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def formatted_param_type ( ptype ) : """Return the short name for a type . Special treatment for by - name and var args"""
pt_name = ptype [ "name" ] if pt_name . startswith ( "<byname>" ) : pt_name = pt_name . replace ( "<byname>[" , "=> " ) [ : - 1 ] elif pt_name . startswith ( "<repeated>" ) : pt_name = pt_name . replace ( "<repeated>[" , "" ) [ : - 1 ] + "*" return pt_name
def do_media ( self , args ) : """Media management command demonstrates multiple layers of sub - commands being handled by AutoCompleter"""
func = getattr ( args , 'func' , None ) if func is not None : # Call whatever subcommand function was selected func ( self , args ) else : # No subcommand was provided , so call help self . do_help ( 'media' )
def __handle_changed_state ( self , state ) : """we need to pack a struct with the following five numbers : tv _ sec , tv _ usec , ev _ type , code , value then write it using _ _ write _ to _ character _ device seconds , mircroseconds , ev _ type , code , value time we just use now ev _ type we look up code we look up value is 0 or 1 for the buttons axis value is maybe the same as Linux ? Hope so !"""
timeval = self . __get_timeval ( ) events = self . __get_button_events ( state , timeval ) events . extend ( self . __get_axis_events ( state , timeval ) ) if events : self . __write_to_character_device ( events , timeval )
def bind ( cls , app , * paths , methods = None , name = None , view = None ) : """Connect to admin interface and application ."""
# Register self in admin if view is None : app . ps . admin . register ( cls ) if not paths : paths = ( '%s/%s' % ( app . ps . admin . cfg . prefix , name or cls . name ) , ) cls . url = paths [ 0 ] return super ( AdminHandler , cls ) . bind ( app , * paths , methods = methods , name = name , view = view )
def trial ( path = TESTS_PATH , coverage = False ) : """Run tests using trial"""
args = [ 'trial' ] if coverage : args . append ( '--coverage' ) args . append ( path ) print args local ( ' ' . join ( args ) )
def to_source ( node , indent_with = ' ' * 4 ) : """This function can convert a node tree back into python sourcecode . This is useful for debugging purposes , especially if you ' re dealing with custom asts not generated by python itself . It could be that the sourcecode is evaluable when the AST itself is not compilable / evaluable . The reason for this is that the AST contains some more data than regular sourcecode does , which is dropped during conversion . Each level of indentation is replaced with ` indent _ with ` . Per default this parameter is equal to four spaces as suggested by PEP 8 , but it might be adjusted to match the application ' s styleguide ."""
generator = SourceGenerator ( indent_with ) generator . visit ( node ) return '' . join ( generator . result )
def _set_objective_bank_view ( self , session ) : """Sets the underlying objective _ bank view to match current view"""
if self . _objective_bank_view == FEDERATED : try : session . use_federated_objective_bank_view ( ) except AttributeError : pass else : try : session . use_isolated_objective_bank_view ( ) except AttributeError : pass
def _align_series ( self , indexer , ser , multiindex_indexer = False ) : """Parameters indexer : tuple , slice , scalar The indexer used to get the locations that will be set to ` ser ` ser : pd . Series The values to assign to the locations specified by ` indexer ` multiindex _ indexer : boolean , optional Defaults to False . Should be set to True if ` indexer ` was from a ` pd . MultiIndex ` , to avoid unnecessary broadcasting . Returns : ` np . array ` of ` ser ` broadcast to the appropriate shape for assignment to the locations selected by ` indexer `"""
if isinstance ( indexer , ( slice , np . ndarray , list , Index ) ) : indexer = tuple ( [ indexer ] ) if isinstance ( indexer , tuple ) : # flatten np . ndarray indexers def ravel ( i ) : return i . ravel ( ) if isinstance ( i , np . ndarray ) else i indexer = tuple ( map ( ravel , indexer ) ) aligners = [ not com . is_null_slice ( idx ) for idx in indexer ] sum_aligners = sum ( aligners ) single_aligner = sum_aligners == 1 is_frame = self . obj . ndim == 2 is_panel = self . obj . ndim >= 3 obj = self . obj # are we a single alignable value on a non - primary # dim ( e . g . panel : 1,2 , or frame : 0 ) ? # hence need to align to a single axis dimension # rather that find all valid dims # frame if is_frame : single_aligner = single_aligner and aligners [ 0 ] # panel elif is_panel : single_aligner = ( single_aligner and ( aligners [ 1 ] or aligners [ 2 ] ) ) # we have a frame , with multiple indexers on both axes ; and a # series , so need to broadcast ( see GH5206) if ( sum_aligners == self . ndim and all ( is_sequence ( _ ) for _ in indexer ) ) : ser = ser . reindex ( obj . axes [ 0 ] [ indexer [ 0 ] ] , copy = True ) . _values # single indexer if len ( indexer ) > 1 and not multiindex_indexer : len_indexer = len ( indexer [ 1 ] ) ser = np . tile ( ser , len_indexer ) . reshape ( len_indexer , - 1 ) . T return ser for i , idx in enumerate ( indexer ) : ax = obj . axes [ i ] # multiple aligners ( or null slices ) if is_sequence ( idx ) or isinstance ( idx , slice ) : if single_aligner and com . is_null_slice ( idx ) : continue new_ix = ax [ idx ] if not is_list_like_indexer ( new_ix ) : new_ix = Index ( [ new_ix ] ) else : new_ix = Index ( new_ix ) if ser . index . equals ( new_ix ) or not len ( new_ix ) : return ser . _values . copy ( ) return ser . reindex ( new_ix ) . _values # 2 dims elif single_aligner and is_frame : # reindex along index ax = self . obj . axes [ 1 ] if ser . index . equals ( ax ) or not len ( ax ) : return ser . _values . copy ( ) return ser . reindex ( ax ) . _values # > 2 dims elif single_aligner : broadcast = [ ] for n , labels in enumerate ( self . obj . _get_plane_axes ( i ) ) : # reindex along the matching dimensions if len ( labels & ser . index ) : ser = ser . reindex ( labels ) else : broadcast . append ( ( n , len ( labels ) ) ) # broadcast along other dims ser = ser . _values . copy ( ) for ( axis , l ) in broadcast : shape = [ - 1 ] * ( len ( broadcast ) + 1 ) shape [ axis ] = l ser = np . tile ( ser , l ) . reshape ( shape ) if self . obj . ndim == 3 : ser = ser . T return ser elif is_scalar ( indexer ) : ax = self . obj . _get_axis ( 1 ) if ser . index . equals ( ax ) : return ser . _values . copy ( ) return ser . reindex ( ax ) . _values raise ValueError ( 'Incompatible indexer with Series' )
def master_using_raster ( mdf , raster , endpoint = False ) : """get single master based on the raster Parameters mdf : asammdf . MDF measurement object raster : float new raster endpoint = False : bool include maximum time stamp in the new master Returns master : np . array new master"""
if not raster : master = np . array ( [ ] , dtype = '<f8' ) else : t_min = [ ] t_max = [ ] for i , group in enumerate ( mdf . groups ) : cycles_nr = group . channel_group . cycles_nr if cycles_nr : master_min = mdf . get_master ( i , record_offset = 0 , record_count = 1 , ) if len ( master_min ) : t_min . append ( master_min [ 0 ] ) mdf . _master_channel_cache . clear ( ) master_max = mdf . get_master ( i , record_offset = cycles_nr - 1 , record_count = 1 , ) if len ( master_max ) : t_max . append ( master_max [ 0 ] ) mdf . _master_channel_cache . clear ( ) if t_min : t_min = np . amin ( t_min ) t_max = np . amax ( t_max ) num = float ( np . float32 ( ( t_max - t_min ) / raster ) ) if int ( num ) == num : master = np . linspace ( t_min , t_max , int ( num ) + 1 ) else : master = np . arange ( t_min , t_max , raster ) if endpoint : master = np . concatenate ( [ master , [ t_max ] ] ) else : master = np . array ( [ ] , dtype = '<f8' ) return master
def unique_justseen ( iterable , key = None ) : """Yields elements in order , ignoring serial duplicates > > > list ( unique _ justseen ( ' AAAABBBCCDAABBB ' ) ) [ ' A ' , ' B ' , ' C ' , ' D ' , ' A ' , ' B ' ] > > > list ( unique _ justseen ( ' ABBCcAD ' , str . lower ) ) [ ' A ' , ' B ' , ' C ' , ' A ' , ' D ' ]"""
return map ( next , map ( operator . itemgetter ( 1 ) , groupby ( iterable , key ) ) )
def timestep_text ( self ) : """Return a text string representing the timestep of the collection ."""
if self . header . analysis_period . timestep == 1 : return 'Hourly' else : return '{} Minute' . format ( int ( 60 / self . header . analysis_period . timestep ) )
def itersplit_to_fields ( self , _str ) : """Split ( or parse ) repository log output into fields Returns : tuple : self . _ tuple ( * values )"""
if self . preparse : _str = self . preparse ( _str ) _fields = itersplit ( _str , self . fsep ) try : values = ( t [ 1 ] for t in izip_longest ( self . _tuple . _fields , _fields ) ) return self . _tuple ( * values ) except Exception as e : log . error ( self . _tuple ) log . error ( _fields ) log . exception ( e ) raise
async def set ( self , * args , ** kwargs ) : '''Sets the value of the event .'''
return await _maybe_await ( self . event . set ( * args , ** kwargs ) )
def _format_bf ( bf , precision = 3 , trim = '0' ) : """Format BF10 to floating point or scientific notation ."""
if bf >= 1e4 or bf <= 1e-4 : out = np . format_float_scientific ( bf , precision = precision , trim = trim ) else : out = np . format_float_positional ( bf , precision = precision , trim = trim ) return out
def p_instance_bodylist_noname ( self , p ) : 'instance _ bodylist _ noname : instance _ bodylist _ noname COMMA instance _ body _ noname'
p [ 0 ] = p [ 1 ] + ( p [ 3 ] , ) p . set_lineno ( 0 , p . lineno ( 1 ) )
def immediate ( self , name , value ) : """Load something immediately"""
setattr ( self , name , value ) self . _all . add ( name )
def lock_version ( self , service_id , version_number ) : """Locks the specified version ."""
