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def plot _ program ( ephem, start _ date = none, stop _ date = none, style ='localtime ', include _ monsoon = false, include _ full _ moon = false, include _ twilight = true, night _ start = - 6. 5, night _ stop = 7. 5, num _ points = 500, bg _ color ='lightblue ', save = none ) : import matplotlib. pyplot as plt impor...
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def test _ addition _ scalar ( ctx _ factory ) : context = ctx _ factory ( ) queue = cl. commandqueue ( context ) a = np. array ( [ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 ] ). astype ( np. float32 ) a _ gpu = cl _ array. to _ device ( queue, a ) a _ added = ( 7 + a _ gpu ). get ( ) assert ( 7 + a = = a _ added ). all ( )
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def delete ( self ) : self. _ api. post ( self. _ api. url + " dodelete " )
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def test _ none _ kwargs ( self ) : with self. assertraises ( typeerror ) : basemodel ( id = none, created _ at = none, updated _ at = none )
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def save ( self ) : filelen = 0x3c + sum ( 4 + 0xc + len ( s. data ) for s in self. waves ) data = bytearray ( ) data. extend ( _ common. nds _ std _ file _ header. pack ( b'swar ', 0xfeff, 0x100, filelen, 0x10, 1 ) ) data. extend ( struct. pack ('< 4si32xi ', b'data ', filelen - 0x10, len ( self. waves ) ) ) lenoffset...
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def _ _ init _ _ ( self ) : self. data = none self. file _ name ='data. json'self. indexer = indexer ( ) self. read _ data ( )
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def delete _ group ( self, group _ id, logged _ in _ user _ id, access _ token, client _ token, * * kwargs ) : kwargs ['_ return _ http _ data _ only'] = true if kwargs. get ('callback') : return self. delete _ group _ with _ http _ info ( group _ id, logged _ in _ user _ id, access _ token, client _ token, * * kwargs ...
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def maddpg ( config ) : scores _ window = deque ( maxlen = config. window ) scores = [ ] ma _ scores = [ ] std _ scores = [ ] solved = false # instantiate two agents in a list agents = [ agent ( config ) for _ in range ( config. n _ agents ) ] for i _ episode in range ( 1, config. n _ episodes + 1 ) : env _ info = conf...
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def test _ unkown _ shape _ print ( self, stateful, capfd ) : samples = np. ones ( ( 2, 3, 4, 5 ) ) result = result ( samples, is _ stateful = stateful ) print ( result ) out, err = capfd. readouterr ( ) assert " modes " not in out assert " shots " not in out assert " timebins " not in out assert f " contains state = {...
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def _ files _ as _ cmd ( self, files ) : tokens = self. _ tokenise _ files _ expression ( files ) return self. _ tokenised _ files _ expression _ to _ cmd ( tokens )
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def set _ defaults ( self ) : logger. debug ( " setting defaults " ) self. set _ globals ( ) current _ dir = os. path. dirname ( _ _ file _ _ ) for dirpath, _, filenames in os. walk ( current _ dir ) : default _ files = [ fname for fname in filenames if fname. endswith ( " _ defaults. py " ) ] if not default _ files : ...
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def all ( self ) : return list ( self. data. values ( ) )
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def next _ player ( self ) : if " b " in self. properties or " ab " in self. properties : # root or black moved return " w " else : return " b "
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def headers ( self ) : return self. _ _ headers. copy ( )
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async def reset _ table _ moderator _ application ( self, ctx ) - > none : if not await self. table _ moderator _ application _ exists ( ) : return await ctx. send ( " * * table ` moderatorapplication ` doesn't exist yet! * * " ) mycursor, db = await the _ database ( ) await mycursor. execute ( " delete from moderatora...
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def factor ( self ) : token = self. c _ token if token. type = = integer : self. eat ( integer ) return token. value elif token. type = = lpar : self. eat ( lpar ) res = self. expr ( ) self. eat ( rpar ) return res
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def _ get _ gallery _ folders ( self, page _ idx ) : return self. _ api ( " / gallery / folders ", get _ data = { " username " : self. user, " offset " : page _ idx * daexplorer. max _ items _ per _ request, " limit " : daexplorer. max _ items _ per _ request, " mature _ content " : true } )
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def gettemperaturef ( ) : andor _ solis. gettemperaturef. restype = ctypes. c _ uint temperature = ctypes. c _ float ( ) result = andor _ solis. gettemperaturef ( ctypes. byref ( temperature ) ) check _ status ( result ) status = _ sc [ result ] return float ( temperature. value ), str ( status )
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def add _ travel _ fee ( request ) : if request. user. is _ stylist = ='yes': if request. method = ='post': appointment = appointment. objects. get ( pk = request. post. get ('appointment _ pk') ) if ( appointment. status is not appointment. status _ completed ) and ( appointment. status is not appointment. status _ ac...
