c']) == 1 and data['c'][0]['t'] == 'Str': if data['c'][0]['c'] in ['true', 'True', 'TRUE']: return True elif data['c'][0]['c'] in ['false', 'False', 'FALSE']: return False return stringify(data['c']) elif data['t'] == 'MetaList': return [stringify(v['c']) for v in data['c']] else: raise RuntimeError("Could not understand metadata variable '%s'." % name)
Retrieves the metadata variable 'name' from the 'meta' dict.
def fileinfo(self, fid): """Ask lain about what he knows about given file. If the given file exists in the file dict, it will get updated.""" if not isinstance(fid, str): raise TypeError("Your file ID must be a string") try: info = self.conn.make_call_with_cb("getFileinfo", fid).get(timeout=5) if not info: warnings.warn( f"Your query for file with ID: '{fid}' failed.", RuntimeWarning ) elif fid in self.__files and not self.__files[fid].updated: self.__files[fid].fileupdate(info) except queue.Empty as ex: raise ValueError( "lain didn't produce a callback!\n" "Are you sure your query wasn't malformed?" ) from ex return info
Ask lain about what he knows about given file. If the given file exists in the file dict, it will get updated.
def make_url(self, container=None, resource=None, query_items=None): """Create a URL from the specified parts.""" pth = [self._base_url] if container: pth.append(container.strip('/')) if resource: pth.append(resource) else: pth.append('') url = '/'.join(pth) if isinstance(query_items, (list, tuple, set)): url += RestHttp._list_query_str(query_items) query_items = None p = requests.PreparedRequest() p.prepare_url(url, query_items) return p.url
Create a URL from the specified parts.
def list_files(self, offset=None, limit=None, api=None): """List files in a folder :param api: Api instance :param offset: Pagination offset :param limit: Pagination limit :return: List of files """ api = api or self._API if not self.is_folder(): raise SbgError('{name} is not a folder'.format(name=self.name)) url = self._URL['list_folder'].format(id=self.id) return super(File, self.__class__)._query( api=api, url=url, offset=offset, limit=limit, fields='_all' )
List files in a folder :param api: Api instance :param offset: Pagination offset :param limit: Pagination limit :return: List of files
def process_tick(self, tup): """Called every window_duration """ curtime = int(time.time()) window_info = WindowContext(curtime - self.window_duration, curtime) self.processWindow(window_info, list(self.current_tuples)) for tup in self.current_tuples: self.ack(tup) self.current_tuples.clear()
Called every window_duration
def _dict_to_pio(d, class_=None): """ Convert a single dictionary object to a Physical Information Object. :param d: Dictionary to convert. :param class_: Subclass of :class:`.Pio` to produce, if not unambiguous :return: Single object derived from :class:`.Pio`. """ d = keys_to_snake_case(d) if class_: return class_(**d) if 'category' not in d: raise ValueError('Dictionary does not contains a category field: ' + ', '.join(d.keys())) elif d['category'] == 'system': return System(**d) elif d['category'] == 'system.chemical': return ChemicalSystem(**d) elif d['category'] == 'system.chemical.alloy': # Legacy support return Alloy(**d) elif d['category'] == 'system.chemical.alloy.phase': # Legacy support return ChemicalSystem(**d) raise ValueError('Dictionary does not contain a valid top-level category: ' + str(d['category']))
Convert a single dictionary object to a Physical Information Object. :param d: Dictionary to convert. :param class_: Subclass of :class:`.Pio` to produce, if not unambiguous :return: Single object derived from :class:`.Pio`.
def authorize_url(self, state=''): """ return user authorize url """ url = 'https://openapi.youku.com/v2/oauth2/authorize?' params = { 'client_id': self.client_id, 'response_type': 'code', 'state': state, 'redirect_uri': self.redirect_uri } return url + urlencode(params)
return user authorize url
def jcrop_css(css_url=None): """Load jcrop css file. :param css_url: The custom CSS URL. """ if css_url is None: if current_app.config['AVATARS_SERVE_LOCAL']: css_url = url_for('avatars.static', filename='jcrop/css/jquery.Jcrop.min.css') else: css_url = 'https://cdn.jsdelivr.net/npm/jcrop-0.9.12@0.9.12/css/jquery.Jcrop.min.css' return Markup('<link rel="stylesheet" href="%s">' % css_url)
Load jcrop css file. :param css_url: The custom CSS URL.
def last_job_statuses(self) -> List[str]: """The last constants of the job in this experiment.""" statuses = [] for status in self.jobs.values_list('status__status', flat=True): if status is not None: statuses.append(status) return statuses
The last constants of the job in this experiment.
def set_logger(self, logger): """subscribe to fortran log messages""" # we don't expect anything back try: self.library.set_logger.restype = None except AttributeError: logger.warn("Tried to set logger but method is not implemented in %s", self.engine) return # as an argument we need a pointer to a fortran log func... self.library.set_logger.argtypes = [ (fortran_log_functype)] self.library.set_logger(fortran_log_func)
subscribe to fortran log messages
def get_all_tasks(self, course): """ :return: a table containing taskid=>Task pairs """ tasks = self.get_readable_tasks(course) output = {} for task in tasks: try: output[task] = self.get_task(course, task) except: pass return output
:return: a table containing taskid=>Task pairs
def set_ylim(self, xlims, dx, xscale, reverse=False): """Set y limits for plot. This will set the limits for the y axis for the specific plot. Args: ylims (len-2 list of floats): The limits for the axis. dy (float): Amount to increment by between the limits. yscale (str): Scale of the axis. Either `log` or `lin`. reverse (bool, optional): If True, reverse the axis tick marks. Default is False. """ self._set_axis_limits('y', xlims, dx, xscale, reverse) return
Set y limits for plot. This will set the limits for the y axis for the specific plot. Args: ylims (len-2 list of floats): The limits for the axis. dy (float): Amount to increment by between the limits. yscale (str): Scale of the axis. Either `log` or `lin`. reverse (bool, optional): If True, reverse the axis tick marks. Default is False.
def does_sqlatype_require_index_len( coltype: Union[TypeEngine, VisitableType]) -> bool: """ Is the SQLAlchemy column type one that requires its indexes to have a length specified? (MySQL, at least, requires index length to be specified for ``BLOB`` and ``TEXT`` columns: http://dev.mysql.com/doc/refman/5.7/en/create-index.html.) """ coltype = _coltype_to_typeengine(coltype) if isinstance(coltype, sqltypes.Text): return True if isinstance(coltype, sqltypes.LargeBinary): return True return False
Is the SQLAlchemy column type one that requires its indexes to have a length specified? (MySQL, at least, requires index length to be specified for ``BLOB`` and ``TEXT`` columns: http://dev.mysql.com/doc/refman/5.7/en/create-index.html.)
def is_iterable(obj): """ Are we being asked to look up a list of things, instead of a single thing? We check for the `__iter__` attribute so that this can cover types that don't have to be known by this module, such as NumPy arrays. Strings, however, should be considered as atomic values to look up, not iterables. We don't need to check for the Python 2 `unicode` type, because it doesn't have an `__iter__` attribute anyway. """ # pylint: disable=consider-using-ternary return hasattr(obj, '__iter__') and not isinstance(obj, str) or isinstance(obj, GeneratorType)
Are we being asked to look up a list of things, instead of a single thing? We check for the `__iter__` attribute so that this can cover types that don't have to be known by this module, such as NumPy arrays. Strings, however, should be considered as atomic values to look up, not iterables. We don't need to check for the Python 2 `unicode` type, because it doesn't have an `__iter__` attribute anyway.
