From 6a1eb14e6d9065377aa80b0f33eb9a2fd7e64112 Mon Sep 17 00:00:00 2001
From: kohlhaasrebecca <rebecca.kohlhaas@outlook.com>
Date: Fri, 28 Jun 2024 22:56:04 +0200
Subject: [PATCH] Undo botched rebase
---
.coverage | Bin 0 -> 53248 bytes
.idea/.gitignore | 8 +++
.idea/bayesvalidrox.iml | 18 +++++
.../inspectionProfiles/profiles_settings.xml | 6 ++
.idea/misc.xml | 7 ++
.idea/modules.xml | 8 +++
.idea/other.xml | 6 ++
.idea/vcs.xml | 6 ++
CHANGELOG.md | 5 +-
examples/.coverage | Bin 0 -> 53248 bytes
.../example_analytical_function.py | 66 ++++++++++--------
.../bayes_inference/discrepancy.py | 16 ++++-
.../surrogate_models/__init__.py | 9 ++-
.../surrogate_models/desktop.ini | 2 +
.../surrogate_models/exploration.py | 1 +
src/bayesvalidrox/surrogate_models/inputs.py | 20 +++---
.../surrogate_models/reg_fast_ard.py | 2 +-
tests/test_BayesModelComparison.py | 28 ++++++++
tests/test_Discrepancy.py | 18 +----
tests/test_ExpDesign.py | 49 ++++++++++---
tests/test_Input.py | 6 +-
21 files changed, 207 insertions(+), 74 deletions(-)
create mode 100644 .coverage
create mode 100644 .idea/.gitignore
create mode 100644 .idea/bayesvalidrox.iml
create mode 100644 .idea/inspectionProfiles/profiles_settings.xml
create mode 100644 .idea/misc.xml
create mode 100644 .idea/modules.xml
create mode 100644 .idea/other.xml
create mode 100644 .idea/vcs.xml
create mode 100644 examples/.coverage
create mode 100644 src/bayesvalidrox/surrogate_models/desktop.ini
create mode 100644 tests/test_BayesModelComparison.py
diff --git a/.coverage b/.coverage
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diff --git a/.idea/.gitignore b/.idea/.gitignore
new file mode 100644
index 000000000..13566b81b
--- /dev/null
+++ b/.idea/.gitignore
@@ -0,0 +1,8 @@
+# Default ignored files
+/shelf/
+/workspace.xml
+# Editor-based HTTP Client requests
+/httpRequests/
+# Datasource local storage ignored files
+/dataSources/
+/dataSources.local.xml
diff --git a/.idea/bayesvalidrox.iml b/.idea/bayesvalidrox.iml
new file mode 100644
index 000000000..fab03b6ec
--- /dev/null
+++ b/.idea/bayesvalidrox.iml
@@ -0,0 +1,18 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+ <component name="NewModuleRootManager">
+ <content url="file://$MODULE_DIR$">
+ <sourceFolder url="file://$MODULE_DIR$/src" isTestSource="false" />
+ <sourceFolder url="file://$MODULE_DIR$/tests" isTestSource="true" />
+ </content>
+ <orderEntry type="inheritedJdk" />
+ <orderEntry type="sourceFolder" forTests="false" />
+ </component>
+ <component name="PyDocumentationSettings">
+ <option name="format" value="NUMPY" />
+ <option name="myDocStringFormat" value="NumPy" />
+ </component>
+ <component name="TestRunnerService">
+ <option name="PROJECT_TEST_RUNNER" value="py.test" />
+ </component>
+</module>
\ No newline at end of file
diff --git a/.idea/inspectionProfiles/profiles_settings.xml b/.idea/inspectionProfiles/profiles_settings.xml
new file mode 100644
index 000000000..105ce2da2
--- /dev/null
+++ b/.idea/inspectionProfiles/profiles_settings.xml
@@ -0,0 +1,6 @@
+<component name="InspectionProjectProfileManager">
+ <settings>
+ <option name="USE_PROJECT_PROFILE" value="false" />
+ <version value="1.0" />
+ </settings>
