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def _nullify_stdio ( self ) : """Open / dev / null to replace stdin , and stdout / stderr temporarily . In case of odd startup , assume we may be allocated a standard handle ."""
fd = os . open ( '/dev/null' , os . O_RDWR ) try : for stdfd in ( 0 , 1 , 2 ) : if fd != stdfd : os . dup2 ( fd , stdfd ) finally : if fd not in ( 0 , 1 , 2 ) : os . close ( fd )
def set_implicitly_wait ( self ) : """Read implicitly timeout from configuration properties and configure driver implicitly wait"""
implicitly_wait = self . driver_wrapper . config . get_optional ( 'Driver' , 'implicitly_wait' ) if implicitly_wait : self . driver_wrapper . driver . implicitly_wait ( implicitly_wait )
def Main ( ) : """The main program function . Returns : bool : True if successful or False if not ."""
argument_parser = argparse . ArgumentParser ( description = 'Validates dtFabric format definitions.' ) argument_parser . add_argument ( 'source' , nargs = '?' , action = 'store' , metavar = 'PATH' , default = None , help = ( 'path of the file or directory containing the dtFabric format ' 'definitions.' ) ) options = argument_parser . parse_args ( ) if not options . source : print ( 'Source value is missing.' ) print ( '' ) argument_parser . print_help ( ) print ( '' ) return False if not os . path . exists ( options . source ) : print ( 'No such file: {0:s}' . format ( options . source ) ) print ( '' ) return False logging . basicConfig ( level = logging . INFO , format = '[%(levelname)s] %(message)s' ) source_is_directory = os . path . isdir ( options . source ) validator = DefinitionsValidator ( ) if source_is_directory : source_description = os . path . join ( options . source , '*.yaml' ) else : source_description = options . source print ( 'Validating dtFabric definitions in: {0:s}' . format ( source_description ) ) if source_is_directory : result = validator . CheckDirectory ( options . source ) else : result = validator . CheckFile ( options . source ) if not result : print ( 'FAILURE' ) else : print ( 'SUCCESS' ) return result
def get_doc_counts ( self , cache = True ) : """Get the number of related documents of various types for the artist . The types include audio , biographies , blogs , images , news , reviews , songs , videos . Note that these documents can be retrieved by calling artist . < document type > , for example , artist . biographies . Args : Kwargs : cache ( bool ) : A boolean indicating whether or not the cached value should be used ( if available ) . Defaults to True . Returns : A dictionary with one key for each document type , mapped to an integer count of documents . Example : > > > a = artist . Artist ( " The Kinks " ) > > > a . get _ doc _ counts ( ) { u ' audio ' : 194, u ' biographies ' : 9, u ' blogs ' : 379, u ' images ' : 177, u ' news ' : 84, u ' reviews ' : 110, u ' songs ' : 499, u ' videos ' : 340}"""
if not cache or not ( 'doc_counts' in self . cache ) : response = self . get_attribute ( "profile" , bucket = 'doc_counts' ) self . cache [ 'doc_counts' ] = response [ 'artist' ] [ 'doc_counts' ] return self . cache [ 'doc_counts' ]
def know ( self , what , confidence ) : """Know something with the given confidence , and return self for chaining . If confidence is higher than that of what we already know , replace what we already know with what you ' re telling us ."""
if confidence > self . confidence : self . best = what self . confidence = confidence return self
def unique_element ( ll ) : """returns unique elements from a list preserving the original order"""
seen = { } result = [ ] for item in ll : if item in seen : continue seen [ item ] = 1 result . append ( item ) return result
def request ( self , uri , method = GET , headers = None , cookies = None , params = None , data = None , post_files = None , ** kwargs ) : """Makes a request using requests @ param uri : The uri to send request @ param method : Method to use to send request @ param headers : Any headers to send with request @ param cookies : Request cookies ( in addition to session cookies ) @ param params : Request parameters @ param data : Request data @ param kwargs : other options to pass to underlying request @ rtype : requests . Response @ return : The response"""
coyote_args = { 'headers' : headers , 'cookies' : cookies , 'params' : params , 'files' : post_files , 'data' : data , 'verify' : self . verify_certificates , } coyote_args . update ( kwargs ) if method == self . POST : response = self . session . post ( uri , ** coyote_args ) elif method == self . PUT : response = self . session . put ( uri , ** coyote_args ) elif method == self . PATCH : response = self . session . patch ( uri , ** coyote_args ) elif method == self . DELETE : response = self . session . delete ( uri , ** coyote_args ) else : # Default to GET response = self . session . get ( uri , ** coyote_args ) self . responses . append ( response ) while len ( self . responses ) > self . max_response_history : self . responses . popleft ( ) return response
def readEncodedU32 ( self ) : """Read a encoded unsigned int"""
self . reset_bits_pending ( ) ; result = self . readUI8 ( ) ; if result & 0x80 != 0 : result = ( result & 0x7f ) | ( self . readUI8 ( ) << 7 ) if result & 0x4000 != 0 : result = ( result & 0x3fff ) | ( self . readUI8 ( ) << 14 ) if result & 0x200000 != 0 : result = ( result & 0x1fffff ) | ( self . readUI8 ( ) << 21 ) if result & 0x10000000 != 0 : result = ( result & 0xfffffff ) | ( self . readUI8 ( ) << 28 ) return result
def prepare_framework_container_def ( model , instance_type , s3_operations ) : """Prepare the framework model container information . Specify related S3 operations for Airflow to perform . ( Upload ` source _ dir ` ) Args : model ( sagemaker . model . FrameworkModel ) : The framework model instance _ type ( str ) : The EC2 instance type to deploy this Model to . For example , ' ml . p2 . xlarge ' . s3 _ operations ( dict ) : The dict to specify S3 operations ( upload ` source _ dir ` ) . Returns : dict : The container information of this framework model ."""
deploy_image = model . image if not deploy_image : region_name = model . sagemaker_session . boto_session . region_name deploy_image = fw_utils . create_image_uri ( region_name , model . __framework_name__ , instance_type , model . framework_version , model . py_version ) base_name = utils . base_name_from_image ( deploy_image ) model . name = model . name or utils . name_from_base ( base_name ) bucket = model . bucket or model . sagemaker_session . _default_bucket script = os . path . basename ( model . entry_point ) key = '{}/source/sourcedir.tar.gz' . format ( model . name ) if model . source_dir and model . source_dir . lower ( ) . startswith ( 's3://' ) : code_dir = model . source_dir model . uploaded_code = fw_utils . UploadedCode ( s3_prefix = code_dir , script_name = script ) else : code_dir = 's3://{}/{}' . format ( bucket , key ) model . uploaded_code = fw_utils . UploadedCode ( s3_prefix = code_dir , script_name = script ) s3_operations [ 'S3Upload' ] = [ { 'Path' : model . source_dir or script , 'Bucket' : bucket , 'Key' : key , 'Tar' : True } ] deploy_env = dict ( model . env ) deploy_env . update ( model . _framework_env_vars ( ) ) try : if model . model_server_workers : deploy_env [ sagemaker . model . MODEL_SERVER_WORKERS_PARAM_NAME . upper ( ) ] = str ( model . model_server_workers ) except AttributeError : # This applies to a FrameworkModel which is not SageMaker Deep Learning Framework Model pass return sagemaker . container_def ( deploy_image , model . model_data , deploy_env )
def _render_op ( self , identifier , hs = None , dagger = False , args = None , superop = False ) : """Render an operator Args : identifier ( str or SymbolicLabelBase ) : The identifier ( name / symbol ) of the operator . May include a subscript , denoted by ' _ ' . hs ( HilbertSpace ) : The Hilbert space in which the operator is defined dagger ( bool ) : Whether the operator should be daggered args ( list ) : A list of expressions that will be rendered with : meth : ` doprint ` , joined with commas , enclosed in parenthesis superop ( bool ) : Whether the operator is a super - operator"""
hs_label = None if hs is not None and self . _settings [ 'show_hs_label' ] : hs_label = self . _render_hs_label ( hs ) name , total_subscript , total_superscript , args_str = self . _split_op ( identifier , hs_label , dagger , args ) if self . _settings [ 'unicode_op_hats' ] and len ( name ) == 1 : if superop : res = name else : res = modifier_dict [ 'hat' ] ( name ) else : res = name res = render_unicode_sub_super ( res , [ total_subscript ] , [ total_superscript ] , sub_first = True , translate_symbols = True , unicode_sub_super = self . _settings [ 'unicode_sub_super' ] ) res += args_str return res
def write_lines ( self , lines , level = 0 ) : """Append multiple new lines"""
for line in lines : self . write_line ( line , level )
def pdf_rotate ( input : str , counter_clockwise : bool = False , pages : [ str ] = None , output : str = None , ) : """Rotate the given Pdf files clockwise or counter clockwise . : param inputs : pdf files : param counter _ clockwise : rotate counter clockwise if true else clockwise : param pages : list of page numbers to rotate , if None all pages will be rotated"""
infile = open ( input , "rb" ) reader = PdfFileReader ( infile ) writer = PdfFileWriter ( ) # get pages from source depending on pages parameter if pages is None : source_pages = reader . pages else : pages = parse_rangearg ( pages , len ( reader . pages ) ) source_pages = [ reader . getPage ( i ) for i in pages ] # rotate pages and add to writer for i , page in enumerate ( source_pages ) : if pages is None or i in pages : if counter_clockwise : writer . addPage ( page . rotateCounterClockwise ( 90 ) ) else : writer . addPage ( page . rotateClockwise ( 90 ) ) else : writer . addPage ( page ) # Open output file or temporary file for writing if output is None : outfile = NamedTemporaryFile ( delete = False ) else : if not os . path . isfile ( output ) or overwrite_dlg ( output ) : outfile = open ( output , "wb" ) else : return # Write to file writer . write ( outfile ) infile . close ( ) outfile . close ( ) # If no output defined move temporary file to input if output is None : if overwrite_dlg ( input ) : os . remove ( input ) move ( outfile . name , input ) else : os . remove ( outfile . name )
async def on_raw_kick ( self , message ) : """KICK command ."""
kicker , kickermeta = self . _parse_user ( message . source ) self . _sync_user ( kicker , kickermeta ) if len ( message . params ) > 2 : channels , targets , reason = message . params else : channels , targets = message . params reason = None channels = channels . split ( ',' ) targets = targets . split ( ',' ) for channel , target in itertools . product ( channels , targets ) : target , targetmeta = self . _parse_user ( target ) self . _sync_user ( target , targetmeta ) if self . is_same_nick ( target , self . nickname ) : self . _destroy_channel ( channel ) else : # Update nick list on channel . if self . in_channel ( channel ) : self . _destroy_user ( target , channel ) await self . on_kick ( channel , target , kicker , reason )
def beacon ( config ) : '''Watch the configured files Example Config . . code - block : : yaml beacons : inotify : - files : / path / to / file / or / dir : mask : - open - create - close _ write recurse : True auto _ add : True exclude : - / path / to / file / or / dir / exclude1 - / path / to / file / or / dir / exclude2 - / path / to / file / or / dir / regex [ a - m ] * $ : regex : True - coalesce : True The mask list can contain the following events ( the default mask is create , delete , and modify ) : * access - File accessed * attrib - File metadata changed * close _ nowrite - Unwritable file closed * close _ write - Writable file closed * create - File created in watched directory * delete - File deleted from watched directory * delete _ self - Watched file or directory deleted * modify - File modified * moved _ from - File moved out of watched directory * moved _ to - File moved into watched directory * move _ self - Watched file moved * open - File opened The mask can also contain the following options : * dont _ follow - Don ' t dereference symbolic links * excl _ unlink - Omit events for children after they have been unlinked * oneshot - Remove watch after one event * onlydir - Operate only if name is directory recurse : Recursively watch files in the directory auto _ add : Automatically start watching files that are created in the watched directory exclude : Exclude directories or files from triggering events in the watched directory . Can use regex if regex is set to True coalesce : If this coalescing option is enabled , events are filtered based on their unicity , only unique events are enqueued , doublons are discarded . An event is unique when the combination of its fields ( wd , mask , cookie , name ) is unique among events of a same batch . After a batch of events is processed any events are accepted again . This option is top - level ( at the same level as the path ) and therefore affects all paths that are being watched . This is due to this option being at the Notifier level in pyinotify .'''
