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def _from_dict ( cls , _dict ) : """Initialize a DialogNodeOutput object from a json dictionary ."""
args = { } xtra = _dict . copy ( ) if 'generic' in _dict : args [ 'generic' ] = [ DialogNodeOutputGeneric . _from_dict ( x ) for x in ( _dict . get ( 'generic' ) ) ] del xtra [ 'generic' ] if 'modifiers' in _dict : args [ 'modifiers' ] = DialogNodeOutputModifiers . _from_dict ( _dict . get ( 'modifiers' ) ) del xtra [ 'modifiers' ] args . update ( xtra ) return cls ( ** args )
def create_bulk_device_enrollment ( self , enrollment_identities , ** kwargs ) : # noqa : E501 """Bulk upload # noqa : E501 With bulk upload , you can upload a ` CSV ` file containing a number of enrollment IDs . * * Example usage : * * ` ` ` curl - X POST \\ - H ' Authorization : Bearer < valid access token > ' \\ - F ' enrollment _ identities = @ / path / to / enrollments / enrollments . csv ' \\ https : / / api . us - east - 1 . mbedcloud . com / v3 / device - enrollments - bulk - uploads ` ` ` * * An example ` CSV ` file : * * 1 . The first line is assumed to be the header . The content of the header is not validated . 2 . Each line can contain comma - separated values , where the first value is always assumed to be the Enrollment ID . 3 . Only one enrollment ID is expected per line . 4 . Valid enrollments begin with A followed by a - and 95 characters in the format as below . 5 . Valid enrollment identities may be enclosed within quotes . 6 . UTF - 8 encoding is expected . ` ` ` \" enrollment _ identity \" \" A - 4E : 63:2D : AE : 14 : BC : D1:09:77:21:95:44 : ED : 34:06:57:1E : 03 : B1 : EF : 0E : F2:59:44:71:93:23:22:15:43:23:12 \" , \" A - 4E : 63:2D : AE : 14 : BC : D1:09:77:21:95:44 : ED : 34:06:57:1E : 03 : B1 : EF : 0E : F2:59:25:48:44:71:22:15:43:23:12 \" , ` ` ` # noqa : E501 This method makes a synchronous HTTP request by default . To make an asynchronous HTTP request , please pass asynchronous = True > > > thread = api . create _ bulk _ device _ enrollment ( enrollment _ identities , asynchronous = True ) > > > result = thread . get ( ) : param asynchronous bool : param file enrollment _ identities : The ` CSV ` file containing the enrollment IDs . The maximum file size is 10MB . ( required ) : return : BulkResponse If the method is called asynchronously , returns the request thread ."""
kwargs [ '_return_http_data_only' ] = True if kwargs . get ( 'asynchronous' ) : return self . create_bulk_device_enrollment_with_http_info ( enrollment_identities , ** kwargs ) # noqa : E501 else : ( data ) = self . create_bulk_device_enrollment_with_http_info ( enrollment_identities , ** kwargs ) # noqa : E501 return data
def sites ( c ) : """Build both doc sites w / maxed nitpicking ."""
# TODO : This is super lolzy but we haven ' t actually tackled nontrivial # in - Python task calling yet , so we do this to get a copy of ' our ' context , # which has been updated with the per - collection config data of the # docs / www subcollections . docs_c = Context ( config = c . config . clone ( ) ) www_c = Context ( config = c . config . clone ( ) ) docs_c . update ( ** docs . configuration ( ) ) www_c . update ( ** www . configuration ( ) ) # Must build both normally first to ensure good intersphinx inventory files # exist = / circular dependencies ahoy ! Do it quietly to avoid pulluting # output ; only super - serious errors will bubble up . # TODO : wants a ' temporarily tweak context settings ' contextmanager # TODO : also a fucking spinner cuz this confuses me every time I run it # when the docs aren ' t already prebuilt docs_c [ "run" ] . hide = True www_c [ "run" ] . hide = True docs [ "build" ] ( docs_c ) www [ "build" ] ( www_c ) docs_c [ "run" ] . hide = False www_c [ "run" ] . hide = False # Run the actual builds , with nitpick = True ( nitpicks + tracebacks ) docs [ "build" ] ( docs_c , nitpick = True ) www [ "build" ] ( www_c , nitpick = True )
def _compute_magnitude_scaling ( self , mag , C ) : """Compute magnitude - scaling term ( Page 141 , Eq 1)"""
dmag = mag - 6. return ( C [ 'B2' ] * dmag ) + ( C [ 'B3' ] * ( dmag ** 2. ) )
def _query ( self , params , direct = False ) : """: param params : dict : return : pybomb . clients . response"""
params [ "api_key" ] = self . _api_key if "format" not in params : params [ "format" ] = self . _default_format response = self . _query_api ( params , direct ) self . _validate_response ( response ) return Response . from_response_data ( response )
def process_line ( self , line ) : """Process a line of data . Sends the data through the pipe to the process and flush it . Reads a resulting line and returns it . Parameters line : str The data sent to process . Make sure it does not contain any newline characters . Returns str : The line returned by the Java process Raises Exception In case of EOF is encountered . IoError In case it was impossible to read or write from the subprocess standard input / output ."""
assert isinstance ( line , str ) try : self . _process . stdin . write ( as_binary ( line ) ) self . _process . stdin . write ( as_binary ( '\n' ) ) self . _process . stdin . flush ( ) result = as_unicode ( self . _process . stdout . readline ( ) ) if result == '' : stderr = as_unicode ( self . _process . stderr . read ( ) ) raise Exception ( 'EOF encountered while reading stream. Stderr is {0}.' . format ( stderr ) ) return result except Exception : self . _process . terminate ( ) raise
def answerPreCheckoutQuery ( self , pre_checkout_query_id , ok , error_message = None ) : """See : https : / / core . telegram . org / bots / api # answerprecheckoutquery"""
p = _strip ( locals ( ) ) return self . _api_request ( 'answerPreCheckoutQuery' , _rectify ( p ) )
def collection_response ( cls , resources , start = None , stop = None ) : """Return a response for the * resources * of the appropriate content type . : param resources : resources to be returned in request : type resource : list of : class : ` sandman . model . Model ` : rtype : : class : ` flask . Response `"""
if _get_acceptable_response_type ( ) == JSON : return _collection_json_response ( cls , resources , start , stop ) else : return _collection_html_response ( resources , start , stop )
def quaternion_inverse ( quaternion ) : """Return inverse of quaternion . > > > q0 = random _ quaternion ( ) > > > q1 = quaternion _ inverse ( q0) > > > numpy . allclose ( quaternion _ multiply ( q0 , q1 ) , [ 1 , 0 , 0 , 0 ] ) True"""
q = numpy . array ( quaternion , dtype = numpy . float64 , copy = True ) numpy . negative ( q [ 1 : ] , q [ 1 : ] ) return q / numpy . dot ( q , q )
def send_to_backends ( self , event ) : """Sends the event to all registered backends . Logs and swallows all ` Exception ` ."""
for name , backend in six . iteritems ( self . backends ) : try : backend . send ( event ) except Exception : # pylint : disable = broad - except LOG . exception ( 'Unable to send event to backend: %s' , name )
def agg ( self , aggregations ) : """Multiple aggregations optimized . Parameters aggregations : list of str Which aggregations to perform . Returns DataFrame DataFrame with the aggregations per column ."""
check_type ( aggregations , list ) df = _drop_str_columns ( self ) if len ( df . _data ) == 0 : # conforming to what pandas does raise ValueError ( 'No results' ) new_index = Index ( np . array ( aggregations , dtype = np . bytes_ ) , np . dtype ( np . bytes_ ) ) new_data = OrderedDict ( ( column . name , _series_agg ( column , aggregations , new_index ) ) for column in df . _iter ( ) ) return DataFrame ( new_data , new_index )
def from_utf8 ( buf , errors = 'replace' ) : """Decodes a UTF - 8 compatible , ASCII string into a unicode object . ` buf ` string or unicode string to convert . Returns unicode ` string . * Raises a ` ` UnicodeDecodeError ` ` exception if encoding failed and ` errors ` isn ' t set to ' replace ' ."""
if isinstance ( buf , unicode ) : return buf else : return unicode ( buf , 'utf-8' , errors )
def normalize_names ( column_names ) : """Given an arbitrary column name , translate to a SQL - normalized column name a la CARTO ' s Import API will translate to Examples * ' Field : 2 ' - > ' field _ 2' * ' 2 Items ' - > ' _ 2 _ items ' * ' Unnamed : 0 ' - > ' unnamed _ 0 ' , * ' 201moore ' - > ' _ 201moore ' , * ' 201moore ' - > ' _ 201moore _ 1 ' , * ' Acadia 1.2.3 ' - > ' acadia _ 1_2_3 ' , * ' old _ soaker ' - > ' old _ soaker ' , * ' _ testingTesting ' - > ' _ testingtesting ' , * 1 - > ' _ 1 ' , * 1.0 - > ' _ 1_0 ' , * ' public ' - > ' public ' , * ' SELECT ' - > ' _ select ' , * ' à ' - > ' a ' , * ' longcolumnshouldbesplittedsomehowanditellyouwhereitsgonnabesplittedrightnow ' - > ' longcolumnshouldbesplittedsomehowanditellyouwhereitsgonnabespli ' , * ' longcolumnshouldbesplittedsomehowanditellyouwhereitsgonnabesplittedrightnow ' - > ' longcolumnshouldbesplittedsomehowanditellyouwhereitsgonnabe _ 1 ' , * ' all ' - > ' _ all ' Args : column _ names ( list ) : List of column names that will be SQL normalized Returns : list : List of SQL - normalized column names"""
result = [ ] for column_name in column_names : column = Column ( column_name ) . normalize ( forbidden_column_names = result ) result . append ( column . name ) return result
def create_wish_list ( cls , wish_list , ** kwargs ) : """Create WishList Create a new WishList This method makes a synchronous HTTP request by default . To make an asynchronous HTTP request , please pass async = True > > > thread = api . create _ wish _ list ( wish _ list , async = True ) > > > result = thread . get ( ) : param async bool : param WishList wish _ list : Attributes of wishList to create ( required ) : return : WishList If the method is called asynchronously , returns the request thread ."""