content = self . _fetch ( "/service/%s/version/%d/lock" % ( service_id , version_number ) ) return self . _status ( content )
def mkdir ( name , mode = 0o750 ) : """Implementation of ` ` mkdir - p ` ` : Creates folder with the given ` name ` and the given permissions ( ` mode ` ) * Create missing parents folder * Do nothing if the folder with the given ` name ` already exists * Raise ` OSError ` if there is already a file with the given ` name `"""
if os . path . isdir ( name ) : pass elif os . path . isfile ( name ) : raise OSError ( "A file with the same name as the desired " "dir, '%s', already exists." % name ) else : os . makedirs ( name , mode )
def convert_halo_to_array_form ( halo , ndim ) : """Converts the : samp : ` { halo } ` argument to a : samp : ` ( ndim , 2 ) ` shaped array . : type halo : : samp : ` None ` , : obj : ` int ` , an : samp : ` { ndim } ` length sequence of : samp : ` int ` or : samp : ` ( { ndim } , 2 ) ` shaped array of : samp : ` int ` : param halo : Halo to be converted to : samp : ` ( { ndim } , 2 ) ` shaped array form . : type ndim : : obj : ` int ` : param ndim : Number of dimensions . : rtype : : obj : ` numpy . ndarray ` : return : A : samp : ` ( { ndim } , 2 ) ` shaped array of : obj : ` numpy . int64 ` elements . Examples : : > > > convert _ halo _ to _ array _ form ( halo = 2 , ndim = 4) array ( [ [ 2 , 2 ] , [2 , 2 ] , [2 , 2 ] , [2 , 2 ] ] ) > > > convert _ halo _ to _ array _ form ( halo = [ 0 , 1 , 2 ] , ndim = 3) array ( [ [ 0 , 0 ] , [1 , 1 ] , [2 , 2 ] ] ) > > > convert _ halo _ to _ array _ form ( halo = [ [ 0 , 1 ] , [ 2 , 3 ] , [ 3 , 4 ] ] , ndim = 3) array ( [ [ 0 , 1 ] , [2 , 3 ] , [3 , 4 ] ] )"""
dtyp = _np . int64 if halo is None : halo = _np . zeros ( ( ndim , 2 ) , dtype = dtyp ) elif is_scalar ( halo ) : halo = _np . zeros ( ( ndim , 2 ) , dtype = dtyp ) + halo elif ( ndim == 1 ) and ( _np . array ( halo ) . shape == ( 2 , ) ) : halo = _np . array ( [ halo , ] , copy = True , dtype = dtyp ) elif len ( _np . array ( halo ) . shape ) == 1 : halo = _np . array ( [ halo , halo ] , dtype = dtyp ) . T . copy ( ) else : halo = _np . array ( halo , copy = True , dtype = dtyp ) if halo . shape [ 0 ] != ndim : raise ValueError ( "Got halo.shape=%s, expecting halo.shape=(%s, 2)" % ( halo . shape , ndim ) ) return halo
def ParseSmsRow ( self , parser_mediator , query , row , ** unused_kwargs ) : """Parses an SMS row . Args : parser _ mediator ( ParserMediator ) : mediates interactions between parsers and other components , such as storage and dfvfs . query ( str ) : query that created the row . row ( sqlite3 . Row ) : row ."""
query_hash = hash ( query ) sms_read = self . _GetRowValue ( query_hash , row , 'read' ) sms_type = self . _GetRowValue ( query_hash , row , 'type' ) event_data = AndroidSMSEventData ( ) event_data . address = self . _GetRowValue ( query_hash , row , 'address' ) event_data . body = self . _GetRowValue ( query_hash , row , 'body' ) event_data . offset = self . _GetRowValue ( query_hash , row , 'id' ) event_data . query = query event_data . sms_read = self . SMS_READ . get ( sms_read , 'UNKNOWN' ) event_data . sms_type = self . SMS_TYPE . get ( sms_type , 'UNKNOWN' ) timestamp = self . _GetRowValue ( query_hash , row , 'date' ) date_time = dfdatetime_java_time . JavaTime ( timestamp = timestamp ) event = time_events . DateTimeValuesEvent ( date_time , definitions . TIME_DESCRIPTION_CREATION ) parser_mediator . ProduceEventWithEventData ( event , event_data )
def throughput ( self , points ) : """A setter for the throughput Parameters throughput : sequence The array of throughput points"""
# Test shape if not points . shape == self . wave . shape : raise ValueError ( "Throughput and wavelength must be same shape." ) self . _throughput = points
def account_balance_before ( self ) : """Get the balance of the account associated with this leg before the transaction"""
# TODO : Consider moving to annotation , particularly once we can count on Django 1.11 ' s subquery support transaction_date = self . transaction . date return self . account . balance ( leg_query = ( models . Q ( transaction__date__lt = transaction_date ) | ( models . Q ( transaction__date = transaction_date ) & models . Q ( transaction_id__lt = self . transaction_id ) ) ) )
def units_from_metadata ( obj , guess = True ) : """Try to extract hints from metadata and if that fails guess based on the object scale . Parameters obj : object Has attributes ' metadata ' ( dict ) and ' scale ' ( float ) guess : bool If metadata doesn ' t indicate units , guess from scale Returns units : str A guess of what the units might be"""
# try to guess from metadata for key in [ 'file_name' , 'name' ] : if key not in obj . metadata : continue # get the string which might contain unit hints hints = obj . metadata [ key ] . lower ( ) if 'unit' in hints : # replace all delimiter options with white space for delim in '_-.' : hints = hints . replace ( delim , ' ' ) # loop through each hint for hint in hints . strip ( ) . split ( ) : # key word is " unit " or " units " if 'unit' not in hint : continue # get rid of keyword and whitespace hint = hint . replace ( 'units' , '' ) . replace ( 'unit' , '' ) . strip ( ) # if the hint is a valid unit return it if hint in TO_INCH : return hint if not guess : raise ValueError ( 'no units and not allowed to guess' ) # we made it to the wild ass guess section # if the scale is larger than 100 mystery units # declare the model to be millimeters , otherwise inches log . warning ( 'no units: guessing from scale' ) if float ( obj . scale ) > 100.0 : return 'millimeters' else : return 'inches'
def reverse ( self ) : """Reverse the audio data . : raises : : class : ` ~ aeneas . audiofile . AudioFileNotInitializedError ` : if the audio file is not initialized yet . . versionadded : : 1.2.0"""
if self . __samples is None : if self . file_path is None : self . log_exc ( u"AudioFile object not initialized" , None , True , AudioFileNotInitializedError ) else : self . read_samples_from_file ( ) self . log ( u"Reversing..." ) self . __samples [ 0 : self . __samples_length ] = numpy . flipud ( self . __samples [ 0 : self . __samples_length ] ) self . log ( u"Reversing... done" )
def get_cache ( self , decorated_function , * args , ** kwargs ) : """: meth : ` WCacheStorage . get _ cache ` method implementation"""
self . __check ( decorated_function , * args , ** kwargs ) if decorated_function in self . _storage : for i in self . _storage [ decorated_function ] : if i [ 'instance' ] ( ) == args [ 0 ] : result = i [ 'result' ] . cache_entry ( * args , ** kwargs ) if self . __statistic is True : if result . has_value is True : self . __cache_hit += 1 else : self . __cache_missed += 1 return result if self . __statistic is True : self . __cache_missed += 1 return WCacheStorage . CacheEntry ( )
def _app_config_select ( self , request , obj ) : """Return the select value for apphook configs : param request : request object : param obj : current object : return : False if no preselected value is available ( more than one or no apphook config is present ) , apphook config instance if exactly one apphook config is defined or apphook config defined in the request or in the current object , False otherwise"""
if not obj and not request . GET . get ( self . app_config_attribute , False ) : config_model = get_apphook_model ( self . model , self . app_config_attribute ) if config_model . objects . count ( ) == 1 : return config_model . objects . first ( ) return None elif obj and getattr ( obj , self . app_config_attribute , False ) : return getattr ( obj , self . app_config_attribute ) elif request . GET . get ( self . app_config_attribute , False ) : config_model = get_apphook_model ( self . model , self . app_config_attribute ) return config_model . objects . get ( pk = int ( request . GET . get ( self . app_config_attribute , False ) ) ) return False
def run ( self ) : """run CMake"""
command = [ self . cmake ] if self . generator : command . extend ( [ '-G' , self . generator ] ) if self . path : command . append ( self . path ) if self . definitions is not None : for item in self . definitions . items ( ) : command . append ( '-D%s=%s' % item ) if self . options is not None : command . extend ( self . options ) cmd = yield self . makeRemoteShellCommand ( command = command ) yield self . runCommand ( cmd ) return cmd . results ( )
def step_indices ( group_idx ) : """Return the edges of areas within group _ idx , which are filled with the same value ."""
ilen = step_count ( group_idx ) + 1 indices = np . empty ( ilen , np . int64 ) indices [ 0 ] = 0 indices [ - 1 ] = group_idx . size cmp_pos = 0 ri = 1 for i in range ( len ( group_idx ) ) : if group_idx [ cmp_pos ] != group_idx [ i ] : cmp_pos = i indices [ ri ] = i ri += 1 return indices
def _make_datetime ( value ) : """Helper function for ` make _ datetime ( ) ` . Tries to convert the given value to a : class : ` datetime . datetime ` . But , unlike make _ datetime ( ) , if no timezone is given , makes a naive ` datetime . datetime ` . Strings will be parsed as ISO 8601 timestamps . If a number is provided , it will be interpreted as a UNIX timestamp , which by definition is UTC . If a ` dict ` is provided , does ` datetime . datetime ( * * value ) ` . If a ` tuple ` or a ` list ` is provided , does ` datetime . datetime ( * value ) ` . Uses the timezone in the tuple or list if provided . : param value : something to convert : type value : str | unicode | float | int | : class : ` datetime . datetime ` | dict | list | tuple : return : the value after conversion : rtype : : class : ` datetime . datetime ` : raises : ValueError | TypeError"""
if isinstance ( value , basestring ) : try : return aniso8601 . parse_datetime ( value ) except Exception as e : raise ValueError ( "Conversion to datetime.datetime failed. Could not " "parse the given string as an ISO 8601 timestamp: " "%s\n\n" "%s" % ( repr ( value ) , e . message , ) ) try : if isinstance ( value , datetime . datetime ) : return value elif isinstance ( value , dict ) : tzinfo = value . pop ( 'tzinfo' , None ) if tzinfo : return tzinfo . localize ( datetime . datetime ( ** value ) ) else : return datetime . datetime ( ** value ) # struct _ time does not preserve millisecond accuracy per # TinCan spec , so this is disabled to discourage its use . # elif isinstance ( value , struct _ time ) : # posix = mktime ( value ) # return datetime . datetime . utcfromtimestamp ( posix ) . replace ( tzinfo = utc ) elif isinstance ( value , ( tuple , list ) ) : return tuple_to_datetime ( value ) else : return datetime . datetime . utcfromtimestamp ( value ) . replace ( tzinfo = utc ) except Exception as e : msg = ( "Could not convert the given value of type '%s' to a " "datetime.datetime: %s\n\n" "%s" % ( value . __class__ . __name__ , repr ( value ) , e . message , ) ) raise TypeError ( msg ) if isinstance ( e , TypeError ) else ValueError ( msg )
def to_glyphs_family_user_data_from_designspace ( self ) : """Set the GSFont userData from the designspace family - wide lib data ."""
