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def print_label_for_requisition(self, request, requisition): <NEW_LINE> <INDENT> if requisition.requisition_identifier: <NEW_LINE> <INDENT> self.print_label(request, requisition, 1)
Prints a requisition label.
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def _get_network_id(self): <NEW_LINE> <INDENT> return self.__network_id
Getter method for network_id, mapped from YANG variable /networks/network/network_id (network-id) YANG Description: Identifies a network.
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def rescale_by(self, factor): <NEW_LINE> <INDENT> for node in self.iter_descendants(): <NEW_LINE> <INDENT> node.length *= factor
Rescale the height of the tree by the given factor (equally on each branch). Args: factor (float): Scaling factor.
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def test_recipients_to_addresses_with_groups_inactive_members(self): <NEW_LINE> <INDENT> group1 = self.create_review_group('group1') <NEW_LINE> group2 = self.create_review_group('group2') <NEW_LINE> user1 = User.objects.create(username='user1', first_name='User', last_name='One') <NEW_LINE> user2 = User.objects.create(...
Testing generating addresses form recipients that are groups with inactive members
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@app.task(ignore_result=True) <NEW_LINE> def download_file(pk): <NEW_LINE> <INDENT> release_file = models.ReleaseFile.objects.get(pk=pk) <NEW_LINE> logger.info("Downloading %s", release_file.url) <NEW_LINE> proxies = None <NEW_LINE> if settings.LOCALSHOP_HTTP_PROXY: <NEW_LINE> <INDENT> proxies = settings.LOCALSHOP_HTTP...
Download the file reference in `models.ReleaseFile` with the given pk.
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def _get_dataset_filename(split_name, shard_id): <NEW_LINE> <INDENT> output_filename = FLAGS.output_filename % ( split_name, shard_id, FLAGS._NUM_SHARDS) <NEW_LINE> return os.path.join(FLAGS.output_dataset_dir, output_filename)
return data_filename like that /home/mao/Documents/datasets/flowers_train_00000-of-00005.tfrecord /home/mao/Documents/datasets/flowers_validation_00000-of-00005.tfrecord
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def load_breast_cancer_data(): <NEW_LINE> <INDENT> dataset = load_breast_cancer() <NEW_LINE> X = pd.DataFrame(dataset.data, columns=dataset.feature_names) <NEW_LINE> y = pd.DataFrame(dataset.target, columns=['y']) <NEW_LINE> return X, y
データセットを取得する 乳がんの診断結果 classification
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def __init__(self, cosmo, bias_params): <NEW_LINE> <INDENT> self.__cosmo = cosmo <NEW_LINE> self.__bias_params = bias_params
Packages all parameters for the cosmology and BiasParams object. Parameters ---------- cosmo : Cosmology bias_params : BiasParams
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@Operation.factory <NEW_LINE> def Log(a): <NEW_LINE> <INDENT> return np.log(a),
Logarithm op.
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def strip_fixed(fstr): <NEW_LINE> <INDENT> Fi = cStringIO.StringIO() <NEW_LINE> Fi.write(fstr) <NEW_LINE> Fi.seek(0) <NEW_LINE> Fo = cStringIO.StringIO() <NEW_LINE> Fhead = None <NEW_LINE> for line in Fi: <NEW_LINE> <INDENT> if line[:4] == "FIX:": <NEW_LINE> <INDENT> Fhead = string.strip(line) <NEW_LINE> Fo.write('\n')...
Take a psc file string and return two strings: (1) The file header containing the "FIX: " line and (2) the remainder of file. Parameters ---------- fstr : str String representation of psc file. Returns ------- tuple of str 1st element contains file header, second the remainder of the file. See also -------- ...
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def p_recursive(self, p): <NEW_LINE> <INDENT> if p[1] == "R": <NEW_LINE> <INDENT> p[0] = Recursive(None) <NEW_LINE> <DEDENT> else: <NEW_LINE> <INDENT> p[0] = Recursive(p[1])
recursive : 'R' | number
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def get_bodyfat(self, base_date=None, user_id=None, period=None, end_date=None): <NEW_LINE> <INDENT> return self._get_body('fat', base_date, user_id, period, end_date)
https://dev.fitbit.com/docs/body/#get-body-fat-logs base_date should be a datetime.date object (defaults to today), period can be '1d', '7d', '30d', '1w', '1m', '3m', '6m', '1y', 'max' or None end_date should be a datetime.date object, or None. You can specify period or end_date, or neither, but not both.
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def RIE(actives, scores, alpha): <NEW_LINE> <INDENT> N=len(actives) <NEW_LINE> n=sum(scores) <NEW_LINE> x = np.array(actives) <NEW_LINE> e = np.exp(-alpha*x) <NEW_LINE> summation = sum(e) <NEW_LINE> RIE = ((1/n)*summation)/((1/N)*((1-np.exp(-alpha))/np.exp(alpha/N-1))) <NEW_LINE> return RIE
Returns Robust Initial Enhancement
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def _evaluate(self,R,z,phi=0.,t=0.): <NEW_LINE> <INDENT> r2= R**2.+z**2. <NEW_LINE> r= nu.sqrt(r2) <NEW_LINE> return (0.5*nu.log(1+r2/self._a2) +self._a/r*nu.arctan(r/self._a))/self._a
NAME: _evaluate PURPOSE: evaluate the potential at R,z INPUT: R - Galactocentric cylindrical radius z - vertical height phi - azimuth t - time OUTPUT: Phi(R,z) HISTORY: 2015-12-04 - Started - Bovy (UofT)
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def __init__(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, __props__=None, __name__=None, __opts__=None): <NEW_LINE> <INDENT> if __name__ is not None: <NEW_LINE> <INDENT> warnings.warn("explicit use of __name__ is deprecated", DeprecationWarning) <NEW_LINE> resource_name = __name__ <NEW_L...
