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def logging_syslog_server_port ( self , ** kwargs ) : """Auto Generated Code"""
config = ET . Element ( "config" ) logging = ET . SubElement ( config , "logging" , xmlns = "urn:brocade.com:mgmt:brocade-ras" ) syslog_server = ET . SubElement ( logging , "syslog-server" ) syslogip_key = ET . SubElement ( syslog_server , "syslogip" ) syslogip_key . text = kwargs . pop ( 'syslogip' ) use_vrf_key = ET . SubElement ( syslog_server , "use-vrf" ) use_vrf_key . text = kwargs . pop ( 'use_vrf' ) port = ET . SubElement ( syslog_server , "port" ) port . text = kwargs . pop ( 'port' ) callback = kwargs . pop ( 'callback' , self . _callback ) return callback ( config )
def autoscroll ( self , autoscroll ) : """Autoscroll will ' right justify ' text from the cursor if set True , otherwise it will ' left justify ' the text ."""
if autoscroll : self . displaymode |= LCD_ENTRYSHIFTINCREMENT else : self . displaymode &= ~ LCD_ENTRYSHIFTINCREMENT self . write8 ( LCD_ENTRYMODESET | self . displaymode )
def _reads_per_position ( bam_in , loci_file , out_dir ) : """Create input for compute entropy"""
data = Counter ( ) a = pybedtools . BedTool ( bam_in ) b = pybedtools . BedTool ( loci_file ) c = a . intersect ( b , s = True , bed = True , wo = True ) for line in c : end = int ( line [ 1 ] ) + 1 + int ( line [ 2 ] ) if line [ 5 ] == "+" else int ( line [ 1 ] ) + 1 start = int ( line [ 1 ] ) + 1 if line [ 5 ] == "+" else int ( line [ 1 ] ) + 1 + int ( line [ 2 ] ) side5 = "%s\t5p\t%s" % ( line [ 15 ] , start ) side3 = "%s\t3p\t%s" % ( line [ 15 ] , end ) data [ side5 ] += 1 data [ side3 ] += 1 counts_reads = op . join ( out_dir , 'locus_readpos.counts' ) with open ( counts_reads , 'w' ) as out_handle : for k in data : print ( k , file = out_handle , end = "" ) return counts_reads
def validate ( ref_intervals , ref_pitches , ref_velocities , est_intervals , est_pitches , est_velocities ) : """Checks that the input annotations have valid time intervals , pitches , and velocities , and throws helpful errors if not . Parameters ref _ intervals : np . ndarray , shape = ( n , 2) Array of reference notes time intervals ( onset and offset times ) ref _ pitches : np . ndarray , shape = ( n , ) Array of reference pitch values in Hertz ref _ velocities : np . ndarray , shape = ( n , ) Array of MIDI velocities ( i . e . between 0 and 127 ) of reference notes est _ intervals : np . ndarray , shape = ( m , 2) Array of estimated notes time intervals ( onset and offset times ) est _ pitches : np . ndarray , shape = ( m , ) Array of estimated pitch values in Hertz est _ velocities : np . ndarray , shape = ( m , ) Array of MIDI velocities ( i . e . between 0 and 127 ) of estimated notes"""
transcription . validate ( ref_intervals , ref_pitches , est_intervals , est_pitches ) # Check that velocities have the same length as intervals / pitches if not ref_velocities . shape [ 0 ] == ref_pitches . shape [ 0 ] : raise ValueError ( 'Reference velocities must have the same length as ' 'pitches and intervals.' ) if not est_velocities . shape [ 0 ] == est_pitches . shape [ 0 ] : raise ValueError ( 'Estimated velocities must have the same length as ' 'pitches and intervals.' ) # Check that the velocities are positive if ref_velocities . size > 0 and np . min ( ref_velocities ) < 0 : raise ValueError ( 'Reference velocities must be positive.' ) if est_velocities . size > 0 and np . min ( est_velocities ) < 0 : raise ValueError ( 'Estimated velocities must be positive.' )
def emoticons ( string ) : '''emot . emoticons is use to detect emoticons from text > > > text = " I love python 👨 : - ) " > > > emot . emoticons ( text ) > > > { ' value ' : [ ' : - ) ' ] , ' location ' : [ [ 16 , 19 ] ] , ' mean ' : [ ' Happy face smiley ' ] , ' flag ' : True }'''
__entities = [ ] flag = True try : pattern = u'(' + u'|' . join ( k for k in emo_unicode . EMOTICONS ) + u')' __entities = [ ] __value = [ ] __location = [ ] matches = re . finditer ( r"%s" % pattern , str ( string ) ) for et in matches : __value . append ( et . group ( ) . strip ( ) ) __location . append ( [ et . start ( ) , et . end ( ) ] ) __mean = [ ] for each in __value : __mean . append ( emo_unicode . EMOTICONS_EMO [ each ] ) if len ( __value ) < 1 : flag = False __entities = { 'value' : __value , 'location' : __location , 'mean' : __mean , 'flag' : flag } except Exception as e : __entities = [ { 'flag' : False } ] # print ( " No emoiticons found " ) return __entities return __entities
def learn_q ( self , predicted_q_arr , real_q_arr ) : '''Infernce Q - Value . Args : predicted _ q _ arr : ` np . ndarray ` of predicted Q - Values . real _ q _ arr : ` np . ndarray ` of real Q - Values .'''
self . __predicted_q_arr_list . append ( predicted_q_arr ) while len ( self . __predicted_q_arr_list ) > self . __seq_len : self . __predicted_q_arr_list = self . __predicted_q_arr_list [ 1 : ] while len ( self . __predicted_q_arr_list ) < self . __seq_len : self . __predicted_q_arr_list . append ( self . __predicted_q_arr_list [ - 1 ] ) predicted_q_arr = np . array ( self . __predicted_q_arr_list ) predicted_q_arr = predicted_q_arr . transpose ( ( 1 , 0 , 2 ) ) self . __real_q_arr_list . append ( real_q_arr ) while len ( self . __real_q_arr_list ) > self . __seq_len : self . __real_q_arr_list = self . __real_q_arr_list [ 1 : ] while len ( self . __real_q_arr_list ) < self . __seq_len : self . __real_q_arr_list . append ( self . __real_q_arr_list [ - 1 ] ) real_q_arr = np . array ( self . __real_q_arr_list ) real_q_arr = real_q_arr . transpose ( ( 1 , 0 , 2 ) ) loss = self . __computable_loss . compute_loss ( predicted_q_arr , real_q_arr ) delta_arr = self . __computable_loss . compute_delta ( predicted_q_arr , real_q_arr ) delta_arr , lstm_output_grads_list = self . __lstm_model . output_back_propagate ( predicted_q_arr , delta_arr ) delta_arr , _ , lstm_hidden_grads_list = self . __lstm_model . hidden_back_propagate ( delta_arr [ : , - 1 ] ) lstm_grads_list = lstm_output_grads_list lstm_grads_list . extend ( lstm_hidden_grads_list ) self . __lstm_model . optimize ( lstm_grads_list , self . __learning_rate , 1 ) self . __loss_list . append ( loss )
def export ( self , file_path = None , export_format = None ) : """Write the users to a file ."""
with io . open ( file_path , mode = 'w' , encoding = "utf-8" ) as export_file : if export_format == 'yaml' : import yaml yaml . safe_dump ( self . to_dict ( ) , export_file , default_flow_style = False ) elif export_format == 'json' : export_file . write ( text_type ( json . dumps ( self . to_dict ( ) , ensure_ascii = False ) ) ) return True
def list ( self , bank ) : '''Lists entries stored in the specified bank . : param bank : The name of the location inside the cache which will hold the key and its associated data . : return : An iterable object containing all bank entries . Returns an empty iterator if the bank doesn ' t exists . : raises SaltCacheError : Raises an exception if cache driver detected an error accessing data in the cache backend ( auth , permissions , etc ) .'''
fun = '{0}.list' . format ( self . driver ) return self . modules [ fun ] ( bank , ** self . _kwargs )
def createLearningRateScheduler ( self , optimizer ) : """Creates the learning rate scheduler and attach the optimizer"""
if self . lr_scheduler_class is None : return None return self . lr_scheduler_class ( optimizer , ** self . lr_scheduler_params )
def prepare_query ( self , symbol , start_date , end_date ) : """Method returns prepared request query for Yahoo YQL API ."""
query = 'select * from yahoo.finance.historicaldata where symbol = "%s" and startDate = "%s" and endDate = "%s"' % ( symbol , start_date , end_date ) return query
def get_song ( self , netease = False ) : """获取歌曲 , 对外统一接口"""
song = self . _playlist . get ( True ) self . hash_sid [ song [ 'sid' ] ] = True # 去重 self . get_netease_song ( song , netease ) # 判断是否网易320k self . _playingsong = song return song
def stop_proxy ( self ) : """Stop the mitmproxy"""
self . runner . info_log ( "Stopping proxy..." ) if hasattr ( self , 'proxy_pid' ) : try : kill_by_pid ( self . proxy_pid ) except psutil . NoSuchProcess : pass
def _extract_and_handle_mpbgp_withdraws ( self , mp_unreach_attr ) : """Extracts withdraws advertised in the given update message ' s * MpUnReachNlri * attribute . Assumes MPBGP capability is enabled . Parameters : - update _ msg : ( Update ) is assumed to be checked for all bgp message errors . Extracted withdraws are added to appropriate * Destination * for further processing ."""
msg_rf = mp_unreach_attr . route_family # Check if this route family is among supported route families . if msg_rf not in SUPPORTED_GLOBAL_RF : LOG . info ( 'Received route family %s is not supported. ' 'Ignoring withdraw routes on this UPDATE message.' , msg_rf ) return w_nlris = mp_unreach_attr . withdrawn_routes if not w_nlris : # If this is EOR of some kind , handle it self . _handle_eor ( msg_rf ) for w_nlri in w_nlris : w_path = bgp_utils . create_path ( self , w_nlri , is_withdraw = True ) block , blocked_cause = self . _apply_in_filter ( w_path ) received_route = ReceivedRoute ( w_path , self , block ) nlri_str = w_nlri . formatted_nlri_str if nlri_str in self . _adj_rib_in : del self . _adj_rib_in [ nlri_str ] self . _signal_bus . adj_rib_in_changed ( self , received_route ) if not block : # Update appropriate table with withdraws . tm = self . _core_service . table_manager tm . learn_path ( w_path ) else : LOG . debug ( 'prefix : %s is blocked by in-bound filter: %s' , w_nlri , blocked_cause )
def fragmentate ( self , give_only_index = False , use_lookup = None ) : """Get the indices of non bonded parts in the molecule . Args : give _ only _ index ( bool ) : If ` ` True ` ` a set of indices is returned . Otherwise a new Cartesian instance . use _ lookup ( bool ) : Use a lookup variable for : meth : ` ~ chemcoord . Cartesian . get _ bonds ` . use _ lookup ( bool ) : Use a lookup variable for : meth : ` ~ chemcoord . Cartesian . get _ bonds ` . The default is specified in ` ` settings [ ' defaults ' ] [ ' use _ lookup ' ] ` ` Returns : list : A list of sets of indices or new Cartesian instances ."""
if use_lookup is None : use_lookup = settings [ 'defaults' ] [ 'use_lookup' ] fragments = [ ] pending = set ( self . index ) self . get_bonds ( use_lookup = use_lookup ) while pending : index = self . get_coordination_sphere ( pending . pop ( ) , use_lookup = True , n_sphere = float ( 'inf' ) , only_surface = False , give_only_index = True ) pending = pending - index if give_only_index : fragments . append ( index ) else : fragment = self . loc [ index ] fragment . _metadata [ 'bond_dict' ] = fragment . restrict_bond_dict ( self . _metadata [ 'bond_dict' ] ) try : fragment . _metadata [ 'val_bond_dict' ] = ( fragment . restrict_bond_dict ( self . _metadata [ 'val_bond_dict' ] ) ) except KeyError : pass fragments . append ( fragment ) return fragments
def parse_n_jobs ( s ) : """This function parses a " math " - like string as a function of CPU count . It is useful for specifying the number of jobs . For example , on an 8 - core machine : : assert parse _ n _ jobs ( ' 0.5 * n ' ) = = 4 assert parse _ n _ jobs ( ' 2n ' ) = = 16 assert parse _ n _ jobs ( ' n ' ) = = 8 assert parse _ n _ jobs ( ' 4 ' ) = = 4 : param str s : string to parse for number of CPUs"""
n_jobs = None N = cpu_count ( ) if isinstance ( s , int ) : n_jobs = s elif isinstance ( s , float ) : n_jobs = int ( s ) elif isinstance ( s , str ) : m = re . match ( r'(\d*(?:\.\d*)?)?(\s*\*?\s*n)?$' , s . strip ( ) ) if m is None : raise ValueError ( 'Unable to parse n_jobs="{}"' . format ( s ) ) k = float ( m . group ( 1 ) ) if m . group ( 1 ) else 1 if m . group ( 2 ) : n_jobs = k * N elif k < 1 : n_jobs = k * N else : n_jobs = int ( k ) else : raise TypeError ( 'n_jobs argument must be of type str, int, or float.' ) n_jobs = int ( n_jobs ) if n_jobs <= 0 : warnings . warn ( 'n_jobs={} is invalid. Setting n_jobs=1.' . format ( n_jobs ) ) n_jobs = 1 # end if return int ( n_jobs )
def _run_program ( self , bin , fastafile , params = None ) : """Run HMS and predict motifs from a FASTA file . Parameters bin : str Command used to run the tool . fastafile : str Name of the FASTA input file . params : dict , optional Optional parameters . For some of the tools required parameters are passed using this dictionary . Returns motifs : list of Motif instances The predicted motifs . stdout : str Standard out of the tool . stderr : str Standard error of the tool ."""
