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def addRule ( self , doc , func , _preprocess = True ) : """Add a grammar rules to _ self . rules _ , _ self . rule2func _ , and _ self . rule2name _ Comments , lines starting with # and blank lines are stripped from doc . We also allow limited form of * and + when there it is of the RHS has a single item , e . g . stmts : : = stmt +"""
fn = func # remove blanks lines and comment lines , e . g . lines starting with " # " doc = os . linesep . join ( [ s for s in doc . splitlines ( ) if s and not re . match ( "^\s*#" , s ) ] ) rules = doc . split ( ) index = [ ] for i in range ( len ( rules ) ) : if rules [ i ] == '::=' : index . append ( i - 1 ) index . append ( len ( rules ) ) for i in range ( len ( index ) - 1 ) : lhs = rules [ index [ i ] ] rhs = rules [ index [ i ] + 2 : index [ i + 1 ] ] rule = ( lhs , tuple ( rhs ) ) if _preprocess : rule , fn = self . preprocess ( rule , func ) # Handle a stripped - down form of * , + , and ? : # allow only one nonterminal on the right - hand side if len ( rule [ 1 ] ) == 1 : if rule [ 1 ] [ 0 ] == rule [ 0 ] : raise TypeError ( "Complete recursive rule %s" % rule2str ( rule ) ) repeat = rule [ 1 ] [ - 1 ] [ - 1 ] if repeat in ( '*' , '+' , '?' ) : nt = rule [ 1 ] [ - 1 ] [ : - 1 ] if repeat == '?' : new_rule_pair = [ rule [ 0 ] , list ( ( nt , ) ) ] self . optional_nt . add ( rule [ 0 ] ) else : self . list_like_nt . add ( rule [ 0 ] ) new_rule_pair = [ rule [ 0 ] , [ rule [ 0 ] ] + list ( ( nt , ) ) ] new_rule = rule2str ( new_rule_pair ) self . addRule ( new_rule , func , _preprocess ) if repeat == '+' : second_rule_pair = ( lhs , ( nt , ) ) else : second_rule_pair = ( lhs , tuple ( ) ) new_rule = rule2str ( second_rule_pair ) self . addRule ( new_rule , func , _preprocess ) continue if lhs in self . rules : if rule in self . rules [ lhs ] : if 'dups' in self . debug and self . debug [ 'dups' ] : self . duplicate_rule ( rule ) continue self . rules [ lhs ] . append ( rule ) else : self . rules [ lhs ] = [ rule ] self . rule2func [ rule ] = fn self . rule2name [ rule ] = func . __name__ [ 2 : ] self . ruleschanged = True # Note : In empty rules , i . e . len ( rule [ 1 ] = = 0 , we don ' t # call reductions on explicitly . Instead it is computed # implicitly . if self . profile_info is not None and len ( rule [ 1 ] ) > 0 : rule_str = self . reduce_string ( rule ) if rule_str not in self . profile_info : self . profile_info [ rule_str ] = 0 pass return
def prior ( self , samples ) : """priori distribution Parameters samples : list a collection of sample , it ' s a ( NUM _ OF _ INSTANCE * NUM _ OF _ FUNCTIONS ) matrix , representing { { w11 , w12 , . . . , w1k } , { w21 , w22 , . . . w2k } , . . . { wk1 , wk2 , . . . , wkk } } Returns float priori distribution"""
ret = np . ones ( NUM_OF_INSTANCE ) for i in range ( NUM_OF_INSTANCE ) : for j in range ( self . effective_model_num ) : if not samples [ i ] [ j ] > 0 : ret [ i ] = 0 if self . f_comb ( 1 , samples [ i ] ) >= self . f_comb ( self . target_pos , samples [ i ] ) : ret [ i ] = 0 return ret
def list_images ( img_dpath_ , ignore_list = [ ] , recursive = False , fullpath = False , full = None , sort = True ) : r"""Returns a list of images in a directory . By default returns relative paths . TODO : rename to ls _ images TODO : Change all instances of fullpath to full Args : img _ dpath _ ( str ) : ignore _ list ( list ) : ( default = [ ] ) recursive ( bool ) : ( default = False ) fullpath ( bool ) : ( default = False ) full ( None ) : ( default = None ) sort ( bool ) : ( default = True ) Returns : list : gname _ list CommandLine : python - m utool . util _ path - - exec - list _ images Example : > > > # DISABLE _ DOCTEST > > > from utool . util _ path import * # NOQA > > > img _ dpath _ = ' ? ' > > > ignore _ list = [ ] > > > recursive = False > > > fullpath = False > > > full = None > > > sort = True > > > gname _ list = list _ images ( img _ dpath _ , ignore _ list , recursive , > > > fullpath , full , sort ) > > > result = ( ' gname _ list = % s ' % ( str ( gname _ list ) , ) ) > > > print ( result )"""
# if not QUIET : # print ( ignore _ list ) if full is not None : fullpath = fullpath or full img_dpath_ = util_str . ensure_unicode ( img_dpath_ ) img_dpath = realpath ( img_dpath_ ) ignore_set = set ( ignore_list ) gname_list_ = [ ] assertpath ( img_dpath ) # Get all the files in a directory recursively true_imgpath = truepath ( img_dpath ) for root , dlist , flist in os . walk ( true_imgpath ) : root = util_str . ensure_unicode ( root ) rel_dpath = relpath ( root , img_dpath ) # Ignore directories if any ( [ dname in ignore_set for dname in dirsplit ( rel_dpath ) ] ) : continue for fname in iter ( flist ) : fname = util_str . ensure_unicode ( fname ) gname = join ( rel_dpath , fname ) . replace ( '\\' , '/' ) if gname . startswith ( './' ) : gname = gname [ 2 : ] if fpath_has_imgext ( gname ) : # Ignore Files if gname in ignore_set : continue if fullpath : gpath = join ( img_dpath , gname ) gname_list_ . append ( gpath ) else : gname_list_ . append ( gname ) if not recursive : break if sort : gname_list = sorted ( gname_list_ ) return gname_list
def data_files ( self ) : """Returns a python list of all ( sharded ) data subset files . Returns : python list of all ( sharded ) data set files . Raises : ValueError : if there are not data _ files matching the subset ."""
tf_record_pattern = os . path . join ( FLAGS . data_dir , '%s-*' % self . subset ) data_files = tf . gfile . Glob ( tf_record_pattern ) if not data_files : print ( 'No files found for dataset %s/%s at %s' % ( self . name , self . subset , FLAGS . data_dir ) ) self . download_message ( ) exit ( - 1 ) return data_files
def _make_class_unpicklable ( cls ) : """Make the given class un - picklable ."""
def _break_on_call_reduce ( self ) : raise TypeError ( '%r cannot be pickled' % self ) cls . __reduce__ = _break_on_call_reduce cls . __module__ = '<unknown>'
def list_permissions ( self , group_name = None , resource = None , url_prefix = None , auth = None , session = None , send_opts = None ) : """List the permission sets for the logged in user Optionally filter by resource or group . Args : group _ name ( string ) : Name of group to filter on resource ( intern . resource . boss . BossResource ) : Identifies which data model object to filter on url _ prefix ( string ) : Protocol + host such as https : / / api . theboss . io auth ( string ) : Token to send in the request header . session ( requests . Session ) : HTTP session to use for request . send _ opts ( dictionary ) : Additional arguments to pass to session . send ( ) . Returns : ( list [ dict ] ) : List of dictionaries of permission sets"""
filter_params = { } if group_name : filter_params [ "group" ] = group_name if resource : filter_params . update ( resource . get_dict_route ( ) ) req = self . get_permission_request ( 'GET' , 'application/json' , url_prefix , auth , query_params = filter_params ) prep = session . prepare_request ( req ) resp = session . send ( prep , ** send_opts ) if resp . status_code != 200 : msg = "Failed to get permission sets. " if group_name : msg = "{} Group: {}" . format ( msg , group_name ) if resource : msg = "{} Resource: {}" . format ( msg , resource . name ) msg = '{}, got HTTP response: ({}) - {}' . format ( msg , resp . status_code , resp . text ) raise HTTPError ( msg , request = req , response = resp ) else : return resp . json ( ) [ "permission-sets" ]
def Overlay_setInspectMode ( self , mode , ** kwargs ) : """Function path : Overlay . setInspectMode Domain : Overlay Method name : setInspectMode Parameters : Required arguments : ' mode ' ( type : InspectMode ) - > Set an inspection mode . Optional arguments : ' highlightConfig ' ( type : HighlightConfig ) - > A descriptor for the highlight appearance of hovered - over nodes . May be omitted if < code > enabled = = false < / code > . No return value . Description : Enters the ' inspect ' mode . In this mode , elements that user is hovering over are highlighted . Backend then generates ' inspectNodeRequested ' event upon element selection ."""
expected = [ 'highlightConfig' ] passed_keys = list ( kwargs . keys ( ) ) assert all ( [ ( key in expected ) for key in passed_keys ] ) , "Allowed kwargs are ['highlightConfig']. Passed kwargs: %s" % passed_keys subdom_funcs = self . synchronous_command ( 'Overlay.setInspectMode' , mode = mode , ** kwargs ) return subdom_funcs
def read_blocking ( self ) : """Same as read , except blocks untill data is available to be read ."""
while True : data = self . _read ( ) if data != None : break return self . _parse_message ( data )
def update_frame ( self , key , ranges = None , plot = None , element = None ) : """Updates an existing plot with data corresponding to the key ."""
reused = isinstance ( self . hmap , DynamicMap ) and ( self . overlaid or self . batched ) if not reused and element is None : element = self . _get_frame ( key ) elif element is not None : self . current_key = key self . current_frame = element renderer = self . handles . get ( 'glyph_renderer' , None ) glyph = self . handles . get ( 'glyph' , None ) visible = element is not None if hasattr ( renderer , 'visible' ) : renderer . visible = visible if hasattr ( glyph , 'visible' ) : glyph . visible = visible if ( ( self . batched and not element ) or element is None or ( not self . dynamic and self . static ) or ( self . streaming and self . streaming [ 0 ] . data is self . current_frame . data and not self . streaming [ 0 ] . _triggering ) ) : return if self . batched : style_element = element . last max_cycles = None else : style_element = element max_cycles = self . style . _max_cycles style = self . lookup_options ( style_element , 'style' ) self . style = style . max_cycles ( max_cycles ) if max_cycles else style ranges = self . compute_ranges ( self . hmap , key , ranges ) self . param . set_param ( ** self . lookup_options ( style_element , 'plot' ) . options ) ranges = util . match_spec ( style_element , ranges ) self . current_ranges = ranges plot = self . handles [ 'plot' ] if not self . overlaid : self . _update_ranges ( style_element , ranges ) self . _update_plot ( key , plot , style_element ) self . _set_active_tools ( plot ) if 'hover' in self . handles and 'hv_created' in self . handles [ 'hover' ] . tags : self . _update_hover ( element ) self . _update_glyphs ( element , ranges , self . style [ self . cyclic_index ] ) self . _execute_hooks ( element )
def step_note_that ( context , remark ) : """Used as generic step that provides an additional remark / hint and enhance the readability / understanding without performing any check . . . code - block : : gherkin Given that today is " April 1st " But note that " April 1st is Fools day ( and beware ) " """
log = getattr ( context , "log" , None ) if log : log . info ( u"NOTE: %s;" % remark )
def wait_for_responses ( self , client ) : """Waits for all responses to come back and resolves the eventual results ."""
assert_open ( self ) if self . has_pending_requests : raise RuntimeError ( 'Cannot wait for responses if there are ' 'pending requests outstanding. You need ' 'to wait for pending requests to be sent ' 'first.' ) pending = self . pending_responses self . pending_responses = [ ] for command_name , options , promise in pending : value = client . parse_response ( self . connection , command_name , ** options ) promise . resolve ( value )
def WindowsSdkVersion ( self ) : """Microsoft Windows SDK versions for specified MSVC + + version ."""