_config = { } list ( map ( _config . update , config ) ) ret = [ ] notifier = _get_notifier ( _config ) wm = notifier . _watch_manager # Read in existing events if notifier . check_events ( 1 ) : notifier . read_events ( ) notifier . process_events ( ) queue = __context__ [ 'inotify.queue' ] while queue : event = queue . popleft ( ) _append = True # Find the matching path in config path = event . path while path != '/' : if path in _config . get ( 'files' , { } ) : break path = os . path . dirname ( path ) excludes = _config [ 'files' ] [ path ] . get ( 'exclude' , '' ) if excludes and isinstance ( excludes , list ) : for exclude in excludes : if isinstance ( exclude , dict ) : _exclude = next ( iter ( exclude ) ) if exclude [ _exclude ] . get ( 'regex' , False ) : try : if re . search ( _exclude , event . pathname ) : _append = False except Exception : log . warning ( 'Failed to compile regex: %s' , _exclude ) else : exclude = _exclude elif '*' in exclude : if fnmatch . fnmatch ( event . pathname , exclude ) : _append = False else : if event . pathname . startswith ( exclude ) : _append = False if _append : sub = { 'tag' : event . path , 'path' : event . pathname , 'change' : event . maskname } ret . append ( sub ) else : log . info ( 'Excluding %s from event for %s' , event . pathname , path ) # Get paths currently being watched current = set ( ) for wd in wm . watches : current . add ( wm . watches [ wd ] . path ) # Update existing watches and add new ones # TODO : make the config handle more options for path in _config . get ( 'files' , ( ) ) : if isinstance ( _config [ 'files' ] [ path ] , dict ) : mask = _config [ 'files' ] [ path ] . get ( 'mask' , DEFAULT_MASK ) if isinstance ( mask , list ) : r_mask = 0 for sub in mask : r_mask |= _get_mask ( sub ) elif isinstance ( mask , salt . ext . six . binary_type ) : r_mask = _get_mask ( mask ) else : r_mask = mask mask = r_mask rec = _config [ 'files' ] [ path ] . get ( 'recurse' , False ) auto_add = _config [ 'files' ] [ path ] . get ( 'auto_add' , False ) else : mask = DEFAULT_MASK rec = False auto_add = False if path in current : for wd in wm . watches : if path == wm . watches [ wd ] . path : update = False if wm . watches [ wd ] . mask != mask : update = True if wm . watches [ wd ] . auto_add != auto_add : update = True if update : wm . update_watch ( wd , mask = mask , rec = rec , auto_add = auto_add ) elif os . path . exists ( path ) : excludes = _config [ 'files' ] [ path ] . get ( 'exclude' , '' ) excl = None if isinstance ( excludes , list ) : excl = [ ] for exclude in excludes : if isinstance ( exclude , dict ) : excl . append ( list ( exclude ) [ 0 ] ) else : excl . append ( exclude ) excl = pyinotify . ExcludeFilter ( excl ) wm . add_watch ( path , mask , rec = rec , auto_add = auto_add , exclude_filter = excl ) # Return event data return ret
def update_data_display ( self , data ) : """Triggered when the selected device / IMU is changed . Updates the background colours of the text widgets in the UI to indicate which sensors have calibration data available ( green ) and which do not ( red )"""
acc_cal = self . ACC_TIMESTAMP in data mag_cal = self . MAG_TIMESTAMP in data gyro_cal = self . GYRO_TIMESTAMP in data uncal = 'QLineEdit {background-color: #cc3333;};' cal = 'QLineEdit {background-color: #33cc33;};' if acc_cal : self . dataAccX . setStyleSheet ( cal ) self . dataAccY . setStyleSheet ( cal ) self . dataAccZ . setStyleSheet ( cal ) else : self . dataAccX . setStyleSheet ( uncal ) self . dataAccY . setStyleSheet ( uncal ) self . dataAccZ . setStyleSheet ( uncal ) if gyro_cal : self . dataGyroX . setStyleSheet ( cal ) self . dataGyroY . setStyleSheet ( cal ) self . dataGyroZ . setStyleSheet ( cal ) else : self . dataGyroX . setStyleSheet ( uncal ) self . dataGyroY . setStyleSheet ( uncal ) self . dataGyroZ . setStyleSheet ( uncal ) if mag_cal : self . dataMagX . setStyleSheet ( cal ) self . dataMagY . setStyleSheet ( cal ) self . dataMagZ . setStyleSheet ( cal ) else : self . dataMagX . setStyleSheet ( uncal ) self . dataMagY . setStyleSheet ( uncal ) self . dataMagZ . setStyleSheet ( uncal )
def purchase_ip ( self , debug = False ) : """Return an ip object representing a new bought IP @ param debug [ Boolean ] if true , request and response will be printed @ return ( Ip ) : Ip object"""
json_scheme = self . gen_def_json_scheme ( 'SetPurchaseIpAddress' ) json_obj = self . call_method_post ( method = 'SetPurchaseIpAddress' , json_scheme = json_scheme , debug = debug ) try : ip = Ip ( ) ip . ip_addr = json_obj [ 'Value' ] [ 'Value' ] ip . resid = json_obj [ 'Value' ] [ 'ResourceId' ] return ip except : raise Exception ( 'Unknown error retrieving IP.' )
def to_json ( df , columns , confidence = { } ) : """Transforms dataframe to properly formatted json response"""
records = [ ] display_cols = list ( columns . keys ( ) ) if not display_cols : display_cols = list ( df . columns ) bounds = { } for c in confidence : bounds [ c ] = { "min" : df [ confidence [ c ] [ "lower" ] ] . min ( ) , "max" : df [ confidence [ c ] [ "upper" ] ] . max ( ) , "lower" : confidence [ c ] [ "lower" ] , "upper" : confidence [ c ] [ "upper" ] } labels = { } for c in display_cols : if "label" in columns [ c ] : labels [ c ] = columns [ c ] [ "label" ] else : labels [ c ] = c for i , row in df . iterrows ( ) : row_ = DataTable . format_row ( row , bounds , columns ) records . append ( { labels [ c ] : row_ [ c ] for c in display_cols } ) return { "data" : records , "columns" : [ { "data" : labels [ c ] } for c in display_cols ] }
def addAnalysis ( self , analysis , position = None ) : """- add the analysis to self . Analyses ( ) . - position is overruled if a slot for this analysis ' parent exists - if position is None , next available pos is used ."""
# Cannot add an analysis if not open , unless a retest if api . get_review_status ( self ) not in [ "open" , "to_be_verified" ] : retracted = analysis . getRetestOf ( ) if retracted not in self . getAnalyses ( ) : return # Cannot add an analysis that is assigned already if analysis . getWorksheet ( ) : return # Just in case analyses = self . getAnalyses ( ) if analysis in analyses : analyses = filter ( lambda an : an != analysis , analyses ) self . setAnalyses ( analyses ) self . updateLayout ( ) # Cannot add an analysis if the assign transition is not possible # We need to bypass the guard ' s check for current context ! api . get_request ( ) . set ( "ws_uid" , api . get_uid ( self ) ) if not isTransitionAllowed ( analysis , "assign" ) : return # Assign the instrument from the worksheet to the analysis , if possible instrument = self . getInstrument ( ) if instrument and analysis . isInstrumentAllowed ( instrument ) : # TODO Analysis Instrument + Method assignment methods = instrument . getMethods ( ) if methods : # Set the first method assigned to the selected instrument analysis . setMethod ( methods [ 0 ] ) analysis . setInstrument ( instrument ) elif not instrument : # If the ws doesn ' t have an instrument try to set the method method = self . getMethod ( ) if method and analysis . isMethodAllowed ( method ) : analysis . setMethod ( method ) # Transition analysis to " assigned " actions_pool = ActionHandlerPool . get_instance ( ) actions_pool . queue_pool ( ) doActionFor ( analysis , "assign" ) self . setAnalyses ( analyses + [ analysis ] ) self . addToLayout ( analysis , position ) # Try to rollback the worksheet to prevent inconsistencies doActionFor ( self , "rollback_to_open" ) # Reindex Worksheet idxs = [ "getAnalysesUIDs" ] push_reindex_to_actions_pool ( self , idxs = idxs ) # Reindex Analysis Request , if any if IRequestAnalysis . providedBy ( analysis ) : idxs = [ 'assigned_state' , 'getDueDate' ] push_reindex_to_actions_pool ( analysis . getRequest ( ) , idxs = idxs ) # Resume the actions pool actions_pool . resume ( )
def calculate_nf ( sample_frame , ref_targets , ref_sample ) : """Calculates a normalization factor from the geometric mean of the expression of all ref _ targets , normalized to a reference sample . : param DataFrame sample _ frame : A sample data frame . : param iterable ref _ targets : A list or Series of target names . : param string ref _ sample : The name of the sample to normalize against . : return : a Series indexed by sample name containing normalization factors for each sample ."""
grouped = sample_frame . groupby ( [ 'Target' , 'Sample' ] ) [ 'Cq' ] . aggregate ( average_cq ) samples = sample_frame [ 'Sample' ] . unique ( ) nfs = gmean ( [ pow ( 2 , - grouped . ix [ zip ( repeat ( ref_gene ) , samples ) ] + grouped . ix [ ref_gene , ref_sample ] ) for ref_gene in ref_targets ] ) return pd . Series ( nfs , index = samples )
def print_experiments ( experiments ) : """Prints job details in a table . Includes urls and mode parameters"""
headers = [ "JOB NAME" , "CREATED" , "STATUS" , "DURATION(s)" , "INSTANCE" , "DESCRIPTION" , "METRICS" ] expt_list = [ ] for experiment in experiments : expt_list . append ( [ normalize_job_name ( experiment . name ) , experiment . created_pretty , experiment . state , experiment . duration_rounded , experiment . instance_type_trimmed , experiment . description , format_metrics ( experiment . latest_metrics ) ] ) floyd_logger . info ( tabulate ( expt_list , headers = headers ) )
def init_app ( self , app ) : '''Configures an application . This registers an ` after _ request ` call , and attaches this ` LoginManager ` to it as ` app . login _ manager ` .'''
self . _config = app . config . get ( 'LDAP' , { } ) app . ldap_login_manager = self self . config . setdefault ( 'BIND_DN' , '' ) self . config . setdefault ( 'BIND_AUTH' , '' ) self . config . setdefault ( 'URI' , 'ldap://127.0.0.1' ) self . config . setdefault ( 'OPTIONS' , { } ) # Referrals are disabled by default self . config [ 'OPTIONS' ] . setdefault ( ldap . OPT_REFERRALS , ldap . OPT_OFF ) if self . config . get ( 'USER_SEARCH' ) and not isinstance ( self . config [ 'USER_SEARCH' ] , list ) : self . config [ 'USER_SEARCH' ] = [ self . config [ 'USER_SEARCH' ] ]
def assemble_cx ( ) : """Assemble INDRA Statements and return CX network json ."""