params = self . _parse_params ( params ) default_params = { "width" : 10 } if params is not None : default_params . update ( params ) fgfile , summitfile , outfile = self . _prepare_files ( fastafile ) current_path = os . getcwd ( ) os . chdir ( self . tmpdir ) cmd = "{} -i {} -w {} -dna 4 -iteration 50 -chain 20 -seqprop -0.1 -strand 2 -peaklocation {} -t_dof 3 -dep 2" . format ( bin , fgfile , params [ 'width' ] , summitfile ) p = Popen ( cmd , shell = True , stdout = PIPE , stderr = PIPE ) stdout , stderr = p . communicate ( ) os . chdir ( current_path ) motifs = [ ] if os . path . exists ( outfile ) : with open ( outfile ) as f : motifs = self . parse ( f ) for i , m in enumerate ( motifs ) : m . id = "HMS_w{}_{}" . format ( params [ 'width' ] , i + 1 ) return motifs , stdout , stderr
def get_chunks ( sequence , chunk_size ) : """Split sequence into chunks . : param list sequence : : param int chunk _ size :"""
return [ sequence [ idx : idx + chunk_size ] for idx in range ( 0 , len ( sequence ) , chunk_size ) ]
def _apply_auth ( self , view_func ) : """Apply decorator to authenticate the user who is making the request . : param view _ func : The flask view func ."""
@ functools . wraps ( view_func ) def decorated ( * args , ** kwargs ) : if not self . auth : return view_func ( * args , ** kwargs ) auth_data = self . auth . get_authorization ( ) if auth_data is None : return self . _handle_authentication_error ( ) if not self . _authentication_callback or not self . _authentication_callback ( auth_data ) : return self . _handle_authentication_error ( ) return view_func ( * args , ** kwargs ) return decorated
def build ( tasks , worker_scheduler_factory = None , detailed_summary = False , ** env_params ) : """Run internally , bypassing the cmdline parsing . Useful if you have some luigi code that you want to run internally . Example : . . code - block : : python luigi . build ( [ MyTask1 ( ) , MyTask2 ( ) ] , local _ scheduler = True ) One notable difference is that ` build ` defaults to not using the identical process lock . Otherwise , ` build ` would only be callable once from each process . : param tasks : : param worker _ scheduler _ factory : : param env _ params : : return : True if there were no scheduling errors , even if tasks may fail ."""
if "no_lock" not in env_params : env_params [ "no_lock" ] = True luigi_run_result = _schedule_and_run ( tasks , worker_scheduler_factory , override_defaults = env_params ) return luigi_run_result if detailed_summary else luigi_run_result . scheduling_succeeded
def extract_index ( index_data , global_index = False ) : '''Instantiates and returns an AllIndex object given a valid index configuration CLI Example : salt myminion boto _ dynamodb . extract _ index index'''
parsed_data = { } keys = [ ] for key , value in six . iteritems ( index_data ) : for item in value : for field , data in six . iteritems ( item ) : if field == 'hash_key' : parsed_data [ 'hash_key' ] = data elif field == 'hash_key_data_type' : parsed_data [ 'hash_key_data_type' ] = data elif field == 'range_key' : parsed_data [ 'range_key' ] = data elif field == 'range_key_data_type' : parsed_data [ 'range_key_data_type' ] = data elif field == 'name' : parsed_data [ 'name' ] = data elif field == 'read_capacity_units' : parsed_data [ 'read_capacity_units' ] = data elif field == 'write_capacity_units' : parsed_data [ 'write_capacity_units' ] = data elif field == 'includes' : parsed_data [ 'includes' ] = data elif field == 'keys_only' : parsed_data [ 'keys_only' ] = True if parsed_data [ 'hash_key' ] : keys . append ( HashKey ( parsed_data [ 'hash_key' ] , data_type = parsed_data [ 'hash_key_data_type' ] ) ) if parsed_data . get ( 'range_key' ) : keys . append ( RangeKey ( parsed_data [ 'range_key' ] , data_type = parsed_data [ 'range_key_data_type' ] ) ) if ( global_index and parsed_data [ 'read_capacity_units' ] and parsed_data [ 'write_capacity_units' ] ) : parsed_data [ 'throughput' ] = { 'read' : parsed_data [ 'read_capacity_units' ] , 'write' : parsed_data [ 'write_capacity_units' ] } if parsed_data [ 'name' ] and keys : if global_index : if parsed_data . get ( 'keys_only' ) and parsed_data . get ( 'includes' ) : raise SaltInvocationError ( 'Only one type of GSI projection can be used.' ) if parsed_data . get ( 'includes' ) : return GlobalIncludeIndex ( parsed_data [ 'name' ] , parts = keys , throughput = parsed_data [ 'throughput' ] , includes = parsed_data [ 'includes' ] ) elif parsed_data . get ( 'keys_only' ) : return GlobalKeysOnlyIndex ( parsed_data [ 'name' ] , parts = keys , throughput = parsed_data [ 'throughput' ] , ) else : return GlobalAllIndex ( parsed_data [ 'name' ] , parts = keys , throughput = parsed_data [ 'throughput' ] ) else : return AllIndex ( parsed_data [ 'name' ] , parts = keys )
def request ( method = 'GET' ) : """send restful post http request decorator Provide a brief way to manipulate restful api , : param method : : class : ` str ` , : return : : class : ` func `"""
def decorator ( func ) : @ functools . wraps ( func ) def action ( self , * args , ** kwargs ) : f = furl ( self . server ) path , body = func ( self , * args , ** kwargs ) # deal with query string query = dict ( ) if isinstance ( path , tuple ) : path , query = path f . path . add ( path ) f . query . set ( query ) status_code , result = send_rest ( f . url , method = method . upper ( ) , body = body , session = self . session , headers = self . headers ) if status_code != httplib . OK : self . logger . error ( "{impl} {url} headers: {headers}, code: {code}" . format ( impl = method , url = f . url , headers = self . headers , code = status_code ) ) return status_code , result return action return decorator
def _check_configs ( self ) : """Reloads the configuration files ."""
configs = set ( self . _find_configs ( ) ) known_configs = set ( self . configs . keys ( ) ) new_configs = configs - known_configs for cfg in ( known_configs - configs ) : self . log . debug ( "Compass configuration has been removed: " + cfg ) del self . configs [ cfg ] for cfg in new_configs : self . log . debug ( "Found new compass configuration: " + cfg ) self . configs [ cfg ] = CompassConfig ( cfg )
def user_tickets_assigned ( self , user_id , external_id = None , ** kwargs ) : "https : / / developer . zendesk . com / rest _ api / docs / core / tickets # allowed - for"
api_path = "/api/v2/users/{user_id}/tickets/assigned.json" api_path = api_path . format ( user_id = user_id ) api_query = { } if "query" in kwargs . keys ( ) : api_query . update ( kwargs [ "query" ] ) del kwargs [ "query" ] if external_id : api_query . update ( { "external_id" : external_id , } ) return self . call ( api_path , query = api_query , ** kwargs )
def detalhe ( self , posicao = 0 ) : """Retorna o detalhe de um CEP da última lista de resultados"""
handle = self . _url_open ( 'detalheCEPAction.do' , { 'Metodo' : 'detalhe' , 'TipoCep' : 2 , 'Posicao' : posicao + 1 , 'CEP' : '' } ) html = handle . read ( ) return self . _parse_detalhe ( html )
def list_distribute_contents_simple ( input_list , function = lambda x : x ) : # type : ( List , Callable [ [ Any ] , Any ] ) - > List """Distribute the contents of a list eg . [ 1 , 1 , 1 , 2 , 2 , 3 ] - > [ 1 , 2 , 3 , 1 , 2 , 1 ] . List can contain complex types like dictionaries in which case the function can return the appropriate value eg . lambda x : x [ KEY ] Args : input _ list ( List ) : List to distribute values function ( Callable [ [ Any ] , Any ] ) : Return value to use for distributing . Defaults to lambda x : x . Returns : List : Distributed list"""
dictionary = dict ( ) for obj in input_list : dict_of_lists_add ( dictionary , function ( obj ) , obj ) output_list = list ( ) i = 0 done = False while not done : found = False for key in sorted ( dictionary ) : if i < len ( dictionary [ key ] ) : output_list . append ( dictionary [ key ] [ i ] ) found = True if found : i += 1 else : done = True return output_list
def _cnn_filter ( in_file , vrn_files , data ) : """Perform CNN filtering on input VCF using pre - trained models ."""
# tensor _ type = " reference " # 1D , reference sequence tensor_type = "read_tensor" # 2D , reads , flags , mapping quality score_file = _cnn_score_variants ( in_file , tensor_type , data ) return _cnn_tranch_filtering ( score_file , vrn_files , tensor_type , data )
def dissect ( self , data ) : """Dissect the field . : param bytes data : The data to extract the field value from : return : The rest of the data not used to dissect the field value : rtype : bytes"""
size = struct . calcsize ( "B" ) if len ( data ) < size : raise NotEnoughData ( "Not enough data to decode field '%s' value" % self . name ) curve_type = struct . unpack ( "B" , data [ : size ] ) [ 0 ] if curve_type == 0x03 : self . _value = ECParametersNamedCurveField ( "none" ) data = self . _value . dissect ( data ) else : raise NotImplementedError ( "Decoding of KeyExchange message for curve 0x%.2X not implemented" % curve_type ) return data
def get_annotation ( self , id_ ) : """Data for a specific annotation ."""
endpoint = "annotations/{id}" . format ( id = id_ ) return self . _make_request ( endpoint )
def compile_string ( string , compiler_class = Compiler , ** kwargs ) : """Compile a single string , and return a string of CSS . Keyword arguments are passed along to the underlying ` Compiler ` ."""