+</component>
\ No newline at end of file
diff --git a/.idea/misc.xml b/.idea/misc.xml
new file mode 100644
index 000000000..a6218fed0
--- /dev/null
+++ b/.idea/misc.xml
@@ -0,0 +1,7 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+ <component name="Black">
+ <option name="sdkName" value="Python 3.11" />
+ </component>
+ <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.11" project-jdk-type="Python SDK" />
+</project>
\ No newline at end of file
diff --git a/.idea/modules.xml b/.idea/modules.xml
new file mode 100644
index 000000000..482c611f3
--- /dev/null
+++ b/.idea/modules.xml
@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+ <component name="ProjectModuleManager">
+ <modules>
+ <module fileurl="file://$PROJECT_DIR$/.idea/bayesvalidrox.iml" filepath="$PROJECT_DIR$/.idea/bayesvalidrox.iml" />
+ </modules>
+ </component>
+</project>
\ No newline at end of file
diff --git a/.idea/other.xml b/.idea/other.xml
new file mode 100644
index 000000000..2e75c2e2a
--- /dev/null
+++ b/.idea/other.xml
@@ -0,0 +1,6 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+ <component name="PySciProjectComponent">
+ <option name="PY_INTERACTIVE_PLOTS_SUGGESTED" value="true" />
+ </component>
+</project>
\ No newline at end of file
diff --git a/.idea/vcs.xml b/.idea/vcs.xml
new file mode 100644
index 000000000..35eb1ddfb
--- /dev/null
+++ b/.idea/vcs.xml
@@ -0,0 +1,6 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+ <component name="VcsDirectoryMappings">
+ <mapping directory="" vcs="Git" />
+ </component>
+</project>
\ No newline at end of file
diff --git a/CHANGELOG.md b/CHANGELOG.md
index be1a97712..42c974fb5 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,8 +1,9 @@
# CHANGELOG
-## v1.0.0
+## [Unreleased]
### Requirements
-* updated for python 3.10
+* numpy now at 1.23.3
+* ....
### Added
Features
diff --git a/examples/.coverage b/examples/.coverage
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z0D-~;%H?Lw{Qm#Ua-J2IEi!@t1Rwwb2tWV=5P$##AOHafK%gLjioH;)o%+o-zyCkC
zoaY5)jBFqP0SG_<0uX=z1Rwwb2tWV=5GYb$fxZDqfB&~m6`3vaf&c^{009U<00Izz
z00bZa0SG{#XaWBHAD{n=R!4pifB*y_009U<00Izz00bZafno)4{r_UUksAac009U<
W00Izz00bZa0SG{#V1e}d|Nj6bO?%Y<
literal 0
HcmV?d00001
diff --git a/examples/analytical-function/example_analytical_function.py b/examples/analytical-function/example_analytical_function.py
index f80767bef..bdf22598a 100644
--- a/examples/analytical-function/example_analytical_function.py
+++ b/examples/analytical-function/example_analytical_function.py
@@ -139,7 +139,7 @@ if __name__ == "__main__":
# One-shot (normal) or Sequential Adaptive (sequential) Design
ExpDesign.method = 'sequential'
- ExpDesign.n_init_samples = 100#3*ndim
+ ExpDesign.n_init_samples = 140#00#3*ndim
# Sampling methods
# 1) random 2) latin_hypercube 3) sobol 4) halton 5) hammersley
@@ -225,7 +225,8 @@ if __name__ == "__main__":
MetaModelOpts.ExpDesign = ExpDesign
engine = Engine(MetaModelOpts, Model, ExpDesign)
engine.start_engine()
- engine.train_sequential()
+ #engine.train_sequential()
+ engine.train_normal()
# Load the objects
# with open(f"PCEModel_{Model.name}.pkl", "rb") as input:
@@ -264,12 +265,12 @@ if __name__ == "__main__":
