update examples

python/doc/pyplots/GaussianProcessFitter.py

@@ -0,0 +1,24 @@
+import openturns as ot
+from openturns.experimental import GaussianProcessFitter
+from openturns.viewer import View
+
+f = ot.SymbolicFunction(["x"], ["x * sin(x)"])
+sampleX = [[1.0], [2.0], [3.0], [4.0], [5.0], [6.0], [7.0], [8.0]]
+sampleY = f(sampleX)
+basis = ot.Basis(
+    [ot.SymbolicFunction(["x"], ["x"]), ot.SymbolicFunction(["x"], ["x^2"])]
+)
+covarianceModel = ot.SquaredExponential([1.0])
+covarianceModel.setActiveParameter([])
+algo = GaussianProcessFitter(sampleX, sampleY, covarianceModel, basis)
+algo.run()
+result = algo.getResult()
+
+graph = f.draw(0.0, 10.0)
+graph.add(result.getMetaModel().draw(0.0, 10.0))
+graph.add(ot.Cloud(sampleX, sampleY))
+graph.setColors(["blue", "red", "black"])
+graph.setLegends(["model", "meta model", "sample"])
+graph.setLegendPosition("upper left")
+graph.setTitle("y(x)=x * sin(x)")
+View(graph, figure_kw={"figsize": (8, 4)})

python/doc/pyplots/GaussianProcessRegression.py

@@ -0,0 +1,26 @@
+import openturns as ot
+from openturns.experimental import GaussianProcessFitter, GaussianProcessRegression
+from openturns.viewer import View
+
+f = ot.SymbolicFunction(["x"], ["x * sin(x)"])
+sampleX = [[1.0], [2.0], [3.0], [4.0], [5.0], [6.0], [7.0], [8.0]]
+sampleY = f(sampleX)
+basis = ot.Basis(
+    [ot.SymbolicFunction(["x"], ["x"]), ot.SymbolicFunction(["x"], ["x^2"])]
+)
+covarianceModel = ot.SquaredExponential([1.0])
+covarianceModel.setActiveParameter([])
+fitter_algo = GaussianProcessFitter(sampleX, sampleY, covarianceModel, basis)
+fitter_algo.run()
+algo = GaussianProcessRegression(fitter_algo.getResult())
+algo.run()
+result = algo.getResult()
+
+graph = f.draw(0.0, 10.0)
+graph.add(result.getMetaModel().draw(0.0, 10.0))
+graph.add(ot.Cloud(sampleX, sampleY))
+graph.setColors(["blue", "red", "black"])
+graph.setLegends(["model", "meta model", "sample"])
+graph.setLegendPosition("upper left")
+graph.setTitle("y(x)=x * sin(x)")
+View(graph, figure_kw={"figsize": (8, 4)})

python/doc/user_manual/response_surface/kriging.rst

@@ -22,14 +22,14 @@ Gaussian Process Regression
 
 .. autosummary::
     :toctree: _generated/
-    :template: class.rst_t
+    :template: classWithPlot.rst_t
 
     GaussianProcessRegression
     GaussianProcessFitter
 
     :template: class.rst_t
-    GaussianProcessRegressionResult
-    GaussianProcessFitterResult
+    experimental.GaussianProcessRegressionResult
+    experimental.GaussianProcessFitterResult
 
 
 Construction of the regression basis