kwargs [ '_return_http_data_only' ] = True if kwargs . get ( 'async' ) : return cls . _create_wish_list_with_http_info ( wish_list , ** kwargs ) else : ( data ) = cls . _create_wish_list_with_http_info ( wish_list , ** kwargs ) return data
def copyPort ( port , targetLNode , reverseDir , topPortName = None ) : """Create identical port on targetNode"""
newP = _copyPort ( port , targetLNode , reverseDir ) if topPortName is not None : newP . name = topPortName return newP
def train ( self , X ) : """Trains multiple logistic regression classifiers to handle the multiclass problem posed by ` ` X ` ` X ( numpy . ndarray ) : The input data matrix . This must be a numpy . ndarray with 3 dimensions or an iterable containing 2 numpy . ndarrays with 2 dimensions each . Each correspond to the data for one of the input classes , every row corresponds to one example of the data set , every column , one different feature . Returns : Machine : A trained multiclass machine ."""
_trainer = bob . learn . linear . CGLogRegTrainer ( ** { 'lambda' : self . regularizer } ) if len ( X ) == 2 : # trains and returns a single logistic regression classifer return _trainer . train ( add_bias ( X [ 0 ] ) , add_bias ( X [ 1 ] ) ) else : # trains and returns a multi - class logistic regression classifier # use one - versus - all strategy machines = [ ] for k in range ( len ( X ) ) : NC_range = list ( range ( 0 , k ) ) + list ( range ( k + 1 , len ( X ) ) ) machines . append ( _trainer . train ( add_bias ( numpy . vstack ( X [ NC_range ] ) ) , add_bias ( X [ k ] ) ) ) return MultiClassMachine ( machines )
def _sigma_inel ( self , Tp ) : """Inelastic cross - section for p - p interaction . KATV14 Eq . 1 Parameters Tp : float Kinetic energy of proton ( i . e . Ep - m _ p * c * * 2 ) [ GeV ] Returns sigma _ inel : float Inelastic cross - section for p - p interaction [ 1 / cm2 ] ."""
L = np . log ( Tp / self . _Tth ) sigma = 30.7 - 0.96 * L + 0.18 * L ** 2 sigma *= ( 1 - ( self . _Tth / Tp ) ** 1.9 ) ** 3 return sigma * 1e-27
def parse_image_response ( self , response ) : """Parse a single object from the RETS feed : param response : The response from the RETS server : return : Object"""
if 'xml' in response . headers . get ( 'Content-Type' ) : # Got an XML response , likely an error code . xml = xmltodict . parse ( response . text ) self . analyze_reply_code ( xml_response_dict = xml ) obj = self . _response_object_from_header ( obj_head_dict = response . headers , content = response . content ) return obj
def generate ( env ) : """Add Builders and construction variables for MIPSPro to an Environment ."""
link . generate ( env ) env [ 'LINK' ] = env . Detect ( linkers ) or 'cc' env [ 'SHLINKFLAGS' ] = SCons . Util . CLVar ( '$LINKFLAGS -shared' ) # _ _ RPATH is set to $ _ RPATH in the platform specification if that # platform supports it . env [ 'RPATHPREFIX' ] = '-rpath ' env [ 'RPATHSUFFIX' ] = '' env [ '_RPATH' ] = '${_concat(RPATHPREFIX, RPATH, RPATHSUFFIX, __env__)}'
def merge ( self , imgs ) : """Merge image channels . Parameters imgs : ` list ` of ` PIL . Image . Image ` Returns ` PIL . Image . Image ` Raises ValueError If image channel list is empty ."""
if not imgs : raise ValueError ( 'empty channel list' ) if len ( imgs ) == 1 : return imgs [ 0 ] return Image . merge ( self . mode , imgs )
def read_version ( ) : """Read package version"""
with open ( './oi/version.py' ) as fh : for line in fh : if line . startswith ( 'VERSION' ) : return line . split ( '=' ) [ 1 ] . strip ( ) . strip ( "'" )
def get_filterset ( self , request , queryset , view ) : """Sometimes there ' s no ` filterset _ class ` defined yet the client still requests a filter . Make sure they see an error too . This means we have to ` get _ filterset _ kwargs ( ) ` even if there ' s no ` filterset _ class ` ."""
# TODO : . base _ filters vs . . filters attr ( not always present ) filterset_class = self . get_filterset_class ( view , queryset ) kwargs = self . get_filterset_kwargs ( request , queryset , view ) self . _validate_filter ( kwargs . pop ( 'filter_keys' ) , filterset_class ) if filterset_class is None : return None return filterset_class ( ** kwargs )
def parse_version ( version : str ) -> tuple : """Parse a string formatted X [ . Y . Z ] version number into a tuple > > > parse _ version ( ' 10.2.3 ' ) (10 , 2 , 3) > > > parse _ version ( ' 12 ' ) (12 , 0 , 0)"""
if not version : return None parts = version . split ( '.' ) missing = 3 - len ( parts ) return tuple ( int ( i ) for i in parts + ( [ 0 ] * missing ) )
def train ( self , s , path = "spelling.txt" ) : """Counts the words in the given string and saves the probabilities at the given path . This can be used to generate a new model for the Spelling ( ) constructor ."""
model = { } for w in re . findall ( "[a-z]+" , s . lower ( ) ) : model [ w ] = w in model and model [ w ] + 1 or 1 model = ( "%s %s" % ( k , v ) for k , v in sorted ( model . items ( ) ) ) model = "\n" . join ( model ) f = open ( path , "w" ) f . write ( model ) f . close ( )
def call_actions ( self , service_name , actions , expansions = None , raise_job_errors = True , raise_action_errors = True , timeout = None , ** kwargs ) : """Build and send a single job request with one or more actions . Returns a list of action responses , one for each action in the same order as provided , or raises an exception if any action response is an error ( unless ` raise _ action _ errors ` is passed as ` False ` ) or if the job response is an error ( unless ` raise _ job _ errors ` is passed as ` False ` ) . This method performs expansions if the Client is configured with an expansion converter . : param service _ name : The name of the service to call : type service _ name : union [ str , unicode ] : param actions : A list of ` ActionRequest ` objects and / or dicts that can be converted to ` ActionRequest ` objects : type actions : iterable [ union [ ActionRequest , dict ] ] : param expansions : A dictionary representing the expansions to perform : type expansions : dict : param raise _ job _ errors : Whether to raise a JobError if the job response contains errors ( defaults to ` True ` ) : type raise _ job _ errors : bool : param raise _ action _ errors : Whether to raise a CallActionError if any action responses contain errors ( defaults to ` True ` ) : type raise _ action _ errors : bool : param timeout : If provided , this will override the default transport timeout values to ; requests will expire after this number of seconds plus some buffer defined by the transport , and the client will not block waiting for a response for longer than this amount of time . : type timeout : int : param switches : A list of switch value integers : type switches : list : param correlation _ id : The request correlation ID : type correlation _ id : union [ str , unicode ] : param continue _ on _ error : Whether to continue executing further actions once one action has returned errors : type continue _ on _ error : bool : param context : A dictionary of extra values to include in the context header : type context : dict : param control _ extra : A dictionary of extra values to include in the control header : type control _ extra : dict : return : The job response : rtype : JobResponse : raise : ConnectionError , InvalidField , MessageSendError , MessageSendTimeout , MessageTooLarge , MessageReceiveError , MessageReceiveTimeout , InvalidMessage , JobError , CallActionError"""
return self . call_actions_future ( service_name , actions , expansions , raise_job_errors , raise_action_errors , timeout , ** kwargs ) . result ( )
def parse ( self , rec ) : """Retrieve row data from files associated with the ISATabRecord ."""