def recipients(messenger, addresses): """Structures recipients data. :param str|unicode, MessageBase messenger: MessengerBase heir :param list[str|unicode]|str|unicode addresses: recipients addresses or Django User model heir instances (NOTE: if supported by a messenger) :return: list of Recipient :rtype: list[Recipient] """ if isinstance(messenger, six.string_types): messenger = get_registered_messenger_object(messenger) return messenger._structure_recipients_data(addresses)
Structures recipients data. :param str|unicode, MessageBase messenger: MessengerBase heir :param list[str|unicode]|str|unicode addresses: recipients addresses or Django User model heir instances (NOTE: if supported by a messenger) :return: list of Recipient :rtype: list[Recipient]
def request_vpc_peering_connection(requester_vpc_id=None, requester_vpc_name=None, peer_vpc_id=None, peer_vpc_name=None, name=None, peer_owner_id=None, peer_region=None, region=None, key=None, keyid=None, profile=None, dry_run=False): ''' Request a VPC peering connection between two VPCs. .. versionadded:: 2016.11.0 requester_vpc_id ID of the requesting VPC. Exclusive with requester_vpc_name. requester_vpc_name Name tag of the requesting VPC. Exclusive with requester_vpc_id. peer_vpc_id ID of the VPC to create VPC peering connection with. This can be a VPC in another account. Exclusive with peer_vpc_name. peer_vpc_name Name tag of the VPC to create VPC peering connection with. This can only be a VPC in the same account and same region, else resolving it into a vpc ID will almost certainly fail. Exclusive with peer_vpc_id. name The name to use for this VPC peering connection. peer_owner_id ID of the owner of the peer VPC. Defaults to your account ID, so a value is required if peering with a VPC in a different account. peer_region Region of peer VPC. For inter-region vpc peering connections. Not required for intra-region peering connections. region Region to connect to. key Secret key to be used. keyid Access key to be used. profile A dict with region, key and keyid, or a pillar key (string) that contains a dict with region, key and keyid. dry_run If True, skip application and return status. CLI Example: .. code-block:: bash # Create a named VPC peering connection salt myminion boto_vpc.request_vpc_peering_connection vpc-4a3e622e vpc-be82e9da name=my_vpc_connection # Without a name salt myminion boto_vpc.request_vpc_peering_connection vpc-4a3e622e vpc-be82e9da # Specify a region salt myminion boto_vpc.request_vpc_peering_connection vpc-4a3e622e vpc-be82e9da region=us-west-2 ''' conn = _get_conn3(region=region, key=key, keyid=keyid, profile=profile) if name and _vpc_peering_conn_id_for_name(name, conn): raise SaltInvocationError('A VPC peering connection with this name already ' 'exists! Please specify a different name.') if not _exactly_one((requester_vpc_id, requester_vpc_name)): raise SaltInvocationError('Exactly one of requester_vpc_id or ' 'requester_vpc_name is required') if not _exactly_one((peer_vpc_id, peer_vpc_name)): raise SaltInvocationError('Exactly one of peer_vpc_id or ' 'peer_vpc_name is required.') if requester_vpc_name: requester_vpc_id = _get_id(vpc_name=requester_vpc_name, region=region, key=key, keyid=keyid, profile=profile) if not requester_vpc_id: return {'error': 'Could not resolve VPC name {0} to an ID'.format(requester_vpc_name)} if peer_vpc_name: peer_vpc_id = _get_id(vpc_name=peer_vpc_name, region=region, key=key, keyid=keyid, profile=profile) if not peer_vpc_id: return {'error': 'Could not resolve VPC name {0} to an ID'.format(peer_vpc_name)} peering_params = {"VpcId": requester_vpc_id, "PeerVpcId": peer_vpc_id, "DryRun": dry_run} if peer_owner_id: peering_params.update({"PeerOwnerId": peer_owner_id}) if peer_region: peering_params.update({"PeerRegion": peer_region}) try: log.debug('Trying to request vpc peering connection') vpc_peering = conn.create_vpc_peering_connection(**peering_params) peering = vpc_peering.get('VpcPeeringConnection', {}) peering_conn_id = peering.get('VpcPeeringConnectionId', 'ERROR') msg = 'VPC peering {0} requested.'.format(peering_conn_id) log.debug(msg) if name: log.debug('Adding name tag to vpc peering connection') conn.create_tags( Resources=[peering_conn_id], Tags=[{'Key': 'Name', 'Value': name}] ) log.debug('Applied name tag to vpc peering connection') msg += ' With name {0}.'.format(name) return {'msg': msg} except botocore.exceptions.ClientError as err: log.error('Got an error while trying to request vpc peering') return {'error': __utils__['boto.get_error'](err)}
Request a VPC peering connection between two VPCs. .. versionadded:: 2016.11.0 requester_vpc_id ID of the requesting VPC. Exclusive with requester_vpc_name. requester_vpc_name Name tag of the requesting VPC. Exclusive with requester_vpc_id. peer_vpc_id ID of the VPC to create VPC peering connection with. This can be a VPC in another account. Exclusive with peer_vpc_name. peer_vpc_name Name tag of the VPC to create VPC peering connection with. This can only be a VPC in the same account and same region, else resolving it into a vpc ID will almost certainly fail. Exclusive with peer_vpc_id. name The name to use for this VPC peering connection. peer_owner_id ID of the owner of the peer VPC. Defaults to your account ID, so a value is required if peering with a VPC in a different account. peer_region Region of peer VPC. For inter-region vpc peering connections. Not required for intra-region peering connections. region Region to connect to. key Secret key to be used. keyid Access key to be used. profile A dict with region, key and keyid, or a pillar key (string) that contains a dict with region, key and keyid. dry_run If True, skip application and return status. CLI Example: .. code-block:: bash # Create a named VPC peering connection salt myminion boto_vpc.request_vpc_peering_connection vpc-4a3e622e vpc-be82e9da name=my_vpc_connection # Without a name salt myminion boto_vpc.request_vpc_peering_connection vpc-4a3e622e vpc-be82e9da # Specify a region salt myminion boto_vpc.request_vpc_peering_connection vpc-4a3e622e vpc-be82e9da region=us-west-2
def friendfeed_request(self, path, callback, access_token=None, post_args=None, **args): """Fetches the given relative API path, e.g., "/bret/friends" If the request is a POST, post_args should be provided. Query string arguments should be given as keyword arguments. All the FriendFeed methods are documented at http://friendfeed.com/api/documentation. Many methods require an OAuth access token which you can obtain through authorize_redirect() and get_authenticated_user(). The user returned through that process includes an 'access_token' attribute that can be used to make authenticated requests via this method. Example usage:: class MainHandler(tornado.web.RequestHandler, tornado.auth.FriendFeedMixin): @tornado.web.authenticated @tornado.web.asynchronous def get(self): self.friendfeed_request( "/entry", post_args={"body": "Testing Tornado Web Server"}, access_token=self.current_user["access_token"], callback=self.async_callback(self._on_post)) def _on_post(self, new_entry): if not new_entry: # Call failed; perhaps missing permission? self.authorize_redirect() return self.finish("Posted a message!") """ # Add the OAuth resource request signature if we have credentials url = "http://friendfeed-api.com/v2" + path if access_token: all_args = {} all_args.update(args) all_args.update(post_args or {}) consumer_token = self._oauth_consumer_token() method = "POST" if post_args is not None else "GET" oauth = self._oauth_request_parameters( url, access_token, all_args, method=method) args.update(oauth) if args: url += "?" + urllib.urlencode(args) callback = self.async_callback(self._on_friendfeed_request, callback) http = httpclient.AsyncHTTPClient() if post_args is not None: http.fetch(url, method="POST", body=urllib.urlencode(post_args), callback=callback) else: http.fetch(url, callback=callback)
Fetches the given relative API path, e.g., "/bret/friends" If the request is a POST, post_args should be provided. Query string arguments should be given as keyword arguments. All the FriendFeed methods are documented at http://friendfeed.com/api/documentation. Many methods require an OAuth access token which you can obtain through authorize_redirect() and get_authenticated_user(). The user returned through that process includes an 'access_token' attribute that can be used to make authenticated requests via this method. Example usage:: class MainHandler(tornado.web.RequestHandler, tornado.auth.FriendFeedMixin): @tornado.web.authenticated @tornado.web.asynchronous def get(self): self.friendfeed_request( "/entry", post_args={"body": "Testing Tornado Web Server"}, access_token=self.current_user["access_token"], callback=self.async_callback(self._on_post)) def _on_post(self, new_entry): if not new_entry: # Call failed; perhaps missing permission? self.authorize_redirect() return self.finish("Posted a message!")
def generate_csr(self, basename='djangoafip'): """ Creates a CSR for this TaxPayer's key Creates a file-like object that contains the CSR which can be used to request a new certificate from AFIP. """ csr = BytesIO() crypto.create_csr( self.key.file, self.name, '{}{}'.format(basename, int(datetime.now().timestamp())), 'CUIT {}'.format(self.cuit), csr, ) csr.seek(0) return csr
Creates a CSR for this TaxPayer's key Creates a file-like object that contains the CSR which can be used to request a new certificate from AFIP.
def solve_let(expr, vars): """Solves a let-form by calling RHS with nested scope.""" lhs_value = solve(expr.lhs, vars).value if not isinstance(lhs_value, structured.IStructured): raise errors.EfilterTypeError( root=expr.lhs, query=expr.original, message="The LHS of 'let' must evaluate to an IStructured. Got %r." % (lhs_value,)) return solve(expr.rhs, __nest_scope(expr.lhs, vars, lhs_value))
Solves a let-form by calling RHS with nested scope.
def solve_tsp(V,c): """solve_tsp -- solve the traveling salesman problem - start with assignment model - check flow from a source to every other node; - if no flow, a sub-cycle has been found --> add cut - otherwise, the solution is optimal Parameters: - V: set/list of nodes in the graph - c[i,j]: cost for traversing edge (i,j) Returns the optimum objective value and the list of edges used. """ def addcut(X): for sink in V[1:]: mflow = maxflow(V,X,V[0],sink) mflow.optimize() f,cons = mflow.data if mflow.ObjVal < 2-EPS: # no flow to sink, can add cut break else: return False #add a cut/constraint CutA = set([V[0]]) for i in cons: if cons[i].Pi <= -1+EPS: CutA.add(i) CutB = set(V) - CutA main.addCons( quicksum(x[i,j] for i in CutA for j in CutB if j>i) + \ quicksum(x[j,i] for i in CutA for j in CutB if j<i) >= 2) print("mflow:",mflow.getObjVal(),"cut:",CutA,"+",CutB,">= 2") print("mflow:",mflow.getObjVal(),"cut:",[(i,j) for i in CutA for j in CutB if j>i],"+",[(j,i) for i in CutA for j in CutB if j<i],">= 2") return True def isMIP(x): for var in x: if var.vtype == "CONTINUOUS": return False return True # main part of the solution process: main = Model("tsp") x = {} for i in V: for j in V: if j > i: x[i,j] = main.addVar(ub=1, vtype="C", name="x(%s,%s)"%(i,j)) for i in V: main.addCons(quicksum(x[j,i] for j in V if j < i) + \ quicksum(x[i,j] for j in V if j > i) == 2, "Degree(%s)"%i) main.setObjective(quicksum(c[i,j]*x[i,j] for i in V for j in V if j > i), "minimize") while True: main.optimize() z = main.getObjVal() X = {} for (i,j) in x: if main.getVal(x[i,j]) > EPS: X[i,j] = main.getVal(x[i,j]) if addcut(X) == False: # i.e., components are connected if isMIP(): # integer variables, components connected: solution found break for (i,j) in x: # all components connected, switch to integer model main.chgVarType(x[i,j], "BINARY") # process solution edges = [] for (i,j) in x: if main.getVal(x[i,j]) > EPS: edges.append((i,j)) return main.getObjVal(),edges
solve_tsp -- solve the traveling salesman problem - start with assignment model - check flow from a source to every other node; - if no flow, a sub-cycle has been found --> add cut - otherwise, the solution is optimal Parameters: - V: set/list of nodes in the graph - c[i,j]: cost for traversing edge (i,j) Returns the optimum objective value and the list of edges used.