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def origin _ user _ options ( self ) : return self. _ _ user _ options _ string
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def prompt _ for _ spacing ( ) : num = input ( " please choose the board spacing : " ) return num
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def clean _ df ( df ) : text = df ['title'] + " " + df ['content'] df _ clean = pd. dataframe ( [ clean _ text ( i ) for i in text ] ) df _ clean. columns = [ " text " ] # df _ clean [ " tags " ] = df [ " tags " ] df _ clean = pd. concat ( [ df _ clean, pd. dataframe ( df [ " tags " ] ) ], axis = 1, sort = false ) retu...
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def gettwitterconfig ( ) : config = configparser. configparser ( ) config. read ( twitter _ api _ config _ file ) return config
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def _ dispatch _ push _ notification ( self, message, from _ myself = false ) : header = message ['header'] # type : dict payload = message ['payload'] # type : dict # identify the uuid of the target device by looking at the from field of the message header dev _ uuid = header ['from']. split ('/') [ 2 ] # let's interc...
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def not _ found _ error ( msg ) : status _ code = 404 message = {'status': status _ code,'message': msg } resp = jsonify ( message ) resp. status _ code = status _ code return resp
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def registra _ monedas ( carga _ rapida = false ) : from teritorio import currencies from cacao _ accounting. contabilidad. registros. moneda import registromoneda log. debug ( " iniciando carga de base monedas a la base de datos. " ) moneda = registromoneda ( ) if carga _ rapida : nio = transaccion ( registro = " mone...
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def get _ user _ by _ email ( self, email ) : users _ list = user ( self. db ). list ( email = email ) if len ( users _ list ) = = 0 : return none if len ( users _ list ) > 1 : raise pysaaerror ( " duplicate email % s, it must be unique " % email ) return users _ list [ 0 ]
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def describe _ table ( self, tablename ) : self. do _ describe _ table ( tablename, false )
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def topic _ matches _ sub ( sub, topic ) : result = true multilevel _ wildcard = false slen = len ( sub ) tlen = len ( topic ) if slen > 0 and tlen > 0 : if ( sub [ 0 ] = ='$'and topic [ 0 ]! ='$') or ( topic [ 0 ] = ='$'and sub [ 0 ]! ='$') : return false spos = 0 tpos = 0 while spos < slen and tpos < tlen : if sub [ ...
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def define _ treatment _ wells ( exclude _ outer = 1, plate _ dims = [ 16, 24 ] ) : cols = [ " % 02d " % s for s in range ( 1, plate _ dims [ 1 ] + 1 ) ] rows = [ chr ( 65 + n ) for n in range ( plate _ dims [ 0 ] ) ] if exclude _ outer : rows = rows [ exclude _ outer : - exclude _ outer ] cols = cols [ exclude _ outer...
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def intenzitet ( a, b, c ) : return ( a * a + b * b + c * c ) * * 0. 5
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def create _ datasets ( code, spark ) : label _ header = config [ code ] ['label _ header'] title _ header = config [ code ] ['title _ header'] id _ col = config [ code ] ['id _ col'] dl = dataloader ( code = code, spark = spark, sample = true, lim = none ) dl _ full = dataloader ( code = code, spark = spark, sample = ...
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def generate _ scheme _ function ( annotations, genes ) : annotations _ comp ='( list'for a in annotations : if not ( a. filters is none ) : filters = " " for f in a. filters : if f. filter = ='parents': filters + = f. value else : filters + ='\ "'+ f. value +'\ "'annotations _ comp + ='( { fn _ name } { filters } ) '....
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def list _ objects ( prefix ) : objects = minio _ client. list _ objects ( bucket _ name = bucket _ name, prefix = prefix, recursive = true, ) return objects
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def outputpath ( self ) : # begin by calling longestpath ( ) to find the path with the highest scores self. longestpath ( ) # insert the last node the last node into the path thisnode = self. endnode self. path. insert ( 0, self. endnode ) # iterate through the max predecessors for each node while thisnode! = self. sta...
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def step2d ( ystart, ystop, ysteps, xstart, xstop, xsteps, count _ time, snake = true, *, x3m = true, * * kwargs ) : dets = [ sclr1 ] # if xrd : # dets. append ( pe1 ) if x3m : dets. append ( xs ) yield from bps. mov ( xs. total _ points, xsteps * ysteps ) yield from set _ count _ time ( count _ time ) yield from bp. g...
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def func ( self ) : session = self. caller num _ guests = 1 playerlist = accountdb. objects. typeclass _ search ( guest ) guest = none bans = serverconfig. objects. conf ( " server _ bans " ) addr = session. address if bans and ( any ( tup [ 2 ]. match ( session. address ) for tup in bans if tup [ 2 ] ) ) : # this is a...
