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def _validate_information ( self ) : """Validate that all information has been filled in"""
needed_variables = [ "ModuleName" , "ModuleVersion" , "APIVersion" ] for var in needed_variables : if var not in self . variables : raise DataError ( "Needed variable was not defined in mib file." , variable = var ) # Make sure ModuleName is < = 6 characters if len ( self . variables [ "ModuleName" ] ) > 6 : raise DataError ( "ModuleName too long, must be 6 or fewer characters." , module_name = self . variables [ "ModuleName" ] ) if not isinstance ( self . variables [ "ModuleVersion" ] , str ) : raise ValueError ( "ModuleVersion ('%s') must be a string of the form X.Y.Z" % str ( self . variables [ 'ModuleVersion' ] ) ) if not isinstance ( self . variables [ "APIVersion" ] , str ) : raise ValueError ( "APIVersion ('%s') must be a string of the form X.Y" % str ( self . variables [ 'APIVersion' ] ) ) self . variables [ 'ModuleVersion' ] = self . _convert_module_version ( self . variables [ "ModuleVersion" ] ) self . variables [ 'APIVersion' ] = self . _convert_api_version ( self . variables [ "APIVersion" ] ) self . variables [ "ModuleName" ] = self . variables [ "ModuleName" ] . ljust ( 6 ) self . valid = True
def visit_Call ( self , node ) : """Call visitor - used for finding setup ( ) call ."""
self . generic_visit ( node ) # Setup ( ) is a keywords - only function . if node . args : return keywords = set ( ) for k in node . keywords : if k . arg is not None : keywords . add ( k . arg ) # Simple case for dictionary expansion for Python > = 3.5. if k . arg is None and isinstance ( k . value , ast . Dict ) : keywords . update ( x . s for x in k . value . keys ) # Simple case for dictionary expansion for Python < = 3.4. if getattr ( node , 'kwargs' , ( ) ) and isinstance ( node . kwargs , ast . Dict ) : keywords . update ( x . s for x in node . kwargs . keys ) # The bare minimum number of arguments seems to be around five , which # includes author , name , version , module / package and something extra . if len ( keywords ) < 5 : return score = sum ( self . attributes . get ( x , 0 ) for x in keywords ) / len ( keywords ) if score < 0.5 : LOG . debug ( "Scoring for setup%r below 0.5: %.2f" , tuple ( keywords ) , score ) return # Redirect call to our setup ( ) tap function . node . func = ast . Name ( id = '__f8r_setup' , ctx = node . func . ctx ) self . redirected = True
def settings ( ** kwargs ) : """Generally , this will automatically be added to a newly initialized : class : ` phoebe . frontend . bundle . Bundle ` : parameter * * kwargs : defaults for the values of any of the parameters : return : a : class : ` phoebe . parameters . parameters . ParameterSet ` of all newly created : class : ` phoebe . parameters . parameters . Parameter ` s"""
params = [ ] params += [ StringParameter ( qualifier = 'phoebe_version' , value = kwargs . get ( 'phoebe_version' , __version__ ) , description = 'Version of PHOEBE - change with caution' ) ] params += [ BoolParameter ( qualifier = 'log_history' , value = kwargs . get ( 'log_history' , False ) , description = 'Whether to log history (undo/redo)' ) ] params += [ DictParameter ( qualifier = 'dict_filter' , value = kwargs . get ( 'dict_filter' , { } ) , description = 'Filters to use when using dictionary access' ) ] params += [ BoolParameter ( qualifier = 'dict_set_all' , value = kwargs . get ( 'dict_set_all' , False ) , description = 'Whether to set all values for dictionary access that returns more than 1 result' ) ] # params + = [ ChoiceParameter ( qualifier = ' plotting _ backend ' , value = kwargs . get ( ' plotting _ backend ' , ' mpl ' ) , choices = [ ' mpl ' , ' mpld3 ' , ' mpl2bokeh ' , ' bokeh ' ] if conf . devel else [ ' mpl ' ] , description = ' Default backend to use for plotting ' ) ] # problem with try _ sympy parameter : it can ' t be used during initialization . . . so this may need to be a phoebe - level setting # params + = [ BoolParameter ( qualifier = ' try _ sympy ' , value = kwargs . get ( ' try _ sympy ' , True ) , description = ' Whether to use sympy if installed for constraints ' ) ] # This could be complicated - because then we ' ll have to specifically watch to see when its enabled and then run all constraints - not sure if that is worth the time savings # params + = [ BoolParameter ( qualifier = ' run _ constraints ' , value = kwargs . get ( ' run _ constraints ' , True ) , description = ' Whether to run _ constraints whenever a parameter changes ( warning : turning off will disable constraints until enabled at which point all constraints will be run ) ' ) ] return ParameterSet ( params )
def show ( config_file = False ) : '''Return a list of sysctl parameters for this minion CLI Example : . . code - block : : bash salt ' * ' sysctl . show'''
roots = ( 'compat' , 'debug' , 'dev' , 'hptmv' , 'hw' , 'kern' , 'machdep' , 'net' , 'p1003_1b' , 'security' , 'user' , 'vfs' , 'vm' ) cmd = 'sysctl -ae' ret = { } comps = [ '' ] if config_file : # If the file doesn ' t exist , return an empty list if not os . path . exists ( config_file ) : return [ ] try : with salt . utils . files . fopen ( config_file , 'r' ) as f : for line in f . readlines ( ) : l = line . strip ( ) if l != "" and not l . startswith ( "#" ) : comps = line . split ( '=' , 1 ) ret [ comps [ 0 ] ] = comps [ 1 ] return ret except ( OSError , IOError ) : log . error ( 'Could not open sysctl config file' ) return None else : out = __salt__ [ 'cmd.run' ] ( cmd , output_loglevel = 'trace' ) for line in out . splitlines ( ) : if any ( [ line . startswith ( '{0}.' . format ( root ) ) for root in roots ] ) : comps = line . split ( '=' , 1 ) ret [ comps [ 0 ] ] = comps [ 1 ] elif comps [ 0 ] : ret [ comps [ 0 ] ] += '{0}\n' . format ( line ) else : continue return ret
def _get_device_names_in_group ( self ) : '''_ get _ device _ names _ in _ group : returns : list - - list of device names in group'''
device_names = [ ] dg = pollster ( self . _get_device_group ) ( self . devices [ 0 ] ) members = dg . devices_s . get_collection ( ) for member in members : member_name = member . name . replace ( '/%s/' % self . partition , '' ) device_names . append ( member_name ) return device_names
def _open_archive ( path ) : """: param path : A unicode string of the filesystem path to the archive : return : An archive object"""
if path . endswith ( '.zip' ) : return zipfile . ZipFile ( path , 'r' ) return tarfile . open ( path , 'r' )
def _refresh_url ( self ) : """刷新获取 url , 失败的时候返回空而不是 None"""
songs = self . _api . weapi_songs_url ( [ int ( self . identifier ) ] ) if songs and songs [ 0 ] [ 'url' ] : self . url = songs [ 0 ] [ 'url' ] else : self . url = ''
def tospark ( self , engine = None ) : """Convert to spark mode ."""
from thunder . series . readers import fromarray if self . mode == 'spark' : logging . getLogger ( 'thunder' ) . warn ( 'images already in local mode' ) pass if engine is None : raise ValueError ( 'Must provide SparkContext' ) return fromarray ( self . toarray ( ) , index = self . index , labels = self . labels , engine = engine )
def get_tag ( self , el ) : """Get tag ."""
name = self . get_tag_name ( el ) return util . lower ( name ) if name is not None and not self . is_xml else name
async def listHooks ( self , * args , ** kwargs ) : """List hooks in a given group This endpoint will return a list of all the hook definitions within a given hook group . This method gives output : ` ` v1 / list - hooks - response . json # ` ` This method is ` ` stable ` `"""
return await self . _makeApiCall ( self . funcinfo [ "listHooks" ] , * args , ** kwargs )
def smart_initialize ( self ) : '''Use k - means + + to initialize a good set of centroids'''
if self . seed is not None : # useful for obtaining consistent results np . random . seed ( self . seed ) centroids = np . zeros ( ( self . k , self . data . shape [ 1 ] ) ) # Randomly choose the first centroid . # Since we have no prior knowledge , choose uniformly at random idx = np . random . randint ( self . data . shape [ 0 ] ) centroids [ 0 ] = self . data [ idx , : ] . toarray ( ) # Compute distances from the first centroid chosen to all the other data points squared_distances = pairwise_distances ( self . data , centroids [ 0 : 1 ] , metric = 'euclidean' ) . flatten ( ) ** 2 for i in range ( 1 , self . k ) : # Choose the next centroid randomly , so that the probability for each data point to be chosen # is directly proportional to its squared distance from the nearest centroid . # Roughtly speaking , a new centroid should be as far as from ohter centroids as possible . idx = np . random . choice ( self . data . shape [ 0 ] , 1 , p = squared_distances / sum ( squared_distances ) ) centroids [ i ] = self . data [ idx , : ] . toarray ( ) # Now compute distances from the centroids to all data points squared_distances = np . min ( pairwise_distances ( self . data , centroids [ 0 : i + 1 ] , metric = 'euclidean' ) ** 2 , axis = 1 ) self . centroids = centroids return centroids
def _mirror_groups ( self ) : """Mirrors the user ' s LDAP groups in the Django database and updates the user ' s membership ."""
target_group_names = frozenset ( self . _get_groups ( ) . get_group_names ( ) ) current_group_names = frozenset ( self . _user . groups . values_list ( "name" , flat = True ) . iterator ( ) ) # These were normalized to sets above . MIRROR_GROUPS_EXCEPT = self . settings . MIRROR_GROUPS_EXCEPT MIRROR_GROUPS = self . settings . MIRROR_GROUPS # If the settings are white - or black - listing groups , we ' ll update # target _ group _ names such that we won ' t modify the membership of groups # beyond our purview . if isinstance ( MIRROR_GROUPS_EXCEPT , ( set , frozenset ) ) : target_group_names = ( target_group_names - MIRROR_GROUPS_EXCEPT ) | ( current_group_names & MIRROR_GROUPS_EXCEPT ) elif isinstance ( MIRROR_GROUPS , ( set , frozenset ) ) : target_group_names = ( target_group_names & MIRROR_GROUPS ) | ( current_group_names - MIRROR_GROUPS ) if target_group_names != current_group_names : existing_groups = list ( Group . objects . filter ( name__in = target_group_names ) . iterator ( ) ) existing_group_names = frozenset ( group . name for group in existing_groups ) new_groups = [ Group . objects . get_or_create ( name = name ) [ 0 ] for name in target_group_names if name not in existing_group_names ] self . _user . groups . set ( existing_groups + new_groups )
def _is_vis ( channel ) : """Determine whether the given channel is a visible channel"""
if isinstance ( channel , str ) : return channel == '00_7' elif isinstance ( channel , int ) : return channel == 1 else : raise ValueError ( 'Invalid channel' )
def insert ( key , value ) : """Store a value with a key . If the key is already present in the database , this does nothing ."""