compiler = compiler_class ( ** kwargs ) return compiler . compile_string ( string )
def rpc_v2 ( self , cmd , arg_format , result_format , * args , ** kw ) : """Send an RPC call to this module , interpret the return value according to the result _ type kw argument . Unless raise keyword is passed with value False , raise an RPCException if the command is not successful . v2 enforces the use of arg _ format and result _ format v2 combines the feature + cmd chunks in to a single 2 - byte chunk"""
if args : packed_args = pack_rpc_payload ( arg_format , list ( args ) ) elif arg_format == "" : packed_args = b'' else : raise RPCInvalidArgumentsError ( "Arg format expects arguments to be present" , arg_format = arg_format , args = args ) passed_kw = dict ( ) if 'timeout' in kw : passed_kw [ 'timeout' ] = kw [ 'timeout' ] try : should_retry = False payload = self . stream . send_rpc ( self . addr , cmd , packed_args , ** passed_kw ) except BusyRPCResponse : if "retries" not in kw : kw [ 'retries' ] = 10 # Sleep 100 ms and try again unless we ' ve exhausted our retry attempts if kw [ "retries" ] == 0 : raise BusyRPCResponse ( "Could not complete RPC %d:%04X after 10 attempts due to busy tile" % ( self . addr , cmd ) ) should_retry = True # If the tile was busy , automatically retry up to 10 times if should_retry : kw [ 'retries' ] -= 1 sleep ( 0.1 ) return self . rpc_v2 ( cmd , arg_format , result_format , * args , ** kw ) return unpack_rpc_payload ( result_format , payload )
def _inspect_and_map ( self , identifier ) : """example response : u ' comment ' : u ' ' , u ' virtual _ size ' : 566087127, u ' container ' : u ' a2ea130e8c7a945823c804253c20f7c877376c69a36311a0cc614d5c455f645f ' , u ' os ' : u ' linux ' , u ' parent ' : u ' 14e75a5684c2fabb7db24d92bdda09d11da1179a7d86ab4c9640ef70d1fd4082 ' , u ' author ' : u ' alexb @ tune . com ' , u ' checksum ' : u ' tarsum . dev + sha256:1b755912c77197c6a43539f2a708ef89d5849b8ce02642cb702e47afaa8195c3 ' , u ' created ' : u ' 2014-10-16T23:41:25.445801849Z ' , u ' container _ config ' : { u ' tty ' : False , u ' on _ build ' : [ ] , u ' domainname ' : u ' ' , u ' attach _ stdin ' : False , u ' image ' : u ' 14e75a5684c2fabb7db24d92bdda09d11da1179a7d86ab4c9640ef70d1fd4082 ' , u ' port _ specs ' : None , u ' hostname ' : u ' 2c1b05d4dd63 ' , u ' mac _ address ' : u ' ' , u ' working _ dir ' : u ' ' , u ' entrypoint ' : [ u ' / usr / local / bin / dockerjenkins . sh ' ] , u ' env ' : [ u ' PATH = / usr / local / sbin : / usr / local / bin : / usr / sbin : / usr / bin : / sbin : / bin ' , u ' REFRESHED _ AT = 2014-10-14 ' , u ' JENKINS _ HOME = / opt / jenkins / data ' , u ' JENKINS _ MIRROR = http : / / mirrors . jenkins - ci . org ' u ' memory ' : 0, u ' attach _ stdout ' : False , u ' exposed _ ports ' : { u ' 8080 / tcp ' : { } u ' stdin _ once ' : False , u ' cpuset ' : u ' ' , u ' user ' : u ' ' , u ' network _ disabled ' : False , u ' memory _ swap ' : 0, u ' attach _ stderr ' : False , u ' cmd ' : [ u ' / bin / sh ' , u ' - c ' , u ' # ( nop ) ENTRYPOINT [ / usr / local / bin / dockerjenkins . sh ] ' u ' open _ stdin ' : False , u ' volumes ' : { u ' / var / lib / docker ' : { } u ' cpu _ shares ' : 0 u ' architecture ' : u ' amd64 ' , u ' docker _ version ' : u ' 1.3.0 ' , u ' config ' : { u ' tty ' : False , u ' on _ build ' : [ ] , u ' domainname ' : u ' ' , u ' attach _ stdin ' : False , u ' image ' : u ' 14e75a5684c2fabb7db24d92bdda09d11da1179a7d86ab4c9640ef70d1fd4082 ' , u ' port _ specs ' : None , u ' hostname ' : u ' 2c1b05d4dd63 ' , u ' mac _ address ' : u ' ' , u ' working _ dir ' : u ' ' , u ' entrypoint ' : [ u ' / usr / local / bin / dockerjenkins . sh ' ] , u ' env ' : [ u ' PATH = / usr / local / sbin : / usr / local / bin : / usr / sbin : / usr / bin : / sbin : / bin ' , u ' REFRESHED _ AT = 2014-10-14 ' , u ' JENKINS _ HOME = / opt / jenkins / data ' , u ' JENKINS _ MIRROR = http : / / mirrors . jenkins - ci . org ' u ' memory ' : 0, u ' attach _ stdout ' : False , u ' exposed _ ports ' : { u ' 8080 / tcp ' : { } u ' stdin _ once ' : False , u ' cpuset ' : u ' ' , u ' user ' : u ' ' , u ' network _ disabled ' : False , u ' memory _ swap ' : 0, u ' attach _ stderr ' : False , u ' cmd ' : None , u ' open _ stdin ' : False , u ' volumes ' : { u ' / var / lib / docker ' : { } u ' cpu _ shares ' : 0 u ' id ' : u ' d37e267af092e02aaab68e962fadcc1107a3b42a34b0c581ee1e3a54aed62ad4 ' , u ' size ' : 0"""
# validate try : response = normalize_keys ( self . client . inspect_image ( identifier ) ) self . comment = response [ 'comment' ] if response [ 'comment' ] else None self . id = response [ "id" ] self . virtual_size = response [ 'virtual_size' ] self . container = response [ 'container' ] self . os = response [ 'os' ] self . parent = response [ 'parent' ] self . author = response . get ( 'author' , None ) self . created_at = self . created_at = dateutil . parser . parse ( response [ 'created' ] , ignoretz = True ) self . architecture = response [ 'architecture' ] self . docker_version = response [ 'docker_version' ] self . size = response [ 'size' ] self . container_config = ContainerConfig ( response . get ( 'container_config' ) ) if response . get ( 'config' ) else ContainerConfig ( ) self . config = ContainerConfig ( response . get ( 'config' ) ) if response . get ( 'config' ) else ContainerConfig ( ) except Exception as e : raise e
def to_primitive ( self , value , context = None ) : """Schematics serializer override If epoch _ date is true then convert the ` datetime . datetime ` object into an epoch ` int ` ."""
if context and context . get ( 'epoch_date' ) : epoch = dt ( 1970 , 1 , 1 ) value = ( value - epoch ) . total_seconds ( ) return int ( value ) elif context and context . get ( 'datetime_date' ) : return value else : return super ( Type , self ) . to_primitive ( value , context )
def slamdunkFilterStatsTable ( self ) : """Take the parsed filter stats from Slamdunk and add it to a separate table"""
headers = OrderedDict ( ) headers [ 'mapped' ] = { 'namespace' : 'Slamdunk' , 'title' : '{} Mapped' . format ( config . read_count_prefix ) , 'description' : '# mapped reads ({})' . format ( config . read_count_desc ) , 'shared_key' : 'read_count' , 'min' : 0 , 'format' : '{:,.2f}' , 'suffix' : config . read_count_prefix , 'scale' : 'YlGn' , 'modify' : lambda x : float ( x ) * config . read_count_multiplier , } headers [ 'multimapper' ] = { 'namespace' : 'Slamdunk' , 'title' : '{} Multimap-Filtered' . format ( config . read_count_prefix ) , 'description' : '# multimap-filtered reads ({})' . format ( config . read_count_desc ) , 'shared_key' : 'read_count' , 'min' : 0 , 'format' : '{:,.2f}' , 'suffix' : config . read_count_prefix , 'scale' : 'OrRd' , 'modify' : lambda x : float ( x ) * config . read_count_multiplier , } headers [ 'nmfiltered' ] = { 'namespace' : 'Slamdunk' , 'title' : '{} NM-Filtered' . format ( config . read_count_prefix ) , 'description' : '# NM-filtered reads ({})' . format ( config . read_count_desc ) , 'shared_key' : 'read_count' , 'min' : 0 , 'format' : '{:,.2f}' , 'suffix' : config . read_count_prefix , 'scale' : 'OrRd' , 'modify' : lambda x : float ( x ) * config . read_count_multiplier , } headers [ 'idfiltered' ] = { 'namespace' : 'Slamdunk' , 'title' : '{} Identity-Filtered' . format ( config . read_count_prefix ) , 'description' : '# identity-filtered reads ({})' . format ( config . read_count_desc ) , 'shared_key' : 'read_count' , 'min' : 0 , 'format' : '{:,.2f}' , 'suffix' : config . read_count_prefix , 'scale' : 'OrRd' , 'modify' : lambda x : float ( x ) * config . read_count_multiplier , } headers [ 'mqfiltered' ] = { 'namespace' : 'Slamdunk' , 'title' : '{} MQ-Filtered' . format ( config . read_count_prefix ) , 'description' : '# MQ-filtered reads ({})' . format ( config . read_count_desc ) , 'shared_key' : 'read_count' , 'min' : 0 , 'format' : '{:,.2f}' , 'suffix' : config . read_count_prefix , 'scale' : 'OrRd' , 'modify' : lambda x : float ( x ) * config . read_count_multiplier , } pconfig = { 'id' : 'slamdunk_filtering_table' , 'min' : 0 , } self . add_section ( name = 'Filter statistics' , anchor = 'slamdunk_filtering' , description = 'This table shows the number of reads filtered with each filter criterion during filtering phase of slamdunk.' , plot = table . plot ( self . slamdunk_data , headers , pconfig ) )
def expand_nested ( self , cats ) : """Populate widget with nested catalogs"""
down = '│' right = '└──' def get_children ( parent ) : return [ e ( ) for e in parent . _entries . values ( ) if e . _container == 'catalog' ] if len ( cats ) == 0 : return cat = cats [ 0 ] old = list ( self . options . items ( ) ) name = next ( k for k , v in old if v == cat ) index = next ( i for i , ( k , v ) in enumerate ( old ) if v == cat ) if right in name : prefix = f'{name.split(right)[0]}{down} {right}' else : prefix = right children = get_children ( cat ) for i , child in enumerate ( children ) : old . insert ( index + i + 1 , ( f'{prefix} {child.name}' , child ) ) self . widget . options = dict ( old )
def predict_size_distribution_component_models ( self , model_names , input_columns , output_columns , metadata_cols , data_mode = "forecast" , location = 6 ) : """Make predictions using fitted size distribution models . Args : model _ names : Name of the models for predictions input _ columns : Data columns used for input into ML models output _ columns : Names of output columns metadata _ cols : Columns from input data that should be included in the data frame with the predictions . data _ mode : Set of data used as input for prediction models location : Value of fixed location parameter Returns : Predictions in dictionary of data frames grouped by group type"""
groups = self . size_distribution_models . keys ( ) predictions = pd . DataFrame ( self . data [ data_mode ] [ "combo" ] [ metadata_cols ] ) for group in groups : group_idxs = self . data [ data_mode ] [ "combo" ] [ self . group_col ] == group group_count = np . count_nonzero ( group_idxs ) print ( self . size_distribution_models [ group ] ) if group_count > 0 : log_mean = self . size_distribution_models [ group ] [ "lognorm" ] [ "mean" ] log_sd = self . size_distribution_models [ group ] [ "lognorm" ] [ "sd" ] for m , model_name in enumerate ( model_names ) : raw_preds = np . zeros ( ( group_count , len ( output_columns ) ) ) for c in range ( len ( output_columns ) ) : raw_preds [ : , c ] = self . size_distribution_models [ group ] [ "pc_{0:d}" . format ( c ) ] [ model_name ] . predict ( self . data [ data_mode ] [ "combo" ] . loc [ group_idxs , input_columns ] ) log_norm_preds = self . size_distribution_models [ group ] [ "lognorm" ] [ "pca" ] . inverse_transform ( raw_preds ) log_norm_preds [ : , 0 ] *= - 1 multi_predictions = np . exp ( log_norm_preds * log_sd + log_mean ) if multi_predictions . shape [ 1 ] == 2 : multi_predictions_temp = np . zeros ( ( multi_predictions . shape [ 0 ] , 3 ) ) multi_predictions_temp [ : , 0 ] = multi_predictions [ : , 0 ] multi_predictions_temp [ : , 1 ] = location multi_predictions_temp [ : , 2 ] = multi_predictions [ : , 1 ] multi_predictions = multi_predictions_temp for p , pred_col in enumerate ( [ "shape" , "location" , "scale" ] ) : predictions . loc [ group_idxs , model_name . replace ( " " , "-" ) + "_" + pred_col ] = multi_predictions [ : , p ] return predictions
def numRegisteredByRole ( self ) : '''Return a dictionary listing registrations by all available roles ( including no role )'''
role_list = list ( self . availableRoles ) + [ None , ] return { getattr ( x , 'name' , None ) : self . numRegisteredForRole ( x ) for x in role_list }
def disable_auto_login ( ) : '''. . versionadded : : 2016.3.0 Disables auto login on the machine Returns : bool : ` ` True ` ` if successful , otherwise ` ` False ` ` CLI Example : . . code - block : : bash salt ' * ' user . disable _ auto _ login'''
# Remove the kcpassword file cmd = 'rm -f /etc/kcpassword' __salt__ [ 'cmd.run' ] ( cmd ) # Remove the entry from the defaults file cmd = [ 'defaults' , 'delete' , '/Library/Preferences/com.apple.loginwindow.plist' , 'autoLoginUser' ] __salt__ [ 'cmd.run' ] ( cmd ) return True if not get_auto_login ( ) else False
def _GetRecord ( self , offset , record_size ) : """Retrieve a single record from the file . Args : offset : offset from start of input _ dat where header starts record _ size : length of the header according to file ( untrusted ) Returns : A dict containing a single browser history record ."""
