def run_with_params( x0s, thetas, _theta, _main_method, _ls_method, test_params, test_ls_params): # Create the permutations of parameters permutations = list(itertools.product( *[*test_params.values(), *test_ls_params.values()] )) param_keys = [*test_params.keys()] ls_param_keys = [*test_ls_params.keys()] total_iterations = len(permutations) * len(x0s) bar = progressbar.ProgressBar( maxval=total_iterations, widgets=[ progressbar.Percentage(), ' (', progressbar.Counter(), f'/{total_iterations}) ', progressbar.Bar('=', '[', ']'), ' ', progressbar.ETA(), ' ', progressbar.AdaptiveETA(), ] ) bar.start() k = 0 results = [] for p in permutations: # Format the params params = {key: p[i] for i, key in enumerate(param_keys)} ls_params = { key: p[i + len(param_keys)] for i, key in enumerate(ls_param_keys) } ls_method = _ls_method(ls_params) main_method = _main_method(params, ls_method) current_config = Configuration( _theta, x0s, test_params, test_ls_params, _main_method, _ls_method, params, ls_params ) # Test for each starting point and function for i, x0 in enumerate(x0s): theta = thetas[i] result = main_method(theta, np.array(x0)) current_config.update(result) k += 1 bar.update(k) results.append(current_config) bar.finish() return results
def get_cluster(self, cloud_provider=None, config=None, nodes=None): if not cloud_provider: cloud_provider = BotoCloudProvider("https://hobbes.gc3.uzh.ch/", "nova", "a-key", "s-key") if not config: config = Configuration().get_config(self.path) setup = Mock() configurator = Configurator(config) conf_login = configurator.cluster_conf['mycluster']['login'] repository = PickleRepository(self.storage_path) cluster = Cluster( name="mycluster", cloud_provider=cloud_provider, setup_provider=setup, repository=repository, user_key_name=conf_login['user_key_name'], user_key_public=conf_login['user_key_public'], user_key_private=conf_login['user_key_private'], ) if not nodes: nodes = {"compute": 2, "frontend": 1} for kind, num in nodes.iteritems(): conf_kind = configurator.cluster_conf['mycluster']['nodes'][kind] cluster.add_nodes(kind, num, conf_kind['image_id'], conf_login['image_user'], conf_kind['flavor'], conf_kind['security_group']) return cluster
def test_get_frontend_node(self): """ Get frontend node """ config = Configuration().get_config(self.path) ssh_to = "frontend" config["mycluster"]["cluster"]["ssh_to"] = ssh_to cluster = self.get_cluster(config=config) cluster.ssh_to = ssh_to frontend = cluster.get_frontend_node() self.assertEqual(cluster.nodes['frontend'][0], frontend)
def test_dict_mixin(self): """Check that the node class can be seen as dictionary""" config = Configuration().get_config(self.path) ssh_to = "frontend" config["mycluster"]["cluster"]["ssh_to"] = ssh_to cluster = self.get_cluster(config=config) cluster.ssh_to = ssh_to frontend = cluster.get_frontend_node() dcluster = dict(cluster) self.assertEqual(dcluster['ssh_to'], ssh_to) self.assertEqual(dcluster['nodes'].keys(), cluster.nodes.keys()) self.failUnlessRaises(KeyError, lambda x: x['_cloud_provider'], dcluster) self.assertEqual(cluster['_cloud_provider'], cluster._cloud_provider)
import os from inspect import getsourcefile from helpers import Configuration, Database from saby_invoker import SabyInvoker from server import flask_server from neural_network import NeuralNetwork # change directory to package directory package_dir = os.path.dirname(os.path.abspath(getsourcefile(lambda: 0))) os.chdir(package_dir) # read configuration from config file Configuration.load_configuration() # connect to database Database.connect_to_database() # init RpcInvoker SabyInvoker.initialize() # init NeuralNetwork NeuralNetwork.initialize() # run server on flask flask_server.run() # from api import get_user_info # get_user_info(14893668, '00000003-007537f4-00bd-310e086f458d384b')
#!/usr/bin/python3 # coding: utf-8 from optparse import OptionParser import json import time import os from helpers import Configuration from helpers import TheMovieDatabase TMDB = TheMovieDatabase.TMDB_Handle(Configuration.TMDB.get("api_key"), Configuration.TMDB.get("language"), Configuration.TMDB.isDebugOn()) MOVIE_EXTENSIONS = Configuration.loadExtensions("movie") SUBTITLE_EXTENSIONS = Configuration.loadExtensions("subtitle") PARSERS = Configuration.loadParsers() # ============================================================================== # def get_metadata(query, year="any"): results = TMDB.search_movie(query, year) if len(results) > 0: details = TMDB.get_movie_details(results[0]["id"]) if details: metadata = { "title" : details["title"], "tmdb_id" : details["id"], "imdb_id" : details["imdb_id"],
def setUp(self): file, path = tempfile.mkstemp() self.path = path self.config = Configuration().get_config(self.path)