[ -0.6184419393539429, 0.5196551084518433, 0.8992584347724915, 1.057801365852356, 0.5079922676086426, -0.24051600694656372, 0.20850464701652527, -0.24960820376873016, 0.6343717575073242, 0.794922947883606, 0.05903356894850731, 0.7136548757553101, -0.5659583210945129, -0.12880422174930573, ...
def export ( self, filename : str, format : str = " tfrecord ", ) : try : import tensorflow as tf # noqa : f401 except importerror : logger. error ( " tensorflow needs to be installed to be able to return tensorflow tensors. " ) # from https : / / www. tensorflow. org / tutorials / load _ data / tfrecord def _ bytes _ ...
[ 0.12954436242580414, 0.08657058328390121, 0.6083860993385315, 0.26843345165252686, -0.06531385332345963, -0.6851586699485779, 0.08127518743276596, -0.7297247052192688, 0.1318267434835434, -0.08188436180353165, -0.2087596356868744, 0.8036196231842041, -0.3441431224346161, 0.3066698312759399...
def train ( self, x, labels, n _ epochs = 100, n _ batch = 128, reporting _ period = 10, n _ critic = 5 ) : bat _ per _ epo = int ( x. shape [ 0 ] / n _ batch ) half _ batch = int ( n _ batch / 2 ) # for recording metrics. self. g _ loss _ authenticity = np. zeros ( ( n _ epochs * bat _ per _ epo, 1 ) ) self. g _ loss ...
[ -1.0774509906768799, 0.5221097469329834, 0.8779773116111755, -0.14102771878242493, -0.08728393912315369, 0.6715194582939148, 0.05689190700650215, 0.18503528833389282, -0.7561957240104675, 0.17636224627494812, -0.5165092349052429, -0.17369785904884338, 0.6925593614578247, -0.133835673332214...
def _ _ init _ _ ( self ) : self. rsync = sh. rsync. bake ('- ah')
[ 1.3628517389297485, 0.7181689739227295, 0.47510164976119995, 1.2302039861679077, 0.32690030336380005, -0.3668273091316223, -0.07860720902681351, 1.0140539407730103, 0.10194041579961777, -0.5550312995910645, -0.21425406634807587, 0.30549752712249756, 0.6489596366882324, 0.6444388628005981, ...
def played ( self ) : return self. _ game _ played
[ 0.09770028293132782, -0.44451457262039185, 0.49134793877601624, -0.15035425126552582, 1.2245055437088013, 0.9533805251121521, 0.10216832160949707, -0.561869204044342, -0.029835006222128868, 0.01825951226055622, -0.43559232354164124, -0.35015103220939636, -0.05258483067154884, -0.8569975495...
def train ( self, train _ set, val _ set, batch _ size, learning _ rate, n _ iterations, n _ test ) : # setup generators train _ gen = mnist _ data _ generator ( dset = train _ set, batch _ size = batch _ size ) val _ gen = mnist _ data _ generator ( dset = val _ set, batch _ size = n _ test ) # train for n _ iteration...
[ 0.10368555039167404, 0.7002289891242981, 0.4103468954563141, 0.5272262096405029, -0.6756660342216492, 0.014439073391258717, 0.02202475816011429, -0.06534260511398315, -0.43505969643592834, -0.2697870433330536, 0.418650358915329, 0.07780113071203232, 0.012765402905642986, 0.4954733550548553...
async def se ( self, ctx, name = none ) : files = [ f for f in listdir ( " soundeffects / " ) if isfile ( join ( " soundeffects / ", f ) ) ] if name is not none : files = list ( filter ( lambda string : name in string, files ) ) if len ( files ) = = 0 : await ctx. send ( " can't find the sound effect you asked for! " )...
[ 0.14508412778377533, 0.28579849004745483, 0.5605164766311646, 0.4969313442707062, 0.37172260880470276, -0.23644568026065826, -0.34341588616371155, -0.042320650070905685, 0.7814598083496094, -0.23760943114757538, -0.3368835747241974, 0.38326606154441833, -0.9013437032699585, 0.4507987201213...
def preprocess _ frame ( screen : np. ndarray, exclude : union [ tuple, none ] = none, output : union [ int, none ] = none ) - > np. ndarray : # convert image to gray scale screen = cv2. cvtcolor ( screen, cv2. color _ rgb2gray ) if exclude : # crop screen [ up : down, left : right ] screen = screen [ exclude [ 0 ] : e...
[ -0.5115339159965515, 0.7750211358070374, 0.9331998825073242, 0.5065311193466187, -0.36282777786254883, -0.43454882502555847, 0.5662050843238831, -1.1269375085830688, 1.4560739994049072, 0.5281597971916199, 0.7265587449073792, 0.11154152452945709, 0.14237159490585327, 0.664607584476471, 0...
def vadwalk ( self ) : log. debug ( " executing volatility vadwalk plugin on " " { 0 } ". format ( self. memdump ) ) self. _ _ config ( ) if pid is not none : conf = copy. deepcopy ( self. config ) conf. pid = pid else : conf = self. config results = [ ] command = self. plugins [ " vadwalk " ] ( conf ) for task in comm...