def get_email_link(email, value=None): """ Returns a well-formed link to an email address. If email is None/empty, returns an empty string :param email: email address :param link_text: text to be displayed. If None, the email itself is used :return: a well-formatted html anchor """ if not email: return "" mailto = 'mailto:{}'.format(email) link_value = value and value or email return get_link(mailto, link_value)
Returns a well-formed link to an email address. If email is None/empty, returns an empty string :param email: email address :param link_text: text to be displayed. If None, the email itself is used :return: a well-formatted html anchor
def _validate_entity_cls(self, entity_cls): """Validate that Entity is a valid class""" # Import here to avoid cyclic dependency from protean.core.entity import Entity if not issubclass(entity_cls, Entity): raise AssertionError( f'Entity {entity_cls.__name__} must be subclass of `Entity`') if entity_cls.meta_.abstract is True: raise NotSupportedError( f'{entity_cls.__name__} class has been marked abstract' f' and cannot be instantiated')
Validate that Entity is a valid class
def to_array(self): """ Serializes this InlineQueryResultMpeg4Gif to a dictionary. :return: dictionary representation of this object. :rtype: dict """ array = super(InlineQueryResultMpeg4Gif, self).to_array() array['type'] = u(self.type) # py2: type unicode, py3: type str array['id'] = u(self.id) # py2: type unicode, py3: type str array['mpeg4_url'] = u(self.mpeg4_url) # py2: type unicode, py3: type str array['thumb_url'] = u(self.thumb_url) # py2: type unicode, py3: type str if self.mpeg4_width is not None: array['mpeg4_width'] = int(self.mpeg4_width) # type int if self.mpeg4_height is not None: array['mpeg4_height'] = int(self.mpeg4_height) # type int if self.mpeg4_duration is not None: array['mpeg4_duration'] = int(self.mpeg4_duration) # type int if self.title is not None: array['title'] = u(self.title) # py2: type unicode, py3: type str if self.caption is not None: array['caption'] = u(self.caption) # py2: type unicode, py3: type str if self.parse_mode is not None: array['parse_mode'] = u(self.parse_mode) # py2: type unicode, py3: type str if self.reply_markup is not None: array['reply_markup'] = self.reply_markup.to_array() # type InlineKeyboardMarkup if self.input_message_content is not None: array['input_message_content'] = self.input_message_content.to_array() # type InputMessageContent return array
Serializes this InlineQueryResultMpeg4Gif to a dictionary. :return: dictionary representation of this object. :rtype: dict
def is_bootstrapped(metadata): """Return True if cihai is correctly bootstrapped.""" fields = UNIHAN_FIELDS + DEFAULT_COLUMNS if TABLE_NAME in metadata.tables.keys(): table = metadata.tables[TABLE_NAME] if set(fields) == set(c.name for c in table.columns): return True else: return False else: return False
Return True if cihai is correctly bootstrapped.
def removeBiosample(self, biosample): """ Removes the specified biosample from this repository. """ q = models.Biosample.delete().where( models.Biosample.id == biosample.getId()) q.execute()
Removes the specified biosample from this repository.
def main(): """ Simple command-line program for powering on virtual machines on a system. """ args = GetArgs() if args.password: password = args.password else: password = getpass.getpass(prompt='Enter password for host %s and user %s: ' % (args.host,args.user)) try: vmnames = args.vmname if not len(vmnames): print("No virtual machine specified for poweron") sys.exit() context = None if hasattr(ssl, '_create_unverified_context'): context = ssl._create_unverified_context() si = SmartConnect(host=args.host, user=args.user, pwd=password, port=int(args.port), sslContext=context) if not si: print("Cannot connect to specified host using specified username and password") sys.exit() atexit.register(Disconnect, si) # Retreive the list of Virtual Machines from the inventory objects # under the rootFolder content = si.content objView = content.viewManager.CreateContainerView(content.rootFolder, [vim.VirtualMachine], True) vmList = objView.view objView.Destroy() # Find the vm and power it on tasks = [vm.PowerOn() for vm in vmList if vm.name in vmnames] # Wait for power on to complete WaitForTasks(tasks, si) print("Virtual Machine(s) have been powered on successfully") except vmodl.MethodFault as e: print("Caught vmodl fault : " + e.msg) except Exception as e: print("Caught Exception : " + str(e))
Simple command-line program for powering on virtual machines on a system.
def t_op(self, s): r'\+=|-=|\*=|/=|%=|&=|\|=|^=|<<=|>>=|\*\*=|//=|//|==|<=|>=|<<|>>|[<>%^&+/=~-]' # Operators need to be further classified since the grammar requires this if s in ('<', '>', '==', '>=', '<=', '<>', '!='): self.add_token('COMP_OP', s) elif s in ('+=', '-=', '*=', '/=', '%=', '&=', '|=', '^=', '<<=', '>>=', '**=', '//='): self.add_token('AUGASSIGN', s) elif s in self.UNOP2NAME.keys(): self.add_token(self.UNOP2NAME[s], s) elif s in ('|', '^', '&', '<<', '>>', '**', '/', '%', '//'): # These are *ONLY* binary operators. Operators which are exclusively or # can be unary operators were handled previously self.add_token('BINOP', s) elif s == '=': self.add_token('EQUAL', s) else: print("Internal error: Unknown operator %s" % s) raise SystemExit
r'\+=|-=|\*=|/=|%=|&=|\|=|^=|<<=|>>=|\*\*=|//=|//|==|<=|>=|<<|>>|[<>%^&+/=~-]
def whole_subnet_maker(ip_addr, cidr): """ Function to return a whole subnet value from a IP address and CIDR pair Args: ip_addr: Unicast or Multicast IP address or subnet in the following format 192.168.1.1, 239.1.1.1 cidr: CIDR value of 0 to 32 Returns: returns the corrected whole subnet """ if ucast_ip(ip_addr, False) == False and mcast_ip(ip_addr, False) == False: LOGGER.critical('Function whole_subnet_maker ip_addr {item}'.format(item=ip_addr)) raise ValueError("Not a good ipv4 address") if not cidr_check(cidr, False): LOGGER.critical('Function whole_subnet_maker cidr {item}'.format(item=cidr)) raise ValueError("Not a good CIDR value should be 0 to 32") def subnet_corrector(octet, cidr): """ Function to correct a octet for a subnet """ cidr_int = int(cidr) octet_int = int(octet) if cidr_int >= 24: cidr_int = __mask_conversion[cidr_int]["OCT4"] elif cidr_int >= 16: cidr_int = __mask_conversion[cidr_int]["OCT3"] elif cidr_int >= 8: cidr_int = __mask_conversion[cidr_int]["OCT2"] elif cidr_int >= 1: cidr_int = __mask_conversion[cidr_int]["OCT1"] cidr_count = 0 cidr_v = 256 - cidr_int cidr_2 = 256 - cidr_int while cidr_count < 300: if octet_int >= cidr_count and octet_int <= cidr_2: cidr_int = cidr_count cidr_count = cidr_2 cidr_2 = cidr_2 + cidr_v return str(cidr_int) ip_addr_split = ip_addr.split(".") if int(cidr) >= 24: octet = subnet_corrector(ip_addr_split[3], cidr) completed = ip_addr_split[0] + "." + ip_addr_split[1] + "." + ip_addr_split[2] + "." + octet return completed elif int(cidr) >= 16: octet = subnet_corrector(ip_addr_split[2], cidr) completed = ip_addr_split[0] + "." + ip_addr_split[1] + "." + octet + ".0" return completed elif int(cidr) >= 8: octet = subnet_corrector(ip_addr_split[1], cidr) completed = ip_addr_split[0] + "." + octet + ".0.0" return completed elif int(cidr) >= 1: octet = subnet_corrector(ip_addr_split[0], cidr) completed = octet + ".0.0.0" return completed else: return "0.0.0.0"
Function to return a whole subnet value from a IP address and CIDR pair Args: ip_addr: Unicast or Multicast IP address or subnet in the following format 192.168.1.1, 239.1.1.1 cidr: CIDR value of 0 to 32 Returns: returns the corrected whole subnet
def spdhg_generic(x, f, g, A, tau, sigma, niter, **kwargs): r"""Computes a saddle point with a stochastic PDHG. This means, a solution (x*, y*), y* = (y*_1, ..., y*_n) such that (x*, y*) in arg min_x max_y sum_i=1^n <y_i, A_i> - f*[i](y_i) + g(x) where g : X -> IR_infty and f[i] : Y[i] -> IR_infty are convex, l.s.c. and proper functionals. For this algorithm, they all may be non-smooth and no strong convexity is assumed. Parameters ---------- x : primal variable This variable is both input and output of the method. f : functions Functionals Y[i] -> IR_infty that all have a convex conjugate with a proximal operator, i.e. f[i].convex_conj.proximal(sigma[i]) : Y[i] -> Y[i]. g : function Functional X -> IR_infty that has a proximal operator, i.e. g.proximal(tau) : X -> X. A : functions Operators A[i] : X -> Y[i] that possess adjoints: A[i].adjoint tau : scalar / vector / matrix Step size for primal variable. Note that the proximal operator of g has to be well-defined for this input. sigma : scalar Scalar / vector / matrix used as step size for dual variable. Note that the proximal operator related to f (see above) has to be well-defined for this input. niter : int Number of iterations Other Parameters ---------------- y : dual variable, optional Dual variable is part of a product space. By default equals 0. z : variable, optional Adjoint of dual variable, z = A^* y. By default equals 0 if y = 0. mu_g : scalar Strong convexity constant of g. theta : scalar Global extrapolation factor. extra: list List of local extrapolation paramters for every index i. By default extra_i = 1. fun_select : function Function that selects blocks at every iteration IN -> {1,...,n}. By default this is serial uniform sampling, fun_select(k) selects an index i \in {1,...,n} with probability 1/n. callback : callable, optional Function called with the current iterate after each iteration. References ---------- [CERS2017] A. Chambolle, M. J. Ehrhardt, P. Richtarik and C.-B. Schoenlieb, *Stochastic Primal-Dual Hybrid Gradient Algorithm with Arbitrary Sampling and Imaging Applications*. ArXiv: http://arxiv.org/abs/1706.04957 (2017). [E+2017] M. J. Ehrhardt, P. J. Markiewicz, P. Richtarik, J. Schott, A. Chambolle and C.-B. Schoenlieb, *Faster PET reconstruction with a stochastic primal-dual hybrid gradient method*. Wavelets and Sparsity XVII, 58 (2017) http://doi.org/10.1117/12.2272946. """ # Callback object callback = kwargs.pop('callback', None) if callback is not None and not callable(callback): raise TypeError('`callback` {} is not callable' ''.format(callback)) # Dual variable y = kwargs.pop('y', None) if y is None: y = A.range.zero() # Adjoint of dual variable z = kwargs.pop('z', None) if z is None: if y.norm() == 0: z = A.domain.zero() else: z = A.adjoint(y) # Strong convexity of g mu_g = kwargs.pop('mu_g', None) if mu_g is None: update_proximal_primal = False else: update_proximal_primal = True # Global extrapolation factor theta theta = kwargs.pop('theta', 1) # Second extrapolation factor extra = kwargs.pop('extra', None) if extra is None: extra = [1] * len(sigma) # Selection function fun_select = kwargs.pop('fun_select', None) if fun_select is None: def fun_select(x): return [int(np.random.choice(len(A), 1, p=1 / len(A)))] # Initialize variables z_relax = z.copy() dz = A.domain.element() y_old = A.range.element() # Save proximal operators proximal_dual_sigma = [fi.convex_conj.proximal(si) for fi, si in zip(f, sigma)] proximal_primal_tau = g.proximal(tau) # run the iterations for k in range(niter): # select block selected = fun_select(k) # update primal variable # tmp = x - tau * z_relax; z_relax used as tmp variable z_relax.lincomb(1, x, -tau, z_relax) # x = prox(tmp) proximal_primal_tau(z_relax, out=x) # update extrapolation parameter theta if update_proximal_primal: theta = float(1 / np.sqrt(1 + 2 * mu_g * tau)) # update dual variable and z, z_relax z_relax.assign(z) for i in selected: # save old yi y_old[i].assign(y[i]) # tmp = Ai(x) A[i](x, out=y[i]) # tmp = y_old + sigma_i * Ai(x) y[i].lincomb(1, y_old[i], sigma[i], y[i]) # y[i]= prox(tmp) proximal_dual_sigma[i](y[i], out=y[i]) # update adjoint of dual variable y_old[i].lincomb(-1, y_old[i], 1, y[i]) A[i].adjoint(y_old[i], out=dz) z += dz # compute extrapolation z_relax.lincomb(1, z_relax, 1 + theta * extra[i], dz) # update the step sizes tau and sigma for acceleration if update_proximal_primal: for i in range(len(sigma)): sigma[i] /= theta tau *= theta proximal_dual_sigma = [fi.convex_conj.proximal(si) for fi, si in zip(f, sigma)] proximal_primal_tau = g.proximal(tau) if callback is not None: callback([x, y])
