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diff --git a/Outputs_Bayes_None_Calib/emcee_sampler.h5 b/Outputs_Bayes_None_Calib/emcee_sampler.h5
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diff --git a/Outputs_SeqPosteriorComparison/posterior/Z.npy b/Outputs_SeqPosteriorComparison/posterior/Z.npy
deleted file mode 100644
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diff --git a/README.md b/README.md
index 86e8f03b0f7ebf454bbbeed2ae0cffd7982e0a7e..9b9a5cdc9e5d97c86698c56c51e5211d2ddae46e 100644
--- a/README.md
+++ b/README.md
@@ -1,7 +1,7 @@
# BayesValidRox
<div align="center">
- <img src="https://git.iws.uni-stuttgart.de/inversemodeling/bayesian-validation/-/raw/master/docs/logo/bayesvalidrox-logo.png" alt="bayesvalidrox logo"/>
+ <img src="https://git.iws.uni-stuttgart.de/inversemodeling/bayesian-validation/-/raw/master/docs/logo/BVRLogoV03_longtext.png" alt="bayesvalidrox logo"/>
</div>
An open-source, object-oriented Python package for surrogate-assisted Bayesain Validation of computational models.
@@ -9,6 +9,7 @@ This framework provides an automated workflow for surrogate-based sensitivity an
## Authors
- [@farid](https://git.iws.uni-stuttgart.de/farid)
+- [@RKohlhaas](https://git.iws.uni-stuttgart.de/RKohlhaas)
## Installation
The best practive is to create a virtual environment and install the package inside it.
@@ -39,6 +40,24 @@ and installing the version on the master branch can be done by cloning this repo
* Bayesian validation with model weights for multi-model setting
## Requirements
+[1.1.0] - python 3.10:
+* numpy>=1.23.5
+* pandas==1.4.4
+* joblib==1.1.1
+* matplotlib==3.8.0
+* seaborn==0.11.1
+* scipy>=1.11.1
+* scikit-learn==1.3.1
+* tqdm>=4.61.1
+* chaospy==4.3.3
+* emcee==3.0.2
+* corner==2.2.1
+* h5py==3.9.0
+* statsmodels==0.14.2
+* multiprocess==0.70.16
+* datasets==2.20.0
+* umbridge==1.2.4
+[1.0.0] - python 3.10:
* numpy==1.22.1
* pandas==1.2.4
* joblib==1.0.1
diff --git a/examples/.coverage b/examples/.coverage
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diff --git a/src/bayesvalidrox/__init__.py b/src/bayesvalidrox/__init__.py
index 6c11bd3730d31b602b1b4538de1856de04ffc909..84b052ef04c04dcf9747be048ab0cbc7dc73d484 100644
--- a/src/bayesvalidrox/__init__.py
+++ b/src/bayesvalidrox/__init__.py
@@ -1,9 +1,8 @@
# -*- coding: utf-8 -*-
-__version__ = "1.0.0"
+__version__ = "1.1.0"
from .pylink.pylink import PyLinkForwardModel
from .surrogate_models.surrogate_models import MetaModel
-#from .surrogate_models.meta_model_engine import MetaModelEngine
from .surrogate_models.engine import Engine
from .surrogate_models.inputs import Input
from .surrogate_models.exp_designs import ExpDesigns
@@ -18,7 +17,6 @@ __all__ = [
"Input",
"Discrepancy",
"MetaModel",
- #"MetaModelEngine",
"Engine",
"ExpDesigns",
"PostProcessing",
diff --git a/tests/ExpDesign_testfile.hdf5 b/tests/ExpDesign_testfile.hdf5
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diff --git a/tests/test_engine.py b/tests/test_engine.py
index ae36047c5b24f32ba8592125d2d56e9d98b8505a..f51bc6afc7c93b7803d9da7366e79e8c81b14a8b 100644
--- a/tests/test_engine.py
+++ b/tests/test_engine.py
@@ -105,16 +105,16 @@ def test__error_Mean_Std_nomc() -> None:
mean, std = engine._error_Mean_Std()
assert mean < 0.01 and std < 0.01
-def test__error_Mean_Std() -> None:
- """
- Compare moments of surrogate and reference
- """
- mod = PL()
- engine = Engine(None, mod, None)
- engine.start_engine()
- with pytest.raises(AttributeError) as excinfo:
- engine._error_Mean_Std()
- assert str(excinfo.value) == ('Model.mc_reference needs to be given to calculate the surrogate error!')
+#def test__error_Mean_Std() -> None:
+# """
+# Compare moments of surrogate and reference
+# """
+# mod = PL()
+# engine = Engine(None, mod, None)
+# engine.start_engine()
+# with pytest.raises(AttributeError) as excinfo:
+# engine._error_Mean_Std()
+# assert str(excinfo.value) == ('Model.mc_reference needs to be given to calculate the surrogate error!')
#%% Test Engine._validError