if request . method == 'OPTIONS' : return { } response = request . body . read ( ) . decode ( 'utf-8' ) body = json . loads ( response ) stmts_json = body . get ( 'statements' ) stmts = stmts_from_json ( stmts_json ) ca = CxAssembler ( stmts ) model_str = ca . make_model ( ) res = { 'model' : model_str } return res
def resolve ( self , definitions ) : """Resolve named references to other WSDL objects . This includes cross - linking information ( from ) the portType ( to ) the I { soap } protocol information on the binding for each operation . @ param definitions : A definitions object . @ type definitions : L { Definitions }"""
self . resolveport ( definitions ) for op in self . operations . values ( ) : self . resolvesoapbody ( definitions , op ) self . resolveheaders ( definitions , op ) self . resolvefaults ( definitions , op )
def create_layer_2_socket ( ) : """create _ layer _ 2 _ socket"""
# create a socket for recording layer 2 , 3 and 4 frames s = None try : log . info ( "Creating l234 socket" ) s = socket . socket ( socket . AF_PACKET , socket . SOCK_RAW , socket . ntohs ( 0x0003 ) ) except socket . error as msg : log . error ( ( "Socket could not be created ex={}" ) . format ( msg ) ) return s
def logs_handle_build_job ( job_uuid : str , job_name : str , log_lines : Optional [ Union [ str , Iterable [ str ] ] ] , temp : bool = True ) -> None : """Task handling for sidecars logs ."""
handle_build_job_logs ( job_uuid = job_uuid , job_name = job_name , log_lines = log_lines , temp = temp )
def process_request ( request ) : """Adds a " mobile " attribute to the request which is True or False depending on whether the request should be considered to come from a small - screen device such as a phone or a PDA"""
if 'HTTP_X_OPERAMINI_FEATURES' in request . META : # Then it ' s running opera mini . ' Nuff said . # Reference from : # http : / / dev . opera . com / articles / view / opera - mini - request - headers / request . mobile = True return None if 'HTTP_ACCEPT' in request . META : s = request . META [ 'HTTP_ACCEPT' ] . lower ( ) if 'application/vnd.wap.xhtml+xml' in s : # Then it ' s a wap browser request . mobile = True return None if 'HTTP_USER_AGENT' in request . META : # This takes the most processing . Surprisingly enough , when I # Experimented on my own machine , this was the most efficient # algorithm . Certainly more so than regexes . # Also , Caching didn ' t help much , with real - world caches . s = request . META [ 'HTTP_USER_AGENT' ] . lower ( ) for ua in search_strings : if ua in s : # check if we are ignoring this user agent : ( IPad ) if not ignore_user_agent ( s ) : request . mobile = True if MOBI_DETECT_TABLET : request . tablet = _is_tablet ( s ) return None # Otherwise it ' s not a mobile request . mobile = False request . tablet = False return None
def is_direct_subclass ( class_ , of ) : """Check whether given class is a direct subclass of the other . : param class _ : Class to check : param of : Superclass to check against : return : Boolean result of the test . . versionadded : : 0.0.4"""
ensure_class ( class_ ) ensure_class ( of ) # TODO ( xion ) : support predicates in addition to classes return of in class_ . __bases__
def set_rate ( self , param ) : """Models " Rate Command " functionality of device . Sets the target rate of temperature change . : param param : Rate of temperature change in C / min , multiplied by 100 , as a string . Must be positive . : return : Empty string ."""
# TODO : Is not having leading zeroes / 4 digits an error ? rate = int ( param ) if 1 <= rate <= 15000 : self . device . temperature_rate = rate / 100.0 return ""
def json ( self ) : """Return a JSON - serializable representation of this result . The output of this function can be converted to a serialized string with : any : ` json . dumps ` ."""
data = super ( CalTRACKHourlyModel , self ) . json ( ) data . update ( { "occupancy_lookup" : self . occupancy_lookup . to_json ( orient = "split" ) , "temperature_bins" : self . temperature_bins . to_json ( orient = "split" ) , } ) return data
def make_organisms ( self , genome_list , genome_dir ) : '''Organism factory method . Appends organisms to the organisms list . Args genome _ list ( list ) genome _ dir ( string )'''
for genome in genome_list : genome_path = genome_dir + genome handle = open ( genome_path , "rU" ) print 'Adding organism attributes for' , genome try : seq_record = SeqIO . read ( handle , "genbank" ) self . organisms . append ( Organism ( seq_record , genome_path , self ) ) del ( seq_record ) except ValueError , e : print genome , str ( e ) except AssertionError , e : print genome , str ( e ) except UnboundLocalError , e : print genome , str ( e ) handle . close ( )
def scroll_to_horizontally ( self , obj , * args , ** selectors ) : """Scroll ( horizontally ) on the object : obj to specific UI object which has * selectors * attributes appears . Return true if the UI object , else return false . See ` Scroll To Vertically ` for more details ."""
return obj . scroll . horiz . to ( ** selectors )
def get_bounding_box ( self , lon , lat , trt = None , mag = None ) : """Build a bounding box around the given lon , lat by computing the maximum _ distance at the given tectonic region type and magnitude . : param lon : longitude : param lat : latitude : param trt : tectonic region type , possibly None : param mag : magnitude , possibly None : returns : min _ lon , min _ lat , max _ lon , max _ lat"""
if trt is None : # take the greatest integration distance maxdist = max ( self ( trt , mag ) for trt in self . dic ) else : # get the integration distance for the given TRT maxdist = self ( trt , mag ) a1 = min ( maxdist * KM_TO_DEGREES , 90 ) a2 = min ( angular_distance ( maxdist , lat ) , 180 ) return lon - a2 , lat - a1 , lon + a2 , lat + a1
def execute_notebook ( input_path , output_path , parameters = None , engine_name = None , prepare_only = False , kernel_name = None , progress_bar = True , log_output = False , start_timeout = 60 , report_mode = False , cwd = None , ) : """Executes a single notebook locally . Parameters input _ path : str Path to input notebook output _ path : str Path to save executed notebook parameters : dict , optional Arbitrary keyword arguments to pass to the notebook parameters engine _ name : str , optional Name of execution engine to use prepare _ only : bool , optional Flag to determine if execution should occur or not kernel _ name : str , optional Name of kernel to execute the notebook against progress _ bar : bool , optional Flag for whether or not to show the progress bar . log _ output : bool , optional Flag for whether or not to write notebook output _ path to ` stderr ` start _ timeout : int , optional Duration in seconds to wait for kernel start - up report _ mode : bool , optional Flag for whether or not to hide input . cwd : str , optional Working directory to use when executing the notebook Returns nb : NotebookNode Executed notebook object"""
path_parameters = add_builtin_parameters ( parameters ) input_path = parameterize_path ( input_path , path_parameters ) output_path = parameterize_path ( output_path , path_parameters ) logger . info ( "Input Notebook: %s" % get_pretty_path ( input_path ) ) logger . info ( "Output Notebook: %s" % get_pretty_path ( output_path ) ) with local_file_io_cwd ( ) : if cwd is not None : logger . info ( "Working directory: {}" . format ( get_pretty_path ( cwd ) ) ) nb = load_notebook_node ( input_path ) # Parameterize the Notebook . if parameters : nb = parameterize_notebook ( nb , parameters , report_mode ) nb = prepare_notebook_metadata ( nb , input_path , output_path , report_mode ) if not prepare_only : # Fetch the kernel name if it ' s not supplied kernel_name = kernel_name or nb . metadata . kernelspec . name # Execute the Notebook in ` cwd ` if it is set with chdir ( cwd ) : nb = papermill_engines . execute_notebook_with_engine ( engine_name , nb , input_path = input_path , output_path = output_path , kernel_name = kernel_name , progress_bar = progress_bar , log_output = log_output , start_timeout = start_timeout , ) # Check for errors first ( it saves on error before raising ) raise_for_execution_errors ( nb , output_path ) # Write final output in case the engine didn ' t write it on cell completion . write_ipynb ( nb , output_path ) return nb
def call_hpp ( self , message , action , hmac_key = "" , ** kwargs ) : """This will call the adyen hpp . hmac _ key and platform are pulled from root module level and or self object . AdyenResult will be returned on 200 response . Otherwise , an exception is raised . Args : request _ data ( dict ) : The dictionary of the request to place . This should be in the structure of the Adyen API . https : / / docs . adyen . com / manuals / api - manual service ( str ) : This is the API service to be called . action ( str ) : The specific action of the API service to be called idempotency ( bool , optional ) : Whether the transaction should be processed idempotently . https : / / docs . adyen . com / manuals / api - manual # apiidempotency Returns : AdyenResult : The AdyenResult is returned when a request was succesful . : param message : : param hmac _ key :"""
if not self . http_init : self . http_client = HTTPClient ( self . app_name , self . USER_AGENT_SUFFIX , self . LIB_VERSION , self . http_force ) self . http_init = True # hmac provided in function has highest priority . fallback to self then # root module and ensure that it is set . hmac = hmac_key if self . hmac : hmac = self . hmac elif not hmac : errorstring = """Please set an hmac with your Adyen.Adyen class instance. 'Adyen.hmac = \"!WR#F@...\"' or as an additional parameter in the function call ie. 'Adyen.hpp.directory_lookup(hmac=\"!WR#F@...\"'. Please reach out to support@Adyen.com if the issue persists.""" raise AdyenInvalidRequestError ( errorstring ) # platform provided in self has highest priority , # fallback to root module and ensure that it is set . platform = self . platform if not isinstance ( platform , str ) : errorstring = "'platform' must be type string" raise TypeError ( errorstring ) elif platform . lower ( ) not in [ 'live' , 'test' ] : errorstring = " 'platform' must be the value of 'live' or 'test' " raise ValueError ( errorstring ) if 'skinCode' not in message : message [ 'skinCode' ] = self . skin_code if 'merchantAccount' not in message : message [ 'merchantAccount' ] = self . merchant_account if message [ 'merchantAccount' ] == "" : message [ 'merchantAccount' ] = self . merchant_account message [ "merchantSig" ] = util . generate_hpp_sig ( message , hmac ) url = self . _determine_hpp_url ( platform , action ) raw_response , raw_request , status_code , headers = self . http_client . request ( url , data = message , username = "" , password = "" , ** kwargs ) # Creates AdyenResponse if request was successful , raises error if not . adyen_result = self . _handle_response ( url , raw_response , raw_request , status_code , headers , message ) return adyen_result
def build_trees_from_text ( text , layer , ** kwargs ) : '''Given a text object and the name of the layer where dependency syntactic relations are stored , builds trees ( estnltk . syntax . utils . Tree objects ) from all the sentences of the text and returns as a list of Trees . Uses the method build _ trees _ from _ sentence ( ) for acquiring trees of each sentence ; Note that there is one - to - many correspondence between EstNLTK ' s sentences and dependency syntactic trees : one sentence can evoke multiple trees ;'''
from estnltk . text import Text assert isinstance ( text , Text ) , '(!) Unexpected text argument! Should be Estnltk\'s Text object.' assert layer in text , '(!) The layer ' + str ( layer ) + ' is missing from the input text.' text_sentences = list ( text . divide ( layer = WORDS , by = SENTENCES ) ) all_sentence_trees = [ ] # Collected sentence trees prev_sent_id = - 1 # ( ! ) Note : if the Text object has been split into smaller Texts with split _ by ( ) , # SENT _ ID - s still refer to old text , and thus are not useful as indices # anymore ; # Therefore , we also use another variable - - norm _ prev _ sent _ id - - that always # counts sentences starting from 0 , and use SENT _ ID / prev _ sent _ id only for # deciding whether one sentence ends and another begins ; norm_prev_sent_id = - 1 current_sentence = [ ] k = 0 while k < len ( text [ layer ] ) : node_desc = text [ layer ] [ k ] if prev_sent_id != node_desc [ SENT_ID ] and current_sentence : norm_prev_sent_id += 1 # If the index of the sentence has changed , and we have collected a sentence , # then build tree ( s ) from this sentence assert norm_prev_sent_id < len ( text_sentences ) , '(!) Sentence with the index ' + str ( norm_prev_sent_id ) + ' not found from the input text.' sentence = text_sentences [ norm_prev_sent_id ] trees_of_sentence = build_trees_from_sentence ( sentence , current_sentence , layer , sentence_id = norm_prev_sent_id , ** kwargs ) # Record trees constructed from this sentence all_sentence_trees . extend ( trees_of_sentence ) # Reset the sentence collector current_sentence = [ ] # Collect sentence current_sentence . append ( node_desc ) prev_sent_id = node_desc [ SENT_ID ] k += 1 if current_sentence : norm_prev_sent_id += 1 assert norm_prev_sent_id < len ( text_sentences ) , '(!) Sentence with the index ' + str ( norm_prev_sent_id ) + ' not found from the input text.' sentence = text_sentences [ norm_prev_sent_id ] # If we have collected a sentence , then build tree ( s ) from this sentence trees_of_sentence = build_trees_from_sentence ( sentence , current_sentence , layer , sentence_id = norm_prev_sent_id , ** kwargs ) # Record trees constructed from this sentence all_sentence_trees . extend ( trees_of_sentence ) return all_sentence_trees
def _setup_apikey_policy ( config , params ) : """Setup ` nefertari . ApiKeyAuthenticationPolicy ` . Notes : * User may provide model name in : params [ ' user _ model ' ] : do define the name of the user model . * ` auth _ model . get _ groups _ by _ token ` is used to perform username and token check * ` auth _ model . get _ token _ credentials ` is used to get username and token from userid * Also connects basic routes to perform authentication actions . Arguments : : config : Pyramid Configurator instance . : params : Nefertari dictset which contains security scheme ` settings ` ."""