r"""Computes a saddle point with a stochastic PDHG. This means, a solution (x*, y*), y* = (y*_1, ..., y*_n) such that (x*, y*) in arg min_x max_y sum_i=1^n <y_i, A_i> - f*[i](y_i) + g(x) where g : X -> IR_infty and f[i] : Y[i] -> IR_infty are convex, l.s.c. and proper functionals. For this algorithm, they all may be non-smooth and no strong convexity is assumed. Parameters ---------- x : primal variable This variable is both input and output of the method. f : functions Functionals Y[i] -> IR_infty that all have a convex conjugate with a proximal operator, i.e. f[i].convex_conj.proximal(sigma[i]) : Y[i] -> Y[i]. g : function Functional X -> IR_infty that has a proximal operator, i.e. g.proximal(tau) : X -> X. A : functions Operators A[i] : X -> Y[i] that possess adjoints: A[i].adjoint tau : scalar / vector / matrix Step size for primal variable. Note that the proximal operator of g has to be well-defined for this input. sigma : scalar Scalar / vector / matrix used as step size for dual variable. Note that the proximal operator related to f (see above) has to be well-defined for this input. niter : int Number of iterations Other Parameters ---------------- y : dual variable, optional Dual variable is part of a product space. By default equals 0. z : variable, optional Adjoint of dual variable, z = A^* y. By default equals 0 if y = 0. mu_g : scalar Strong convexity constant of g. theta : scalar Global extrapolation factor. extra: list List of local extrapolation paramters for every index i. By default extra_i = 1. fun_select : function Function that selects blocks at every iteration IN -> {1,...,n}. By default this is serial uniform sampling, fun_select(k) selects an index i \in {1,...,n} with probability 1/n. callback : callable, optional Function called with the current iterate after each iteration. References ---------- [CERS2017] A. Chambolle, M. J. Ehrhardt, P. Richtarik and C.-B. Schoenlieb, *Stochastic Primal-Dual Hybrid Gradient Algorithm with Arbitrary Sampling and Imaging Applications*. ArXiv: http://arxiv.org/abs/1706.04957 (2017). [E+2017] M. J. Ehrhardt, P. J. Markiewicz, P. Richtarik, J. Schott, A. Chambolle and C.-B. Schoenlieb, *Faster PET reconstruction with a stochastic primal-dual hybrid gradient method*. Wavelets and Sparsity XVII, 58 (2017) http://doi.org/10.1117/12.2272946.
def overlap_bbox_and_point(bbox, xp, yp): """Given a bbox that contains a given point, return the (x, y) displacement necessary to make the bbox not overlap the point.""" cx, cy = get_midpoint(bbox) dir_x = np.sign(cx-xp) dir_y = np.sign(cy-yp) if dir_x == -1: dx = xp - bbox.xmax elif dir_x == 1: dx = xp - bbox.xmin else: dx = 0 if dir_y == -1: dy = yp - bbox.ymax elif dir_y == 1: dy = yp - bbox.ymin else: dy = 0 return dx, dy
Given a bbox that contains a given point, return the (x, y) displacement necessary to make the bbox not overlap the point.
def envs(backend=None, sources=False): ''' Return the available fileserver environments. If no backend is provided, then the environments for all configured backends will be returned. backend Narrow fileserver backends to a subset of the enabled ones. .. versionchanged:: 2015.5.0 If all passed backends start with a minus sign (``-``), then these backends will be excluded from the enabled backends. However, if there is a mix of backends with and without a minus sign (ex: ``backend=-roots,git``) then the ones starting with a minus sign will be disregarded. Additionally, fileserver backends can now be passed as a comma-separated list. In earlier versions, they needed to be passed as a python list (ex: ``backend="['roots', 'git']"``) CLI Example: .. code-block:: bash salt-run fileserver.envs salt-run fileserver.envs backend=roots,git salt-run fileserver.envs git ''' fileserver = salt.fileserver.Fileserver(__opts__) return sorted(fileserver.envs(back=backend, sources=sources))
Return the available fileserver environments. If no backend is provided, then the environments for all configured backends will be returned. backend Narrow fileserver backends to a subset of the enabled ones. .. versionchanged:: 2015.5.0 If all passed backends start with a minus sign (``-``), then these backends will be excluded from the enabled backends. However, if there is a mix of backends with and without a minus sign (ex: ``backend=-roots,git``) then the ones starting with a minus sign will be disregarded. Additionally, fileserver backends can now be passed as a comma-separated list. In earlier versions, they needed to be passed as a python list (ex: ``backend="['roots', 'git']"``) CLI Example: .. code-block:: bash salt-run fileserver.envs salt-run fileserver.envs backend=roots,git salt-run fileserver.envs git
def count(self): """ Count the number of domain for each status. """ if self.status: # The status is parsed. # We increase the number of tested. PyFunceble.INTERN["counter"]["number"]["tested"] += 1 if ( self.status.lower() in PyFunceble.STATUS["list"]["up"] or self.status.lower() in PyFunceble.STATUS["list"]["valid"] ): # The status is in the list of up status. # We increase the number of up. PyFunceble.INTERN["counter"]["number"]["up"] += 1 elif self.status.lower() in PyFunceble.STATUS["list"]["down"]: # The status is in the list of down status. # We increase the number of down. PyFunceble.INTERN["counter"]["number"]["down"] += 1 else: # The status is not in the list of up nor down status. # We increase the number of invalid. PyFunceble.INTERN["counter"]["number"]["invalid"] += 1
Count the number of domain for each status.
def _ctorCmprRange(self, vals): ''' Override default *range= handler to account for relative computation. ''' if not isinstance(vals, (list, tuple)): raise s_exc.BadCmprValu(valu=vals, cmpr='*range=') if len(vals) != 2: raise s_exc.BadCmprValu(valu=vals, cmpr='*range=') tick, tock = self.getTickTock(vals) if tick > tock: # User input has requested a nullset def cmpr(valu): return False return cmpr def cmpr(valu): return tick <= valu <= tock return cmpr
Override default *range= handler to account for relative computation.
def create_superuser(self, email, password, **extra_fields): """Save new User with is_staff and is_superuser set to True""" extra_fields.setdefault('is_staff', True) extra_fields.setdefault('is_superuser', True) if extra_fields.get('is_staff') is not True: raise ValueError('Superuser must have is_staff=True.') if extra_fields.get('is_superuser') is not True: raise ValueError('Superuser must have is_superuser=True.') return self._create_user(email, password, **extra_fields)
Save new User with is_staff and is_superuser set to True
def apply(self, spectrum, plot=False): """ Apply the filter to the given [W, F], or [W, F, E] spectrum Parameters ---------- spectrum: array-like The wavelength [um] and flux of the spectrum to apply the filter to plot: bool Plot the original and filtered spectrum Returns ------- np.ndarray The filtered spectrum and error """ # Convert to filter units if possible f_units = 1. if hasattr(spectrum[0], 'unit'): spectrum[0] = spectrum[0].to(self.wave_units) if hasattr(spectrum[1], 'unit'): spectrum[1] = spectrum[1].to(self.flux_units) f_units = self.flux_units if len(spectrum) >= 3 and hasattr(spectrum[2], 'unit'): spectrum[2] = spectrum[2].to(self.flux_units) # Make into iterable arrays wav, flx, *err = [np.asarray(i) for i in spectrum] # Check for error array if len(err) == 0: err = np.ones_like(flx)*np.nan unc = False else: err = err[0] unc = True # Make flux 2D if len(flx.shape) == 1: flx = np.expand_dims(flx, axis=0) err = np.expand_dims(err, axis=0) # Make throughput 3D rsr = np.copy(self.rsr) # Make empty filtered arrays filtered_flx = np.zeros((rsr.shape[0], flx.shape[0], rsr.shape[2])) filtered_err = np.zeros_like(filtered_flx) # Rebin the input spectra to the filter wavelength array # and apply the RSR curve to the spectrum for i, bn in enumerate(rsr): for j, (f, e) in enumerate(zip(flx, err)): filtered_flx[i][j] = np.interp(bn[0], wav, f, left=np.nan, right=np.nan)*bn[1] filtered_err[i][j] = np.interp(bn[0], wav, e, left=np.nan, right=np.nan)*bn[1] # Propagate the filter systematic uncertainties if unc: filtered_err += filtered_flx*self.systematics if plot: # Make the figure COLORS = color_gen('Category10') xlab = 'Wavelength [{}]'.format(self.wave_units) ylab = 'Flux Density [{}]'.format(self.flux_units) fig = figure(title=self.filterID, x_axis_label=xlab, y_axis_label=ylab) # Plot the unfiltered spectrum fig.line(wav, flx[0], legend='Input spectrum', color='black') # Plot the uncertainties if unc: band_x = np.append(wav, wav[::-1]) band_y = np.append(flx-err, (flx+err)[::-1]) fig.patch(band_x, band_y, color='black', fill_alpha=0.1, line_alpha=0) # Plot each spectrum bin for wav, bn, bne in zip(self.wave, filtered_flx, filtered_err): color = next(COLORS) fig.line(wav, bn[0], color=color) # Plot the uncertainties if unc: band_x = np.append(wav, wav[::-1]) band_y = np.append(bn[0]-bne[0], (bn[0]+bne[0])[::-1]) fig.patch(band_x, band_y, color=color, fill_alpha=0.1, line_alpha=0) show(fig) return filtered_flx.squeeze()*f_units, filtered_err.squeeze()*f_units
Apply the filter to the given [W, F], or [W, F, E] spectrum Parameters ---------- spectrum: array-like The wavelength [um] and flux of the spectrum to apply the filter to plot: bool Plot the original and filtered spectrum Returns ------- np.ndarray The filtered spectrum and error
async def movehere(self, channel): """ Moves the embed message to a new channel; can also be used to move the musicplayer to the front Args: channel (discord.Channel): The channel to move to """ self.logger.debug("movehere command") # Delete the old message await self.embed.delete() # Set the channel to this channel self.embed.channel = channel # Send a new embed to the channel await self.embed.send() # Re-add the reactions await self.add_reactions() self.statuslog.info("Moved to front")
Moves the embed message to a new channel; can also be used to move the musicplayer to the front Args: channel (discord.Channel): The channel to move to
def norm_slash(name): """Normalize path slashes.""" if isinstance(name, str): return name.replace('/', "\\") if not is_case_sensitive() else name else: return name.replace(b'/', b"\\") if not is_case_sensitive() else name
Normalize path slashes.