final_studies = [ ] for study in rec . studies : source_data = self . _parse_study ( study . metadata [ "Study File Name" ] , [ "Source Name" , "Sample Name" , "Comment[ENA_SAMPLE]" ] ) if source_data : study . nodes = source_data final_assays = [ ] for assay in study . assays : cur_assay = ISATabAssayRecord ( assay ) assay_data = self . _parse_study ( assay [ "Study Assay File Name" ] , [ "Sample Name" , "Extract Name" , "Raw Data File" , "Derived Data File" , "Image File" , "Acquisition Parameter Data File" , "Free Induction Decay Data File" ] ) cur_assay . nodes = assay_data self . _get_process_nodes ( assay [ "Study Assay File Name" ] , cur_assay ) final_assays . append ( cur_assay ) study . assays = final_assays # get process nodes self . _get_process_nodes ( study . metadata [ "Study File Name" ] , study ) final_studies . append ( study ) rec . studies = final_studies return rec
def vserver_exists ( v_name , v_ip = None , v_port = None , v_type = None , ** connection_args ) : '''Checks if a vserver exists CLI Example : . . code - block : : bash salt ' * ' netscaler . vserver _ exists ' vserverName ' '''
vserver = _vserver_get ( v_name , ** connection_args ) if vserver is None : return False if v_ip is not None and vserver . get_ipv46 ( ) != v_ip : return False if v_port is not None and vserver . get_port ( ) != v_port : return False if v_type is not None and vserver . get_servicetype ( ) . upper ( ) != v_type . upper ( ) : return False return True
def log_last_error ( fname , context = None ) : """Log last error in filename * fname * - - * context * : string ( optional )"""
fd = open ( fname , 'a' ) log_time ( fd ) if context : print ( "Context" , file = fd ) print ( "-------" , file = fd ) print ( "" , file = fd ) if PY2 : print ( u' ' . join ( context ) . encode ( 'utf-8' ) . strip ( ) , file = fd ) else : print ( context , file = fd ) print ( "" , file = fd ) print ( "Traceback" , file = fd ) print ( "---------" , file = fd ) print ( "" , file = fd ) traceback . print_exc ( file = fd ) print ( "" , file = fd ) print ( "" , file = fd )
def _api_all_views ( self ) : """Glances API RESTful implementation . Return the JSON representation of all the plugins views HTTP / 200 if OK HTTP / 400 if plugin is not found HTTP / 404 if others error"""
response . content_type = 'application/json; charset=utf-8' try : # Get the JSON value of the stat view limits = json . dumps ( self . stats . getAllViewsAsDict ( ) ) except Exception as e : abort ( 404 , "Cannot get views (%s)" % ( str ( e ) ) ) return limits
def _from_frame_string ( contents ) : """Convert a single frame XYZ string to a molecule"""
lines = contents . split ( "\n" ) num_sites = int ( lines [ 0 ] ) coords = [ ] sp = [ ] coord_patt = re . compile ( r"(\w+)\s+([0-9\-\+\.eEdD]+)\s+([0-9\-\+\.eEdD]+)\s+([0-9\-\+\.eEdD]+)" ) for i in range ( 2 , 2 + num_sites ) : m = coord_patt . search ( lines [ i ] ) if m : sp . append ( m . group ( 1 ) ) # this is 1 - indexed # this is 0 - indexed # in case of 0.0D + 00 or 0.00d + 01 old double precision writing # replace d or D by e for ten power exponent xyz = [ val . lower ( ) . replace ( "d" , "e" ) for val in m . groups ( ) [ 1 : 4 ] ] coords . append ( [ float ( val ) for val in xyz ] ) return Molecule ( sp , coords )
def extract_units ( string_in ) : """Extract units from parenthesis in a string . i . e . " elevation ( meters ) " : param str string _ in : : return str :"""
start = '(' stop = ')' return string_in [ string_in . index ( start ) + 1 : string_in . index ( stop ) ]
def fetch ( self , minutes = values . unset , start_date = values . unset , end_date = values . unset , task_queue_sid = values . unset , task_queue_name = values . unset , friendly_name = values . unset , task_channel = values . unset ) : """Fetch a WorkersStatisticsInstance : param unicode minutes : Filter cumulative statistics by up to ' x ' minutes in the past . : param datetime start _ date : Filter cumulative statistics by a start date . : param datetime end _ date : Filter cumulative statistics by a end date . : param unicode task _ queue _ sid : Filter the real - time and cumulative statistics based on Workers tied to a particular queue : param unicode task _ queue _ name : Filter the real - time and cumulative statistics based on Workers tied to a particular queue : param unicode friendly _ name : The friendly _ name : param unicode task _ channel : Filter cumulative statistics by TaskChannel . : returns : Fetched WorkersStatisticsInstance : rtype : twilio . rest . taskrouter . v1 . workspace . worker . workers _ statistics . WorkersStatisticsInstance"""
return self . _proxy . fetch ( minutes = minutes , start_date = start_date , end_date = end_date , task_queue_sid = task_queue_sid , task_queue_name = task_queue_name , friendly_name = friendly_name , task_channel = task_channel , )
def fit ( self , X ) : """Fit Kernel density estimation to an list of values . Args : X : 1 - d ` np . ndarray ` or ` pd . Series ` or ` list ` datapoints to be estimated from . This function will fit a gaussian _ kde model to a list of datapoints and store it as a class attribute ."""
self . constant_value = self . _get_constant_value ( X ) if self . constant_value is None : self . model = scipy . stats . gaussian_kde ( X ) else : self . _replace_constant_methods ( ) self . fitted = True
def set_attribute ( self , id , value , version = 1 ) : """Set attribute to a specific value : param id : id of the attribute : param value : value of the attribute : param version : version of the attribute ( default = 1)"""
attributes = self . _get_attributes ( cache = True ) formatted_id = '{0}' . format ( id ) attributes [ 'attributes_values' ] [ formatted_id ] = value response = self . requester . patch ( '/{endpoint}/custom-attributes-values/{id}' , endpoint = self . endpoint , id = self . id , payload = { 'attributes_values' : attributes [ 'attributes_values' ] , 'version' : version } ) cache_key = self . requester . get_full_url ( '/{endpoint}/custom-attributes-values/{id}' , endpoint = self . endpoint , id = self . id ) self . requester . cache . put ( cache_key , response ) return response . json ( )
def depfilter ( class_ , filter_name ) : """Register the decorated method at the addressed : class : ` ~ . callbacks . Filter ` on a class on which the service depends . : param class _ : A service class which is listed in the : attr : ` ~ . Meta . ORDER _ AFTER ` relationship . : type class _ : : class : ` Service ` class or : class : ` aioxmpp . stream . StanzaStream ` : param filter _ name : Attribute name of the filter to register at : type filter _ name : : class : ` str ` The filter at which the decorated method is registered is discovered by accessing the attribute with the name ` filter _ name ` on the instance of the dependent class ` class _ ` . If ` class _ ` is : class : ` aioxmpp . stream . StanzaStream ` , the filter is searched for on the stream ( and no dependendency needs to be declared ) . . . versionadded : : 0.9"""
spec = _depfilter_spec ( class_ , filter_name ) def decorator ( f ) : add_handler_spec ( f , spec , ) return f return decorator
def get_partition_trees ( self , p ) : """Return the trees associated with a partition , p"""
trees = [ ] for grp in p . get_membership ( ) : try : result = self . get_group_result ( grp ) trees . append ( result [ 'ml_tree' ] ) except ValueError : trees . append ( None ) logger . error ( 'No tree found for group {}' . format ( grp ) ) return trees
def __bindings ( self ) : """Binds events to handlers"""
self . textctrl . Bind ( wx . EVT_TEXT , self . OnText ) self . fontbutton . Bind ( wx . EVT_BUTTON , self . OnFont ) self . Bind ( csel . EVT_COLOURSELECT , self . OnColor )
def create_device ( device_args ) : """Creates an AlarmDecoder from the specified USB device arguments . : param device _ args : Tuple containing information on the USB device to open . : type device _ args : Tuple ( vid , pid , serialnumber , interface _ count , description )"""
device = AlarmDecoder ( USBDevice . find ( device_args ) ) device . on_message += handle_message device . open ( ) return device
def _next_id ( self ) : """Return the next available message id ."""
assert get_thread_ident ( ) == self . ioloop_thread_id self . _last_msg_id += 1 return str ( self . _last_msg_id )
def node_is_noop ( node : ast . AST ) -> bool : """Node does nothing ."""
return isinstance ( node . value , ast . Str ) if isinstance ( node , ast . Expr ) else isinstance ( node , ast . Pass )
def post_status ( app , user , status , visibility = 'public' , media_ids = None , sensitive = False , spoiler_text = None , in_reply_to_id = None ) : """Posts a new status . https : / / github . com / tootsuite / documentation / blob / master / Using - the - API / API . md # posting - a - new - status"""
# Idempotency key assures the same status is not posted multiple times # if the request is retried . headers = { "Idempotency-Key" : uuid . uuid4 ( ) . hex } return http . post ( app , user , '/api/v1/statuses' , { 'status' : status , 'media_ids[]' : media_ids , 'visibility' : visibility , 'sensitive' : str_bool ( sensitive ) , 'spoiler_text' : spoiler_text , 'in_reply_to_id' : in_reply_to_id , } , headers = headers ) . json ( )
def msg_callback ( self , callback ) : """Set the message callback ."""
if callable ( callback ) : self . _msg_callback = callback else : self . _msg_callback = None
def run ( self ) : """Run the main loop . Returns exit code ."""