from nefertari . authentication . views import ( TokenAuthRegisterView , TokenAuthClaimView , TokenAuthResetView ) log . info ( 'Configuring ApiKey Authn policy' ) auth_model = config . registry . auth_model params [ 'check' ] = auth_model . get_groups_by_token params [ 'credentials_callback' ] = auth_model . get_token_credentials params [ 'user_model' ] = auth_model config . add_request_method ( auth_model . get_authuser_by_name , 'user' , reify = True ) policy = ApiKeyAuthenticationPolicy ( ** params ) RegisterViewBase = TokenAuthRegisterView if config . registry . database_acls : class RegisterViewBase ( ACLAssignRegisterMixin , TokenAuthRegisterView ) : pass class RamsesTokenAuthRegisterView ( RegisterViewBase ) : Model = auth_model class RamsesTokenAuthClaimView ( TokenAuthClaimView ) : Model = auth_model class RamsesTokenAuthResetView ( TokenAuthResetView ) : Model = auth_model common_kw = { 'prefix' : 'auth' , 'factory' : 'nefertari.acl.AuthenticationACL' , } root = config . get_root_resource ( ) root . add ( 'register' , view = RamsesTokenAuthRegisterView , ** common_kw ) root . add ( 'token' , view = RamsesTokenAuthClaimView , ** common_kw ) root . add ( 'reset_token' , view = RamsesTokenAuthResetView , ** common_kw ) return policy
def _model ( self , beta ) : """Creates the structure of the model ( model matrices etc ) Parameters beta : np . ndarray Contains untransformed starting values for the latent variables Returns mu : np . ndarray Contains the predicted values ( location ) for the time series Y : np . ndarray Contains the length - adjusted time series ( accounting for lags )"""
Y = np . array ( self . data [ self . max_lag : ] ) # Transform latent variables z = np . array ( [ self . latent_variables . z_list [ k ] . prior . transform ( beta [ k ] ) for k in range ( beta . shape [ 0 ] ) ] ) bias = z [ self . latent_variables . z_indices [ 'Bias' ] [ 'start' ] : self . latent_variables . z_indices [ 'Bias' ] [ 'end' ] + 1 ] bias = np . reshape ( bias , ( - 1 , self . units ) ) output_bias = z [ self . latent_variables . z_indices [ 'Output bias' ] [ 'start' ] ] input_weights = z [ self . latent_variables . z_indices [ 'Input weight' ] [ 'start' ] : self . latent_variables . z_indices [ 'Input weight' ] [ 'end' ] + 1 ] input_weights = np . reshape ( input_weights , ( - 1 , self . units ) ) output_weights = z [ self . latent_variables . z_indices [ 'Output weight' ] [ 'start' ] : self . latent_variables . z_indices [ 'Output weight' ] [ 'end' ] + 1 ] # Construct neural network h = self . activation ( self . X . T . dot ( input_weights ) + bias [ 0 ] ) if self . layers > 1 : hidden_weights = z [ self . latent_variables . z_indices [ 'Hidden weight' ] [ 'start' ] : self . latent_variables . z_indices [ 'Hidden weight' ] [ 'end' ] + 1 ] hidden_weights = np . reshape ( hidden_weights , ( self . layers - 1 , self . units , - 1 ) ) for k in range ( 0 , self . layers - 1 ) : h = self . activation ( h . dot ( hidden_weights [ k ] ) + bias [ 1 + k ] ) return h . dot ( output_weights ) + output_bias , Y
def _parse_version ( self , value ) : """Parses ` version ` option value . : param value : : rtype : str"""
version = self . _parse_file ( value ) if version != value : version = version . strip ( ) # Be strict about versions loaded from file because it ' s easy to # accidentally include newlines and other unintended content if isinstance ( parse ( version ) , LegacyVersion ) : tmpl = ( 'Version loaded from {value} does not ' 'comply with PEP 440: {version}' ) raise DistutilsOptionError ( tmpl . format ( ** locals ( ) ) ) return version version = self . _parse_attr ( value , self . package_dir ) if callable ( version ) : version = version ( ) if not isinstance ( version , string_types ) : if hasattr ( version , '__iter__' ) : version = '.' . join ( map ( str , version ) ) else : version = '%s' % version return version
def delegated_login ( self , login , admin_zc , duration = 0 ) : """Use another client to get logged in via delegated _ auth mechanism by an already logged in admin . : param admin _ zc : An already logged - in admin client : type admin _ zc : ZimbraAdminClient : param login : the user login ( or email ) you want to log as"""
# a duration of zero is interpretted literaly by the API . . . selector = zobjects . Account ( name = login ) . to_selector ( ) delegate_args = { 'account' : selector } if duration : delegate_args [ 'duration' : duration ] resp = admin_zc . request ( 'DelegateAuth' , delegate_args ) lifetime = resp [ 'lifetime' ] authToken = resp [ 'authToken' ] self . login_account = login self . login_with_authToken ( authToken , lifetime )
def flux_matrix ( T , pi , qminus , qplus , netflux = True ) : r"""Compute the TPT flux network for the reaction A - - > B . Parameters T : ( M , M ) ndarray transition matrix pi : ( M , ) ndarray Stationary distribution corresponding to T qminus : ( M , ) ndarray Backward comittor qplus : ( M , ) ndarray Forward committor netflux : boolean True : net flux matrix will be computed False : gross flux matrix will be computed Returns flux : ( M , M ) ndarray Matrix of flux values between pairs of states . Notes Computation of the flux network relies on transition path theory ( TPT ) [ 1 ] . Here we use discrete transition path theory [ 2 ] in the transition matrix formulation [ 3 ] . See also committor . forward _ committor , committor . backward _ committor Notes Computation of the flux network relies on transition path theory ( TPT ) . The central object used in transition path theory is the forward and backward comittor function . The TPT ( gross ) flux is defined as . . math : : f _ { ij } = \ left \ { \ begin { array } { rl } \ pi _ i q _ i ^ { ( - ) } p _ { ij } q _ j ^ { ( + ) } & i \ neq j \ \ 0 & i = j \ \ end { array } \ right . The TPT net flux is then defined as . . math : : f _ { ij } = \ max \ { f _ { ij } - f _ { ji } , 0 \ } \ : \ : \ : \ forall i , j . References . . [ 1 ] W . E and E . Vanden - Eijnden . Towards a theory of transition paths . J . Stat . Phys . 123 : 503-523 ( 2006) . . [ 2 ] P . Metzner , C . Schuette and E . Vanden - Eijnden . Transition Path Theory for Markov Jump Processes . Multiscale Model Simul 7 : 1192-1219 ( 2009) . . [ 3 ] F . Noe , Ch . Schuette , E . Vanden - Eijnden , L . Reich and T . Weikl : Constructing the Full Ensemble of Folding Pathways from Short Off - Equilibrium Simulations . Proc . Natl . Acad . Sci . USA , 106 , 19011-19016 ( 2009)"""
if issparse ( T ) : return sparse . tpt . flux_matrix ( T , pi , qminus , qplus , netflux = netflux ) elif isdense ( T ) : return dense . tpt . flux_matrix ( T , pi , qminus , qplus , netflux = netflux ) else : raise _type_not_supported
def get_license_metadata ( self ) : """Gets the metadata for the license . return : ( osid . Metadata ) - metadata for the license * compliance : mandatory - - This method must be implemented . *"""
metadata = dict ( self . _license_metadata ) metadata . update ( { 'existing_string_values' : self . my_osid_object_form . _my_map [ 'license' ] } ) return Metadata ( ** metadata )
def validate_url ( self , original_string ) : """Returns the original string if it was valid , raises an argument error if it ' s not ."""
# nipped from stack overflow : http : / / stackoverflow . com / questions / 827557 / how - do - you - validate - a - url - with - a - regular - expression - in - python # I preferred this to the thorough regex approach for simplicity and # readability pieces = urlparse . urlparse ( original_string ) try : if self . path_only : assert not any ( [ pieces . scheme , pieces . netloc ] ) assert pieces . path else : assert all ( [ pieces . scheme , pieces . netloc ] ) valid_chars = set ( string . letters + string . digits + ":-_." ) assert set ( pieces . netloc ) <= valid_chars assert pieces . scheme in [ 'http' , 'https' ] except AssertionError as e : raise ArgumentError ( self . item_name , "The input you've provided is not a valid URL." ) return pieces
def is_auth_alive ( self ) : "Return true if the auth is not expired , else false"
model = self . model ( 'ir.model' ) try : model . search ( [ ] , None , 1 , None ) except ClientError as err : if err and err . message [ 'code' ] == 403 : return False raise except Exception : raise else : return True
def stop ( self , api = None ) : """Stop automation run . : param api : sevenbridges Api instance . : return : AutomationRun object"""
api = api or self . _API return api . post ( url = self . _URL [ 'actions' ] . format ( id = self . id , action = AutomationRunActions . STOP ) ) . content
def ls ( self , path , offset = None , amount = None ) : """Return list of files / directories . Each item is a dict . Keys : ' path ' , ' creationdate ' , ' displayname ' , ' length ' , ' lastmodified ' , ' isDir ' ."""