if self . vc_ver <= 9.0 : return ( '7.0' , '6.1' , '6.0a' ) elif self . vc_ver == 10.0 : return ( '7.1' , '7.0a' ) elif self . vc_ver == 11.0 : return ( '8.0' , '8.0a' ) elif self . vc_ver == 12.0 : return ( '8.1' , '8.1a' ) elif self . vc_ver >= 14.0 : return ( '10.0' , '8.1' )
def qos_map_cos_traffic_class_cos4 ( self , ** kwargs ) : """Auto Generated Code"""
config = ET . Element ( "config" ) qos = ET . SubElement ( config , "qos" , xmlns = "urn:brocade.com:mgmt:brocade-qos" ) map = ET . SubElement ( qos , "map" ) cos_traffic_class = ET . SubElement ( map , "cos-traffic-class" ) name_key = ET . SubElement ( cos_traffic_class , "name" ) name_key . text = kwargs . pop ( 'name' ) cos4 = ET . SubElement ( cos_traffic_class , "cos4" ) cos4 . text = kwargs . pop ( 'cos4' ) callback = kwargs . pop ( 'callback' , self . _callback ) return callback ( config )
def _schedule_pending_unlocked ( self , state ) : """Consider the pending transfers for a stream , pumping new chunks while the unacknowledged byte count is below : attr : ` window _ size _ bytes ` . Must be called with the FileStreamState lock held . : param FileStreamState state : Stream to schedule chunks for ."""
while state . jobs and state . unacked < self . window_size_bytes : sender , fp = state . jobs [ 0 ] s = fp . read ( self . IO_SIZE ) if s : state . unacked += len ( s ) sender . send ( mitogen . core . Blob ( s ) ) else : # File is done . Cause the target ' s receive loop to exit by # closing the sender , close the file , and remove the job entry . sender . close ( ) fp . close ( ) state . jobs . pop ( 0 )
def search_url ( self , searchterm ) : """Search for URLs : type searchterm : str : rtype : list"""
return self . __search ( type_attribute = self . __mispurltypes ( ) , value = searchterm )
def dots_to_empty_cells ( config , tsv_fpath ) : """Put dots instead of empty cells in order to view TSV with column - t"""
def proc_line ( l , i ) : while '\t\t' in l : l = l . replace ( '\t\t' , '\t.\t' ) return l return iterate_file ( config , tsv_fpath , proc_line , suffix = 'dots' )
def deprecate_and_include ( parser , token ) : """Raises a deprecation warning about using the first argument . The remaining arguments are passed to an ` ` { % include % } ` ` tag . Usage : : { % deprecate _ and _ include " old _ template . html " " new _ template . html " % } In order to avoid re - implementing { % include % } so as to resolve variables , this tag currently only works with literal template path strings ."""
split_contents = token . split_contents ( ) current_template = split_contents [ 1 ] new_template = split_contents [ 2 ] if settings . DEBUG : warnings . simplefilter ( 'always' , DeprecationWarning ) warnings . warn ( "The %s template is deprecated; Use %s instead." % ( current_template , new_template ) , DeprecationWarning , stacklevel = 2 ) new_contents = [ split_contents [ 0 ] ] + split_contents [ 2 : ] include_token = Token ( token . token_type , " " . join ( new_contents ) ) return do_include ( parser , include_token )
def exchange_partition ( self , partitionSpecs , source_db , source_table_name , dest_db , dest_table_name ) : """Parameters : - partitionSpecs - source _ db - source _ table _ name - dest _ db - dest _ table _ name"""
self . send_exchange_partition ( partitionSpecs , source_db , source_table_name , dest_db , dest_table_name ) return self . recv_exchange_partition ( )
def phi_from_spinx_spiny ( spinx , spiny ) : """Returns the angle between the x - component axis and the in - plane spin ."""
phi = numpy . arctan2 ( spiny , spinx ) return phi % ( 2 * numpy . pi )
def list_cron_job_for_all_namespaces ( self , ** kwargs ) : """list or watch objects of kind CronJob This method makes a synchronous HTTP request by default . To make an asynchronous HTTP request , please pass async _ req = True > > > thread = api . list _ cron _ job _ for _ all _ namespaces ( async _ req = True ) > > > result = thread . get ( ) : param async _ req bool : param str _ continue : The continue option should be set when retrieving more results from the server . Since this value is server defined , clients may only use the continue value from a previous query result with identical query parameters ( except for the value of continue ) and the server may reject a continue value it does not recognize . If the specified continue value is no longer valid whether due to expiration ( generally five to fifteen minutes ) or a configuration change on the server , the server will respond with a 410 ResourceExpired error together with a continue token . If the client needs a consistent list , it must restart their list without the continue field . Otherwise , the client may send another list request with the token received with the 410 error , the server will respond with a list starting from the next key , but from the latest snapshot , which is inconsistent from the previous list results - objects that are created , modified , or deleted after the first list request will be included in the response , as long as their keys are after the \" next key \" . This field is not supported when watch is true . Clients may start a watch from the last resourceVersion value returned by the server and not miss any modifications . : param str field _ selector : A selector to restrict the list of returned objects by their fields . Defaults to everything . : param str label _ selector : A selector to restrict the list of returned objects by their labels . Defaults to everything . : param int limit : limit is a maximum number of responses to return for a list call . If more items exist , the server will set the ` continue ` field on the list metadata to a value that can be used with the same initial query to retrieve the next set of results . Setting a limit may return fewer than the requested amount of items ( up to zero items ) in the event all requested objects are filtered out and clients should only use the presence of the continue field to determine whether more results are available . Servers may choose not to support the limit argument and will return all of the available results . If limit is specified and the continue field is empty , clients may assume that no more results are available . This field is not supported if watch is true . The server guarantees that the objects returned when using continue will be identical to issuing a single list call without a limit - that is , no objects created , modified , or deleted after the first request is issued will be included in any subsequent continued requests . This is sometimes referred to as a consistent snapshot , and ensures that a client that is using limit to receive smaller chunks of a very large result can ensure they see all possible objects . If objects are updated during a chunked list the version of the object that was present at the time the first list result was calculated is returned . : param str pretty : If ' true ' , then the output is pretty printed . : param str resource _ version : When specified with a watch call , shows changes that occur after that particular version of a resource . Defaults to changes from the beginning of history . When specified for list : - if unset , then the result is returned from remote storage based on quorum - read flag ; - if it ' s 0 , then we simply return what we currently have in cache , no guarantee ; - if set to non zero , then the result is at least as fresh as given rv . : param int timeout _ seconds : Timeout for the list / watch call . This limits the duration of the call , regardless of any activity or inactivity . : param bool watch : Watch for changes to the described resources and return them as a stream of add , update , and remove notifications . Specify resourceVersion . : return : V2alpha1CronJobList If the method is called asynchronously , returns the request thread ."""
kwargs [ '_return_http_data_only' ] = True if kwargs . get ( 'async_req' ) : return self . list_cron_job_for_all_namespaces_with_http_info ( ** kwargs ) else : ( data ) = self . list_cron_job_for_all_namespaces_with_http_info ( ** kwargs ) return data
def _remove_duplicates ( self ) : """Remove every maximal rectangle contained by another one ."""
contained = set ( ) for m1 , m2 in itertools . combinations ( self . _max_rects , 2 ) : if m1 . contains ( m2 ) : contained . add ( m2 ) elif m2 . contains ( m1 ) : contained . add ( m1 ) # Remove from max _ rects self . _max_rects = [ m for m in self . _max_rects if m not in contained ]
def transform ( self , X ) : """Return this basis applied to X . Parameters X : ndarray of shape ( N , d ) of observations where N is the number of samples , and d is the dimensionality of X . Returns ndarray : of shape ( N , d + 1 ) , or ( N , d ) depending on onescol ."""
N , D = X . shape return np . hstack ( ( np . ones ( ( N , 1 ) ) , X ) ) if self . onescol else X
def project ( self , projected_meta = None , new_attr_dict = None , all_but_meta = None , projected_regs = None , new_field_dict = None , all_but_regs = None ) : """* Wrapper of * ` ` PROJECT ` ` The PROJECT operator creates , from an existing dataset , a new dataset with all the samples ( with their regions and region values ) in the input one , but keeping for each sample in the input dataset only those metadata and / or region attributes expressed in the operator parameter list . Region coordinates and values of the remaining metadata and region attributes remain equal to those in the input dataset . Differently from the SELECT operator , PROJECT allows to : * Remove existing metadata and / or region attributes from a dataset ; * Create new metadata and / or region attributes to be added to the result . : param projected _ meta : list of metadata attributes to project on : param new _ attr _ dict : an optional dictionary of the form { ' new _ meta _ 1 ' : function1, ' new _ meta _ 2 ' : function2 , . . . } in which every function computes the new metadata attribute based on the values of the others : param all _ but _ meta : list of metadata attributes that must be excluded from the projection : param projected _ regs : list of the region fields to select : param new _ field _ dict : an optional dictionary of the form { ' new _ field _ 1 ' : function1 , ' new _ field _ 2 ' : function2 , . . . } in which every function computes the new region field based on the values of the others : param all _ but _ regs : list of region fields that must be excluded from the projection : return : a new GMQLDataset"""
projected_meta_exists = False if isinstance ( projected_meta , list ) and all ( [ isinstance ( x , str ) for x in projected_meta ] ) : projected_meta = Some ( projected_meta ) projected_meta_exists = True elif projected_meta is None : projected_meta = none ( ) else : raise TypeError ( "projected_meta must be a list of strings or None." " {} was provided" . format ( type ( projected_meta ) ) ) if isinstance ( new_attr_dict , dict ) : meta_ext = [ ] expBuild = self . pmg . getNewExpressionBuilder ( self . __index ) for k in new_attr_dict . keys ( ) : item = new_attr_dict [ k ] if isinstance ( k , str ) : if isinstance ( item , MetaField ) : me = expBuild . createMetaExtension ( k , item . getMetaExpression ( ) ) elif isinstance ( item , int ) : me = expBuild . createMetaExtension ( k , expBuild . getMEType ( "int" , str ( item ) ) ) elif isinstance ( item , str ) : me = expBuild . createMetaExtension ( k , expBuild . getMEType ( "string" , item ) ) elif isinstance ( item , float ) : me = expBuild . createMetaExtension ( k , expBuild . getMEType ( "float" , str ( item ) ) ) else : raise TypeError ( "Type {} of item of new_attr_dict is not valid" . format ( type ( item ) ) ) meta_ext . append ( me ) else : raise TypeError ( "The key of new_attr_dict must be a string. " "{} was provided" . format ( type ( k ) ) ) meta_ext = Some ( meta_ext ) elif new_attr_dict is None : meta_ext = none ( ) else : raise TypeError ( "new_attr_dict must be a dictionary." " {} was provided" . format ( type ( new_attr_dict ) ) ) if isinstance ( all_but_meta , list ) and all ( [ isinstance ( x , str ) for x in all_but_meta ] ) : if not projected_meta_exists : all_but_meta = Some ( all_but_meta ) all_but_value = True else : raise ValueError ( "all_but_meta and projected_meta are mutually exclusive" ) elif all_but_meta is None : all_but_meta = none ( ) all_but_value = False else : raise TypeError ( "all_but_meta must be a list of strings." " {} was provided" . format ( type ( all_but_meta ) ) ) projected_meta = all_but_meta if all_but_value else projected_meta projected_regs_exists = False if isinstance ( projected_regs , list ) and all ( [ isinstance ( x , str ) for x in projected_regs ] ) : projected_regs = Some ( projected_regs ) projected_regs_exists = True elif projected_regs is None : projected_regs = none ( ) else : raise TypeError ( "projected_regs must be a list of strings or None." " {} was provided" . format ( type ( projected_regs ) ) ) if isinstance ( new_field_dict , dict ) : regs_ext = [ ] expBuild = self . pmg . getNewExpressionBuilder ( self . __index ) for k in new_field_dict . keys ( ) : item = new_field_dict [ k ] if isinstance ( k , str ) : if isinstance ( item , RegField ) : re = expBuild . createRegionExtension ( k , item . getRegionExpression ( ) ) elif isinstance ( item , MetaField ) : re = expBuild . createRegionExtension ( k , item . reMetaNode ) elif isinstance ( item , int ) : re = expBuild . createRegionExtension ( k , expBuild . getREType ( "float" , str ( item ) ) ) elif isinstance ( item , str ) : re = expBuild . createRegionExtension ( k , expBuild . getREType ( "string" , item ) ) elif isinstance ( item , float ) : re = expBuild . createRegionExtension ( k , expBuild . getREType ( "float" , str ( item ) ) ) else : raise TypeError ( "Type {} of item of new_field_dict is not valid" . format ( type ( item ) ) ) regs_ext . append ( re ) else : raise TypeError ( "The key of new_field_dict must be a string. " "{} was provided" . format ( type ( k ) ) ) regs_ext = Some ( regs_ext ) elif new_field_dict is None : regs_ext = none ( ) else : raise TypeError ( "new_field_dict must be a dictionary." " {} was provided" . format ( type ( new_field_dict ) ) ) if isinstance ( all_but_regs , list ) and all ( [ isinstance ( x , str ) for x in all_but_regs ] ) : if not projected_regs_exists : all_but_regs = Some ( all_but_regs ) else : raise ValueError ( "all_but_meta and projected_meta are mutually exclusive" ) elif all_but_regs is None : all_but_regs = none ( ) else : raise TypeError ( "all_but_regs must be a list of strings." " {} was provided" . format ( type ( all_but_regs ) ) ) new_index = self . opmng . project ( self . __index , projected_meta , meta_ext , all_but_value , projected_regs , all_but_regs , regs_ext ) return GMQLDataset ( index = new_index , location = self . location , local_sources = self . _local_sources , remote_sources = self . _remote_sources , meta_profile = self . meta_profile )
def cmd ( self , endpoints , cmd ) : """endpoints is [ ( host1 , port1 ) , ( host2 , port ) , . . . ]"""
replies = [ ] for ep in endpoints : try : replies . append ( self . _cmd ( ep , cmd ) ) except self . CmdFailed as ex : # if there ' s only 1 endpoint , give up . # if there ' s more , keep trying . if len ( endpoints ) == 1 : raise ex return "" . join ( replies )
def insert_from_segwizard ( self , fileobj , instruments , name , version = None , comment = None ) : """Parse the contents of the file object fileobj as a segwizard - format segment list , and insert the result as a new list of " active " segments into this LigolwSegments object . A new entry will be created in the segment _ definer table for the segment list , and instruments , name and comment are used to populate the entry ' s metadata . Note that the " valid " segments are left empty , nominally indicating that there are no periods of validity ."""