def transliterate(table, text): """ Transliterate text according to one of the tables above. `table` chooses the table. It looks like a language code but comes from a very restricted set: - 'sr-Latn' means to convert Serbian, which may be in Cyrillic, into the Latin alphabet. - 'az-Latn' means the same for Azerbaijani Cyrillic to Latn. """ if table == 'sr-Latn': return text.translate(SR_LATN_TABLE) elif table == 'az-Latn': return text.translate(AZ_LATN_TABLE) else: raise ValueError("Unknown transliteration table: {!r}".format(table))
Transliterate text according to one of the tables above. `table` chooses the table. It looks like a language code but comes from a very restricted set: - 'sr-Latn' means to convert Serbian, which may be in Cyrillic, into the Latin alphabet. - 'az-Latn' means the same for Azerbaijani Cyrillic to Latn.
def URIUnescapeString(str, len, target): """Unescaping routine, but does not check that the string is an URI. The output is a direct unsigned char translation of %XX values (no encoding) Note that the length of the result can only be smaller or same size as the input string. """ ret = libxml2mod.xmlURIUnescapeString(str, len, target) return ret
Unescaping routine, but does not check that the string is an URI. The output is a direct unsigned char translation of %XX values (no encoding) Note that the length of the result can only be smaller or same size as the input string.
def normalize_name(decl): """ Cached variant of normalize Args: decl (declaration.declaration_t): the declaration Returns: str: normalized name """ if decl.cache.normalized_name is None: decl.cache.normalized_name = normalize(decl.name) return decl.cache.normalized_name
Cached variant of normalize Args: decl (declaration.declaration_t): the declaration Returns: str: normalized name
def legal_graph(graph): '''judge if a graph is legal or not. ''' descriptor = graph.extract_descriptor() skips = descriptor.skip_connections if len(skips) != len(set(skips)): return False return True
judge if a graph is legal or not.
def GetNBits(value, nbits): """ Get the first `nbits` from `value`. :param value: Source value from which to extract :type value: int or long or BitVec :param int nbits: How many bits to extract :return: Low `nbits` bits of `value`. :rtype int or long or BitVec """ # NOP if sizes are the same if isinstance(value, int): return Operators.EXTRACT(value, 0, nbits) elif isinstance(value, BitVec): if value.size < nbits: return Operators.ZEXTEND(value, nbits) else: return Operators.EXTRACT(value, 0, nbits)
Get the first `nbits` from `value`. :param value: Source value from which to extract :type value: int or long or BitVec :param int nbits: How many bits to extract :return: Low `nbits` bits of `value`. :rtype int or long or BitVec
def state(self, context): """ Get instance state. :param resort.engine.execution.Context context: Current execution context. :rtype: str :return: Instance state name. """ state = None for line in self.read(context, [ "status", context.resolve(self.__name) ]): if line[2] == "state": state = line[3].strip() return state
Get instance state. :param resort.engine.execution.Context context: Current execution context. :rtype: str :return: Instance state name.
def _validate_compression_params(self, img_array, cparams, colorspace): """Check that the compression parameters are valid. Parameters ---------- img_array : ndarray Image data to be written to file. cparams : CompressionParametersType(ctypes.Structure) Corresponds to cparameters_t type in openjp2 headers. """ self._validate_j2k_colorspace(cparams, colorspace) self._validate_codeblock_size(cparams) self._validate_precinct_size(cparams) self._validate_image_rank(img_array) self._validate_image_datatype(img_array)
Check that the compression parameters are valid. Parameters ---------- img_array : ndarray Image data to be written to file. cparams : CompressionParametersType(ctypes.Structure) Corresponds to cparameters_t type in openjp2 headers.
def iterate(self, params, repetition, iteration): """ Called once for each training iteration (== epoch here). """ try: print("\nStarting iteration",iteration) t1 = time.time() ret = {} # Update learning rate using learning rate scheduler if configured if self.lr_scheduler is not None: # ReduceLROnPlateau lr_scheduler step should be called after validation, # all other lr_schedulers should be called before training if params["lr_scheduler"] != "ReduceLROnPlateau": self.lr_scheduler.step() self.train(params, epoch=iteration) # Run validation test if self.validation_loader is not None: validation = self.test(params, self.validation_loader) # ReduceLROnPlateau step should be called after validation if params["lr_scheduler"] == "ReduceLROnPlateau": self.lr_scheduler.step(validation["test_loss"]) ret["validation"] = validation print("Validation: Test error=", validation["testerror"], "entropy=", validation["entropy"]) # Run noise test if (params["test_noise_every_epoch"] or iteration == params["iterations"] - 1): ret.update(self.runNoiseTests(params)) print("Noise test results: totalCorrect=", ret["totalCorrect"], "Test error=", ret["testerror"], ", entropy=", ret["entropy"]) if ret["totalCorrect"] > 100000 and ret["testerror"] > 98.3: print("*******") print(params) ret.update({"elapsedTime": time.time() - self.startTime}) ret.update({"learningRate": self.learningRate if self.lr_scheduler is None else self.lr_scheduler.get_lr()}) print("Iteration time= {0:.3f} secs, " "total elapsed time= {1:.3f} mins".format( time.time() - t1,ret["elapsedTime"]/60.0)) except Exception as e: # Tracebacks are not printed if using multiprocessing so we do it here tb = sys.exc_info()[2] traceback.print_tb(tb) raise RuntimeError("Something went wrong in iterate", e) return ret
Called once for each training iteration (== epoch here).
def crud_mutation_name(action, model): """ This function returns the name of a mutation that performs the specified crud action on the given model service """ model_string = get_model_string(model) # make sure the mutation name is correctly camelcases model_string = model_string[0].upper() + model_string[1:] # return the mutation name return "{}{}".format(action, model_string)
This function returns the name of a mutation that performs the specified crud action on the given model service
def current(instance=True): """Returns the current thread's `IOLoop`. If an `IOLoop` is currently running or has been marked as current by `make_current`, returns that instance. If there is no current `IOLoop` and ``instance`` is true, creates one. .. versionchanged:: 4.1 Added ``instance`` argument to control the fallback to `IOLoop.instance()`. .. versionchanged:: 5.0 The ``instance`` argument now controls whether an `IOLoop` is created automatically when there is none, instead of whether we fall back to `IOLoop.instance()` (which is now an alias for this method) """ current = getattr(IOLoop._current, "instance", None) if current is None and instance: current = None #if asyncio is not None: # from tornado.platform.asyncio import AsyncIOLoop, AsyncIOMainLoop # if IOLoop.configured_class() is AsyncIOLoop: # current = AsyncIOMainLoop() if current is None: if sys.platform == 'darwin': from .platforms import KQueueIOLoop current = KQueueIOLoop() else: from .platforms import EPollIOLoop current = EPollIOLoop() current.initialize() #current = IOLoop() if IOLoop._current.instance is not current: raise RuntimeError("new IOLoop did not become current") return current
Returns the current thread's `IOLoop`. If an `IOLoop` is currently running or has been marked as current by `make_current`, returns that instance. If there is no current `IOLoop` and ``instance`` is true, creates one. .. versionchanged:: 4.1 Added ``instance`` argument to control the fallback to `IOLoop.instance()`. .. versionchanged:: 5.0 The ``instance`` argument now controls whether an `IOLoop` is created automatically when there is none, instead of whether we fall back to `IOLoop.instance()` (which is now an alias for this method)
def time_zone_by_name(self, hostname): """ Returns time zone in tzdata format (e.g. America/New_York or Europe/Paris) :arg hostname: Hostname (e.g. example.com) """ addr = self._gethostbyname(hostname) return self.time_zone_by_addr(addr)
Returns time zone in tzdata format (e.g. America/New_York or Europe/Paris) :arg hostname: Hostname (e.g. example.com)
def get_classification_node(self, project, structure_group, path=None, depth=None): """GetClassificationNode. Gets the classification node for a given node path. :param str project: Project ID or project name :param TreeStructureGroup structure_group: Structure group of the classification node, area or iteration. :param str path: Path of the classification node. :param int depth: Depth of children to fetch. :rtype: :class:`<WorkItemClassificationNode> <azure.devops.v5_0.work_item_tracking.models.WorkItemClassificationNode>` """ route_values = {} if project is not None: route_values['project'] = self._serialize.url('project', project, 'str') if structure_group is not None: route_values['structureGroup'] = self._serialize.url('structure_group', structure_group, 'TreeStructureGroup') if path is not None: route_values['path'] = self._serialize.url('path', path, 'str') query_parameters = {} if depth is not None: query_parameters['$depth'] = self._serialize.query('depth', depth, 'int') response = self._send(http_method='GET', location_id='5a172953-1b41-49d3-840a-33f79c3ce89f', version='5.0', route_values=route_values, query_parameters=query_parameters) return self._deserialize('WorkItemClassificationNode', response)
GetClassificationNode. Gets the classification node for a given node path. :param str project: Project ID or project name :param TreeStructureGroup structure_group: Structure group of the classification node, area or iteration. :param str path: Path of the classification node. :param int depth: Depth of children to fetch. :rtype: :class:`<WorkItemClassificationNode> <azure.devops.v5_0.work_item_tracking.models.WorkItemClassificationNode>`
def calc_geo_dist_vincenty(node_source, node_target): """ Calculates the geodesic distance between `node_source` and `node_target` incorporating the detour factor specified in :file:`ding0/ding0/config/config_calc.cfg`. Parameters ---------- node_source: LVStationDing0, GeneratorDing0, or CableDistributorDing0 source node, member of GridDing0._graph node_target: LVStationDing0, GeneratorDing0, or CableDistributorDing0 target node, member of GridDing0._graph Returns ------- :any:`float` Distance in m """ branch_detour_factor = cfg_ding0.get('assumptions', 'branch_detour_factor') # notice: vincenty takes (lat,lon) branch_length = branch_detour_factor * vincenty((node_source.geo_data.y, node_source.geo_data.x), (node_target.geo_data.y, node_target.geo_data.x)).m # ========= BUG: LINE LENGTH=0 WHEN CONNECTING GENERATORS =========== # When importing generators, the geom_new field is used as position. If it is empty, EnergyMap's geom # is used and so there are a couple of generators at the same position => length of interconnecting # line is 0. See issue #76 if branch_length == 0: branch_length = 1 logger.warning('Geo distance is zero, check objects\' positions. ' 'Distance is set to 1m') # =================================================================== return branch_length
Calculates the geodesic distance between `node_source` and `node_target` incorporating the detour factor specified in :file:`ding0/ding0/config/config_calc.cfg`. Parameters ---------- node_source: LVStationDing0, GeneratorDing0, or CableDistributorDing0 source node, member of GridDing0._graph node_target: LVStationDing0, GeneratorDing0, or CableDistributorDing0 target node, member of GridDing0._graph Returns ------- :any:`float` Distance in m
def extract_key_value(line, environ): """Return key, value from given line if present, else return None. """ segments = line.split("=", 1) if len(segments) < 2: return None key, value = segments # foo passes through as-is (with spaces stripped) # '{foo}' passes through literally # "{foo}" substitutes from environ's foo value = value.strip() if value[0] == "'" and _SQUOTE_RE.match(value): value = value[1:-1] elif value[0] == '"' and _DQUOTE_RE.match(value): template = value[1:-1] value = template.format(**environ) key = key.strip() value = value.strip() return key, value
Return key, value from given line if present, else return None.