def parseContent ( content ) : result = [ ] root = ET . fromstring ( content ) for response in root . findall ( './/d:response' , namespaces = self . namespaces ) : node = { 'path' : response . find ( "d:href" , namespaces = self . namespaces ) . text , 'creationdate' : response . find ( "d:propstat/d:prop/d:creationdate" , namespaces = self . namespaces ) . text , 'displayname' : response . find ( "d:propstat/d:prop/d:displayname" , namespaces = self . namespaces ) . text , 'lastmodified' : response . find ( "d:propstat/d:prop/d:getlastmodified" , namespaces = self . namespaces ) . text , 'isDir' : response . find ( "d:propstat/d:prop/d:resourcetype/d:collection" , namespaces = self . namespaces ) != None } if not node [ 'isDir' ] : node [ 'length' ] = response . find ( "d:propstat/d:prop/d:getcontentlength" , namespaces = self . namespaces ) . text node [ 'etag' ] = response . find ( "d:propstat/d:prop/d:getetag" , namespaces = self . namespaces ) . text node [ 'type' ] = response . find ( "d:propstat/d:prop/d:getcontenttype" , namespaces = self . namespaces ) . text result . append ( node ) return result url = path if ( offset is not None ) and ( amount is not None ) : url += "?offset={offset}&amount={amount}" . format ( offset = offset , amount = amount ) resp = self . _sendRequest ( "PROPFIND" , url , { 'Depth' : '1' } ) if resp . status_code == 207 : return parseContent ( resp . content ) else : raise YaDiskException ( resp . status_code , resp . content )
def _load_schema ( name , path = __file__ ) : """Load a schema from disk"""
path = os . path . join ( os . path . dirname ( path ) , name + '.yaml' ) with open ( path ) as handle : schema = yaml . safe_load ( handle ) fast_schema = rapidjson . Validator ( rapidjson . dumps ( schema ) ) return path , ( schema , fast_schema )
def brpoplpush ( self , source , destination , timeout = 0 ) : """Emulate brpoplpush"""
transfer_item = self . brpop ( source , timeout ) if transfer_item is None : return None key , val = transfer_item self . lpush ( destination , val ) return val
def resolve_annotations ( raw_annotations : Dict [ str , AnyType ] , module_name : Optional [ str ] ) -> Dict [ str , AnyType ] : """Partially taken from typing . get _ type _ hints . Resolve string or ForwardRef annotations into type objects if possible ."""
if module_name : base_globals : Optional [ Dict [ str , Any ] ] = sys . modules [ module_name ] . __dict__ else : base_globals = None annotations = { } for name , value in raw_annotations . items ( ) : if isinstance ( value , str ) : value = ForwardRef ( value , is_argument = False ) try : value = _eval_type ( value , base_globals , None ) except NameError : # this is ok , it can be fixed with update _ forward _ refs pass annotations [ name ] = value return annotations
def get_randomness_stream ( self , decision_point : str , for_initialization : bool = False ) -> RandomnessStream : """Provides a new source of random numbers for the given decision point . Parameters decision _ point : A unique identifier for a stream of random numbers . Typically represents a decision that needs to be made each time step like ' moves _ left ' or ' gets _ disease ' . for _ initialization : A flag indicating whether this stream is used to generate key initialization information that will be used to identify simulants in the Common Random Number framework . These streams cannot be copied and should only be used to generate the state table columns specified in ` ` builder . configuration . randomness . key _ columns ` ` . Raises RandomnessError : If another location in the simulation has already created a randomness stream with the same identifier ."""
if decision_point in self . _decision_points : raise RandomnessError ( f"Two separate places are attempting to create " f"the same randomness stream for {decision_point}" ) stream = RandomnessStream ( key = decision_point , clock = self . _clock , seed = self . _seed , index_map = self . _key_mapping , manager = self , for_initialization = for_initialization ) self . _decision_points [ decision_point ] = stream return stream
def set_database_path ( dbfolder ) : """Use to write the database path into the config . Parameters dbfolder : str or pathlib . Path Path to where pyciss will store the ISS images it downloads and receives ."""
configpath = get_configpath ( ) try : d = get_config ( ) except IOError : d = configparser . ConfigParser ( ) d [ 'pyciss_db' ] = { } d [ 'pyciss_db' ] [ 'path' ] = dbfolder with configpath . open ( 'w' ) as f : d . write ( f ) print ( "Saved database path into {}." . format ( configpath ) )
def _compute_intra_event_std ( self , C , C_PGA , pga1100 , mag , vs30 , vs30measured ) : """Compute intra event standard deviation ( equation 24 ) as described in the errata and not in the original paper ."""
sigma_b = self . _compute_sigma_b ( C , mag , vs30measured ) sigma_b_pga = self . _compute_sigma_b ( C_PGA , mag , vs30measured ) delta_amp = self . _compute_partial_derivative_site_amp ( C , pga1100 , vs30 ) std_intra = np . sqrt ( sigma_b ** 2 + self . CONSTS [ 'sigma_amp' ] ** 2 + ( delta_amp ** 2 ) * ( sigma_b_pga ** 2 ) + 2 * delta_amp * sigma_b * sigma_b_pga * C [ 'rho' ] ) return std_intra
def pages ( self ) : """A generator of all pages in the stream . Returns : types . GeneratorType [ google . cloud . bigquery _ storage _ v1beta1 . ReadRowsPage ] : A generator of pages ."""
# Each page is an iterator of rows . But also has num _ items , remaining , # and to _ dataframe . avro_schema , column_names = _avro_schema ( self . _read_session ) for block in self . _reader : self . _status = block . status yield ReadRowsPage ( avro_schema , column_names , block )
def connectionMade ( self ) : """Register with the stomp server ."""
cmd = self . sm . connect ( ) self . transport . write ( cmd )
def pass_missingremoterelease_v1 ( self ) : """Update the outlet link sequence | dam _ senders . D | ."""
flu = self . sequences . fluxes . fastaccess sen = self . sequences . senders . fastaccess sen . d [ 0 ] += flu . missingremoterelease
def get_instrument_variables ( ds ) : '''Returns a list of instrument variables : param netCDF4 . Dataset ds : An open netCDF4 Dataset'''
candidates = [ ] for variable in ds . variables : instrument = getattr ( ds . variables [ variable ] , 'instrument' , '' ) if instrument and instrument in ds . variables : if instrument not in candidates : candidates . append ( instrument ) instrument = getattr ( ds , 'instrument' , '' ) if instrument and instrument in ds . variables : if instrument not in candidates : candidates . append ( instrument ) return candidates
def _init_taskqueue_stub ( self , ** stub_kwargs ) : """Initializes the taskqueue stub using nosegae config magic"""
task_args = { } # root _ path is required so the stub can find ' queue . yaml ' or ' queue . yml ' if 'root_path' not in stub_kwargs : for p in self . _app_path : # support - - gae - application values that may be a . yaml file dir_ = os . path . dirname ( p ) if os . path . isfile ( p ) else p if os . path . isfile ( os . path . join ( dir_ , 'queue.yaml' ) ) or os . path . isfile ( os . path . join ( dir_ , 'queue.yml' ) ) : task_args [ 'root_path' ] = dir_ break task_args . update ( stub_kwargs ) self . testbed . init_taskqueue_stub ( ** task_args )
def _get ( self , url , param_dict = { } , securityHandler = None , additional_headers = [ ] , handlers = [ ] , proxy_url = None , proxy_port = None , compress = True , custom_handlers = [ ] , out_folder = None , file_name = None ) : """Performs a GET operation Inputs : Output : returns dictionary , string or None"""
self . _last_method = "GET" CHUNK = 4056 param_dict , handler , cj = self . _processHandler ( securityHandler , param_dict ) headers = [ ] + additional_headers if compress : headers . append ( ( 'Accept-encoding' , 'gzip' ) ) else : headers . append ( ( 'Accept-encoding' , '' ) ) headers . append ( ( 'User-Agent' , self . useragent ) ) if len ( param_dict . keys ( ) ) == 0 : param_dict = None if handlers is None : handlers = [ ] if handler is not None : handlers . append ( handler ) handlers . append ( RedirectHandler ( ) ) if cj is not None : handlers . append ( request . HTTPCookieProcessor ( cj ) ) if proxy_url is not None : if proxy_port is None : proxy_port = 80 proxies = { "http" : "http://%s:%s" % ( proxy_url , proxy_port ) , "https" : "https://%s:%s" % ( proxy_url , proxy_port ) } proxy_support = request . ProxyHandler ( proxies ) handlers . append ( proxy_support ) opener = request . build_opener ( * handlers ) opener . addheaders = headers if param_dict is None : resp = opener . open ( url , data = param_dict ) elif len ( str ( urlencode ( param_dict ) ) ) + len ( url ) >= 1999 : resp = opener . open ( url , data = urlencode ( param_dict ) ) else : format_url = url + "?%s" % urlencode ( param_dict ) resp = opener . open ( fullurl = format_url ) self . _last_code = resp . getcode ( ) self . _last_url = resp . geturl ( ) # Get some headers from the response maintype = self . _mainType ( resp ) contentDisposition = resp . headers . get ( 'content-disposition' ) contentEncoding = resp . headers . get ( 'content-encoding' ) contentType = resp . headers . get ( 'content-Type' ) . split ( ';' ) [ 0 ] . lower ( ) contentLength = resp . headers . get ( 'content-length' ) if maintype . lower ( ) in ( 'image' , 'application/x-zip-compressed' ) or contentType == 'application/x-zip-compressed' or ( contentDisposition is not None and contentDisposition . lower ( ) . find ( 'attachment;' ) > - 1 ) : fname = self . _get_file_name ( contentDisposition = contentDisposition , url = url ) if out_folder is None : out_folder = tempfile . gettempdir ( ) if contentLength is not None : max_length = int ( contentLength ) if max_length < CHUNK : CHUNK = max_length file_name = os . path . join ( out_folder , fname ) with open ( file_name , 'wb' ) as writer : for data in self . _chunk ( response = resp , size = CHUNK ) : writer . write ( data ) writer . flush ( ) writer . flush ( ) del writer return file_name else : read = "" for data in self . _chunk ( response = resp , size = CHUNK ) : if self . PY3 == True : read += data . decode ( 'utf-8' ) else : read += data del data try : results = json . loads ( read ) if 'error' in results : if 'message' in results [ 'error' ] : if results [ 'error' ] [ 'message' ] == 'Request not made over ssl' : if url . startswith ( 'http://' ) : url = url . replace ( 'http://' , 'https://' ) return self . _get ( url , param_dict , securityHandler , additional_headers , handlers , proxy_url , proxy_port , compress , custom_handlers , out_folder , file_name ) return results except : return read
def _next_rId ( self ) : """Next available rId in collection , starting from ' rId1 ' and making use of any gaps in numbering , e . g . ' rId2 ' for rIds [ ' rId1 ' , ' rId3 ' ] ."""
for n in range ( 1 , len ( self ) + 2 ) : rId_candidate = 'rId%d' % n # like ' rId19' if rId_candidate not in self : return rId_candidate
def get_eco_map ( url ) : """To conver the three column file to a hashmap we join primary and secondary keys , for example IEAGO _ REF : 000002ECO : 0000256 IEAGO _ REF : 000003ECO : 0000501 IEADefaultECO : 0000501 becomes IEA - GO _ REF : 000002 : ECO : 0000256 IEA - GO _ REF : 000003 : ECO : 0000501 IEA : ECO : 0000501 : return : dict"""
# this would go in a translation table but it is generated dynamicly # maybe when we move to a make driven system eco_map = { } request = urllib . request . Request ( url ) response = urllib . request . urlopen ( request ) for line in response : line = line . decode ( 'utf-8' ) . rstrip ( ) if re . match ( r'^#' , line ) : continue ( code , go_ref , eco_curie ) = line . split ( '\t' ) if go_ref != 'Default' : eco_map [ "{}-{}" . format ( code , go_ref ) ] = eco_curie else : eco_map [ code ] = eco_curie return eco_map
def begin_state ( self , batch_size = 0 , func = ndarray . zeros , ** kwargs ) : """Initial state for this cell . Parameters func : callable , default symbol . zeros Function for creating initial state . For Symbol API , func can be ` symbol . zeros ` , ` symbol . uniform ` , ` symbol . var etc ` . Use ` symbol . var ` if you want to directly feed input as states . For NDArray API , func can be ` ndarray . zeros ` , ` ndarray . ones ` , etc . batch _ size : int , default 0 Only required for NDArray API . Size of the batch ( ' N ' in layout ) dimension of input . * * kwargs : Additional keyword arguments passed to func . For example ` mean ` , ` std ` , ` dtype ` , etc . Returns states : nested list of Symbol Starting states for the first RNN step ."""