target_user_data = self . font . userData for key , value in self . designspace . lib . items ( ) : if key == UFO2FT_FEATURE_WRITERS_KEY and value == DEFAULT_FEATURE_WRITERS : # if the designspace contains featureWriters settings that are the # same as glyphsLib default settings , there ' s no need to store them continue if _user_data_has_no_special_meaning ( key ) : target_user_data [ key ] = value
def remove_namespace ( self , ns_uri ) : """Removes the indicated namespace from this set ."""
if not self . contains_namespace ( ns_uri ) : return ni = self . __ns_uri_map . pop ( ns_uri ) for prefix in ni . prefixes : del self . __prefix_map [ prefix ]
def _maybeCreateTable ( self , tableClass , key ) : """A type ID has been requested for an Item subclass whose table was not present when this Store was opened . Attempt to create the table , and if that fails because another Store object ( perhaps in another process ) has created the table , re - read the schema . When that ' s done , return the typeID . This method is internal to the implementation of getTypeID . It must be run in a transaction . @ param tableClass : an Item subclass @ param key : a 2 - tuple of the tableClass ' s typeName and schemaVersion @ return : a typeID for the table ; a new one if no table exists , or the existing one if the table was created by another Store object referencing this database ."""
try : self . _justCreateTable ( tableClass ) except errors . TableAlreadyExists : # Although we don ' t have a memory of this table from the last time # we called " _ startup ( ) " , another process has updated the schema # since then . self . _startup ( ) return self . typenameAndVersionToID [ key ] typeID = self . executeSchemaSQL ( _schema . CREATE_TYPE , [ tableClass . typeName , tableClass . __module__ , tableClass . schemaVersion ] ) self . typenameAndVersionToID [ key ] = typeID if self . tablesCreatedThisTransaction is not None : self . tablesCreatedThisTransaction . append ( tableClass ) # If the new type is a legacy type ( not the current version ) , we need # to queue it for upgrade to ensure that if we are in the middle of an # upgrade , legacy items of this version get upgraded . cls = _typeNameToMostRecentClass . get ( tableClass . typeName ) if cls is not None and tableClass . schemaVersion != cls . schemaVersion : self . _upgradeManager . queueTypeUpgrade ( tableClass ) # We can pass ( ) for extantIndexes here because since the table didn ' t # exist for tableClass , none of its indexes could have either . # Whatever checks _ createIndexesFor will make would give the same # result against the actual set of existing indexes as they will # against ( ) . self . _createIndexesFor ( tableClass , ( ) ) for n , ( name , storedAttribute ) in enumerate ( tableClass . getSchema ( ) ) : self . executeSchemaSQL ( _schema . ADD_SCHEMA_ATTRIBUTE , [ typeID , n , storedAttribute . indexed , storedAttribute . sqltype , storedAttribute . allowNone , storedAttribute . attrname , storedAttribute . doc , storedAttribute . __class__ . __name__ ] ) # XXX probably need something better for pythontype eventually , # when we figure out a good way to do user - defined attributes or we # start parameterizing references . return typeID
def fast_steady_state ( Ep , epsilonp , detuning_knob , gamma , omega_level , rm , xi , theta , file_name = None , return_code = False ) : r"""Return a fast function that returns a steady state . We test a basic two - level system . > > > import numpy as np > > > from scipy . constants import physical _ constants > > > from sympy import Matrix , symbols > > > from fast . electric _ field import electric _ field _ amplitude _ top > > > from fast . symbolic import ( define _ laser _ variables , . . . polarization _ vector ) > > > Ne = 2 > > > Nl = 1 > > > a0 = physical _ constants [ " Bohr radius " ] [ 0] > > > rm = [ np . array ( [ [ 0 , 0 ] , [ a0 , 0 ] ] ) , . . . np . array ( [ [ 0 , 0 ] , [ 0 , 0 ] ] ) , . . . np . array ( [ [ 0 , 0 ] , [ 0 , 0 ] ] ) ] > > > xi = np . array ( [ [ [ 0 , 1 ] , [ 1 , 0 ] ] ] ) > > > omega _ level = [ 0 , 1.0e9] > > > gamma21 = 2 * np . pi * 6e6 > > > gamma = np . array ( [ [ 0 , - gamma21 ] , [ gamma21 , 0 ] ] ) > > > theta = phase _ transformation ( Ne , Nl , rm , xi ) We define symbolic variables to be used as token arguments . > > > Ep , omega _ laser = define _ laser _ variables ( Nl ) > > > epsilonps = [ polarization _ vector ( 0 , 0 , 0 , 0 , 1 ) ] > > > detuning _ knob = [ symbols ( " delta1 " , real = True ) ] An map to unfold the density matrix . > > > unfolding = Unfolding ( Ne , True , True , True ) We obtain a function to calculate Hamiltonian terms . > > > aux = ( Ep , epsilonps , detuning _ knob , gamma , . . . omega _ level , rm , xi , theta ) > > > steady _ state = fast _ steady _ state ( * aux ) We specify values for the variables > > > detuning _ knobs = [ 100e6] > > > Eps = electric _ field _ amplitude _ top ( 1e - 3 , 1e - 3 , 1 , " SI " ) > > > Eps * = np . exp ( 1j * np . pi ) > > > Eps = [ Eps ] > > > print ( steady _ state ( Eps , detuning _ knobs ) ) [ 0.018 0.1296 - 0.0244]"""
# We unpack variables . if True : Ne = len ( omega_level ) Nl = xi . shape [ 0 ] unfolding = Unfolding ( Ne , True , True , True ) # We determine which arguments are constants . if True : try : Ep = np . array ( [ complex ( Ep [ l ] ) for l in range ( Nl ) ] ) variable_Ep = False except : variable_Ep = True try : epsilonp = [ np . array ( [ complex ( epsilonp [ l ] [ i ] ) for i in range ( 3 ) ] ) for l in range ( Nl ) ] variable_epsilonp = False except : variable_epsilonp = True try : detuning_knob = np . array ( [ float ( detuning_knob [ l ] ) for l in range ( Nl ) ] ) variable_detuning_knob = False except : variable_detuning_knob = True # We obtain code for the three parts . if True : args = ( Ep , epsilonp , detuning_knob , gamma , omega_level , rm , xi , theta , unfolding , True , None , True ) bloch_equations = fast_bloch_equations ( * args ) code = bloch_equations + "\n\n" if ( ( not variable_Ep ) and ( not variable_epsilonp ) and ( not variable_detuning_knob ) ) : # We can call bloch _ equations here ! code += "bloch_equations = bloch_equations()\n" # We establish the arguments of the output function . if True : code += "def steady_state(" if variable_Ep : code += "Ep, " if variable_epsilonp : code += "epsilonp, " if variable_detuning_knob : code += "detuning_knob, " code += "bloch_equations=bloch_equations):\n" code += ' r"""A fast calculation of the steady state."""\n' # We call the Bloch equations . if True : code += r""" A, b = bloch_equations""" if ( ( not variable_Ep ) and ( not variable_epsilonp ) and ( not variable_detuning_knob ) ) : code += "\n" else : code += "(" if variable_Ep : code += "Ep, " if variable_epsilonp : code += "epsilonp, " if variable_detuning_knob : code += "detuning_knob, " if code [ - 2 : ] == ", " : code = code [ : - 2 ] code += ")\n" code += """ rhox = np.linalg.solve(A, b)\n""" code += """ return rhox\n""" # We write the code to file if provided , and execute it . if True : if file_name is not None : f = file ( file_name + ".py" , "w" ) f . write ( code ) f . close ( ) steady_state = code if not return_code : exec steady_state return steady_state
def create_gist ( self , public , files , description = github . GithubObject . NotSet ) : """: calls : ` POST / gists < http : / / developer . github . com / v3 / gists > ` _ : param public : bool : param files : dict of string to : class : ` github . InputFileContent . InputFileContent ` : param description : string : rtype : : class : ` github . Gist . Gist `"""
assert isinstance ( public , bool ) , public assert all ( isinstance ( element , github . InputFileContent ) for element in files . itervalues ( ) ) , files assert description is github . GithubObject . NotSet or isinstance ( description , ( str , unicode ) ) , description post_parameters = { "public" : public , "files" : { key : value . _identity for key , value in files . iteritems ( ) } , } if description is not github . GithubObject . NotSet : post_parameters [ "description" ] = description headers , data = self . _requester . requestJsonAndCheck ( "POST" , "/gists" , input = post_parameters ) return github . Gist . Gist ( self . _requester , headers , data , completed = True )
def _is_iterable ( val ) : """Ensure that a value is iterable and not some sort of string"""
try : iter ( val ) except ( ValueError , TypeError ) : return False else : return not isinstance ( val , basestring )
def sigusr1_handler ( self , unused_signum , unused_frame ) : """Handle SIGUSR1 signal . Call function which is defined in the * * settings . SIGUSR1 _ HANDLER * * . If main process , forward the signal to all child processes ."""
for process in self . processes : if process . pid and os . getpid ( ) == self . main_pid : try : os . kill ( process . pid , signal . SIGUSR1 ) except ProcessLookupError : pass if self . _sigusr1_handler_func is not None : self . _sigusr1_handler_func ( self . context )
def exception ( self ) : """Try retrieving the last subprocess exception . If set , the exception is returned . Otherwise None is returned ."""