# Pickle the value . value = pickle . dumps ( value , protocol = constants . PICKLE_PROTOCOL ) # Store the value as binary data in a document . doc = { KEY_FIELD : key , VALUE_FIELD : Binary ( value ) } # Pickle and store the value with its key . If the key already exists , we # don ' t insert ( since the key is a unique index ) , and we don ' t care . try : return collection . insert ( doc ) except pymongo . errors . DuplicateKeyError : return None
def cli_verify_jar_signature ( argument_list ) : """Command - line wrapper around verify ( ) TODO : use trusted keystore ;"""
usage_message = "jarutil v file.jar trusted_certificate.pem [SF_NAME.SF]" if len ( argument_list ) < 2 or len ( argument_list ) > 3 : print ( usage_message ) return 1 jar_file , certificate , sf_name = ( argument_list + [ None ] ) [ : 3 ] try : verify ( certificate , jar_file , sf_name ) except VerificationError as error_message : print ( error_message ) return 1 else : print ( "Jar verified." ) return 0
def _set_description ( self , schema ) : """Set description from schema . : type schema : Sequence [ google . cloud . bigquery . schema . SchemaField ] : param schema : A description of fields in the schema ."""
if schema is None : self . description = None return self . description = tuple ( [ Column ( name = field . name , type_code = field . field_type , display_size = None , internal_size = None , precision = None , scale = None , null_ok = field . is_nullable , ) for field in schema ] )
def append_line ( self , new_line ) : """Appends the new _ line to the LS340 program ."""
# TODO : The user still has to write the raw line , this is error prone . self . _write ( ( 'PGM' , [ Integer , String ] ) , self . idx , new_line )
def resolve_reference ( target_reference , project ) : """Given a target _ reference , made in context of ' project ' , returns the AbstractTarget instance that is referred to , as well as properties explicitly specified for this reference ."""
# Separate target name from properties override assert isinstance ( target_reference , basestring ) assert isinstance ( project , ProjectTarget ) split = _re_separate_target_from_properties . match ( target_reference ) if not split : raise BaseException ( "Invalid reference: '%s'" % target_reference ) id = split . group ( 1 ) sproperties = [ ] if split . group ( 3 ) : sproperties = property . create_from_strings ( feature . split ( split . group ( 3 ) ) ) sproperties = feature . expand_composites ( sproperties ) # Find the target target = project . find ( id ) return ( target , property_set . create ( sproperties ) )
def add_comment ( self , app_id , record_id , field_id , message ) : """Directly add a comment to a record without retrieving the app or record first Warnings : Does not perform any app , record , or field ID validation Args : app _ id ( str ) : Full App ID string record _ id ( str ) : Full parent Record ID string field _ id ( str ) : Full field ID to target reference field on parent Record string message ( str ) : New comment message body"""
self . _swimlane . request ( 'post' , 'app/{0}/record/{1}/{2}/comment' . format ( app_id , record_id , field_id ) , json = { 'message' : message , 'createdDate' : pendulum . now ( ) . to_rfc3339_string ( ) } )
def _set_people ( self , people ) : """Sets who the object is sent to"""
if hasattr ( people , "object_type" ) : people = [ people ] elif hasattr ( people , "__iter__" ) : people = list ( people ) return people
def convert_time_string ( date_str ) : """Change a date string from the format 2018-08-15T23:55:17 into a datetime object"""
dt , _ , _ = date_str . partition ( "." ) dt = datetime . strptime ( dt , "%Y-%m-%dT%H:%M:%S" ) return dt
def phi4 ( gold_clustering , predicted_clustering ) : """Subroutine for ceafe . Computes the mention F measure between gold and predicted mentions in a cluster ."""
return 2 * len ( [ mention for mention in gold_clustering if mention in predicted_clustering ] ) / float ( len ( gold_clustering ) + len ( predicted_clustering ) )
def _build_likelihood ( self ) : """Construct a tensorflow function to compute the bound on the marginal likelihood ."""
pX = DiagonalGaussian ( self . X_mean , self . X_var ) num_inducing = len ( self . feature ) psi0 = tf . reduce_sum ( expectation ( pX , self . kern ) ) psi1 = expectation ( pX , ( self . kern , self . feature ) ) psi2 = tf . reduce_sum ( expectation ( pX , ( self . kern , self . feature ) , ( self . kern , self . feature ) ) , axis = 0 ) Kuu = features . Kuu ( self . feature , self . kern , jitter = settings . jitter ) L = tf . cholesky ( Kuu ) sigma2 = self . likelihood . variance sigma = tf . sqrt ( sigma2 ) # Compute intermediate matrices A = tf . matrix_triangular_solve ( L , tf . transpose ( psi1 ) , lower = True ) / sigma tmp = tf . matrix_triangular_solve ( L , psi2 , lower = True ) AAT = tf . matrix_triangular_solve ( L , tf . transpose ( tmp ) , lower = True ) / sigma2 B = AAT + tf . eye ( num_inducing , dtype = settings . float_type ) LB = tf . cholesky ( B ) log_det_B = 2. * tf . reduce_sum ( tf . log ( tf . matrix_diag_part ( LB ) ) ) c = tf . matrix_triangular_solve ( LB , tf . matmul ( A , self . Y ) , lower = True ) / sigma # KL [ q ( x ) | | p ( x ) ] dX_var = self . X_var if len ( self . X_var . get_shape ( ) ) == 2 else tf . matrix_diag_part ( self . X_var ) NQ = tf . cast ( tf . size ( self . X_mean ) , settings . float_type ) D = tf . cast ( tf . shape ( self . Y ) [ 1 ] , settings . float_type ) KL = - 0.5 * tf . reduce_sum ( tf . log ( dX_var ) ) + 0.5 * tf . reduce_sum ( tf . log ( self . X_prior_var ) ) - 0.5 * NQ + 0.5 * tf . reduce_sum ( ( tf . square ( self . X_mean - self . X_prior_mean ) + dX_var ) / self . X_prior_var ) # compute log marginal bound ND = tf . cast ( tf . size ( self . Y ) , settings . float_type ) bound = - 0.5 * ND * tf . log ( 2 * np . pi * sigma2 ) bound += - 0.5 * D * log_det_B bound += - 0.5 * tf . reduce_sum ( tf . square ( self . Y ) ) / sigma2 bound += 0.5 * tf . reduce_sum ( tf . square ( c ) ) bound += - 0.5 * D * ( tf . reduce_sum ( psi0 ) / sigma2 - tf . reduce_sum ( tf . matrix_diag_part ( AAT ) ) ) bound -= KL return bound
def add_sparql_line_nums ( sparql ) : """Returns a sparql query with line numbers prepended"""
lines = sparql . split ( "\n" ) return "\n" . join ( [ "%s %s" % ( i + 1 , line ) for i , line in enumerate ( lines ) ] )
def _augmenting_row_reduction ( self ) : """Augmenting row reduction step from LAPJV algorithm"""
unassigned = np . where ( self . _x == - 1 ) [ 0 ] for i in unassigned : for _ in range ( self . c . size ) : # Time in this loop can be proportional to 1 / epsilon # This step is not strictly necessary , so cutoff early # to avoid near - infinite loops # find smallest 2 values and indices temp = self . c [ i ] - self . _v j1 = np . argmin ( temp ) u1 = temp [ j1 ] temp [ j1 ] = np . inf j2 = np . argmin ( temp ) u2 = temp [ j2 ] if u1 < u2 : self . _v [ j1 ] -= u2 - u1 elif self . _y [ j1 ] != - 1 : j1 = j2 k = self . _y [ j1 ] if k != - 1 : self . _x [ k ] = - 1 self . _x [ i ] = j1 self . _y [ j1 ] = i i = k if k == - 1 or abs ( u1 - u2 ) < self . epsilon : break
def new ( self , time_flags ) : # type : ( int ) - > None '''Create a new Rock Ridge Time Stamp record . Parameters : time _ flags - The flags to use for this time stamp record . Returns : Nothing .'''
if self . _initialized : raise pycdlibexception . PyCdlibInternalError ( 'TF record already initialized!' ) self . time_flags = time_flags tflen = 7 if self . time_flags & ( 1 << 7 ) : tflen = 17 for index , fieldname in enumerate ( self . FIELDNAMES ) : if self . time_flags & ( 1 << index ) : if tflen == 7 : setattr ( self , fieldname , dates . DirectoryRecordDate ( ) ) elif tflen == 17 : setattr ( self , fieldname , dates . VolumeDescriptorDate ( ) ) getattr ( self , fieldname ) . new ( ) self . _initialized = True
def show_download_links ( self ) : """Query PyPI for pkg download URI for a packge @ returns : 0"""
# In case they specify version as ' dev ' instead of using - T svn , # don ' t show three svn URI ' s if self . options . file_type == "all" and self . version == "dev" : self . options . file_type = "svn" if self . options . file_type == "svn" : version = "dev" else : if self . version : version = self . version else : version = self . all_versions [ 0 ] if self . options . file_type == "all" : # Search for source , egg , and svn self . print_download_uri ( version , True ) self . print_download_uri ( version , False ) self . print_download_uri ( "dev" , True ) else : if self . options . file_type == "source" : source = True else : source = False self . print_download_uri ( version , source ) return 0
def is_none ( string_ , default = 'raise' ) : """Check if a string is equivalent to None . Parameters string _ : str default : { ' raise ' , False } Default behaviour if none of the " None " strings is detected . Returns is _ none : bool Examples > > > is _ none ( ' 2 ' , default = False ) False > > > is _ none ( ' undefined ' , default = False ) True"""
none = [ 'none' , 'undefined' , 'unknown' , 'null' , '' ] if string_ . lower ( ) in none : return True elif not default : return False else : raise ValueError ( 'The value \'{}\' cannot be mapped to none.' . format ( string_ ) )
def _setSpeed ( self , speed , motor , device ) : """Set motor speed . This method takes into consideration the PWM frequency that the hardware is currently running at and limits the values passed to the hardware accordingly . : Parameters : speed : ` int ` Motor speed as an integer . Negative numbers indicate reverse speeds . motor : ` str ` A string value indicating the motor to set the speed on . device : ` int ` The device is the integer number of the hardware devices ID and is only used with the Pololu Protocol ."""