record_header = "<4sLQQL" get4 = lambda x : struct . unpack ( "<L" , self . input_dat [ x : x + 4 ] ) [ 0 ] url_offset = struct . unpack ( "B" , self . input_dat [ offset + 52 : offset + 53 ] ) [ 0 ] if url_offset in [ 0xFF , 0xFE ] : return None data_offset = get4 ( offset + 68 ) data_size = get4 ( offset + 72 ) start_pos = offset + data_offset data = struct . unpack ( "{0}s" . format ( data_size ) , self . input_dat [ start_pos : start_pos + data_size ] ) [ 0 ] fmt = record_header unknown_size = url_offset - struct . calcsize ( fmt ) fmt += "{0}s" . format ( unknown_size ) fmt += "{0}s" . format ( record_size - struct . calcsize ( fmt ) ) dat = struct . unpack ( fmt , self . input_dat [ offset : offset + record_size ] ) header , blocks , mtime , ctime , ftime , _ , url = dat url = url . split ( b"\x00" ) [ 0 ] . decode ( "utf-8" ) if mtime : mtime = mtime // 10 - WIN_UNIX_DIFF_MSECS if ctime : ctime = ctime // 10 - WIN_UNIX_DIFF_MSECS return { "header" : header , # the header "blocks" : blocks , # number of blocks "urloffset" : url_offset , # offset of URL in file "data_offset" : data_offset , # offset for start of data "data_size" : data_size , # size of data "data" : data , # actual data "mtime" : mtime , # modified time "ctime" : ctime , # created time "ftime" : ftime , # file time "url" : url # the url visited }
def flux_components ( self , kwargs_light , n_grid = 400 , delta_grid = 0.01 , deltaPix = 0.05 , type = "lens" ) : """computes the total flux in each component of the model : param kwargs _ light : : param n _ grid : : param delta _ grid : : return :"""
flux_list = [ ] R_h_list = [ ] x_grid , y_grid = util . make_grid ( numPix = n_grid , deltapix = delta_grid ) kwargs_copy = copy . deepcopy ( kwargs_light ) for k , kwargs in enumerate ( kwargs_light ) : if 'center_x' in kwargs_copy [ k ] : kwargs_copy [ k ] [ 'center_x' ] = 0 kwargs_copy [ k ] [ 'center_y' ] = 0 if type == 'lens' : light = self . LensLightModel . surface_brightness ( x_grid , y_grid , kwargs_copy , k = k ) elif type == 'source' : light = self . SourceModel . surface_brightness ( x_grid , y_grid , kwargs_copy , k = k ) else : raise ValueError ( "type %s not supported!" % type ) flux = np . sum ( light ) * delta_grid ** 2 / deltaPix ** 2 R_h = analysis_util . half_light_radius ( light , x_grid , y_grid ) flux_list . append ( flux ) R_h_list . append ( R_h ) return flux_list , R_h_list
def CopyToDateTimeString ( self ) : """Copies the time elements to a date and time string . Returns : str : date and time value formatted as : " YYYY - MM - DD hh : mm : ss " or " YYYY - MM - DD hh : mm : ss . # # # # # " or None if time elements are missing . Raises : ValueError : if the precision value is unsupported ."""
if self . _number_of_seconds is None or self . fraction_of_second is None : return None precision_helper = precisions . PrecisionHelperFactory . CreatePrecisionHelper ( self . _precision ) return precision_helper . CopyToDateTimeString ( self . _time_elements_tuple , self . fraction_of_second )
def tables_with_counts ( self ) : """Return the number of entries in all table ."""
table_to_count = lambda t : self . count_rows ( t ) return zip ( self . tables , map ( table_to_count , self . tables ) )
def write ( self , file ) : r"""Save CAPTCHA image in given filepath . Property calls self . image and saves image contents in a file , returning CAPTCHA text and filepath as a tuple . See : image . : param file : Path to file , where CAPTCHA image will be saved . : returns : ` ` tuple ` ` ( CAPTCHA text , filepath )"""
text , image = self . image image . save ( file , format = self . format ) return ( text , file )
def get_client_ip ( environ ) : # type : ( Dict [ str , str ] ) - > Optional [ Any ] """Infer the user IP address from various headers . This cannot be used in security sensitive situations since the value may be forged from a client , but it ' s good enough for the event payload ."""
try : return environ [ "HTTP_X_FORWARDED_FOR" ] . split ( "," ) [ 0 ] . strip ( ) except ( KeyError , IndexError ) : pass try : return environ [ "HTTP_X_REAL_IP" ] except KeyError : pass return environ . get ( "REMOTE_ADDR" )
def format_phone_number ( number ) : """Formats a phone number in international notation . : param number : str or phonenumber object : return : str"""
if not isinstance ( number , phonenumbers . PhoneNumber ) : number = phonenumbers . parse ( number ) return phonenumbers . format_number ( number , phonenumbers . PhoneNumberFormat . INTERNATIONAL )
def report ( self , filename = None ) : """Write details of each versioned target to file : param string filename : file to write out the report to Fields in the report : invocation _ id : A sequence number that increases each time a task is invoked task _ name : The name of the task targets _ hash : an id from a hash of all target ids to identify a VersionedTargetSet target _ id : target id cache _ key _ id : the Id for the cache key cache _ key _ hash : computed hash for the cache key phase : What part of the validation check the values were captured valid : True if the cache is valid for the VersionedTargetSet"""
# TODO ( zundel ) set report to stream to the file filename = filename or self . _filename if filename : # Usually the directory exists from reporting initialization , but not if clean - all was a goal . with safe_open ( filename , 'w' ) as writer : writer . write ( 'invocation_id,task_name,targets_hash,target_id,cache_key_id,cache_key_hash,phase,valid' + '\n' ) for task_report in self . _task_reports . values ( ) : task_report . report ( writer )
def get_sites ( self , entry ) : """Return the sites linked in HTML ."""
try : index_url = reverse ( 'zinnia:entry_archive_index' ) except NoReverseMatch : index_url = '' return format_html_join ( ', ' , '<a href="{}://{}{}" target="blank">{}</a>' , [ ( settings . PROTOCOL , site . domain , index_url , conditional_escape ( site . name ) ) for site in entry . sites . all ( ) ] )
def get_topic_triggers ( rs , topic , thats , depth = 0 , inheritance = 0 , inherited = False ) : """Recursively scan a topic and return a list of all triggers . Arguments : rs ( RiveScript ) : A reference to the parent RiveScript instance . topic ( str ) : The original topic name . thats ( bool ) : Are we getting triggers for ' previous ' replies ? depth ( int ) : Recursion step counter . inheritance ( int ) : The inheritance level counter , for topics that inherit other topics . inherited ( bool ) : Whether the current topic is inherited by others . Returns : [ ] str : List of all triggers found ."""
# Break if we ' re in too deep . if depth > rs . _depth : rs . _warn ( "Deep recursion while scanning topic inheritance" ) # Keep in mind here that there is a difference between ' includes ' and # ' inherits ' - - topics that inherit other topics are able to OVERRIDE # triggers that appear in the inherited topic . This means that if the top # topic has a trigger of simply ' * ' , then NO triggers are capable of # matching in ANY inherited topic , because even though * has the lowest # priority , it has an automatic priority over all inherited topics . # The getTopicTriggers method takes this into account . All topics that # inherit other topics will have their triggers prefixed with a fictional # { inherits } tag , which would start at { inherits = 0 } and increment if this # topic has other inheriting topics . So we can use this tag to make sure # topics that inherit things will have their triggers always be on top of # the stack , from inherits = 0 to inherits = n . # Important info about the depth vs inheritance params to this function : # depth increments by 1 each time this function recursively calls itrs . # inheritance increments by 1 only when this topic inherits another # topic . # This way , ' > topic alpha includes beta inherits gamma ' will have this # effect : # alpha and beta ' s triggers are combined together into one matching # pool , and then those triggers have higher matching priority than # gamma ' s . # The inherited option is True if this is a recursive call , from a topic # that inherits other topics . This forces the { inherits } tag to be added # to the triggers . This only applies when the top topic ' includes ' # another topic . rs . _say ( "\tCollecting trigger list for topic " + topic + "(depth=" + str ( depth ) + "; inheritance=" + str ( inheritance ) + "; " + "inherited=" + str ( inherited ) + ")" ) # topic : the name of the topic # depth : starts at 0 and + + ' s with each recursion # Topic doesn ' t exist ? if not topic in rs . _topics : rs . _warn ( "Inherited or included topic {} doesn't exist or has no triggers" . format ( topic ) ) return [ ] # Collect an array of triggers to return . triggers = [ ] # Get those that exist in this topic directly . inThisTopic = [ ] if not thats : # The non - that structure is { topic } - > [ array of triggers ] if topic in rs . _topics : for trigger in rs . _topics [ topic ] : inThisTopic . append ( [ trigger [ "trigger" ] , trigger ] ) else : # The ' that ' structure is : { topic } - > { cur trig } - > { prev trig } - > { trig info } if topic in rs . _thats . keys ( ) : for curtrig in rs . _thats [ topic ] . keys ( ) : for previous , pointer in rs . _thats [ topic ] [ curtrig ] . items ( ) : inThisTopic . append ( [ pointer [ "trigger" ] , pointer ] ) # Does this topic include others ? if topic in rs . _includes : # Check every included topic . for includes in rs . _includes [ topic ] : rs . _say ( "\t\tTopic " + topic + " includes " + includes ) triggers . extend ( get_topic_triggers ( rs , includes , thats , ( depth + 1 ) , inheritance , True ) ) # Does this topic inherit others ? if topic in rs . _lineage : # Check every inherited topic . for inherits in rs . _lineage [ topic ] : rs . _say ( "\t\tTopic " + topic + " inherits " + inherits ) triggers . extend ( get_topic_triggers ( rs , inherits , thats , ( depth + 1 ) , ( inheritance + 1 ) , False ) ) # Collect the triggers for * this * topic . If this topic inherits any # other topics , it means that this topic ' s triggers have higher # priority than those in any inherited topics . Enforce this with an # { inherits } tag . if topic in rs . _lineage or inherited : for trigger in inThisTopic : rs . _say ( "\t\tPrefixing trigger with {inherits=" + str ( inheritance ) + "}" + trigger [ 0 ] ) triggers . append ( [ "{inherits=" + str ( inheritance ) + "}" + trigger [ 0 ] , trigger [ 1 ] ] ) else : triggers . extend ( inThisTopic ) return triggers
def construct ( path , name = None ) : "Selects an appropriate CGroup subclass for the given CGroup path ."
name = name if name else path . split ( "/" ) [ 4 ] classes = { "memory" : Memory , "cpu" : CPU , "cpuacct" : CPUAcct } constructor = classes . get ( name , CGroup ) log . debug ( "Chose %s for: %s" , constructor . __name__ , path ) return constructor ( path , name )
def adddeploykey ( self , project_id , title , key ) : """Creates a new deploy key for a project . : param project _ id : project id : param title : title of the key : param key : the key itself : return : true if success , false if not"""
data = { 'id' : project_id , 'title' : title , 'key' : key } request = requests . post ( '{0}/{1}/keys' . format ( self . projects_url , project_id ) , headers = self . headers , data = data , verify = self . verify_ssl , auth = self . auth , timeout = self . timeout ) if request . status_code == 201 : return request . json ( ) else : return False
def stc_system_info ( stc_addr ) : """Return dictionary of STC and API information . If a session already exists , then use it to get STC information and avoid taking the time to start a new session . A session is necessary to get STC information ."""
stc = stchttp . StcHttp ( stc_addr ) sessions = stc . sessions ( ) if sessions : # If a session already exists , use it to get STC information . stc . join_session ( sessions [ 0 ] ) sys_info = stc . system_info ( ) else : # Create a new session to get STC information . stc . new_session ( 'anonymous' ) try : sys_info = stc . system_info ( ) finally : # Make sure the temporary session in terminated . stc . end_session ( ) return sys_info
def extend ( base : Dict [ Any , Any ] , extension : Dict [ Any , Any ] ) -> Dict [ Any , Any ] : '''Extend base by updating with the extension . * * Arguments * * : ` ` base ` ` : dictionary to have keys updated or added : ` ` extension ` ` : dictionary to update base with * * Return Value ( s ) * * Resulting dictionary from updating base with extension .'''
