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Questions tagged [openturns]

OpenTURNS is a scientific C++ and Python library dedicated to the treatment of uncertainties. The main goal of this library is giving to specific applications all the functionalities needed to treat uncertainties in studies. Targeted users are all engineers who want to introduce the probabilistic dimension in their so far deterministic studies. The project is open source and commercially usable (Lesser General Public License).

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How to set the legends outside of the graphics in OpenTURNS?

I want to create a contour plot of the log-likelihood of a Gaussian sample with OpenTURNS. Each contour maps to a function value, which is indicated by the legend of the plot. The problem is that the legend somewhat hides the contours: how to setup…
Michael Baudin
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How to estimate the parameters of a mixture model in OpenTURNS?

I would like to estimate the parameters of a mixture model of normal distributions in OpenTURNS (that is, the distribution of a weighted sum of Gaussian random variables). OpenTURNS can create such a mixture, but it cannot estimate its parameters.…
Michael Baudin
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How to perform calibration with OpenTURNS without observed inputs?

In general, I have a model g which has observed inputs X, parameters θ and observed outputs Y. However, there are some situations where I have no observed inputs X. In this case, using OpenTURNS seems to be impossible, because the constructor of…
Michael Baudin
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How to estimate the Taylor decomposition variance from a Python function with user-defined gradient in OpenTURNS?

I have a Python function which has 2 inputs X0 and X1 and 1 output Y: def mySimulator(x): y0 = 1. - x[0] * x[1] y = [y0] return y I would like to estimate the variance of the output Y from Taylor decomposition when for example…
Michael Baudin
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Python package import conflicts (Theano and openturns)

I'm running Anaconda 4.3.1 (Python 3.6.1) on Windows 7 64-bit and am unable to import both theano and openturns into my session, however importing only one or the other works fine. Obviously one is causing some sort of import conflict in the other,…
Aorus
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xlwings doesn't recognize imported module openturns

I set up a spreadsheet tool with Python scripts using xlwings. So far so good and everything works fine, I'm running it from Anaconda using Spyder. I can run the script from Excel (using the VBA connection) and from Python, both are working fine.…
WouterK
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Which packages is proper for dependence modeling using copula in Python?

I'm facing a stochastic model which needs the copula tool to formulate the dependence within several random variables. For the unknown dependence structure, it would be better if as more the copula families as possible are supported, such as…
Wynn
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Using openturns from R via reticulate

I am trying to use functions from the openturns Python package from R. I believe it should be possible to install and import Python packages using the R-package reticulate, but it does not seem to work for openturns. Can anyone help? It seems to…
Erik
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Is there a way of seeing steps in importance sampling?

In the following code from Openturns FORM example: import openturns as ot model = ot.SymbolicFunction(['x1', 'x2'], ['x1^2+x2']) R = ot.CorrelationMatrix(2) R[0,1] = -0.6 inputDist = ot.Normal([0.,0.], R) inputDist.setDescription(['X1',…
Aeroman
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How to create a discrete distribution in OpenTURNS?

I have a sample of real values which contains independent realizations of a discrete random variable and I want to create the distribution which fits this data. sample = [2.0, 2.0, 1.0, 1.0, 2.0, 3.0, 1.0, 2.0, 2.0, 1.0] The UserDefined…
Michael Baudin
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Continuous and discrete variables with OpenTURNS

How to create a design of experiments with both continuous and discrete random variables with OpenTURNS? I get that we can do: X0 = ot.Normal() X1 = ot.Normal() distribution = ot.ComposedDistribution([X0,X1]) But this creates only a continuous…
tupui
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How to configure the optimization algorithm during maximum likelihood estimation in OpenTURNS?

I have a Sample and i want to fit the parameters of a Beta distribution with maximum likelihood estimation. Moreover, I want to truncate its parameters into the [0,100] interval. This should be easy with MaximumLikelihoodFactory, but the problem is…
Michael Baudin
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