self . exit_code = 1 self . mainloop = GLib . MainLoop ( ) try : future = ensure_future ( self . _start_async_tasks ( ) ) future . callbacks . append ( self . set_exit_code ) self . mainloop . run ( ) return self . exit_code except KeyboardInterrupt : return 1
def _append_comment ( ret , comment ) : '''append ` ` comment ` ` to ` ` ret [ ' comment ' ] ` `'''
if ret [ 'comment' ] : ret [ 'comment' ] = ret [ 'comment' ] . rstrip ( ) + '\n' + comment else : ret [ 'comment' ] = comment return ret
def sma ( self , np_array , n , array = False ) : """简单均线"""
if n < 2 : result = np_array else : result = talib . SMA ( np_array , n ) if array : return result return result [ - 1 ]
def ks_synth ( freq ) : """Synthesize the given frequency into a Stream by using a model based on Karplus - Strong ."""
ks_mem = ( sum ( lz . sinusoid ( x * freq ) for x in [ 1 , 3 , 9 ] ) + lz . white_noise ( ) + lz . Stream ( - 1 , 1 ) ) / 5 return lz . karplus_strong ( freq , memory = ks_mem )
def transform ( self , X ) : """Encode categorical columns into sparse matrix with one - hot - encoding . Args : X ( pandas . DataFrame ) : categorical columns to encode Returns : X _ new ( scipy . sparse . coo _ matrix ) : sparse matrix encoding categorical variables into dummy variables"""
for i , col in enumerate ( X . columns ) : X_col = self . _transform_col ( X [ col ] , i ) if X_col is not None : if i == 0 : X_new = X_col else : X_new = sparse . hstack ( ( X_new , X_col ) ) logger . debug ( '{} --> {} features' . format ( col , self . label_encoder . label_maxes [ i ] ) ) return X_new
def _init_notes ( self ) : """Set up the UserNotes page with the initial JSON schema ."""
self . cached_json = { 'ver' : self . schema , 'users' : { } , 'constants' : { 'users' : [ x . name for x in self . subreddit . moderator ( ) ] , 'warnings' : Note . warnings } } self . set_json ( 'Initializing JSON via puni' , True )
def _load_fits ( self , h5file ) : """Loads fits from h5file and returns a dictionary of fits ."""
fits = { } for key in [ 'mf' ] : fits [ key ] = self . _load_scalar_fit ( fit_key = key , h5file = h5file ) for key in [ 'chif' , 'vf' ] : fits [ key ] = self . _load_vector_fit ( key , h5file ) return fits
def extract_annotation ( data ) : """Extract names and values of rows and columns . Parameter : data : DataFrame | Panel Returns : col _ name , col _ values , row _ name , row _ values"""
xlabel = None xvalues = None ylabel = None yvalues = None if hasattr ( data , 'minor_axis' ) : xvalues = data . minor_axis if hasattr ( data . minor_axis , 'name' ) : xlabel = data . minor_axis . name if hasattr ( data , 'columns' ) : xvalues = data . columns if hasattr ( data . columns , 'name' ) : xlabel = data . columns . name if hasattr ( data , 'major_axis' ) : yvalues = data . major_axis if hasattr ( data . major_axis , 'name' ) : ylabel = data . major_axis . name if hasattr ( data , 'index' ) : yvalues = data . index if hasattr ( data . index , 'name' ) : ylabel = data . index . name return xlabel , xvalues , ylabel , yvalues
def _evaluate ( dataset , predictions ) : '''Evaluate function .'''
f1_result = exact_match = total = 0 count = 0 for article in dataset : for paragraph in article [ 'paragraphs' ] : for qa_pair in paragraph [ 'qas' ] : total += 1 if qa_pair [ 'id' ] not in predictions : count += 1 continue ground_truths = list ( map ( lambda x : x [ 'text' ] , qa_pair [ 'answers' ] ) ) prediction = predictions [ qa_pair [ 'id' ] ] exact_match += metric_max_over_ground_truths ( exact_match_score , prediction , ground_truths ) f1_result += metric_max_over_ground_truths ( f1_score , prediction , ground_truths ) print ( 'total' , total , 'exact_match' , exact_match , 'unanswer_question ' , count ) exact_match = 100.0 * exact_match / total f1_result = 100.0 * f1_result / total return { 'exact_match' : exact_match , 'f1' : f1_result }
def _process_call ( self , req , resource ) : """This is were all callbacks are made and the req is processed ."""
if resource == "ports" : if req . method . upper ( ) in ( 'PUT' , 'POST' ) : # Pass the request back to be processed by other filters # and Neutron first resp = req . get_response ( self . app ) if resp . status_code not in ( 200 , 204 ) : return resp resp_body = resp . json # Variables for Nova Call , obtained from Neutron response action = "create" address = resp_body [ 'port' ] [ 'mac_address' ] fixed_ips = resp_body [ 'port' ] [ 'fixed_ips' ] instance_id = resp_body [ 'port' ] [ 'instance_id' ] network_id = resp_body [ 'port' ] [ 'network_id' ] port_id = resp_body [ 'port' ] [ 'id' ] tenant_id = resp_body [ 'port' ] [ 'tenant_id' ] elif req . method . upper ( ) == "DELETE" : action = "delete" port_id = req . path . split ( "/" ) port_id = port_id [ port_id . index ( "ports" ) + 1 ] # DELETEs do not have all the port info that we need , so a # call to Neutron must be made first . neutron_conn = NeutronConn ( log = self . log , port = self . neutron_port , url = self . neutron_url , verify_ssl = self . neutron_verify_ssl ) status , neutron_resp = neutron_conn . ports ( port_id = port_id ) if isinstance ( neutron_resp , Exception ) : return neutron_resp elif status not in ( 200 , 204 ) : resp = Response ( ) resp . status = 500 new_body = { "neutron_callback" : { "port_id" : port_id , "status" : "error" , "error" : neutron_resp } } resp . body = json . dumps ( new_body ) return resp # Now that we have the port info , we can make the variables # for the Nova Call address = neutron_resp [ 'port' ] [ 'mac_address' ] fixed_ips = neutron_resp [ 'port' ] [ 'fixed_ips' ] instance_id = neutron_resp [ 'port' ] [ 'instance_id' ] network_id = neutron_resp [ 'port' ] [ 'network_id' ] tenant_id = neutron_resp [ 'port' ] [ 'tenant_id' ] # Port info saved , now send the request back to processed by # other filters and Neutron resp = req . get_response ( self . app ) if resp . status_code not in ( 200 , 204 ) : return resp else : new_body = resp . json new_body [ 'neutron_callback' ] = { "port_id" : port_id , "status" : "success" } resp . body = json . dumps ( new_body ) nova_conn = NovaConn ( log = self . log , url = self . nova_url , verify_ssl = self . nova_verify_ssl ) status , nova_resp = nova_conn . admin_virtual_interfaces ( action = action , address = address , fixed_ips = fixed_ips , network_id = network_id , port_id = port_id , tenant_id = tenant_id , instance_id = instance_id ) if isinstance ( nova_resp , Exception ) : return nova_resp elif status not in ( 200 , 204 ) : # We ' ll likely want to provide the customer with a call here # such as virtual - interface - delete / virtual - interface - update resp . status = 500 new_body = resp . json new_body [ 'nova_callback' ] = { "instance_id" : instance_id , "status" : "error" , "error" : nova_resp } resp . body = json . dumps ( new_body ) else : new_body = resp . json new_body [ 'nova_callback' ] = { "instance_id" : instance_id , "status" : "success" } resp . body = json . dumps ( new_body ) return resp elif resource == "ip_addresses" : pass # Insert logic to call Nova for ip _ addresses changes here return resp
def append_flags_into_file ( self , filename ) : """Appends all flags assignments from this FlagInfo object to a file . Output will be in the format of a flagfile . NOTE : MUST mirror the behavior of the C + + AppendFlagsIntoFile from https : / / github . com / gflags / gflags . Args : filename : str , name of the file ."""