if self . _exception is not None : return self . _exception try : exc , tblines = self . exc_queue . get_nowait ( ) except Empty : self . _exception , self . tb_lines = None , None else : # Raise any exception that the subprocess encountered and sent . self . _exception , self . tb_lines = exc , tblines return self . _exception
def format_tasks ( tasks ) : """Converts a list of tasks to a list of string representations . Args : tasks : A list of the tasks to convert . Returns : A list of string formatted tasks ."""
return [ '%d : %s (%s)' % ( task . key . id ( ) , task . description , ( 'done' if task . done else 'created %s' % task . created ) ) for task in tasks ]
def merge ( self , data ) : '''Merge an array of output dictionaries into a single dictionary with properly scoped names . Parameters data : list of dict Output dicts as produced by ` pumpp . task . BaseTaskTransformer . transform ` or ` pumpp . feature . FeatureExtractor . transform ` . Returns data _ out : dict All elements of the input dicts are stacked along the 0 axis , and keys are re - mapped by ` scope ` .'''
data_out = dict ( ) # Iterate over all keys in data for key in set ( ) . union ( * data ) : data_out [ self . scope ( key ) ] = np . stack ( [ np . asarray ( d [ key ] ) for d in data ] , axis = 0 ) return data_out
def get_mapping_from_db3_file ( db_path ) : '''Does the work of reading the Rosetta SQLite3 . db3 file to retrieve the mapping'''
import sqlite3 # should be moved to the top but we do this here for CentOS 5 support conn = sqlite3 . connect ( db_path ) results = conn . cursor ( ) . execute ( ''' SELECT chain_id, pdb_residue_number, insertion_code, residues.struct_id, residues.resNum, residues.name3, residues.res_type FROM residue_pdb_identification INNER JOIN residues ON residue_pdb_identification.struct_id=residues.struct_id AND residue_pdb_identification.residue_number=residues.resNum ''' ) # Create the mapping from PDB residues to Rosetta residues rosetta_residue_ids = [ ] mapping = { } for r in results : mapping [ "%s%s%s" % ( r [ 0 ] , str ( r [ 1 ] ) . rjust ( 4 ) , r [ 2 ] ) ] = { 'pose_residue_id' : r [ 4 ] , 'name3' : r [ 5 ] , 'res_type' : r [ 6 ] } rosetta_residue_ids . append ( r [ 4 ] ) # Ensure that the the range of the map is exactly the set of Rosetta residues i . e . the map from ( a subset of ) the PDB residues to the Rosetta residues is surjective raw_residue_list = [ r for r in conn . cursor ( ) . execute ( '''SELECT resNum, name3 FROM residues ORDER BY resNum''' ) ] assert ( sorted ( [ r [ 0 ] for r in raw_residue_list ] ) == sorted ( rosetta_residue_ids ) ) return mapping
def load_GODag ( ) : """OBO file retrieved from http : / / obo . cvs . sourceforge . net / viewvc / obo / obo / ontology / genomic - proteomic / so . obo"""
from jcvi . apps . base import download so_file_url = "http://obo.cvs.sourceforge.net/viewvc/obo/obo/ontology/genomic-proteomic/so.obo" so_file = download ( so_file_url , debug = False ) return GODag ( so_file )
def encode ( self , payload ) : """Encode payload"""
try : return self . encoder . encode ( payload ) except Exception as exception : raise EncodeError ( str ( exception ) )
def time_average ( rho , t ) : r"""Return a time - averaged density matrix ( using trapezium rule ) . We test a basic two - level system . > > > import numpy as np > > > from scipy . constants import physical _ constants > > > from sympy import Matrix , symbols > > > from fast . electric _ field import electric _ field _ amplitude _ top > > > from fast . symbolic import ( define _ laser _ variables , . . . polarization _ vector ) > > > Ne = 2 > > > Nl = 1 > > > a0 = physical _ constants [ " Bohr radius " ] [ 0] > > > rm = [ np . array ( [ [ 0 , 0 ] , [ a0 , 0 ] ] ) , . . . np . array ( [ [ 0 , 0 ] , [ 0 , 0 ] ] ) , . . . np . array ( [ [ 0 , 0 ] , [ 0 , 0 ] ] ) ] > > > xi = np . array ( [ [ [ 0 , 1 ] , [ 1 , 0 ] ] ] ) > > > omega _ level = [ 0 , 1.0e9] > > > gamma21 = 2 * np . pi * 6e6 > > > gamma = np . array ( [ [ 0 , - gamma21 ] , [ gamma21 , 0 ] ] ) > > > theta = phase _ transformation ( Ne , Nl , rm , xi ) We define symbolic variables to be used as token arguments . > > > Ep , omega _ laser = define _ laser _ variables ( Nl ) > > > epsilonps = [ polarization _ vector ( 0 , 0 , 0 , 0 , 1 ) ] > > > detuning _ knob = [ symbols ( " delta1 " , real = True ) ] An map to unfold the density matrix . > > > unfolding = Unfolding ( Ne , True , True , True ) We obtain a function to calculate Hamiltonian terms . > > > aux = ( Ep , epsilonps , detuning _ knob , gamma , . . . omega _ level , rm , xi , theta ) > > > time _ evolution = fast _ time _ evolution ( * aux ) We specify values for the variables > > > detuning _ knobs = [ 100e6] > > > Eps = electric _ field _ amplitude _ top ( 1e - 3 , 1e - 3 , 1 , " SI " ) > > > Eps * = np . exp ( 1j * np . pi ) > > > Eps = [ Eps ] > > > t = np . linspace ( 0 , 1e - 6 , 11) > > > rho0 = np . array ( [ [ 1 , 0 ] , [ 0 , 0 ] ] ) > > > rho0 = unfolding ( rho0) > > > rho = time _ evolution ( t , rho0 , Eps , detuning _ knobs ) > > > print ( time _ average ( rho , t ) ) [ 0.0175 0.1244 - 0.0222]"""
T = t [ - 1 ] - t [ 0 ] dt = t [ 1 ] - t [ 0 ] rhoav = np . sum ( rho [ 1 : - 1 ] , axis = 0 ) + 0.5 * ( rho [ 0 ] + rho [ - 1 ] ) rhoav = dt / T * rhoav return rhoav
def _display_error ( normalized_data , stream ) : """print error message from docker - py stream and raise Exception . u ' message ' : u " Error getting container 981c3e17bfc6138d1985c0c8f5616e9064e56559e817646ad38211a456d6bcf2 from driver devicemapper : Error mounting ' / dev / mapper / docker - 8:3-34393696-981c3e17bfc6138d1985c0c8f5616e9064e56559e817646ad38211a456d6bcf2' on ' / data / docker / devicemapper / mnt / 981c3e17bfc6138d1985c0c8f5616e9064e56559e817646ad38211a456d6bcf2 ' : no such file or directory " """
# TODO : need to revisit this later . error = normalized_data [ 'error' ] if 'error_detail' in normalized_data : stream . write ( "exit code: {0}\n" . format ( normalized_data [ 'error_detail' ] . get ( 'code' ) , 'There was no exit code provided' ) ) stream . write ( normalized_data [ 'error_detail' ] . get ( 'message' , 'There were no message details provided.' ) ) raise DockerStreamException ( error )
def watch_length ( params , ctxt , scope , stream , coord ) : """WatchLength - Watch the total length of each of the params . Example : The code below uses the ` ` WatchLength ` ` update function to update the ` ` length ` ` field to the length of the ` ` data ` ` field : : int length < watch = data , update = WatchLength > ; char data [ length ] ;"""
if len ( params ) <= 1 : raise errors . InvalidArguments ( coord , "{} args" . format ( len ( params ) ) , "at least two arguments" ) to_update = params [ 0 ] total_size = 0 for param in params [ 1 : ] : total_size += param . _pfp__width ( ) to_update . _pfp__set_value ( total_size )
async def cities ( self , country : str , state : str ) -> list : """Return a list of supported cities in a country / state ."""
data = await self . _request ( 'get' , 'cities' , params = { 'state' : state , 'country' : country } ) return [ d [ 'city' ] for d in data [ 'data' ] ]
def get_configurations ( self ) : """Generates a dictionary that ' s made up of the configurations on the project . Any configurations on a project that are duplicated on a stage , the stage configuration will take precedence ."""
project_configurations_dictionary = { } project_configurations = self . project . project_configurations ( ) # Create project specific configurations dictionary for config in project_configurations : project_configurations_dictionary [ config . key ] = config stage_configurations_dictionary = { } stage_configurations = self . stage_configurations ( ) # Create stage specific configurations dictionary for s in stage_configurations : stage_configurations_dictionary [ s . key ] = s # override project specific configuration with the ones in the stage if they are there project_configurations_dictionary . update ( stage_configurations_dictionary ) # Return the updated configurations return project_configurations_dictionary
def which_lease_to_steal ( self , stealable_leases , have_lease_count ) : """Determines and return which lease to steal If the number of leases is a multiple of the number of hosts , then the desired configuration is that all hosts own the name number of leases , and the difference between the " biggest " owner and any other is 0. If the number of leases is not a multiple of the number of hosts , then the most even configurationpossible is for some hosts to have ( self , leases / hosts ) leases and others to have ( self , ( self , leases / hosts ) + 1 ) . For example , for 16 partitions distributed over five hosts , the distribution would be 4 , 3 , 3 , 3 , 3 , or any of the possible reorderings . In either case , if the difference between this host and the biggest owner is 2 or more , then thesystem is not in the most evenly - distributed configuration , so steal one lease from the biggest . If there is a tie for biggest , we pick whichever appears first in the list because it doesn ' t really matter which " biggest " is trimmed down . Stealing one at a time prevents flapping because it reduces the difference between the biggest and this host by two at a time . If the starting difference is two or greater , then the difference cannot end up below 0 . This host may become tied for biggest , but it cannot become larger than the host that it is stealing from . : param stealable _ leases : List of leases to determine which can be stolen . : type stealable _ leases : list [ ~ azure . eventprocessorhost . lease . Lease ] : param have _ lease _ count : Lease count . : type have _ lease _ count : int : rtype : ~ azure . eventprocessorhost . lease . Lease"""
counts_by_owner = self . count_leases_by_owner ( stealable_leases ) biggest_owner = ( sorted ( counts_by_owner . items ( ) , key = lambda kv : kv [ 1 ] ) ) . pop ( ) steal_this_lease = None if ( biggest_owner [ 1 ] - have_lease_count ) >= 2 : steal_this_lease = [ l for l in stealable_leases if l . owner == biggest_owner [ 0 ] ] [ 0 ] return steal_this_lease
def call_env_doctree_read ( cls , kb_app , sphinx_app : Sphinx , doctree : doctree ) : """On doctree - read , do callbacks"""
for callback in EventAction . get_callbacks ( kb_app , SphinxEvent . DREAD ) : callback ( kb_app , sphinx_app , doctree )
def get ( self , url , params ) : """Issues a GET request against the API , properly formatting the params : param url : a string , the url you are requesting : param params : a dict , the key - value of all the paramaters needed in the request : returns : a dict parsed of the JSON response"""
url = self . host + url if params : url = url + "?" + urllib . parse . urlencode ( params ) try : resp = requests . get ( url , allow_redirects = False , headers = self . headers , auth = self . oauth ) except TooManyRedirects as e : resp = e . response return self . json_parse ( resp )
def transformer_tall_pretrain_lm ( ) : """Hparams for transformer on LM pretraining ( with 64k vocab ) ."""