Create a Vpc resource with the given unique name, props, and options. :param str resource_name: The name of the resource. :param pulumi.ResourceOptions opts: Options for the resource.
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def wvar(x,w=None,ddof=1,robust=False): <NEW_LINE> <INDENT> if (w!=None): <NEW_LINE> <INDENT> assert len(w) == len(x), 'w must be the same length as x' <NEW_LINE> <DEDENT> return wcov(x,x,w,ddof,robust)
Weighted variance Calculate the variance of x using weights w. If ddof=1 (default), then the result is the unbiased (sample) variance when w=1. Args: x : array of values w : array of weights for each element of x; can be ommitted if robust=True ddof : scalar differential degrees of freedom (De...
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def apply_lighting_adjustment(self): <NEW_LINE> <INDENT> image = self.modification_information.image <NEW_LINE> min = -self.preference.lighting_factor <NEW_LINE> max = self.preference.lighting_factor <NEW_LINE> contrast_factor = int(min + random.random() * (max - min) + 1) <NEW_LINE> exposure_factor = int(min + random....
Adjust lighting of image by random factor in range specified by the user
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def run_service(self): <NEW_LINE> <INDENT> self.alerts_queue = Queue(maxsize=SERVICE_ALERT_QUEUE_SIZE) <NEW_LINE> self.thread_server = Thread(target=self._on_server_start) <NEW_LINE> self.thread_server.start() <NEW_LINE> try: <NEW_LINE> <INDENT> while self.thread_server.is_alive(): <NEW_LINE> <INDENT> try: <NEW_LINE> <...
Run the service and start an alert processing queue. .. seealso:: Use :func:`on_server_start` and :func:`on_server_shutdown` for starting and shutting down your service
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def send_message(chan, msg): <NEW_LINE> <INDENT> con.send(bytes("PRIVMSG {} :{}\r\n".format(chan, msg), "UTF-8"))
Send PRIVMSG to IRC.
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def parse_flow(self, flow): <NEW_LINE> <INDENT> fb = None <NEW_LINE> for k in self._flow_terms(flow): <NEW_LINE> <INDENT> fb = self.f_index(k) <NEW_LINE> if fb is not None: <NEW_LINE> <INDENT> break <NEW_LINE> <DEDENT> <DEDENT> if fb is None: <NEW_LINE> <INDENT> fn = flow['Name'] <NEW_LINE> <DEDENT> else: <NEW_LINE> <I...
Return a valid flowable name and a compartment object as a 2-tuple. To find the flowable: Start with the flow's link, then the flow's name, then the flow's cas. To return: preferentially return CAS number, then name if CAS is none. :param flow: :return:
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def get_NamespaceURI(self, index): <NEW_LINE> <INDENT> return super(IXMLNamespaces, self).get_NamespaceURI(index)
Method IXMLNamespaces.get_NamespaceURI INPUT index : long OUTPUT uri : BSTR*
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def drawShadedContours(xlist, ylist, zmatrix, levels): <NEW_LINE> <INDENT> dislin.conshd(xlist, len(xlist), ylist, len(ylist), zmatrix, levels, len(levels))
Draws contours with colors between contour lines.
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def put(self, local_file): <NEW_LINE> <INDENT> with open(local_file, "rb") as fd: <NEW_LINE> <INDENT> self.write(fd.read())
Copy a file from the controller to the instrument. :param local_file: :return:
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def getDict(self): <NEW_LINE> <INDENT> return { "name": self.name, "type": self.type, "time": self.formatTime(), "room": self.room }
return dictionary format notation for jsonifying the object
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def mayfly(x,b,t): <NEW_LINE> <INDENT> for i in range(t): <NEW_LINE> <INDENT> x = b*(1-x)*x <NEW_LINE> figure(num=1, figsize=(6, 5)) <NEW_LINE> plot(i,x,'c.') <NEW_LINE> title('Mayfly Population over Time') <NEW_LINE> xlabel('Time (Years)') <NEW_LINE> ylabel('Population (x)') <NEW_LINE> patch = mpatches.Patch(color='c'...
Function in which mayfly(x,b,tmin,tmax): x, population as percent of max, b, ratio of surviving offspring to females, t, Generations
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def getUrl(self): <NEW_LINE> <INDENT> return self.obj.o.getUrl(page=self.field.pageName, nav='no')
Returns the URL for going back to the initiator object, on the page showing self.field.