reverse = False if speed < 0 : speed = - speed reverse = True # 0 and 2 for Qik 2s9v1 , 0 , 2 , and 4 for 2s12v10 if self . _deviceConfig [ device ] [ 'pwm' ] in ( 0 , 2 , 4 , ) and speed > 127 : speed = 127 if speed > 127 : if speed > 255 : speed = 255 if reverse : cmd = self . _COMMAND . get ( '{}-reverse-8bit' . format ( motor ) ) else : cmd = self . _COMMAND . get ( '{}-forward-8bit' . format ( motor ) ) speed -= 128 else : if reverse : cmd = self . _COMMAND . get ( '{}-reverse-7bit' . format ( motor ) ) else : cmd = self . _COMMAND . get ( '{}-forward-7bit' . format ( motor ) ) if not cmd : msg = "Invalid motor specified: {}" . format ( motor ) self . _log and self . _log . error ( msg ) raise ValueError ( msg ) self . _writeData ( cmd , device , params = ( speed , ) )
def local_to_global ( self , index ) : """Calculate local index from global index : param index : input index : return : local index for data"""
if ( type ( index ) is int ) or ( type ( index ) is slice ) : if len ( self . __mask ) > 1 : raise IndexError ( 'check length of parameter index' ) # 1D array if type ( index ) is int : return self . int_local_to_global ( index ) elif type ( index ) is slice : return self . slice_local_to_global ( index ) else : raise IndexError ( 'check data type of index to be integer or slice' ) elif type ( index ) is tuple : local_index = [ ] for k , item in enumerate ( index ) : if k < len ( self . __mask ) : if type ( item ) is slice : temp_index = self . slice_local_to_global ( item , k ) elif type ( item ) in [ int , np . int64 , np . int32 ] : temp_index = self . int_local_to_global ( item , k ) if temp_index is None : return temp_index else : temp_index = item local_index . append ( temp_index ) return tuple ( local_index ) else : raise IndexError ( 'check index for correct length and type' )
def plot_gos ( fout_img , goids , go2obj , ** kws ) : """Given GO ids and the obo _ dag , create a plot of paths from GO ids ."""
gosubdag = GoSubDag ( goids , go2obj , rcntobj = True ) godagplot = GoSubDagPlot ( gosubdag , ** kws ) godagplot . plt_dag ( fout_img )
def run ( self ) : '''Spin up the multiprocess event returner'''
salt . utils . process . appendproctitle ( self . __class__ . __name__ ) self . event = get_event ( 'master' , opts = self . opts , listen = True ) events = self . event . iter_events ( full = True ) self . event . fire_event ( { } , 'salt/event_listen/start' ) try : for event in events : if event [ 'tag' ] == 'salt/event/exit' : self . stop = True if self . _filter ( event ) : self . event_queue . append ( event ) if len ( self . event_queue ) >= self . event_return_queue : self . flush_events ( ) if self . stop : break finally : # flush all we have at this moment if self . event_queue : self . flush_events ( )
def make_ica_funs ( observed_dimension , latent_dimension ) : """These functions implement independent component analysis . The model is : latents are drawn i . i . d . for each data point from a product of student - ts . weights are the same across all datapoints . each data = latents * weghts + noise ."""
def sample ( weights , n_samples , noise_std , rs ) : latents = rs . randn ( latent_dimension , n_samples ) latents = np . array ( sorted ( latents . T , key = lambda a_entry : a_entry [ 0 ] ) ) . T noise = rs . randn ( n_samples , observed_dimension ) * noise_std observed = predict ( weights , latents ) + noise return latents , observed def predict ( weights , latents ) : return np . dot ( weights , latents ) . T def logprob ( weights , latents , noise_std , observed ) : preds = predict ( weights , latents ) log_lik = np . sum ( t . logpdf ( preds , 2.4 , observed , noise_std ) ) return log_lik num_weights = observed_dimension * latent_dimension def unpack_weights ( weights ) : return np . reshape ( weights , ( observed_dimension , latent_dimension ) ) return num_weights , sample , logprob , unpack_weights
def create ( self , name , backend_router_id , flavor , instances , test = False ) : """Orders a Virtual _ ReservedCapacityGroup : param string name : Name for the new reserved capacity : param int backend _ router _ id : This selects the pod . See create _ options for a list : param string flavor : Capacity KeyName , see create _ options for a list : param int instances : Number of guest this capacity can support : param bool test : If True , don ' t actually order , just test ."""
# Since orderManger needs a DC id , just send in 0 , the API will ignore it args = ( self . capacity_package , 0 , [ flavor ] ) extras = { "backendRouterId" : backend_router_id , "name" : name } kwargs = { 'extras' : extras , 'quantity' : instances , 'complex_type' : 'SoftLayer_Container_Product_Order_Virtual_ReservedCapacity' , 'hourly' : True } if test : receipt = self . ordering_manager . verify_order ( * args , ** kwargs ) else : receipt = self . ordering_manager . place_order ( * args , ** kwargs ) return receipt
def change_tunnel_ad_url ( self ) : '''Change tunnel ad url .'''
if self . is_open : self . close ( ) req = requests . delete ( 'https://api.psiturk.org/api/tunnel/' , auth = ( self . access_key , self . secret_key ) ) # the request content here actually will include the tunnel _ hostname # if needed or wanted . if req . status_code in [ 401 , 403 , 500 ] : print ( req . content ) return False
def analyze ( self , filename ) : """Reimplement analyze method"""
if self . dockwidget and not self . ismaximized : self . dockwidget . setVisible ( True ) self . dockwidget . setFocus ( ) self . dockwidget . raise_ ( ) self . pylint . analyze ( filename )
def command ( self , function = None , prefix = None , unobserved = False ) : """Decorator to define a new command for this Ingredient or Experiment . The name of the command will be the name of the function . It can be called from the command - line or by using the run _ command function . Commands are automatically also captured functions . The command can be given a prefix , to restrict its configuration space to a subtree . ( see ` ` capture ` ` for more information ) A command can be made unobserved ( i . e . ignoring all observers ) by passing the unobserved = True keyword argument ."""
captured_f = self . capture ( function , prefix = prefix ) captured_f . unobserved = unobserved self . commands [ function . __name__ ] = captured_f return captured_f
def serialize_wrapped_key ( key_provider , wrapping_algorithm , wrapping_key_id , encrypted_wrapped_key ) : """Serializes EncryptedData into a Wrapped EncryptedDataKey . : param key _ provider : Info for Wrapping MasterKey : type key _ provider : aws _ encryption _ sdk . structures . MasterKeyInfo : param wrapping _ algorithm : Wrapping Algorithm with which to wrap plaintext _ data _ key : type wrapping _ algorithm : aws _ encryption _ sdk . identifiers . WrappingAlgorithm : param bytes wrapping _ key _ id : Key ID of wrapping MasterKey : param encrypted _ wrapped _ key : Encrypted data key : type encrypted _ wrapped _ key : aws _ encryption _ sdk . internal . structures . EncryptedData : returns : Wrapped EncryptedDataKey : rtype : aws _ encryption _ sdk . structures . EncryptedDataKey"""
if encrypted_wrapped_key . iv is None : key_info = wrapping_key_id key_ciphertext = encrypted_wrapped_key . ciphertext else : key_info = struct . pack ( ">{key_id_len}sII{iv_len}s" . format ( key_id_len = len ( wrapping_key_id ) , iv_len = wrapping_algorithm . algorithm . iv_len ) , to_bytes ( wrapping_key_id ) , len ( encrypted_wrapped_key . tag ) * 8 , # Tag Length is stored in bits , not bytes wrapping_algorithm . algorithm . iv_len , encrypted_wrapped_key . iv , ) key_ciphertext = encrypted_wrapped_key . ciphertext + encrypted_wrapped_key . tag return EncryptedDataKey ( key_provider = MasterKeyInfo ( provider_id = key_provider . provider_id , key_info = key_info ) , encrypted_data_key = key_ciphertext , )
def valid_config_exists ( config_path = CONFIG_PATH ) : """Verify that a valid config file exists . Args : config _ path ( str ) : Path to the config file . Returns : boolean : True if there is a valid config file , false if not ."""
if os . path . isfile ( config_path ) : try : config = read_config ( config_path ) check_config ( config ) except ( ConfigurationError , IOError ) : return False else : return False return True
def _delete ( self , tree ) : """Run a DELETE statement"""
tablename = tree . table table = self . describe ( tablename , require = True ) kwargs = { } visitor = Visitor ( self . reserved_words ) if tree . where : constraints = ConstraintExpression . from_where ( tree . where ) kwargs [ "condition" ] = constraints . build ( visitor ) kwargs [ "expr_values" ] = visitor . expression_values kwargs [ "alias" ] = visitor . attribute_names return self . _query_and_op ( tree , table , "delete_item" , kwargs )
def _get_end_time ( self , start_time : datetime ) -> datetime : """Generates the end time to be used for the store range query . : param start _ time : Start time to use as an offset to calculate the end time based on the window type in the schema . : return :"""
if Type . is_type_equal ( self . _schema . window_type , Type . DAY ) : return start_time + timedelta ( days = self . _schema . window_value ) elif Type . is_type_equal ( self . _schema . window_type , Type . HOUR ) : return start_time + timedelta ( hours = self . _schema . window_value )
def tarbell_switch ( command , args ) : """Switch to a project ."""
with ensure_settings ( command , args ) as settings : projects_path = settings . config . get ( "projects_path" ) if not projects_path : show_error ( "{0} does not exist" . format ( projects_path ) ) sys . exit ( ) project = args . get ( 0 ) args . remove ( project ) project_path = os . path . join ( projects_path , project ) if os . path . isdir ( project_path ) : os . chdir ( project_path ) puts ( "\nSwitching to {0}" . format ( colored . red ( project ) ) ) tarbell_serve ( command , args ) else : show_error ( "{0} isn't a tarbell project" . format ( project_path ) )
def init ( opts ) : '''Open the connection to the Junos device , login , and bind to the Resource class'''
opts [ 'multiprocessing' ] = False log . debug ( 'Opening connection to junos' ) args = { "host" : opts [ 'proxy' ] [ 'host' ] } optional_args = [ 'user' , 'username' , 'password' , 'passwd' , 'port' , 'gather_facts' , 'mode' , 'baud' , 'attempts' , 'auto_probe' , 'ssh_private_key_file' , 'ssh_config' , 'normalize' ] if 'username' in opts [ 'proxy' ] . keys ( ) : opts [ 'proxy' ] [ 'user' ] = opts [ 'proxy' ] . pop ( 'username' ) proxy_keys = opts [ 'proxy' ] . keys ( ) for arg in optional_args : if arg in proxy_keys : args [ arg ] = opts [ 'proxy' ] [ arg ] thisproxy [ 'conn' ] = jnpr . junos . Device ( ** args ) try : thisproxy [ 'conn' ] . open ( ) except ( ProbeError , ConnectAuthError , ConnectRefusedError , ConnectTimeoutError , ConnectError ) as ex : log . error ( "{} : not able to initiate connection to the device" . format ( str ( ex ) ) ) thisproxy [ 'initialized' ] = False return if 'timeout' in proxy_keys : timeout = int ( opts [ 'proxy' ] [ 'timeout' ] ) try : thisproxy [ 'conn' ] . timeout = timeout except Exception as ex : log . error ( 'Not able to set timeout due to: %s' , str ( ex ) ) else : log . debug ( 'RPC timeout set to %d seconds' , timeout ) try : thisproxy [ 'conn' ] . bind ( cu = jnpr . junos . utils . config . Config ) except Exception as ex : log . error ( 'Bind failed with Config class due to: {}' . format ( str ( ex ) ) ) try : thisproxy [ 'conn' ] . bind ( sw = jnpr . junos . utils . sw . SW ) except Exception as ex : log . error ( 'Bind failed with SW class due to: {}' . format ( str ( ex ) ) ) thisproxy [ 'initialized' ] = True
def _check_error ( response ) : """Checks for JSON error messages and raises Python exception"""
if 'error' in response : raise InfluxDBError ( response [ 'error' ] ) elif 'results' in response : for statement in response [ 'results' ] : if 'error' in statement : msg = '{d[error]} (statement {d[statement_id]})' raise InfluxDBError ( msg . format ( d = statement ) )
def mb_neg_logposterior ( self , beta , mini_batch ) : """Returns negative log posterior Parameters beta : np . array Contains untransformed starting values for latent variables mini _ batch : int Batch size for the data Returns Negative log posterior"""
post = ( self . data . shape [ 0 ] / mini_batch ) * self . mb_neg_loglik ( beta , mini_batch ) for k in range ( 0 , self . z_no ) : post += - self . latent_variables . z_list [ k ] . prior . logpdf ( beta [ k ] ) return post
def remove_quotes ( self , value ) : """Remove any surrounding quotes from a value and unescape any contained quotes of that type ."""