hparams = transformer_tall ( ) hparams . learning_rate_constant = 2e-4 hparams . learning_rate_schedule = ( "linear_warmup*constant*cosdecay" ) hparams . optimizer = "adam_w" hparams . optimizer_adam_beta1 = 0.9 hparams . optimizer_adam_beta2 = 0.999 hparams . optimizer_adam_epsilon = 1e-8 # Set max examples to something big when pretraining only the LM , definitely # something an order of magnitude bigger than number of train steps . hparams . multiproblem_schedule_max_examples = 5e8 # Set train steps to learning _ rate _ decay _ steps or less hparams . learning_rate_decay_steps = 5000000 return hparams
def get_ids ( cs ) : """Return chemical identifier records ."""
records = [ ] for c in cs : records . append ( { k : c [ k ] for k in c if k in { 'names' , 'labels' } } ) return records
def getPort ( self ) : """Helper method for testing ; returns the TCP port used for this registration , even if it was specified as 0 and thus allocated by the OS ."""
disp = self . pbmanager . dispatchers [ self . portstr ] return disp . port . getHost ( ) . port
def get_machine_stats ( self ) : '''Gather spider based stats'''
self . logger . debug ( "Gathering machine stats" ) the_dict = { } keys = self . redis_conn . keys ( 'stats:crawler:*:*:*:*' ) for key in keys : # break down key elements = key . split ( ":" ) machine = elements [ 2 ] spider = elements [ 3 ] response = elements [ 4 ] end = elements [ 5 ] # we only care about the machine , not spider type if machine not in the_dict : the_dict [ machine ] = { } if response not in the_dict [ machine ] : the_dict [ machine ] [ response ] = { } if end in the_dict [ machine ] [ response ] : the_dict [ machine ] [ response ] [ end ] = the_dict [ machine ] [ response ] [ end ] + self . _get_key_value ( key , end == 'lifetime' ) else : the_dict [ machine ] [ response ] [ end ] = self . _get_key_value ( key , end == 'lifetime' ) # simple count the_dict [ 'count' ] = len ( list ( the_dict . keys ( ) ) ) ret_dict = { } ret_dict [ 'machines' ] = the_dict return ret_dict
def csv ( self , text = TEXT , sep = ',' , index = True , float_fmt = "%.2g" ) : """Generate a CSV table from the table data ."""
return self . _data . to_csv ( sep = sep , index = index , float_format = float_fmt )
def createCells ( self ) : '''Function to instantiate Cell objects based on the characteristics of this population'''
# add individual cells if 'cellsList' in self . tags : cells = self . createCellsList ( ) # create cells based on fixed number of cells elif 'numCells' in self . tags : cells = self . createCellsFixedNum ( ) # create cells based on density ( optional ynorm - dep ) elif 'density' in self . tags : cells = self . createCellsDensity ( ) # create cells based on density ( optional ynorm - dep ) elif 'gridSpacing' in self . tags : cells = self . createCellsGrid ( ) # not enough tags to create cells else : self . tags [ 'numCells' ] = 1 print ( 'Warninig: number or density of cells not specified for population %s; defaulting to numCells = 1' % ( self . tags [ 'pop' ] ) ) cells = self . createCellsFixedNum ( ) return cells
def paint ( self , painter , option , widget ) : """Overloads the default QGraphicsItem paint event to update the node when necessary and call the draw method for the node . : param painter < QPainter > : param option < QStyleOptionGraphicsItem > : param widget < QWidget >"""
# rebuild when dirty if self . isDirty ( ) : self . rebuild ( ) painter . save ( ) painter . setOpacity ( self . opacity ( ) ) if self . drawHotspotsUnderneath ( ) : self . drawHotspots ( painter ) if self . isEnabled ( ) : painter . setPen ( self . penColor ( ) ) painter . setBrush ( self . brush ( ) ) else : painter . setPen ( self . disabledPenColor ( ) ) painter . setBrush ( self . disabledBrush ( ) ) # draw the item self . draw ( painter , option , widget ) if not self . drawHotspotsUnderneath ( ) : self . drawHotspots ( painter ) painter . restore ( )
def iter_by_year ( self ) : """Split the return objects by year and iterate"""
for key , grp in self . rets . groupby ( lambda x : x . year ) : yield key , CumulativeRets ( rets = grp )
def parse_doctype ( cls , file , encoding = None ) : '''Get the doctype from the document . Returns : str , None'''
if encoding : lxml_encoding = to_lxml_encoding ( encoding ) or 'latin1' else : lxml_encoding = encoding try : parser = lxml . etree . XMLParser ( encoding = lxml_encoding , recover = True ) tree = lxml . etree . parse ( io . BytesIO ( wpull . util . peek_file ( file ) ) , parser = parser ) if tree . getroot ( ) is not None : return tree . docinfo . doctype except lxml . etree . LxmlError : pass
def duplicate ( self , name ) : """. . versionadded : : 0.5.8 Requires SMC version > = 6.3.2 Duplicate this element . This is a shortcut method that will make a direct copy of the element under the new name and type . : param str name : name for the duplicated element : raises ActionCommandFailed : failed to duplicate the element : return : the newly created element : rtype : Element"""
dup = self . make_request ( method = 'update' , raw_result = True , resource = 'duplicate' , params = { 'name' : name } ) return type ( self ) ( name = name , href = dup . href , type = type ( self ) . typeof )
def slice_3d_grid ( grid , n ) : """Takes a three dimensional array and an integer ( n ) and returns a 2d array containing the Nth value from the 3rd dimension at each location in the grid ."""
phen_grid = initialize_grid ( ( len ( grid [ 0 ] ) , len ( grid ) ) , 0 ) for i in range ( len ( grid ) ) : for j in range ( len ( grid [ i ] ) ) : phen_grid [ i ] [ j ] = grid [ i ] [ j ] [ n ] return phen_grid
def stepThroughJsWaf_selenium_chromium ( self , url , titleContains = '' , titleNotContains = '' ) : '''Use Selenium + SeleniumChromium to access a resource behind cloudflare protection . Params : ` ` url ` ` - The URL to access that is protected by cloudflare ` ` titleContains ` ` - A string that is in the title of the protected page , and NOT the cloudflare intermediate page . The presence of this string in the page title is used to determine whether the cloudflare protection has been successfully penetrated . The current WebGetRobust headers are installed into the selenium browser , which is then used to access the protected resource . Once the protected page has properly loaded , the cloudflare access cookie is then extracted from the selenium browser , and installed back into the WebGetRobust instance , so it can continue to use the cloudflare auth in normal requests .'''
if ( not titleContains ) and ( not titleNotContains ) : raise ValueError ( "You must pass either a string the title should contain, or a string the title shouldn't contain!" ) if titleContains and titleNotContains : raise ValueError ( "You can only pass a single conditional statement!" ) self . log . info ( "Attempting to access page through cloudflare browser verification." ) if not self . selenium_chromium_driver : self . _initSeleniumChromiumWebDriver ( ) self . _syncIntoSeleniumChromiumWebDriver ( ) self . selenium_chromium_driver . get ( url ) if titleContains : condition = EC . title_contains ( titleContains ) elif titleNotContains : condition = SeleniumCommon . title_not_contains ( titleNotContains ) else : raise ValueError ( "Wat?" ) try : WebDriverWait ( self . selenium_chromium_driver , 45 ) . until ( condition ) success = True self . log . info ( "Successfully accessed main page!" ) except TimeoutException : self . log . error ( "Could not pass through cloudflare blocking!" ) success = False # Add cookies to cookiejar self . _syncOutOfSeleniumChromiumWebDriver ( ) self . _syncCookiesFromFile ( ) return success
def generate ( self , id_or_uri ) : """Generates and returns a random range . Args : id _ or _ uri : ID or URI of range . Returns : dict : A dict containing a list with IDs ."""
uri = self . _client . build_uri ( id_or_uri ) + "/generate" return self . _client . get ( uri )
def envs ( ignore_cache = False ) : '''Return a list of refs that can be used as environments'''
if not ignore_cache : env_cache = os . path . join ( __opts__ [ 'cachedir' ] , 'svnfs/envs.p' ) cache_match = salt . fileserver . check_env_cache ( __opts__ , env_cache ) if cache_match is not None : return cache_match ret = set ( ) for repo in init ( ) : trunk = os . path . join ( repo [ 'repo' ] , repo [ 'trunk' ] ) if os . path . isdir ( trunk ) : # Add base as the env for trunk ret . add ( 'base' ) else : log . error ( 'svnfs trunk path \'%s\' does not exist in repo %s, no base ' 'environment will be provided by this remote' , repo [ 'trunk' ] , repo [ 'url' ] ) branches = os . path . join ( repo [ 'repo' ] , repo [ 'branches' ] ) if os . path . isdir ( branches ) : ret . update ( os . listdir ( branches ) ) else : log . error ( 'svnfs branches path \'%s\' does not exist in repo %s' , repo [ 'branches' ] , repo [ 'url' ] ) tags = os . path . join ( repo [ 'repo' ] , repo [ 'tags' ] ) if os . path . isdir ( tags ) : ret . update ( os . listdir ( tags ) ) else : log . error ( 'svnfs tags path \'%s\' does not exist in repo %s' , repo [ 'tags' ] , repo [ 'url' ] ) return [ x for x in sorted ( ret ) if _env_is_exposed ( x ) ]
def hsv_to_rgb ( hsv ) : """Converts a tuple of hue , saturation , value to a tuple of red , green blue . Hue should be an angle from 0.0 to 359.0 . Saturation and value should be a value from 0.0 to 1.0 , where saturation controls the intensity of the hue and value controls the brightness ."""