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def move_files_in_dir(src, dst): <NEW_LINE> <INDENT> logger.debug(u'Move files to directory %s %s', src, dst) <NEW_LINE> for f in glob(src): <NEW_LINE> <INDENT> dst_path = os.path.join(dst, os.path.basename(f)) <NEW_LINE> shutil.move(f, dst_path)
Move files or directories :param str src: source files or directories :param str dst: destination directory
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@click.group() <NEW_LINE> def cli(): <NEW_LINE> <INDENT> pass
Manage EMS
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def centered_alignment(k1: np.ndarray, k2: np.ndarray) -> float: <NEW_LINE> <INDENT> k1_centered = center_kernel(k1) <NEW_LINE> k2_centered = center_kernel(k2) <NEW_LINE> return alignment(k1_centered, k2_centered)
Centered kernel alignment Cortes et al. (2012)
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def diagnostics(self): <NEW_LINE> <INDENT> super(GMM, self).diagnostics() <NEW_LINE> self.plot_results(self.x_train, self.labels, self.model.means_, self.model.covariances_) <NEW_LINE> scikit_mixin.plot_silhouette(data=self.x_train, cluster_labels=self.labels)
Diagnostics for GMM. Generates a silhouette plot and a biplot of the clusters on the first 2 features.
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def on_save(self): <NEW_LINE> <INDENT> super(Users, self).on_save() <NEW_LINE> if self.settingsMode == 'tool': <NEW_LINE> <INDENT> for item in self.__editedItems__['added']: <NEW_LINE> <INDENT> item.itemObj.writeFile() <NEW_LINE> <DEDENT> for item in self.__editedItems__['edited']: <NEW_LINE> <INDENT> item.itemObj.writ...
Command launched when 'Save' QPushButton is clicked Save data
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def find_word(line, n, option=None): <NEW_LINE> <INDENT> excelude = ".,-?!\t\n-;'/" <NEW_LINE> for char in excelude: <NEW_LINE> <INDENT> line = line.replace(char, " ") <NEW_LINE> <DEDENT> words = line.split(" ") <NEW_LINE> found = [] <NEW_LINE> for word in words: <NEW_LINE> <INDENT> if len(word) == n: <NEW_LINE> <INDEN...
Assignment 3
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def movmean(X, n=1, axis=0, maskNAN=False): <NEW_LINE> <INDENT> ndim = X.ndim <NEW_LINE> if maskNAN: <NEW_LINE> <INDENT> mnan = np.isnan(X) <NEW_LINE> <DEDENT> if n==0: <NEW_LINE> <INDENT> return X <NEW_LINE> <DEDENT> if axis==1: <NEW_LINE> <INDENT> Xout = np.transpose( movmean( np.transpose(X), n)) <NEW_LINE> return X...
This function generates a moving mean ignoring nan along the axis dimension of X of oder n
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def p_command_stack(p): <NEW_LINE> <INDENT> commands.append({'op' : p[1], 'args' : None})
command : POP | PUSH
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def f_z(X, T, p): <NEW_LINE> <INDENT> (Nt, Nx) = X.shape <NEW_LINE> Ny = len(yids) <NEW_LINE> Nz = 1 + Nx + Ny <NEW_LINE> columns = ["time"] + xids + yids <NEW_LINE> Z = np.empty(shape=(Nt, Nz)) <NEW_LINE> Z[:, 0] = T <NEW_LINE> Z[:, 1:(Nx+1)] = X <NEW_LINE> for kt in range(Nt): <NEW_LINE> <INDENT> y = f_y(x=X[kt, :], ...
DataFrame of full timecourse of solution.
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def filter_list_of_tuples_which_contained_values_from_current_list_of_lists(input_hash_list=None, constraints_hash_list=None): <NEW_LINE> <INDENT> out = input_hash_list <NEW_LINE> for val_lst in constraints_hash_list: <NEW_LINE> <INDENT> out = filter_list_of_tuples_which_contained_data_from_list(input_list=out, list_wi...
Ex: input_hash_list = [ (1, 2, 4), (1, 3, 4), (1, 9, 4), (3, 2, 5), (1, 7, 6), (7, 2, 1), (1, 2, 4), (7, 1, 2), (8, 7, 2), (0, 1, 7), (2, 1, 7), ] bb = [ [1, 7], [1, 0], ] pre-return: [(1, 7, 6), (7, 2, 1), (7, 1, 2), (0, 1, 7), (2, 1, 7)] return: [(0, 1, 7)] :param ...
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def test_email_construction_without_optional_params(self): <NEW_LINE> <INDENT> listing = ( '1. Lead Data Scientist @ Brightwater Group\n' 'Link: http://ie.indeed.com/viewjob?jk=4da3f3ec1f781a3f\n' 'Location: Dublin\n' 'Snippet: Our client, a major, international banking brand, currently ' 'has a job opening for a lead ...
Test we construct a valid email when optional params are missing.
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def __init__(self, db_filename, interface): <NEW_LINE> <INDENT> self._interface = interface <NEW_LINE> self._sql_conn = sqlite3.connect(db_filename, check_same_thread=False) <NEW_LINE> self._sql = self._sql_conn.cursor()
Interface for the SQLite 3 Database that stores processed comments/submissions Args: db_filename (str): Filename of the SQLite 3 database interface (CLI): CLI for the bot to allow live updates.
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def use_drone_imgs(self): <NEW_LINE> <INDENT> self.cam = ARDroneCamera() <NEW_LINE> im = cv2.imread('tests/test_imgs/drone_dataset/test{}.png'.format(self.viewset.numViews)) <NEW_LINE> return im
For the test and demonstration purposes only, replaces camera images and parameters with ones from the dataset.