# beware the empty string if not value : return value if value [ 0 ] == value [ - 1 ] == '"' : return value [ 1 : - 1 ] . replace ( '\\"' , '"' ) if value [ 0 ] == value [ - 1 ] == "'" : return value [ 1 : - 1 ] . replace ( "\\'" , "'" ) return value
def remove ( local_file_name ) : """Function attempts to remove file , if failure occures - > print exception : param local _ file _ name : name of file to remove"""
try : os . remove ( local_file_name ) except Exception as e : print ( "Cannot remove file '" + local_file_name + "'. Please remove it manually." ) print ( e )
def opponent_rank ( self ) : """Returns a ` ` string ` ` of the opponent ' s rank when the game was played and None if the team was unranked ."""
rank = re . findall ( r'\d+' , self . _opponent_name ) if len ( rank ) > 0 : return int ( rank [ 0 ] ) return None
def set_line_width ( self , width ) : """Sets the current line width within the cairo context . The line width value specifies the diameter of a pen that is circular in user space , ( though device - space pen may be an ellipse in general due to scaling / shear / rotation of the CTM ) . . . note : : When the description above refers to user space and CTM it refers to the user space and CTM in effect at the time of the stroking operation , not the user space and CTM in effect at the time of the call to : meth : ` set _ line _ width ` . The simplest usage makes both of these spaces identical . That is , if there is no change to the CTM between a call to : meth : ` set _ line _ width ` and the stroking operation , then one can just pass user - space values to : meth : ` set _ line _ width ` and ignore this note . As with the other stroke parameters , the current line cap style is examined by : meth : ` stroke ` , : meth : ` stroke _ extents ` , and : meth : ` stroke _ to _ path ` , but does not have any effect during path construction . The default line width value is 2.0. : type width : float : param width : The new line width ."""
cairo . cairo_set_line_width ( self . _pointer , width ) self . _check_status ( )
def get_appointment_groups ( self , ** kwargs ) : """List appointment groups . : calls : ` GET / api / v1 / appointment _ groups < https : / / canvas . instructure . com / doc / api / appointment _ groups . html # method . appointment _ groups . index > ` _ : rtype : : class : ` canvasapi . paginated _ list . PaginatedList ` of : class : ` canvasapi . appointment _ group . AppointmentGroup `"""
from canvasapi . appointment_group import AppointmentGroup return PaginatedList ( AppointmentGroup , self . __requester , 'GET' , 'appointment_groups' , _kwargs = combine_kwargs ( ** kwargs ) )
def get_next_departures ( stop , filter_line = None , num_line_groups = 1 , verbose = False ) : """Get all real - time departure times for given stop and return as filtered table . Terminate if we can assume there is no connection to the internet ."""
# Get departures table from online service # ( great : we don ' t have to iterate over multiple pages ) . url = BVG_URL_PAT % stop if verbose : print ( '- Fetching table for URL "%s".' % url ) try : tables = pd . read_html ( url . encode ( 'utf-8' ) ) except urllib . error . URLError : msg = 'Not connected to the internet?' termcolor . cprint ( msg , 'red' , attrs = [ 'bold' ] ) sys . exit ( 1 ) except ValueError : return [ ] table = tables [ 0 ] table . columns = [ 'Departure' , 'Line' , 'Destination' ] if verbose : print ( '- Got table with %d entries for "%s".' % ( len ( table ) , stop ) ) # Cleanup # Drop entries with ' * ' in column Departure . . . # ( causes trouble when resulting in an empty table ! ) # table = table [ table . Departure . apply ( lambda row : " * " not in row ) ] # So , instead remove ' * ' in column Departure . . . table . is_copy = False # prevents SettingWithCopyWarning table . Departure = table . apply ( lambda row : re . sub ( '\s*\*\s*' , '' , row . Departure ) , axis = 1 ) # Replace regex ' + ' with ' ' in column Line . . . table . Line = table . apply ( lambda row : re . sub ( ' +' , ' ' , row . Line ) , axis = 1 ) # Filter desired number of unique combinations of Line and Destination column . indices = [ ] for i in range ( num_line_groups ) : try : indices += sorted ( [ tab . index . values [ i ] for line_dest , tab in table . groupby ( [ 'Line' , 'Destination' ] ) ] ) except IndexError : break table = table [ table . index . map ( lambda x : x in indices ) ] # Insert a left - most column with minutes and seconds from now # until the departure time . table . insert ( 0 , "Wait" , table . Departure . apply ( lambda dep : wait_time ( dep ) ) ) # Filter on desired lines only if filter_line : table = table [ table . Line . apply ( lambda cell : filter_line . lower ( ) . encode ( 'utf-8' ) in cell . lower ( ) ) ] return table
def extract_fields ( lines , delim , searches , match_lineno = 1 , ** kwargs ) : """Return generator of fields matching ` searches ` . Parameters lines : iterable Provides line number ( 1 - based ) and line ( str ) delim : str Delimiter to split line by to produce fields searches : iterable Returns search ( str ) to match against line fields . match _ lineno : int Line number of line to split and search fields Remaining keyword arguments are passed to ` match _ fields ` ."""
keep_idx = [ ] for lineno , line in lines : if lineno < match_lineno or delim not in line : if lineno == match_lineno : raise WcutError ( 'Delimter not found in line {}' . format ( match_lineno ) ) yield [ line ] continue fields = line . split ( delim ) if lineno == match_lineno : keep_idx = list ( match_fields ( fields , searches , ** kwargs ) ) keep_fields = [ fields [ i ] for i in keep_idx ] if keep_fields : yield keep_fields
def sanitize_op ( self , op_data ) : """Remove unnecessary fields for an operation , i . e . prior to committing it . This includes any invariant tags we ' ve added with our invariant decorators ( such as @ state _ create or @ state _ transition ) . TODO : less ad - hoc way to do this"""
op_data = super ( BlockstackDB , self ) . sanitize_op ( op_data ) # remove invariant tags ( i . e . added by our invariant state _ * decorators ) to_remove = get_state_invariant_tags ( ) for tag in to_remove : if tag in op_data . keys ( ) : del op_data [ tag ] # NOTE : this is called the opcode family , because # different operation names can have the same operation code # ( such as NAME _ RENEWAL and NAME _ REGISTRATION ) . They must # have the same mutation fields . opcode_family = op_get_opcode_name ( op_data [ 'op' ] ) # for each column in the appropriate state table , # if the column is not identified in the operation ' s # MUTATE _ FIELDS list , then set it to None here . mutate_fields = op_get_mutate_fields ( opcode_family ) for mf in mutate_fields : if not op_data . has_key ( mf ) : log . debug ( "Adding NULL mutate field '%s.%s'" % ( opcode_family , mf ) ) op_data [ mf ] = None # TODO : less ad - hoc for extra_field in [ 'opcode' ] : if extra_field in op_data : del op_data [ extra_field ] return op_data
def _expire_data ( self ) : """Remove all expired entries ."""
expire_time_stamp = time . time ( ) - self . expire_time self . timed_data = { d : t for d , t in self . timed_data . items ( ) if t > expire_time_stamp }
def format ( self , message_format ) : """Set the message format : param message _ format : The format to set : type message _ format : str"""
if message_format not in self . formats : self . _log . error ( 'Invalid Message format specified: {format}' . format ( format = message_format ) ) return self . _log . debug ( 'Setting message format to {format}' . format ( format = message_format ) ) self . _format = message_format
def _collect_placeholders_required ( self ) : """* collect placeholders required from filename etc *"""
self . log . info ( 'starting the ``_collect_placeholders_required`` method' ) phs = self . settings [ "frankenstein" ] [ "placeholder delimiters" ] phsString = "|" . join ( phs ) matchObject = re . finditer ( r'(%(phsString)s)([^\s]*?)\1' % locals ( ) , string = self . contentString , flags = re . S # re . S ) phDict = { } for match in matchObject : phDict [ match . group ( 2 ) ] = None self . phDict = phDict self . log . info ( 'completed the ``_collect_placeholders_required`` method' ) return None
def set_current_operation_progress ( self , percent ) : """Internal method , not to be called externally . in percent of type int"""
if not isinstance ( percent , baseinteger ) : raise TypeError ( "percent can only be an instance of type baseinteger" ) self . _call ( "setCurrentOperationProgress" , in_p = [ percent ] )
def inserir ( self , name ) : """Inserts a new Group L3 and returns its identifier . : param name : Group L3 name . String with a minimum 2 and maximum of 80 characters : return : Dictionary with the following structure : { ' group _ l3 ' : { ' id ' : < id _ group _ l3 > } } : raise InvalidParameterError : Name is null and invalid . : raise NomeGrupoL3DuplicadoError : There is already a registered Group L3 with the value of name . : raise DataBaseError : Networkapi failed to access the database . : raise XMLError : Networkapi failed to generate the XML response ."""