# Algorithm adapted from http : / / www . cs . rit . edu / ~ ncs / color / t _ convert . html h , s , v = hsv if s == 0 : return ( v , v , v ) h /= 60.0 i = math . floor ( h ) f = h - i p = v * ( 1.0 - s ) q = v * ( 1.0 - s * f ) t = v * ( 1.0 - s * ( 1.0 - f ) ) if i == 0 : return ( v , t , p ) elif i == 1 : return ( q , v , p ) elif i == 2 : return ( p , v , t ) elif i == 3 : return ( p , q , v ) elif i == 4 : return ( t , p , v ) else : return ( v , p , q )
def _remove_from_index ( index , obj ) : """Removes object ` ` obj ` ` from the ` ` index ` ` ."""
try : index . value_map [ indexed_value ( index , obj ) ] . remove ( obj . id ) except KeyError : pass
def grep ( self , path , content , flags ) : """grep every child path under path for content"""
try : match = re . compile ( content , flags ) except sre_constants . error as ex : print ( "Bad regexp: %s" % ( ex ) ) return for gpath , matches in self . do_grep ( path , match ) : yield ( gpath , matches )
def _process_interaction ( self , source_id , interaction , text , pmid , extra_annotations ) : """Process an interaction JSON tuple from the ISI output , and adds up to one statement to the list of extracted statements . Parameters source _ id : str the JSON key corresponding to the sentence in the ISI output interaction : the JSON list with subject / verb / object information about the event in the ISI output text : str the text of the sentence pmid : str the PMID of the article from which the information was extracted extra _ annotations : dict Additional annotations to add to the statement ' s evidence , potentially containing metadata about the source . Annotations with the key " interaction " will be overridden by the JSON interaction tuple from the ISI output"""
verb = interaction [ 0 ] . lower ( ) subj = interaction [ - 2 ] obj = interaction [ - 1 ] # Make ungrounded agent objects for the subject and object # Grounding will happen after all statements are extracted in _ _ init _ _ subj = self . _make_agent ( subj ) obj = self . _make_agent ( obj ) # Make an evidence object annotations = deepcopy ( extra_annotations ) if 'interaction' in extra_annotations : logger . warning ( "'interaction' key of extra_annotations ignored" + " since this is reserved for storing the raw ISI " + "input." ) annotations [ 'source_id' ] = source_id annotations [ 'interaction' ] = interaction ev = ist . Evidence ( source_api = 'isi' , pmid = pmid , text = text . rstrip ( ) , annotations = annotations ) # For binding time interactions , it is said that a catayst might be # specified . We don ' t use this for now , but extract in case we want # to in the future cataylst_specified = False if len ( interaction ) == 4 : catalyst = interaction [ 1 ] if catalyst is not None : cataylst_specified = True self . verbs . add ( verb ) statement = None if verb in verb_to_statement_type : statement_class = verb_to_statement_type [ verb ] if statement_class == ist . Complex : statement = ist . Complex ( [ subj , obj ] , evidence = ev ) else : statement = statement_class ( subj , obj , evidence = ev ) if statement is not None : # For Complex statements , the ISI reader produces two events : # binds ( A , B ) and binds ( B , A ) # We want only one Complex statement for each sentence , so check # to see if we already have a Complex for this source _ id with the # same members already_have = False if type ( statement ) == ist . Complex : for old_s in self . statements : old_id = statement . evidence [ 0 ] . source_id new_id = old_s . evidence [ 0 ] . source_id if type ( old_s ) == ist . Complex and old_id == new_id : old_statement_members = [ m . db_refs [ 'TEXT' ] for m in old_s . members ] old_statement_members = sorted ( old_statement_members ) new_statement_members = [ m . db_refs [ 'TEXT' ] for m in statement . members ] new_statement_members = sorted ( new_statement_members ) if old_statement_members == new_statement_members : already_have = True break if not already_have : self . statements . append ( statement )
def firstChild ( self ) : '''firstChild - property , Get the first child block , text or tag . @ return < str / AdvancedTag / None > - The first child block , or None if no child blocks'''
blocks = object . __getattribute__ ( self , 'blocks' ) # First block is empty string for indent , but don ' t hardcode incase that changes if blocks [ 0 ] == '' : firstIdx = 1 else : firstIdx = 0 if len ( blocks ) == firstIdx : # No first child return None return blocks [ 1 ]
def is_grounded_to_name ( c : Concept , name : str , cutoff = 0.7 ) -> bool : """Check if a concept is grounded to a given name ."""
return ( top_grounding ( c ) == name ) if is_well_grounded ( c , cutoff ) else False
async def send_api ( container , targetname , name , params = { } ) : """Send API and discard the result"""
handle = object ( ) apiEvent = ModuleAPICall ( handle , targetname , name , params = params ) await container . wait_for_send ( apiEvent )
def _dict ( self , with_name = True ) : """Returns the identity as a dict . values that are empty are removed"""
d = dict ( [ ( k , getattr ( self , k ) ) for k , _ , _ in self . name_parts ] ) if with_name : d [ 'name' ] = self . name try : d [ 'vname' ] = self . vname except ValueError : pass return self . clear_dict ( d )
def get_tuple_version ( name , default = DEFAULT_TUPLE_NOT_FOUND , allow_ambiguous = True ) : """Get tuple version from installed package information for easy handling . It will return : attr : ` default ` value when the named package is not installed . Parameters name : string An application name used to install via setuptools . default : tuple A default returning value used when the named application is not installed yet allow _ ambiguous : boolean ` ` True ` ` for allowing ambiguous version information . Returns string A version tuple Examples > > > v = get _ tuple _ version ( ' app _ version ' , allow _ ambiguous = True ) > > > len ( v ) > = 3 True > > > isinstance ( v [ 0 ] , int ) True > > > isinstance ( v [ 1 ] , int ) True > > > isinstance ( v [ 2 ] , int ) True > > > get _ tuple _ version ( ' distribution _ which _ is _ not _ installed ' ) (0 , 0 , 0)"""
def _prefer_int ( x ) : try : return int ( x ) except ValueError : return x version = get_string_version ( name , default = default , allow_ambiguous = allow_ambiguous ) # convert string version to tuple version # prefer integer for easy handling if isinstance ( version , tuple ) : # not found return version return tuple ( map ( _prefer_int , version . split ( '.' ) ) )
def get_source_and_pgp_key ( source_and_key ) : """Look for a pgp key ID or ascii - armor key in the given input . : param source _ and _ key : Sting , " source _ spec | keyid " where ' | keyid ' is optional . : returns ( source _ spec , key _ id OR None ) as a tuple . Returns None for key _ id if there was no ' | ' in the source _ and _ key string ."""
try : source , key = source_and_key . split ( '|' , 2 ) return source , key or None except ValueError : return source_and_key , None
def within_kilometers ( self , key , point , max_distance , min_distance = None ) : """增加查询条件 , 限制返回结果指定字段值的位置在某点的一段距离之内 。 : param key : 查询条件字段名 : param point : 查询地理位置 : param max _ distance : 最大距离限定 ( 千米 ) : param min _ distance : 最小距离限定 ( 千米 ) : rtype : Query"""
if min_distance is not None : min_distance = min_distance / 6371.0 return self . within_radians ( key , point , max_distance / 6371.0 , min_distance )
def append ( self , item ) : """Append item to end of model"""
self . beginInsertRows ( QtCore . QModelIndex ( ) , self . rowCount ( ) , self . rowCount ( ) ) self . items . append ( item ) self . endInsertRows ( )
def timedelta_seconds ( td ) : '''Return the offset stored by a : class : ` datetime . timedelta ` object as an integer number of seconds . Microseconds , if present , are rounded to the nearest second . Delegates to : meth : ` timedelta . total _ seconds ( ) < datetime . timedelta . total _ seconds ( ) > ` if available . > > > timedelta _ seconds ( timedelta ( hours = 1 ) ) 3600 > > > timedelta _ seconds ( timedelta ( hours = - 1 ) ) -3600 > > > timedelta _ seconds ( timedelta ( hours = 1 , minutes = 30 ) ) 5400 > > > timedelta _ seconds ( timedelta ( hours = 1 , minutes = 30, . . . microseconds = 300000 ) ) 5400 > > > timedelta _ seconds ( timedelta ( hours = 1 , minutes = 30, . . . microseconds = 900000 ) ) 5401'''
try : return int ( round ( td . total_seconds ( ) ) ) except AttributeError : days = td . days seconds = td . seconds microseconds = td . microseconds return int ( round ( ( days * 86400 ) + seconds + ( microseconds / 1000000 ) ) )
def _set_policy ( self , v , load = False ) : """Setter method for policy , mapped from YANG variable / rbridge _ id / maps / policy ( list ) If this variable is read - only ( config : false ) in the source YANG file , then _ set _ policy is considered as a private method . Backends looking to populate this variable should do so via calling thisObj . _ set _ policy ( ) directly ."""