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def install_requires(): <NEW_LINE> <INDENT> skip_install_requires = environ.get('SKIP_INSTALL_REQUIRES') <NEW_LINE> if not skip_install_requires: <NEW_LINE> <INDENT> with open('requirements.pip') as r: <NEW_LINE> <INDENT> return r.readlines() <NEW_LINE> <DEDENT> <DEDENT> return []
Check for required packages
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def activityTimeInfo(self, *args): <NEW_LINE> <INDENT> return _ArNetworkingPy.ArServerInfoRobot_activityTimeInfo(self, *args)
activityTimeInfo(self, ArServerClient client, ArNetPacket packet)
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def predict(self, x): <NEW_LINE> <INDENT> probs = sigmoid(self._exp_dot(x)) <NEW_LINE> return (probs > 0.5).astype(np.int)
Return the predicted classes. :param x: (batch_size, num_features) :return: (batch_size)
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@app_views.route('/states/', strict_slashes=False, methods=['POST']) <NEW_LINE> def create_state(): <NEW_LINE> <INDENT> try: <NEW_LINE> <INDENT> states = request.get_json() <NEW_LINE> if states.get("name") is None: <NEW_LINE> <INDENT> return abort(400, 'Missing name') <NEW_LINE> <DEDENT> <DEDENT> except: <NEW_LINE> <IN...
define how to create a new state objects Returns: 201 on successful creation 400 "Not a JSON" if HTTP body request is not valid 404 if state_id is not linked to any State object
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def register_delete_thread_response(self, thread_id): <NEW_LINE> <INDENT> assert httpretty.is_enabled(), 'httpretty must be enabled to mock calls.' <NEW_LINE> httpretty.register_uri( httpretty.DELETE, "http://localhost:4567/api/v1/threads/{id}".format(id=thread_id), body=json.dumps({}), status=200 )
Register a mock response for DELETE on the CS thread instance endpoint
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def bt_save_favoris(user_current, id_produit, request): <NEW_LINE> <INDENT> produit = Produits.objects.get(id__exact=id_produit) <NEW_LINE> Favoris.objects.create( user=user_current, produits=produit, date_ajout=datetime.today, aff_index=False) <NEW_LINE> path_back = request.path <NEW_LINE> path_good = path_back.replac...
Saving in faovris
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def plotParticle(sequence,radar): <NEW_LINE> <INDENT> for i,item in enumerate(sequence): <NEW_LINE> <INDENT> z,p=item <NEW_LINE> z=Polar2Coor(z,radar) <NEW_LINE> plt.plot(p[:,0],p[:,1],'.',label='particles t%d'%(i)) <NEW_LINE> plt.plot(z[0],z[1],'*',label='measurement t%d'%(i)) <NEW_LINE> <DEDENT> plt.grid(linestyle='d...
各时刻的量测值和粒子群位置 :param sequence: [[z0,p0]...[zt,pt]] z0[2] p0[500,2] :param radar: [2] 雷达位置
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def test_follow_dont_allow_get_request(self): <NEW_LINE> <INDENT> foo = createUser("foo", "[email protected]", "example") <NEW_LINE> juan = createUser("juan", "[email protected]", "example") <NEW_LINE> c = Client() <NEW_LINE> c.login(username='foo', password='example') <NEW_LINE> response = c.get(f"/follow/juan") <NEW_LI...
*** Should a user follow another user via GET or PUT, return 404 response ***
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def create_tar_sr_il_abc(self): <NEW_LINE> <INDENT> self.create_tar_sr_il() <NEW_LINE> fragments_to_concat = [] <NEW_LINE> not_matched = self.tar_sr_il <NEW_LINE> for i in [self.abc_2, self.abc_1]: <NEW_LINE> <INDENT> entire_table = not_matched.merge(i, left_on=['icd_9'], right_on=['icd_9'], how='left', validate="m:1")...
Creates tar_sr_il as normally should and adds ABC categories to procedures.
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def __mul__(self, other): <NEW_LINE> <INDENT> from datatypes.integers.UInt import UInt <NEW_LINE> if (isinstance(other, UInt8)): <NEW_LINE> <INDENT> result = [] <NEW_LINE> for i in xrange(7, -1, -1): <NEW_LINE> <INDENT> arrayTemp = [] <NEW_LINE> result += [arrayTemp] <NEW_LINE> for k in xrange (0, 7-i): <NEW_LINE> <IND...
This method will multiply 2 UInt8. We override this operator to be able to write operations more easily The multiplication seems to work fine, however there may be a problem in the addition of two UInt Since the addition od two UInt is used in this method there may be some error see addition of UInts of different sizes...
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def read_a_shift_file(filename, parameters, res_incl=None, res_excl=None): <NEW_LINE> <INDENT> data = sc.loadtxt(filename, dtype=[('resonance_id', 'S10'), ('shift_ppb', 'f8'), ('shift_ppb_err', 'f8')]) <NEW_LINE> data_points = list() <NEW_LINE> exp_type = parameters['experiment_type'].replace('_shift', '') <NEW_LINE> d...
Reads in the fuda file and spit out the intensities
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def get_operators( kspace_data, loc, mask, fourier_type=1, max_iter=80, regularisation=None, linear=None, ): <NEW_LINE> <INDENT> n_coils = 1 if kspace_data.ndim == 2 else kspace_data.shape[0] <NEW_LINE> shape = kspace_data.shape[-2:] <NEW_LINE> if fourier_type == 0: <NEW_LINE> <INDENT> kspace_generator = KspaceGenerato...
Create the various operators from the config file.
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def is_four_kind(self): <NEW_LINE> <INDENT> rank_freq = self.rank_freq() <NEW_LINE> return 4 in rank_freq.values()
See if there are four of a kind in the hand.