[ -0.29192492365837097, -0.9794993996620178, 0.4689089357852936, -0.8347207307815552, 0.12607897818088531, -0.17635487020015717, 0.31744635105133057, -0.1663484126329422, 0.07211009413003922, -0.05108165368437767, -0.527233362197876, -0.28685083985328674, 0.07410605996847153, 0.8326950669288...
def gettabletrans ( kv, cu ) : kvtable = np. array ( [ 60, 80, 110, 125 ] ) cutable = np. array ( [ 0, 0. 1, 0. 2, 0. 3, 0. 6, 0. 9 ] ) lookup _ kv = find _ nearest ( kvtable, kv ) lookup _ cu = find _ nearest ( cutable, cu ) lookuparray = np. array ( [ [ 0. 80, 0. 82, 0. 82, 0. 82 ], [ 0. 84, 0. 84, 0. 86, 0. 87 ], [ ...
[ 0.10379009693861008, -0.23918703198432922, 1.1286691427230835, -0.39655283093452454, -0.8420839309692383, -0.1849769502878189, 0.2657955586910248, -0.7168291807174683, -0.6118870377540588, 1.0250866413116455, -0.2198486328125, 0.4139866232872009, -0.10216592997312546, -0.2937072813510895, ...
def copy _ if ( ary, predicate, extra _ args = [ ], preamble = " ", queue = none, wait _ for = none ) : if len ( ary ) > np. iinfo ( np. int32 ). max : scan _ dtype = np. int64 else : scan _ dtype = np. int32 extra _ args _ types, extra _ args _ values = extract _ extra _ args _ types _ values ( extra _ args ) knl = _ ...
[ 0.20569168031215668, 0.30540892481803894, 0.811458945274353, 1.0270792245864868, -1.3966403007507324, -0.47625356912612915, 0.24563078582286835, -0.3430041968822479, 0.06779767572879791, 1.210539698600769, 0.2542446553707123, 0.2625540792942047, 0.5636411309242249, 0.305570125579834, -0....
def _ _ str _ _ ( self ) : return self. header _ text
[ -0.0684482529759407, -2.1889090538024902, 0.7242748141288757, -0.6869141459465027, -1.1001194715499878, 0.6680023074150085, -0.8525452613830566, -0.4178568422794342, 0.1947007179260254, 0.2680610120296478, 0.18900468945503235, 0.37955042719841003, -0.3985401690006256, -0.9510363340377808, ...
def _ messages _ default ( self ) : from message import message messages = [ message ( author ='anon ', text ='work hard and be good to your mother'), ] return messages
[ -0.626934289932251, 0.11759345978498459, 0.23804950714111328, 0.9700123071670532, 1.3401373624801636, 0.10516500473022461, -0.517158031463623, -0.3920319974422455, -0.20306521654129028, -0.07736922800540924, -1.044089913368225, -0.40081676840782166, -0.7367368340492249, 1.2829198837280273,...
def _ compute _ subharmonics ( self, orders ) : return frequencymaths. compute _ subharmonics ( self. stimulation. frequencies, fmin = self. fmin, fmax = self. fmax, orders = orders )
[ 0.3275095820426941, 0.7691057920455933, 0.3265279531478882, 0.28382253646850586, -0.6403611898422241, -0.5316804647445679, -0.21818669140338898, -0.5456185936927795, -0.16002434492111206, -0.6274132132530212, 0.16640323400497437, 0.37414631247520447, 0.05696510523557663, -1.339678525924682...
def after _ state _ change ( self, old, new, errstr ='', params = { }, silent = false ) : return 0
[ -0.35570642352104187, -0.8801978230476379, 0.5031242966651917, 0.6126096248626709, -1.0301594734191895, -0.22276023030281067, -0.01920400746166706, 0.04303711652755737, 0.4151040017604828, 0.047214481979608536, -0.4569496512413025, 0.5724708437919617, 0.2500862181186676, 0.4645362496376037...
def _ _ ne _ _ ( self, other ) : if not isinstance ( other, model ) : return true return self. to _ dict ( )! = other. to _ dict ( )
[ -1.7673962116241455, 0.01796775497496128, 0.7451136112213135, 0.056895915418863297, -0.18422751128673553, 0.4192875921726227, -0.7190725207328796, -0.6185450553894043, -0.18611474335193634, 0.13414107263088226, -1.2597384452819824, -0.5653454661369324, -0.15131650865077972, 0.1208484470844...
def _ count _ data ( path ) : matcher = re. compile ( r'[ 0 - 9 ] + \. json') match = lambda name : bool ( matcher. match ( name ) ) names = os. listdir ( path ) n _ data = len ( list ( filter ( match, names ) ) ) return n _ data
[ -0.7260815501213074, 0.06932131201028824, 0.8300243020057678, -0.8550094962120056, -0.43028154969215393, 0.12115044891834259, 0.19408075511455536, 0.24357978999614716, -0.42339393496513367, 0.1600303202867508, -1.321747064590454, -0.06462103873491287, 1.1304802894592285, 0.223918616771698,...
