# TODO: FIND ALTERNATIVE TO THIS PYTHONPATH HACK
import os
import sys
# PYTHONPATH is not found when running mpiexec,
# so inject it so that we can load SROMPy modules...
if 'PYTHONPATH' not in os.environ:
base_path = os.path.abspath('.')
sys.path.insert(0, base_path)
sys.path.insert(0, os.path.join(base_path, 'SROMPy'))
from SROMPy.srom import SROM
from SROMPy.target import BetaRandomVariable
# Random variable to optimize to.
random_variable = BetaRandomVariable(alpha=3., beta=2., shift=1., scale=2.5)
# Run each SROM optimization 10 times to generate performance data.
performance_data = []
# Get MPI information.
comm = MPI.COMM_WORLD
# Load previously saved scalability data if available.
data_filename = os.path.join("data", "weak_scalability_data.txt")
if os.path.isfile(data_filename):
if comm.rank == 0:
print 'Loading previously saved data set for modification:'
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
import numpy as np
from model import SpringMass1D
from SROMPy.postprocess import Postprocessor
from SROMPy.srom import SROM, FiniteDifference as FD, SROMSurrogate
from SROMPy.target import SampleRandomVector, BetaRandomVariable
# Random variable for spring stiffness.
stiffness_random_variable = \
BetaRandomVariable(alpha=3., beta=2., shift=1., scale=2.5)
# Specify spring-mass system:
m = 1.5 # Deterministic mass.
state0 = [0., 0.] # Initial conditions.
t_grid = np.arange(0., 10., 0.1) # Time.
# Initialize model,
model = SpringMass1D(m, state0, t_grid)
# ----------Monte Carlo------------------
# Generate stiffness input samples for Monte Carlo.
num_samples = 5000
stiffness_samples = stiffness_random_variable.draw_random_sample(num_samples)