with open ( filename , 'a' ) as out_file : out_file . write ( self . flags_into_string ( ) )
def add_host_comment ( self , host , author , comment ) : """Add a host comment Format of the line that triggers function call : : ADD _ HOST _ COMMENT ; < host _ name > ; < persistent : obsolete > ; < author > ; < comment > : param host : host to add the comment : type host : alignak . objects . host . Host : param author : author name : type author : str : param comment : text comment : type comment : str : return : None"""
data = { 'author' : author , 'comment' : comment , 'comment_type' : 1 , 'entry_type' : 1 , 'source' : 1 , 'expires' : False , 'ref' : host . uuid } comm = Comment ( data ) host . add_comment ( comm ) self . send_an_element ( host . get_update_status_brok ( ) ) try : brok = make_monitoring_log ( 'info' , "HOST COMMENT: %s;%s;%s" % ( host . get_name ( ) , str ( author , 'utf-8' ) , str ( comment , 'utf-8' ) ) ) except TypeError : brok = make_monitoring_log ( 'info' , "HOST COMMENT: %s;%s;%s" % ( host . get_name ( ) , author , comment ) ) self . send_an_element ( brok ) self . send_an_element ( comm . get_comment_brok ( self . hosts [ host ] . get_name ( ) ) )
def build ( self , ** kwargs ) : """Build an image and return it . Similar to the ` ` docker build ` ` command . Either ` ` path ` ` or ` ` fileobj ` ` must be set . If you have a tar file for the Docker build context ( including a Dockerfile ) already , pass a readable file - like object to ` ` fileobj ` ` and also pass ` ` custom _ context = True ` ` . If the stream is compressed also , set ` ` encoding ` ` to the correct value ( e . g ` ` gzip ` ` ) . If you want to get the raw output of the build , use the : py : meth : ` ~ docker . api . build . BuildApiMixin . build ` method in the low - level API . Args : path ( str ) : Path to the directory containing the Dockerfile fileobj : A file object to use as the Dockerfile . ( Or a file - like object ) tag ( str ) : A tag to add to the final image quiet ( bool ) : Whether to return the status nocache ( bool ) : Don ' t use the cache when set to ` ` True ` ` rm ( bool ) : Remove intermediate containers . The ` ` docker build ` ` command now defaults to ` ` - - rm = true ` ` , but we have kept the old default of ` False ` to preserve backward compatibility timeout ( int ) : HTTP timeout custom _ context ( bool ) : Optional if using ` ` fileobj ` ` encoding ( str ) : The encoding for a stream . Set to ` ` gzip ` ` for compressing pull ( bool ) : Downloads any updates to the FROM image in Dockerfiles forcerm ( bool ) : Always remove intermediate containers , even after unsuccessful builds dockerfile ( str ) : path within the build context to the Dockerfile buildargs ( dict ) : A dictionary of build arguments container _ limits ( dict ) : A dictionary of limits applied to each container created by the build process . Valid keys : - memory ( int ) : set memory limit for build - memswap ( int ) : Total memory ( memory + swap ) , - 1 to disable swap - cpushares ( int ) : CPU shares ( relative weight ) - cpusetcpus ( str ) : CPUs in which to allow execution , e . g . , ` ` " 0-3 " ` ` , ` ` " 0,1 " ` ` shmsize ( int ) : Size of ` / dev / shm ` in bytes . The size must be greater than 0 . If omitted the system uses 64MB labels ( dict ) : A dictionary of labels to set on the image cache _ from ( list ) : A list of images used for build cache resolution target ( str ) : Name of the build - stage to build in a multi - stage Dockerfile network _ mode ( str ) : networking mode for the run commands during build squash ( bool ) : Squash the resulting images layers into a single layer . extra _ hosts ( dict ) : Extra hosts to add to / etc / hosts in building containers , as a mapping of hostname to IP address . platform ( str ) : Platform in the format ` ` os [ / arch [ / variant ] ] ` ` . isolation ( str ) : Isolation technology used during build . Default : ` None ` . use _ config _ proxy ( bool ) : If ` ` True ` ` , and if the docker client configuration file ( ` ` ~ / . docker / config . json ` ` by default ) contains a proxy configuration , the corresponding environment variables will be set in the container being built . Returns : ( tuple ) : The first item is the : py : class : ` Image ` object for the image that was build . The second item is a generator of the build logs as JSON - decoded objects . Raises : : py : class : ` docker . errors . BuildError ` If there is an error during the build . : py : class : ` docker . errors . APIError ` If the server returns any other error . ` ` TypeError ` ` If neither ` ` path ` ` nor ` ` fileobj ` ` is specified ."""
resp = self . client . api . build ( ** kwargs ) if isinstance ( resp , six . string_types ) : return self . get ( resp ) last_event = None image_id = None result_stream , internal_stream = itertools . tee ( json_stream ( resp ) ) for chunk in internal_stream : if 'error' in chunk : raise BuildError ( chunk [ 'error' ] , result_stream ) if 'stream' in chunk : match = re . search ( r'(^Successfully built |sha256:)([0-9a-f]+)$' , chunk [ 'stream' ] ) if match : image_id = match . group ( 2 ) last_event = chunk if image_id : return ( self . get ( image_id ) , result_stream ) raise BuildError ( last_event or 'Unknown' , result_stream )
def target ( self ) : """Return the target of the BFD file being processed ."""
if not self . _ptr : raise BfdException ( "BFD not initialized" ) return _bfd . get_bfd_attribute ( self . _ptr , BfdAttributes . TARGET )
def _get_min_distance_to_sub_trench ( lons , lats ) : """Compute and return minimum distance between subduction trench and points specified by ' lon ' and ' lat ' The method creates an instance of : class : ` openquake . hazardlib . geo . SimpleFaultSurface ` to model the subduction trench . The surface is assumed vertical and extending from 0 to 10 km depth . The 10 km depth value is arbitrary given that distance calculation depend only on top edge depth . The method calls then : meth : ` openquake . hazardlib . geo . base . BaseSurface . get _ rx _ distance ` and return its absolute value ."""
trench = _construct_surface ( SUB_TRENCH_LONS , SUB_TRENCH_LATS , 0. , 10. ) sites = Mesh ( lons , lats , None ) return np . abs ( trench . get_rx_distance ( sites ) )
def marvcli_cleanup ( ctx , discarded , unused_tags ) : """Cleanup unused tags and discarded datasets ."""
if not any ( [ discarded , unused_tags ] ) : click . echo ( ctx . get_help ( ) ) ctx . exit ( 1 ) site = create_app ( ) . site if discarded : site . cleanup_discarded ( ) if unused_tags : site . cleanup_tags ( ) site . cleanup_relations ( )
def process_json_file ( file_path , pmid = None , extra_annotations = None , add_grounding = True ) : """Extracts statements from the given ISI output file . Parameters file _ path : str The ISI output file from which to extract statements pmid : int The PMID of the document being preprocessed , or None if not specified extra _ annotations : dict Extra annotations to be added to each statement from this document ( can be the empty dictionary ) add _ grounding : Optional [ bool ] If True the extracted Statements ' grounding is mapped"""
logger . info ( 'Extracting from %s' % file_path ) with open ( file_path , 'rb' ) as fh : jd = json . load ( fh ) ip = IsiProcessor ( jd , pmid , extra_annotations ) ip . get_statements ( ) if add_grounding : ip . add_grounding ( ) return ip
def tofits ( outfilename , pixelarray , hdr = None , verbose = True ) : """Takes a 2D numpy array and write it into a FITS file . If you specify a header ( pyfits format , as returned by fromfits ( ) ) it will be used for the image . You can give me boolean numpy arrays , I will convert them into 8 bit integers ."""
pixelarrayshape = pixelarray . shape if verbose : print "FITS export shape : (%i, %i)" % ( pixelarrayshape [ 0 ] , pixelarrayshape [ 1 ] ) if pixelarray . dtype . name == "bool" : pixelarray = np . cast [ "uint8" ] ( pixelarray ) if os . path . isfile ( outfilename ) : os . remove ( outfilename ) if hdr == None : # then a minimal header will be created hdu = pyfits . PrimaryHDU ( pixelarray . transpose ( ) ) else : # this if else is probably not needed but anyway . . . hdu = pyfits . PrimaryHDU ( pixelarray . transpose ( ) , hdr ) hdu . writeto ( outfilename ) if verbose : print "Wrote %s" % outfilename
def _get_all_lengths ( self ) : """For every utterance , get the length of the data in every container . Return a list of tuples ."""
utt_lengths = { } for utt_idx in self . utt_ids : per_container = [ c . _file [ utt_idx ] . shape [ 0 ] for c in self . containers ] utt_lengths [ utt_idx ] = tuple ( per_container ) return utt_lengths
def com_google_fonts_check_metadata_valid_filename_values ( font , family_metadata ) : """METADATA . pb font . filename field contains font name in right format ?"""
expected = os . path . basename ( font ) failed = True for font_metadata in family_metadata . fonts : if font_metadata . filename == expected : failed = False yield PASS , ( "METADATA.pb filename field contains" " font name in right format." ) break if failed : yield FAIL , ( "None of the METADATA.pb filename fields match" f" correct font name format (\"{expected}\")." )
def ConfigureRequest ( self , upload_config , http_request , url_builder ) : """Configure the request and url for this upload ."""
# Validate total _ size vs . max _ size if ( self . total_size and upload_config . max_size and self . total_size > upload_config . max_size ) : raise exceptions . InvalidUserInputError ( 'Upload too big: %s larger than max size %s' % ( self . total_size , upload_config . max_size ) ) # Validate mime type if not util . AcceptableMimeType ( upload_config . accept , self . mime_type ) : raise exceptions . InvalidUserInputError ( 'MIME type %s does not match any accepted MIME ranges %s' % ( self . mime_type , upload_config . accept ) ) self . __SetDefaultUploadStrategy ( upload_config , http_request ) if self . strategy == SIMPLE_UPLOAD : url_builder . relative_path = upload_config . simple_path if http_request . body : url_builder . query_params [ 'uploadType' ] = 'multipart' self . __ConfigureMultipartRequest ( http_request ) else : url_builder . query_params [ 'uploadType' ] = 'media' self . __ConfigureMediaRequest ( http_request ) # Once the entire body is written , compress the body if configured # to . Both multipart and media request uploads will read the # entire stream into memory , which means full compression is also # safe to perform . Because the strategy is set to SIMPLE _ UPLOAD , # StreamInChunks throws an exception , meaning double compression # cannot happen . if self . __gzip_encoded : http_request . headers [ 'Content-Encoding' ] = 'gzip' # Turn the body into a stream so that we can compress it , then # read the compressed bytes . In the event of a retry ( e . g . if # our access token has expired ) , we need to be able to re - read # the body , which we can ' t do with a stream . So , we consume the # bytes from the stream now and store them in a re - readable # bytes container . http_request . body = ( compression . CompressStream ( six . BytesIO ( http_request . body ) ) [ 0 ] . read ( ) ) else : url_builder . relative_path = upload_config . resumable_path url_builder . query_params [ 'uploadType' ] = 'resumable' self . __ConfigureResumableRequest ( http_request )
def make_trace_api ( client ) : """Create an instance of the gapic Trace API . Args : client ( ~ google . cloud . trace . client . Client ) : The client that holds configuration details . Returns : A : class : ` ~ google . cloud . trace . _ gapic . _ TraceAPI ` instance with the proper configurations ."""