self . add ( LigolwSegmentList ( active = segmentsUtils . fromsegwizard ( fileobj , coltype = LIGOTimeGPS ) , instruments = instruments , name = name , version = version , comment = comment ) )
def move ( self , i , lat , lng , change_time = True ) : '''move a rally point'''
if i < 1 or i > self . rally_count ( ) : print ( "Invalid rally point number %u" % i ) self . rally_points [ i - 1 ] . lat = int ( lat * 1e7 ) self . rally_points [ i - 1 ] . lng = int ( lng * 1e7 ) if change_time : self . last_change = time . time ( )
def help ( self , print_output = True ) : """Calls the help RPC , which returns the list of RPC calls available . This RPC should normally be used in an interactive console environment where the output should be printed instead of returned . Otherwise , newlines will be escaped , which will make the output difficult to read . Args : print _ output : A bool for whether the output should be printed . Returns : A str containing the help output otherwise None if print _ output wasn ' t set ."""
help_text = self . _rpc ( 'help' ) if print_output : print ( help_text ) else : return help_text
def detect_ts ( df , max_anoms = 0.10 , direction = 'pos' , alpha = 0.05 , only_last = None , threshold = None , e_value = False , longterm = False , piecewise_median_period_weeks = 2 , plot = False , y_log = False , xlabel = '' , ylabel = 'count' , title = None , verbose = False ) : """Anomaly Detection Using Seasonal Hybrid ESD Test A technique for detecting anomalies in seasonal univariate time series where the input is a series of < timestamp , value > pairs . Args : x : Time series as a two column data frame where the first column consists of the timestamps and the second column consists of the observations . max _ anoms : Maximum number of anomalies that S - H - ESD will detect as a percentage of the data . direction : Directionality of the anomalies to be detected . Options are : ( ' pos ' | ' neg ' | ' both ' ) . alpha : The level of statistical significance with which to accept or reject anomalies . only _ last : Find and report anomalies only within the last day or hr in the time series . Options : ( None | ' day ' | ' hr ' ) threshold : Only report positive going anoms above the threshold specified . Options are : ( None | ' med _ max ' | ' p95 ' | ' p99 ' ) e _ value : Add an additional column to the anoms output containing the expected value . longterm : Increase anom detection efficacy for time series that are greater than a month . See Details below . piecewise _ median _ period _ weeks : The piecewise median time window as described in Vallis , Hochenbaum , and Kejariwal ( 2014 ) . Defaults to 2. plot : ( Currently unsupported ) A flag indicating if a plot with both the time series and the estimated anoms , indicated by circles , should also be returned . y _ log : Apply log scaling to the y - axis . This helps with viewing plots that have extremely large positive anomalies relative to the rest of the data . xlabel : X - axis label to be added to the output plot . ylabel : Y - axis label to be added to the output plot . Details ' longterm ' This option should be set when the input time series is longer than a month . The option enables the approach described in Vallis , Hochenbaum , and Kejariwal ( 2014 ) . ' threshold ' Filter all negative anomalies and those anomalies whose magnitude is smaller than one of the specified thresholds which include : the median of the daily max values ( med _ max ) , the 95th percentile of the daily max values ( p95 ) , and the 99th percentile of the daily max values ( p99 ) . ' title ' Title for the output plot . ' verbose ' Enable debug messages The returned value is a dictionary with the following components : anoms : Data frame containing timestamps , values , and optionally expected values . plot : A graphical object if plotting was requested by the user . The plot contains the estimated anomalies annotated on the input time series"""
if not isinstance ( df , DataFrame ) : raise ValueError ( "data must be a single data frame." ) else : if len ( df . columns ) != 2 or not df . iloc [ : , 1 ] . map ( np . isreal ) . all ( ) : raise ValueError ( ( "data must be a 2 column data.frame, with the" "first column being a set of timestamps, and " "the second coloumn being numeric values." ) ) if ( not ( df . dtypes [ 0 ] . type is np . datetime64 ) and not ( df . dtypes [ 0 ] . type is np . int64 ) ) : df = format_timestamp ( df ) if list ( df . columns . values ) != [ "timestamp" , "value" ] : df . columns = [ "timestamp" , "value" ] # Sanity check all input parameters if max_anoms > 0.49 : length = len ( df . value ) raise ValueError ( ( "max_anoms must be less than 50% of " "the data points (max_anoms =%f data_points =%s)." ) % ( round ( max_anoms * length , 0 ) , length ) ) if not direction in [ 'pos' , 'neg' , 'both' ] : raise ValueError ( "direction options are: pos | neg | both." ) if not ( 0.01 <= alpha or alpha <= 0.1 ) : if verbose : import warnings warnings . warn ( ( "alpha is the statistical signifigance, " "and is usually between 0.01 and 0.1" ) ) if only_last and not only_last in [ 'day' , 'hr' ] : raise ValueError ( "only_last must be either 'day' or 'hr'" ) if not threshold in [ None , 'med_max' , 'p95' , 'p99' ] : raise ValueError ( "threshold options are: None | med_max | p95 | p99" ) if not isinstance ( e_value , bool ) : raise ValueError ( "e_value must be a boolean" ) if not isinstance ( longterm , bool ) : raise ValueError ( "longterm must be a boolean" ) if piecewise_median_period_weeks < 2 : raise ValueError ( "piecewise_median_period_weeks must be at greater than 2 weeks" ) if not isinstance ( plot , bool ) : raise ValueError ( "plot must be a boolean" ) if not isinstance ( y_log , bool ) : raise ValueError ( "y_log must be a boolean" ) if not isinstance ( xlabel , string_types ) : raise ValueError ( "xlabel must be a string" ) if not isinstance ( ylabel , string_types ) : raise ValueError ( "ylabel must be a string" ) if title and not isinstance ( title , string_types ) : raise ValueError ( "title must be a string" ) if not title : title = '' else : title = title + " : " gran = get_gran ( df ) if gran == "day" : num_days_per_line = 7 if isinstance ( only_last , string_types ) and only_last == 'hr' : only_last = 'day' else : num_days_per_line = 1 if gran == 'sec' : df . timestamp = date_format ( df . timestamp , "%Y-%m-%d %H:%M:00" ) df = format_timestamp ( df . groupby ( 'timestamp' ) . aggregate ( np . sum ) ) # if the data is daily , then we need to bump # the period to weekly to get multiple examples gran_period = { 'min' : 1440 , 'hr' : 24 , 'day' : 7 } period = gran_period . get ( gran ) if not period : raise ValueError ( '%s granularity detected. This is currently not supported.' % gran ) num_obs = len ( df . value ) clamp = ( 1 / float ( num_obs ) ) if max_anoms < clamp : max_anoms = clamp if longterm : if gran == "day" : num_obs_in_period = period * piecewise_median_period_weeks + 1 num_days_in_period = 7 * piecewise_median_period_weeks + 1 else : num_obs_in_period = period * 7 * piecewise_median_period_weeks num_days_in_period = 7 * piecewise_median_period_weeks last_date = df . timestamp . iloc [ - 1 ] all_data = [ ] for j in range ( 0 , len ( df . timestamp ) , num_obs_in_period ) : start_date = df . timestamp . iloc [ j ] end_date = min ( start_date + datetime . timedelta ( days = num_days_in_period ) , df . timestamp . iloc [ - 1 ] ) # if there is at least 14 days left , subset it , # otherwise subset last _ date - 14days if ( end_date - start_date ) . days == num_days_in_period : sub_df = df [ ( df . timestamp >= start_date ) & ( df . timestamp < end_date ) ] else : sub_df = df [ ( df . timestamp > ( last_date - datetime . timedelta ( days = num_days_in_period ) ) ) & ( df . timestamp <= last_date ) ] all_data . append ( sub_df ) else : all_data = [ df ] all_anoms = DataFrame ( columns = [ 'timestamp' , 'value' ] ) seasonal_plus_trend = DataFrame ( columns = [ 'timestamp' , 'value' ] ) # Detect anomalies on all data ( either entire data in one - pass , # or in 2 week blocks if longterm = TRUE ) for i in range ( len ( all_data ) ) : directions = { 'pos' : Direction ( True , True ) , 'neg' : Direction ( True , False ) , 'both' : Direction ( False , True ) } anomaly_direction = directions [ direction ] # detect _ anoms actually performs the anomaly detection and # returns the results in a list containing the anomalies # as well as the decomposed components of the time series # for further analysis . s_h_esd_timestamps = detect_anoms ( all_data [ i ] , k = max_anoms , alpha = alpha , num_obs_per_period = period , use_decomp = True , one_tail = anomaly_direction . one_tail , upper_tail = anomaly_direction . upper_tail , verbose = verbose ) # store decomposed components in local variable and overwrite # s _ h _ esd _ timestamps to contain only the anom timestamps data_decomp = s_h_esd_timestamps [ 'stl' ] s_h_esd_timestamps = s_h_esd_timestamps [ 'anoms' ] # - - Step 3 : Use detected anomaly timestamps to extract the actual # anomalies ( timestamp and value ) from the data if s_h_esd_timestamps : anoms = all_data [ i ] [ all_data [ i ] . timestamp . isin ( s_h_esd_timestamps ) ] else : anoms = DataFrame ( columns = [ 'timestamp' , 'value' ] ) # Filter the anomalies using one of the thresholding functions if applicable if threshold : # Calculate daily max values periodic_maxes = df . groupby ( df . timestamp . map ( Timestamp . date ) ) . aggregate ( np . max ) . value # Calculate the threshold set by the user if threshold == 'med_max' : thresh = periodic_maxes . median ( ) elif threshold == 'p95' : thresh = periodic_maxes . quantile ( .95 ) elif threshold == 'p99' : thresh = periodic_maxes . quantile ( .99 ) # Remove any anoms below the threshold anoms = anoms [ anoms . value >= thresh ] all_anoms = all_anoms . append ( anoms ) seasonal_plus_trend = seasonal_plus_trend . append ( data_decomp ) # Cleanup potential duplicates try : all_anoms . drop_duplicates ( subset = [ 'timestamp' ] , inplace = True ) seasonal_plus_trend . drop_duplicates ( subset = [ 'timestamp' ] , inplace = True ) except TypeError : all_anoms . drop_duplicates ( cols = [ 'timestamp' ] , inplace = True ) seasonal_plus_trend . drop_duplicates ( cols = [ 'timestamp' ] , inplace = True ) # - - If only _ last was set by the user , # create subset of the data that represent the most recent day if only_last : start_date = df . timestamp . iloc [ - 1 ] - datetime . timedelta ( days = 7 ) start_anoms = df . timestamp . iloc [ - 1 ] - datetime . timedelta ( days = 1 ) if gran is "day" : breaks = 3 * 12 num_days_per_line = 7 else : if only_last == 'day' : breaks = 12 else : start_date = df . timestamp . iloc [ - 1 ] - datetime . timedelta ( days = 2 ) # truncate to days start_date = datetime . date ( start_date . year , start_date . month , start_date . day ) start_anoms = ( df . timestamp . iloc [ - 1 ] - datetime . timedelta ( hours = 1 ) ) breaks = 3 # subset the last days worth of data x_subset_single_day = df [ df . timestamp > start_anoms ] # When plotting anoms for the last day only # we only show the previous weeks data x_subset_week = df [ ( df . timestamp <= start_anoms ) & ( df . timestamp > start_date ) ] if len ( all_anoms ) > 0 : all_anoms = all_anoms [ all_anoms . timestamp >= x_subset_single_day . timestamp . iloc [ 0 ] ] num_obs = len ( x_subset_single_day . value ) # Calculate number of anomalies as a percentage anom_pct = ( len ( df . value ) / float ( num_obs ) ) * 100 if anom_pct == 0 : return { "anoms" : None , "plot" : None } # The original R implementation handles plotting here . # Plotting is currently not implemented in this version . # if plot : # plot _ something ( ) all_anoms . index = all_anoms . timestamp if e_value : d = { 'timestamp' : all_anoms . timestamp , 'anoms' : all_anoms . value , 'expected_value' : seasonal_plus_trend [ seasonal_plus_trend . timestamp . isin ( all_anoms . timestamp ) ] . value } else : d = { 'timestamp' : all_anoms . timestamp , 'anoms' : all_anoms . value } anoms = DataFrame ( d , index = d [ 'timestamp' ] . index ) return { 'anoms' : anoms , 'plot' : None }
