jschueller

import openturns as ot

class CensoredDistribution(ot.PythonDistribution):
    def __init__(self, distribution, bounds):
        dim = distribution.getDimension()
        super(CensoredDistribution, self).__init__(dim)
        if dim != bounds.getDimension():
            raise ValueError("distribution/bounds dimension do not match")
        if dim > 1:
            raise ValueError("TODO")

jschueller

#!/usr/bin/env python

import openturns as ot

from sklearn.metrics import mean_squared_error
import numpy as np


print(ot.__file__)
def calculate_metrics(y_test, y_mean_prediction, y_var_prediction):

jschueller

#! /usr/bin/env python

import openturns as ot
import openturns.experimental as otexp
from openturns.usecases import ishigami_function as ishigami_function
import time

ot.TESTPREAMBLE()
#ot.Log.Show(ot.Log.INFO)
im = ishigami_function.IshigamiModel()

jschueller

ASAN:

cmake -DCMAKE_BUILD_TYPE="" -DCMAKE_CXX_FLAGS="-fadress-sanitizer -O1 -fomit-framepointer" ..

debug modelica leaks using valgrind:

LD_PRELOAD=/tmp/zoe/binaries/linux64/IshigamiFunction.so valgrind --leak-check=yes --track-origins=no --log-file=valgrind_output.txt --suppressions=valgrind-python.supp --keep-debuginfo=yes /usr/bin/python    ex_zoe.py

gdb inside docker:

jschueller

#!/usr/bin/env python

import openturns as ot
import math

class InverseFORMResult:
    def __init__(self, p, n):
        self.p_ = p
        self.n_ = n
    def getOptimalValue(self):

jschueller

docker

• sudo apt install docker.io
• sudo usermod -a -G docker doe
• sudo vim /lib/systemd/system/docker.service
• /usr/bin/dockerd ... -g /data/docker --max-concurrent-downloads 1
• see options: https://docs.docker.com/engine/reference/commandline/dockerd/
• sudo systemctl daemon-reload
• sudo systemctl restart docker

jschueller

jschueller

#! /usr/bin/env python

from __future__ import print_function
from openturns import *
from math import *
import openturns as ot
from time import time

TESTPREAMBLE()
#Log.Show(Log.INFO)

jschueller

#! /usr/bin/env python

from __future__ import print_function
from openturns import *
from math import *
import openturns as ot
from time import time

TESTPREAMBLE()
RandomGenerator.SetSeed(0)

jschueller

#! /usr/bin/env python

from __future__ import print_function
import openturns as ot
import math as m

class InverseFORM(object):
    def __init__(self, event, parameterName, startingPoint, targetBeta):
        assert(parameterName in event.getParameterDescription())
        self.event_ = event