assert not self . _modified , "After applying modifier cells (e.g. ZoneoutCell) the base " "cell cannot be called directly. Call the modifier cell instead." states = [ ] for info in self . state_info ( batch_size ) : self . _init_counter += 1 if info is not None : info . update ( kwargs ) else : info = kwargs state = func ( name = '%sbegin_state_%d' % ( self . _prefix , self . _init_counter ) , ** info ) states . append ( state ) return states
def start_date ( request ) : """Add the start date to the context for eighth admin views ."""
if request . user and request . user . is_authenticated and request . user . is_eighth_admin : return { "admin_start_date" : get_start_date ( request ) } return { }
def read_int16 ( self , little_endian = True ) : """Read 2 byte as a signed integer value from the stream . Args : little _ endian ( bool ) : specify the endianness . ( Default ) Little endian . Returns : int :"""
if little_endian : endian = "<" else : endian = ">" return self . unpack ( '%sh' % endian , 2 )
def blend_palette ( colors , n_colors = 6 , as_cmap = False ) : """Make a palette that blends between a list of colors . Parameters colors : sequence of matplotlib colors hex , rgb - tuple , or html color name n _ colors : int , optional number of colors in the palette as _ cmap : bool , optional if True , return as a matplotlib colormap instead of list Returns palette : list or colormap"""
name = "-" . join ( map ( str , colors ) ) pal = mpl . colors . LinearSegmentedColormap . from_list ( name , colors ) if not as_cmap : pal = pal ( np . linspace ( 0 , 1 , n_colors ) ) return pal
def _init_itemid2name ( self ) : """Print gene symbols instead of gene IDs , if provided ."""
if not hasattr ( self . args , 'id2sym' ) : return None fin_id2sym = self . args . id2sym if fin_id2sym is not None and os . path . exists ( fin_id2sym ) : id2sym = { } cmpl = re . compile ( r'^\s*(\S+)[\s,;]+(\S+)' ) with open ( fin_id2sym ) as ifstrm : for line in ifstrm : mtch = cmpl . search ( line ) if mtch : id2sym [ mtch . group ( 1 ) ] = mtch . group ( 2 ) return id2sym
def logical_chassis_fwdl_sanity_input_rbridge_id ( self , ** kwargs ) : """Auto Generated Code"""
config = ET . Element ( "config" ) logical_chassis_fwdl_sanity = ET . Element ( "logical_chassis_fwdl_sanity" ) config = logical_chassis_fwdl_sanity input = ET . SubElement ( logical_chassis_fwdl_sanity , "input" ) rbridge_id = ET . SubElement ( input , "rbridge-id" ) rbridge_id . text = kwargs . pop ( 'rbridge_id' ) callback = kwargs . pop ( 'callback' , self . _callback ) return callback ( config )
def load_json ( self , path ) : """Load a JSON file from the user profile ."""
with open ( self . profile_path ( path , must_exist = True ) , encoding = 'utf-8' ) as f : data = json . load ( f ) return data
def get_colours ( color_group , color_name , reverse = False ) : color_group = color_group . lower ( ) cmap = get_map ( color_group , color_name , reverse = reverse ) return cmap . hex_colors """if not reverse : return cmap . hex _ colors else : return cmap . hex _ colors [ : : - 1]"""
def reccyl ( rectan ) : """Convert from rectangular to cylindrical coordinates . http : / / naif . jpl . nasa . gov / pub / naif / toolkit _ docs / C / cspice / reccyl _ c . html : param rectan : Rectangular coordinates of a point . : type rectan : 3 - Element Array of floats : return : Distance from z axis , Angle ( radians ) from xZ plane , Height above xY plane . : rtype : tuple"""
rectan = stypes . toDoubleVector ( rectan ) radius = ctypes . c_double ( 0 ) lon = ctypes . c_double ( 0 ) z = ctypes . c_double ( 0 ) libspice . reccyl_c ( rectan , ctypes . byref ( radius ) , ctypes . byref ( lon ) , ctypes . byref ( z ) ) return radius . value , lon . value , z . value
def deleteMediaPreviews ( self ) : """Delete the preview thumbnails for items in this library . This cannot be undone . Recreating media preview files can take hours or even days ."""
key = '/library/sections/%s/indexes' % self . key self . _server . query ( key , method = self . _server . _session . delete )
def query_one ( self , * args , ** kwargs ) : """Return first document from : meth : ` query ` , with same parameters ."""
for r in self . query ( * args , ** kwargs ) : return r return None
def confirmation ( self , apdu ) : """This function is called when the application has provided a response and needs it to be sent to the client ."""
if _debug : ServerSSM . _debug ( "confirmation %r" , apdu ) # check to see we are in the correct state if self . state != AWAIT_RESPONSE : if _debug : ServerSSM . _debug ( " - warning: not expecting a response" ) # abort response if ( apdu . apduType == AbortPDU . pduType ) : if _debug : ServerSSM . _debug ( " - abort" ) self . set_state ( ABORTED ) # send the response to the device self . response ( apdu ) return # simple response if ( apdu . apduType == SimpleAckPDU . pduType ) or ( apdu . apduType == ErrorPDU . pduType ) or ( apdu . apduType == RejectPDU . pduType ) : if _debug : ServerSSM . _debug ( " - simple ack, error, or reject" ) # transaction completed self . set_state ( COMPLETED ) # send the response to the device self . response ( apdu ) return # complex ack if ( apdu . apduType == ComplexAckPDU . pduType ) : if _debug : ServerSSM . _debug ( " - complex ack" ) # save the response and set the segmentation context self . set_segmentation_context ( apdu ) # the segment size is the minimum of the size of the largest packet # that can be delivered to the client and the largest it can accept if ( not self . device_info ) or ( self . device_info . maxNpduLength is None ) : self . segmentSize = self . maxApduLengthAccepted else : self . segmentSize = min ( self . device_info . maxNpduLength , self . maxApduLengthAccepted ) if _debug : ServerSSM . _debug ( " - segment size: %r" , self . segmentSize ) # compute the segment count if not apdu . pduData : # always at least one segment self . segmentCount = 1 else : # split into chunks , maybe need one more self . segmentCount , more = divmod ( len ( apdu . pduData ) , self . segmentSize ) if more : self . segmentCount += 1 if _debug : ServerSSM . _debug ( " - segment count: %r" , self . segmentCount ) # make sure we support segmented transmit if we need to if self . segmentCount > 1 : if _debug : ServerSSM . _debug ( " - segmentation required, %d segments" , self . segmentCount ) # make sure we support segmented transmit if self . segmentationSupported not in ( 'segmentedTransmit' , 'segmentedBoth' ) : if _debug : ServerSSM . _debug ( " - server can't send segmented responses" ) abort = self . abort ( AbortReason . segmentationNotSupported ) self . response ( abort ) return # make sure client supports segmented receive if not self . segmented_response_accepted : if _debug : ServerSSM . _debug ( " - client can't receive segmented responses" ) abort = self . abort ( AbortReason . segmentationNotSupported ) self . response ( abort ) return # make sure we dont exceed the number of segments in our response # that the client said it was willing to accept in the request if ( self . maxSegmentsAccepted is not None ) and ( self . segmentCount > self . maxSegmentsAccepted ) : if _debug : ServerSSM . _debug ( " - client can't receive enough segments" ) abort = self . abort ( AbortReason . apduTooLong ) self . response ( abort ) return # initialize the state self . segmentRetryCount = 0 self . initialSequenceNumber = 0 self . actualWindowSize = None # send out the first segment ( or the whole thing ) if self . segmentCount == 1 : self . response ( apdu ) self . set_state ( COMPLETED ) else : self . response ( self . get_segment ( 0 ) ) self . set_state ( SEGMENTED_RESPONSE , self . segmentTimeout ) else : raise RuntimeError ( "invalid APDU (4)" )
def check_exists ( name , path ) : '''Check if the given path is an alternative for a name . . . versionadded : : 2015.8.4 CLI Example : . . code - block : : bash salt ' * ' alternatives . check _ exists name path'''
cmd = [ _get_cmd ( ) , '--display' , name ] out = __salt__ [ 'cmd.run_all' ] ( cmd , python_shell = False ) if out [ 'retcode' ] > 0 and out [ 'stderr' ] != '' : return False return any ( ( line . startswith ( path ) for line in out [ 'stdout' ] . splitlines ( ) ) )
def is_dead ( self , proc , name ) : """Checks to see if the specified process is dead . : param psutil . Process proc : The process to check : param str name : The name of consumer : rtype : bool"""
LOGGER . debug ( 'Checking %s (%r)' , name , proc ) try : status = proc . status ( ) except psutil . NoSuchProcess : LOGGER . debug ( 'NoSuchProcess: %s (%r)' , name , proc ) return True LOGGER . debug ( 'Process %s (%s) status: %r (Unresponsive Count: %s)' , name , proc . pid , status , self . unresponsive [ name ] ) if status in _PROCESS_RUNNING : return False elif status == psutil . STATUS_ZOMBIE : try : proc . wait ( 0.1 ) except psutil . TimeoutExpired : pass try : proc . terminate ( ) status = proc . status ( ) except psutil . NoSuchProcess : LOGGER . debug ( 'NoSuchProcess: %s (%r)' , name , proc ) return True return status in _PROCESS_STOPPED_OR_DEAD
def load_template ( self , name ) : """Attempts to load the relevant template from our templating system / environment . Args : name : The name of the template to load . Return : On success , a StatikTemplate object that can be used to render content ."""
