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)