_ = copy . deepcopy ( base ) _ . update ( extension ) return _
def makedict ( self , dictfile , fnamefobject ) : """stuff file data into the blank dictionary"""
# fname = ' . / exapmlefiles / 5ZoneDD . idf ' # fname = ' . / 1ZoneUncontrolled . idf ' if isinstance ( dictfile , Idd ) : localidd = copy . deepcopy ( dictfile ) dt , dtls = localidd . dt , localidd . dtls else : dt , dtls = self . initdict ( dictfile ) # astr = mylib2 . readfile ( fname ) astr = fnamefobject . read ( ) try : astr = astr . decode ( 'ISO-8859-2' ) except AttributeError : pass fnamefobject . close ( ) nocom = removecomment ( astr , '!' ) idfst = nocom # alist = string . split ( idfst , ' ; ' ) alist = idfst . split ( ';' ) lss = [ ] for element in alist : # lst = string . split ( element , ' , ' ) lst = element . split ( ',' ) lss . append ( lst ) for i in range ( 0 , len ( lss ) ) : for j in range ( 0 , len ( lss [ i ] ) ) : lss [ i ] [ j ] = lss [ i ] [ j ] . strip ( ) for element in lss : node = element [ 0 ] . upper ( ) if node in dt : # stuff data in this key dt [ node . upper ( ) ] . append ( element ) else : # scream if node == '' : continue print ( 'this node -%s-is not present in base dictionary' % ( node ) ) self . dt , self . dtls = dt , dtls return dt , dtls
def _delete_partition ( self , tenant_id , tenant_name ) : """Function to delete a service partition ."""
self . dcnm_obj . delete_partition ( tenant_name , fw_const . SERV_PART_NAME )
def opens ( self , tag = None , fromdate = None , todate = None ) : """Gets total counts of recipients who opened your emails . This is only recorded when open tracking is enabled for that email ."""
return self . call ( "GET" , "/stats/outbound/opens" , tag = tag , fromdate = fromdate , todate = todate )
def get_gradebook_column_ids_by_gradebooks ( self , gradebook_ids ) : """Gets the list of ` ` GradebookColumn Ids ` ` corresponding to a list of ` ` Gradebooks ` ` . arg : gradebook _ ids ( osid . id . IdList ) : list of gradebook ` ` Ids ` ` return : ( osid . id . IdList ) - list of gradebook column ` ` Ids ` ` raise : NullArgument - ` ` gradebook _ ids ` ` is ` ` null ` ` raise : OperationFailed - unable to complete request raise : PermissionDenied - authorization failure * compliance : mandatory - - This method must be implemented . *"""
# Implemented from template for # osid . resource . ResourceBinSession . get _ resource _ ids _ by _ bins id_list = [ ] for gradebook_column in self . get_gradebook_columns_by_gradebooks ( gradebook_ids ) : id_list . append ( gradebook_column . get_id ( ) ) return IdList ( id_list )
def ssh ( gandi , resource , login , identity , wipe_key , wait , args ) : """Spawn an SSH session to virtual machine . Resource can be a Hostname or an ID"""
if '@' in resource : ( login , resource ) = resource . split ( '@' , 1 ) if wipe_key : gandi . iaas . ssh_keyscan ( resource ) if wait : gandi . iaas . wait_for_sshd ( resource ) gandi . iaas . ssh ( resource , login , identity , args )
def listFieldsFromWorkitem ( self , copied_from , keep = False ) : """List all the attributes to be rendered directly from some to - be - copied workitems More details , please refer to : class : ` rtcclient . template . Templater . listFieldsFromWorkitem `"""
return self . templater . listFieldsFromWorkitem ( copied_from , keep = keep )
def get_pfam_accession_numbers_from_pdb_id ( self , pdb_id ) : '''Note : an alternative is to use the RCSB API e . g . http : / / www . rcsb . org / pdb / rest / hmmer ? structureId = 1cdg .'''
pdb_id = pdb_id . lower ( ) if self . pdb_chain_to_pfam_mapping . get ( pdb_id ) : return self . pdb_chain_to_pfam_mapping [ pdb_id ] . copy ( )
def get_addon_id ( addonxml ) : '''Parses an addon id from the given addon . xml filename .'''
xml = parse ( addonxml ) addon_node = xml . getElementsByTagName ( 'addon' ) [ 0 ] return addon_node . getAttribute ( 'id' )
def binary_shader ( self , output_jar , main , jar , custom_rules = None , jvm_options = None ) : """Yields an ` Executor . Runner ` that will perform shading of the binary ` jar ` when ` run ( ) ` . The default rules will ensure the ` main ` class name is un - changed along with a minimal set of support classes but that everything else will be shaded . Any ` custom _ rules ` are given highest precedence and so they can interfere with this automatic binary shading . In general its safe to add exclusion rules to open up classes that need to be shared between the binary and the code it runs over . An example would be excluding the ` org . junit . Test ` annotation class from shading since both a tool running junit needs to be able to scan for this annotation applied to the user code it tests . : param unicode output _ jar : The path to dump the shaded jar to ; will be over - written if it exists . : param unicode main : The main class in the ` jar ` to preserve as the entry point . : param unicode jar : The path to the jar file to shade . : param list custom _ rules : An optional list of custom ` Shader . Rule ` s . : param list jvm _ options : an optional sequence of options for the underlying jvm : returns : An ` Executor . Runner ` that can be ` run ( ) ` to shade the given ` jar ` . : rtype : : class : ` pants . java . executor . Executor . Runner `"""
all_rules = self . assemble_binary_rules ( main , jar , custom_rules = custom_rules ) return self . binary_shader_for_rules ( output_jar , jar , all_rules , jvm_options = jvm_options )
def output ( ret , ** kwargs ) : '''Display the output as table . Args : * nested _ indent : integer , specify the left alignment . * has _ header : boolean specifying if header should be displayed . Default : True . * row _ delimiter : character to separate rows . Default : ` ` _ ` ` . * delim : character to separate columns . Default : ` ` " | " ` ` . * justify : text alignment . Default : ` ` center ` ` . * separate _ rows : boolean specifying if row separator will be displayed between consecutive rows . Default : True . * prefix : character at the beginning of the row . Default : ` ` " | " ` ` . * suffix : character at the end of the row . Default : ` ` " | " ` ` . * width : column max width . Default : ` ` 50 ` ` . * rows _ key : display the rows under a specific key . * labels _ key : use the labels under a certain key . Otherwise will try to use the dictionary keys ( if any ) . * title : display title when only one table is selected ( using the ` ` rows _ key ` ` argument ) .'''
# to facilitate re - use if 'opts' in kwargs : global __opts__ # pylint : disable = W0601 __opts__ = kwargs . pop ( 'opts' ) # Prefer kwargs before opts base_indent = kwargs . get ( 'nested_indent' , 0 ) or __opts__ . get ( 'out.table.nested_indent' , 0 ) rows_key = kwargs . get ( 'rows_key' ) or __opts__ . get ( 'out.table.rows_key' ) labels_key = kwargs . get ( 'labels_key' ) or __opts__ . get ( 'out.table.labels_key' ) title = kwargs . get ( 'title' ) or __opts__ . get ( 'out.table.title' ) class_kvargs = { } argks = ( 'has_header' , 'row_delimiter' , 'delim' , 'justify' , 'separate_rows' , 'prefix' , 'suffix' , 'width' ) for argk in argks : argv = kwargs . get ( argk ) or __opts__ . get ( 'out.table.{key}' . format ( key = argk ) ) if argv is not None : class_kvargs [ argk ] = argv table = TableDisplay ( ** class_kvargs ) out = [ ] if title and rows_key : out . append ( table . ustring ( base_indent , title , table . WHITE , # pylint : disable = no - member suffix = '\n' ) ) return '\n' . join ( table . display ( salt . utils . data . decode ( ret ) , base_indent , out , rows_key = rows_key , labels_key = labels_key ) )
def chat_post_message ( self , channel , text , ** params ) : """chat . postMessage This method posts a message to a channel . https : / / api . slack . com / methods / chat . postMessage"""
method = 'chat.postMessage' params . update ( { 'channel' : channel , 'text' : text , } ) return self . _make_request ( method , params )
def split_sentences_spacy ( text , language_model = 'en' ) : r"""You must download a spacy language model with python - m download ' en ' The default English language model for spacy tends to be a lot more agressive than NLTK ' s punkt : > > > split _ sentences _ nltk ( " Hi Ms . Lovelace . \ nI ' m a wanna - \ nbe human @ I . B . M . ; ) - - Watson 2.0 " ) [ ' Hi Ms . Lovelace . ' , " I ' m a wanna - \ nbe human @ I . B . M . " , ' ; ) - - Watson 2.0 ' ] > > > split _ sentences _ spacy ( " Hi Ms . Lovelace . \ nI ' m a wanna - \ nbe human @ I . B . M . ; ) - - Watson 2.0 " ) [ ' Hi Ms . Lovelace . ' , " I ' m a wanna - " , ' be human @ ' , ' I . B . M . ; ) - - Watson 2.0 ' ] > > > split _ sentences _ spacy ( " Hi Ms . Lovelace . I ' m at I . B . M . - - Watson 2.0 " ) [ ' Hi Ms . Lovelace . ' , " I ' m at I . B . M . - - Watson 2.0 " ] > > > split _ sentences _ nltk ( " Hi Ms . Lovelace . I ' m at I . B . M . - - Watson 2.0 " ) [ ' Hi Ms . Lovelace . ' , " I ' m at I . B . M . " , ' - - Watson 2.0 ' ]"""
doc = nlp ( text ) sentences = [ ] if not hasattr ( doc , 'sents' ) : logger . warning ( "Using NLTK sentence tokenizer because SpaCy language model hasn't been loaded" ) return split_sentences_nltk ( text ) for w , span in enumerate ( doc . sents ) : sent = '' . join ( doc [ i ] . string for i in range ( span . start , span . end ) ) . strip ( ) if len ( sent ) : sentences . append ( sent ) return sentences
def hasField ( cls , fieldName ) : """returns True / False wether the collection has field K in it ' s schema . Use the dot notation for the nested fields : address . street"""
path = fieldName . split ( "." ) v = cls . _fields for k in path : try : v = v [ k ] except KeyError : return False return True
def is_zero_user ( self ) : """返回当前用户是否为三零用户 , 其实是四零 : 赞同0 , 感谢0 , 提问0 , 回答0. : return : 是否是三零用户 : rtype : bool"""
return self . upvote_num + self . thank_num + self . question_num + self . answer_num == 0
def getBox ( box , pagesize ) : """Parse sizes by corners in the form : < X - Left > < Y - Upper > < Width > < Height > The last to values with negative values are interpreted as offsets form the right and lower border ."""
box = str ( box ) . split ( ) if len ( box ) != 4 : raise Exception ( "box not defined right way" ) x , y , w , h = [ getSize ( pos ) for pos in box ] return getCoords ( x , y , w , h , pagesize )
def createEditor ( self , parent , option , index ) : """Returns the widget used to change data from the model and can be reimplemented to customize editing behavior . Reimplemented from QStyledItemDelegate ."""
logger . debug ( "ConfigItemDelegate.createEditor, parent: {!r}" . format ( parent . objectName ( ) ) ) assert index . isValid ( ) , "sanity check failed: invalid index" cti = index . model ( ) . getItem ( index ) editor = cti . createEditor ( self , parent , option ) return editor
def maximum_size_bytes ( self ) : """Gets the biggest disk drive : returns size in bytes ."""
return utils . max_safe ( [ device . get ( 'CapacityBytes' ) for device in self . devices if device . get ( 'CapacityBytes' ) is not None ] )
def mutagen_call ( action , path , func , * args , ** kwargs ) : """Call a Mutagen function with appropriate error handling . ` action ` is a string describing what the function is trying to do , and ` path ` is the relevant filename . The rest of the arguments describe the callable to invoke . We require at least Mutagen 1.33 , where ` IOError ` is * never * used , neither for internal parsing errors * nor * for ordinary IO error conditions such as a bad filename . Mutagen - specific parsing errors and IO errors are reraised as ` UnreadableFileError ` . Other exceptions raised inside Mutagen - - - i . e . , bugs - - - are reraised as ` MutagenError ` ."""