def _adjust_legend(self, overlay, axis): """ Accumulate the legend handles and labels for all subplots and set up the legend """ legend_data = [] dimensions = overlay.kdims title = ', '.join([d.name for d in dimensions]) for key, subplot in self.subplots.items(): element = overlay.data.get(key, False) if not subplot.show_legend or not element: continue title = ', '.join([d.name for d in dimensions]) handle = subplot.traverse(lambda p: p.handles['artist'], [lambda p: 'artist' in p.handles]) if isinstance(overlay, NdOverlay): key = (dim.pprint_value(k) for k, dim in zip(key, dimensions)) label = ','.join([str(k) + dim.unit if dim.unit else str(k) for dim, k in zip(dimensions, key)]) if handle: legend_data.append((handle, label)) else: if isinstance(subplot, OverlayPlot): legend_data += subplot.handles.get('legend_data', {}).items() elif element.label and handle: legend_data.append((handle, element.label)) all_handles, all_labels = list(zip(*legend_data)) if legend_data else ([], []) data = OrderedDict() used_labels = [] for handle, label in zip(all_handles, all_labels): # Ensure that artists with multiple handles are supported if isinstance(handle, list): handle = tuple(handle) if handle and (handle not in data) and label and label not in used_labels: data[handle] = label used_labels.append(label) if (not len(set(data.values())) > 0) or not self.show_legend: legend = axis.get_legend() if legend: legend.set_visible(False) else: leg_spec = self.legend_specs[self.legend_position] if self.legend_cols: leg_spec['ncol'] = self.legend_cols leg = axis.legend(list(data.keys()), list(data.values()), title=title, scatterpoints=1, **dict(leg_spec, **self._fontsize('legend'))) title_fontsize = self._fontsize('legend_title') if title_fontsize: leg.get_title().set_fontsize(title_fontsize['fontsize']) frame = leg.get_frame() frame.set_facecolor('1.0') frame.set_edgecolor('0.0') frame.set_linewidth('1.0') leg.set_zorder(10e6) self.handles['legend'] = leg self.handles['bbox_extra_artists'].append(leg) self.handles['legend_data'] = data
Accumulate the legend handles and labels for all subplots and set up the legend
def intervaljoin(left, right, lstart='start', lstop='stop', rstart='start', rstop='stop', lkey=None, rkey=None, include_stop=False, lprefix=None, rprefix=None): """ Join two tables by overlapping intervals. E.g.:: >>> import petl as etl >>> left = [['begin', 'end', 'quux'], ... [1, 2, 'a'], ... [2, 4, 'b'], ... [2, 5, 'c'], ... [9, 14, 'd'], ... [1, 1, 'e'], ... [10, 10, 'f']] >>> right = [['start', 'stop', 'value'], ... [1, 4, 'foo'], ... [3, 7, 'bar'], ... [4, 9, 'baz']] >>> table1 = etl.intervaljoin(left, right, ... lstart='begin', lstop='end', ... rstart='start', rstop='stop') >>> table1.lookall() +-------+-----+------+-------+------+-------+ | begin | end | quux | start | stop | value | +=======+=====+======+=======+======+=======+ | 1 | 2 | 'a' | 1 | 4 | 'foo' | +-------+-----+------+-------+------+-------+ | 2 | 4 | 'b' | 1 | 4 | 'foo' | +-------+-----+------+-------+------+-------+ | 2 | 4 | 'b' | 3 | 7 | 'bar' | +-------+-----+------+-------+------+-------+ | 2 | 5 | 'c' | 1 | 4 | 'foo' | +-------+-----+------+-------+------+-------+ | 2 | 5 | 'c' | 3 | 7 | 'bar' | +-------+-----+------+-------+------+-------+ | 2 | 5 | 'c' | 4 | 9 | 'baz' | +-------+-----+------+-------+------+-------+ >>> # include stop coordinate in intervals ... table2 = etl.intervaljoin(left, right, ... lstart='begin', lstop='end', ... rstart='start', rstop='stop', ... include_stop=True) >>> table2.lookall() +-------+-----+------+-------+------+-------+ | begin | end | quux | start | stop | value | +=======+=====+======+=======+======+=======+ | 1 | 2 | 'a' | 1 | 4 | 'foo' | +-------+-----+------+-------+------+-------+ | 2 | 4 | 'b' | 1 | 4 | 'foo' | +-------+-----+------+-------+------+-------+ | 2 | 4 | 'b' | 3 | 7 | 'bar' | +-------+-----+------+-------+------+-------+ | 2 | 4 | 'b' | 4 | 9 | 'baz' | +-------+-----+------+-------+------+-------+ | 2 | 5 | 'c' | 1 | 4 | 'foo' | +-------+-----+------+-------+------+-------+ | 2 | 5 | 'c' | 3 | 7 | 'bar' | +-------+-----+------+-------+------+-------+ | 2 | 5 | 'c' | 4 | 9 | 'baz' | +-------+-----+------+-------+------+-------+ | 9 | 14 | 'd' | 4 | 9 | 'baz' | +-------+-----+------+-------+------+-------+ | 1 | 1 | 'e' | 1 | 4 | 'foo' | +-------+-----+------+-------+------+-------+ Note start coordinates are included and stop coordinates are excluded from the interval. Use the `include_stop` keyword argument to include the upper bound of the interval when finding overlaps. An additional key comparison can be made, e.g.:: >>> import petl as etl >>> left = (('fruit', 'begin', 'end'), ... ('apple', 1, 2), ... ('apple', 2, 4), ... ('apple', 2, 5), ... ('orange', 2, 5), ... ('orange', 9, 14), ... ('orange', 19, 140), ... ('apple', 1, 1)) >>> right = (('type', 'start', 'stop', 'value'), ... ('apple', 1, 4, 'foo'), ... ('apple', 3, 7, 'bar'), ... ('orange', 4, 9, 'baz')) >>> table3 = etl.intervaljoin(left, right, ... lstart='begin', lstop='end', lkey='fruit', ... rstart='start', rstop='stop', rkey='type') >>> table3.lookall() +----------+-------+-----+----------+-------+------+-------+ | fruit | begin | end | type | start | stop | value | +==========+=======+=====+==========+=======+======+=======+ | 'apple' | 1 | 2 | 'apple' | 1 | 4 | 'foo' | +----------+-------+-----+----------+-------+------+-------+ | 'apple' | 2 | 4 | 'apple' | 1 | 4 | 'foo' | +----------+-------+-----+----------+-------+------+-------+ | 'apple' | 2 | 4 | 'apple' | 3 | 7 | 'bar' | +----------+-------+-----+----------+-------+------+-------+ | 'apple' | 2 | 5 | 'apple' | 1 | 4 | 'foo' | +----------+-------+-----+----------+-------+------+-------+ | 'apple' | 2 | 5 | 'apple' | 3 | 7 | 'bar' | +----------+-------+-----+----------+-------+------+-------+ | 'orange' | 2 | 5 | 'orange' | 4 | 9 | 'baz' | +----------+-------+-----+----------+-------+------+-------+ """ assert (lkey is None) == (rkey is None), \ 'facet key field must be provided for both or neither table' return IntervalJoinView(left, right, lstart=lstart, lstop=lstop, rstart=rstart, rstop=rstop, lkey=lkey, rkey=rkey, include_stop=include_stop, lprefix=lprefix, rprefix=rprefix)
Join two tables by overlapping intervals. E.g.:: >>> import petl as etl >>> left = [['begin', 'end', 'quux'], ... [1, 2, 'a'], ... [2, 4, 'b'], ... [2, 5, 'c'], ... [9, 14, 'd'], ... [1, 1, 'e'], ... [10, 10, 'f']] >>> right = [['start', 'stop', 'value'], ... [1, 4, 'foo'], ... [3, 7, 'bar'], ... [4, 9, 'baz']] >>> table1 = etl.intervaljoin(left, right, ... lstart='begin', lstop='end', ... rstart='start', rstop='stop') >>> table1.lookall() +-------+-----+------+-------+------+-------+ | begin | end | quux | start | stop | value | +=======+=====+======+=======+======+=======+ | 1 | 2 | 'a' | 1 | 4 | 'foo' | +-------+-----+------+-------+------+-------+ | 2 | 4 | 'b' | 1 | 4 | 'foo' | +-------+-----+------+-------+------+-------+ | 2 | 4 | 'b' | 3 | 7 | 'bar' | +-------+-----+------+-------+------+-------+ | 2 | 5 | 'c' | 1 | 4 | 'foo' | +-------+-----+------+-------+------+-------+ | 2 | 5 | 'c' | 3 | 7 | 'bar' | +-------+-----+------+-------+------+-------+ | 2 | 5 | 'c' | 4 | 9 | 'baz' | +-------+-----+------+-------+------+-------+ >>> # include stop coordinate in intervals ... table2 = etl.intervaljoin(left, right, ... lstart='begin', lstop='end', ... rstart='start', rstop='stop', ... include_stop=True) >>> table2.lookall() +-------+-----+------+-------+------+-------+ | begin | end | quux | start | stop | value | +=======+=====+======+=======+======+=======+ | 1 | 2 | 'a' | 1 | 4 | 'foo' | +-------+-----+------+-------+------+-------+ | 2 | 4 | 'b' | 1 | 4 | 'foo' | +-------+-----+------+-------+------+-------+ | 2 | 4 | 'b' | 3 | 7 | 'bar' | +-------+-----+------+-------+------+-------+ | 2 | 4 | 'b' | 4 | 9 | 'baz' | +-------+-----+------+-------+------+-------+ | 2 | 5 | 'c' | 1 | 4 | 'foo' | +-------+-----+------+-------+------+-------+ | 2 | 5 | 'c' | 3 | 7 | 'bar' | +-------+-----+------+-------+------+-------+ | 2 | 5 | 'c' | 4 | 9 | 'baz' | +-------+-----+------+-------+------+-------+ | 9 | 14 | 'd' | 4 | 9 | 'baz' | +-------+-----+------+-------+------+-------+ | 1 | 1 | 'e' | 1 | 4 | 'foo' | +-------+-----+------+-------+------+-------+ Note start coordinates are included and stop coordinates are excluded from the interval. Use the `include_stop` keyword argument to include the upper bound of the interval when finding overlaps. An additional key comparison can be made, e.g.:: >>> import petl as etl >>> left = (('fruit', 'begin', 'end'), ... ('apple', 1, 2), ... ('apple', 2, 4), ... ('apple', 2, 5), ... ('orange', 2, 5), ... ('orange', 9, 14), ... ('orange', 19, 140), ... ('apple', 1, 1)) >>> right = (('type', 'start', 'stop', 'value'), ... ('apple', 1, 4, 'foo'), ... ('apple', 3, 7, 'bar'), ... ('orange', 4, 9, 'baz')) >>> table3 = etl.intervaljoin(left, right, ... lstart='begin', lstop='end', lkey='fruit', ... rstart='start', rstop='stop', rkey='type') >>> table3.lookall() +----------+-------+-----+----------+-------+------+-------+ | fruit | begin | end | type | start | stop | value | +==========+=======+=====+==========+=======+======+=======+ | 'apple' | 1 | 2 | 'apple' | 1 | 4 | 'foo' | +----------+-------+-----+----------+-------+------+-------+ | 'apple' | 2 | 4 | 'apple' | 1 | 4 | 'foo' | +----------+-------+-----+----------+-------+------+-------+ | 'apple' | 2 | 4 | 'apple' | 3 | 7 | 'bar' | +----------+-------+-----+----------+-------+------+-------+ | 'apple' | 2 | 5 | 'apple' | 1 | 4 | 'foo' | +----------+-------+-----+----------+-------+------+-------+ | 'apple' | 2 | 5 | 'apple' | 3 | 7 | 'bar' | +----------+-------+-----+----------+-------+------+-------+ | 'orange' | 2 | 5 | 'orange' | 4 | 9 | 'baz' | +----------+-------+-----+----------+-------+------+-------+