group_l3_map = dict ( ) group_l3_map [ 'name' ] = name code , xml = self . submit ( { 'group_l3' : group_l3_map } , 'POST' , 'groupl3/' ) return self . response ( code , xml )
def write ( self , data , ** keys ) : """Write data into this HDU parameters data : ndarray or list of ndarray A numerical python array . Should be an ordinary array for image HDUs , should have fields for tables . To write an ordinary array to a column in a table HDU , use write _ column . If data already exists in this HDU , it will be overwritten . See the append ( ( ) method to append new rows to a table HDU . firstrow : integer , optional At which row you should begin writing to tables . Be sure you know what you are doing ! For appending see the append ( ) method . Default 0. columns : list , optional If data is a list of arrays , you must send columns as a list of names or column numbers You can also send names = names : list , optional same as columns ="""
slow = keys . get ( 'slow' , False ) isrec = False if isinstance ( data , ( list , dict ) ) : if isinstance ( data , list ) : data_list = data columns_all = keys . get ( 'columns' , None ) if columns_all is None : columns_all = keys . get ( 'names' , None ) if columns_all is None : raise ValueError ( "you must send columns with a list of arrays" ) else : columns_all = list ( data . keys ( ) ) data_list = [ data [ n ] for n in columns_all ] colnums_all = [ self . _extract_colnum ( c ) for c in columns_all ] names = [ self . get_colname ( c ) for c in colnums_all ] isobj = numpy . zeros ( len ( data_list ) , dtype = numpy . bool ) for i in xrange ( len ( data_list ) ) : isobj [ i ] = is_object ( data_list [ i ] ) else : if data . dtype . fields is None : raise ValueError ( "You are writing to a table, so I expected " "an array with fields as input. If you want " "to write a simple array, you should use " "write_column to write to a single column, " "or instead write to an image hdu" ) if data . shape is ( ) : raise ValueError ( "cannot write data with shape ()" ) isrec = True names = data . dtype . names # only write object types ( variable - length columns ) after # writing the main table isobj = fields_are_object ( data ) data_list = [ ] colnums_all = [ ] for i , name in enumerate ( names ) : colnum = self . _extract_colnum ( name ) data_list . append ( data [ name ] ) colnums_all . append ( colnum ) if slow : for i , name in enumerate ( names ) : if not isobj [ i ] : self . write_column ( name , data_list [ i ] , ** keys ) else : nonobj_colnums = [ ] nonobj_arrays = [ ] for i in xrange ( len ( data_list ) ) : if not isobj [ i ] : nonobj_colnums . append ( colnums_all [ i ] ) if isrec : # this still leaves possibility of f - order sub - arrays . . colref = array_to_native ( data_list [ i ] , inplace = False ) else : colref = array_to_native_c ( data_list [ i ] , inplace = False ) if IS_PY3 and colref . dtype . char == 'U' : # for python3 , we convert unicode to ascii # this will error if the character is not in ascii colref = colref . astype ( 'S' , copy = False ) nonobj_arrays . append ( colref ) for tcolnum , tdata in zip ( nonobj_colnums , nonobj_arrays ) : self . _verify_column_data ( tcolnum , tdata ) if len ( nonobj_arrays ) > 0 : firstrow = keys . get ( 'firstrow' , 0 ) self . _FITS . write_columns ( self . _ext + 1 , nonobj_colnums , nonobj_arrays , firstrow = firstrow + 1 , write_bitcols = self . write_bitcols ) # writing the object arrays always occurs the same way # need to make sure this works for array fields for i , name in enumerate ( names ) : if isobj [ i ] : self . write_var_column ( name , data_list [ i ] , ** keys ) self . _update_info ( )
def generate_mfa_token ( self , user_id , expires_in = 259200 , reusable = False ) : """Use to generate a temporary MFA token that can be used in place of other MFA tokens for a set time period . For example , use this token for account recovery . : param user _ id : Id of the user : type user _ id : int : param expires _ in : Set the duration of the token in seconds . ( default : 259200 seconds = 72h ) 72 hours is the max value . : type expires _ in : int : param reusable : Defines if the token reusable . ( default : false ) If set to true , token can be used for multiple apps , until it expires . : type reusable : bool Returns a mfa token : return : return the object if success : rtype : MFAToken See https : / / developers . onelogin . com / api - docs / 1 / multi - factor - authentication / generate - mfa - token Generate MFA Token documentation"""
self . clean_error ( ) try : url = self . get_url ( Constants . GENERATE_MFA_TOKEN_URL , user_id ) data = { 'expires_in' : expires_in , 'reusable' : reusable } response = self . execute_call ( 'post' , url , json = data ) if response . status_code == 201 : json_data = response . json ( ) if json_data : return MFAToken ( json_data ) else : self . error = self . extract_status_code_from_response ( response ) self . error_description = self . extract_error_message_from_response ( response ) except Exception as e : self . error = 500 self . error_description = e . args [ 0 ]
async def status ( request : web . Request ) -> web . Response : """Get request will return the status of the machine ' s connection to the internet as well as the status of its network interfaces . The body of the response is a json dict containing ' status ' : internet connectivity status , where the options are : " none " - no connection to router or network " portal " - device behind a captive portal and cannot reach full internet " limited " - connection to router but not internet " full " - connection to router and internet " unknown " - an exception occured while trying to determine status ' interfaces ' : JSON object of networking interfaces , keyed by device name , where the value of each entry is another object with the keys : - ' type ' : " ethernet " or " wifi " - ' state ' : state string , e . g . " disconnected " , " connecting " , " connected " - ' ipAddress ' : the ip address , if it exists ( null otherwise ) ; this also contains the subnet mask in CIDR notation , e . g . 10.2.12.120/16 - ' macAddress ' : the MAC address of the interface device - ' gatewayAddress ' : the address of the current gateway , if it exists ( null otherwise ) Example request : GET / networking / status Example response : 200 OK " status " : " full " , " interfaces " : { " wlan0 " : { " ipAddress " : " 192.168.43.97/24 " , " macAddress " : " B8:27 : EB : 6C : 95 : CF " , " gatewayAddress " : " 192.168.43.161 " , " state " : " connected " , " type " : " wifi " " eth0 " : { " ipAddress " : " 169.254.229.173/16 " , " macAddress " : " B8:27 : EB : 39 : C0:9A " , " gatewayAddress " : null , " state " : " connected " , " type " : " ethernet " """
connectivity = { 'status' : 'none' , 'interfaces' : { } } try : connectivity [ 'status' ] = await nmcli . is_connected ( ) connectivity [ 'interfaces' ] = { i . value : await nmcli . iface_info ( i ) for i in nmcli . NETWORK_IFACES } log . debug ( "Connectivity: {}" . format ( connectivity [ 'status' ] ) ) log . debug ( "Interfaces: {}" . format ( connectivity [ 'interfaces' ] ) ) status = 200 except subprocess . CalledProcessError as e : log . error ( "CalledProcessError: {}" . format ( e . stdout ) ) status = 500 except FileNotFoundError as e : log . error ( "FileNotFoundError: {}" . format ( e ) ) status = 500 return web . json_response ( connectivity , status = status )
def exerciseOptions ( self , tickerId , contract , exerciseAction , exerciseQuantity , account , override ) : """exerciseOptions ( EClientSocketBase self , TickerId tickerId , Contract contract , int exerciseAction , int exerciseQuantity , IBString const & account , int override )"""
return _swigibpy . EClientSocketBase_exerciseOptions ( self , tickerId , contract , exerciseAction , exerciseQuantity , account , override )
def rdb_repository ( _context , name = None , make_default = False , aggregate_class = None , repository_class = None , db_string = None , metadata_factory = None ) : """Directive for registering a RDBM based repository ."""
cnf = { } if not db_string is None : cnf [ 'db_string' ] = db_string if not metadata_factory is None : cnf [ 'metadata_factory' ] = metadata_factory _repository ( _context , name , make_default , aggregate_class , repository_class , REPOSITORY_TYPES . RDB , 'add_rdb_repository' , cnf )
async def AddMetricBatches ( self , batches ) : '''batches : typing . Sequence [ ~ MetricBatchParam ] Returns - > typing . Sequence [ ~ ErrorResult ]'''
# map input types to rpc msg _params = dict ( ) msg = dict ( type = 'MetricsAdder' , request = 'AddMetricBatches' , version = 2 , params = _params ) _params [ 'batches' ] = batches reply = await self . rpc ( msg ) return reply
def set_reverb ( self , roomsize = - 1.0 , damping = - 1.0 , width = - 1.0 , level = - 1.0 ) : """roomsize Reverb room size value ( 0.0-1.2) damping Reverb damping value ( 0.0-1.0) width Reverb width value ( 0.0-100.0) level Reverb level value ( 0.0-1.0)"""
set = 0 if roomsize >= 0 : set += 0b0001 if damping >= 0 : set += 0b0010 if width >= 0 : set += 0b0100 if level >= 0 : set += 0b1000 return fluid_synth_set_reverb_full ( self . synth , set , roomsize , damping , width , level )
def load_from_sens_file ( self , filename ) : """Load real and imaginary parts from a sens . dat file generated by CRMod Parameters filename : string filename of sensitivity file Returns nid _ re : int ID of real part of sensitivities nid _ im : int ID of imaginary part of sensitivities"""
sens_data = np . loadtxt ( filename , skiprows = 1 ) nid_re = self . add_data ( sens_data [ : , 2 ] ) nid_im = self . add_data ( sens_data [ : , 3 ] ) return nid_re , nid_im
def make_format ( self , fmt , width ) : """Make subreport text in a specified format"""
if not self . report_data : return for data_item in self . report_data : if data_item . results : if fmt is None or fmt == 'text' : data_item . make_text ( width ) elif fmt == 'html' : data_item . make_html ( ) elif fmt == 'csv' : data_item . make_csv ( )
def download_subtitle ( self , subtitle ) : """Download ` subtitle ` ' s : attr : ` ~ subliminal . subtitle . Subtitle . content ` . : param subtitle : subtitle to download . : type subtitle : : class : ` ~ subliminal . subtitle . Subtitle ` : return : ` True ` if the subtitle has been successfully downloaded , ` False ` otherwise . : rtype : bool"""
# check discarded providers if subtitle . provider_name in self . discarded_providers : logger . warning ( 'Provider %r is discarded' , subtitle . provider_name ) return False logger . info ( 'Downloading subtitle %r' , subtitle ) try : self [ subtitle . provider_name ] . download_subtitle ( subtitle ) except ( requests . Timeout , socket . timeout ) : logger . error ( 'Provider %r timed out, discarding it' , subtitle . provider_name ) self . discarded_providers . add ( subtitle . provider_name ) return False except : logger . exception ( 'Unexpected error in provider %r, discarding it' , subtitle . provider_name ) self . discarded_providers . add ( subtitle . provider_name ) return False # check subtitle validity if not subtitle . is_valid ( ) : logger . error ( 'Invalid subtitle' ) return False return True
def get_svc_stats ( self , svcs ) : """Get statistics for Services , resp . Service entities"""
stats = { "services.total" : 0 , "services.ok" : 0 , "services.warning" : 0 , "services.critical" : 0 , "services.unknown" : 0 , "services.flapping" : 0 , "services.in_downtime" : 0 , "services.checked" : 0 , "services.scheduled" : 0 , "services.active_checks" : 0 , "services.passive_checks" : 0 , } for svc in svcs : if type ( svc ) is not dict : continue sane = self . _sanitize_entity ( svc ) stats [ "services.total" ] += 1 stats [ "services.flapping" ] += self . _trans_binary ( sane [ "flapping" ] ) stats [ "services.in_downtime" ] += self . _trans_dtime ( sane [ "in_downtime" ] ) stats [ "services.checked" ] += self . _trans_binary ( sane [ "checked" ] ) stats [ "services.scheduled" ] += self . _trans_binary ( sane [ "scheduled" ] ) stats [ "services.active_checks" ] += sane [ "active_checks" ] stats [ "services.passive_checks" ] += sane [ "passive_checks" ] state_key = self . _trans_svc_state ( sane [ "state" ] ) stats [ "services.%s" % ( state_key ) ] += 1 return stats