try : return func ( * args , ** kwargs ) except mutagen . MutagenError as exc : log . debug ( u'%s failed: %s' , action , six . text_type ( exc ) ) raise UnreadableFileError ( path , six . text_type ( exc ) ) except Exception as exc : # Isolate bugs in Mutagen . log . debug ( u'%s' , traceback . format_exc ( ) ) log . error ( u'uncaught Mutagen exception in %s: %s' , action , exc ) raise MutagenError ( path , exc )
def resolve ( self , definitions ) : """Resolve named references to other WSDL objects . Can be safely called multiple times . @ param definitions : A definitions object . @ type definitions : L { Definitions }"""
if not self . __resolved : self . do_resolve ( definitions ) self . __resolved = True
def do_cancel ( self , taskid : int ) -> None : """Cancel an indicated task"""
task = task_by_id ( taskid , self . _loop ) if task : fut = asyncio . run_coroutine_threadsafe ( cancel_task ( task ) , loop = self . _loop ) fut . result ( timeout = 3 ) self . _sout . write ( 'Cancel task %d\n' % taskid ) else : self . _sout . write ( 'No task %d\n' % taskid )
def rms ( self , x , params = ( ) ) : """Returns root mean square value of f ( x , params )"""
internal_x , internal_params = self . pre_process ( np . asarray ( x ) , np . asarray ( params ) ) if internal_params . ndim > 1 : raise NotImplementedError ( "Parameters should be constant." ) result = np . empty ( internal_x . size // self . nx ) for idx in range ( internal_x . shape [ 0 ] ) : result [ idx ] = np . sqrt ( np . mean ( np . square ( self . f_cb ( internal_x [ idx , : ] , internal_params ) ) ) ) return result
def valid_conkey ( self , conkey ) : """Check that the conkey is a valid one . Return True if valid . A condition key is valid if it is one in the _ COND _ PREFIXES list . With the prefix removed , the remaining string must be either a number or the empty string ."""
for prefix in _COND_PREFIXES : trailing = conkey . lstrip ( prefix ) if trailing == '' and conkey : # conkey is not empty return True try : int ( trailing ) return True except ValueError : pass return False
def matches ( self , a , b , ** config ) : """The message must match by package"""
package_a = self . processor . _u2p ( a [ 'msg' ] [ 'update' ] [ 'title' ] ) [ 0 ] package_b = self . processor . _u2p ( b [ 'msg' ] [ 'update' ] [ 'title' ] ) [ 0 ] if package_a != package_b : return False return True
def main ( argv = None ) : """The entry point of the application ."""
if argv is None : argv = sys . argv [ 1 : ] usage = '\n\n\n' . join ( __doc__ . split ( '\n\n\n' ) [ 1 : ] ) version = 'Gitpress ' + __version__ # Parse options args = docopt ( usage , argv = argv , version = version ) # Execute command try : return execute ( args ) except RepositoryNotFoundError as ex : error ( 'No Gitpress repository found at' , ex . directory )
def almost_unitary ( gate : Gate ) -> bool : """Return true if gate tensor is ( almost ) unitary"""
res = ( gate @ gate . H ) . asoperator ( ) N = gate . qubit_nb return np . allclose ( asarray ( res ) , np . eye ( 2 ** N ) , atol = TOLERANCE )
def extract_names ( sender ) : """Tries to extract sender ' s names from ` From : ` header . It could extract not only the actual names but e . g . the name of the company , parts of email , etc . > > > extract _ names ( ' Sergey N . Obukhov < serobnic @ mail . ru > ' ) [ ' Sergey ' , ' Obukhov ' , ' serobnic ' ] > > > extract _ names ( ' ' )"""
sender = to_unicode ( sender , precise = True ) # Remove non - alphabetical characters sender = "" . join ( [ char if char . isalpha ( ) else ' ' for char in sender ] ) # Remove too short words and words from " black " list i . e . # words like ` ru ` , ` gmail ` , ` com ` , ` org ` , etc . sender = [ word for word in sender . split ( ) if len ( word ) > 1 and not word in BAD_SENDER_NAMES ] # Remove duplicates names = list ( set ( sender ) ) return names
def validate_code_path ( valid_paths , code_path , ** kw ) : """Raise an exception if code _ path is not one of our whitelisted valid _ paths ."""
root , name = code_path . split ( ':' , 1 ) if name not in valid_paths [ root ] : raise ValueError ( "%r is not a valid code_path" % code_path )
def Fritzsche ( SG , Tavg , L = None , D = None , P1 = None , P2 = None , Q = None , Ts = 288.7 , Ps = 101325. , Zavg = 1 , E = 1 ) : r'''Calculation function for dealing with flow of a compressible gas in a pipeline with the Fritzsche formula . Can calculate any of the following , given all other inputs : * Flow rate * Upstream pressure * Downstream pressure * Diameter of pipe * Length of pipe A variety of different constants and expressions have been presented for the Fritzsche formula . Here , the form as in [ 1 ] _ is used but with all inputs in base SI units . . . math : : Q = 93.500 \ frac { T _ s } { P _ s } \ left ( \ frac { P _ 1 ^ 2 - P _ 2 ^ 2} { L \ cdot { SG } ^ { 0.8587 } \ cdot T _ { avg } } \ right ) ^ { 0.538 } D ^ { 2.69} Parameters SG : float Specific gravity of fluid with respect to air at the reference temperature and pressure ` Ts ` and ` Ps ` , [ - ] Tavg : float Average temperature of the fluid in the pipeline , [ K ] L : float , optional Length of pipe , [ m ] D : float , optional Diameter of pipe , [ m ] P1 : float , optional Inlet pressure to pipe , [ Pa ] P2 : float , optional Outlet pressure from pipe , [ Pa ] Q : float , optional Flow rate of gas through pipe , [ m ^ 3 / s ] Ts : float , optional Reference temperature for the specific gravity of the gas , [ K ] Ps : float , optional Reference pressure for the specific gravity of the gas , [ Pa ] Zavg : float , optional Average compressibility factor for gas , [ - ] E : float , optional Pipeline efficiency , a correction factor between 0 and 1 Returns Q , P1 , P2 , D , or L : float The missing input which was solved for [ base SI ] Notes This model is also presented in [ 1 ] _ with a leading constant of 2.827, the same exponents as used here , units of mm ( diameter ) , kPa , km ( length ) , and flow in m ^ 3 / hour . This model is shown in base SI units in [ 2 ] _ , and with a leading constant of 94.2565 , a diameter power of 2.6911 , main group power of 0.5382 and a specific gravity power of 0.858 . The difference is very small . Examples > > > Fritzsche ( D = 0.340 , P1 = 90E5 , P2 = 20E5 , L = 160E3 , SG = 0.693 , Tavg = 277.15) 39.421535157535565 References . . [ 1 ] Menon , E . Shashi . Gas Pipeline Hydraulics . 1st edition . Boca Raton , FL : CRC Press , 2005. . . [ 2 ] Coelho , Paulo M . , and Carlos Pinho . " Considerations about Equations for Steady State Flow in Natural Gas Pipelines . " Journal of the Brazilian Society of Mechanical Sciences and Engineering 29 , no . 3 ( September 2007 ) : 262-73 . doi : 10.1590 / S1678-58782007000300005.'''
# Rational ( ' 2.827E - 3 ' ) / ( 3600*24 ) * ( 1000 ) * * Rational ( ' 2.69 ' ) * ( 1000 ) * * Rational ( ' 0.538 ' ) * 1000 / ( 1000 * * 2 ) * * Rational ( ' 0.538 ' ) c5 = 93.50009798751128188757518688244137811221 # 14135*10 * * ( 57/125 ) / 432 c2 = 0.8587 c3 = 0.538 c4 = 2.69 if Q is None and ( None not in [ L , D , P1 , P2 ] ) : return c5 * E * ( Ts / Ps ) * ( ( P1 ** 2 - P2 ** 2 ) / ( SG ** c2 * Tavg * L * Zavg ) ) ** c3 * D ** c4 elif D is None and ( None not in [ L , Q , P1 , P2 ] ) : return ( Ps * Q * ( SG ** ( - c2 ) * ( P1 ** 2 - P2 ** 2 ) / ( L * Tavg * Zavg ) ) ** ( - c3 ) / ( E * Ts * c5 ) ) ** ( 1. / c4 ) elif P1 is None and ( None not in [ L , Q , D , P2 ] ) : return ( L * SG ** c2 * Tavg * Zavg * ( D ** ( - c4 ) * Ps * Q / ( E * Ts * c5 ) ) ** ( 1. / c3 ) + P2 ** 2 ) ** 0.5 elif P2 is None and ( None not in [ L , Q , D , P1 ] ) : return ( - L * SG ** c2 * Tavg * Zavg * ( D ** ( - c4 ) * Ps * Q / ( E * Ts * c5 ) ) ** ( 1. / c3 ) + P1 ** 2 ) ** 0.5 elif L is None and ( None not in [ P2 , Q , D , P1 ] ) : return SG ** ( - c2 ) * ( D ** ( - c4 ) * Ps * Q / ( E * Ts * c5 ) ) ** ( - 1. / c3 ) * ( P1 ** 2 - P2 ** 2 ) / ( Tavg * Zavg ) else : raise Exception ( 'This function solves for either flow, upstream pressure, downstream pressure, diameter, or length; all other inputs must be provided.' )
def _getPowerupInterfaces ( self ) : """Collect powerup interfaces this object declares that it can be installed on ."""
powerupInterfaces = getattr ( self . __class__ , "powerupInterfaces" , ( ) ) pifs = [ ] for x in powerupInterfaces : if isinstance ( x , type ( Interface ) ) : # just an interface pifs . append ( ( x , 0 ) ) else : # an interface and a priority pifs . append ( x ) m = getattr ( self , "__getPowerupInterfaces__" , None ) if m is not None : pifs = m ( pifs ) try : pifs = [ ( i , p ) for ( i , p ) in pifs ] except ValueError : raise ValueError ( "return value from %r.__getPowerupInterfaces__" " not an iterable of 2-tuples" % ( self , ) ) return pifs
def send_ether_over_wpa ( self , pkt , ** kwargs ) : """Send an Ethernet packet using the WPA channel Extra arguments will be ignored , and are just left for compatibility"""
payload = LLC ( ) / SNAP ( ) / pkt [ Ether ] . payload dest = pkt . dst if dest == "ff:ff:ff:ff:ff:ff" : self . send_wpa_to_group ( payload , dest ) else : assert dest == self . client self . send_wpa_to_client ( payload )
def normalized_messages ( self , no_field_name = '_entity' ) : """Return all the error messages as a dictionary"""
if isinstance ( self . messages , dict ) : return self . messages if not self . field_names : return { no_field_name : self . messages } return dict ( ( name , self . messages ) for name in self . field_names )
def as_dict ( self , join = '.' ) : """Returns the error as a path to message dictionary . Paths are joined with the ` ` join ` ` string ."""
if self . path : path = [ str ( node ) for node in self . path ] else : path = '' return { join . join ( path ) : self . message }
def destroy ( self , request , pk = None ) : '''For DELETE actions , actually deactivate the user , don ' t delete .'''
user = self . get_object ( ) user . is_active = False user . save ( ) return Response ( status = status . HTTP_204_NO_CONTENT )
def ytickangle ( self , angle , index = 1 ) : """Set the angle of the y - axis tick labels . Parameters value : int Angle in degrees index : int , optional Y - axis index Returns Chart"""
self . layout [ 'yaxis' + str ( index ) ] [ 'tickangle' ] = angle return self
def make_response ( status , headers , payload , environ ) : """This function generates an appropriate response object for this async mode ."""
return Response ( body = payload , status = int ( status . split ( ) [ 0 ] ) , headers = headers )
def is_transport_reaction_formulae ( rxn ) : """Return boolean if a reaction is a transport reaction ( from formulae ) . Parameters rxn : cobra . Reaction The metabolic reaction under investigation ."""