def get_trees ( self , data , showerrors = False ) : # - > list : """returns a list of trees with valid guesses"""
if not all ( check ( self . _productionset . alphabet , [ x ] ) for x in data ) : raise ValueError ( "Unknown element in {}, alphabet:{}" . format ( str ( data ) , self . productionset . alphabet ) ) result = self . __recursive_parser ( self . _productionset . initialsymbol , data , self . _productionset . main_production , showerrors ) finalresult = [ ] for eresult in result : if eresult . left == 0 and eresult . right == len ( data ) and eresult not in finalresult : finalresult . append ( eresult ) return finalresult
def _getGlobals ( self , ** kwargs ) : """Return the globals dictionary for the formula calculation"""
# Default globals globs = { "__builtins__" : None , "all" : all , "any" : any , "bool" : bool , "chr" : chr , "cmp" : cmp , "complex" : complex , "divmod" : divmod , "enumerate" : enumerate , "float" : float , "format" : format , "frozenset" : frozenset , "hex" : hex , "int" : int , "len" : len , "list" : list , "long" : long , "math" : math , "max" : max , "min" : min , "oct" : oct , "ord" : ord , "pow" : pow , "range" : range , "reversed" : reversed , "round" : round , "str" : str , "sum" : sum , "tuple" : tuple , "xrange" : xrange , } # Update with keyword arguments globs . update ( kwargs ) # Update with additional Python libraries for imp in self . getPythonImports ( ) : mod = imp [ "module" ] func = imp [ "function" ] member = self . _getModuleMember ( mod , func ) if member is None : raise ImportError ( "Could not find member {} of module {}" . format ( func , mod ) ) globs [ func ] = member return globs
def rand_email ( ) : """Random email . Usage Example : : > > > rand _ email ( ) Z4Lljcbdw7m @ npa . net"""
name = random . choice ( string . ascii_letters ) + rand_str ( string . ascii_letters + string . digits , random . randint ( 4 , 14 ) ) domain = rand_str ( string . ascii_lowercase , random . randint ( 2 , 10 ) ) kind = random . choice ( _all_email_kinds ) return "%s@%s%s" % ( name , domain , kind )
def delete_collection_node ( self , ** kwargs ) : # noqa : E501 """delete _ collection _ node # noqa : E501 delete collection of Node # noqa : E501 This method makes a synchronous HTTP request by default . To make an asynchronous HTTP request , please pass async _ req = True > > > thread = api . delete _ collection _ node ( async _ req = True ) > > > result = thread . get ( ) : param async _ req bool : param bool include _ uninitialized : If true , partially initialized resources are included in the response . : param str pretty : If ' true ' , then the output is pretty printed . : param str _ continue : The continue option should be set when retrieving more results from the server . Since this value is server defined , clients may only use the continue value from a previous query result with identical query parameters ( except for the value of continue ) and the server may reject a continue value it does not recognize . If the specified continue value is no longer valid whether due to expiration ( generally five to fifteen minutes ) or a configuration change on the server , the server will respond with a 410 ResourceExpired error together with a continue token . If the client needs a consistent list , it must restart their list without the continue field . Otherwise , the client may send another list request with the token received with the 410 error , the server will respond with a list starting from the next key , but from the latest snapshot , which is inconsistent from the previous list results - objects that are created , modified , or deleted after the first list request will be included in the response , as long as their keys are after the \" next key \" . This field is not supported when watch is true . Clients may start a watch from the last resourceVersion value returned by the server and not miss any modifications . : param str field _ selector : A selector to restrict the list of returned objects by their fields . Defaults to everything . : param str label _ selector : A selector to restrict the list of returned objects by their labels . Defaults to everything . : param int limit : limit is a maximum number of responses to return for a list call . If more items exist , the server will set the ` continue ` field on the list metadata to a value that can be used with the same initial query to retrieve the next set of results . Setting a limit may return fewer than the requested amount of items ( up to zero items ) in the event all requested objects are filtered out and clients should only use the presence of the continue field to determine whether more results are available . Servers may choose not to support the limit argument and will return all of the available results . If limit is specified and the continue field is empty , clients may assume that no more results are available . This field is not supported if watch is true . The server guarantees that the objects returned when using continue will be identical to issuing a single list call without a limit - that is , no objects created , modified , or deleted after the first request is issued will be included in any subsequent continued requests . This is sometimes referred to as a consistent snapshot , and ensures that a client that is using limit to receive smaller chunks of a very large result can ensure they see all possible objects . If objects are updated during a chunked list the version of the object that was present at the time the first list result was calculated is returned . : param str resource _ version : When specified with a watch call , shows changes that occur after that particular version of a resource . Defaults to changes from the beginning of history . When specified for list : - if unset , then the result is returned from remote storage based on quorum - read flag ; - if it ' s 0 , then we simply return what we currently have in cache , no guarantee ; - if set to non zero , then the result is at least as fresh as given rv . : param int timeout _ seconds : Timeout for the list / watch call . This limits the duration of the call , regardless of any activity or inactivity . : param bool watch : Watch for changes to the described resources and return them as a stream of add , update , and remove notifications . Specify resourceVersion . : return : V1Status If the method is called asynchronously , returns the request thread ."""
kwargs [ '_return_http_data_only' ] = True if kwargs . get ( 'async_req' ) : return self . delete_collection_node_with_http_info ( ** kwargs ) # noqa : E501 else : ( data ) = self . delete_collection_node_with_http_info ( ** kwargs ) # noqa : E501 return data
def getMapScale ( self , latitude , level , dpi = 96 ) : '''returns the map scale on the dpi of the screen'''
dpm = dpi / 0.0254 # convert to dots per meter return self . getGroundResolution ( latitude , level ) * dpm
def request_system_arm ( blink , network ) : """Arm system . : param blink : Blink instance . : param network : Sync module network id ."""
url = "{}/network/{}/arm" . format ( blink . urls . base_url , network ) return http_post ( blink , url )
def close ( self ) : """Flush data , write 28 bytes BGZF EOF marker , and close BGZF file . samtools will look for a magic EOF marker , just a 28 byte empty BGZF block , and if it is missing warns the BAM file may be truncated . In addition to samtools writing this block , so too does bgzip - so this implementation does too ."""
if self . _buffer : self . flush ( ) self . _handle . write ( _bgzf_eof ) self . _handle . flush ( ) self . _handle . close ( )
def __display_top ( self , stat_display , stats ) : """Display the second line in the Curses interface . < QUICKLOOK > + CPU | PERCPU + < GPU > + MEM + SWAP + LOAD"""
self . init_column ( ) self . new_line ( ) # Init quicklook stat_display [ 'quicklook' ] = { 'msgdict' : [ ] } # Dict for plugins width plugin_widths = { } for p in self . _top : plugin_widths [ p ] = self . get_stats_display_width ( stat_display . get ( p , 0 ) ) if hasattr ( self . args , 'disable_' + p ) else 0 # Width of all plugins stats_width = sum ( itervalues ( plugin_widths ) ) # Number of plugin but quicklook stats_number = sum ( [ int ( stat_display [ p ] [ 'msgdict' ] != [ ] ) for p in self . _top if not getattr ( self . args , 'disable_' + p ) ] ) if not self . args . disable_quicklook : # Quick look is in the place ! if self . args . full_quicklook : quicklook_width = self . screen . getmaxyx ( ) [ 1 ] - ( stats_width + 8 + stats_number * self . space_between_column ) else : quicklook_width = min ( self . screen . getmaxyx ( ) [ 1 ] - ( stats_width + 8 + stats_number * self . space_between_column ) , self . _quicklook_max_width - 5 ) try : stat_display [ "quicklook" ] = stats . get_plugin ( 'quicklook' ) . get_stats_display ( max_width = quicklook_width , args = self . args ) except AttributeError as e : logger . debug ( "Quicklook plugin not available (%s)" % e ) else : plugin_widths [ 'quicklook' ] = self . get_stats_display_width ( stat_display [ "quicklook" ] ) stats_width = sum ( itervalues ( plugin_widths ) ) + 1 self . space_between_column = 1 self . display_plugin ( stat_display [ "quicklook" ] ) self . new_column ( ) # Compute spaces between plugins # Note : Only one space between Quicklook and others plugin_display_optional = { } for p in self . _top : plugin_display_optional [ p ] = True if stats_number > 1 : self . space_between_column = max ( 1 , int ( ( self . screen . getmaxyx ( ) [ 1 ] - stats_width ) / ( stats_number - 1 ) ) ) for p in [ 'mem' , 'cpu' ] : # No space ? Remove optional stats if self . space_between_column < 3 : plugin_display_optional [ p ] = False plugin_widths [ p ] = self . get_stats_display_width ( stat_display [ p ] , without_option = True ) if hasattr ( self . args , 'disable_' + p ) else 0 stats_width = sum ( itervalues ( plugin_widths ) ) + 1 self . space_between_column = max ( 1 , int ( ( self . screen . getmaxyx ( ) [ 1 ] - stats_width ) / ( stats_number - 1 ) ) ) else : self . space_between_column = 0 # Display CPU , MEM , SWAP and LOAD for p in self . _top : if p == 'quicklook' : continue if p in stat_display : self . display_plugin ( stat_display [ p ] , display_optional = plugin_display_optional [ p ] ) if p is not 'load' : # Skip last column self . new_column ( ) # Space between column self . space_between_column = 3 # Backup line position self . saved_line = self . next_line
def signedDistance ( actor , maxradius = 0.5 , bounds = ( 0 , 1 , 0 , 1 , 0 , 1 ) , dims = ( 10 , 10 , 10 ) ) : """` ` vtkSignedDistance ` ` filter . : param float maxradius : how far out to propagate distance calculation : param list bounds : volume bounds ."""
dist = vtk . vtkSignedDistance ( ) dist . SetInputData ( actor . polydata ( True ) ) dist . SetRadius ( maxradius ) dist . SetBounds ( bounds ) dist . SetDimensions ( dims ) dist . Update ( ) return Volume ( dist . GetOutput ( ) )
def determine_intent ( self , utterance , num_results = 1 , include_tags = False , context_manager = None ) : """Given an utterance , provide a valid intent . Args : utterance ( str ) : an ascii or unicode string representing natural language speech include _ tags ( list ) : includes the parsed tags ( including position and confidence ) as part of result context _ manager ( list ) : a context manager to provide context to the utterance num _ results ( int ) : a maximum number of results to be returned . Returns : A generator that yields dictionaries ."""