def _ _ chunks ( i _ list, n ) : for i in range ( 0, len ( i _ list ), n ) : yield i _ list [ i : i + n ]
[ -1.106885552406311, 0.5200860500335693, 0.43093234300613403, 0.22687530517578125, -0.050697602331638336, 0.35954493284225464, -0.5754736661911011, 0.20568978786468506, -0.49274522066116333, -0.17004215717315674, -0.8086432218551636, -0.40329352021217346, -0.27091550827026367, 0.40825933218...
def srcdisconnected ( self, protocol ) : self. connections. pop ( protocol. conn _ id )
[ -0.41102421283721924, -0.4710533618927002, 0.2592654526233673, -1.141818642616272, 0.5319453477859497, -0.04130740836262703, -0.45332279801368713, -0.09068933129310608, 0.0116737587377429, -0.11094068735837936, -0.8869497179985046, 0.11230796575546265, -1.5696401596069336, -0.1146800145506...
def info ( ) : status ( ) l = [ " name ", " memory ", " consumers ", " messages ", " messages _ ready ", " messages _ unacknowledged " ] r = list _ queues ( " ". join ( l ) ). split ( " \ n " ) [ 1 ]. split ( " \ t " ) print r d = zip ( l, r ) pprint ( d )
[ 0.27790889143943787, -1.010995864868164, 0.6909299492835999, -0.39998605847358704, -0.09306443482637405, -0.17316491901874542, -0.4464949369430542, -0.1713886260986328, -0.3380337059497833, 0.6220511198043823, -0.6433454751968384, 1.0388007164001465, 0.38501229882240295, 0.8102130889892578...
def calc _ acc _ auto _ encoder ( original _ queries, reconstructed _ queries ) : l _ acc _ sent = [ ] for idx _ sent, raw _ sent in enumerate ( original _ queries ) : raw _ sent _ split = raw _ sent. split ( ) del raw _ sent _ split [ - 1 ] # get rid of '?'word _ hits = [ word in raw _ sent _ split for word in reconst...
[ -0.051314447075128555, -0.880469024181366, 0.5091467499732971, -0.7260571122169495, -0.9335324168205261, -0.49017566442489624, 1.1558146476745605, 0.8033801913261414, 0.4176916480064392, 0.7614814639091492, -0.24064765870571136, 0.5868256092071533, 0.4801202416419983, 0.5012181997299194, ...
def scale _ vector _ twice ( v, w ) : w1, w2 = w if w1 = = 1 and w2 = = 1 : return vector ( copy = v ), vector ( copy = v ) else : return ( vector ( index = v. _ index, value = [ w1 * x for x in v. _ value ] ), vector ( index = v. _ index, value = [ w2 * x for x in v. _ value ] ) )
[ -0.9711589217185974, -0.9617372155189514, 0.6789571642875671, -0.3714011311531067, -0.42022839188575745, -0.4754587709903717, -0.31166958808898926, -0.7734125256538391, 0.02130107767879963, 0.8466867208480835, -0.25424203276634216, 1.0173110961914062, 0.2348167598247528, 0.8741281032562256...
def hashcode ( self, * args ) : return _ topods. topods _ shape _ hashcode ( self, * args )
[ 0.308700829744339, -0.023535367101430893, 0.33101847767829895, 0.10876163840293884, 0.5247729420661926, 0.5660645365715027, 0.44035542011260986, -0.4275529086589813, -0.5263645648956299, 0.23049452900886536, 0.38834771513938904, -0.6293156147003174, -0.004857965279370546, -0.10115177929401...
def get _ tables ( self, *, replacements = none ) : tables = { } for i in range ( len ( self. sources ) ) : s = self. sources [ i ] if isinstance ( s, tabledescription ) : if replacements is not none and s. key in replacements : orig _ table = replacements [ s. key ] if s. column _ set! = orig _ table. column _ set : r...
[ -0.27720576524734497, 0.6396673321723938, 0.6967104077339172, 0.12690459191799164, -0.31047511100769043, -0.32249921560287476, 0.287191241979599, 0.15360601246356964, -0.562558650970459, -0.17194469273090363, -0.6675989627838135, 0.5121943950653076, -0.011286186054348946, 1.069479823112487...
async def createmarkdown ( gl, event ) : with open ( " markdown. txt ",'r') as file : line = file. read ( ) url = f " / projects / { event. project _ id } / issues / { event. object _ attributes ['iid'] } / notes " message = line await gl. post ( url, data = { " body " : message } )
[ 1.139125108718872, -0.2303752899169922, 0.6758275628089905, 0.03030574508011341, 0.9797785878181458, 1.6111247539520264, -0.5088692307472229, 0.40056416392326355, -0.9986350536346436, -0.12390533089637756, 0.045540813356637955, 0.40569305419921875, -0.5767396092414856, 0.41089800000190735,...
def test _ get _ feature _ parameter ( self ) : pass
[ -0.41991689801216125, 0.476921021938324, 0.23388491570949554, 1.6033905744552612, 0.9972969889640808, -0.34105566143989563, 1.7799924612045288, 0.05475162714719772, -0.15748515725135803, -0.4361839294433594, -0.6049938797950745, 1.0296549797058105, -0.32695499062538147, 0.5606216788291931,...
def update _ nn _ component ( c, candidates ) : ( v, vm ) = subgraphs. queues [ c ]. top ( ) # vm ∈ c { not a foreign nearest neighbor } # go through the queue until an edge is found between this node # and the set of candidates, updating the neighbors in the connected # components queue in the process. while vm not in...