def plot_contours ( self , grid , filled = True , ax = None , labels = None , subplots_kw = dict ( ) , ** kwargs ) : """Plot equipotentials contours . Computes the potential energy on a grid ( specified by the array ` grid ` ) . . . warning : : Right now the grid input must be arrays and must already be in the unit system of the potential . Quantity support is coming . . . Parameters grid : tuple Coordinate grids or slice value for each dimension . Should be a tuple of 1D arrays or numbers . filled : bool ( optional ) Use : func : ` ~ matplotlib . pyplot . contourf ` instead of : func : ` ~ matplotlib . pyplot . contour ` . Default is ` ` True ` ` . ax : matplotlib . Axes ( optional ) labels : iterable ( optional ) List of axis labels . subplots _ kw : dict kwargs passed to matplotlib ' s subplots ( ) function if an axes object is not specified . kwargs : dict kwargs passed to either contourf ( ) or plot ( ) . Returns fig : ` ~ matplotlib . Figure `"""
import matplotlib . pyplot as plt from matplotlib import cm # figure out which elements are iterable , which are numeric _grids = [ ] _slices = [ ] for ii , g in enumerate ( grid ) : if isiterable ( g ) : _grids . append ( ( ii , g ) ) else : _slices . append ( ( ii , g ) ) # figure out the dimensionality ndim = len ( _grids ) # if ndim > 2 , don ' t know how to handle this ! if ndim > 2 : raise ValueError ( "ndim > 2: you can only make contours on a 2D grid. For other " "dimensions, you have to specify values to slice." ) if ax is None : # default figsize fig , ax = plt . subplots ( 1 , 1 , ** subplots_kw ) else : fig = ax . figure if ndim == 1 : # 1D curve x1 = _grids [ 0 ] [ 1 ] r = np . zeros ( ( len ( _grids ) + len ( _slices ) , len ( x1 ) ) ) r [ _grids [ 0 ] [ 0 ] ] = x1 for ii , slc in _slices : r [ ii ] = slc Z = self . energy ( r * self . units [ 'length' ] ) . value ax . plot ( x1 , Z , ** kwargs ) if labels is not None : ax . set_xlabel ( labels [ 0 ] ) ax . set_ylabel ( "potential" ) else : # 2D contours x1 , x2 = np . meshgrid ( _grids [ 0 ] [ 1 ] , _grids [ 1 ] [ 1 ] ) shp = x1 . shape x1 , x2 = x1 . ravel ( ) , x2 . ravel ( ) r = np . zeros ( ( len ( _grids ) + len ( _slices ) , len ( x1 ) ) ) r [ _grids [ 0 ] [ 0 ] ] = x1 r [ _grids [ 1 ] [ 0 ] ] = x2 for ii , slc in _slices : r [ ii ] = slc Z = self . energy ( r * self . units [ 'length' ] ) . value # make default colormap not suck cmap = kwargs . pop ( 'cmap' , cm . Blues ) if filled : cs = ax . contourf ( x1 . reshape ( shp ) , x2 . reshape ( shp ) , Z . reshape ( shp ) , cmap = cmap , ** kwargs ) else : cs = ax . contour ( x1 . reshape ( shp ) , x2 . reshape ( shp ) , Z . reshape ( shp ) , cmap = cmap , ** kwargs ) if labels is not None : ax . set_xlabel ( labels [ 0 ] ) ax . set_ylabel ( labels [ 1 ] ) return fig
def summary ( app ) : """Print a summary of a deployed app ' s status ."""
r = requests . get ( 'https://{}.herokuapp.com/summary' . format ( app ) ) summary = r . json ( ) [ 'summary' ] click . echo ( "\nstatus \t| count" ) click . echo ( "----------------" ) for s in summary : click . echo ( "{}\t| {}" . format ( s [ 0 ] , s [ 1 ] ) ) num_101s = sum ( [ s [ 1 ] for s in summary if s [ 0 ] == 101 ] ) num_10xs = sum ( [ s [ 1 ] for s in summary if s [ 0 ] >= 100 ] ) if num_10xs > 0 : click . echo ( "\nYield: {:.2%}" . format ( 1.0 * num_101s / num_10xs ) )
def _request_callback ( self , request_id ) : """Construct a request callback for the given request ID ."""
def callback ( future ) : # Remove the future from the client requests map self . _client_request_futures . pop ( request_id , None ) if future . cancelled ( ) : future . set_exception ( JsonRpcRequestCancelled ( ) ) message = { 'jsonrpc' : JSONRPC_VERSION , 'id' : request_id , } try : message [ 'result' ] = future . result ( ) except JsonRpcException as e : log . exception ( "Failed to handle request %s" , request_id ) message [ 'error' ] = e . to_dict ( ) except Exception : # pylint : disable = broad - except log . exception ( "Failed to handle request %s" , request_id ) message [ 'error' ] = JsonRpcInternalError . of ( sys . exc_info ( ) ) . to_dict ( ) self . _consumer ( message ) return callback
def curve_spline ( x , y = None , weights = None , order = 1 , even_out = True , smoothing = None , periodic = False , meta_data = None ) : '''curve _ spline ( coords ) yields a bicubic spline function through the points in the given coordinate matrix . curve _ spline ( x , y ) uses the coordinate matrix [ x , y ] . The function returned by curve _ spline ( ) is f ( t ) , defined on the interval from 0 to n - 1 where n is the number of points in the coordinate matrix provided . The following options are accepted : * weights ( None ) the weights to use in smoothing . * smoothing ( None ) the amount to smooth the points . * order ( 3 ) the order of the polynomial used in the splines . * periodic ( False ) whether the points are periodic or not . * even _ out ( True ) whether to even out the distances along the curve . * meta _ data ( None ) an optional map of meta - data to give the spline representation .'''
curv = CurveSpline ( x , y , weights = weights , order = order , smoothing = smoothing , periodic = periodic , meta_data = meta_data ) if even_out : curv = curv . even_out ( ) return curv
def now ( self ) : """Return a : py : class : ` datetime . datetime ` instance representing the current time . : rtype : : py : class : ` datetime . datetime `"""
if self . use_utc : return datetime . datetime . utcnow ( ) else : return datetime . datetime . now ( )
def unlink ( self , node , hyperedge ) : """Unlink given node and hyperedge . @ type node : node @ param node : Node . @ type hyperedge : hyperedge @ param hyperedge : Hyperedge ."""
self . node_links [ node ] . remove ( hyperedge ) self . edge_links [ hyperedge ] . remove ( node ) self . graph . del_edge ( ( ( node , 'n' ) , ( hyperedge , 'h' ) ) )
def disable_token ( platform , user_id , token , on_error = None , on_success = None ) : """Disable a device token for a user . : param str platform The platform which to disable token on . One of either Google Cloud Messaging ( outbound . GCM ) or Apple Push Notification Service ( outbound . APNS ) . : param str | number user _ id : the id you use to identify a user . this should be static for the lifetime of a user . : param str token : the token to disable . : param func on _ error : An optional function to call in the event of an error . on _ error callback should take 2 parameters : ` code ` and ` error ` . ` code ` will be one of outbound . ERROR _ XXXXX . ` error ` will be the corresponding message . : param func on _ success : An optional function to call if / when the API call succeeds . on _ success callback takes no parameters ."""
__device_token ( platform , False , user_id , token = token , on_error = on_error , on_success = on_success )
def stored_bind ( self , instance ) : """Bind an instance to this Pangler , using the bound Pangler store . This method functions identically to ` bind ` , except that it might return a Pangler which was previously bound to the provided instance ."""
if self . id is None : return self . bind ( instance ) store = self . _bound_pangler_store . setdefault ( instance , { } ) p = store . get ( self . id ) if p is None : p = store [ self . id ] = self . bind ( instance ) return p
def _notify_remove ( self , slice_ ) : """Notify about a RemoveChange ."""
change = RemoveChange ( self , slice_ ) self . notify_observers ( change )
def clear_screen ( ) : import os , platform """http : / / stackoverflow . com / questions / 18937058 / python - clear - screen - in - shell"""
if platform . system ( ) == "Windows" : tmp = os . system ( 'cls' ) # for window else : tmp = os . system ( 'clear' ) # for Linux return True
def get ( self , _create = False , ** ctx_options ) : """NOTE : ` ctx _ options ` are ignored"""
if _create : return self . _kind_factory . create ( key = self ) else : return self . _kind_factory ( key = self )
def tempo_account_delete_account_by_id ( self , account_id ) : """Delete an Account by id . Caller must have the Manage Account Permission for the Account . The Account can not be deleted if it has an AccountLinkBean . : param account _ id : the id of the Account to be deleted . : return :"""
url = 'rest/tempo-accounts/1/account/{id}/' . format ( id = account_id ) return self . delete ( url )
def load ( self ) : """Get load time series ( only active power ) Returns dict or : pandas : ` pandas . DataFrame < dataframe > ` See class definition for details ."""
try : return self . _load . loc [ [ self . timeindex ] , : ] except : return self . _load . loc [ self . timeindex , : ]
def _sampleRange ( rng , start , end , step , k ) : """Equivalent to : random . sample ( xrange ( start , end , step ) , k ) except it uses our random number generator . This wouldn ' t need to create the arange if it were implemented in C ."""
array = numpy . empty ( k , dtype = "uint32" ) rng . sample ( numpy . arange ( start , end , step , dtype = "uint32" ) , array ) return array
def read_config ( file_name ) : """Read YAML file with configuration and pointers to example data . Args : file _ name ( str ) : Name of the file , where the configuration is stored . Returns : dict : Parsed and processed data ( see : func : ` _ process _ config _ item ` ) . Example YAML file : : html : simple _ xml . xml first : data : i wan ' t this required : true notfoundmsg : Can ' t find variable $ name . second : data : and this html : simple _ xml2 . xml first : data : something wanted required : true notfoundmsg : Can ' t find variable $ name . second : data : another wanted thing"""
dirname = os . path . dirname ( os . path . abspath ( file_name ) ) dirname = os . path . relpath ( dirname ) # create utf - 8 strings , not unicode def custom_str_constructor ( loader , node ) : return loader . construct_scalar ( node ) . encode ( 'utf-8' ) yaml . add_constructor ( u'tag:yaml.org,2002:str' , custom_str_constructor ) config = [ ] with open ( file_name ) as f : for item in yaml . load_all ( f . read ( ) ) : config . append ( _process_config_item ( item , dirname ) ) return config
def gen_front_term ( self , x , dmp_num ) : """Generates the front term on the forcing term . For rhythmic DMPs it ' s non - diminishing , so this function is just a placeholder to return 1. x float : the current value of the canonical system dmp _ num int : the index of the current dmp"""
if isinstance ( x , np . ndarray ) : return np . ones ( x . shape ) return 1
def find_all_mappings ( self , other_lattice : "Lattice" , ltol : float = 1e-5 , atol : float = 1 , skip_rotation_matrix : bool = False , ) -> Iterator [ Tuple [ "Lattice" , Optional [ np . ndarray ] , np . ndarray ] ] : """Finds all mappings between current lattice and another lattice . Args : other _ lattice ( Lattice ) : Another lattice that is equivalent to this one . ltol ( float ) : Tolerance for matching lengths . Defaults to 1e - 5. atol ( float ) : Tolerance for matching angles . Defaults to 1. skip _ rotation _ matrix ( bool ) : Whether to skip calculation of the rotation matrix Yields : ( aligned _ lattice , rotation _ matrix , scale _ matrix ) if a mapping is found . aligned _ lattice is a rotated version of other _ lattice that has the same lattice parameters , but which is aligned in the coordinate system of this lattice so that translational points match up in 3D . rotation _ matrix is the rotation that has to be applied to other _ lattice to obtain aligned _ lattice , i . e . , aligned _ matrix = np . inner ( other _ lattice , rotation _ matrix ) and op = SymmOp . from _ rotation _ and _ translation ( rotation _ matrix ) aligned _ matrix = op . operate _ multi ( latt . matrix ) Finally , scale _ matrix is the integer matrix that expresses aligned _ matrix as a linear combination of this lattice , i . e . , aligned _ matrix = np . dot ( scale _ matrix , self . matrix ) None is returned if no matches are found ."""