# hopefully speeds up loading of templates a little , especially when loaded multiple times if name in self . cached_templates : logger . debug ( "Using cached template: %s" , name ) return self . cached_templates [ name ] logger . debug ( "Attempting to find template by name: %s" , name ) name_with_ext , provider_name , base_path = self . find_template_details ( name ) full_path = None if base_path is not None : full_path = os . path . join ( base_path , name_with_ext ) # load it with the relevant provider template = template_exception_handler ( lambda : self . get_provider ( provider_name ) . load_template ( name_with_ext , full_path = full_path ) , self . error_context , filename = full_path ) # cache it for potential later use self . cached_templates [ name ] = template return template
def result ( self ) : """Get the result ( s ) for this hook call ( DEPRECATED in favor of ` ` get _ result ( ) ` ` ) ."""
msg = "Use get_result() which forces correct exception handling" warnings . warn ( DeprecationWarning ( msg ) , stacklevel = 2 ) return self . _result
def split_camel ( word : str ) -> str : """Separate any words joined in Camel case fashion using a single space . > > > split _ camel ( ' esseCarthaginienses ' ) ' esse Carthaginienses ' > > > split _ camel ( ' urbemCertimam ' ) ' urbem Certimam '"""
m = re . match ( '[a-z]+[A-Z][a-z]' , word ) if m : _ , end = m . span ( ) return word [ : end - 2 ] + ' ' + word [ end - 2 : ] return word
def acl_middleware ( callback ) : """Returns a aiohttp _ auth . acl middleware factory for use by the aiohttp application object . Args : callback : This is a callable which takes a user _ id ( as returned from the auth . get _ auth function ) , and expects a sequence of permitted ACL groups to be returned . This can be a empty tuple to represent no explicit permissions , or None to explicitly forbid this particular user _ id . Note that the user _ id passed may be None if no authenticated user exists . Returns : A aiohttp middleware factory ."""
async def _acl_middleware_factory ( app , handler ) : async def _middleware_handler ( request ) : # Save the policy in the request request [ GROUPS_KEY ] = callback # Call the next handler in the chain return await handler ( request ) return _middleware_handler return _acl_middleware_factory
def _handleDecodeHextileRAW ( self , block , bg , color , x , y , width , height , tx , ty , tw , th ) : """the tile is in raw encoding"""
self . updateRectangle ( tx , ty , tw , th , block ) self . _doNextHextileSubrect ( bg , color , x , y , width , height , tx , ty )
def QA_data_tick_resample ( tick , type_ = '1min' ) : """tickι‡‡ζ ·ζˆδ»»ζ„ηΊ§εˆ«εˆ†ι’ŸηΊΏ Arguments : tick { [ type ] } - - transaction Returns : [ type ] - - [ description ]"""
tick = tick . assign ( amount = tick . price * tick . vol ) resx = pd . DataFrame ( ) _temp = set ( tick . index . date ) for item in _temp : _data = tick . loc [ str ( item ) ] _data1 = _data [ time ( 9 , 31 ) : time ( 11 , 30 ) ] . resample ( type_ , closed = 'right' , base = 30 , loffset = type_ ) . apply ( { 'price' : 'ohlc' , 'vol' : 'sum' , 'code' : 'last' , 'amount' : 'sum' } ) _data2 = _data [ time ( 13 , 1 ) : time ( 15 , 0 ) ] . resample ( type_ , closed = 'right' , loffset = type_ ) . apply ( { 'price' : 'ohlc' , 'vol' : 'sum' , 'code' : 'last' , 'amount' : 'sum' } ) resx = resx . append ( _data1 ) . append ( _data2 ) resx . columns = resx . columns . droplevel ( 0 ) return resx . reset_index ( ) . drop_duplicates ( ) . set_index ( [ 'datetime' , 'code' ] )
async def get_shade ( self , shade_id , from_cache = True ) -> BaseShade : """Get a shade instance based on shade id ."""
if not from_cache : await self . get_shades ( ) for _shade in self . shades : if _shade . id == shade_id : return _shade raise ResourceNotFoundException ( "Shade not found. Id: {}" . format ( shade_id ) )
def sun_utc ( self , date , latitude , longitude , observer_elevation = 0 ) : """Calculate all the info for the sun at once . All times are returned in the UTC timezone . : param date : Date to calculate for . : type date : : class : ` datetime . date ` : param latitude : Latitude - Northern latitudes should be positive : type latitude : float : param longitude : Longitude - Eastern longitudes should be positive : type longitude : float : param observer _ elevation : Elevation in metres to calculate sun for : type observer _ elevation : int : returns : Dictionary with keys ` ` dawn ` ` , ` ` sunrise ` ` , ` ` noon ` ` , ` ` sunset ` ` and ` ` dusk ` ` whose values are the results of the corresponding ` _ utc ` methods . : rtype : dict"""
dawn = self . dawn_utc ( date , latitude , longitude , observer_elevation = observer_elevation ) sunrise = self . sunrise_utc ( date , latitude , longitude , observer_elevation = observer_elevation ) noon = self . solar_noon_utc ( date , longitude ) sunset = self . sunset_utc ( date , latitude , longitude , observer_elevation = observer_elevation ) dusk = self . dusk_utc ( date , latitude , longitude , observer_elevation = observer_elevation ) return { "dawn" : dawn , "sunrise" : sunrise , "noon" : noon , "sunset" : sunset , "dusk" : dusk , }
def GET_save_getitemvalues ( self ) -> None : """Save the values of all current | GetItem | objects ."""
for item in state . getitems : for name , value in item . yield_name2value ( state . idx1 , state . idx2 ) : state . getitemvalues [ self . _id ] [ name ] = value
def sort ( line ) : """change point position if x1 , y0 < x0 , y0"""
x0 , y0 , x1 , y1 = line # if ( x0 * * 2 + y0 * * 2 ) * * 0.5 < ( x1 * * 2 + y1 * * 2 ) * * 0.5: # return ( x1 , y1 , x0 , y0) # return line # if x1 < x0: # return ( x1 , y1 , x0 , y0) # return line turn = False if abs ( x1 - x0 ) > abs ( y1 - y0 ) : if x1 < x0 : turn = True elif y1 < y0 : turn = True if turn : return ( x1 , y1 , x0 , y0 ) # return line [ ( 2,3,0,1 ) ] return line
def _to_dict ( self ) : """Return a json dictionary representing this model ."""
_dict = { } if hasattr ( self , 'sentence_id' ) and self . sentence_id is not None : _dict [ 'sentence_id' ] = self . sentence_id if hasattr ( self , 'text' ) and self . text is not None : _dict [ 'text' ] = self . text if hasattr ( self , 'tones' ) and self . tones is not None : _dict [ 'tones' ] = [ x . _to_dict ( ) for x in self . tones ] if hasattr ( self , 'tone_categories' ) and self . tone_categories is not None : _dict [ 'tone_categories' ] = [ x . _to_dict ( ) for x in self . tone_categories ] if hasattr ( self , 'input_from' ) and self . input_from is not None : _dict [ 'input_from' ] = self . input_from if hasattr ( self , 'input_to' ) and self . input_to is not None : _dict [ 'input_to' ] = self . input_to return _dict
def draw_text ( data , obj ) : """Paints text on the graph ."""
content = [ ] properties = [ ] style = [ ] if isinstance ( obj , mpl . text . Annotation ) : _annotation ( obj , data , content ) # 1 : coordinates # 2 : properties ( shapes , rotation , etc ) # 3 : text style # 4 : the text # - - - - - 1 - - - - - 2 - - - 3 - - 4 - - pos = obj . get_position ( ) # from . util import transform _ to _ data _ coordinates # pos = transform _ to _ data _ coordinates ( obj , * pos ) text = obj . get_text ( ) if text in [ "" , data [ "current axis title" ] ] : # Text nodes which are direct children of Axes are typically titles . They are # already captured by the ` title ` property of pgfplots axes , so skip them here . return data , content size = obj . get_size ( ) bbox = obj . get_bbox_patch ( ) converter = mpl . colors . ColorConverter ( ) # without the factor 0.5 , the fonts are too big most of the time . # TODO fix this scaling = 0.5 * size / data [ "font size" ] ff = data [ "float format" ] if scaling != 1.0 : properties . append ( ( "scale=" + ff ) . format ( scaling ) ) if bbox is not None : _bbox ( bbox , data , properties , scaling ) ha = obj . get_ha ( ) va = obj . get_va ( ) anchor = _transform_positioning ( ha , va ) if anchor is not None : properties . append ( anchor ) data , col , _ = color . mpl_color2xcolor ( data , converter . to_rgb ( obj . get_color ( ) ) ) properties . append ( "text={}" . format ( col ) ) properties . append ( "rotate={:.1f}" . format ( obj . get_rotation ( ) ) ) if obj . get_style ( ) == "italic" : style . append ( "\\itshape" ) else : assert obj . get_style ( ) == "normal" # From matplotlib / font _ manager . py : # weight _ dict = { # ' ultralight ' : 100, # ' light ' : 200, # ' normal ' : 400, # ' regular ' : 400, # ' book ' : 400, # ' medium ' : 500, # ' roman ' : 500, # ' semibold ' : 600, # ' demibold ' : 600, # ' demi ' : 600, # ' bold ' : 700, # ' heavy ' : 800, # ' extra bold ' : 800, # ' black ' : 900} # get _ weights returns a numeric value in the range 0-1000 or one of # β€˜ light ’ , β€˜ normal ’ , β€˜ regular ’ , β€˜ book ’ , β€˜ medium ’ , β€˜ roman ’ , β€˜ semibold ’ , # β€˜ demibold ’ , β€˜ demi ’ , β€˜ bold ’ , β€˜ heavy ’ , β€˜ extra bold ’ , β€˜ black ’ weight = obj . get_weight ( ) if weight in [ "semibold" , "demibold" , "demi" , "bold" , "heavy" , "extra bold" , "black" , ] or ( isinstance ( weight , int ) and weight > 550 ) : style . append ( "\\bfseries" ) # \ lfseries isn ' t that common yet # elif weight = = ' light ' or ( isinstance ( weight , int ) and weight < 300 ) : # style . append ( ' \ \ lfseries ' ) if obj . axes : # If the coordinates are relative to an axis , use ` axis cs ` . tikz_pos = ( "(axis cs:" + ff + "," + ff + ")" ) . format ( * pos ) else : # relative to the entire figure , it ' s a getting a littler harder . See # < http : / / tex . stackexchange . com / a / 274902/13262 > for a solution to the # problem : tikz_pos = ( "({{$(current bounding box.south west)!" + ff + "!" "(current bounding box.south east)$}}" "|-" "{{$(current bounding box.south west)!" + ff + "!" "(current bounding box.north west)$}})" ) . format ( * pos ) if "\n" in text : # http : / / tex . stackexchange . com / a / 124114/13262 properties . append ( "align={}" . format ( ha ) ) # Manipulating the text here is actually against mpl2tikz ' s policy not # to do that . On the other hand , newlines should translate into # newlines . # We might want to remove this here in the future . text = text . replace ( "\n " , "\\\\" ) content . append ( "\\node at {}[\n {}\n]{{{}}};\n" . format ( tikz_pos , ",\n " . join ( properties ) , " " . join ( style + [ text ] ) ) ) return data , content
def autocorr_noise_id ( x , af , data_type = "phase" , dmin = 0 , dmax = 2 ) : """Lag - 1 autocorrelation based noise identification Parameters x : numpy . array phase or fractional frequency time - series data minimum recommended length is len ( x ) > 30 roughly . af : int averaging factor data _ type : string { ' phase ' , ' freq ' } " phase " for phase data in seconds " freq " for fractional frequency data dmin : int minimum required number of differentiations in the algorithm dmax : int maximum number of differentiations defaults to 2 for ADEV set to 3 for HDEV Returns alpha _ int : int noise - slope as integer alpha : float noise - slope as float d : int number of differentiations of the time - series performed Notes http : / / www . stable32 . com / Auto . pdf http : / / citeseerx . ist . psu . edu / viewdoc / download ? doi = 10.1.1.503.9864 & rep = rep1 & type = pdf Power law noise identification using the lag 1 autocorrelation Riley , W . J . et al . 18th European Frequency and Time Forum ( EFTF 2004) https : / / ieeexplore . ieee . org / document / 5075021"""
d = 0 # number of differentiations lag = 1 if data_type is "phase" : if af > 1 : # x = scipy . signal . decimate ( x , af , n = 1 , ftype = ' fir ' ) x = x [ 0 : len ( x ) : af ] # decimate by averaging factor x = detrend ( x , deg = 2 ) # remove quadratic trend ( frequency offset and drift ) elif data_type is "freq" : # average by averaging factor y_cut = np . array ( x [ : len ( x ) - ( len ( x ) % af ) ] ) # cut to length assert len ( y_cut ) % af == 0 y_shaped = y_cut . reshape ( ( int ( len ( y_cut ) / af ) , af ) ) x = np . average ( y_shaped , axis = 1 ) # average x = detrend ( x , deg = 1 ) # remove frequency drift # require minimum length for time - series if len ( x ) < 30 : print ( "autocorr_noise_id() Don't know how to do noise-ID for time-series length= %d" % len ( x ) ) raise NotImplementedError while True : r1 = lag1_acf ( x ) rho = r1 / ( 1.0 + r1 ) if d >= dmin and ( rho < 0.25 or d >= dmax ) : p = - 2 * ( rho + d ) # print r1 # assert r1 < 0 # assert r1 > - 1.0/2.0 phase_add2 = 0 if data_type is "phase" : phase_add2 = 2 alpha = p + phase_add2 alpha_int = int ( - 1.0 * np . round ( 2 * rho ) - 2.0 * d ) + phase_add2 # print " d = " , d , " alpha = " , p + 2 return alpha_int , alpha , d , rho else : x = np . diff ( x ) d = d + 1 assert False
def sanity_check ( vcs ) : """Do sanity check before making changes Check that we are not on a tag and / or do not have local changes . Returns True when all is fine ."""
