Make numpy version requirements stricter to avoid numpy2.0 which has major changes. Future work will try to enable numpy2.0 and greater

Author: jdjakem

.github/workflows/continuous-integration-workflow-conda.yml

@@ -45,7 +45,7 @@ jobs:
       - name: Setup PyApprox
         shell: bash -l {0}
         run: |
-          pip install -e .
+          python -m pip install -e .
       - name: Test PyApprox
         shell: bash -l {0}
         run: |

.github/workflows/continuous-integration-workflow-docs-pip.yml

@@ -37,7 +37,7 @@ jobs:
       - name: Setup PyApprox Documentation
         shell: bash -l {0}
         run: |
-          pip install -e .[docs]
+          python -m pip install -e .[docs]
       - name: Create PyApprox Documentation
         shell: bash -l {0}
         run: |

.github/workflows/continuous-integration-workflow-docs.yml

@@ -43,11 +43,11 @@ jobs:
       - name: Setup PyApprox
         shell: bash -l {0}
         run: |
-          pip install -e . --no-build-isolation
+          python -m pip install -e . --no-build-isolation
       - name: Setup PyApprox Documentation
         shell: bash -l {0}
         run: |
-          pip install -e .[docs]
+          python -m pip install -e .[docs]
       - name: Create PyApprox Documentation
         shell: bash -l {0}
         run: |

.github/workflows/continuous-integration-workflow-pip.yml

@@ -40,7 +40,7 @@ jobs:
           python -m pip install --upgrade pip
       - name: Setup PyApprox
         run: |
-          pip install -e .
+          python -m pip install -e .
       - name: Test PyApprox
         run: |
           pytest -s --cov-report term --cov=pyapprox

environment.yml

@@ -3,8 +3,8 @@ channels:
   - defaults
   - conda-forge
 dependencies:
-  - python>=3.8
-  - numpy>=1.20
+  - python>=3.9
+  - numpy>=1.20,<=1.26.4
   - matplotlib
   - scipy
   - jupyter

pyproject.toml

@@ -4,7 +4,7 @@ requires = [
     "setuptools",
     "wheel",
     "Cython",
-    "numpy>=1.16.4",
+    "numpy>=1.20, <=1.26.4",
     "scipy>=1.0.0",
 ]
 
@@ -27,8 +27,7 @@ classifiers=[
     "Operating System :: OS Independent",
 ]    
 dependencies = [
-    'setuptools',
-    'numpy >= 1.16.4',
+    'numpy >= 1.20, <=1.26.4',
     'matplotlib',
     'scipy >= 1.0.0',
     'Cython',

setup.py

@@ -48,10 +48,10 @@ def no_cythonize(extensions, **_ignore):
         "Operating System :: OS Independent",
     ],
     include_dirs=[np.get_include()],
-    setup_requires=['setuptools', 'numpy >= 1.16.4', 'Cython',
+    setup_requires=['setuptools', 'numpy >= 1.20, <=1.26.4', 'Cython',
                     'scipy >= 1.0.0'],
     install_requires=[
-        'numpy >= 1.16.4',
+        'numpy >= 1.20, <=1.26.4',
         'matplotlib',
         'scipy >= 1.0.0',
         'Cython',

tutorials/multi_fidelity/plot_ensemble_selection.py

@@ -111,8 +111,7 @@
 ax = plt.subplots(1, 1, figsize=(8, 6))[1]
 _ = multifidelity.plot_estimator_variance_reductions(
     best_ests, est_labels, ax)
-ax.set_xlabel(mathrm_label("Low fidelity models"))
-plt.show()
+_ = ax.set_xlabel(mathrm_label("Low fidelity models"))
 
 #%%
 #Find the best estimator
@@ -156,5 +155,4 @@
 ax = plt.subplots(1, 1, figsize=(8, 6))[1]
 _ = multifidelity.plot_estimator_variance_reductions(
     best_ests, est_labels, ax)
-ax.set_xlabel(mathrm_label("Estimator types"))
-plt.show()
+_ = ax.set_xlabel(mathrm_label("Estimator types"))