( lengths , angles ) = other_lattice . lengths_and_angles ( alpha , beta , gamma ) = angles frac , dist , _ , _ = self . get_points_in_sphere ( [ [ 0 , 0 , 0 ] ] , [ 0 , 0 , 0 ] , max ( lengths ) * ( 1 + ltol ) , zip_results = False ) cart = self . get_cartesian_coords ( frac ) # this can ' t be broadcast because they ' re different lengths inds = [ np . logical_and ( dist / l < 1 + ltol , dist / l > 1 / ( 1 + ltol ) ) for l in lengths ] c_a , c_b , c_c = ( cart [ i ] for i in inds ) f_a , f_b , f_c = ( frac [ i ] for i in inds ) l_a , l_b , l_c = ( np . sum ( c ** 2 , axis = - 1 ) ** 0.5 for c in ( c_a , c_b , c_c ) ) def get_angles ( v1 , v2 , l1 , l2 ) : x = np . inner ( v1 , v2 ) / l1 [ : , None ] / l2 x [ x > 1 ] = 1 x [ x < - 1 ] = - 1 angles = np . arccos ( x ) * 180.0 / pi return angles alphab = np . abs ( get_angles ( c_b , c_c , l_b , l_c ) - alpha ) < atol betab = np . abs ( get_angles ( c_a , c_c , l_a , l_c ) - beta ) < atol gammab = np . abs ( get_angles ( c_a , c_b , l_a , l_b ) - gamma ) < atol for i , all_j in enumerate ( gammab ) : inds = np . logical_and ( all_j [ : , None ] , np . logical_and ( alphab , betab [ i ] [ None , : ] ) ) for j , k in np . argwhere ( inds ) : scale_m = np . array ( ( f_a [ i ] , f_b [ j ] , f_c [ k ] ) , dtype = np . int ) if abs ( np . linalg . det ( scale_m ) ) < 1e-8 : continue aligned_m = np . array ( ( c_a [ i ] , c_b [ j ] , c_c [ k ] ) ) if skip_rotation_matrix : rotation_m = None else : rotation_m = np . linalg . solve ( aligned_m , other_lattice . matrix ) yield Lattice ( aligned_m ) , rotation_m , scale_m
def main ( args , stop = False ) : """Arguments parsing , etc . ."""
daemon = AMQPDaemon ( con_param = getConParams ( settings . RABBITMQ_MX2MODS_VIRTUALHOST ) , queue = settings . RABBITMQ_MX2MODS_INPUT_QUEUE , out_exch = settings . RABBITMQ_MX2MODS_EXCHANGE , out_key = settings . RABBITMQ_MX2MODS_OUTPUT_KEY , react_fn = reactToAMQPMessage , glob = globals ( ) # used in deserializer ) if not stop and args and args . foreground : # run at foreground daemon . run ( ) else : daemon . run_daemon ( )
def update_lipd_v1_1 ( d ) : """Update LiPD v1.0 to v1.1 - chronData entry is a list that allows multiple tables - paleoData entry is a list that allows multiple tables - chronData now allows measurement , model , summary , modelTable , ensemble , calibratedAges tables - Added ' lipdVersion ' key : param dict d : Metadata v1.0 : return dict d : Metadata v1.1"""
logger_versions . info ( "enter update_lipd_v1_1" ) tmp_all = [ ] try : # ChronData is the only structure update if "chronData" in d : # As of v1.1 , ChronData should have an extra level of abstraction . # No longer shares the same structure of paleoData # If no measurement table , then make a measurement table list with the table as the entry for table in d [ "chronData" ] : if "chronMeasurementTable" not in table : tmp_all . append ( { "chronMeasurementTable" : [ table ] } ) # If the table exists , but it is a dictionary , then turn it into a list with one entry elif "chronMeasurementTable" in table : if isinstance ( table [ "chronMeasurementTable" ] , dict ) : tmp_all . append ( { "chronMeasurementTable" : [ table [ "chronMeasurementTable" ] ] } ) if tmp_all : d [ "chronData" ] = tmp_all # Log that this is now a v1.1 structured file d [ "lipdVersion" ] = 1.1 except Exception as e : logger_versions . error ( "update_lipd_v1_1: Exception: {}" . format ( e ) ) logger_versions . info ( "exit update_lipd_v1_1" ) return d
def update_steadystate ( x , z , K , H = None ) : """Add a new measurement ( z ) to the Kalman filter . If z is None , nothing is changed . Parameters x : numpy . array ( dim _ x , 1 ) , or float State estimate vector z : ( dim _ z , 1 ) : array _ like measurement for this update . z can be a scalar if dim _ z is 1, otherwise it must be convertible to a column vector . K : numpy . array , or float Kalman gain matrix H : numpy . array ( dim _ x , dim _ x ) , or float , optional Measurement function . If not provided , a value of 1 is assumed . Returns x : numpy . array Posterior state estimate vector Examples This can handle either the multidimensional or unidimensional case . If all parameters are floats instead of arrays the filter will still work , and return floats for x , P as the result . > > > update _ steadystate ( 1 , 2 , 1 ) # univariate > > > update _ steadystate ( x , P , z , H )"""
if z is None : return x if H is None : H = np . array ( [ 1 ] ) if np . isscalar ( H ) : H = np . array ( [ H ] ) Hx = np . atleast_1d ( dot ( H , x ) ) z = reshape_z ( z , Hx . shape [ 0 ] , x . ndim ) # error ( residual ) between measurement and prediction y = z - Hx # estimate new x with residual scaled by the kalman gain return x + dot ( K , y )
def _group_detect ( templates , stream , threshold , threshold_type , trig_int , plotvar , group_size = None , pre_processed = False , daylong = False , parallel_process = True , xcorr_func = None , concurrency = None , cores = None , ignore_length = False , overlap = "calculate" , debug = 0 , full_peaks = False , process_cores = None , ** kwargs ) : """Pre - process and compute detections for a group of templates . Will process the stream object , so if running in a loop , you will want to copy the stream before passing it to this function . : type templates : list : param templates : List of : class : ` eqcorrscan . core . match _ filter . Template ` : type stream : ` obspy . core . stream . Stream ` : param stream : Continuous data to detect within using the Template . : type threshold : float : param threshold : Threshold level , if using ` threshold _ type = ' MAD ' ` then this will be the multiple of the median absolute deviation . : type threshold _ type : str : param threshold _ type : The type of threshold to be used , can be MAD , absolute or av _ chan _ corr . See Note on thresholding below . : type trig _ int : float : param trig _ int : Minimum gap between detections in seconds . If multiple detections occur within trig _ int of one - another , the one with the highest cross - correlation sum will be selected . : type plotvar : bool : param plotvar : Turn plotting on or off , see warning about plotting below . : type group _ size : int : param group _ size : Maximum number of templates to run at once , use to reduce memory consumption , if unset will use all templates . : type pre _ processed : bool : param pre _ processed : Set to True if ` stream ` has already undergone processing , in this case eqcorrscan will only check that the sampling rate is correct . Defaults to False , which will use the : mod : ` eqcorrscan . utils . pre _ processing ` routines to resample and filter the continuous data . : type daylong : bool : param daylong : Set to True to use the : func : ` eqcorrscan . utils . pre _ processing . dayproc ` routine , which preforms additional checks and is more efficient for day - long data over other methods . : type parallel _ process : bool : param parallel _ process : : type xcorr _ func : str or callable : param xcorr _ func : A str of a registered xcorr function or a callable for implementing a custom xcorr function . For more details see : : func : ` eqcorrscan . utils . correlate . register _ array _ xcorr ` : type concurrency : str : param concurrency : The type of concurrency to apply to the xcorr function . Options are ' multithread ' , ' multiprocess ' , ' concurrent ' . For more details see : func : ` eqcorrscan . utils . correlate . get _ stream _ xcorr ` : type cores : int : param cores : Number of workers for processing and correlation . : type ignore _ length : bool : param ignore _ length : If using daylong = True , then dayproc will try check that the data are there for at least 80 % of the day , if you don ' t want this check ( which will raise an error if too much data are missing ) then set ignore _ length = True . This is not recommended ! : type overlap : float : param overlap : Either None , " calculate " or a float of number of seconds to overlap detection streams by . This is to counter the effects of the delay - and - stack in calculating cross - correlation sums . Setting overlap = " calculate " will work out the appropriate overlap based on the maximum lags within templates . : type debug : int : param debug : Debug level from 0-5 where five is more output , for debug levels 4 and 5 , detections will not be computed in parallel . : type full _ peaks : bool : param full _ peaks : See ` eqcorrscan . utils . findpeaks . find _ peaks2 _ short ` : type process _ cores : int : param process _ cores : Number of processes to use for pre - processing ( if different to ` cores ` ) . : return : : class : ` eqcorrscan . core . match _ filter . Party ` of families of detections ."""
