def open(pool_uuid, cont_uuid, flag):
"""Open a container and return a daosdm() object"""
if flag not in ['r', 'w']:
raise error
container = pydaos.Cont(pool_uuid, cont_uuid)
kvstore = container.rootkv()
# pylint: disable=redefined-variable-type
if flag == 'w':
db = daosdm_rw(kvstore)
else:
db = daosdm(kvstore)
# pylint: enable=redefined-variable-type
return db
DIMENSIONS = int(os.getenv("DIMENSIONS", "500"))
NUMBER_OF_CENTERS = int(os.getenv("NUMBER_OF_CENTERS", "20"))
NUMBER_OF_ITERATIONS = int(os.getenv("NUMBER_OF_ITERATIONS", "10"))
NUMBER_OF_KMEANS_ITERATIONS = int(
os.getenv("NUMBER_OF_KMEANS_ITERATIONS", "10"))
SEED = 42
MODE = 'uniform'
DAOS_POOL_UUID = os.environ["DAOS_POOL"]
DAOS_CONT_UUID = os.environ["DAOS_CONT"]
#############################################
#############################################
DAOS_CONT = pydaos.Cont(DAOS_POOL_UUID, DAOS_CONT_UUID)
DAOS_KV = DAOS_CONT.rootkv()
NP_FROMSTRING_DTYPE = np.dtype('float64')
NP_FROMSTRING_SHAPES = list()
def generate_points(num_points, dim, mode, seed):
# Random generation distributions
rand = {
'normal': lambda k: np.random.normal(0, 1, k),
'uniform': lambda k: np.random.random(k),
}
r = rand[mode]
np.random.seed(seed)
mat = np.array([r(dim) for __ in range(num_points)])