Prepare release 2.8 (#675)

* Bump version 2.8 * Move MFCK notebook with MFK ones under MultiFi folder * Add contributor * Mention kriging output limitation in the doc
SMTorg · Nov 8, 2024 · 451526f · 451526f
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diff --git a/AUTHORS.md b/AUTHORS.md
@@ -26,6 +26,7 @@ SMT has been developed thanks to contributions from:
 * Lisa Pretsch
 * Lucas Alber
 * Maël Tremouille
+* Mauricio Castano Aguirre
 * Mostafa Meliani
 * Nick Thompson
 * Nicolas Gonel

diff --git a/doc/_src_docs/surrogate_models/gpr/krg.rst b/doc/_src_docs/surrogate_models/gpr/krg.rst
diff --git a/doc/_src_docs/surrogate_models/gpr/krg.rstx b/doc/_src_docs/surrogate_models/gpr/krg.rstx
@@ -55,6 +55,8 @@ In the implementations, data are normalized by substracting the mean from each v
 .. math ::
   X_{\text{norm}} = \frac{X - X_{\text{mean}}}{X_{\text{std}}}
 
+All SMT kriging implementations work with only one-dimensional output (ie output training data must be vector-like).
+
 More details about the Kriging approach could be found in [1]_.
 
 Kriging with categorical or integer variables 
@@ -83,7 +85,7 @@ Usage
 -----
 
 Example 1
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+^^^^^^^^^
 
 .. embed-test-print-plot :: smt.surrogate_models.tests.test_surrogate_model_examples , Test , test_krg , 80
 

diff --git a/smt/__init__.py b/smt/__init__.py
@@ -1,4 +1,4 @@
-__version__ = "2.7.0"
+__version__ = "2.8.0"
 
 __all__ = [
     "surrogate_models",

diff --git a/tutorial/MFCK/SMT_MFCK_tutorial.ipynb → tutorial/MultiFi/SMT_MFCK_tutorial.ipynb b/tutorial/MFCK/SMT_MFCK_tutorial.ipynb → tutorial/MultiFi/SMT_MFCK_tutorial.ipynb
diff --git a/tutorial/MFK/SMT_MFK_Noise.ipynb → tutorial/MultiFi/SMT_MFK_Noise.ipynb b/tutorial/MFK/SMT_MFK_Noise.ipynb → tutorial/MultiFi/SMT_MFK_Noise.ipynb
diff --git a/tutorial/MFK/SMT_MFK_tutorial.ipynb → tutorial/MultiFi/SMT_MFK_tutorial.ipynb b/tutorial/MFK/SMT_MFK_tutorial.ipynb → tutorial/MultiFi/SMT_MFK_tutorial.ipynb
diff --git a/tutorial/README.md b/tutorial/README.md
@@ -22,17 +22,21 @@ These tutorials introduce to use the opensource Surrogate Modeling Toolbox where
 
 [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/SMTorg/smt/blob/master/tutorial/SBO/SMT_EGO_noisyGP.ipynb)
 
-
 ## Multi-Fidelity Gaussian Process
 
-### Without noise
+### With required nested sampling
+
+#### Without noise
+
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/SMTorg/smt/blob/master/tutorial/MultiFi/SMT_MFK_tutorial.ipynb)
 
-[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/SMTorg/smt/blob/master/tutorial/MFK/SMT_MFK_tutorial.ipynb)
+#### With noise
 
-### With noise
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/SMTorg/smt/blob/master/tutorial/MultiFi/SMT_MFK_Noise.ipynb)
 
-[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/SMTorg/smt/blob/master/tutorial/MFK/SMT_MFK_Noise.ipynb)
+### Without nested sampling
 
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/SMTorg/smt/blob/master/tutorial/MultiFi/SMT_MFCK_tutorial.ipynb)
 
 ## Proper Orthogonal Decomposition and Interpolation