Merge branch 'main' into MMathisLab-icon

Author: MMathisLab

.dockerignore

@@ -5,3 +5,5 @@ tests/
 third_party/
 tools/
 PKGBUILD
+
+!docs/requirements.txt

.github/workflows/build.yml

@@ -10,6 +10,7 @@ on:
 
 jobs:
   build:
+    timeout-minutes: 30
     strategy:
       fail-fast: true
       matrix:
@@ -67,6 +68,10 @@ jobs:
         run: |
           make codespell
 
+      - name: Check the documentation coverage
+        run: |
+          make interrogate
+
       - name: Check CITATION.cff validity
         run: |
           cffconvert --validate

.github/workflows/doc-coverage.yml

@@ -7,14 +7,6 @@ on:
   pull_request:
     branches:
       - main
-      - public
-      - dev
-    paths:
-      - '**.py'
-      - '**.ipynb'
-      - '**.js'
-      - '**.rst'
-      - '**.md'
 
 jobs:
   build:
@@ -55,12 +47,16 @@ jobs:
         with:
           repository: AdaptiveMotorControlLab/cebra-demos
           path: docs/source/demo_notebooks
-          ref: main
+          # NOTE(stes): This is a temporary branch to add the xCEBRA demo notebooks
+          # to the docs. Once the notebooks are merged into main, we can remove this
+          # branch and change the ref to main.
+          # ref: main
+          ref: stes/add-xcebra
 
-      - name: Set up Python ${{ matrix.python-version }}
+      - name: Set up Python 3.10
         uses: actions/setup-python@v5
         with:
-          python-version: ${{ matrix.python-version }}
+          python-version: "3.10"
 
       - name: Install package
         run: |
@@ -69,17 +65,21 @@ jobs:
           # as of 29/10/23. Ubuntu 22.04 which is used for ubuntu-latest only has an
           # old pandoc version (2.9.). We will hence install the latest version manually.
           # previou: sudo apt-get install -y pandoc
-          wget https://github.com/jgm/pandoc/releases/download/3.1.9/pandoc-3.1.9-1-amd64.deb
-          sudo dpkg -i pandoc-3.1.9-1-amd64.deb
-          rm pandoc-3.1.9-1-amd64.deb
-          pip install torch --extra-index-url https://download.pytorch.org/whl/cpu
-          pip install '.[docs]'
+          # NOTE(stes): Updated to latest version as of 17/04/2025, v3.6.4.
+          wget -q https://github.com/jgm/pandoc/releases/download/3.6.4/pandoc-3.6.4-1-amd64.deb
+          sudo dpkg -i pandoc-3.6.4-1-amd64.deb
+          rm pandoc-3.6.4-1-amd64.deb
+          pip install -r docs/requirements.txt
 
+      - name: Check software versions
+        run: |
+          sphinx-build --version
+          pandoc --version
 
       - name: Build docs
         run: |
           ls docs/source/cebra-figures
-          # later also add the -n option to check for broken links
+          export SPHINXBUILD="sphinx-build"
           export SPHINXOPTS="-W --keep-going -n"
           make docs
 

.github/workflows/docs.yml

@@ -7,6 +7,25 @@ experiments/sweeps
 exports/
 demo_notebooks/
 assets/
+.remove
+
+# demo run
+.vscode/
+auxiliary_behavior_data.h5
+cebra_model.pt
+data.npz
+grid_search_models/
+neural_data.npz
+saved_models/
+
+# demo run
+.vscode/
+auxiliary_behavior_data.h5
+cebra_model.pt
+data.npz
+grid_search_models/
+neural_data.npz
+saved_models/
 
 # Binary files
 *.png

.gitignore

@@ -40,7 +40,7 @@ RUN make dist
 FROM cebra-base
 
 # install the cebra wheel
-ENV WHEEL=cebra-0.5.0-py3-none-any.whl
+ENV WHEEL=cebra-0.6.0a1-py3-none-any.whl
 WORKDIR /build
 COPY --from=wheel /build/dist/${WHEEL} .
 RUN pip install --no-cache-dir ${WHEEL}'[dev,integrations,datasets]'