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def rforest(self): <NEW_LINE> <INDENT> if self.smoteit: <NEW_LINE> <INDENT> self.train = SMOTE( self.train, atleast=500, atmost=500, resample=self.duplicate) <NEW_LINE> <DEDENT> clf = RandomForestClassifier(random_state=1) <NEW_LINE> train_df = formatData(self.train) <NEW_LINE> test_df = formatData(self.test) <NEW_LINE...
RF
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def __init__(self, x, y, pic_path, wid, hgt): <NEW_LINE> <INDENT> super().__init__(x, y, pic_path) <NEW_LINE> self.img = pg.transform.smoothscale(self.img, (wid, hgt))
int x: initial x coor of picture int y: initial y coor of picture str pic_path: relative path of object picture int wid: the width of the picture int hgt: the hight of the picture
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def __init__(self: 'ConsoleController', number_of_cheeses: int, number_of_stools: int): <NEW_LINE> <INDENT> self.number_of_cheeses = number_of_cheeses <NEW_LINE> self.num_of_stools = number_of_stools <NEW_LINE> self.model = TOAHModel(number_of_stools) <NEW_LINE> self.model.fill_first_stool(number_of_cheeses)
Initialize a new 'ConsoleController'. number_of_cheeses - number of cheese to tower on the first stool number_of_stools - number of stools
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def rotated(self, angle_degrees): <NEW_LINE> <INDENT> radians = -math.radians(angle_degrees) <NEW_LINE> cos = math.cos(radians) <NEW_LINE> sin = math.sin(radians) <NEW_LINE> x = self.x*cos - self.y*sin <NEW_LINE> y = self.x*sin + self.y*cos <NEW_LINE> return Vec2d(x, y)
Create and return a new vector by rotating this vector by angle_degrees degrees clockwise. :return: Rotated vector
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def create_db(connection): <NEW_LINE> <INDENT> driver = connection.engine.name <NEW_LINE> if driver == 'sqlite': <NEW_LINE> <INDENT> return create_sqlite_db(connection) <NEW_LINE> <DEDENT> def _execute(sql, *args, **kwargs): <NEW_LINE> <INDENT> engine = _get_admin_connection(connection) <NEW_LINE> engine.execute(text(s...
Creates the test database tables.
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def train_input_fn(data_dir_path, params): <NEW_LINE> <INDENT> with tf.name_scope("Data_Pipeline"): <NEW_LINE> <INDENT> dataset = train(data_dir_path) <NEW_LINE> dataset = dataset.shuffle(params["train_size"] + params["valid_size"]) <NEW_LINE> dataset = dataset.repeat(params["num_epochs"]) <NEW_LINE> dataset = dataset....
Train input function for the MNIST dataset. Args: data_dir_path: (string) path to the data directory params: (Params) contains hyperparameters of the model (ex: `params.num_epochs`)
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def italic(dec_func): <NEW_LINE> <INDENT> def wrapper(): <NEW_LINE> <INDENT> return '<i>' + dec_func() + '</i>' <NEW_LINE> <DEDENT> return wrapper
Make input string italic
625941b83617ad0b5ed67d4f
def OnSelChanged(self, event=None): <NEW_LINE> <INDENT> x = event.GetItem() <NEW_LINE> self.master.check_active() <NEW_LINE> self.master.activate_item(x) <NEW_LINE> event.Skip()
zorgen dat het eerder actieve item onthouden wordt, daarna het geselecteerde tot nieuw actief item benoemen
625941b8d6c5a10208143e97
def __init__(self, allowed_keys=None): <NEW_LINE> <INDENT> self.allowed_keys = allowed_keys <NEW_LINE> self._valid_values = [{0: 1}]
Validator for dictionary keys Args: allowed_keys (List): if set, all keys must be in allowed_keys
625941b8b57a9660fec336d0
def game_loop(self): <NEW_LINE> <INDENT> while self.run: <NEW_LINE> <INDENT> self.cleanup_wait_thread() <NEW_LINE> if not self.msgs: <NEW_LINE> <INDENT> self.recv_msgs() <NEW_LINE> <DEDENT> msg = self.get_msg() <NEW_LINE> while msg: <NEW_LINE> <INDENT> self.process_msg(msg) <NEW_LINE> msg = self.get_msg()
Main loop. Receives messages, and processes them in order.
625941b8cc0a2c11143dcce8
@connect_on_app_finalize <NEW_LINE> def add_unlock_chord_task(app): <NEW_LINE> <INDENT> from celery.canvas import maybe_signature <NEW_LINE> from celery.exceptions import ChordError <NEW_LINE> from celery.result import allow_join_result, result_from_tuple <NEW_LINE> default_propagate = app.conf.chord_propagates <NEW_LI...
This task is used by result backends without native chord support. It joins chords by creating a task chain polling the header for completion.
625941b80a50d4780f666cdf
def _get_subproduct_factor(self, cr, uid, production_id, move_id=None, context=None): <NEW_LINE> <INDENT> return 1
Compute the factor to compute the qty of procucts to produce for the given production_id. By default, it's always equal to the quantity encoded in the production order or the production wizard, but if the module mrp_subproduct is installed, then we must use the move_id to identify the product to produce and...