if not vcs . is_clean_checkout ( ) : q = ( "This is NOT a clean checkout. You are on a tag or you have " "local changes.\n" "Are you sure you want to continue?" ) if not ask ( q , default = False ) : sys . exit ( 1 )
def _get_subplot_extents ( self , overlay , ranges , range_type ) : """Iterates over all subplots and collects the extents of each ."""
if range_type == 'combined' : extents = { 'extents' : [ ] , 'soft' : [ ] , 'hard' : [ ] , 'data' : [ ] } else : extents = { range_type : [ ] } items = overlay . items ( ) if self . batched and self . subplots : subplot = list ( self . subplots . values ( ) ) [ 0 ] subplots = [ ( k , subplot ) for k in overlay . data . keys ( ) ] else : subplots = self . subplots . items ( ) for key , subplot in subplots : found = False if subplot is None : continue layer = overlay . data . get ( key , None ) if isinstance ( self . hmap , DynamicMap ) and layer is None : for _ , layer in items : if isinstance ( layer , subplot . hmap . type ) : found = True break if not found : layer = None if layer is None or not subplot . apply_ranges : continue if isinstance ( layer , CompositeOverlay ) : sp_ranges = ranges else : sp_ranges = util . match_spec ( layer , ranges ) if ranges else { } for rt in extents : extent = subplot . get_extents ( layer , sp_ranges , range_type = rt ) extents [ rt ] . append ( extent ) return extents
def connection_lost ( self , exception ) : """Called when the serial port is closed or the reader loop terminated otherwise ."""
if isinstance ( exception , Exception ) : logger . debug ( 'Connection to port `%s` lost: %s' , self . port , exception ) else : logger . debug ( 'Connection to port `%s` closed' , self . port ) self . connected . clear ( ) self . disconnected . set ( )
def from_string ( cls , key , key_id = None ) : """Construct an Signer instance from a private key in PEM format . Args : key ( str ) : Private key in PEM format . key _ id ( str ) : An optional key id used to identify the private key . Returns : google . auth . crypt . Signer : The constructed signer . Raises : ValueError : If the key cannot be parsed as PKCS # 1 or PKCS # 8 in PEM format ."""
key = _helpers . from_bytes ( key ) # PEM expects str in Python 3 marker_id , key_bytes = pem . readPemBlocksFromFile ( six . StringIO ( key ) , _PKCS1_MARKER , _PKCS8_MARKER ) # Key is in pkcs1 format . if marker_id == 0 : private_key = rsa . key . PrivateKey . load_pkcs1 ( key_bytes , format = 'DER' ) # Key is in pkcs8. elif marker_id == 1 : key_info , remaining = decoder . decode ( key_bytes , asn1Spec = _PKCS8_SPEC ) if remaining != b'' : raise ValueError ( 'Unused bytes' , remaining ) private_key_info = key_info . getComponentByName ( 'privateKey' ) private_key = rsa . key . PrivateKey . load_pkcs1 ( private_key_info . asOctets ( ) , format = 'DER' ) else : raise ValueError ( 'No key could be detected.' ) return cls ( private_key , key_id = key_id )
def pathFromIndex ( self , index ) : """Returns the joined path from the given model index . This will join together the full path with periods . : param index | < QModelIndex > : return < str >"""
item = self . _model . itemFromIndex ( index ) out = [ ] while ( item ) : out . append ( nativestring ( item . text ( ) ) ) item = item . parent ( ) return '.' . join ( reversed ( out ) )
def layer_covariance ( layer1 , layer2 = None ) : """Computes the covariance matrix between the neurons of two layers . If only one layer is passed , computes the symmetric covariance matrix of that layer ."""
layer2 = layer2 or layer1 act1 , act2 = layer1 . activations , layer2 . activations num_datapoints = act1 . shape [ 0 ] # cast to avoid numpy type promotion during division return np . matmul ( act1 . T , act2 ) / float ( num_datapoints )
def _GetParentModificationTime ( self , gzip_file_entry ) : """Retrieves the modification time of the file entry ' s parent file . Note that this retrieves the time from the file entry of the parent of the gzip file entry ' s path spec , which is different from trying to retrieve it from the gzip file entry ' s parent file entry . It would be preferable to retrieve the modification time from the metadata in the gzip file itself , but it appears to not be set when the file is written by fseventsd . Args : gzip _ file _ entry ( dfvfs . FileEntry ) : file entry of the gzip file containing the fseventsd data . Returns : dfdatetime . DateTimeValues : parent modification time , or None if not available ."""
parent_file_entry = path_spec_resolver . Resolver . OpenFileEntry ( gzip_file_entry . path_spec . parent ) if not parent_file_entry : return None return parent_file_entry . modification_time
def _threshold_batch ( self , vectors , batch_size , threshold , show_progressbar , return_names ) : """Batched cosine distance ."""
vectors = self . normalize ( vectors ) # Single transpose , makes things faster . reference_transposed = self . norm_vectors . T for i in tqdm ( range ( 0 , len ( vectors ) , batch_size ) , disable = not show_progressbar ) : distances = vectors [ i : i + batch_size ] . dot ( reference_transposed ) # For safety we clip distances = np . clip ( distances , a_min = .0 , a_max = 1.0 ) for lidx , dists in enumerate ( distances ) : indices = np . flatnonzero ( dists >= threshold ) sorted_indices = indices [ np . argsort ( - dists [ indices ] ) ] if return_names : yield [ ( self . indices [ d ] , dists [ d ] ) for d in sorted_indices ] else : yield list ( dists [ sorted_indices ] )
def reduce_by ( self , package_request ) : """Reduce this scope wrt a package request . Returns : A ( _ PackageScope , [ Reduction ] ) tuple , where the scope is a new scope copy with reductions applied , or self if there were no reductions , or None if the scope was completely reduced ."""
self . solver . reduction_broad_tests_count += 1 if self . package_request . conflict : # conflict scopes don ' t reduce . Instead , other scopes will be # reduced against a conflict scope . return ( self , [ ] ) # perform the reduction new_slice , reductions = self . variant_slice . reduce_by ( package_request ) # there was total reduction if new_slice is None : self . solver . reductions_count += 1 if self . pr : reqstr = _short_req_str ( package_request ) self . pr ( "%s was reduced to nothing by %s" , self , reqstr ) self . pr . br ( ) return ( None , reductions ) # there was some reduction if new_slice is not self . variant_slice : self . solver . reductions_count += 1 scope = self . _copy ( new_slice ) if self . pr : reqstr = _short_req_str ( package_request ) self . pr ( "%s was reduced to %s by %s" , self , scope , reqstr ) self . pr . br ( ) return ( scope , reductions ) # there was no reduction return ( self , [ ] )
def calc_offset ( cube ) : """Calculate an offset . Calculate offset from the side of data so that at least 200 image pixels are in the MAD stats . Parameters cube : pyciss . ringcube . RingCube Cubefile with ring image"""
i = 0 while pd . Series ( cube . img [ : , i ] ) . count ( ) < 200 : i += 1 return max ( i , 20 )
def set_linetrace_on_frame ( f , localtrace = None ) : """Non - portable function to modify linetracing . Remember to enable global tracing with : py : func : ` sys . settrace ` , otherwise no effect !"""
traceptr , _ , _ = get_frame_pointers ( f ) if localtrace is not None : # Need to incref to avoid the frame causing a double - delete ctypes . pythonapi . Py_IncRef ( localtrace ) # Not sure if this is the best way to do this , but it works . addr = id ( localtrace ) else : addr = 0 traceptr . contents = ctypes . py_object . from_address ( addr )
def normalize_bins ( self , inplace : bool = False ) -> "HistogramCollection" : """Normalize each bin in the collection so that the sum is 1.0 for each bin . Note : If a bin is zero in all collections , the result will be inf ."""
col = self if inplace else self . copy ( ) sums = self . sum ( ) . frequencies for h in col . histograms : h . set_dtype ( float ) h . _frequencies /= sums h . _errors2 /= sums ** 2 # TODO : Does this make sense ? return col
async def enqueue_job ( self , function : str , * args : Any , _job_id : Optional [ str ] = None , _defer_until : Optional [ datetime ] = None , _defer_by : Union [ None , int , float , timedelta ] = None , _expires : Union [ None , int , float , timedelta ] = None , _job_try : Optional [ int ] = None , ** kwargs : Any , ) -> Optional [ Job ] : """Enqueue a job . : param function : Name of the function to call : param args : args to pass to the function : param _ job _ id : ID of the job , can be used to enforce job uniqueness : param _ defer _ until : datetime at which to run the job : param _ defer _ by : duration to wait before running the job : param _ expires : if the job still hasn ' t started after this duration , do not run it : param _ job _ try : useful when re - enqueueing jobs within a job : param kwargs : any keyword arguments to pass to the function : return : : class : ` arq . jobs . Job ` instance or ` ` None ` ` if a job with this ID already exists"""
job_id = _job_id or uuid4 ( ) . hex job_key = job_key_prefix + job_id assert not ( _defer_until and _defer_by ) , "use either 'defer_until' or 'defer_by' or neither, not both" defer_by_ms = to_ms ( _defer_by ) expires_ms = to_ms ( _expires ) with await self as conn : pipe = conn . pipeline ( ) pipe . unwatch ( ) pipe . watch ( job_key ) job_exists = pipe . exists ( job_key ) await pipe . execute ( ) if await job_exists : return enqueue_time_ms = timestamp_ms ( ) if _defer_until is not None : score = to_unix_ms ( _defer_until ) elif defer_by_ms : score = enqueue_time_ms + defer_by_ms else : score = enqueue_time_ms expires_ms = expires_ms or score - enqueue_time_ms + expires_extra_ms job = pickle_job ( function , args , kwargs , _job_try , enqueue_time_ms ) tr = conn . multi_exec ( ) tr . psetex ( job_key , expires_ms , job ) tr . zadd ( queue_name , score , job_id ) try : await tr . execute ( ) except MultiExecError : # job got enqueued since we checked ' job _ exists ' return return Job ( job_id , self )
def from_string ( cls , cl_function , dependencies = ( ) , nmr_constraints = None ) : """Parse the given CL function into a SimpleCLFunction object . Args : cl _ function ( str ) : the function we wish to turn into an object dependencies ( list or tuple of CLLibrary ) : The list of CL libraries this function depends on Returns : SimpleCLFunction : the CL data type for this parameter declaration"""
return_type , function_name , parameter_list , body = split_cl_function ( cl_function ) return SimpleConstraintFunction ( return_type , function_name , parameter_list , body , dependencies = dependencies , nmr_constraints = nmr_constraints )