# BayesOpts.selected_indices = [0, 3, 5, 7, 9]
# BME Bootstrap
- # BayesOpts.bootstrap = True
- # BayesOpts.n_bootstrap_itrs = 500
- # BayesOpts.bootstrap_noise = 100
+ BayesOpts.bootstrap = True
+ BayesOpts.n_bootstrap_itrs = 500
+ BayesOpts.bootstrap_noise = 100
# Bayesian cross validation
- # BayesOpts.bayes_loocv = True
+ BayesOpts.bayes_loocv = True # TODO: test what this does
# Select the inference method
import emcee
@@ -294,31 +295,34 @@ if __name__ == "__main__":
BayesOpts.Discrepancy = DiscrepancyOpts
# -- (Option C) --
- # DiscOutputOpts = Input()
- # # # OutputName = 'Z'
- # DiscOutputOpts.add_marginals()
- # DiscOutputOpts.Marginals[0].Nnme = '$\sigma^2_{\epsilon}$'
- # DiscOutputOpts.Marginals[0].dist_type = 'uniform'
- # DiscOutputOpts.Marginals[0].parameters = [0, 10]
- # BayesOpts.Discrepancy = {'known': DiscrepancyOpts,
- # 'infer': Discrepancy(DiscOutputOpts)}
-
- # BayesOpts.bias_inputs = {'Z':np.arange(0, 10, 1.).reshape(-1,1) / 9}
- # DiscOutputOpts = Input()
- # # OutputName = 'lambda'
- # DiscOutputOpts.add_marginals()
- # DiscOutputOpts.Marginals[0].name = '$\lambda$'
- # DiscOutputOpts.Marginals[0].dist_type = 'uniform'
- # DiscOutputOpts.Marginals[0].parameters = [0, 1]
-
- # # OutputName = 'sigma_f'
- # DiscOutputOpts.add_marginals()
- # DiscOutputOpts.Marginals[1].Name = '$\sigma_f$'
- # DiscOutputOpts.Marginals[1].dist_type = 'uniform'
- # DiscOutputOpts.Marginals[1].parameters = [0, 1e-4]
- # BayesOpts.Discrepancy = Discrepancy(DiscOutputOpts)
- # BayesOpts.Discrepancy = {'known': DiscrepancyOpts,
- # 'infer': Discrepancy(DiscOutputOpts)}
+ if 0:
+ DiscOutputOpts = Input()
+ # # # OutputName = 'Z'
+ DiscOutputOpts.add_marginals()
+ DiscOutputOpts.Marginals[0].Nnme = '$\sigma^2_{\epsilon}$'
+ DiscOutputOpts.Marginals[0].dist_type = 'uniform'
+ DiscOutputOpts.Marginals[0].parameters = [0, 10]
+ #BayesOpts.Discrepancy = {'known': DiscrepancyOpts,
+ # 'infer': Discrepancy(DiscOutputOpts)}
+
+ BayesOpts.bias_inputs = {'Z':np.arange(0, 10, 1.).reshape(-1,1) / 9}
+
+ DiscOutputOpts = Input()
+ # OutputName = 'lambda'
+ DiscOutputOpts.add_marginals()
+ DiscOutputOpts.Marginals[0].name = '$\lambda$'
+ DiscOutputOpts.Marginals[0].dist_type = 'uniform'
+ DiscOutputOpts.Marginals[0].parameters = [0, 1]
+
+ # # OutputName = 'sigma_f'
+ DiscOutputOpts.add_marginals()
+ DiscOutputOpts.Marginals[1].Name = '$\sigma_f$'
+ DiscOutputOpts.Marginals[1].dist_type = 'uniform'
+ DiscOutputOpts.Marginals[1].parameters = [0, 1e-4]
+ #BayesOpts.Discrepancy = Discrepancy(DiscOutputOpts)
+ BayesOpts.Discrepancy = {'known': DiscrepancyOpts,
+ 'infer': Discrepancy(DiscOutputOpts)}
+
# Start the calibration/inference
Bayes_PCE = BayesOpts.create_inference()
diff --git a/src/bayesvalidrox/bayes_inference/discrepancy.py b/src/bayesvalidrox/bayes_inference/discrepancy.py
index fff32a250..b3c235ebe 100644
--- a/src/bayesvalidrox/bayes_inference/discrepancy.py
+++ b/src/bayesvalidrox/bayes_inference/discrepancy.py
@@ -36,7 +36,7 @@ class Discrepancy:
* Option B: With unknown redidual covariance matrix \\(\\Sigma\\),
paramethrized as \\(\\Sigma(\\theta_{\\epsilon})=\\sigma^2 \\textbf{I}_
{N_{out}}\\) with unknown residual variances \\(\\sigma^2\\).