generated = trace_service_client . TraceServiceClient ( credentials = client . _credentials , client_info = _CLIENT_INFO ) return _TraceAPI ( generated , client )
def parse_away_face_offs ( self ) : """Parse only the away faceoffs : returns : ` ` self ` ` on success , ` ` None ` ` otherwise"""
self . __set_team_docs ( ) self . face_offs [ 'away' ] = FaceOffRep . __read_team_doc ( self . __vis_doc ) return self
def add_root_objective_bank ( self , alias = None , objective_bank_id = None ) : """Adds a root objective bank . arg : objective _ bank _ id ( osid . id . Id ) : the ` ` Id ` ` of an objective bank raise : AlreadyExists - ` ` objective _ bank _ id ` ` is already in hierarchy raise : NotFound - ` ` objective _ bank _ id ` ` not found raise : NullArgument - ` ` objective _ bank _ id ` ` is ` ` null ` ` raise : OperationFailed - unable to complete request raise : PermissionDenied - authorization failure * compliance : mandatory - - This method must be implemented . *"""
url_path = self . _urls . roots ( alias = alias ) current_root_ids = self . _get_request ( url_path ) [ 'ids' ] current_root_ids . append ( str ( objective_bank_id ) ) new_root_ids = { 'ids' : current_root_ids } return self . _put_request ( url_path , new_root_ids )
def read ( self , size = None ) : """Reads a byte string from the file - like object at the current offset . The function will read a byte string of the specified size or all of the remaining data if no size was specified . Args : size ( Optional [ int ] ) : number of bytes to read , where None is all remaining data . Returns : bytes : data read . Raises : IOError : if the read failed . OSError : if the read failed ."""
if not self . _is_open : raise IOError ( 'Not opened.' ) return self . _vshadow_store . read ( size )
def location ( self ) : """Returns the geolocation as a lat / lng pair"""
try : lat , lng = self [ "metadata" ] [ "latitude" ] , self [ "metadata" ] [ "longitude" ] except KeyError : return None if not lat or not lng : return None return lat , lng
def shutdown_login_server ( self , ) : """Shutdown the login server and thread : returns : None : rtype : None : raises : None"""
log . debug ( 'Shutting down the login server thread.' ) self . login_server . shutdown ( ) self . login_server . server_close ( ) self . login_thread . join ( )
def ToJson ( self ) : """Convert object members to a dictionary that can be parsed as JSON . Returns : dict :"""
name = 'Contract' try : name = self . Name . decode ( 'utf-8' ) except Exception as e : pass jsn = { 'version' : self . StateVersion } jsn_code = self . Code . ToJson ( ) jsn_contract = { 'name' : name , 'code_version' : self . CodeVersion . decode ( 'utf-8' ) , 'author' : self . Author . decode ( 'utf-8' ) , 'email' : self . Email . decode ( 'utf-8' ) , 'description' : self . Description . decode ( 'utf-8' ) , 'properties' : { 'storage' : self . HasStorage , 'dynamic_invoke' : self . HasDynamicInvoke , 'payable' : self . Payable } } jsn . update ( jsn_code ) jsn . update ( jsn_contract ) if self . _nep_token : jsn [ 'token' ] = self . _nep_token . ToJson ( ) return jsn
def watch_for_events ( ) : """Wait for events and print them to stdout ."""
fd = inotify . init ( ) try : wd = inotify . add_watch ( fd , '/tmp' , inotify . IN_CLOSE_WRITE ) while True : for event in inotify . get_events ( fd ) : print ( "event:" , event . name , event . get_mask_description ( ) ) finally : os . close ( fd )
def smartDumpDictHdf5 ( RV , o ) : """Dump a dictionary where each page is a list or an array or still a dictionary ( in this case , it iterates )"""
for key in list ( RV . keys ( ) ) : if type ( RV [ key ] ) == dict : g = o . create_group ( key ) smartDumpDictHdf5 ( RV [ key ] , g ) else : o . create_dataset ( name = key , data = SP . array ( RV [ key ] ) , chunks = True , compression = 'gzip' )
def save ( self , to_save , manipulate = True , check_keys = True , ** kwargs ) : """Save a document in this collection . * * DEPRECATED * * - Use : meth : ` insert _ one ` or : meth : ` replace _ one ` instead . . . versionchanged : : 3.0 Removed the ` safe ` parameter . Pass ` ` w = 0 ` ` for unacknowledged write operations ."""
warnings . warn ( "save is deprecated. Use insert_one or replace_one " "instead" , DeprecationWarning , stacklevel = 2 ) common . validate_is_document_type ( "to_save" , to_save ) write_concern = None collation = validate_collation_or_none ( kwargs . pop ( 'collation' , None ) ) if kwargs : write_concern = WriteConcern ( ** kwargs ) with self . _socket_for_writes ( ) as sock_info : if not ( isinstance ( to_save , RawBSONDocument ) or "_id" in to_save ) : return self . _insert ( sock_info , to_save , True , check_keys , manipulate , write_concern ) else : self . _update ( sock_info , { "_id" : to_save [ "_id" ] } , to_save , True , check_keys , False , manipulate , write_concern , collation = collation ) return to_save . get ( "_id" )
def find_by_id ( self , project , params = { } , ** options ) : """Returns the complete project record for a single project . Parameters project : { Id } The project to get . [ params ] : { Object } Parameters for the request"""
path = "/projects/%s" % ( project ) return self . client . get ( path , params , ** options )
def load_extension ( self , name ) : """Loads an extension . An extension is a python module that contains commands , cogs , or listeners . An extension must have a global function , ` ` setup ` ` defined as the entry point on what to do when the extension is loaded . This entry point must have a single argument , the ` ` bot ` ` . Parameters name : : class : ` str ` The extension name to load . It must be dot separated like regular Python imports if accessing a sub - module . e . g . ` ` foo . test ` ` if you want to import ` ` foo / test . py ` ` . Raises ExtensionNotFound The extension could not be imported . ExtensionAlreadyLoaded The extension is already loaded . NoEntryPointError The extension does not have a setup function . ExtensionFailed The extension setup function had an execution error ."""
if name in self . __extensions : raise errors . ExtensionAlreadyLoaded ( name ) try : lib = importlib . import_module ( name ) except ImportError as e : raise errors . ExtensionNotFound ( name , e ) from e else : self . _load_from_module_spec ( lib , name )
def save ( self , target , ensure_ascii = True ) : """https : / / github . com / frictionlessdata / tableschema - py # schema"""
mode = 'w' encoding = 'utf-8' if six . PY2 : mode = 'wb' encoding = None helpers . ensure_dir ( target ) with io . open ( target , mode = mode , encoding = encoding ) as file : json . dump ( self . __current_descriptor , file , indent = 4 , ensure_ascii = ensure_ascii )
def user_patterns ( self ) : """: class : ` ~ zhmcclient . UserPatternManager ` : Access to the : term : ` User Patterns < User Pattern > ` in this Console ."""
# We do here some lazy loading . if not self . _user_patterns : self . _user_patterns = UserPatternManager ( self ) return self . _user_patterns
def get ( self , index ) : """Get the element by index . If index is out of bounds for the internal list , None is returned . Indexes cannot be negative . : param int index : retrieve element by positive index in list : rtype : SubElement or None"""
if self and ( index <= len ( self ) - 1 ) : return self . _result_cache [ index ]
def wait_for_service ( self , interval = 1 ) : """Wait for the online model to be ready for service . : param interval : check interval"""
while self . status in ( OnlineModel . Status . DEPLOYING , OnlineModel . Status . UPDATING ) : time . sleep ( interval ) if self . status == OnlineModel . Status . DEPLOY_FAILED : raise OnlineModelError ( self . last_fail_msg , self ) elif self . status != OnlineModel . Status . SERVING : raise OnlineModelError ( 'Unexpected status occurs: %s' % self . status . value , self )
def hungarian ( A , B ) : """Hungarian reordering . Assume A and B are coordinates for atoms of SAME type only"""
# should be kabasch here i think distances = cdist ( A , B , 'euclidean' ) # Perform Hungarian analysis on distance matrix between atoms of 1st # structure and trial structure indices_a , indices_b = linear_sum_assignment ( distances ) return indices_b
def set_scale ( self , xscale = None , yscale = None , zscale = None , reset_camera = True ) : """Scale all the datasets in the scene of the active renderer . Scaling in performed independently on the X , Y and Z axis . A scale of zero is illegal and will be replaced with one . Parameters xscale : float , optional Scaling of the x axis . Must be greater than zero . yscale : float , optional Scaling of the y axis . Must be greater than zero . zscale : float , optional Scaling of the z axis . Must be greater than zero . reset _ camera : bool , optional Resets camera so all actors can be seen ."""
