Python 3.12 support + scipy 1.16 fix

.github/workflows/tests.yml

@@ -14,21 +14,23 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ["3.8", "3.9", "3.10"]
+        python-version: ["3.9", "3.10", "3.11", "3.12"]
 
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
       - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v5
         with:
           python-version: ${{ matrix.python-version }}
       - name: Install dependencies
         run: |
           python -m pip install --upgrade pip
           pip install flake8 pytest pytest-cov
           pip --default-timeout=100 install -e .
-          pip --default-timeout=100 install "tensorflow>=2.10,<2.16"
-          # pip --default-timeout=100 install "tensorflow>=2.13"
+      - name: Install TensorFlow
+        # TF <2.16 has no 3.12 wheels (3.12 support requires TF 2.16+/Keras 3)
+        if: matrix.python-version != '3.12'
+        run: pip install "tensorflow>=2.10,<2.16"
       - name: Lint with flake8
         run: |
           # stop the build if there are Python syntax errors or undefined names

ewstools/helpers.py

@@ -106,7 +106,7 @@ def pspec_welch(yVals,
     ham_offset_points = int(ham_offset*ham_length)
 
     ## Compute the periodogram using Welch's method (scipy.signal function)
-    pspec_raw = signal.welch(yVals,
+    pspec_raw = signal.welch(np.asarray(yVals),
                                fs,
                                nperseg=ham_length,
                                noverlap=ham_offset_points,

pyproject.toml

@@ -8,13 +8,13 @@ version = "2.1.2"
 description = "A Python package for early warning signals (EWS) of bifurcations in time series data."
 authors = [{ name = "Thomas M Bury", email = "tombury182@gmail.com" }]
 readme = "README.md"
-requires-python = ">=3.8,<3.12" # Adjust based on your supported Python version
+requires-python = ">=3.9"
 dependencies = [
     "pandas>=0.23.0",
-    "numpy>=1.14.0,<1.25.0",
+    "numpy>=1.26.0,<2.0",  # 1.26 is oldest with 3.12 wheels; <2.0 avoids breaking changes
     "plotly>=2.3.0",
     "lmfit>=0.9.0",
-    "arch>=4.4",
+    "arch>=6.2",  # 6.2 is oldest with compiled 3.12 wheels
     "statsmodels>=0.9.0",
     "scipy>=1.0.1",
     "deprecation>=2.0",
@@ -31,9 +31,13 @@ classifiers = [
 
 [project.optional-dependencies]
 tf = [
-    "tensorflow>=2.10,<=2.16 ; sys_platform != 'win32'",
+    # <=2.16 includes 2.16.0 (Keras 3 breaking change); <2.16 excludes it
+    "tensorflow>=2.10,<2.16 ; sys_platform != 'win32'",
 ]
 
+[tool.pytest.ini_options]
+markers = ["tensorflow: tests requiring TensorFlow (deselect with '-m \"not tensorflow\"')"]
+
 [tool.setuptools.packages]
 find = {}
 

tests/test_ewstools.py

@@ -8,10 +8,6 @@
 import pandas as pd
 import plotly
 
-import tensorflow as tf
-from tensorflow.keras.models import load_model
-from packaging import version
-
 # Import ewstools
 import ewstools
 from ewstools import core
@@ -221,11 +217,16 @@ def test_TimeSeries_ews():
     assert type(fig) == plotly.graph_objs._figure.Figure
 
 
+@pytest.mark.tensorflow
 def test_TimeSeries_dl_preds():
     """
     Test the TimeSeries methods that involve computing DL predictions
 
     """
+    # TF imports moved inside test so rest of suite runs without TF installed
+    tf = pytest.importorskip("tensorflow")
+    from tensorflow.keras.models import load_model
+    from packaging import version
 
     # Simulate a time series
     tVals = np.arange(0, 10, 0.1)