parser = Parser ( self . tokenizer , self . tagger ) parser . on ( 'tagged_entities' , ( lambda result : self . emit ( "tagged_entities" , result ) ) ) context = [ ] if context_manager : context = context_manager . get_context ( ) for result in parser . parse ( utterance , N = num_results , context = context ) : self . emit ( "parse_result" , result ) # create a context without entities used in result remaining_context = self . __get_unused_context ( result , context ) best_intent , tags = self . __best_intent ( result , remaining_context ) if best_intent and best_intent . get ( 'confidence' , 0.0 ) > 0 : if include_tags : best_intent [ '__tags__' ] = tags yield best_intent
def checkMgtKeyInUse ( self , CorpNum , MgtKeyType , MgtKey ) : """파트너 관리번호 사용중 여부 확인 . args CorpNum : 회원 사업자 번호 MgtKeyType : 관리번호 유형 one of [ ' SELL ' , ' BUY ' , ' TRUSTEE ' ] MgtKey : 파트너 관리번호 return 사용중 여부 by True / False raise PopbillException"""
if MgtKeyType not in self . __MgtKeyTypes : raise PopbillException ( - 99999999 , "관리번호 형태가 올바르지 않습니다." ) if MgtKey == None or MgtKey == "" : raise PopbillException ( - 99999999 , "관리번호가 입력되지 않았습니다." ) try : result = self . _httpget ( '/Taxinvoice/' + MgtKeyType + "/" + MgtKey , CorpNum ) return result . itemKey != None and result . itemKey != "" except PopbillException as PE : if PE . code == - 11000005 : return False raise PE
def get_version ( ) : "returns the libdbus library version as a tuple of integers ( major , minor , micro ) ."
major = ct . c_int ( ) minor = ct . c_int ( ) micro = ct . c_int ( ) dbus . dbus_get_version ( ct . byref ( major ) , ct . byref ( minor ) , ct . byref ( micro ) ) return ( major . value , minor . value , micro . value )
def _required_attr ( self , attr , key ) : """Wrapper for getting required attributes ."""
assert isinstance ( attr , dict ) if key not in attr : raise AttributeError ( "Required attribute {} not found." . format ( key ) ) return attr [ key ]
def default_partfactory ( part_number = None , content_length = None , content_type = None , content_md5 = None ) : """Get default part factory . : param part _ number : The part number . ( Default : ` ` None ` ` ) : param content _ length : The content length . ( Default : ` ` None ` ` ) : param content _ type : The HTTP Content - Type . ( Default : ` ` None ` ` ) : param content _ md5 : The content MD5 . ( Default : ` ` None ` ` ) : returns : The content length , the part number , the stream , the content type , MD5 of the content ."""
return content_length , part_number , request . stream , content_type , content_md5 , None
def outputjson ( self , obj ) : """Serialize ` obj ` with JSON and output to the client"""
self . header ( 'Content-Type' , 'application/json' ) self . outputdata ( json . dumps ( obj ) . encode ( 'ascii' ) )
def make_node_dict ( outer_list , sort = "zone" ) : """Convert node data from nested - list to sorted dict ."""
raw_dict = { } x = 1 for inner_list in outer_list : for node in inner_list : raw_dict [ x ] = node x += 1 if sort == "name" : # sort by provider - name srt_dict = OrderedDict ( sorted ( raw_dict . items ( ) , key = lambda k : ( k [ 1 ] . cloud , k [ 1 ] . name . lower ( ) ) ) ) else : # sort by provider - zone - name srt_dict = OrderedDict ( sorted ( raw_dict . items ( ) , key = lambda k : ( k [ 1 ] . cloud , k [ 1 ] . zone , k [ 1 ] . name . lower ( ) ) ) ) x = 1 node_dict = { } for i , v in srt_dict . items ( ) : node_dict [ x ] = v x += 1 return node_dict
async def on_data_error ( self , exception ) : """Handle error ."""
self . logger . error ( 'Encountered error on socket.' , exc_info = ( type ( exception ) , exception , None ) ) await self . disconnect ( expected = False )
def initialise_arrays ( group , f ) : """Create EArrays for calibrated hits"""
for node in [ 'pos_x' , 'pos_y' , 'pos_z' , 'dir_x' , 'dir_y' , 'dir_z' , 'du' , 'floor' , 't0' ] : if node in [ 'floor' , 'du' ] : atom = U1_ATOM else : atom = F4_ATOM f . create_earray ( group , node , atom , ( 0 , ) , filters = FILTERS )
def parse_plunge_bearing ( plunge , bearing ) : """Parses strings of plunge and bearing and returns a consistent plunge and bearing measurement as floats . Plunge angles returned by this function will always be between 0 and 90. If no direction letter ( s ) is present , the plunge is assumed to be measured from the end specified by the bearing . If a direction letter ( s ) is present , the bearing will be switched to the opposite ( 180 degrees ) end if the specified direction corresponds to the opposite end specified by the bearing . Parameters plunge : string A plunge measurement . bearing : string A bearing measurement . May be in azimuth or quadrant format . Returns plunge , bearing : floats The plunge and bearing following the conventions outlined above . Examples > > > parse _ plunge _ bearing ( " 30NW " , 160) . . . ( 30 , 340)"""
bearing = parse_azimuth ( bearing ) plunge , direction = split_trailing_letters ( plunge ) if direction is not None : if opposite_end ( bearing , direction ) : bearing += 180 if plunge < 0 : bearing += 180 plunge = - plunge if plunge > 90 : bearing += 180 plunge = 180 - plunge if bearing > 360 : bearing -= 360 return plunge , bearing
def value ( self , name ) : """get value of a track at the current time"""
return self . tracks . get ( name ) . row_value ( self . controller . row )
def cdx_limit ( cdx_iter , limit ) : """limit cdx to at most ` limit ` ."""
# for cdx , _ in itertools . izip ( cdx _ iter , xrange ( limit ) ) : # yield cdx return ( cdx for cdx , _ in zip ( cdx_iter , range ( limit ) ) )
def calibrate_counts ( array , attributes , index ) : """Calibration for counts channels ."""
offset = np . float32 ( attributes [ "corrected_counts_offsets" ] [ index ] ) scale = np . float32 ( attributes [ "corrected_counts_scales" ] [ index ] ) array = ( array - offset ) * scale return array
def get_derived_metric_tags ( self , id , ** kwargs ) : # noqa : E501 """Get all tags associated with a specific derived metric definition # noqa : E501 # noqa : E501 This method makes a synchronous HTTP request by default . To make an asynchronous HTTP request , please pass async _ req = True > > > thread = api . get _ derived _ metric _ tags ( id , async _ req = True ) > > > result = thread . get ( ) : param async _ req bool : param str id : ( required ) : return : ResponseContainerTagsResponse If the method is called asynchronously , returns the request thread ."""
kwargs [ '_return_http_data_only' ] = True if kwargs . get ( 'async_req' ) : return self . get_derived_metric_tags_with_http_info ( id , ** kwargs ) # noqa : E501 else : ( data ) = self . get_derived_metric_tags_with_http_info ( id , ** kwargs ) # noqa : E501 return data
def _format_local_file ( self ) : """When args . local _ file empty on Windows , tries to map args . entity to a unc path . Updates args . local _ file in - place without returning anything ."""
if self . type != 'file' : return if not self . entity : return if not is_win : return if self . _file_exists ( ) : return self . args . local_file = self . _to_unc_path ( self . entity )
def _check_file ( self ) : """Checks watched file moficiation time and permission changes ."""
try : self . editor . toPlainText ( ) except RuntimeError : self . _timer . stop ( ) return if self . editor and self . editor . file . path : if not os . path . exists ( self . editor . file . path ) and self . _mtime : self . _notify_deleted_file ( ) else : mtime = os . path . getmtime ( self . editor . file . path ) if mtime > self . _mtime : self . _mtime = mtime self . _notify_change ( ) # check for permission change writeable = os . access ( self . editor . file . path , os . W_OK ) self . editor . setReadOnly ( not writeable )
def write_file ( self , filename , cart_coords = False ) : """Write the input string into a file Option : see _ _ str _ _ method"""
with zopen ( filename , "w" ) as f : f . write ( self . to_string ( cart_coords ) )
def shape ( self ) : """Returns ( rowCount , valueCount )"""
bf = self . copy ( ) content = requests . get ( bf . dataset_url ) . json ( ) rowCount = content [ 'status' ] [ 'rowCount' ] valueCount = content [ 'status' ] [ 'valueCount' ] return ( rowCount , valueCount )
def emitCurrentChanged ( self ) : """Emits the current schema changed signal for this combobox , provided \ the signals aren ' t blocked ."""
if ( not self . signalsBlocked ( ) ) : schema = self . currentSchema ( ) self . currentSchemaChanged . emit ( schema ) if ( schema ) : self . currentTableChanged . emit ( schema . model ( ) ) else : self . currentTableChanged . emit ( None )
def data ( self , ctx = None ) : """Returns a copy of this parameter on one context . Must have been initialized on this context before . Parameters ctx : Context Desired context . Returns NDArray on ctx"""
d = self . _check_and_get ( self . _data , ctx ) if self . _rate : d = nd . Dropout ( d , self . _rate , self . _mode , self . _axes ) return d
def find_tags ( self , tokens , ** kwargs ) : """Annotates the given list of tokens with part - of - speech tags . Returns a list of tokens , where each token is now a [ word , tag ] - list ."""
# [ " The " , " cat " , " purs " ] = > [ [ " The " , " DT " ] , [ " cat " , " NN " ] , [ " purs " , " VB " ] ] return find_tags ( tokens , lexicon = kwargs . get ( "lexicon" , self . lexicon or { } ) , model = kwargs . get ( "model" , self . model ) , morphology = kwargs . get ( "morphology" , self . morphology ) , context = kwargs . get ( "context" , self . context ) , entities = kwargs . get ( "entities" , self . entities ) , language = kwargs . get ( "language" , self . language ) , default = kwargs . get ( "default" , self . default ) , map = kwargs . get ( "map" , None ) )
def process_infile ( f , fileStore ) : """Takes an array of files or a single file and imports into the jobstore . This returns a tuple or an array of tuples replacing all previous path strings . Toil does not preserve a file ' s original name upon import and so the tuple keeps track of this with the format : ' ( filepath , preserveThisFilename ) ' : param f : String or an Array . The smallest element must be a string , so : an array of strings , an array of arrays of strings . . . etc . : param fileStore : The filestore object that is called to load files into the filestore . : return : A tuple or an array of tuples ."""