self . renderer . set_scale ( xscale , yscale , zscale , reset_camera )
def default_update_stack ( self , fqn , template , old_parameters , parameters , tags , stack_policy = None , ** kwargs ) : """Update a Cloudformation stack in default mode . Args : fqn ( str ) : The fully qualified name of the Cloudformation stack . template ( : class : ` stacker . providers . base . Template ` ) : A Template object to use when updating the stack . old _ parameters ( list ) : A list of dictionaries that defines the parameter list on the existing Cloudformation stack . parameters ( list ) : A list of dictionaries that defines the parameter list to be applied to the Cloudformation stack . tags ( list ) : A list of dictionaries that defines the tags that should be applied to the Cloudformation stack . stack _ policy ( : class : ` stacker . providers . base . Template ` ) : A template object representing a stack policy ."""
logger . debug ( "Using default provider mode for %s." , fqn ) args = generate_cloudformation_args ( fqn , parameters , tags , template , service_role = self . service_role , stack_policy = stack_policy , ) try : self . cloudformation . update_stack ( ** args ) except botocore . exceptions . ClientError as e : if "No updates are to be performed." in str ( e ) : logger . debug ( "Stack %s did not change, not updating." , fqn , ) raise exceptions . StackDidNotChange elif e . response [ 'Error' ] [ 'Message' ] == ( 'TemplateURL must ' 'reference a valid ' 'S3 object to which ' 'you have access.' ) : s3_fallback ( fqn , template , parameters , tags , self . cloudformation . update_stack , self . service_role ) else : raise
def scale_sfs_folded ( s , n ) : """Scale a folded site frequency spectrum . Parameters s : array _ like , int , shape ( n _ chromosomes / / 2 , ) Folded site frequency spectrum . n : int Number of chromosomes called . Returns sfs _ folded _ scaled : ndarray , int , shape ( n _ chromosomes / / 2 , ) Scaled folded site frequency spectrum ."""
k = np . arange ( s . shape [ 0 ] ) out = s * k * ( n - k ) / n return out
def get_objgrpwr ( self , goea_results ) : """Get a GrpWr object to write grouped GOEA results ."""
sortobj = self . get_sortobj ( goea_results ) return GrpWr ( sortobj , self . pval_fld , ver_list = self . ver_list )
def name ( self ) : """获取用户名字 . : return : 用户名字 : rtype : str"""
if self . url is None : return '匿名用户' if self . soup is not None : return self . soup . find ( 'div' , class_ = 'title-section' ) . span . text else : assert self . card is not None return self . card . find ( 'span' , class_ = 'name' ) . text
def compose_from_srts ( srts , search , searchtype ) : """Takes a list of subtitle ( srt ) filenames , search term and search type and , returns a list of timestamps for composing a supercut ."""
composition = [ ] foundSearchTerm = False # Iterate over each subtitles file . for srt in srts : print ( srt ) lines = clean_srt ( srt ) videofile = "" foundVideoFile = False print ( "[+] Searching for video file corresponding to '" + srt + "'." ) for ext in usable_extensions : tempVideoFile = srt . replace ( '.srt' , '.' + ext ) if os . path . isfile ( tempVideoFile ) : videofile = tempVideoFile foundVideoFile = True print ( "[+] Found '" + tempVideoFile + "'." ) # If a correspndong video file was found for this subtitles file . . . if foundVideoFile : # Check that the subtitles file contains subtitles . if lines : # Iterate over each line in the current subtitles file . for timespan in lines . keys ( ) : line = lines [ timespan ] . strip ( ) # If this line contains the search term if search_line ( line , search , searchtype ) : foundSearchTerm = True # Extract the timespan for this subtitle . start , end = convert_timespan ( timespan ) # Record this occurance of the search term . composition . append ( { 'file' : videofile , 'time' : timespan , 'start' : start , 'end' : end , 'line' : line } ) # If the search was unsuccessful . if foundSearchTerm is False : print ( "[!] Search term '" + search + "'" + " was not found is subtitle file '" + srt + "'." ) # If no subtitles were found in the current file . else : print ( "[!] Subtitle file '" + srt + "' is empty." ) # If no video file was found . . . else : print ( "[!] No video file was found which corresponds to subtitle file '" + srt + "'." ) print ( "[!] The following video formats are currently supported:" ) extList = "" for ext in usable_extensions : extList += ext + ", " print ( extList ) return composition
def get_section_header ( self , section ) : """Get a specific section header by index or name . Args : section ( int or str ) : The index or name of the section header to return . Returns : : class : ` ~ ELF . SectionHeader ` : The section header . Raises : KeyError : The requested section header does not exist ."""
self . _ensure_section_headers_loaded ( ) if type ( section ) is int : return self . _section_headers_by_index [ section ] else : return self . _section_headers_by_name [ section ]
def _form_output ( span_doc : span , output_format : str , relations : Dict , patterns : List ) -> str : """Form an output value according to user input of output _ format Args : span _ doc : span format : str relations : Dict patterns : List Returns : str"""
format_value = [ ] output_inf = [ a_pattern . in_output for a_pattern in patterns ] for i in range ( len ( output_inf ) ) : token_range = relations [ i ] if token_range and output_inf [ i ] : format_value . append ( span_doc [ token_range [ 0 ] : token_range [ 1 ] ] . text ) if not output_format : return " " . join ( format_value ) result_str = re . sub ( "{}" , " " . join ( format_value ) , output_format ) positions = re . findall ( "{[0-9]+}" , result_str ) if not positions : return result_str position_indices = [ int ( x [ 1 : - 1 ] ) for x in positions ] if max ( position_indices ) < len ( format_value ) : result_str = result_str . format ( * format_value ) else : try : result_str = result_str . format ( "" , * format_value ) except : positions = [ x for x in positions if int ( x [ 1 : - 1 ] ) > len ( format_value ) - 1 or int ( x [ 1 : - 1 ] ) < 0 ] for pos in positions : result_str = result_str . replace ( pos , "" ) result_str = result_str . format ( * format_value ) return result_str
def imf ( m ) : '''Returns N ( M ) dM for given mass according to Kroupa IMF , vectorization available via vimf ( )'''
m1 = 0.08 ; m2 = 0.50 a1 = 0.30 ; a2 = 1.30 ; a3 = 2.3 const2 = m1 ** - a1 - m1 ** - a2 const3 = m2 ** - a2 - m2 ** - a3 if m < 0.08 : alpha = 0.3 const = - const2 - const3 elif m < 0.50 : alpha = 1.3 const = - const3 else : alpha = 2.3 const = 0.0 # print m , alpha , const , m * * - alpha + const return m ** - alpha + const
def open ( self ) : '''Open tunnel'''
if self . is_compatible ( ) : tunnel_ad_url = self . get_tunnel_ad_url ( ) if not tunnel_ad_url : return ( "Tunnel server appears to be down." ) cmd = '%s -subdomain=%s -config=%s -log=stdout %s 2>&1 > server.log' % ( self . tunnel_server , tunnel_ad_url , self . tunnel_config , self . local_port ) self . tunnel = subprocess . Popen ( cmd , shell = True ) self . url = '%s.%s' % ( tunnel_ad_url , self . tunnel_host ) self . full_url = 'http://%s.%s:%s' % ( tunnel_ad_url , self . tunnel_host , self . tunnel_port ) self . is_open = True print "Tunnel URL: %s" % self . full_url print "Hint: In OSX, you can open a terminal link using cmd + click"
def visit_BoolOp ( self , node : AST , dfltChaining : bool = True ) -> str : """Return ` node ` s operator and operands as inlined expression ."""
op = node . op with self . op_man ( op ) : src = self . visit ( op ) . join ( [ self . visit ( node . values [ 0 ] ) ] + [ self . visit ( val , dfltChaining = False ) for val in node . values [ 1 : ] ] ) return self . wrap_expr ( src , dfltChaining )
def _set_fcoe ( self , v , load = False ) : """Setter method for fcoe , mapped from YANG variable / interface / fcoe ( list ) If this variable is read - only ( config : false ) in the source YANG file , then _ set _ fcoe is considered as a private method . Backends looking to populate this variable should do so via calling thisObj . _ set _ fcoe ( ) directly . YANG Description : The list of FCoE interfaces . Each row contains FCoE interface name and its status ."""