- This term will be jointly infer with the uncertain input parameters. For
+ This term will be jointly infered with the uncertain input parameters. For
the inversion, you need to define a prior marginal via `Input` class. Note
that \\(\\sigma^2\\) is only a single scalar multiplier for the diagonal
entries of the covariance matrix \\(\\Sigma\\).
@@ -58,10 +58,17 @@ class Discrepancy:
"""
def __init__(self, InputDisc='', disc_type='Gaussian', parameters=None):
+ # Set the values
self.InputDisc = InputDisc
self.disc_type = disc_type
self.parameters = parameters
-
+
+ # Other inits
+ self.ExpDesign = None
+ self.n_samples = None
+ self.sigma2_prior = None
+ self.name = None
+ self.opt_sigma = None # This will be set in the inference class and used in mcmc
# -------------------------------------------------------------------------
def get_sample(self, n_samples):
"""
@@ -87,6 +94,11 @@ class Discrepancy:
# Create and store BoundTuples
self.ExpDesign = ExpDesigns(self.InputDisc)
self.ExpDesign.sampling_method = 'random'
+
+ # TODO: why does it call 'generate_ED' instead of 'generate_samples?
+ # ExpDesign.bound_tuples, onp_sigma, prior_space needed from the outside
+ # Discrepancy opt_sigma, InputDisc needed from the outside
+ # TODO: opt_sigma not defined here, but called from the outside??
self.ExpDesign.generate_ED(
n_samples, max_pce_deg=1
)
diff --git a/src/bayesvalidrox/surrogate_models/__init__.py b/src/bayesvalidrox/surrogate_models/__init__.py
index 70bfb20f5..6d8ce9f1c 100644
--- a/src/bayesvalidrox/surrogate_models/__init__.py
+++ b/src/bayesvalidrox/surrogate_models/__init__.py
@@ -1,7 +1,12 @@
# -*- coding: utf-8 -*-
-
+from .engine import Engine
+from .exp_designs import ExpDesigns
+from .input_space import InputSpace
from .surrogate_models import MetaModel
__all__ = [
- "MetaModel"
+ "MetaModel",
+ "InputSpace",
+ "ExpDesigns",
+ "Engine"
]
diff --git a/src/bayesvalidrox/surrogate_models/desktop.ini b/src/bayesvalidrox/surrogate_models/desktop.ini
new file mode 100644
index 000000000..632de13ae
--- /dev/null
+++ b/src/bayesvalidrox/surrogate_models/desktop.ini
@@ -0,0 +1,2 @@
+[LocalizedFileNames]
+exploration.py=@exploration.py,0
diff --git a/src/bayesvalidrox/surrogate_models/exploration.py b/src/bayesvalidrox/surrogate_models/exploration.py
index 6abb652f1..67decae2b 100644
--- a/src/bayesvalidrox/surrogate_models/exploration.py
+++ b/src/bayesvalidrox/surrogate_models/exploration.py
@@ -33,6 +33,7 @@ class Exploration:
def __init__(self, ExpDesign, n_candidate,
mc_criterion='mc-intersite-proj-th'):
+ self.closestPoints = None
self.ExpDesign = ExpDesign
self.n_candidate = n_candidate
self.mc_criterion = mc_criterion
diff --git a/src/bayesvalidrox/surrogate_models/inputs.py b/src/bayesvalidrox/surrogate_models/inputs.py
index 094e1066f..40ae36337 100644
--- a/src/bayesvalidrox/surrogate_models/inputs.py
+++ b/src/bayesvalidrox/surrogate_models/inputs.py
@@ -4,6 +4,7 @@
Inputs and related marginal distributions
"""
+
class Input:
"""
A class to define the uncertain input parameters.