# check if this has already been processed if isinstance ( f , tuple ) : return f elif isinstance ( f , list ) : return process_array_infile ( f , fileStore ) elif isinstance ( f , basestring ) : return process_single_infile ( f , fileStore ) else : raise RuntimeError ( 'Error processing file: ' . format ( str ( f ) ) )
def _check_rev_dict ( tree , ebt ) : """Verifyies that ` ebt ` is the inverse of the ` edgeBySourceId ` data member of ` tree `"""
ebs = defaultdict ( dict ) for edge in ebt . values ( ) : source_id = edge [ '@source' ] edge_id = edge [ '@id' ] ebs [ source_id ] [ edge_id ] = edge assert ebs == tree [ 'edgeBySourceId' ]
def create_container ( self , conf , detach , tty ) : """Create a single container"""
name = conf . name image_name = conf . image_name if conf . tag is not NotSpecified : image_name = conf . image_name_with_tag container_name = conf . container_name with conf . assumed_role ( ) : env = dict ( e . pair for e in conf . env ) binds = conf . volumes . binds command = conf . formatted_command volume_names = conf . volumes . volume_names volumes_from = list ( conf . volumes . share_with_names ) no_tty_option = conf . no_tty_option ports = [ p . container_port . port_pair for p in conf . ports ] port_bindings = self . exposed ( conf . ports ) uncreated = [ ] for name in binds : if not os . path . exists ( name ) : log . info ( "Making volume for mounting\tvolume=%s" , name ) try : os . makedirs ( name ) except OSError as error : uncreated . append ( ( name , error ) ) if uncreated : raise BadOption ( "Failed to create some volumes on the host" , uncreated = uncreated ) log . info ( "Creating container from %s\timage=%s\tcontainer_name=%s\ttty=%s" , image_name , name , container_name , tty ) if binds : log . info ( "\tUsing volumes\tvolumes=%s" , volume_names ) if env : log . info ( "\tUsing environment\tenv=%s" , sorted ( env . keys ( ) ) ) if ports : log . info ( "\tUsing ports\tports=%s" , ports ) if port_bindings : log . info ( "\tPort bindings: %s" , port_bindings ) if volumes_from : log . info ( "\tVolumes from: %s" , volumes_from ) host_config = conf . harpoon . docker_api . create_host_config ( binds = binds , volumes_from = volumes_from , port_bindings = port_bindings , devices = conf . devices , lxc_conf = conf . lxc_conf , privileged = conf . privileged , restart_policy = conf . restart_policy , dns = conf . network . dns , dns_search = conf . network . dns_search , extra_hosts = conf . network . extra_hosts , network_mode = conf . network . network_mode , publish_all_ports = conf . network . publish_all_ports , cap_add = conf . cpu . cap_add , cap_drop = conf . cpu . cap_drop , mem_limit = conf . cpu . mem_limit , cpu_shares = conf . cpu . cpu_shares , cpuset_cpus = conf . cpu . cpuset_cpus , cpuset_mems = conf . cpu . cpuset_mems , memswap_limit = conf . cpu . memswap_limit , ulimits = conf . ulimits , read_only = conf . read_only_rootfs , log_config = conf . log_config , security_opt = conf . security_opt , ** conf . other_options . host_config ) container_id = conf . harpoon . docker_api . create_container ( image_name , name = container_name , detach = detach , command = command , volumes = volume_names , environment = env , tty = False if no_tty_option else tty , user = conf . user , ports = ports , stdin_open = tty , hostname = conf . network . hostname , domainname = conf . network . domainname , network_disabled = conf . network . disabled , host_config = host_config , ** conf . other_options . create ) if isinstance ( container_id , dict ) : if "errorDetail" in container_id : raise BadImage ( "Failed to create container" , image = name , error = container_id [ "errorDetail" ] ) container_id = container_id [ "Id" ] return container_id
def _unweave ( target , advices , pointcut , ctx , depth , depth_predicate ) : """Unweave deeply advices in target ."""
# if weaving has to be done if pointcut is None or pointcut ( target ) : # do something only if target is intercepted if is_intercepted ( target ) : _remove_advices ( target = target , advices = advices , ctx = ctx ) # search inside the target if depth > 0 : # for an object or a class , weave on methods # get base ctx _base_ctx = None if ctx is not None : _base_ctx = base_ctx ( ctx ) for _ , member in getmembers ( target , depth_predicate ) : _unweave ( target = member , advices = advices , pointcut = pointcut , depth = depth - 1 , depth_predicate = depth_predicate , ctx = _base_ctx )
def GetMessages ( self , formatter_mediator , event ) : """Determines the formatted message strings for an event object . Args : formatter _ mediator ( FormatterMediator ) : mediates the interactions between formatters and other components , such as storage and Windows EventLog resources . event ( EventObject ) : event . Returns : tuple ( str , str ) : formatted message string and short message string . Raises : WrongFormatter : if the event object cannot be formatted by the formatter ."""
if self . DATA_TYPE != event . data_type : raise errors . WrongFormatter ( 'Invalid event object - unsupported data type: {0:s}' . format ( event . data_type ) ) event_values = event . CopyToDict ( ) number_of_volumes = event_values . get ( 'number_of_volumes' , 0 ) volume_serial_numbers = event_values . get ( 'volume_serial_numbers' , None ) volume_device_paths = event_values . get ( 'volume_device_paths' , None ) volumes_strings = [ ] for volume_index in range ( 0 , number_of_volumes ) : if not volume_serial_numbers : volume_serial_number = 'UNKNOWN' else : volume_serial_number = volume_serial_numbers [ volume_index ] if not volume_device_paths : volume_device_path = 'UNKNOWN' else : volume_device_path = volume_device_paths [ volume_index ] volumes_strings . append ( ( 'volume: {0:d} [serial number: 0x{1:08X}, device path: ' '{2:s}]' ) . format ( volume_index + 1 , volume_serial_number , volume_device_path ) ) if volumes_strings : event_values [ 'volumes_string' ] = ', ' . join ( volumes_strings ) return self . _ConditionalFormatMessages ( event_values )
def get_Generic_parameters ( tp , generic_supertype ) : """tp must be a subclass of generic _ supertype . Retrieves the type values from tp that correspond to parameters defined by generic _ supertype . E . g . get _ Generic _ parameters ( tp , typing . Mapping ) is equivalent to get _ Mapping _ key _ value ( tp ) except for the error message . Note that get _ Generic _ itemtype ( tp ) is not exactly equal to get _ Generic _ parameters ( tp , typing . Container ) , as that method additionally contains treatment for typing . Tuple and typing . Iterable ."""
try : res = _select_Generic_superclass_parameters ( tp , generic_supertype ) except TypeError : res = None if res is None : raise TypeError ( "%s has no proper parameters defined by %s." % ( type_str ( tp ) , type_str ( generic_supertype ) ) ) else : return tuple ( res )
def print ( * args , ** kwargs ) : """Normally print function in python prints values to a stream / stdout > > print ( value1 , value2 , sep = ' ' , end = ' \n ' , file = sys . stdout ) Current package usage : print ( value1 , value2 , sep = ' ' , end = ' \n ' , file = sys . stdout , color = None , bg _ color = None , text _ format = None , log _ type = None ) : param args : Values ( str ) to print : param kwargs : Text formats like sep , end , color , background , text format , log type ( ERROR , INFO , WARNING , DEBUG ) : return : Colored text to stdout ( Console )"""
# Pop out color and background values from kwargs color_name = kwargs . pop ( 'color' , None ) bg_color = kwargs . pop ( 'bg_color' , None ) log_type = kwargs . pop ( 'log_type' , None ) # Check formats , create a list of text formats txt_formats = kwargs . pop ( 'text_format' , [ ] ) if sys . version_info [ 0 ] == 2 : str_type = basestring elif sys . version_info [ 0 ] == 3 : str_type = str else : str_type = basestring if isinstance ( txt_formats , str_type ) : txt_formats = [ txt_formats ] # Check for file keyword file_name = kwargs . get ( 'file' , sys . stdout ) # Check for foreground and background colors if color_name or bg_color or log_type : # Pop out the ' end ' argument end_ = kwargs . pop ( 'end' , "\n" ) kwargs [ 'end' ] = "" # If log type argument is provided if log_type : if log_type not in log_types . keys ( ) : print ( 'Log type not valid!' , log_type = 'error' ) sys . exit ( 1 ) if log_type == 'info' : __builtin__ . print ( '\033[{}m[INF] ' . format ( foreground_colors [ log_types [ log_type ] ] ) , file = file_name , end = '' ) __builtin__ . print ( '\033[0m' , file = file_name , end = '' ) if log_type == 'warn' : __builtin__ . print ( '\033[{}m[WRN] ' . format ( foreground_colors [ log_types [ log_type ] ] ) , file = file_name , end = '' ) __builtin__ . print ( '\033[0m' , file = file_name , end = '' ) if log_type == 'error' : __builtin__ . print ( '\033[{}m[ERR] ' . format ( foreground_colors [ log_types [ log_type ] ] ) , file = file_name , end = '' ) __builtin__ . print ( '\033[0m' , file = file_name , end = '' ) if log_type == 'hint' : __builtin__ . print ( '\033[{}m[HNT] ' . format ( foreground_colors [ log_types [ log_type ] ] ) , file = file_name , end = '' ) __builtin__ . print ( '\033[0m' , file = file_name , end = '' ) if log_type == 'debug' : __builtin__ . print ( '\033[{}m[DBG] ' . format ( foreground_colors [ log_types [ log_type ] ] ) , file = file_name , end = '' ) __builtin__ . print ( '\033[0m' , file = file_name , end = '' ) # If foreground color argument is provided if color_name : if color_name not in foreground_colors . keys ( ) : print ( 'Invalid color code!' , log_type = 'error' ) sys . exit ( 1 ) __builtin__ . print ( '\033[{}m' . format ( foreground_colors [ color_name ] ) , file = file_name , end = '' ) # If background color argument is provided if bg_color : if bg_color not in background_colors . keys ( ) : print ( 'Invalid background color code!' , log_type = 'error' ) sys . exit ( 1 ) __builtin__ . print ( '\033[{}m' . format ( background_colors [ bg_color ] ) , file = file_name , end = '' ) # If text formats are provided for txt_format in txt_formats : __builtin__ . print ( '\033[{}m' . format ( text_formats [ txt_format ] ) , file = file_name , end = '' ) # Print values __builtin__ . print ( * args , ** kwargs ) # Reset __builtin__ . print ( '\033[0m' , file = file_name , end = end_ ) else : __builtin__ . print ( * args , ** kwargs )
def unproxy ( possible_proxy ) : '''Unwrap and return the object referenced by a proxy . This function is very similar to : func : ` get _ reference ` , but works for both proxies and regular objects . If the specified object is a proxy , its reference is extracted with ` ` get _ reference ` ` and returned . If it is not a proxy , it is returned as is . If the object references by the proxy is itself a proxy , the unwrapping is repeated until a regular ( non - proxy ) object is found . possible _ proxy : object that might or might not be a proxy .'''
while isinstance ( possible_proxy , ThreadLocalProxy ) : possible_proxy = ThreadLocalProxy . get_reference ( possible_proxy ) return possible_proxy
def get_culture_pair ( self , code ) : """# Return a tuple of the language and country for a given culture code : param code : : return :"""
if not any ( x in code for x in ( '_' , '-' ) ) : raise ValueError ( "%s is not a valid culture code" % code ) cc = CultureCode . objects . get ( code = code . replace ( '_' , '-' ) ) return cc . language , cc . country
def _reset ( self , server , ** kwargs ) : """Reset the server object with new values given as params . - server : a dict representing the server . e . g the API response . - kwargs : any meta fields such as cloud _ manager and populated . Note : storage _ devices and ip _ addresses may be given in server as dicts or in kwargs as lists containing Storage and IPAddress objects ."""
if server : # handle storage , ip _ address dicts and tags if they exist Server . _handle_server_subobjs ( server , kwargs . get ( 'cloud_manager' ) ) for key in server : object . __setattr__ ( self , key , server [ key ] ) for key in kwargs : object . __setattr__ ( self , key , kwargs [ key ] )
def mean_absolute_error ( data , ground_truth , mask = None , normalized = False , force_lower_is_better = True ) : r"""Return L1 - distance between ` ` data ` ` and ` ` ground _ truth ` ` . See also ` this Wikipedia article < https : / / en . wikipedia . org / wiki / Mean _ absolute _ error > ` _ . Parameters data : ` Tensor ` or ` array - like ` Input data to compare to the ground truth . If not a ` Tensor ` , an unweighted tensor space will be assumed . ground _ truth : ` array - like ` Reference to which ` ` data ` ` should be compared . mask : ` array - like ` , optional If given , ` ` data * mask ` ` is compared to ` ` ground _ truth * mask ` ` . normalized : bool , optional If ` ` True ` ` , the output values are mapped to the interval : math : ` [ 0 , 1 ] ` ( see ` Notes ` for details ) , otherwise return the original mean absolute error . force _ lower _ is _ better : bool , optional If ` ` True ` ` , it is ensured that lower values correspond to better matches . For the mean absolute error , this is already the case , and the flag is only present for compatibility to other figures of merit . Returns mae : float FOM value , where a lower value means a better match . Notes The FOM evaluates . . math : : \ mathrm { MAE } ( f , g ) = \ frac { \ | f - g \ | _ 1 } { \ | 1 \ | _ 1 } , where : math : ` \ | 1 \ | _ 1 ` is the volume of the domain of definition of the functions . For : math : ` \ mathbb { R } ^ n ` type spaces , this is equal to the number of elements : math : ` n ` . The normalized form is . . math : : \ mathrm { MAE _ N } ( f , g ) = \ frac { \ | f - g \ | _ 1 } { \ | f \ | _ 1 + \ | g \ | _ 1 } . The normalized variant takes values in : math : ` [ 0 , 1 ] ` ."""
