allow weighted for more cases

tmp: change setup python version to troubleshoot conda

tmp: switch ubuntu image to 20.04 because of latest miniconda issues

tmp: pin name and version in the gh actions

tmp: pin more gh actions

tmp: pin 2024 version

tmp: change to ubuntu-latest, pin miniconda version

tmp: fix indentation

tmp: correct miniconda version name

tmp: set miniconda version to latest

tmp: remove conda path addition

tmp: set mamba and python version

tmp: reset to default conda solver

tmp: redo environment for latest python

tmp: play with the versions

tmp: finish pinning environment, revert ci/cd tasks

tmp: switch nbmake version, fix deep-koopman path

.github/workflows/notebook.yml

@@ -20,12 +20,11 @@ jobs:
         echo $CONDA/bin >> $GITHUB_PATH
     - name: Install dependencies
       run: |
-         conda env update --solver classic --file environment.yml --name base
+        conda env update --file environment.yml --name base
     - name: Test with pytest
       run: |
         pip install .
         conda install pytest
-        pip install nbmake==0.5
+        pip install nbmake==1.5.3
         pytest --nbmake "./notebooks/"
-        pytest
 

.github/workflows/python-package-conda.yml

@@ -20,7 +20,7 @@ jobs:
         echo $CONDA/bin >> $GITHUB_PATH
     - name: Install dependencies
       run: |
-         conda env update --solver classic --file environment.yml --name base
+        conda env update --file environment.yml --name base
     - name: Lint with flake8
       run: |
         conda install flake8

autokoopman/autokoopman.py

@@ -449,14 +449,15 @@ def _sanitize_training_data(
 
     # convert the data to autokoopman trajectories
     if isinstance(training_data, TrajectoriesData):
-        assert scoring_weights is None, f"scoring weights must be None as interpolation is occuring"
         if not isinstance(training_data, UniformTimeTrajectoriesData):
+            assert scoring_weights is None, f"scoring weights must be None as interpolation is occuring"
             print(
                 f"resampling trajectories as they need to be uniform time (sampling period {sampling_period})"
             )
             training_data = training_data.interp_uniform_time(sampling_period)
         else:
             if not np.isclose(training_data.sampling_period, sampling_period):
+                assert scoring_weights is None, f"scoring weights must be None as interpolation is occuring"
                 print(
                     f"resampling trajectories because the sampling periods differ (original {training_data.sampling_period}, new {sampling_period})"
                 )

environment.yml

@@ -3,77 +3,15 @@ channels:
   - conda-forge
   - defaults
 dependencies:
-  - blas=1.0
-  - ca-certificates=2023.08.22
-  - cffi=1.15.1
-  - filelock=3.9.0
-  - gmp=6.2.1
-  - gmpy2=2.1.2
-  - jinja2=3.1.2
-  - libcxx=16.0.6
-  - libffi=3.3
-  - libopenblas=0.3.21
-  - libprotobuf=3.20.3
-  - libsqlite=3.43.2
-  - libuv=1.44.2
-  - libzlib=1.2.13
-  - llvm-openmp=14.0.6
-  - markupsafe=2.1.1
-  - mpc=1.1.0
-  - mpfr=4.0.2
-  - ncurses=6.4
-  - networkx=3.1
-  - ninja=1.10.2
-  - ninja-base=1.10.2
-  - numpy-base=1.26.0
-  - openssl=1.1.1w
-  - pip=23.3.1
-  - pycparser=2.21
-  - python=3.9.0
-  - pytorch=2.0.1
-  - readline=8.2
-  - setuptools=68.2.2
-  - sleef=3.5.1
-  - sqlite=3.43.2
-  - sympy=1.11.1
-  - tk=8.6.13
-  - typing-extensions=4.7.1
-  - typing_extensions=4.7.1
-  - tzdata=2023c
-  - wheel=0.41.2
-  - xz=5.2.6
-  - zlib=1.2.13
+  - pysindy=1.3.0
+  - pip=24.0
+  - matplotlib>=3.3.4
+  - sympy>=1.9
+  - pandas>=1.1.5
+  - pydata-sphinx-theme==0.7.2
+  - conda-forge::scikit-learn
   - pip:
-      - attrs==22.2.0
-      - cmake==3.25.2
-      - contourpy==1.0.7
-      - cycler==0.11.0
-      - cython==0.29.33
-      - decorator==5.1.1
-      - derivative==0.5.3
-      - exceptiongroup==1.1.0
-      - fonttools==4.38.0
-      - gpy==1.10.0
-      - gpyopt==1.2.6
-      - iniconfig==2.0.0
-      - joblib==1.2.0
-      - kiwisolver==1.4.4
-      - matplotlib==3.6.3
-      - mpmath==1.2.1
-      - numpy==1.21.0
-      - packaging==23.0
-      - pandas==1.5.3
-      - paramz==0.9.5
-      - pillow==9.4.0
-      - pluggy==1.0.0
-      - pyparsing==3.0.9
-      - pysindy==1.7.2
-      - pytest==7.2.1
-      - python-dateutil==2.8.2
-      - pytz==2022.7.1
-      - scikit-learn==1.0.2
-      - scipy==1.10.0
-      - six==1.16.0
-      - threadpoolctl==3.1.0
-      - tomli==2.0.1
-      - tqdm==4.64.1
+    - gpy==1.13.1
+    - gpyopt==1.2.6
+    - torch==2.2.1
+    - sphinx_mdinclude==0.5.1

notebooks/deep-koopman.ipynb

@@ -96,6 +96,8 @@
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
     "\n",
+    "import sys\n",
+    "sys.path.append(\"..\")\n",
     "# this is the convenience function\n",
     "from autokoopman import auto_koopman"
    ]
@@ -248,7 +250,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.7"
+   "version": "3.9.0"
   }
  },
  "nbformat": 4,

requirements.txt

@@ -5,5 +5,5 @@ pydata-sphinx-theme==0.7.2
 sphinx_mdinclude==0.5.1
 gpy==1.10.0
 gpyopt==1.2.6
-torch==1.12.1
-pysindy==1.7.2
+torch==2.2.1
+scikit-learn==1.4.1.post1