[ -0.03272197023034096, -1.0336135625839233, 0.6427627205848694, -0.5657314658164978, -0.2125665843486786, 0.5418474674224854, -0.6015530824661255, -0.386722594499588, 0.0451706126332283, 0.6966463327407837, 0.0862814411520958, -0.15984943509101868, -0.35478395223617554, -0.00887188129127025...
def test _ space _ derivative ( self ) : n _ points = 3 dim = 3 curve = gs. random. rand ( n _ points, dim ) result = self. srv _ metric _ r3. space _ derivative ( curve ) delta = 1 / n _ points d _ curve _ 1 = ( curve [ 1 ] - curve [ 0 ] ) / delta d _ curve _ 2 = ( curve [ 2 ] - curve [ 0 ] ) / ( 2 * delta ) d _ curve...
[ 0.46421900391578674, 0.8438665270805359, 0.7553995251655579, 0.651896595954895, 0.11427411437034607, 1.1703174114227295, 0.5751674771308899, -0.16676081717014313, 0.07835040986537933, -0.4064180254936218, -0.2506866753101349, -0.18392525613307953, 0.322912335395813, 0.12844420969486237, ...
def cu _ 2d _ r4 ( dy, dk, t0, tn, y0, k0, h ) : return ( cu _ r4 ( dy, t0, tn, y0, h, k = cu _ r4 ( dk, t0, tn, k0, h / 2 ) ) )
[ -0.424087256193161, -0.49710410833358765, 0.500519871711731, -0.017546920105814934, -0.23134398460388184, -0.7931729555130005, -0.06627944856882095, -0.2000221163034439, -1.753483772277832, -0.042400579899549484, 0.17283186316490173, -0.5546691417694092, 0.2431926429271698, 0.1539230048656...
def create _ dummy _ computation _ tensorflow _ identity ( ) : type _ spec = tf. float32 value = tensorflow _ computation _ factory. create _ identity ( type _ spec ) type _ signature = computation _ types. functiontype ( type _ spec, type _ spec ) return value, type _ signature
[ -0.10108048468828201, -0.10028529167175293, 0.5264666080474854, 0.1699347347021103, 1.737434983253479, 0.2510005831718445, 0.8407934904098511, -0.6149935126304626, -0.8358941674232483, 0.07258439064025879, -1.1652448177337646, -0.02355412021279335, -0.0573989562690258, 0.17912256717681885,...
def _ _ init _ _ ( self, encoding = none, decode _ errors = none ) : if decode _ errors is none : decode _ errors = default _ decode _ errors if encoding is none : encoding = sys. getdefaultencoding ( ) self. decode _ errors = decode _ errors self. encoding = encoding
[ 0.026123126968741417, 0.13687576353549957, 0.29227012395858765, 0.1727849245071411, 0.12149876356124878, -0.9326590299606323, -0.698809802532196, 0.6902546286582947, 0.4439643919467926, -1.4572649002075195, -0.8662336468696594, 0.25661981105804443, 0.22210483253002167, 0.2505568861961365, ...
def get _ biases ( self ) : bias _ scalars = [ ] for b in self. biases : bias _ scalars. append ( b [ 0, 0 ] ) return bias _ scalars
[ 0.09746374934911728, -0.33491772413253784, 0.3454188108444214, 1.1519709825515747, 1.0198945999145508, 0.6529353857040405, -0.7297354340553284, 0.1506805419921875, -0.5863780975341797, 0.5448394417762756, -0.7360853552818298, 1.9876124858856201, -0.5298659801483154, 0.6610605716705322, -...
def all ( cls, index = none, limit = none ) : hits = super ( ). all ( as _ hit = true, index = index, limit = limit ) # return return [ cls. from _ hit ( hit ) for hit in hits ]
[ -0.21558736264705658, 0.22647616267204285, 0.6195399761199951, 0.8075019717216492, 1.0916264057159424, 0.3035861849784851, -0.3444022536277771, 0.1907949149608612, 0.47725358605384827, -0.5039845108985901, 0.23071277141571045, 0.439540296792984, 0.37816232442855835, -0.7680511474609375, ...
def send _ all _ letters ( self ) : # ask for the directory to save the letters to print ('\ nthe current directory is % s \ n'% os. getcwd ( ) ) new _ dir = self. feedback ('type the directory to save the letters in'' ( blank entry defaults to the current directory ) :') try : full _ dir _ name = self. collection. sav...