625941b863d6d428bbe4433f
def patch(self, pk, **kwargs): <NEW_LINE> <INDENT> args = '{}={}'.format(*kwargs.items()[0]) <NEW_LINE> for key, value in kwargs.items()[1:]: <NEW_LINE> <INDENT> args = '{}&{}={}'.format(args, key, value) <NEW_LINE> <DEDENT> return json.loads( self.conn.patch('{}/{}'.format(self.forms_ep, pk), None, args).text)
Update Form Properties
625941b8adb09d7d5db6c5e3
def has_property_value(self, property, value, name=None): <NEW_LINE> <INDENT> if name is None: <NEW_LINE> <INDENT> name = self._name + ".has_property_value({0}, {1})" .format(repr(property), repr(value)) <NEW_LINE> <DEDENT> return HasPropertyValue(name, property, value, self.datasources.entity)
Returns True if the specified property matches the provided value. :Parameters: property : `str` The name of a property (usually preceeded by "P") value : `mixed` The value to match name : `str` A name to associate with the Feature. If not set, the feature's name will be ...
625941b85f7d997b871748eb
def testParseName(self): <NEW_LINE> <INDENT> value = "_test" <NEW_LINE> self.assertEqual(parseName(value, '_'), 'test') <NEW_LINE> value = "____test____" <NEW_LINE> self.assertEqual(parseName(value, '_'), '___test____') <NEW_LINE> self.assertEqual(parseName(value, '___'), '_test____') <NEW_LINE> self.assertEqual(parseN...
test parse out a string from the beinning of a string
625941b894891a1f4081b8f8
def maxArea(self, height): <NEW_LINE> <INDENT> ans=0 <NEW_LINE> vol=0 <NEW_LINE> for i in range(len(height)): <NEW_LINE> <INDENT> for j in range(i+1,len(height)): <NEW_LINE> <INDENT> vol=min(height[i],height[j])*(j-i) <NEW_LINE> ans=max(ans,vol) <NEW_LINE> <DEDENT> <DEDENT> return ans
:type height: List[int] :rtype: int
625941b855399d3f05588503
def delete(self, model_id): <NEW_LINE> <INDENT> self.running_models.pop(model_id, None)
Delete the model whose ID matches ``model_id``. Using a model_id that does not exist in running_models is a no-op.
625941b8656771135c3eb6c2
def test_unadjusted_minutes_early_close(self): <NEW_LINE> <INDENT> day_before_thanksgiving = Timestamp('2015-11-25', tz='UTC') <NEW_LINE> xmas_eve = Timestamp('2015-12-24', tz='UTC') <NEW_LINE> market_day_after_xmas = Timestamp('2015-12-28', tz='UTC') <NEW_LINE> minutes = [self.market_closes[day_before_thanksgiving] - ...
Test unadjusted minute window, ensuring that early closes are filtered out.
625941b826238365f5f0ecb9
def GetPath(self): <NEW_LINE> <INDENT> return self.path
Get the xml files path @return: string
625941b8460517430c393fde
def __init__(self, system_owned=None, display_name=None, description=None, tags=None, create_user=None, protection=None, create_time=None, last_modified_time=None, last_modified_user=None, id=None, resource_type=None, datasources=None, weight=None, icons=None, shared=None, footer=None, drilldown_id=None, is_drilldown=F...
WidgetConfiguration - a model defined in Swagger
625941b88e05c05ec3eea1c1
def test_closeness_centrality(): <NEW_LINE> <INDENT> g = GeneralGraph() <NEW_LINE> g.load("tests/TOY_graph.csv") <NEW_LINE> closeness_centrality = { '1': 0.0, '2': 0.05555555555555555, '3': 0.05555555555555555, '4': 0.07407407407407407, '5': 0.07407407407407407, '6': 0.1736111111111111, '7': 0.11574074074074076, '8': 0...
The following test checks closeness centrality before any perturbation.
625941b8d10714528d5ffb2f
def report(): <NEW_LINE> <INDENT> print(report_formatter(order_donations(donors)))
Gets the aggregate donations sorted by descending aggregate donations and formats them into a report
625941b8a17c0f6771cbdea4
def dog_detector_from_path(img_path): <NEW_LINE> <INDENT> prediction = ResNet50_predict_labels_from_path(img_path) <NEW_LINE> return ((prediction <= 268) & (prediction >= 151))
returns "True" if a dog is detected in the image stored at img_path
625941b8a79ad161976cbf96
def test_ShackHartmannWFS(n_lenslets=2): <NEW_LINE> <INDENT> wavelength = 635*u.nm <NEW_LINE> shwfs = sub_sampled_optics.ShackHartmannWavefrontSensor(n_lenslets=n_lenslets) <NEW_LINE> dm_size = shwfs.lenslet_pitch*24 <NEW_LINE> wf_flat = poppy.Wavefront(diam=dm_size, wavelength=wavelength, npix=int((shwfs.lenslet_pitch...
Test Shack Hartmann Wavefront Sensor class functionality. Verifies that spot centroid measurement changes when optical system reflects off a deformed mirror Parameters ---------- n_lenslets = 2 n_lenslets parameter for ShackHartmannWavefrontSensor; the number of lenslets per side of a square grid.
625941b8dd821e528d63affb
def find_process_group(process_id): <NEW_LINE> <INDENT> try: <NEW_LINE> <INDENT> group_id = os.getpgid(process_id) <NEW_LINE> logging.info('Process (pid: {}) belongs to group (id: {})'.format(process_id, group_id)) <NEW_LINE> return group_id <NEW_LINE> <DEDENT> except ProcessLookupError: <NEW_LINE> <INDENT> logging.inf...