# Collecting criteria to classify transporters by . rxn_reactants = set ( [ met . formula for met in rxn . reactants ] ) rxn_products = set ( [ met . formula for met in rxn . products ] ) # Looking for formulas that stay the same on both side of the reaction . transported_mets = [ formula for formula in rxn_reactants if formula in rxn_products ] # Collect information on the elemental differences between # compartments in the reaction . delta_dicts = find_transported_elements ( rxn ) non_zero_array = [ v for ( k , v ) in iteritems ( delta_dicts ) if v != 0 ] # Excluding reactions such as oxidoreductases where no net # transport of Hydrogen is occurring , but rather just an exchange of # electrons or charges effecting a change in protonation . if set ( transported_mets ) != set ( 'H' ) and list ( delta_dicts . keys ( ) ) == [ 'H' ] : pass # All other reactions for which the amount of transported elements is # not zero , which are not part of the model ' s exchange nor # biomass reactions , are defined as transport reactions . # This includes reactions where the transported metabolite reacts with # a carrier molecule . elif sum ( non_zero_array ) : return True
def get_x ( self , var , coords = None ) : """Get the centers of the triangles in the x - dimension Parameters % ( CFDecoder . get _ y . parameters ) s Returns % ( CFDecoder . get _ y . returns ) s"""
if coords is None : coords = self . ds . coords # first we try the super class ret = super ( UGridDecoder , self ) . get_x ( var , coords ) # but if that doesn ' t work because we get the variable name in the # dimension of ` var ` , we use the means of the triangles if ret is None or ret . name in var . dims : bounds = self . get_cell_node_coord ( var , axis = 'x' , coords = coords ) if bounds is not None : centers = bounds . mean ( axis = - 1 ) x = self . get_nodes ( self . get_mesh ( var , coords ) , coords ) [ 0 ] try : cls = xr . IndexVariable except AttributeError : # xarray < 0.9 cls = xr . Coordinate return cls ( x . name , centers , attrs = x . attrs . copy ( ) )
def nodes_to_dict_of_dataframes ( grid , nodes , lv_transformer = True ) : """Creates dictionary of dataframes containing grid Parameters grid : ding0 . Network nodes : list of ding0 grid components objects Nodes of the grid graph lv _ transformer : bool , True Toggle transformer representation in power flow analysis Returns : components : dict of pandas . DataFrame DataFrames contain components attributes . Dict is keyed by components type components _ data : dict of pandas . DataFrame DataFrame containing components time - varying data"""
generator_instances = [ MVStationDing0 , GeneratorDing0 ] # TODO : MVStationDing0 has a slack generator cos_phi_load = cfg_ding0 . get ( 'assumptions' , 'cos_phi_load' ) cos_phi_feedin = cfg_ding0 . get ( 'assumptions' , 'cos_phi_gen' ) srid = int ( cfg_ding0 . get ( 'geo' , 'srid' ) ) load_in_generation_case = cfg_ding0 . get ( 'assumptions' , 'load_in_generation_case' ) generation_in_load_case = cfg_ding0 . get ( 'assumptions' , 'generation_in_load_case' ) Q_factor_load = tan ( acos ( cos_phi_load ) ) Q_factor_generation = tan ( acos ( cos_phi_feedin ) ) voltage_set_slack = cfg_ding0 . get ( "mv_routing_tech_constraints" , "mv_station_v_level_operation" ) kw2mw = 1e-3 # define dictionaries buses = { 'bus_id' : [ ] , 'v_nom' : [ ] , 'geom' : [ ] , 'grid_id' : [ ] } bus_v_mag_set = { 'bus_id' : [ ] , 'temp_id' : [ ] , 'v_mag_pu_set' : [ ] , 'grid_id' : [ ] } generator = { 'generator_id' : [ ] , 'bus' : [ ] , 'control' : [ ] , 'grid_id' : [ ] , 'p_nom' : [ ] } generator_pq_set = { 'generator_id' : [ ] , 'temp_id' : [ ] , 'p_set' : [ ] , 'grid_id' : [ ] , 'q_set' : [ ] } load = { 'load_id' : [ ] , 'bus' : [ ] , 'grid_id' : [ ] } load_pq_set = { 'load_id' : [ ] , 'temp_id' : [ ] , 'p_set' : [ ] , 'grid_id' : [ ] , 'q_set' : [ ] } # # TODO : consider other implications of ` lv _ transformer is True ` # if lv _ transformer is True : # bus _ instances . append ( Transformer ) # # TODO : only for debugging , remove afterwards # import csv # nodeslist = sorted ( [ node . _ _ repr _ _ ( ) for node in nodes # if node not in grid . graph _ isolated _ nodes ( ) ] ) # with open ( ' / home / guido / ding0 _ debug / nodes _ via _ dataframe . csv ' , ' w ' , newline = ' ' ) as csvfile : # writer = csv . writer ( csvfile , delimiter = ' \ n ' ) # writer . writerow ( nodeslist ) for node in nodes : if node not in grid . graph_isolated_nodes ( ) : # buses only if isinstance ( node , MVCableDistributorDing0 ) : buses [ 'bus_id' ] . append ( node . pypsa_id ) buses [ 'v_nom' ] . append ( grid . v_level ) buses [ 'geom' ] . append ( from_shape ( node . geo_data , srid = srid ) ) buses [ 'grid_id' ] . append ( grid . id_db ) bus_v_mag_set [ 'bus_id' ] . append ( node . pypsa_id ) bus_v_mag_set [ 'temp_id' ] . append ( 1 ) bus_v_mag_set [ 'v_mag_pu_set' ] . append ( [ 1 , 1 ] ) bus_v_mag_set [ 'grid_id' ] . append ( grid . id_db ) # bus + generator elif isinstance ( node , tuple ( generator_instances ) ) : # slack generator if isinstance ( node , MVStationDing0 ) : logger . info ( 'Only MV side bus of MVStation will be added.' ) generator [ 'generator_id' ] . append ( '_' . join ( [ 'MV' , str ( grid . id_db ) , 'slack' ] ) ) generator [ 'control' ] . append ( 'Slack' ) generator [ 'p_nom' ] . append ( 0 ) bus_v_mag_set [ 'v_mag_pu_set' ] . append ( [ voltage_set_slack , voltage_set_slack ] ) # other generators if isinstance ( node , GeneratorDing0 ) : generator [ 'generator_id' ] . append ( '_' . join ( [ 'MV' , str ( grid . id_db ) , 'gen' , str ( node . id_db ) ] ) ) generator [ 'control' ] . append ( 'PQ' ) generator [ 'p_nom' ] . append ( node . capacity * node . capacity_factor ) generator_pq_set [ 'generator_id' ] . append ( '_' . join ( [ 'MV' , str ( grid . id_db ) , 'gen' , str ( node . id_db ) ] ) ) generator_pq_set [ 'temp_id' ] . append ( 1 ) generator_pq_set [ 'p_set' ] . append ( [ node . capacity * node . capacity_factor * kw2mw * generation_in_load_case , node . capacity * node . capacity_factor * kw2mw ] ) generator_pq_set [ 'q_set' ] . append ( [ node . capacity * node . capacity_factor * kw2mw * Q_factor_generation * generation_in_load_case , node . capacity * node . capacity_factor * kw2mw * Q_factor_generation ] ) generator_pq_set [ 'grid_id' ] . append ( grid . id_db ) bus_v_mag_set [ 'v_mag_pu_set' ] . append ( [ 1 , 1 ] ) buses [ 'bus_id' ] . append ( node . pypsa_id ) buses [ 'v_nom' ] . append ( grid . v_level ) buses [ 'geom' ] . append ( from_shape ( node . geo_data , srid = srid ) ) buses [ 'grid_id' ] . append ( grid . id_db ) bus_v_mag_set [ 'bus_id' ] . append ( node . pypsa_id ) bus_v_mag_set [ 'temp_id' ] . append ( 1 ) bus_v_mag_set [ 'grid_id' ] . append ( grid . id_db ) generator [ 'grid_id' ] . append ( grid . id_db ) generator [ 'bus' ] . append ( node . pypsa_id ) # aggregated load at hv / mv substation elif isinstance ( node , LVLoadAreaCentreDing0 ) : load [ 'load_id' ] . append ( node . pypsa_id ) load [ 'bus' ] . append ( '_' . join ( [ 'HV' , str ( grid . id_db ) , 'trd' ] ) ) load [ 'grid_id' ] . append ( grid . id_db ) load_pq_set [ 'load_id' ] . append ( node . pypsa_id ) load_pq_set [ 'temp_id' ] . append ( 1 ) load_pq_set [ 'p_set' ] . append ( [ node . lv_load_area . peak_load * kw2mw , node . lv_load_area . peak_load * kw2mw * load_in_generation_case ] ) load_pq_set [ 'q_set' ] . append ( [ node . lv_load_area . peak_load * kw2mw * Q_factor_load , node . lv_load_area . peak_load * kw2mw * Q_factor_load * load_in_generation_case ] ) load_pq_set [ 'grid_id' ] . append ( grid . id_db ) # generator representing generation capacity of aggregate LA # analogously to load , generation is connected directly to # HV - MV substation generator [ 'generator_id' ] . append ( '_' . join ( [ 'MV' , str ( grid . id_db ) , 'lcg' , str ( node . id_db ) ] ) ) generator [ 'control' ] . append ( 'PQ' ) generator [ 'p_nom' ] . append ( node . lv_load_area . peak_generation ) generator [ 'grid_id' ] . append ( grid . id_db ) generator [ 'bus' ] . append ( '_' . join ( [ 'HV' , str ( grid . id_db ) , 'trd' ] ) ) generator_pq_set [ 'generator_id' ] . append ( '_' . join ( [ 'MV' , str ( grid . id_db ) , 'lcg' , str ( node . id_db ) ] ) ) generator_pq_set [ 'temp_id' ] . append ( 1 ) generator_pq_set [ 'p_set' ] . append ( [ node . lv_load_area . peak_generation * kw2mw * generation_in_load_case , node . lv_load_area . peak_generation * kw2mw ] ) generator_pq_set [ 'q_set' ] . append ( [ node . lv_load_area . peak_generation * kw2mw * Q_factor_generation * generation_in_load_case , node . lv_load_area . peak_generation * kw2mw * Q_factor_generation ] ) generator_pq_set [ 'grid_id' ] . append ( grid . id_db ) # bus + aggregate load of lv grids ( at mv / ls substation ) elif isinstance ( node , LVStationDing0 ) : # Aggregated load representing load in LV grid load [ 'load_id' ] . append ( '_' . join ( [ 'MV' , str ( grid . id_db ) , 'loa' , str ( node . id_db ) ] ) ) load [ 'bus' ] . append ( node . pypsa_id ) load [ 'grid_id' ] . append ( grid . id_db ) load_pq_set [ 'load_id' ] . append ( '_' . join ( [ 'MV' , str ( grid . id_db ) , 'loa' , str ( node . id_db ) ] ) ) load_pq_set [ 'temp_id' ] . append ( 1 ) load_pq_set [ 'p_set' ] . append ( [ node . peak_load * kw2mw , node . peak_load * kw2mw * load_in_generation_case ] ) load_pq_set [ 'q_set' ] . append ( [ node . peak_load * kw2mw * Q_factor_load , node . peak_load * kw2mw * Q_factor_load * load_in_generation_case ] ) load_pq_set [ 'grid_id' ] . append ( grid . id_db ) # bus at primary MV - LV transformer side buses [ 'bus_id' ] . append ( node . pypsa_id ) buses [ 'v_nom' ] . append ( grid . v_level ) buses [ 'geom' ] . append ( from_shape ( node . geo_data , srid = srid ) ) buses [ 'grid_id' ] . append ( grid . id_db ) bus_v_mag_set [ 'bus_id' ] . append ( node . pypsa_id ) bus_v_mag_set [ 'temp_id' ] . append ( 1 ) bus_v_mag_set [ 'v_mag_pu_set' ] . append ( [ 1 , 1 ] ) bus_v_mag_set [ 'grid_id' ] . append ( grid . id_db ) # generator representing generation capacity in LV grid generator [ 'generator_id' ] . append ( '_' . join ( [ 'MV' , str ( grid . id_db ) , 'gen' , str ( node . id_db ) ] ) ) generator [ 'control' ] . append ( 'PQ' ) generator [ 'p_nom' ] . append ( node . peak_generation ) generator [ 'grid_id' ] . append ( grid . id_db ) generator [ 'bus' ] . append ( node . pypsa_id ) generator_pq_set [ 'generator_id' ] . append ( '_' . join ( [ 'MV' , str ( grid . id_db ) , 'gen' , str ( node . id_db ) ] ) ) generator_pq_set [ 'temp_id' ] . append ( 1 ) generator_pq_set [ 'p_set' ] . append ( [ node . peak_generation * kw2mw * generation_in_load_case , node . peak_generation * kw2mw ] ) generator_pq_set [ 'q_set' ] . append ( [ node . peak_generation * kw2mw * Q_factor_generation * generation_in_load_case , node . peak_generation * kw2mw * Q_factor_generation ] ) generator_pq_set [ 'grid_id' ] . append ( grid . id_db ) elif isinstance ( node , CircuitBreakerDing0 ) : # TODO : remove this elif - case if CircuitBreaker are removed from graph continue else : raise TypeError ( "Node of type" , node , "cannot be handled here" ) else : if not isinstance ( node , CircuitBreakerDing0 ) : add_info = "LA is aggr. {0}" . format ( node . lv_load_area . is_aggregated ) else : add_info = "" logger . warning ( "Node {0} is not connected to the graph and will " "be omitted in power flow analysis. {1}" . format ( node , add_info ) ) components = { 'Bus' : DataFrame ( buses ) . set_index ( 'bus_id' ) , 'Generator' : DataFrame ( generator ) . set_index ( 'generator_id' ) , 'Load' : DataFrame ( load ) . set_index ( 'load_id' ) } components_data = { 'Bus' : DataFrame ( bus_v_mag_set ) . set_index ( 'bus_id' ) , 'Generator' : DataFrame ( generator_pq_set ) . set_index ( 'generator_id' ) , 'Load' : DataFrame ( load_pq_set ) . set_index ( 'load_id' ) } # with open ( ' / home / guido / ding0 _ debug / number _ of _ nodes _ buses . csv ' , ' a ' ) as csvfile : # csvfile . write ( ' , ' . join ( [ ' \ n ' , str ( len ( nodes ) ) , str ( len ( grid . graph _ isolated _ nodes ( ) ) ) , str ( len ( components [ ' Bus ' ] ) ) ] ) ) return components , components_data
def is_domain_class_member_attribute ( ent , attr_name ) : """Checks if the given attribute name is a entity attribute of the given registered resource ."""