Dockerfile

@@ -1,4 +1,4 @@
-CEBRA_VERSION := 0.5.0
+CEBRA_VERSION := 0.6.0a1
 
 dist:
 	python3 -m pip install virtualenv
@@ -55,7 +55,7 @@ interrogate:
 		--ignore-private \
 		--ignore-magic \
 		--omit-covered-files \
-		-f 90 \
+		-f 80 \
 		cebra
 
 # Build documentation using sphinx

Makefile

@@ -35,3 +35,83 @@
     - 'tests/**/*.py'
     - 'docs/**/*.py'
     - 'conda/**/*.yml'
+
+- header: |
+    CEBRA: Consistent EmBeddings of high-dimensional Recordings using Auxiliary variables
+    © Mackenzie W. Mathis & Steffen Schneider (v0.4.0+)
+    Source code:
+    https://github.com/AdaptiveMotorControlLab/CEBRA
+
+    Please see LICENSE.md for the full license document:
+    https://github.com/AdaptiveMotorControlLab/CEBRA/blob/main/LICENSE.md
+
+    Adapted from https://github.com/rpatrik96/nl-causal-representations/blob/master/care_nl_ica/dep_mat.py,
+    licensed under the following MIT License:
+
+      MIT License
+
+      Copyright (c) 2022 Patrik Reizinger
+
+      Permission is hereby granted, free of charge, to any person obtaining a copy
+      of this software and associated documentation files (the "Software"), to deal
+      in the Software without restriction, including without limitation the rights
+      to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+      copies of the Software, and to permit persons to whom the Software is
+      furnished to do so, subject to the following conditions:
+
+      The above copyright notice and this permission notice shall be included in all
+      copies or substantial portions of the Software.
+
+      THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+      IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+      FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+      AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+      LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+      OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+      SOFTWARE.
+
+  include:
+    - 'cebra/attribution/jacobian.py'
+
+
+- header: |
+    CEBRA: Consistent EmBeddings of high-dimensional Recordings using Auxiliary variables
+    © Mackenzie W. Mathis & Steffen Schneider (v0.4.0+)
+    Source code:
+    https://github.com/AdaptiveMotorControlLab/CEBRA
+
+    Please see LICENSE.md for the full license document:
+    https://github.com/AdaptiveMotorControlLab/CEBRA/blob/main/LICENSE.md
+
+    This file contains the PyTorch implementation of Jacobian regularization described in [1].
+      Judy Hoffman, Daniel A. Roberts, and Sho Yaida,
+      "Robust Learning with Jacobian Regularization," 2019.
+      [arxiv:1908.02729](https://arxiv.org/abs/1908.02729)
+
+    Adapted from https://github.com/facebookresearch/jacobian_regularizer/blob/main/jacobian/jacobian.py
+    licensed under the following MIT License:
+
+      MIT License
+
+      Copyright (c) Facebook, Inc. and its affiliates.
+
+      Permission is hereby granted, free of charge, to any person obtaining a copy
+      of this software and associated documentation files (the "Software"), to deal
+      in the Software without restriction, including without limitation the rights
+      to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+      copies of the Software, and to permit persons to whom the Software is
+      furnished to do so, subject to the following conditions:
+
+      The above copyright notice and this permission notice shall be included in all
+      copies or substantial portions of the Software.
+
+      THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+      IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+      FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+      AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+      LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+      OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+      SOFTWARE.
+
+  include:
+    - 'cebra/models/jacobian_regularizer.py'

NOTICE.yml

@@ -1,7 +1,7 @@
 # Maintainer: Steffen Schneider <[email protected]>
 pkgname=python-cebra
 _pkgname=cebra
-pkgver=0.5.0
+pkgver=0.6.0a1
 pkgrel=1
 pkgdesc="Consistent Embeddings of high-dimensional Recordings using Auxiliary variables"
 url="https://cebra.ai"

PKGBUILD

@@ -66,7 +66,7 @@
 
 import cebra.integrations.sklearn as sklearn
 
-__version__ = "0.5.0"
+__version__ = "0.6.0a1"
 __all__ = ["CEBRA"]
 __allow_lazy_imports = False
 __lazy_imports = {}