Return the process group id of the process with process id process_id. Parameters ---------- process_id: int The process id. Returns ------- The process group id of the process with process id process_id or None.
625941b89f2886367277a6e1
def get_surface_storage(self, comid, upcomids = [], tstep = 'daily', dates = None): <NEW_LINE> <INDENT> comids = self.get_upstream_comids(comid, upcomids = upcomids) <NEW_LINE> surss = self.get_subbasin_timeseries(['SURS'], comids, dates = dates) <NEW_LINE> areas = self.get_subbasin_areas(comids) <NEW_LINE> times = se...
Returns a timeseries of surface storage for the area. Note this assumes a daily dataset in the WDM file for storage.
625941b8596a89723608991a
def load_environment(global_conf, app_conf): <NEW_LINE> <INDENT> root = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) <NEW_LINE> paths = dict(root=root, controllers=os.path.join(root, 'controllers'), static_files=os.path.join(root, 'public'), templates=[os.path.join(root, 'templates')]) <NEW_LINE> config....
Configure the Pylons environment via the ``pylons.config`` object
625941b8c4546d3d9de72880
def warning(format, ): <NEW_LINE> <INDENT> utils.lib.zsys_warning(utils.to_bytes(format), )
Log warning condition - high priority
625941b832920d7e50b2801c
def update_routing_table(self, routes): <NEW_LINE> <INDENT> for route in routes: <NEW_LINE> <INDENT> if not self.is_neighbor(route.src): <NEW_LINE> <INDENT> print("update_routing_table: The entry does not come from its directly-connected neighbor!") <NEW_LINE> print("wrong route:", str(route)) <NEW_LINE> continue <NEW_...
Update routring table entries. If there is new route, add it. If the existed metric can be updated, update it.
625941b8bde94217f3682c4c
def subtest_4(ctx): <NEW_LINE> <INDENT> symlink = ctx.pointless() + ctx.termslash() <NEW_LINE> f = ctx.no_file() + ctx.termslash() <NEW_LINE> ctx.open_file(symlink, rw=1, err=ENOENT) <NEW_LINE> ctx.open_file(f, ro=1, err=ENOENT)
Open(broken) O_RDWR
625941b84f88993c3716bec4
def conv2d(x: AbstractTensor, y: AbstractTensor, stride, padding) -> AbstractTensor: <NEW_LINE> <INDENT> with tf.name_scope('conv2d'): <NEW_LINE> <INDENT> h_filter, w_filter, _, n_filters = map(int, y.shape) <NEW_LINE> n_x, _, h_x, w_x = map(int, x.shape) <NEW_LINE> if padding == 'SAME': <NEW_LINE> <INDENT> h_out = int...
Generic convolution implementation with im2col over AbstractTensors.
625941b86aa9bd52df036bf2
def ansi_len(string): <NEW_LINE> <INDENT> return len(string) - wcswidth(re.compile(r'\x1b[^m]*m').sub('', string))
Extra length due to any ANSI sequences in the string.
625941b8851cf427c661a36b
def transfer_landmarks_onto(self, target): <NEW_LINE> <INDENT> from ..surface_regressor import apply_surface_regressor <NEW_LINE> from ..equality import have_same_topology <NEW_LINE> if not target.is_tri: <NEW_LINE> <INDENT> raise ValueError("Target mesh must be triangulated") <NEW_LINE> <DEDENT> if not have_same_topol...
Transfer landmarks onto the given target mesh, which must be in the same topology as the source mesh. Args: target (lacecore.Mesh): Target mesh Returns: dict: A mapping of landmark names to a np.ndarray with shape `3x1`.
625941b8be8e80087fb20aa0
def itkDisplacementFieldJacobianDeterminantFilterIVF22D_cast(*args): <NEW_LINE> <INDENT> return _itkDisplacementFieldJacobianDeterminantFilterPython.itkDisplacementFieldJacobianDeterminantFilterIVF22D_cast(*args)
itkDisplacementFieldJacobianDeterminantFilterIVF22D_cast(itkLightObject obj) -> itkDisplacementFieldJacobianDeterminantFilterIVF22D
625941b856b00c62f0f144ae
def get_vertical_height(self, text, font_size): <NEW_LINE> <INDENT> self.draw.font = self.get_font(font_size) <NEW_LINE> size = 0 <NEW_LINE> for character in text: <NEW_LINE> <INDENT> size += self.draw.font.getsize(character)[1] <NEW_LINE> <DEDENT> return size
縦に並べた際の文字の高さを取得する :param text: :param font_size: :return:
625941b8956e5f7376d70ccb
@app.route('/slack/commands', methods=['POST']) <NEW_LINE> def slack_slash_commands(): <NEW_LINE> <INDENT> raw_data = flask.request.get_data() <NEW_LINE> if not verify_slack_request( flask.request.headers['X-Slack-Signature'], flask.request.headers['X-Slack-Request-Timestamp'], raw_data.decode('utf-8'), ): <NEW_LINE> <...
Handles responding to slash commands for reservations. Commands: /crush watch <campground-tag> <DD/MM/YY> <length> ------------------------------------------------------ Registers a new watcher for a reservation. This will begin a periodic scraping process against the recreation.gov website. When succesful we'll send...
625941b8ab23a570cc24ffd0
def _trustedPeerLoginFailed(self, result, request): <NEW_LINE> <INDENT> return HTTPAuthResource.authenticate(self, request)
If the peer is not trusted, fallback to HTTP basic/digest authentication.
