13.4.1. Macro “samplingFlowrate.py”

13.4.1.1. Objective

The objective of this macro is to generate a design-of-experiments, of length 100 using the LHS method, with eight random attributes (\(r_{\omega}\), \(r\), \(T_u\), \(T_l\), \(H_u\), \(H_l\), \(L\), \(K_{\omega}\)) which obey uniform laws on specific intervals.

13.4.1.2. Macro Uranie

"""
Example of simple flowrate DoE generation
"""
from URANIE import DataServer, Sampler
import ROOT

nS = 1000
# Define the DataServer
tds = DataServer.TDataServer("tdsFlowrate", "Design of experiments")

# Add the study attributes
tds.addAttribute(DataServer.TUniformDistribution("rw", 0.05, 0.15))
tds.addAttribute(DataServer.TUniformDistribution("r", 100.0, 50000.0))
tds.addAttribute(DataServer.TUniformDistribution("tu", 63070.0, 115600.0))
tds.addAttribute(DataServer.TUniformDistribution("tl", 63.1, 116.0))
tds.addAttribute(DataServer.TUniformDistribution("hu", 990.0, 1110.0))
tds.addAttribute(DataServer.TUniformDistribution("hl", 700.0, 820.0))
tds.addAttribute(DataServer.TUniformDistribution("l", 1120.0, 1680.0))
tds.addAttribute(DataServer.TUniformDistribution("kw", 9855.0, 12045.0))


# test Generateur de plan d'experience
sampling = Sampler.TSampling(tds, "lhs", nS)
sampling.generateSample()

tds.exportData("_flowrate_sampler_.dat")


# Visualisation
Canvas = ROOT.TCanvas("Canvas", "Graph samplingFlowrate", 5, 64, 1270, 667)
ROOT.gStyle.SetPalette(1)
pad = ROOT.TPad("pad", "pad", 0, 0.03, 1, 1)
pad.Draw()

pad.Divide(2, 2)
pad.cd(1)
tds.draw("r")
pad.cd(2)
tds.draw("rw")
pad.cd(3)
tds.drawTufte("rw:r")
pad.cd(4)
tds.draw("rw:r:hu")

An uniform law is set for each attribute and then, linked to a the TDataServer:

tds.addAttribute(DataServer.TUniformDistribution("rw", 0.05, 0.15))
tds.addAttribute(DataServer.TUniformDistribution("r", 100.0, 50000.0))
tds.addAttribute(DataServer.TUniformDistribution("tu", 63070.0, 115600.0))
tds.addAttribute(DataServer.TUniformDistribution("tl", 63.1, 116.0))
tds.addAttribute(DataServer.TUniformDistribution("hu", 990.0, 1110.0))
tds.addAttribute(DataServer.TUniformDistribution("hl", 700.0, 820.0))
tds.addAttribute(DataServer.TUniformDistribution("l", 1120.0, 1680.0))
tds.addAttribute(DataServer.TUniformDistribution("kw", 9855.0, 12045.0))

The sampling is generated with the LHS method:

sampling = Sampler.TSampling(tds, "lhs", nS)
sampling.generateSample()

Data are exported in an ASCII file:

tds.exportData("_flowrate_sampler_.dat")

13.4.1.3. Graph

Figure 13.9 Graph of the macro “samplingFlowrate.py”