updating workflows

Author: lorenzotomada

.github/workflows/docs.yml

@@ -17,29 +17,32 @@ jobs:
   docs:
     name: Documentation
     runs-on: ubuntu-latest
+    container:
+      image: cupy/cupy:v13.4.0
+
     steps:
     - uses: actions/checkout@v3
 
-    - name: Set up Python
-      uses: actions/setup-python@v3
-      with:
-        python-version: 3.12.0
-    
-    - name: Set up Python environment
+    - name: Set up git
+      run: apt-get update && apt-get install git -y
+
+    - name: Install system dependencies
       run: |
-        python -m venv venv
-        source venv/bin/activate
+        apt-get update && apt-get install -y python3-venv python3-pip
 
-    - name: Install dependencies
+    - name: Install additional dependencies
       run: |
+        python3 -m venv venv
         source venv/bin/activate
         python -m pip install .
+      shell: bash -e {0}
 
     - name: Generate documentation
       run: |
         source venv/bin/activate
         cd docs
         make html
+      shell: bash -e {0}
 
     - name: Deploy
       if: success()

requirements.txt

@@ -17,7 +17,7 @@ fonttools==4.56.0
 idna==3.10
 imagesize==1.4.1
 iniconfig==2.0.0
-ipython==9.0.1
+ipython==8.33.0
 ipython_pygments_lexers==1.1.1
 jedi==0.19.2
 Jinja2==3.1.5
@@ -46,6 +46,7 @@ pytest==8.3.4
 python-dateutil==2.9.0.post0
 PyYAML==6.0.2
 requests==2.32.3
+roman-numerals-py==3.1.0
 scipy==1.15.2
 setuptools==75.8.0
 six==1.17.0

src/pyclassify/eigenvalues.py

@@ -80,7 +80,7 @@ def eigenvalues_cp(A):
     This function checks if the input matrix is square and symmetric, then computes its eigenvalues using
     CuPy's sparse linear algebra solvers. It uses `eigsh` for more efficient computation.
     Remark that the eigsh function in this case does not allow to compute *all* the eigenvalues, but only a number
-    $m<n$, so here just a reduced portion is computed (starting form the ones which are greater in magnitude).
+    m<n, so here just a reduced portion is computed (starting form the ones which are greater in magnitude).
 
     Args:
         A (cpsp.spmatrix): A square sparse matrix whose eigenvalues are to be computed.