Feature/update packages

azure-pipelines.yml

@@ -5,7 +5,7 @@
 
 
 variables:
-  pythonVersion: 3.9
+  pythonVersion: 3.11
   srcDirectory: src
 
 trigger:

requirements.txt

@@ -1,17 +1,17 @@
-numpy == 1.26.4
-scipy == 1.6.0
-matplotlib == 3.8.4
-scikit-learn == 1.4.2
-fire == 0.6.0
-pytest == 8.2.0
-coverage == 7.5.0
-pytest-cov == 5.0.0
-pylint == 3.1.0
-wheel == 0.43.0
-pytest-azurepipelines == 1.0.5
-twine == 5.0.0
-pathlib~=1.0.1
-beartype == 0.18.5
-setuptools~=65.5.1
-torch ~= 2.2.2
-torchinfo ~= 1.8.0
+numpy >= 1.26.4
+scipy >= 1.6.0
+matplotlib >= 3.8.4
+scikit-learn >= 1.4.2
+fire >= 0.6.0
+pytest >= 8.2.0
+coverage >= 7.5.0
+pytest-cov >= 5.0.0
+pylint >= 3.1.0
+wheel >= 0.43.0
+pytest-azurepipelines >= 1.0.5
+twine >= 5.0.0
+pathlib >= 1.0.1
+beartype >= 0.18.5
+setuptools >= 65.5.1
+torch >= 2.2.2
+torchinfo >= 1.8.0

setup.py

@@ -1,52 +1,61 @@
 #!/usr/bin/env python
 import sys
+
 version = sys.argv[1]
 del sys.argv[1]
 from setuptools import setup, find_packages
 
 from pathlib import Path
+
 this_directory = Path(__file__).parent
 long_description = (this_directory / "README.rst").read_text()
 
 setup(
-    name='UQpy',
+    name="UQpy",
     version=version,
-    url='https://github.com/SURGroup/UQpy',
+    url="https://github.com/SURGroup/UQpy",
     description="UQpy is a general purpose toolbox for Uncertainty Quantification",
     long_description=long_description,
     author="Michael D. Shields, Dimitris G. Giovanis, Audrey Olivier, Aakash Bangalore-Satish, Mohit Chauhan, "
-           "Lohit Vandanapu, Ketson R.M. dos Santos",
-    license='MIT',
+    "Lohit Vandanapu, Ketson R.M. dos Santos",
+    license="MIT",
     platforms=["OSX", "Windows", "Linux"],
     packages=find_packages("src"),
     package_dir={"": "src"},
     package_data={"": ["*.pdf"]},
-    python_requires='>3.9.0',
+    python_requires=">3.9.0",
     install_requires=[
-        "numpy==1.26.4", "scipy>=1.6.0", "matplotlib==3.8.4", "scikit-learn==1.4.2", 'fire==0.6.0',
-        "beartype==0.18.5", "torch ~= 2.2.2", "torchinfo ~= 1.8.0"
+        "numpy >= 1.26.4",
+        "scipy >= 1.6.0",
+        "matplotlib >= 3.8.4",
+        "scikit-learn >= 1.4.2",
+        "fire >= 0.6.0",
+        "beartype >= 0.18.5",
+        "torch >= 2.2.2",
+        "torchinfo >= 1.8.0",
     ],
     extras_require={
-        'dev': [
-            'pytest == 8.2.0',
-            'pytest-cov == 5.0.0',
-            'pylint == 3.1.0',
-            'pytest-azurepipelines == 1.0.5',
-            'pytest-cov == 5.0.0',
-            'wheel == 0.43.0',
-            'twine == 5.0.0',
-            'sphinx_autodoc_typehints == 1.23.0',
-            'sphinx_rtd_theme == 1.2.0',
-            'sphinx_gallery == 0.13.0',
-            'sphinxcontrib_bibtex == 2.5.0',
-            'Sphinx==6.1.3',
+        "dev": [
+            "pytest == 8.2.0",
+            "pytest-cov == 5.0.0",
+            "pylint == 3.1.0",
+            "pytest-azurepipelines == 1.0.5",
+            "pytest-cov == 5.0.0",
+            "wheel == 0.43.0",
+            "twine == 5.0.0",
+            "sphinx_autodoc_typehints == 1.23.0",
+            "sphinx_rtd_theme == 1.2.0",
+            "sphinx_gallery == 0.13.0",
+            "sphinxcontrib_bibtex == 2.5.0",
+            "Sphinx == 6.1.3",
+            "hypothesis ~= 6.131.19"
         ]
     },
     classifiers=[
-        'Programming Language :: Python :: 3',
-        'Intended Audience :: Science/Research',
-        'Topic :: Scientific/Engineering :: Mathematics',
-        'License :: OSI Approved :: MIT License',
-        'Natural Language :: English',
+        "Programming Language :: Python :: 3",
+        "Intended Audience :: Science/Research",
+        "Topic :: Scientific/Engineering :: Mathematics",
+        "License :: OSI Approved :: MIT License",
+        "Natural Language :: English",
     ],
 )

src/UQpy/run_model/model_execution/ThirdPartyModel.py

@@ -227,6 +227,11 @@ def execute_single_sample(self, index, sample_to_send):
     def postprocess_single_file(self, index, model_output):
         if self.output_script is not None:
             output = self._output_serial(index)
+        else:
+            raise RuntimeError(
+                "UQpy: To postprocess a run using postprocess_single_file within RunModel, output_script cannot be equal to None."
+                " See documentation for usage details."
+            )
 
         work_dir = os.path.join(self.model_dir, "run_" + str(index))
         # Remove the copied files and folders

src/UQpy/scientific_machine_learning/functional/generalized_jensen_shannon_divergence.py

@@ -78,7 +78,7 @@ def generalized_jensen_shannon_divergence(
                 alpha * kl_divergence_p_m
             )
     js_divergence /= n_samples
-    js_divergence = torch.tensor(js_divergence, device=device)
+    js_divergence = torch.tensor(js_divergence, device=device, dtype=torch.float32)
 
     if reduction == "none":
         return js_divergence

src/UQpy/sensitivity/PostProcess.py

@@ -67,6 +67,7 @@ def plot_sensitivity_index(
         error = confidence_interval[:, 1] - indices
     else:
         conf_int_flag = False
+        error = None
 
     # x and y data
     _idx = np.arange(num_vars)
@@ -171,12 +172,14 @@ def plot_index_comparison(
         error_1 = confidence_interval_1[:, 1] - indices_1
     else:
         conf_int_flag_1 = False
+        error_1 = None
 
     if confidence_interval_2 is not None:
         conf_int_flag_2 = True
         error_2 = confidence_interval_2[:, 1] - indices_2
     else:
         conf_int_flag_2 = False
+        error_2 = None
 
     # x and y data
     _idx = np.arange(num_vars)
@@ -289,6 +292,7 @@ def plot_second_order_indices(
         error = confidence_interval[:, 1] - indices
     else:
         conf_int_flag = False
+        error = None
 
     # x and y data
     _idx = np.arange(num_second_order_terms)