@@ -20,17 +21,18 @@ class Input:
-------
Marginals can be defined as following:
- >>> Inputs.add_marginals()
- >>> Inputs.Marginals[0].name = 'X_1'
- >>> Inputs.Marginals[0].dist_type = 'uniform'
- >>> Inputs.Marginals[0].parameters = [-5, 5]
+ >>> inputs = Inputs()
+ >>> inputs.add_marginals()
+ >>> inputs.Marginals[0].name = 'X_1'
+ >>> inputs.Marginals[0].dist_type = 'uniform'
+ >>> inputs.Marginals[0].parameters = [-5, 5]
If there is no common data is avaliable, the input data can be given
as following:
- >>> Inputs.add_marginals()
- >>> Inputs.Marginals[0].name = 'X_1'
- >>> Inputs.Marginals[0].input_data = input_data
+ >>> inputs.add_marginals()
+ >>> inputs.Marginals[0].name = 'X_1'
+ >>> inputs.Marginals[0].input_data = [0,0,1,0]
"""
poly_coeffs_flag = True
@@ -63,12 +65,12 @@ class Marginal:
dist_type : string
Name of the distribution. The default is `None`.
parameters : list
- List of the parameters corresponding to the distribution type. The
+ Parameters corresponding to the distribution type. The
default is `None`.
input_data : array
Available input data. The default is `[]`.
moments : list
- List of the moments.
+ Moments of the distribution. The default is `None`.
"""
def __init__(self):
diff --git a/src/bayesvalidrox/surrogate_models/reg_fast_ard.py b/src/bayesvalidrox/surrogate_models/reg_fast_ard.py
index e6883a3ed..fdd0ee747 100755
--- a/src/bayesvalidrox/surrogate_models/reg_fast_ard.py
+++ b/src/bayesvalidrox/surrogate_models/reg_fast_ard.py
@@ -236,7 +236,7 @@ class RegressionFastARD(LinearModel, RegressorMixin):
self.var_y = False
A = np.PINF * np.ones(n_features)
- active = np.zeros(n_features, dtype=np.bool)
+ active = np.zeros(n_features, dtype=bool)
if self.start is not None and not hasattr(self, 'active_'):
start = self.start
diff --git a/tests/test_BayesModelComparison.py b/tests/test_BayesModelComparison.py
new file mode 100644
index 000000000..91f328ec7
--- /dev/null
+++ b/tests/test_BayesModelComparison.py
@@ -0,0 +1,28 @@
+# -*- coding: utf-8 -*-
+"""
+Test the BayesModelComparison class in bayesvalidrox.