625941b8d164cc6175782b9e
def _store_array(self): <NEW_LINE> <INDENT> if self._mat_u is None: <NEW_LINE> <INDENT> self._mat_u = self.to_sparse_array().toarray()
Stores the matrix with counted time points in memory.
625941b8cdde0d52a9e52e7f
def create_folder(self, folder): <NEW_LINE> <INDENT> typ, data = self._imap.create(self._encode_folder_name(folder)) <NEW_LINE> self._checkok('create', typ, data) <NEW_LINE> return data[0]
Create a new folder on the server. @param folder: The folder name. @return: Server response.
625941b81d351010ab85596e
def onXYStagePositionChanged(self, *args): <NEW_LINE> <INDENT> return _MMCorePy.MMEventCallback_onXYStagePositionChanged(self, *args)
onXYStagePositionChanged(self, char name, double xpos, double ypos) Parameters: self: MMEventCallback * value name: char * value xpos: double value ypos: double value name: char * value xpos: double value ypos: double value
625941b8d10714528d5ffb30
def get(self, entry: DNSEntry) -> Optional[DNSRecord]: <NEW_LINE> <INDENT> try: <NEW_LINE> <INDENT> list_ = self.cache[entry.key] <NEW_LINE> for cached_entry in list_: <NEW_LINE> <INDENT> if entry.__eq__(cached_entry): <NEW_LINE> <INDENT> return cached_entry <NEW_LINE> <DEDENT> <DEDENT> return None <NEW_LINE> <DEDENT> ...
Gets an entry by key. Will return None if there is no matching entry.
625941b8435de62698dfdaa5
def get_nationality(nation): <NEW_LINE> <INDENT> with codecs.open("nationalities.txt", "r", "utf-8") as f: <NEW_LINE> <INDENT> nationalities = {} <NEW_LINE> for x in f.readlines(): <NEW_LINE> <INDENT> nationalities[x.strip().lower().split(',')[1]] = x.strip().lower().split(',')[0] <NEW_LINE> <DEDENT> <DEDENT> result = ...
Test id a word is a nationality adjective
625941b810dbd63aa1bd2a00
def display(self): <NEW_LINE> <INDENT> for r in range(1, 4): <NEW_LINE> <INDENT> print("+-+-+-+") <NEW_LINE> print("|", end="") <NEW_LINE> for c in range(1, 3): <NEW_LINE> <INDENT> print(self.gameState[r,c], end="") <NEW_LINE> print("|",end="") <NEW_LINE> <DEDENT> print(self.gameState[r,3], end="") <NEW_LINE> print("|"...
A pleasant view of the current game state :return: nothing
625941b8ab23a570cc24ffd1
def isHangulLetter(S): <NEW_LINE> <INDENT> if isPrecomposedSyllable(S): <NEW_LINE> <INDENT> return True <NEW_LINE> <DEDENT> if isHangulJamo(S): <NEW_LINE> <INDENT> return True <NEW_LINE> <DEDENT> if isCompatibilityLetter(S): <NEW_LINE> <INDENT> return True <NEW_LINE> <DEDENT> if isParenthesizedLetter(S): <NEW_LINE> <IN...
Check S is a Hanggul-related character. :param char S Single character string
625941b86fece00bbac2d58c
def test_li_attr(): <NEW_LINE> <INDENT> con = "This is the second item" <NEW_LINE> li = Li(con, style="color: red") <NEW_LINE> file_contents = render_result(li) <NEW_LINE> print(file_contents) <NEW_LINE> assert '<li style="color: red">\n' in file_contents
a li with an attribute
625941b8d7e4931a7ee9dd6d
def name_of_month(month:int) -> str: <NEW_LINE> <INDENT> dct_month = {1: 'January', 2: 'February', 3: 'March', 4: 'April', 5: 'May', 6: 'June', 7: 'Jule', 8: 'August', 9: 'September', 10: 'October', 11: 'November', 12: 'December'} <NEW_LINE> return dct_month[month]
Возвращает название месяца согласно номеру
625941b8e1aae11d1e749b05
def ca(classLabels): <NEW_LINE> <INDENT> nCorrect = 0 <NEW_LINE> nTotal = 0 <NEW_LINE> for trueLabel, foundLabels in enumerate(classLabels): <NEW_LINE> <INDENT> foundLabels = np.asarray(foundLabels) <NEW_LINE> nCorrect += np.sum(foundLabels == trueLabel) <NEW_LINE> nTotal += len(foundLabels) <NEW_LINE> <DEDENT> return ...
Compute the classification accuracy using predicted class labels with known true labels. Args: classLabels: A list with length equal to the number of classes with one element per class. Each element of this list contains a list of predictec class labels. Returns: Sc...
625941b8dc8b845886cb5386
def _cmidrule(colindex, dataset_width): <NEW_LINE> <INDENT> rule = '\\cmidrule(%s){%d-%d}' <NEW_LINE> if colindex == 1: <NEW_LINE> <INDENT> return rule % ('r', colindex, colindex) <NEW_LINE> <DEDENT> if colindex == dataset_width: <NEW_LINE> <INDENT> return rule % ('l', colindex, colindex) <NEW_LINE> <DEDENT> return rul...
Generates the `cmidrule` for a single column with appropriate trimming based on the column position. :param colindex: Column index :param dataset_width: width of the dataset
625941b8d486a94d0b98df9f