def parse(self, rrstr): # type: (bytes) -> None ''' Parse a Rock Ridge Parent Link record out of a string. Parameters: rrstr - The string to parse the record out of. Returns: Nothing. ''' if self._initialized: raise pycdlibexception.PyCdlibInternalError('PL record already initialized!') # We assume that the caller has already checked the su_entry_version, # so we don't bother. (su_len, su_entry_version_unused, parent_log_block_num_le, parent_log_block_num_be) = struct.unpack_from('=BBLL', rrstr[:12], 2) if su_len != RRPLRecord.length(): raise pycdlibexception.PyCdlibInvalidISO('Invalid length on rock ridge extension') if parent_log_block_num_le != utils.swab_32bit(parent_log_block_num_be): raise pycdlibexception.PyCdlibInvalidISO('Little endian block num does not equal big endian; corrupt ISO') self.parent_log_block_num = parent_log_block_num_le self._initialized = True
Parse a Rock Ridge Parent Link record out of a string. Parameters: rrstr - The string to parse the record out of. Returns: Nothing.
def promote(self, cart_name): """ `name` - name of cart Promote a cart from its current environment to the next in the chain. """ cart = juicer.common.Cart.Cart(cart_name=cart_name, autoload=True, autosync=True) old_env = cart.current_env cart.current_env = juicer.utils.get_next_environment(cart.current_env) # figure out what needs to be done to promote packages. If # packages are going between environments that are on the same # host and we don't need to sign them just associate with both # repos. if juicer.utils.env_same_host(old_env, cart.current_env) and (self.connectors[old_env].requires_signature == self.connectors[cart.current_env].requires_signature): juicer.utils.Log.log_info("Envs %s and %s exist on the same host, calling remote associate action" % (old_env, cart.current_env)) juicer.utils.Log.log_info("Promoting %s from %s to %s" % (cart_name, old_env, cart.current_env)) # iterate through packages and associate to new repo for repo, items in cart.iterrepos(): query = '/repositories/%s-%s/actions/associate/' % (repo, cart.current_env) for item in items: source_repo_id = '%s-%s' % (repo, old_env) data = { 'source_repo_id': str(source_repo_id), 'criteria': { 'type_ids': ['rpm'], 'filters': { 'unit': { 'filename': str(item.path.split('/')[-1]) } } } } _r = self.connectors[cart.current_env].post(query, data) if _r.status_code != Constants.PULP_POST_ACCEPTED: raise JuicerPulpError("Package association call was not accepted. Terminating!") else: # association was accepted so publish destination repo con = self.connectors[cart.current_env] con.post('/repositories/%s-%s/actions/publish/' % (repo, cart.current_env), {'id': 'yum_distributor'}) # also update the item's remote path filename = item.path.split('/')[-1] item.update('%s/%s' % (juicer.utils.pulp_repo_path(con, '%s-%s' % (repo, cart.current_env)), filename)) # we didn't bomb out yet so let the user know what's up juicer.utils.Log.log_info("Package association calls were accepted. Trusting that your packages existed in %s" % old_env) # we can save and publish here because upload does this too... cart.save() self.publish(cart) else: juicer.utils.Log.log_debug("Syncing down rpms...") cart.sync_remotes() self.sign_cart_for_env_maybe(cart, cart.current_env) juicer.utils.Log.log_info("Promoting %s from %s to %s" % (cart_name, old_env, cart.current_env)) for repo in cart.repos(): juicer.utils.Log.log_debug("Promoting %s to %s in %s" % (cart[repo], repo, cart.current_env)) # reiterating that upload will save and publish the cart self.upload(cart.current_env, cart)
`name` - name of cart Promote a cart from its current environment to the next in the chain.
def size_of_varint(value): """ Number of bytes needed to encode an integer in variable-length format. """ value = (value << 1) ^ (value >> 63) if value <= 0x7f: return 1 if value <= 0x3fff: return 2 if value <= 0x1fffff: return 3 if value <= 0xfffffff: return 4 if value <= 0x7ffffffff: return 5 if value <= 0x3ffffffffff: return 6 if value <= 0x1ffffffffffff: return 7 if value <= 0xffffffffffffff: return 8 if value <= 0x7fffffffffffffff: return 9 return 10
Number of bytes needed to encode an integer in variable-length format.
def _get_linewise_report(self): """ Returns a report each line of which comprises a pair of an input line and an error. Unlike in the standard report, errors will appear as many times as they occur. Helper for the get_report method. """ d = defaultdict(list) # line: [] of errors for error, lines in self.errors.items(): for line_num in lines: d[line_num].append(error) return '\n'.join([ '{:>3} → {}'.format(line, error.string) for line in sorted(d.keys()) for error in d[line]])
Returns a report each line of which comprises a pair of an input line and an error. Unlike in the standard report, errors will appear as many times as they occur. Helper for the get_report method.
def frame_parser(version=None, kind=0, extensions=None, protocols=None): '''Create a new :class:`FrameParser` instance. :param version: protocol version, the default is 13 :param kind: the kind of parser, and integer between 0 and 3 (check the :class:`FrameParser` documentation for details) :param extensions: not used at the moment :param protocols: not used at the moment :param pyparser: if ``True`` (default ``False``) uses the python frame parser implementation rather than the much faster cython implementation. ''' version = get_version(version) # extensions, protocols return FrameParser(version, kind, ProtocolError, close_codes=CLOSE_CODES)
Create a new :class:`FrameParser` instance. :param version: protocol version, the default is 13 :param kind: the kind of parser, and integer between 0 and 3 (check the :class:`FrameParser` documentation for details) :param extensions: not used at the moment :param protocols: not used at the moment :param pyparser: if ``True`` (default ``False``) uses the python frame parser implementation rather than the much faster cython implementation.
def read_message_bytes_from_pipe(pipe_handle): """ (coroutine) Read message from this pipe. Return bytes. """ overlapped = OVERLAPPED() overlapped.hEvent = create_event() try: buff = create_string_buffer(BUFSIZE + 1) c_read = DWORD() success = windll.kernel32.ReadFile( pipe_handle, buff, DWORD(BUFSIZE), byref(c_read), byref(overlapped)) if success: buff[c_read.value] = b'\0' raise Return(buff.value) error_code = windll.kernel32.GetLastError() if error_code == ERROR_IO_PENDING: yield From(wait_for_event(overlapped.hEvent)) success = windll.kernel32.GetOverlappedResult( pipe_handle, byref(overlapped), byref(c_read), BOOL(False)) if success: buff[c_read.value] = b'\0' raise Return(buff.value) else: error_code = windll.kernel32.GetLastError() if error_code == ERROR_BROKEN_PIPE: raise BrokenPipeError elif error_code == ERROR_MORE_DATA: more_data = yield From(read_message_bytes_from_pipe(pipe_handle)) raise Return(buff.value + more_data) else: raise Exception( 'reading overlapped IO failed. error_code=%r' % error_code) elif error_code == ERROR_BROKEN_PIPE: raise BrokenPipeError elif error_code == ERROR_MORE_DATA: more_data = yield From(read_message_bytes_from_pipe(pipe_handle)) raise Return(buff.value + more_data) else: raise Exception('Reading pipe failed, error_code=%s' % error_code) finally: windll.kernel32.CloseHandle(overlapped.hEvent)
(coroutine) Read message from this pipe. Return bytes.