if hasattr ( v , "_utype" ) : v = v . _utype ( v ) try : t = YANGDynClass ( v , base = YANGListType ( "policyname" , policy . policy , yang_name = "policy" , rest_name = "policy" , parent = self , is_container = 'list' , user_ordered = False , path_helper = self . _path_helper , yang_keys = 'policyname' , extensions = { u'tailf-common' : { u'info' : u'Configure Policy' , u'callpoint' : u'MapsPolicy' } } ) , is_container = 'list' , yang_name = "policy" , rest_name = "policy" , parent = self , path_helper = self . _path_helper , extmethods = self . _extmethods , register_paths = True , extensions = { u'tailf-common' : { u'info' : u'Configure Policy' , u'callpoint' : u'MapsPolicy' } } , namespace = 'urn:brocade.com:mgmt:brocade-maps' , defining_module = 'brocade-maps' , yang_type = 'list' , is_config = True ) except ( TypeError , ValueError ) : raise ValueError ( { 'error-string' : """policy must be of a type compatible with list""" , 'defined-type' : "list" , 'generated-type' : """YANGDynClass(base=YANGListType("policyname",policy.policy, yang_name="policy", rest_name="policy", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='policyname', extensions={u'tailf-common': {u'info': u'Configure Policy', u'callpoint': u'MapsPolicy'}}), is_container='list', yang_name="policy", rest_name="policy", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Configure Policy', u'callpoint': u'MapsPolicy'}}, namespace='urn:brocade.com:mgmt:brocade-maps', defining_module='brocade-maps', yang_type='list', is_config=True)""" , } ) self . __policy = t if hasattr ( self , '_set' ) : self . _set ( )
def manage_mep ( self , mep_json ) : '''Import a mep as a representative from the json dict fetched from parltrack'''
# Some versions of memopol will connect to this and skip inactive meps . responses = representative_pre_import . send ( sender = self , representative_data = mep_json ) for receiver , response in responses : if response is False : logger . debug ( 'Skipping MEP %s' , mep_json [ 'Name' ] [ 'full' ] ) return changed = False slug = slugify ( '%s-%s' % ( mep_json [ "Name" ] [ "full" ] if 'full' in mep_json [ "Name" ] else mep_json [ "Name" ] [ "sur" ] + " " + mep_json [ "Name" ] [ "family" ] , _parse_date ( mep_json [ "Birth" ] [ "date" ] ) ) ) try : representative = Representative . objects . get ( slug = slug ) except Representative . DoesNotExist : representative = Representative ( slug = slug ) changed = True # Save representative attributes self . import_representative_details ( representative , mep_json , changed ) self . add_mandates ( representative , mep_json ) self . add_contacts ( representative , mep_json ) logger . debug ( 'Imported MEP %s' , unicode ( representative ) ) return representative
def name ( self ) : """Return the person ' s name . If we have special titles , use them , otherwise , don ' t include the title ."""
if self . title in [ "DR" , "SIR" , "LORD" ] : return "%s %s %s" % ( self . get_title_display ( ) , self . first_name , self . last_name ) else : return "%s %s" % ( self . first_name , self . last_name )
def acls ( name , acls , version = - 1 , profile = None , hosts = None , scheme = None , username = None , password = None , default_acl = None ) : '''Update acls on a znode name path to znode acls list of acl dictionaries to set on znode version Specify the version which should be deleted Default : - 1 ( always match ) profile Configured Zookeeper profile to authenticate with ( Default : None ) hosts Lists of Zookeeper Hosts ( Default : ' 127.0.0.1:2181) scheme Scheme to authenticate with ( Default : ' digest ' ) username Username to authenticate ( Default : None ) password Password to authenticate ( Default : None ) default _ acl Default acls to assign if a node is created in this connection ( Default : None ) . . code - block : : yaml update acls : zookeeper . acls : - name : / test / name - acls : - username : daniel password : test all : True - username : gtmanfred password : test all : True'''
ret = { 'name' : name , 'result' : False , 'comment' : 'Failed to set acls on znode {0}' . format ( name ) , 'changes' : { } } connkwargs = { 'profile' : profile , 'hosts' : hosts , 'scheme' : scheme , 'username' : username , 'password' : password , 'default_acl' : default_acl } if isinstance ( acls , dict ) : acls = [ acls ] chk_acls = [ __salt__ [ 'zookeeper.make_digest_acl' ] ( ** acl ) for acl in acls ] if not __salt__ [ 'zookeeper.exists' ] ( name , ** connkwargs ) : ret [ 'comment' ] += ': Znode does not exist' return ret cur_acls = __salt__ [ 'zookeeper.get_acls' ] ( name , ** connkwargs ) if _check_acls ( cur_acls , chk_acls ) : ret [ 'result' ] = True ret [ 'comment' ] = 'Znode {0} acls already set' . format ( name ) return ret if __opts__ [ 'test' ] is True : ret [ 'result' ] = None ret [ 'comment' ] = 'Znode {0} acls will be updated' . format ( name ) ret [ 'changes' ] [ 'old' ] = cur_acls ret [ 'changes' ] [ 'new' ] = chk_acls return ret __salt__ [ 'zookeeper.set_acls' ] ( name , acls , version , ** connkwargs ) new_acls = __salt__ [ 'zookeeper.get_acls' ] ( name , ** connkwargs ) ret [ 'changes' ] = { 'old' : cur_acls , 'new' : new_acls } if _check_acls ( new_acls , chk_acls ) : ret [ 'result' ] = True ret [ 'comment' ] = 'Znode {0} acls updated' . format ( name ) return ret ret [ 'comment' ] = 'Znode {0} acls failed to update' . format ( name ) return ret
def bind_proxy ( self , name , proxy ) : """Adds a mask that maps to a given proxy ."""
if not len ( name ) or name [ 0 ] != '/' or name [ - 1 ] != '/' : raise ValueError ( "name must start and end with '/': {0}" . format ( name ) ) self . _folder_proxys . insert ( 0 , ( name , proxy ) )
def get_waveform_filter_length_in_time ( approximant , template = None , ** kwargs ) : """For filter templates , return the length in time of the template ."""
kwargs = props ( template , ** kwargs ) if approximant in _filter_time_lengths : return _filter_time_lengths [ approximant ] ( ** kwargs ) else : return None
def tree_build ( self ) : """Build a tree from the taxonomy data present in this ` ClassificationsDataFrame ` or ` SampleCollection ` . Returns ` skbio . tree . TreeNode ` , the root node of a tree that contains all the taxa in the current analysis and their parents leading back to the root node ."""
from skbio . tree import TreeNode # build all the nodes nodes = { } for tax_id in self . taxonomy . index : node = TreeNode ( name = tax_id , length = 1 ) node . tax_name = self . taxonomy [ "name" ] [ tax_id ] node . rank = self . taxonomy [ "rank" ] [ tax_id ] node . parent_tax_id = self . taxonomy [ "parent_tax_id" ] [ tax_id ] nodes [ tax_id ] = node # generate all the links for tax_id in self . taxonomy . index : try : parent = nodes [ nodes [ tax_id ] . parent_tax_id ] except KeyError : if tax_id != "1" : warnings . warn ( "tax_id={} has parent_tax_id={} which is not in tree" "" . format ( tax_id , nodes [ tax_id ] . parent_tax_id ) ) continue parent . append ( nodes [ tax_id ] ) return nodes [ "1" ]
def issue_section ( issue ) : """Returns the section heading for the issue , or None if this issue should be ignored ."""
labels = issue . get ( 'labels' , [ ] ) for label in labels : if not label [ 'name' ] . startswith ( 'type: ' ) : continue if label [ 'name' ] in LOG_SECTION : return LOG_SECTION [ label [ 'name' ] ] elif label [ 'name' ] in IGNORE_ISSUE_TYPE : return None else : logging . warning ( 'unknown issue type: "{}" for: {}' . format ( label [ 'name' ] , issue_line ( issue ) ) ) return None
def get_client ( self , client_type ) : """GetClient . [ Preview API ] Get the client package . : param str client _ type : Either " EXE " for a zip file containing a Windows symbol client ( a . k . a . symbol . exe ) along with dependencies , or " TASK " for a VSTS task that can be run on a VSTS build agent . All the other values are invalid . The parameter is case - insensitive . : rtype : object"""
route_values = { } if client_type is not None : route_values [ 'clientType' ] = self . _serialize . url ( 'client_type' , client_type , 'str' ) response = self . _send ( http_method = 'GET' , location_id = '79c83865-4de3-460c-8a16-01be238e0818' , version = '5.0-preview.1' , route_values = route_values ) return self . _deserialize ( 'object' , response )
def almost_equals ( self , other , e = 0.000001 ) : '''Sometimes required for comparing GeoVectors if float error has occurred . Determine if self and other ( another GeoVector ) are equal to within e km of each other in dx and dy . The default ( e = 0.000001 ) will return True if self and other are less than 1 mm apart in distance .'''
return abs ( self . dx - other . dx ) < e and abs ( self . dy - other . dy ) < e
def _get_memory_bank_size ( memBank ) : """Get the size of a memory bank in bytes ."""
fileName = '/sys/devices/system/node/node{0}/meminfo' . format ( memBank ) size = None with open ( fileName ) as f : for line in f : if 'MemTotal' in line : size = line . split ( ':' ) [ 1 ] . strip ( ) if size [ - 3 : ] != ' kB' : raise ValueError ( '"{}" in file {} is not a memory size.' . format ( size , fileName ) ) size = int ( size [ : - 3 ] ) * 1024 # kernel uses KiB but names them kB , convert to Byte logging . debug ( "Memory bank %s has size %s bytes." , memBank , size ) return size raise ValueError ( 'Failed to read total memory from {}.' . format ( fileName ) )
def is_rfc1918 ( ip ) : """Checks to see if an IP address is used for local communications within a private network as specified by RFC 1918"""
if ip_between ( ip , "10.0.0.0" , "10.255.255.255" ) : return True elif ip_between ( ip , "172.16.0.0" , "172.31.255.255" ) : return True elif ip_between ( ip , "192.168.0.0" , "192.168.255.255" ) : return True else : return False
def _vmomentsurfacemass ( self , R , n , m , romberg = False , nsigma = None , relative = False , phi = 0. , deriv = None ) : """Non - physical version of vmomentsurfacemass , otherwise the same"""
# odd moments of vR are zero if isinstance ( n , int ) and n % 2 == 1 : return 0. if nsigma == None : nsigma = _NSIGMA logSigmaR = self . targetSurfacemass ( R , log = True , use_physical = False ) sigmaR2 = self . targetSigma2 ( R , use_physical = False ) sigmaR1 = sc . sqrt ( sigmaR2 ) logsigmaR2 = sc . log ( sigmaR2 ) if relative : norm = 1. else : norm = sc . exp ( logSigmaR + logsigmaR2 * ( n + m ) / 2. ) / self . _gamma ** m # Use the asymmetric drift equation to estimate va va = sigmaR2 / 2. / R ** self . _beta * ( 1. / self . _gamma ** 2. - 1. - R * self . _surfaceSigmaProfile . surfacemassDerivative ( R , log = True ) - R * self . _surfaceSigmaProfile . sigma2Derivative ( R , log = True ) ) if math . fabs ( va ) > sigmaR1 : va = 0. # To avoid craziness near the center if deriv is None : if romberg : return sc . real ( bovy_dblquad ( _vmomentsurfaceIntegrand , self . _gamma * ( R ** self . _beta - va ) / sigmaR1 - nsigma , self . _gamma * ( R ** self . _beta - va ) / sigmaR1 + nsigma , lambda x : - nsigma , lambda x : nsigma , [ R , self , logSigmaR , logsigmaR2 , sigmaR1 , self . _gamma , n , m ] , tol = 10. ** - 8 ) / sc . pi * norm / 2. ) else : return integrate . dblquad ( _vmomentsurfaceIntegrand , self . _gamma * ( R ** self . _beta - va ) / sigmaR1 - nsigma , self . _gamma * ( R ** self . _beta - va ) / sigmaR1 + nsigma , lambda x : - nsigma , lambda x : nsigma , ( R , self , logSigmaR , logsigmaR2 , sigmaR1 , self . _gamma , n , m ) , epsrel = _EPSREL ) [ 0 ] / sc . pi * norm / 2. else : if romberg : return sc . real ( bovy_dblquad ( _vmomentderivsurfaceIntegrand , self . _gamma * ( R ** self . _beta - va ) / sigmaR1 - nsigma , self . _gamma * ( R ** self . _beta - va ) / sigmaR1 + nsigma , lambda x : - nsigma , lambda x : nsigma , [ R , self , logSigmaR , logsigmaR2 , sigmaR1 , self . _gamma , n , m , deriv ] , tol = 10. ** - 8 ) / sc . pi * norm / 2. ) else : return integrate . dblquad ( _vmomentderivsurfaceIntegrand , self . _gamma * ( R ** self . _beta - va ) / sigmaR1 - nsigma , self . _gamma * ( R ** self . _beta - va ) / sigmaR1 + nsigma , lambda x : - nsigma , lambda x : nsigma , ( R , self , logSigmaR , logsigmaR2 , sigmaR1 , self . _gamma , n , m , deriv ) , epsrel = _EPSREL ) [ 0 ] / sc . pi * norm / 2.