[ -0.67547208070755, 0.04502751678228378, 0.4545896351337433, -0.2435067594051361, 0.8659469485282898, 0.4672708809375763, 0.905712366104126, -0.30308130383491516, -0.1673995554447174, 0.1152525544166565, -0.5808988809585571, 1.1249885559082031, -0.579585075378418, 0.9349355101585388, 0.07...
def apply _ lpf ( self, imdata, kernel = ( 1 / 16 ) * np. array ( [ [ 1, 2, 1 ], [ 2, 4, 2 ], [ 1, 2, 1 ] ] ), plotflag = false ) : a = imdata. copy ( ) # copy of dicom image imdata _ conv = ndimage. convolve ( a, kernel, mode ='constant ', cval = 0. 0 ) # convolution of image and kernel # display image and filtered im...
[ 0.5922324657440186, -0.029144104570150375, 0.8270350098609924, -0.31102755665779114, -0.9773696660995483, -0.07254938781261444, -0.11305838078260422, 0.11018697917461395, 0.3297087848186493, -0.32008177042007446, 0.8948329091072083, 0.4566478431224823, -0.4380253851413727, 0.44371226429939...
def recipe _ image _ upload _ url ( recipe _ id ) : return reverse ('recipe : recipe - upload - image ', args = [ recipe _ id ] )
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def convert _ to _ py ( self, x, t ) : n = self. norms. get ( t, t ) ctx = {'type': self. cython _ type ( t ),'var': x,'nptypes': [ ],'classname': self. classname ( t ),'funcname': self. funcname ( t ) } if n in self. _ to _ py _ converters : # basic type or str n0 = ( ) decl, body, expr = self. _ to _ py _ converters ...
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def handle _ operation ( operation ) : if operation = = " register " : register ( ) if operation = = " retrieve " : retrieve ( ) if operation = = " dump " : dump ( )
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def _ _ init _ _ ( self, ctid, outer _ runner ) : self. ctid = ctid self. outer _ runner = outer _ runner
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def fit _ model ( self, parameter _ distribution, time, fit _ function _ electrons, parameters _ electron, fit _ function _ proton = none, parameters _ proton = none, energy _ range = none ) : # load everything into the class self. electron _ fit _ function = fit _ function _ electrons self. proton _ fit _ function = f...
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def tick1on ( self ) : # noqa : n802 return self. _ tick1on and self. _ need _ lower ( )
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def load _ tests ( loader, tests, ignore ) : tests. addtests ( doctest. doctestsuite ( sfc _ models. equation ) ) return tests
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def test _ get _ alumno _ admin _ no _ existente _ o _ distinta _ institucion ( self ) : self. client. force _ authenticate ( user = self. user _ admin ) id _ alumno = alumno. objects. get ( dni = 5 ). id response = self. client. get ( f " / api / alumnos / { id _ alumno } / " ) self. assertequal ( response. status _ c...
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def getelementinfo ( self, baseschema, overrides, verbose = none ) : verbosesav = none if verbose is not none : verbosesav = self. verbose self. verbose = verbose verbose = self. verbose elementdefs = { } self. elementdefs = elementdefs overrides = overrides if none in overrides else ( [ none ] + list ( overrides ) ) f...
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def test _ makeconnectionlogtraffic ( self ) : self. factory. logtraffic = true self. xmlstream. dispatch ( self. xmlstream, xmlstream. stream _ connected _ event ) self. assertnotidentical ( none, self. xmlstream. rawdatainfn ) self. assertnotidentical ( none, self. xmlstream. rawdataoutfn )
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def findfullycoupledwithsameflux ( self, fctable = none ) : if fctable is none : raise attributeerror ('fctable missing!') fcratios = self. _ _ computefullycoupledratios ( fctable ) fcratios [ np. where ( fcratios! = 1 ) ] = 0 equalflux = [ ] for column in range ( np. size ( fcratios, 1 ) ) : rxns = np. where ( fcratio...
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def _ fitgh _ chi2 ( par, x, data ) : return np. sum ( ( data. ravel ( ) - gausshermite ( x, par ) ) * * 2 )
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def _ _ init _ _ ( self, x : num, y : num, z : num ) : super ( ). _ _ init _ _ ( x, y ) self. z = z
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def permute _ by _ pt ( jet, root _ id = none ) : # ensure that the left sub - jet has always a larger pt than the right if root _ id is none : root _ id = jet [ " root _ id " ] if jet [ " tree " ] [ root _ id ] [ 0 ]! = - 1 : left = jet [ " tree " ] [ root _ id ] [ 0 ] right = jet [ " tree " ] [ root _ id ] [ 1 ] pt _...