if not hasattr ( data , 'space' ) : data = odl . vector ( data ) space = data . space ground_truth = space . element ( ground_truth ) l1_norm = odl . solvers . L1Norm ( space ) if mask is not None : data = data * mask ground_truth = ground_truth * mask diff = data - ground_truth fom = l1_norm ( diff ) if normalized : fom /= ( l1_norm ( data ) + l1_norm ( ground_truth ) ) else : fom /= l1_norm ( space . one ( ) ) # Ignore ` force _ lower _ is _ better ` since that ' s already the case return fom
def get_gradebook_columns_by_gradebooks ( self , gradebook_ids ) : """Gets the list of gradebook columns corresponding to a list of ` ` Gradebooks ` ` . arg : gradebook _ ids ( osid . id . IdList ) : list of gradebook ` ` Ids ` ` return : ( osid . grading . GradebookColumnList ) - list of gradebook columns raise : NullArgument - ` ` gradebook _ ids ` ` is ` ` null ` ` raise : OperationFailed - unable to complete request raise : PermissionDenied - authorization failure * compliance : mandatory - - This method must be implemented . *"""
# Implemented from template for # osid . resource . ResourceBinSession . get _ resources _ by _ bins gradebook_column_list = [ ] for gradebook_id in gradebook_ids : gradebook_column_list += list ( self . get_gradebook_columns_by_gradebook ( gradebook_id ) ) return objects . GradebookColumnList ( gradebook_column_list )
def get_metadata ( self , filename ) : '''Fetch all availabe metadata'''
obj = self . bucket . Object ( filename ) checksum = 'md5:{0}' . format ( obj . e_tag [ 1 : - 1 ] ) mime = obj . content_type . split ( ';' , 1 ) [ 0 ] if obj . content_type else None return { 'checksum' : checksum , 'size' : obj . content_length , 'mime' : mime , 'modified' : obj . last_modified , }
def _get_selected_ids ( self ) : """List of currently selected ids"""
selection = self . get_selection ( ) if selection . get_mode ( ) != gtk . SELECTION_MULTIPLE : raise AttributeError ( 'selected_ids only valid for select_multiple' ) model , selected_paths = selection . get_selected_rows ( ) if selected_paths : return zip ( * selected_paths ) [ 0 ] else : return ( )
def patched_function ( self , * args , ** kwargs ) : """Step 3 . Wrapped function calling ."""
result = self . function ( * args , ** kwargs ) self . validate ( result ) return result
def filePath ( self , index ) : """Gets the file path of the item at the specified ` ` index ` ` . : param index : item index - QModelIndex : return : str"""
return self . _fs_model_source . filePath ( self . _fs_model_proxy . mapToSource ( index ) )
def merge ( self , recarray , columns = None ) : """Merge another recarray with the same columns into this table . : Arguments : recarray numpy record array that describes the layout and initializes the table : Returns : n number of inserted rows : Raises : Raises an exception if duplicate and incompatible data exist in the main table and the new one ."""
len_before = len ( self ) # CREATE TEMP TABLE in database tmparray = SQLarray ( self . tmp_table_name , records = recarray , columns = columns , connection = self . connection , is_tmp = True ) len_tmp = len ( tmparray ) # insert into main table SQL = """INSERT OR ABORT INTO __self__ SELECT * FROM %s""" % self . tmp_table_name self . sql ( SQL ) len_after = len ( self ) n_inserted = len_after - len_before assert len_tmp == n_inserted del tmparray # also drops the tmp table ( keep it at end for debugging ) return n_inserted
def dataflagatom ( chans , pol , d , sig , mode , conv ) : """Wrapper function to get shared memory as numpy array into pool Assumes data _ mem is global mps . Array"""
data = numpyview ( data_mem , 'complex64' , datashape ( d ) ) # data = n . ma . masked _ array ( data , data = = 0j ) # this causes massive overflagging on 14sep03 data return rtlib . dataflag ( data , chans , pol , d , sig , mode , conv )
def exp_cov ( prices , span = 180 , frequency = 252 ) : """Estimate the exponentially - weighted covariance matrix , which gives greater weight to more recent data . : param prices : adjusted closing prices of the asset , each row is a date and each column is a ticker / id . : type prices : pd . DataFrame : param span : the span of the exponential weighting function , defaults to 180 : type span : int , optional : param frequency : number of time periods in a year , defaults to 252 ( the number of trading days in a year ) : type frequency : int , optional : return : annualised estimate of exponential covariance matrix : rtype : pd . DataFrame"""
if not isinstance ( prices , pd . DataFrame ) : warnings . warn ( "prices are not in a dataframe" , RuntimeWarning ) prices = pd . DataFrame ( prices ) assets = prices . columns daily_returns = daily_price_returns ( prices ) N = len ( assets ) # Loop over matrix , filling entries with the pairwise exp cov S = np . zeros ( ( N , N ) ) for i in range ( N ) : for j in range ( i , N ) : S [ i , j ] = S [ j , i ] = _pair_exp_cov ( daily_returns . iloc [ : , i ] , daily_returns . iloc [ : , j ] , span ) return pd . DataFrame ( S * frequency , columns = assets , index = assets )
def addlayer ( self , name , srs , geomType ) : """add a layer to the vector layer Parameters name : str the layer name srs : int , str or : osgeo : class : ` osr . SpatialReference ` the spatial reference system . See : func : ` spatialist . auxil . crsConvert ` for options . geomType : int an OGR well - known binary data type . See ` Module ogr < https : / / gdal . org / python / osgeo . ogr - module . html > ` _ . Returns"""
self . vector . CreateLayer ( name , srs , geomType ) self . init_layer ( )
def get_source_link ( thing , source_location ) : """Get a link to the line number a module / class / function is defined at . Parameters thing : function or class Thing to get the link for source _ location : str GitHub url of the source code Returns str String with link to the file & line number , or empty string if it couldn ' t be found"""
try : lineno = get_line ( thing ) try : owner_module = inspect . getmodule ( thing ) assert owner_module is not None except ( TypeError , AssertionError ) : owner_module = inspect . getmodule ( thing . fget ) thing_file = "/" . join ( owner_module . __name__ . split ( "." ) ) if owner_module . __file__ . endswith ( "__init__.py" ) : thing_file += "/__init__.py" else : thing_file += ".py" return ( f"Source: [{escape(thing_file)}]({source_location}/{thing_file}#L{lineno})" + "\n\n" ) except Exception as e : # print ( " Failed to find source file . " ) # print ( e ) # print ( lineno ) # print ( thing ) # print ( owner _ module ) # print ( thing _ file ) # print ( source _ location ) pass return ""
def _create_mapping ( self , func , switch ) : """Internal function to create the mapping ."""
mapping = { } for feature in self . data [ 'features' ] : content = func ( feature ) if switch == 'style' : for key , value in content . items ( ) : if isinstance ( value , MacroElement ) : # Make sure objects are rendered : if value . _parent is None : value . _parent = self . geojson_obj value . render ( ) # Replace objects with their Javascript var names : content [ key ] = "{{'" + value . get_name ( ) + "'}}" key = self . _to_key ( content ) mapping . setdefault ( key , [ ] ) . append ( self . get_feature_id ( feature ) ) self . _set_default_key ( mapping ) return mapping
def make_mutant_tuples ( example_protos , original_feature , index_to_mutate , viz_params ) : """Return a list of ` MutantFeatureValue ` s and a list of mutant Examples . Args : example _ protos : The examples to mutate . original _ feature : A ` OriginalFeatureList ` that encapsulates the feature to mutate . index _ to _ mutate : The index of the int64 _ list or float _ list to mutate . viz _ params : A ` VizParams ` object that contains the UI state of the request . Returns : A list of ` MutantFeatureValue ` s and a list of mutant examples ."""
mutant_features = make_mutant_features ( original_feature , index_to_mutate , viz_params ) mutant_examples = [ ] for example_proto in example_protos : for mutant_feature in mutant_features : copied_example = copy . deepcopy ( example_proto ) feature_name = mutant_feature . original_feature . feature_name try : feature_list = proto_value_for_feature ( copied_example , feature_name ) if index_to_mutate is None : new_values = mutant_feature . mutant_value else : new_values = list ( feature_list ) new_values [ index_to_mutate ] = mutant_feature . mutant_value del feature_list [ : ] feature_list . extend ( new_values ) mutant_examples . append ( copied_example ) except ( ValueError , IndexError ) : # If the mutant value can ' t be set , still add the example to the # mutant _ example even though no change was made . This is necessary to # allow for computation of global PD plots when not all examples have # the same number of feature values for a feature . mutant_examples . append ( copied_example ) return mutant_features , mutant_examples
def handle_endtag ( self , tag ) : """Handles every end tag like e . g . < / p > ."""
if tag in self . stroke_after_elements : if self . text . endswith ( self . stroke_text ) : # Only add a stroke if there isn ' t already a stroke posted # In this case , there was no content between the tags , so # remove the starting stroke self . text = self . text [ : - len ( self . stroke_text ) ] else : # If there ' s no linebreak before the stroke , add one ! if not self . text . endswith ( '\n' ) : self . text += '\n' self . text += self . stroke_text if tag == 'a' : # If it ' s a link , add a footnote self . text += '[{}]' . format ( len ( self . links ) ) elif tag == 'br' and self . text and not self . text . endswith ( '\n' ) : # If it ' s a break , check if there ' s no break at the end of the # content . If there ' s none , add one ! self . text += '\n' # Reset the lasttag , otherwise this parse can geht confused , if the # next element is not wrapped in a new tag . if tag == self . lasttag : self . lasttag = None
def get_beamarea_deg2 ( self , ra , dec ) : """Calculate the area of the synthesized beam in square degrees . Parameters ra , dec : float The sky coordinates at which the calculation is made . Returns area : float The beam area in square degrees ."""
barea = abs ( self . beam . a * self . beam . b * np . pi ) # in deg * * 2 at reference coords if self . lat is not None : barea /= np . cos ( np . radians ( dec - self . lat ) ) return barea
def download_setuptools ( version = DEFAULT_VERSION , download_base = DEFAULT_URL , to_dir = os . curdir , delay = 15 ) : """Download setuptools from a specified location and return its filename ` version ` should be a valid setuptools version number that is available as an egg for download under the ` download _ base ` URL ( which should end with a ' / ' ) . ` to _ dir ` is the directory where the egg will be downloaded . ` delay ` is the number of seconds to pause before an actual download attempt ."""
import urllib2 , shutil egg_name = "setuptools-%s-py%s.egg" % ( version , sys . version [ : 3 ] ) url = download_base + egg_name saveto = os . path . join ( to_dir , egg_name ) src = dst = None if not os . path . exists ( saveto ) : # Avoid repeated downloads try : from distutils import log if delay : log . warn ( """ --------------------------------------------------------------------------- This script requires setuptools version %s to run (even to display help). I will attempt to download it for you (from %s), but you may need to enable firewall access for this script first. I will start the download in %d seconds. (Note: if this machine does not have network access, please obtain the file %s and place it in this directory before rerunning this script.) ---------------------------------------------------------------------------""" , version , download_base , delay , url ) ; from time import sleep ; sleep ( delay ) log . warn ( "Downloading %s" , url ) src = urllib2 . urlopen ( url ) # Read / write all in one block , so we don ' t create a corrupt file # if the download is interrupted . data = _validate_md5 ( egg_name , src . read ( ) ) dst = open ( saveto , "wb" ) ; dst . write ( data ) finally : if src : src . close ( ) if dst : dst . close ( ) return os . path . realpath ( saveto )
def getSamplingStrategy ( self , serviceName ) : """Parameters : - serviceName"""
self . _seqid += 1 future = self . _reqs [ self . _seqid ] = concurrent . Future ( ) self . send_getSamplingStrategy ( serviceName ) return future
def save ( self , path ) : '''Save source video to file . Args : path ( str ) : Filename to save to . Notes : Saves entire source video to file , not just currently selected frames .'''