def validate_args_and_kwargs ( fname , args , kwargs , max_fname_arg_count , compat_args ) : """Checks whether parameters passed to the * args and * * kwargs argument in a function ` fname ` are valid parameters as specified in ` * compat _ args ` and whether or not they are set to their default values . Parameters fname : str The name of the function being passed the ` * * kwargs ` parameter args : tuple The ` * args ` parameter passed into a function kwargs : dict The ` * * kwargs ` parameter passed into ` fname ` max _ fname _ arg _ count : int The minimum number of arguments that the function ` fname ` requires , excluding those in ` args ` . Used for displaying appropriate error messages . Must be non - negative . compat _ args : OrderedDict A ordered dictionary of keys that ` kwargs ` is allowed to have and their associated default values . Note that if there is only one key , a generic dict can be passed in as well . Raises TypeError if ` args ` contains more values than there are ` compat _ args ` OR ` kwargs ` contains keys not in ` compat _ args ` ValueError if ` args ` contains values not at the default value ( ` None ` ) ` kwargs ` contains keys in ` compat _ args ` that do not map to the default value as specified in ` compat _ args ` See Also validate _ args : Purely args validation . validate _ kwargs : Purely kwargs validation ."""
# Check that the total number of arguments passed in ( i . e . # args and kwargs ) does not exceed the length of compat _ args _check_arg_length ( fname , args + tuple ( kwargs . values ( ) ) , max_fname_arg_count , compat_args ) # Check there is no overlap with the positional and keyword # arguments , similar to what is done in actual Python functions args_dict = dict ( zip ( compat_args , args ) ) for key in args_dict : if key in kwargs : raise TypeError ( "{fname}() got multiple values for keyword " "argument '{arg}'" . format ( fname = fname , arg = key ) ) kwargs . update ( args_dict ) validate_kwargs ( fname , kwargs , compat_args )
def flatten ( nested_list ) : '''converts a list - of - lists to a single flat list'''
return_list = [ ] for i in nested_list : if isinstance ( i , list ) : return_list += flatten ( i ) else : return_list . append ( i ) return return_list
def init_static_field ( state , field_class_name , field_name , field_type ) : """Initialize the static field with an allocated , but not initialized , object of the given type . : param state : State associated to the field . : param field _ class _ name : Class containing the field . : param field _ name : Name of the field . : param field _ type : Type of the field and the new object ."""
field_ref = SimSootValue_StaticFieldRef . get_ref ( state , field_class_name , field_name , field_type ) field_val = SimSootValue_ThisRef . new_object ( state , field_type ) state . memory . store ( field_ref , field_val )
def _match_iter_generic ( self , path_elements , start_at ) : """Implementation of match _ iter for > 1 self . elements"""
length = len ( path_elements ) # If bound to start , we stop searching at the first element if self . bound_start : end = 1 else : end = length - self . length + 1 # If bound to end , we start searching as late as possible if self . bound_end : start = length - self . length else : start = start_at if start > end or start < start_at or end > length - self . length + 1 : # It ' s impossible to match . Either # 1 ) the search has a fixed start and end , and path _ elements # does not have enough elements for a match , or # 2 ) To match the bound _ end , we have to start before the start _ at , # which means the search is impossible # 3 ) The end is after the last possible end point in path _ elements return for index in range ( start , end ) : matched = True i = index for matcher in self . elements : element = path_elements [ i ] i += 1 if not matcher . match ( element ) : matched = False break if matched : yield index + self . length
def parse ( self , lines ) : '''Parse signature file lines . @ lines - A list of lines from a signature file . Returns None .'''
signature = None for line in lines : # Split at the first comment delimiter ( if any ) and strip the # result line = line . split ( '#' ) [ 0 ] . strip ( ) # Ignore blank lines and lines that are nothing but comments . # We also don ' t support the ' ! mime ' style line entries . if line and line [ 0 ] != '!' : # Parse this signature line sigline = SignatureLine ( line ) # Level 0 means the first line of a signature entry if sigline . level == 0 : # If there is an existing signature , append it to the signature list , # unless the text in its title field has been filtered by user - defined # filter rules . if signature and not self . _filtered ( signature . title ) : self . signatures . append ( signature ) # Create a new signature object ; use the size of self . signatures to # assign each signature a unique ID . signature = Signature ( len ( self . signatures ) , sigline ) # Else , just append this line to the existing signature elif signature : # signature . append ( sigline ) signature . lines . append ( sigline ) # If this is not the first line of a signature entry and there is no other # existing signature entry , something is very wrong with the # signature file . else : raise ParserException ( "Invalid signature line: '%s'" % line ) # Add the final signature to the signature list if signature : if not self . _filtered ( signature . lines [ 0 ] . format ) : self . signatures . append ( signature ) # Sort signatures by confidence ( aka , length of their magic bytes ) , # largest first self . signatures . sort ( key = lambda x : x . confidence , reverse = True )
def _load_url ( url ) : """Loads a URL resource from a remote server"""
try : response = requests . get ( url ) return BytesIO ( response . content ) except IOError as ex : parser . error ( "{url} could not be loaded remotely! ({ex})" . format ( url = url , ex = ex ) )
def get_activities ( self ) : """Gets all ` ` Activities ` ` . In plenary mode , the returned list contains all known activites or an error results . Otherwise , the returned list may contain only those activities that are accessible through this session . return : ( osid . learning . ActivityList ) - a ` ` ActivityList ` ` raise : OperationFailed - unable to complete request raise : PermissionDenied - authorization failure * compliance : mandatory - - This method must be implemented . *"""
# Implemented from template for # osid . resource . ResourceLookupSession . get _ resources # NOTE : This implementation currently ignores plenary view collection = JSONClientValidated ( 'learning' , collection = 'Activity' , runtime = self . _runtime ) result = collection . find ( self . _view_filter ( ) ) . sort ( '_id' , DESCENDING ) return objects . ActivityList ( result , runtime = self . _runtime , proxy = self . _proxy )
def predict_is ( self , h = 5 , fit_once = True , fit_method = 'MLE' , intervals = False , ** kwargs ) : """Makes dynamic in - sample predictions with the estimated model Parameters h : int ( default : 5) How many steps would you like to forecast ? fit _ once : boolean ( default : True ) Fits only once before the in - sample prediction ; if False , fits after every new datapoint fit _ method : string Which method to fit the model with intervals : boolean Whether to return prediction intervals Returns - pd . DataFrame with predicted values"""
predictions = [ ] for t in range ( 0 , h ) : x = GARCH ( p = self . p , q = self . q , data = self . data [ 0 : - h + t ] ) if fit_once is False : x . fit ( method = fit_method , printer = False ) if t == 0 : if fit_once is True : x . fit ( method = fit_method , printer = False ) saved_lvs = x . latent_variables predictions = x . predict ( 1 , intervals = intervals ) else : if fit_once is True : x . latent_variables = saved_lvs predictions = pd . concat ( [ predictions , x . predict ( 1 , intervals = intervals ) ] ) if intervals is True : predictions . rename ( columns = { 0 : self . data_name , 1 : "1% Prediction Interval" , 2 : "5% Prediction Interval" , 3 : "95% Prediction Interval" , 4 : "99% Prediction Interval" } , inplace = True ) else : predictions . rename ( columns = { 0 : self . data_name } , inplace = True ) predictions . index = self . index [ - h : ] return predictions
def serialize_header ( self , pyobj , typecode = None , ** kw ) : '''Serialize a Python object in SOAP - ENV : Header , make sure everything in Header unique ( no # href ) . Must call serialize first to create a document . Parameters : pyobjs - - instances to serialize in SOAP Header typecode - - default typecode'''
kw [ 'unique' ] = True soap_env = _reserved_ns [ 'SOAP-ENV' ] # header = self . dom . getElement ( soap _ env , ' Header ' ) header = self . _header if header is None : header = self . _header = self . dom . createAppendElement ( soap_env , 'Header' ) typecode = getattr ( pyobj , 'typecode' , typecode ) if typecode is None : raise RuntimeError ( 'typecode is required to serialize pyobj in header' ) helt = typecode . serialize ( header , self , pyobj , ** kw )
def _format_device ( var ) : """Returns the device with an annotation specifying ` ResourceVariable ` . " legacy " means a normal tf . Variable while " resource " means a ResourceVariable . For example : ` ( legacy ) ` ` ( resource ) ` ` / job : learner / task : 0 / device : CPU : * ( legacy ) ` ` / job : learner / task : 0 / device : CPU : * ( resource ) ` Args : var : The Tensorflow Variable to print ."""
if var . dtype . name . endswith ( "_ref" ) : resource_var_annotation = "(legacy)" else : resource_var_annotation = "(resource)" if var . device : return "{} {}" . format ( var . device , resource_var_annotation ) else : return resource_var_annotation