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def calc _ variance ( polybasis, u ) : p, n = u. shape var = np. zeros ( ( n, ) ) for s in range ( 1, p ) : chi _ sq = eval _ chi _ s _ squared ( polybasis, s ) for j in range ( 1, n - 1 ) : var [ j ] + = ( u [ s, j ] * ( u [ s, j - 1 ] + u [ s, j ] + u [ s, j + 1 ] ) ) * chi _ sq return var
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def random _ make _ response ( self ) : resp _ 1 = " i'm an nba search bot, here to answer your nba queries. " resp _ 2 = " i'm a bot made by skekre98 in 2020, waiting for you to ask me real questions! " resp _ 3 = " i was built by skekre98 and the open source community in 2020! " resp _ 4 = " 2020 was crazy! but, its ...
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async def async _ get _ bytes _ total ( self, use _ cache = true ) : now = datetime. utcnow ( ) if use _ cache and self. _ trans _ cache _ timer and self. _ cache _ time > \ ( now - self. _ trans _ cache _ timer ). total _ seconds ( ) : return self. _ transfer _ rates _ cache rx = await self. async _ get _ rx ( ) tx = ...
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def check _ null _ or _ valid ( row _ data ) : no _ na = row _ data. dropna ( ) [ 1 : - 1 ] numeric = pd. to _ numeric ( no _ na ) ge0 = numeric > = 0 return ge0
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def _ get _ gallery _ all ( self, page _ idx ) : return self. _ api ( " / gallery / all ", get _ data = { " username " : self. user, " offset " : page _ idx * daexplorer. max _ items _ per _ request, " limit " : daexplorer. max _ items _ per _ request, " mature _ content " : true } )
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def _ checkconfigfile ( self ) : if osp. exists ( osp. join ( configdir, " dpmgr. conf " ) ) : self. _ config. read ( osp. join ( configdir, " dpmgr. conf " ) ) if not self. _ config. has _ section ( " ip " ) : self. _ config [ " ip " ] = { } self. _ config [ " ip " ] [ " default " ] = " digitalpaper. local " with open...
[ -0.7598292827606201, 0.03389507904648781, 0.5001534819602966, -0.534136950969696, 0.5341048836708069, 0.03482655808329582, 0.014254357665777206, 0.7729485630989075, -1.6561940908432007, 0.6975864171981812, -0.22099973261356354, -1.1565566062927246, -0.2628137469291687, 0.6970077753067017, ...
async def test _ datadisk _ list ( coresys : coresys ) : assert { drive. object _ path for drive in coresys. dbus. udisks2. drives } = = { " / org / freedesktop / udisks2 / drives / bjtd4r _ 0x97cde291 ", " / org / freedesktop / udisks2 / drives / generic _ flash _ disk _ 61bcddb6 ", " / org / freedesktop / udisks2 / d...
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def create _ connection ( cls ) : try : return mq. connect ( host = " localhost ", user = " root ", passwd = " 123456 " ) except exception as e : raise e
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def generate ( term ) : year = int ( term / len ( seasons ) ) + epoch season = term % len ( seasons ) return " % s % 04d " % ( seasons [ season ], year )
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def _ _ convert _ payload ( payload, headers ) : if payload = = u'' : payload = b'' if payload and isinstance ( payload, six. text _ type ) : headers. setdefault ('content - type ','text / plain ; charset = utf - 8') payload = payload. encode ('utf8') elif payload and not isinstance ( payload, six. binary _ type ) : ra...
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def add _ missing _ ntc ( count _ df, ntc _ df ) : ntc _ df ['family'] = ntc _ df ['guide _ id']. apply ( lambda x : _ find _ ntc _ family ( x ) ) ntc _ df = ntc _ df. merge ( count _ df, how ='left ', on ='guide _ id') ntc _ df _ group = ntc _ df. groupby ('family') ntc _ df _ list = [ ] for name, group _ df in ntc _ ...
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def deeplabv3 _ resnetd101b _ coco ( pretrained _ backbone = false, classes = 21, aux = true, * * kwargs ) : backbone = resnetd101b ( pretrained = pretrained _ backbone, ordinary _ init = false, bends = ( 3, ) ). features del backbone. final _ pool return get _ deeplabv3 ( backbone = backbone, classes = classes, aux = ...
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def get _ events ( bids _ dir, subject, run, reject = 5, return _ type ='block ', layout = none ) : if layout is none : layout = bids. bidslayout ( bids _ dir ) # get both events and images, check there is only one of each events = layout. get ( suffix ='events ', extension = '. tsv ', session ='postop ', return _ type...
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def get _ reviews _ by _ product ( product _ id : int, page : int = 1, db : session = depends ( get _ db ) ) : results = crud. get _ reviews _ by _ product ( db, product _ id = product _ id, page = page ) return paginatedresponse ( * * results )
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def filtercoloredcircles ( self, circles, color ) : if circles = = none : return none filtered = [ ] for c in circles : x, y = self. _ reversecoordinates ( c. x, c. y ) pixelcolor = self. getpixelat ( x, y ) if numpyimage. _ isrightcolor ( pixelcolor, color ) : filtered + = [ c ] return filtered
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