if hasattr ( v , "_utype" ) : v = v . _utype ( v ) try : t = YANGDynClass ( v , base = YANGListType ( "fcoe_interface_name" , fcoe . fcoe , yang_name = "fcoe" , rest_name = "Fcoe" , parent = self , is_container = 'list' , user_ordered = False , path_helper = self . _path_helper , yang_keys = 'fcoe-interface-name' , extensions = { u'tailf-common' : { u'info' : u'The list of FCoE Logical interfaces' , u'cli-no-key-completion' : None , u'alt-name' : u'Fcoe' , u'sort-priority' : u'RUNNCFG_LEVEL_INTERFACE_TYPE_LOGICAL' , u'cli-custom-range-actionpoint' : u'FcoeRangeCliActionpoint' , u'cli-custom-range-enumerator' : u'FcoeRangeCliActionpoint' , u'display-when' : u'/vcsmode/vcs-mode = "true"' , u'cli-full-command' : None , u'callpoint' : u'fcoe_interface_cp' } } ) , is_container = 'list' , yang_name = "fcoe" , rest_name = "Fcoe" , parent = self , path_helper = self . _path_helper , extmethods = self . _extmethods , register_paths = True , extensions = { u'tailf-common' : { u'info' : u'The list of FCoE Logical interfaces' , u'cli-no-key-completion' : None , u'alt-name' : u'Fcoe' , u'sort-priority' : u'RUNNCFG_LEVEL_INTERFACE_TYPE_LOGICAL' , u'cli-custom-range-actionpoint' : u'FcoeRangeCliActionpoint' , u'cli-custom-range-enumerator' : u'FcoeRangeCliActionpoint' , u'display-when' : u'/vcsmode/vcs-mode = "true"' , u'cli-full-command' : None , u'callpoint' : u'fcoe_interface_cp' } } , namespace = 'urn:brocade.com:mgmt:brocade-fcoe' , defining_module = 'brocade-fcoe' , yang_type = 'list' , is_config = True ) except ( TypeError , ValueError ) : raise ValueError ( { 'error-string' : """fcoe must be of a type compatible with list""" , 'defined-type' : "list" , 'generated-type' : """YANGDynClass(base=YANGListType("fcoe_interface_name",fcoe.fcoe, yang_name="fcoe", rest_name="Fcoe", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='fcoe-interface-name', extensions={u'tailf-common': {u'info': u'The list of FCoE Logical interfaces', u'cli-no-key-completion': None, u'alt-name': u'Fcoe', u'sort-priority': u'RUNNCFG_LEVEL_INTERFACE_TYPE_LOGICAL', u'cli-custom-range-actionpoint': u'FcoeRangeCliActionpoint', u'cli-custom-range-enumerator': u'FcoeRangeCliActionpoint', u'display-when': u'/vcsmode/vcs-mode = "true"', u'cli-full-command': None, u'callpoint': u'fcoe_interface_cp'}}), is_container='list', yang_name="fcoe", rest_name="Fcoe", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'The list of FCoE Logical interfaces', u'cli-no-key-completion': None, u'alt-name': u'Fcoe', u'sort-priority': u'RUNNCFG_LEVEL_INTERFACE_TYPE_LOGICAL', u'cli-custom-range-actionpoint': u'FcoeRangeCliActionpoint', u'cli-custom-range-enumerator': u'FcoeRangeCliActionpoint', u'display-when': u'/vcsmode/vcs-mode = "true"', u'cli-full-command': None, u'callpoint': u'fcoe_interface_cp'}}, namespace='urn:brocade.com:mgmt:brocade-fcoe', defining_module='brocade-fcoe', yang_type='list', is_config=True)""" , } ) self . __fcoe = t if hasattr ( self , '_set' ) : self . _set ( )
def compute_signature ( self , uri , params , utf = PY3 ) : """Compute the signature for a given request : param uri : full URI that Twilio requested on your server : param params : post vars that Twilio sent with the request : param utf : whether return should be bytestring or unicode ( python3) : returns : The computed signature"""
s = uri if len ( params ) > 0 : for k , v in sorted ( params . items ( ) ) : s += k + v # compute signature and compare signatures mac = hmac . new ( self . token , s . encode ( "utf-8" ) , sha1 ) computed = base64 . b64encode ( mac . digest ( ) ) if utf : computed = computed . decode ( 'utf-8' ) return computed . strip ( )
def validate ( cls , obj , raiseException = False , complainUnrecognized = False ) : """Check if the object satisfies this behavior ' s requirements . @ param obj : The L { ContentLine < base . ContentLine > } or L { Component < base . Component > } to be validated . @ param raiseException : If True , raise a L { base . ValidateError } on validation failure . Otherwise return a boolean . @ param complainUnrecognized : If True , fail to validate if an uncrecognized parameter or child is found . Otherwise log the lack of recognition ."""
if not cls . allowGroup and obj . group is not None : err = "{0} has a group, but this object doesn't support groups" . format ( obj ) raise base . VObjectError ( err ) if isinstance ( obj , base . ContentLine ) : return cls . lineValidate ( obj , raiseException , complainUnrecognized ) elif isinstance ( obj , base . Component ) : count = { } for child in obj . getChildren ( ) : if not child . validate ( raiseException , complainUnrecognized ) : return False name = child . name . upper ( ) count [ name ] = count . get ( name , 0 ) + 1 for key , val in cls . knownChildren . items ( ) : if count . get ( key , 0 ) < val [ 0 ] : if raiseException : m = "{0} components must contain at least {1} {2}" raise base . ValidateError ( m . format ( cls . name , val [ 0 ] , key ) ) return False if val [ 1 ] and count . get ( key , 0 ) > val [ 1 ] : if raiseException : m = "{0} components cannot contain more than {1} {2}" raise base . ValidateError ( m . format ( cls . name , val [ 1 ] , key ) ) return False return True else : err = "{0} is not a Component or Contentline" . format ( obj ) raise base . VObjectError ( err )
def organize ( dirs , config , run_info_yaml , sample_names = None , is_cwl = False , integrations = None ) : """Organize run information from a passed YAML file or the Galaxy API . Creates the high level structure used for subsequent processing . sample _ names is a list of samples to include from the overall file , for cases where we are running multiple pipelines from the same configuration file ."""
from bcbio . pipeline import qcsummary if integrations is None : integrations = { } logger . info ( "Using input YAML configuration: %s" % run_info_yaml ) assert run_info_yaml and os . path . exists ( run_info_yaml ) , "Did not find input sample YAML file: %s" % run_info_yaml run_details = _run_info_from_yaml ( dirs , run_info_yaml , config , sample_names , is_cwl = is_cwl , integrations = integrations ) remote_retriever = None for iname , retriever in integrations . items ( ) : if iname in config : run_details = retriever . add_remotes ( run_details , config [ iname ] ) remote_retriever = retriever out = [ ] for item in run_details : item [ "dirs" ] = dirs if "name" not in item : item [ "name" ] = [ "" , item [ "description" ] ] elif isinstance ( item [ "name" ] , six . string_types ) : description = "%s-%s" % ( item [ "name" ] , clean_name ( item [ "description" ] ) ) item [ "name" ] = [ item [ "name" ] , description ] item [ "description" ] = description # add algorithm details to configuration , avoid double specification item [ "resources" ] = _add_remote_resources ( item [ "resources" ] ) item [ "config" ] = config_utils . update_w_custom ( config , item ) item . pop ( "algorithm" , None ) item = add_reference_resources ( item , remote_retriever ) item [ "config" ] [ "algorithm" ] [ "qc" ] = qcsummary . get_qc_tools ( item ) item [ "config" ] [ "algorithm" ] [ "vcfanno" ] = vcfanno . find_annotations ( item , remote_retriever ) # Create temporary directories and make absolute , expanding environmental variables tmp_dir = tz . get_in ( [ "config" , "resources" , "tmp" , "dir" ] , item ) if tmp_dir : # if no environmental variables , make and normalize the directory # otherwise we normalize later in distributed . transaction : if os . path . expandvars ( tmp_dir ) == tmp_dir : tmp_dir = utils . safe_makedir ( os . path . expandvars ( tmp_dir ) ) tmp_dir = genome . abs_file_paths ( tmp_dir , do_download = not integrations ) item [ "config" ] [ "resources" ] [ "tmp" ] [ "dir" ] = tmp_dir out . append ( item ) out = _add_provenance ( out , dirs , config , not is_cwl ) return out
def initialize ( self ) : """initialize the object"""
self . network_status = self . get_network_status ( ) self . name = self . network_status . get ( 'network_name' , 'Unknown' ) self . location_info = self . get_location_info ( ) self . device_info = self . get_device_info ( ) self . device_id = ( self . device_info . get ( 'device_id' ) if self . device_info else "Unknown" ) self . initialize_socket ( ) self . initialize_worker ( ) self . initialize_zones ( )
def summarize_tensors ( tensor_dict , tag = None ) : """Summarize the tensors . Args : tensor _ dict : a dictionary of tensors . tag : name scope of the summary ; defaults to tensors / ."""
if tag is None : tag = "tensors/" for t_name in list ( tensor_dict ) : t = tensor_dict [ t_name ] tf . summary . histogram ( tag + t_name , t )
def check_url ( aggregate ) : """Helper function waiting for URL queue ."""
while True : try : aggregate . urlqueue . join ( timeout = 30 ) break except urlqueue . Timeout : # Cleanup threads every 30 seconds aggregate . remove_stopped_threads ( ) if not any ( aggregate . get_check_threads ( ) ) : break
def supports ( cls , template_file = None ) : """: return : Whether the engine can process given template file or not ."""
if anytemplate . compat . IS_PYTHON_3 : cls . _priority = 99 return False # Always as it ' s not ported to python 3. return super ( Engine , cls ) . supports ( template_file = template_file )
def addItem ( self , title , link , description , date , append = True ) : """Insert an item ."""
item = self . rss . createElement ( 'item' ) self . addElement ( item , 'title' , title ) self . addElement ( item , 'link' , link ) self . addElement ( item , 'description' , description ) self . addElement ( item , 'guid' , link ) self . addElement ( item , 'pubDate' , date ) if append : self . channel . appendChild ( item ) else : elems = self . rss . getElementsByTagName ( 'item' ) if elems : self . channel . insertBefore ( item , elems [ 0 ] ) else : self . channel . appendChild ( item )