# IMPORTANT WARNING : saves entire source video self . clip . write_videofile ( path , audio_fps = self . clip . audio . fps )
def run ( self ) : """Index the document . Since ids are predictable , we won ' t index anything twice ."""
with self . input ( ) . open ( ) as handle : body = json . loads ( handle . read ( ) ) es = elasticsearch . Elasticsearch ( ) id = body . get ( '_id' ) es . index ( index = 'frontpage' , doc_type = 'html' , id = id , body = body )
def on ( self , event , f = None ) : """Registers the function ` ` f ` ` to the event name ` ` event ` ` . If ` ` f ` ` isn ' t provided , this method returns a function that takes ` ` f ` ` as a callback ; in other words , you can use this method as a decorator , like so : : @ ee . on ( ' data ' ) def data _ handler ( data ) : print ( data ) In both the decorated and undecorated forms , the event handler is returned . The upshot of this is that you can call decorated handlers directly , as well as use them in remove _ listener calls ."""
def _on ( f ) : self . _add_event_handler ( event , f , f ) return f if f is None : return _on else : return _on ( f )
def run ( self ) : """Include a file as part of the content of this reST file ."""
if not self . state . document . settings . file_insertion_enabled : raise self . warning ( '"%s" directive disabled.' % self . name ) source = self . state_machine . input_lines . source ( self . lineno - self . state_machine . input_offset - 1 ) source_dir = os . path . dirname ( os . path . abspath ( source ) ) path = directives . path ( self . arguments [ 0 ] ) path = os . path . normpath ( os . path . join ( source_dir , path ) ) path = utils . relative_path ( None , path ) path = nodes . reprunicode ( path ) encoding = self . options . get ( 'encoding' , self . state . document . settings . input_encoding ) e_handler = self . state . document . settings . input_encoding_error_handler tab_width = self . options . get ( 'tab-width' , self . state . document . settings . tab_width ) try : self . state . document . settings . record_dependencies . add ( path ) include_file = io . FileInput ( source_path = path , encoding = encoding , error_handler = e_handler ) except UnicodeEncodeError as error : raise self . severe ( 'Problems with "%s" directive path:\n' 'Cannot encode input file path "%s" ' '(wrong locale?).' % ( self . name , SafeString ( path ) ) ) except IOError as error : raise self . severe ( 'Problems with "%s" directive path:\n%s.' % ( self . name , ErrorString ( error ) ) ) startline = self . options . get ( 'start-line' , None ) endline = self . options . get ( 'end-line' , None ) try : if startline or ( endline is not None ) : lines = include_file . readlines ( ) rawtext = '' . join ( lines [ startline : endline ] ) else : rawtext = include_file . read ( ) except UnicodeError as error : raise self . severe ( 'Problem with "%s" directive:\n%s' % ( self . name , ErrorString ( error ) ) ) include_lines = statemachine . string2lines ( rawtext , tab_width , convert_whitespace = True ) # default lexer to ' text ' lexer = self . options . get ( 'lexer' , 'text' ) self . options [ 'source' ] = path codeblock = Pygments ( self . name , [ lexer ] , # arguments { } , # no options for this directive include_lines , # content self . lineno , self . content_offset , self . block_text , self . state , self . state_machine ) return codeblock . run ( )
def run_LDA ( df ) : """Run LinearDiscriminantAnalysis on input dataframe ( df ) and return transformed data , scalings and explained variance by discriminants ."""
# Prep variables for sklearn LDA X = df . iloc [ : , 1 : df . shape [ 1 ] ] . values # input data matrix y = df [ "Condition" ] . values # data categories list # Calculate LDA sklearn_lda = LDA ( ) X_lda_sklearn = sklearn_lda . fit_transform ( X , y ) try : exp_var = sklearn_lda . explained_variance_ratio_ except AttributeError as ae : print ( "\n{}: explained variance cannot be computed.\nPlease check this GitHub PR:" " https://github.com/scikit-learn/scikit-learn/pull/6027" . format ( ae ) ) return X_lda_sklearn , y , "NA" return X_lda_sklearn , y , exp_var
def set_connection_ip_list ( addresses = None , grant_by_default = False , server = _DEFAULT_SERVER ) : '''Set the IPGrant list for the SMTP virtual server . : param str addresses : A dictionary of IP + subnet pairs . : param bool grant _ by _ default : Whether the addresses should be a blacklist or whitelist . : param str server : The SMTP server name . : return : A boolean representing whether the change succeeded . : rtype : bool CLI Example : . . code - block : : bash salt ' * ' win _ smtp _ server . set _ connection _ ip _ list addresses = " { ' 127.0.0.1 ' : ' 255.255.255.255 ' } "'''
setting = 'IPGrant' formatted_addresses = list ( ) # It ' s okay to accept an empty list for set _ connection _ ip _ list , # since an empty list may be desirable . if not addresses : addresses = dict ( ) _LOG . debug ( 'Empty %s specified.' , setting ) # Convert addresses to the ' ip _ address , subnet ' format used by # IIsIPSecuritySetting . for address in addresses : formatted_addresses . append ( '{0}, {1}' . format ( address . strip ( ) , addresses [ address ] . strip ( ) ) ) current_addresses = get_connection_ip_list ( as_wmi_format = True , server = server ) # Order is not important , so compare to the current addresses as unordered sets . if set ( formatted_addresses ) == set ( current_addresses ) : _LOG . debug ( '%s already contains the provided addresses.' , setting ) return True # First we should check GrantByDefault , and change it if necessary . current_grant_by_default = _get_wmi_setting ( 'IIsIPSecuritySetting' , 'GrantByDefault' , server ) if grant_by_default != current_grant_by_default : _LOG . debug ( 'Setting GrantByDefault to: %s' , grant_by_default ) _set_wmi_setting ( 'IIsIPSecuritySetting' , 'GrantByDefault' , grant_by_default , server ) _set_wmi_setting ( 'IIsIPSecuritySetting' , setting , formatted_addresses , server ) new_addresses = get_connection_ip_list ( as_wmi_format = True , server = server ) ret = set ( formatted_addresses ) == set ( new_addresses ) if ret : _LOG . debug ( '%s configured successfully: %s' , setting , formatted_addresses ) return ret _LOG . error ( 'Unable to configure %s with value: %s' , setting , formatted_addresses ) return ret
def console_get_height_rect ( con : tcod . console . Console , x : int , y : int , w : int , h : int , fmt : str ) -> int : """Return the height of this text once word - wrapped into this rectangle . Returns : int : The number of lines of text once word - wrapped . . . deprecated : : 8.5 Use : any : ` Console . get _ height _ rect ` instead ."""
return int ( lib . TCOD_console_get_height_rect_fmt ( _console ( con ) , x , y , w , h , _fmt ( fmt ) ) )
def _set_rightMargin ( self , value ) : """value will be an int or float . Subclasses may override this method ."""
bounds = self . bounds if bounds is None : self . width = value else : xMin , yMin , xMax , yMax = bounds self . width = xMax + value
def qAx ( mt , x , q ) : """This function evaluates the APV of a geometrically increasing annual annuity - due"""
q = float ( q ) j = ( mt . i - q ) / ( 1 + q ) mtj = Actuarial ( nt = mt . nt , i = j ) return Ax ( mtj , x )
def wrap_response ( resp , api_call ) : """Wrap the requests response in an ` ApiResponse ` object : param object resp : response object provided by the ` requests ` library . : param object api _ call : Api Call : return : An ` ApiResponse ` object that wraps the content of the response . : rtype : object , list or dict"""
try : js_resp = resp . json ( ) if resp . ok : if "items" in js_resp . keys ( ) : r = ApiListResponse ( js_resp [ "items" ] ) else : r = ApiDictResponse ( js_resp ) if "paging" in js_resp . keys ( ) : cursors = js_resp . get ( "paging" , { } ) . get ( "cursors" , { } ) if "after" in cursors . keys ( ) : r . next = api_call ( after = cursors [ "after" ] ) if "before" in cursors . keys ( ) : r . previous = api_call ( after = cursors [ "before" ] ) else : r = ApiDictResponse ( js_resp ) if "error" in js_resp . keys ( ) : r . error = js_resp [ 'error' ] elif "message" in js_resp . keys ( ) : r . error = js_resp [ 'message' ] # common to all r . status_code = resp . status_code r . headers = resp . headers return r except : return resp
def windows ( self , window_size = 60 , context_len = 90 , step = 10 ) : '''Walk through the sequence of interest in windows of window _ size , evaluate free ( unbound ) pair probabilities . : param window _ size : Window size in base pairs . : type window _ size : int : param context _ len : The number of bases of context to use when analyzing each window . : type context _ len : int : param step : The number of base pairs to move for each new window . : type step : int'''
self . walked = _context_walk ( self . template , window_size , context_len , step ) self . core_starts , self . core_ends , self . scores = zip ( * self . walked ) return self . walked
def reference_text ( ref ) : '''Convert a single reference to plain text format Parameters ref : dict Information about a single reference'''
ref_wrap = textwrap . TextWrapper ( initial_indent = '' , subsequent_indent = ' ' * 8 ) s = '' if ref [ 'type' ] == 'unpublished' : s += ref_wrap . fill ( ', ' . join ( ref [ 'authors' ] ) ) + '\n' s += ref_wrap . fill ( ref [ 'title' ] ) + '\n' s += ref_wrap . fill ( ref [ 'note' ] ) + '\n' elif ref [ 'type' ] == 'article' : s += ref_wrap . fill ( ', ' . join ( ref [ 'authors' ] ) ) + '\n' s += ref_wrap . fill ( ref [ 'title' ] ) + '\n' s += '{}, {}, {} ({})' . format ( ref [ 'journal' ] , ref [ 'volume' ] , ref [ 'page' ] , ref [ 'year' ] ) s += '\n' + ref [ 'doi' ] elif ref [ 'type' ] == 'incollection' : s += ref_wrap . fill ( ', ' . join ( ref [ 'authors' ] ) ) s += ref_wrap . fill ( '\n{}' . format ( ref [ 'title' ] ) ) s += ref_wrap . fill ( '\nin \'{}\'' . format ( ref [ 'booktitle' ] ) ) if 'editors' in ref : s += ref_wrap . fill ( '\ned. ' + ', ' . join ( ref [ 'editors' ] ) ) if 'series' in ref : s += '\n{}, {}, {} ({})' . format ( ref [ 'series' ] , ref [ 'volume' ] , ref [ 'page' ] , ref [ 'year' ] ) if 'doi' in ref : s += '\n' + ref [ 'doi' ] elif ref [ 'type' ] == 'techreport' : s += ref_wrap . fill ( ', ' . join ( ref [ 'authors' ] ) ) s += ref_wrap . fill ( '\n{}' . format ( ref [ 'title' ] ) ) s += '\n\'{}\'' . format ( ref [ 'institution' ] ) s += '\nTechnical Report {}' . format ( ref [ 'number' ] ) s += '\n{}' . format ( ref [ 'year' ] ) if 'doi' in ref : s += '\n' + ref [ 'doi' ] elif ref [ 'type' ] == 'misc' : s += ref_wrap . fill ( ', ' . join ( ref [ 'authors' ] ) ) + '\n' s += ref_wrap . fill ( ref [ 'title' ] ) if 'note' in ref : s += '\n' + ref [ 'note' ] if 'doi' in ref : s += '\n' + ref [ 'doi' ] else : raise RuntimeError ( 'Cannot handle reference type {}' . format ( ref [ 'type' ] ) ) return s
def get_data ( self , file_id ) : """Acquires the data from the table identified by the id . The file is read only once , consecutive calls to this method will return the sale collection . : param file _ id : identifier for the table : return : all the values from the table"""
if file_id not in self . _file_values : file_contents = 'cwr_%s.csv' % file_id self . _file_values [ file_id ] = self . _reader . read_csv_file ( file_contents ) return self . _file_values [ file_id ]
def check_git ( ) : """Check if git command is available ."""
try : with open ( os . devnull , "wb" ) as devnull : subprocess . check_call ( [ "git" , "--version" ] , stdout = devnull , stderr = devnull ) except : raise RuntimeError ( "Please make sure git is installed and on your path." )
def rot_rads_v2 ( vec_a , rads ) : """Rotate vector by angle in radians ."""
x = vec_a . x * math . cos ( rads ) - vec_a . y * math . sin ( rads ) y = vec_a . x * math . sin ( rads ) + vec_a . y * math . cos ( rads ) return Vec2 ( x , y )