def setDragData(self, data, x=None, y=None): """ Sets the drag data for this chart item to the inputed data. :param data | <QMimeData> || None """ self._dragData[(x, y)] = data
Sets the drag data for this chart item to the inputed data. :param data | <QMimeData> || None
def GetRandomDatetime(): """Return a datetime in the next week.""" seconds_offset = random.randint(0, 60 * 60 * 24 * 7) dt = datetime.today() + timedelta(seconds=seconds_offset) return dt.replace(second=0, microsecond=0)
Return a datetime in the next week.
def example(script, explain, contents, requirements, output, outputfmt, details): """Prints the example help for the script.""" blank() cprint(script.upper(), "yellow") cprint(''.join(["=" for i in range(70)]) + '\n', "yellow") cprint("DETAILS", "blue") std(explain + '\n') cprint(requirements, "red") cprint(output, "green") blank() if details != "": std(details) blank() cprint("OUTPUT FORMAT", "blue") std(outputfmt) blank() cprint("EXAMPLES", "blue") for i in range(len(contents)): pre, code, post = contents[i] std("{}) {}".format(i + 1, pre)) cprint(" " + code, "cyan") if post != "": std('\n' + post) blank()
Prints the example help for the script.
def connect_delete_namespaced_service_proxy(self, name, namespace, **kwargs): # noqa: E501 """connect_delete_namespaced_service_proxy # noqa: E501 connect DELETE requests to proxy of Service # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.connect_delete_namespaced_service_proxy(name, namespace, async_req=True) >>> result = thread.get() :param async_req bool :param str name: name of the ServiceProxyOptions (required) :param str namespace: object name and auth scope, such as for teams and projects (required) :param str path: Path is the part of URLs that include service endpoints, suffixes, and parameters to use for the current proxy request to service. For example, the whole request URL is http://localhost/api/v1/namespaces/kube-system/services/elasticsearch-logging/_search?q=user:kimchy. Path is _search?q=user:kimchy. :return: str If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.connect_delete_namespaced_service_proxy_with_http_info(name, namespace, **kwargs) # noqa: E501 else: (data) = self.connect_delete_namespaced_service_proxy_with_http_info(name, namespace, **kwargs) # noqa: E501 return data
connect_delete_namespaced_service_proxy # noqa: E501 connect DELETE requests to proxy of Service # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.connect_delete_namespaced_service_proxy(name, namespace, async_req=True) >>> result = thread.get() :param async_req bool :param str name: name of the ServiceProxyOptions (required) :param str namespace: object name and auth scope, such as for teams and projects (required) :param str path: Path is the part of URLs that include service endpoints, suffixes, and parameters to use for the current proxy request to service. For example, the whole request URL is http://localhost/api/v1/namespaces/kube-system/services/elasticsearch-logging/_search?q=user:kimchy. Path is _search?q=user:kimchy. :return: str If the method is called asynchronously, returns the request thread.
def search_node_namespace_names(graph, query, namespace): """Search for nodes with the given namespace(s) and whose names containing a given string(s). :param pybel.BELGraph graph: A BEL graph :param query: The search query :type query: str or iter[str] :param namespace: The namespace(s) to filter :type namespace: str or iter[str] :return: An iterator over nodes whose names match the search query :rtype: iter """ node_predicates = [ namespace_inclusion_builder(namespace), build_node_name_search(query) ] return filter_nodes(graph, node_predicates)
Search for nodes with the given namespace(s) and whose names containing a given string(s). :param pybel.BELGraph graph: A BEL graph :param query: The search query :type query: str or iter[str] :param namespace: The namespace(s) to filter :type namespace: str or iter[str] :return: An iterator over nodes whose names match the search query :rtype: iter
def simxLoadModel(clientID, modelPathAndName, options, operationMode): ''' Please have a look at the function description/documentation in the V-REP user manual ''' baseHandle = ct.c_int() if (sys.version_info[0] == 3) and (type(modelPathAndName) is str): modelPathAndName=modelPathAndName.encode('utf-8') return c_LoadModel(clientID, modelPathAndName, options, ct.byref(baseHandle), operationMode), baseHandle.value
Please have a look at the function description/documentation in the V-REP user manual
def acl_show(self, msg, args): """Show current allow and deny blocks for the given acl.""" name = args[0] if len(args) > 0 else None if name is None: return "%s: The following ACLs are defined: %s" % (msg.user, ', '.join(self._acl.keys())) if name not in self._acl: return "Sorry, couldn't find an acl named '%s'" % name return '\n'.join([ "%s: ACL '%s' is defined as follows:" % (msg.user, name), "allow: %s" % ', '.join(self._acl[name]['allow']), "deny: %s" % ', '.join(self._acl[name]['deny']) ])
Show current allow and deny blocks for the given acl.
def set_scale(self, xscale=None, yscale=None, zscale=None, reset_camera=True): """ Scale all the datasets in the scene of the active renderer. Scaling in performed independently on the X, Y and Z axis. A scale of zero is illegal and will be replaced with one. Parameters ---------- xscale : float, optional Scaling of the x axis. Must be greater than zero. yscale : float, optional Scaling of the y axis. Must be greater than zero. zscale : float, optional Scaling of the z axis. Must be greater than zero. reset_camera : bool, optional Resets camera so all actors can be seen. """ self.renderer.set_scale(xscale, yscale, zscale, reset_camera)
Scale all the datasets in the scene of the active renderer. Scaling in performed independently on the X, Y and Z axis. A scale of zero is illegal and will be replaced with one. Parameters ---------- xscale : float, optional Scaling of the x axis. Must be greater than zero. yscale : float, optional Scaling of the y axis. Must be greater than zero. zscale : float, optional Scaling of the z axis. Must be greater than zero. reset_camera : bool, optional Resets camera so all actors can be seen.
def generate_message_doc(message_descriptor, locations, path, name_prefix=''): """Generate docs for message and nested messages and enums. Args: message_descriptor: descriptor_pb2.DescriptorProto instance for message to generate docs for. locations: Dictionary of location paths tuples to descriptor_pb2.SourceCodeInfo.Location instances. path: Path tuple to the message definition. name_prefix: Optional prefix for this message's name. """ # message_type is 4 prefixed_name = name_prefix + message_descriptor.name print(make_subsection(prefixed_name)) location = locations[path] if location.HasField('leading_comments'): print(textwrap.dedent(location.leading_comments)) row_tuples = [] for field_index, field in enumerate(message_descriptor.field): field_location = locations[path + (2, field_index)] if field.type not in [11, 14]: type_str = TYPE_TO_STR[field.type] else: type_str = make_link(field.type_name.lstrip('.')) row_tuples.append(( make_code(field.name), field.number, type_str, LABEL_TO_STR[field.label], textwrap.fill(get_comment_from_location(field_location), INFINITY), )) print_table(('Field', 'Number', 'Type', 'Label', 'Description'), row_tuples) # Generate nested messages nested_types = enumerate(message_descriptor.nested_type) for index, nested_message_desc in nested_types: generate_message_doc(nested_message_desc, locations, path + (3, index), name_prefix=prefixed_name + '.') # Generate nested enums for index, nested_enum_desc in enumerate(message_descriptor.enum_type): generate_enum_doc(nested_enum_desc, locations, path + (4, index), name_prefix=prefixed_name + '.')
Generate docs for message and nested messages and enums. Args: message_descriptor: descriptor_pb2.DescriptorProto instance for message to generate docs for. locations: Dictionary of location paths tuples to descriptor_pb2.SourceCodeInfo.Location instances. path: Path tuple to the message definition. name_prefix: Optional prefix for this message's name.
def check_application_state(self, request, callback): "Check optional state parameter." stored = request.session.get(self.session_key, None) returned = request.GET.get('state', None) check = False if stored is not None: if returned is not None: check = constant_time_compare(stored, returned) else: logger.error('No state parameter returned by the provider.') else: logger.error('No state stored in the sesssion.') return check
Check optional state parameter.
def roll_out_and_store(self, batch_info): """ Roll out environment and store result in the replay buffer """ self.model.train() if self.env_roller.is_ready_for_sampling(): rollout = self.env_roller.rollout(batch_info, self.model, self.settings.rollout_steps).to_device(self.device) # Store some information about the rollout, no training phase batch_info['frames'] = rollout.frames() batch_info['episode_infos'] = rollout.episode_information() else: frames = 0 episode_infos = [] with tqdm.tqdm(desc="Populating memory", total=self.env_roller.initial_memory_size_hint()) as pbar: while not self.env_roller.is_ready_for_sampling(): rollout = self.env_roller.rollout(batch_info, self.model, self.settings.rollout_steps).to_device(self.device) new_frames = rollout.frames() frames += new_frames episode_infos.extend(rollout.episode_information()) pbar.update(new_frames) # Store some information about the rollout, no training phase batch_info['frames'] = frames batch_info['episode_infos'] = episode_infos
Roll out environment and store result in the replay buffer
def get_cookie_jar(self): """Returns our cookie jar.""" cookie_file = self._get_cookie_file() cookie_jar = LWPCookieJar(cookie_file) if os.path.exists(cookie_file): cookie_jar.load() else: safe_mkdir_for(cookie_file) # Save an empty cookie jar so we can change the file perms on it before writing data to it. with self._lock: cookie_jar.save() os.chmod(cookie_file, 0o600) return cookie_jar
Returns our cookie jar.
def save_to_internal(self, data): """save """ if self.filetype is "pickle": pickle.dump(data, open(self.location_internal, "wb")) elif self.filetype is "hickle": import hickle hickle.dump(data, open(self.location_internal, "wb")) else: raise ValueError( "Invalid filetype {} (must be {} or {})".format( self.filetype, "pickle", "hickle" ) )
save
def make_int(value, missing=-1): """Convert string value to long, '' to missing""" if isinstance(value, six.string_types): if not value.strip(): return missing elif value is None: return missing return int(value)
Convert string value to long, '' to missing