master = templates [ 0 ] # Check that they are all processed the same . lap = 0.0 for template in templates : starts = [ t . stats . starttime for t in template . st . sort ( [ 'starttime' ] ) ] if starts [ - 1 ] - starts [ 0 ] > lap : lap = starts [ - 1 ] - starts [ 0 ] if not template . same_processing ( master ) : raise MatchFilterError ( 'Templates must be processed the same.' ) if overlap is None : overlap = 0.0 elif not isinstance ( overlap , float ) and str ( overlap ) == str ( "calculate" ) : overlap = lap elif not isinstance ( overlap , float ) : raise NotImplementedError ( "%s is not a recognised overlap type" % str ( overlap ) ) if not pre_processed : if process_cores is None : process_cores = cores streams = _group_process ( template_group = templates , parallel = parallel_process , debug = debug , cores = process_cores , stream = stream , daylong = daylong , ignore_length = ignore_length , overlap = overlap ) else : warnings . warn ( 'Not performing any processing on the continuous data.' ) streams = [ stream ] detections = [ ] party = Party ( ) if group_size is not None : n_groups = int ( len ( templates ) / group_size ) if n_groups * group_size < len ( templates ) : n_groups += 1 else : n_groups = 1 for st_chunk in streams : debug_print ( 'Computing detections between %s and %s' % ( st_chunk [ 0 ] . stats . starttime , st_chunk [ 0 ] . stats . endtime ) , 0 , debug ) st_chunk . trim ( starttime = st_chunk [ 0 ] . stats . starttime , endtime = st_chunk [ 0 ] . stats . endtime ) for tr in st_chunk : if len ( tr ) > len ( st_chunk [ 0 ] ) : tr . data = tr . data [ 0 : len ( st_chunk [ 0 ] ) ] for i in range ( n_groups ) : if group_size is not None : end_group = ( i + 1 ) * group_size start_group = i * group_size if i == n_groups : end_group = len ( templates ) else : end_group = len ( templates ) start_group = 0 template_group = [ t for t in templates [ start_group : end_group ] ] detections += match_filter ( template_names = [ t . name for t in template_group ] , template_list = [ t . st for t in template_group ] , st = st_chunk , xcorr_func = xcorr_func , concurrency = concurrency , threshold = threshold , threshold_type = threshold_type , trig_int = trig_int , plotvar = plotvar , debug = debug , cores = cores , full_peaks = full_peaks , peak_cores = process_cores , ** kwargs ) for template in template_group : family = Family ( template = template , detections = [ ] ) for detection in detections : if detection . template_name == template . name : family . detections . append ( detection ) party += family return party
def perms_check ( perms , prefix , ambiguous = False ) : """Return the user ' s perms for the specified prefix perms < dict > permissions dict prefix < string > namespace to check for perms ambiguous < bool = False > if True reverse wildcard matching is active and a perm check for a . b . * will be matched by the user having perms to a . b . c or a . b . d - only use this if you know what you are doing ."""
try : token = prefix . split ( "." ) i = 1 l = len ( token ) r = 0 # collect permission rules with a wildcard in them , so we dont do unecessary # regex searches later on perms_wc = { } for ns , p in perms . items ( ) : if ns . find ( "*" ) > - 1 : perms_wc [ re . escape ( ns ) . replace ( "\*" , "[^\.]+" ) ] = p while i <= l : k = "." . join ( token [ : i ] ) matched = False # check for exact match if perms . has_key ( k ) : r = perms . get ( k ) # check for wildcard matches ( if any wildcard rules exist ) elif perms_wc : for ns , p in perms_wc . items ( ) : a = "^%s$" % ns b = "^%s\." % ns j = len ( a ) u = len ( b ) if j > matched and re . match ( a , k ) : r = p matched = j elif u > matched and re . match ( b , k ) : r = p matched = u # if not matched at all and ambiguous flag is true , do ambiguous matching if not matched and ambiguous : m = "^%s" % re . escape ( k ) . replace ( "\*" , "[^\.]+" ) for ns , p in perms . items ( ) : if re . match ( m , ns ) and p > r : r = p break i += 1 return r except : raise
def _contains_cftime_datetimes ( array ) -> bool : """Check if an array contains cftime . datetime objects"""
try : from cftime import datetime as cftime_datetime except ImportError : return False else : if array . dtype == np . dtype ( 'O' ) and array . size > 0 : sample = array . ravel ( ) [ 0 ] if isinstance ( sample , dask_array_type ) : sample = sample . compute ( ) if isinstance ( sample , np . ndarray ) : sample = sample . item ( ) return isinstance ( sample , cftime_datetime ) else : return False
def _create_variables ( self , n_features ) : """Create the TensorFlow variables for the model . : param n _ features : number of features : return : self"""
w_name = 'weights' self . W = tf . Variable ( tf . truncated_normal ( shape = [ n_features , self . num_hidden ] , stddev = 0.1 ) , name = w_name ) tf . summary . histogram ( w_name , self . W ) bh_name = 'hidden-bias' self . bh_ = tf . Variable ( tf . constant ( 0.1 , shape = [ self . num_hidden ] ) , name = bh_name ) tf . summary . histogram ( bh_name , self . bh_ ) bv_name = 'visible-bias' self . bv_ = tf . Variable ( tf . constant ( 0.1 , shape = [ n_features ] ) , name = bv_name ) tf . summary . histogram ( bv_name , self . bv_ )
def _extract_service_catalog ( self , body ) : """Set the client ' s service catalog from the response data ."""
self . auth_ref = access . create ( body = body ) self . service_catalog = self . auth_ref . service_catalog self . auth_token = self . auth_ref . auth_token self . auth_tenant_id = self . auth_ref . tenant_id self . auth_user_id = self . auth_ref . user_id if not self . endpoint_url : self . endpoint_url = self . service_catalog . url_for ( region_name = self . region_name , service_type = self . service_type , interface = self . endpoint_type )
def on_linkType_changed ( self , evt ) : """User changed link kind , so prepare available fields ."""
if self . current_idx < 0 : evt . Skip ( ) return n = self . linkType . GetSelection ( ) lt_str = self . linkType . GetString ( n ) lt = self . link_code [ lt_str ] self . prep_link_details ( lt ) lnk = self . page_links [ self . current_idx ] lnk [ "update" ] = True lnk [ "kind" ] = lt self . enable_update ( ) if lt == fitz . LINK_GOTO : if not self . toPage . Value . isdecimal ( ) : self . toPage . ChangeValue ( "1" ) self . toPage . Enable ( ) if not self . toLeft . Value . isdecimal ( ) : self . toLeft . ChangeValue ( "0" ) self . toLeft . Enable ( ) if not self . toHeight . Value . isdecimal ( ) : self . toHeight . ChangeValue ( "0" ) self . toHeight . Enable ( ) lnk [ "page" ] = int ( self . toPage . Value ) - 1 lnk [ "to" ] = fitz . Point ( int ( self . toLeft . Value ) , int ( self . toHeight . Value ) ) elif lt == fitz . LINK_GOTOR : if not self . toFile . Value : self . toFile . SetValue ( self . text_in_rect ( ) ) self . toFile . MarkDirty ( ) if not self . toPage . Value . isdecimal ( ) : self . toPage . ChangeValue ( "1" ) if not self . toLeft . Value . isdecimal ( ) : self . toLeft . ChangeValue ( "0" ) if not self . toHeight . Value . isdecimal ( ) : self . toHeight . ChangeValue ( "0" ) self . toLeft . Enable ( ) self . toPage . Enable ( ) self . toFile . Enable ( ) self . toHeight . Enable ( ) lnk [ "file" ] = self . toFile . Value lnk [ "page" ] = int ( self . toPage . Value ) - 1 lnk [ "to" ] = fitz . Point ( int ( self . toLeft . Value ) , int ( self . toHeight . Value ) ) elif lt == fitz . LINK_URI : if not self . toURI . Value : self . toURI . SetValue ( self . text_in_rect ( ) ) self . toURI . MarkDirty ( ) lnk [ "uri" ] = self . toURI . Value self . toURI . Enable ( ) elif lt == fitz . LINK_LAUNCH : if not self . toFile . Value : self . toFile . SetValue ( self . text_in_rect ( ) ) self . toFile . MarkDirty ( ) lnk [ "file" ] = self . toFile . Value self . toFile . Enable ( ) elif lt == fitz . LINK_NAMED : self . toName . SetSelection ( 0 ) self . toName . Enable ( ) self . page_links [ self . current_idx ] = lnk evt . Skip ( ) return
def _handle_location ( self , location ) : """Return an element located at location with flexible args . Args : location : String xpath to use in an Element . find search OR an Element ( which is simply returned ) . Returns : The found Element . Raises : ValueError if the location is a string that results in a find of None ."""
if not isinstance ( location , ElementTree . Element ) : element = self . find ( location ) if element is None : raise ValueError ( "Invalid path!" ) else : element = location return element
def load_obj_from_path ( import_path , prefix = None , ld = dict ( ) ) : """import a python object from an import path ` import _ path ` - a python import path . For instance : mypackage . module . func or mypackage . module . class ` prefix ` ( str ) - a value to prepend to the import path if it isn ' t already there . For instance : load _ obj _ from _ path ( ' module . func ' , prefix = ' mypackage ' ) is the same as load _ obj _ from _ path ( ' mypackage . module . func ' ) ` ld ` ( dict ) key : value data to pass to the logger if an error occurs"""
if prefix and not import_path . startswith ( prefix ) : import_path = '.' . join ( [ prefix , import_path ] ) log . debug ( 'attempting to load a python object from an import path' , extra = dict ( import_path = import_path , ** ld ) ) try : mod = importlib . import_module ( import_path ) return mod # yay , we found a module . return it except : pass # try to extract an object from a module try : path , obj_name = import_path . rsplit ( '.' , 1 ) except ValueError : log_raise ( ( "import path needs at least 1 period in your import path." " An example import path is something like: module.obj" ) , dict ( import_path = import_path , ** ld ) , InvalidImportPath ) try : mod = importlib . import_module ( path ) except ImportError : newpath = path . replace ( prefix , '' , 1 ) . lstrip ( '.' ) log . debug ( "Could not load import path. Trying a different one" , extra = dict ( oldpath = path , newpath = newpath ) ) path = newpath mod = importlib . import_module ( path ) try : obj = getattr ( mod , obj_name ) except AttributeError : log_raise ( ( "object does not exist in given module." " Your import path is not" " properly defined because the given `obj_name` does not exist" ) , dict ( import_path = path , obj_name = obj_name , ** ld ) , InvalidImportPath ) return obj
def read_firmware_file ( file_path ) : """Reads a firmware file into a dequeue for processing . : param file _ path : Path to the firmware file : type file _ path : string : returns : deque"""
data_queue = deque ( ) with open ( file_path ) as firmware_handle : for line in firmware_handle : line = line . rstrip ( ) if line != '' and line [ 0 ] == ':' : data_queue . append ( line + "\r" ) return data_queue
def get_bool ( self , name , default = None ) : """Retrieves an environment variable value as ` ` bool ` ` . Integer values are converted as expected : zero evaluates to ` ` False ` ` , and non - zero to ` ` True ` ` . String values of ` ` ' true ' ` ` and ` ` ' false ' ` ` are evaluated case insensitive . Args : name ( str ) : The case - insensitive , unprefixed variable name . default : If provided , a default value will be returned instead of throwing ` ` EnvironmentError ` ` . Returns : bool : The environment variable ' s value as a ` ` bool ` ` . Raises : EnvironmentError : If the environment variable does not exist , and ` ` default ` ` was not provided . ValueError : If the environment variable value could not be interpreted as a ` ` bool ` ` ."""
if name not in self : if default is not None : return default raise EnvironmentError . not_found ( self . _prefix , name ) return bool ( self . get_int ( name ) )
def _end_of_decade ( self ) : """Reset the date to the last day of the decade . : rtype : Date"""
year = self . year - self . year % YEARS_PER_DECADE + YEARS_PER_DECADE - 1 return self . set ( year , 12 , 31 )