attr = get_domain_class_attribute ( ent , attr_name ) return attr . kind == RESOURCE_ATTRIBUTE_KINDS . MEMBER
def coords_on_grid ( self , x , y ) : """Snap coordinates on the grid with integer coordinates"""
if isinstance ( x , float ) : x = int ( self . _round ( x ) ) if isinstance ( y , float ) : y = int ( self . _round ( y ) ) if not self . _y_coord_down : y = self . _extents - y return x , y
def colorize ( text , ansi = True ) : """If the client wants ansi , replace the tokens with ansi sequences - - otherwise , simply strip them out ."""
if ansi : text = text . replace ( '^^' , '\x00' ) for token , code in _ANSI_CODES : text = text . replace ( token , code ) text = text . replace ( '\x00' , '^' ) else : text = strip_caret_codes ( text ) return text
def rename ( dct , mapping ) : """Rename the keys of a dictionary with the given mapping > > > rename ( { " a " : 1 , " BBB " : 2 } , { " a " : " AAA " } ) { ' AAA ' : 1 , ' BBB ' : 2}"""
def _block ( memo , key ) : if key in dct : memo [ mapping [ key ] ] = dct [ key ] return memo else : return memo return reduce ( _block , mapping , omit ( dct , * mapping . keys ( ) ) )
def get_lowest_probable_prepared_certificate_in_view ( self , view_no ) -> Optional [ int ] : """Return lowest pp _ seq _ no of the view for which can be prepared but choose from unprocessed PRE - PREPAREs and PREPAREs ."""
# TODO : Naive implementation , dont need to iterate over the complete # data structures , fix this later seq_no_pp = SortedList ( ) # pp _ seq _ no of PRE - PREPAREs # pp _ seq _ no of PREPAREs with count of PREPAREs for each seq_no_p = set ( ) for ( v , p ) in self . prePreparesPendingPrevPP : if v == view_no : seq_no_pp . add ( p ) if v > view_no : break for ( v , p ) , pr in self . preparesWaitingForPrePrepare . items ( ) : if v == view_no and len ( pr ) >= self . quorums . prepare . value : seq_no_p . add ( p ) for n in seq_no_pp : if n in seq_no_p : return n return None
def average_series ( self , * args , ** kwargs ) -> InfoArray : """Average the actual time series of the | Variable | object for all time points . Method | IOSequence . average _ series | works similarly as method | Variable . average _ values | of class | Variable | , from which we borrow some examples . However , firstly , we have to prepare a | Timegrids | object to define the | IOSequence . series | length : > > > from hydpy import pub > > > pub . timegrids = ' 2000-01-01 ' , ' 2000-01-04 ' , ' 1d ' As shown for method | Variable . average _ values | , for 0 - dimensional | IOSequence | objects the result of | IOSequence . average _ series | equals | IOSequence . series | itself : > > > from hydpy . core . sequencetools import IOSequence > > > class SoilMoisture ( IOSequence ) : . . . NDIM = 0 > > > sm = SoilMoisture ( None ) > > > sm . activate _ ram ( ) > > > import numpy > > > sm . series = numpy . array ( [ 190.0 , 200.0 , 210.0 ] ) > > > sm . average _ series ( ) InfoArray ( [ 190 . , 200 . , 210 . ] ) For | IOSequence | objects with an increased dimensionality , a weighting parameter is required , again : > > > SoilMoisture . NDIM = 1 > > > sm . shape = 3 > > > sm . activate _ ram ( ) > > > sm . series = ( . . . [ 190.0 , 390.0 , 490.0 ] , . . . [ 200.0 , 400.0 , 500.0 ] , . . . [ 210.0 , 410.0 , 510.0 ] ) > > > from hydpy . core . parametertools import Parameter > > > class Area ( Parameter ) : . . . NDIM = 1 . . . shape = ( 3 , ) . . . value = numpy . array ( [ 1.0 , 1.0 , 2.0 ] ) > > > area = Area ( None ) > > > SoilMoisture . refweights = property ( lambda self : area ) > > > sm . average _ series ( ) InfoArray ( [ 390 . , 400 . , 410 . ] ) The documentation on method | Variable . average _ values | provides many examples on how to use different masks in different ways . Here we restrict ourselves to the first example , where a new mask enforces that | IOSequence . average _ series | takes only the first two columns of the ` series ` into account : > > > from hydpy . core . masktools import DefaultMask > > > class Soil ( DefaultMask ) : . . . @ classmethod . . . def new ( cls , variable , * * kwargs ) : . . . return cls . array2mask ( [ True , True , False ] ) > > > SoilMoisture . mask = Soil ( ) > > > sm . average _ series ( ) InfoArray ( [ 290 . , 300 . , 310 . ] )"""
try : if not self . NDIM : array = self . series else : mask = self . get_submask ( * args , ** kwargs ) if numpy . any ( mask ) : weights = self . refweights [ mask ] weights /= numpy . sum ( weights ) series = self . series [ : , mask ] axes = tuple ( range ( 1 , self . NDIM + 1 ) ) array = numpy . sum ( weights * series , axis = axes ) else : return numpy . nan return InfoArray ( array , info = { 'type' : 'mean' } ) except BaseException : objecttools . augment_excmessage ( 'While trying to calculate the mean value of ' 'the internal time series of sequence %s' % objecttools . devicephrase ( self ) )
async def terminateInstance ( self , * args , ** kwargs ) : """Terminate an instance Terminate an instance in a specified region This method is ` ` experimental ` `"""
return await self . _makeApiCall ( self . funcinfo [ "terminateInstance" ] , * args , ** kwargs )
def install ( self , package , force = False , upgrade = False , options = None ) : """Installs the given package into this virtual environment , as specified in pip ' s package syntax or a tuple of ( ' name ' , ' ver ' ) , only if it is not already installed . Some valid examples : ' Django ' ' Django = = 1.5' ( ' Django ' , ' 1.5 ' ) ' - r requirements . txt ' If ` force ` is True , force an installation . If ` upgrade ` is True , attempt to upgrade the package in question . If both ` force ` and ` upgrade ` are True , reinstall the package and its dependencies . The ` options ` is a list of strings that can be used to pass to pip ."""
if self . readonly : raise VirtualenvReadonlyException ( ) if options is None : options = [ ] if isinstance ( package , tuple ) : package = '==' . join ( package ) if package . startswith ( ( '-e' , '-r' ) ) : package_args = package . split ( ) else : package_args = [ package ] if not ( force or upgrade ) and ( package_args [ 0 ] != '-r' and self . is_installed ( package_args [ - 1 ] ) ) : self . _write_to_log ( '%s is already installed, skipping (use force=True to override)' % package_args [ - 1 ] ) return if not isinstance ( options , list ) : raise ValueError ( "Options must be a list of strings." ) if upgrade : options += [ '--upgrade' ] if force : options += [ '--force-reinstall' ] elif force : options += [ '--ignore-installed' ] try : self . _execute_pip ( [ 'install' ] + package_args + options ) except subprocess . CalledProcessError as e : raise PackageInstallationException ( ( e . returncode , e . output , package ) )
def input_files_to_stage ( self ) : """Return a list of the input files needed by this link . For ` Link ` sub - classes this will return the union of all the input files of each internal ` Link ` . That is to say this will include files produced by one ` Link ` in a ` Chain ` and used as input to another ` Link ` in the ` Chain `"""
ret_list = [ ] for key , val in self . file_dict . items ( ) : # For input files we only want files that were marked as input if val & FileFlags . in_stage_mask == FileFlags . in_stage_mask : ret_list . append ( key ) return ret_list
def oei ( cn , ns = None , lo = None , di = None , iq = None , ico = None , pl = None , fl = None , fs = None , ot = None , coe = None , moc = None ) : # pylint : disable = too - many - arguments , redefined - outer - name """This function is a wrapper for : meth : ` ~ pywbem . WBEMConnection . OpenEnumerateInstances ` . Open an enumeration session to enumerate the instances of a class ( including instances of its subclasses ) in a namespace . Use the : func : ` ~ wbemcli . piwp ` function to retrieve the next set of instances or the : func : ` ~ wbcmeli . ce ` function to close the enumeration session before it is complete . Parameters : cn ( : term : ` string ` or : class : ` ~ pywbem . CIMClassName ` ) : Name of the class to be enumerated ( case independent ) . If specified as a ` CIMClassName ` object , its ` host ` attribute will be ignored . ns ( : term : ` string ` ) : Name of the CIM namespace to be used ( case independent ) . If ` None ` , defaults to the namespace of the ` cn ` parameter if specified as a ` CIMClassName ` , or to the default namespace of the connection . lo ( : class : ` py : bool ` ) : LocalOnly flag : Exclude inherited properties . ` None ` will cause the server default of ` True ` to be used . Deprecated in : term : ` DSP0200 ` : WBEM server implementations for ` True ` may vary ; this parameter should be set to ` False ` by the caller . di ( : class : ` py : bool ` ) : DeepInheritance flag : Include properties added by subclasses . ` None ` will cause the server default of ` True ` to be used . iq ( : class : ` py : bool ` ) : IncludeQualifiers flag : Include qualifiers . ` None ` will cause the server default of ` False ` to be used . Deprecated in : term : ` DSP0200 ` : Clients cannot rely on qualifiers to be returned in this operation . ico ( : class : ` py : bool ` ) : IncludeClassOrigin flag : Include class origin information for the properties in the retrieved instances . ` None ` will cause the server default of ` False ` to be used . Deprecated in : term : ` DSP0200 ` : WBEM servers may either implement this parameter as specified , or may treat any specified value as ` False ` . pl ( : term : ` string ` or : term : ` py : iterable ` of : term : ` string ` ) : PropertyList : Names of properties to be included ( if not otherwise excluded ) . An empty iterable indicates to include no properties . If ` None ` , all properties will be included . fl ( : term : ` string ` ) : Filter query language to be used for the filter defined in the ` fs ` parameter . The DMTF - defined Filter Query Language ( see : term : ` DSP0212 ` ) is specified as " DMTF : FQL " . ` None ` means that no such filtering is peformed . fs ( : term : ` string ` ) : Filter to apply to objects to be returned . Based on filter query language defined by ` fl ` parameter . ` None ` means that no such filtering is peformed . ot ( : class : ` ~ pywbem . Uint32 ` ) : Operation timeout in seconds . This is the minimum time the WBEM server must keep the enumeration session open between requests on that session . A value of 0 indicates that the server should never time out . The server may reject the proposed value . ` None ` will cause the server to use its default timeout . coe ( : class : ` py : bool ` ) : Continue on error flag . ` None ` will cause the server to use its default of ` False ` . moc ( : class : ` ~ pywbem . Uint32 ` ) : Maximum number of objects to return for this operation . ` None ` will cause the server to use its default of 0. Returns : A : func : ` ~ py : collections . namedtuple ` object containing the following named items : * * * instances * * ( list of : class : ` ~ pywbem . CIMInstance ` ) : The retrieved instances . * * * eos * * ( : class : ` py : bool ` ) : ` True ` if the enumeration session is exhausted after this operation . Otherwise ` eos ` is ` False ` and the ` context ` item is the context object for the next operation on the enumeration session . * * * context * * ( : func : ` py : tuple ` of server _ context , namespace ) : A context object identifying the open enumeration session , including its current enumeration state , and the namespace . This object must be supplied with the next pull or close operation for this enumeration session ."""
return CONN . OpenEnumerateInstances ( cn , ns , LocalOnly = lo , DeepInheritance = di , IncludeQualifiers = iq , IncludeClassOrigin = ico , PropertyList = pl , FilterQueryLanguage = fl , FilterQuery = fs , OperationTimeout = ot , ContinueOnError = coe , MaxObjectCount = moc )
def WalkChildren ( elem ) : """Walk the XML tree of children below elem , returning each in order ."""
for child in elem . childNodes : yield child for elem in WalkChildren ( child ) : yield elem