+Tests are available for the following functions
+Class BayesModelComparison:
+ create_model_comparison
+ compare_models
+ generate_dataset
+ __perturb_data
+ cal_model_weight
+ plot_just_analysis
+ plot_model_weights
+ plot_bayes_factor
+
+"""
+import sys
+sys.path.append("src/")
+import pytest
+import numpy as np
+
+from bayesvalidrox.bayes_inference.bayes_model_comparison import BayesModelComparison
+#from bayesvalidrox.surrogate_models.input_space import InputSpace
+
+def test_BMC() -> None:
+ """
+ Build BMC without inputs
+ """
+ BayesModelComparison()
\ No newline at end of file
diff --git a/tests/test_Discrepancy.py b/tests/test_Discrepancy.py
index c46e0a137..7fb948d90 100644
--- a/tests/test_Discrepancy.py
+++ b/tests/test_Discrepancy.py
@@ -36,22 +36,8 @@ def test_get_sample() -> None:
"""
Get discrepancy sample
"""
- inp = Input()
- inp.add_marginals()
- inp.Marginals[0].dist_type = 'normal'
- inp.Marginals[0].parameters = [0,1]
- disc = Discrepancy(InputDisc = inp)
+ disc = Discrepancy()
with pytest.raises(AttributeError) as excinfo:
disc.get_sample(2)
assert str(excinfo.value) == 'Cannot create new samples, please provide input distributions'
-
-
-
-
-if __name__ == '__main__':
- inp = Input()
- inp.add_marginals()
- inp.Marginals[0].dist_type = 'normal'
- inp.Marginals[0].parameters = [0,1]
- disc = Discrepancy(InputDisc = inp)
- disc.get_sample(2)
\ No newline at end of file
+
\ No newline at end of file
diff --git a/tests/test_ExpDesign.py b/tests/test_ExpDesign.py
index 3da00d32e..0a1191799 100644
--- a/tests/test_ExpDesign.py
+++ b/tests/test_ExpDesign.py
@@ -135,6 +135,47 @@ def test_random_sampler() -> None:
exp = ExpDesigns(inp)
exp.random_sampler(4)
+def test_random_sampler_largedatanoJDist() -> None:
+ """
+ Sample randomly, init_param_space implicitly, more samples wanted than given, no JDist available
+ """
+ x = np.random.uniform(0,1,1000)
+ inp = Input()
+ inp.add_marginals()
+ inp.Marginals[0].input_data = x
+ exp = ExpDesigns(inp)
+ with pytest.raises(AttributeError) as excinfo:
+ exp.random_sampler(100000)
+ assert str(excinfo.value) == 'Sampling cannot proceed, build ExpDesign with max_deg != 0 to create JDist!'
+
+def test_random_sampler_largedataJDist0() -> None:
+ """
+ Sample randomly, init_param_space implicitly, more samples wanted than given,
+ JDist available, priors given via samples
+ """
+ x = np.random.uniform(0,1,1000)
+ inp = Input()
+ inp.add_marginals()
+ inp.Marginals[0].input_data = x
+ exp = ExpDesigns(inp)
+ exp.init_param_space(max_deg = 1)
+ exp.random_sampler(100000)
+
+def test_random_sampler_largedataJDist1() -> None:
+ """
+ Sample randomly, init_param_space implicitly, more samples wanted than given,
+ JDist available, prior distributions given
+ """
+ inp = Input()
+ inp.add_marginals()
+ inp.Marginals[0].dist_type = 'normal'
+ inp.Marginals[0].parameters = [0,1]
+ exp = ExpDesigns(inp)
+ exp.init_param_space(max_deg = 1)
+ exp.random_sampler(100000)
+
+
+
def test_random_sampler_rawdata() -> None:
"""
Sample randomly, init_param_space implicitly, has 2d raw data
@@ -374,11 +415,3 @@ def test_read_from_file():
exp = ExpDesigns(inp, sampling_method = 'user')
exp.hdf5_file = 'tests/ExpDesign_testfile.hdf5'
exp.read_from_file(['Z'])
-
-if __name__ == '__main__':
- x = np.random.uniform(0,1,1000)
- inp = Input()
- inp.add_marginals()
- inp.Marginals[0].input_data = x
- exp = ExpDesigns(inp, sampling_method = 'PCM')
- exp.generate_ED(4)
\ No newline at end of file
diff --git a/tests/test_Input.py b/tests/test_Input.py
index 84b9b239c..41c0e5ab8 100644
--- a/tests/test_Input.py
+++ b/tests/test_Input.py
@@ -9,10 +9,10 @@ Class Input:
@author: Rebecca Kohlhaas
"""
import sys
-sys.path.append("src/")
-import pytest
-from bayesvalidrox.surrogate_models.inputs import Marginal, Input
+from bayesvalidrox.surrogate_models.inputs import Input
+
+sys.path.append("src/")
def test_addmarginals() -> None:
--
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