further checks on documentation and cuda

Author: lorenzotomada

.github/workflows/tests.yml

@@ -19,7 +19,7 @@ jobs:
     name: Testing using pytest
     runs-on: ubuntu-latest
     container:
-      image: nvidia/cuda:12.1.0-devel-ubuntu22.04
+      image: nvidia/cuda:12.1.1-devel-ubuntu22.04
 
     steps:
     - uses: actions/checkout@v3

src/pyclassify/eigenvalues.py

@@ -21,7 +21,8 @@ def eigenvalues_np(A, symmetric=True):
     """
     Compute the eigenvalues of a square matrix using NumPy's `eig` or `eigh` function.
 
-    This function checks if the input matrix is square (and is actually a matrix) using 'check_square_matrix', and then computes its eigenvalues.
+    This function checks if the input matrix is square (and is actually a matrix) using
+    'check_square_matrix', and then computes its eigenvalues.
     If the matrix is symmetric, it uses `eigh` (which is more efficient for symmetric matrices).
     Otherwise, it uses `eig`.
 
@@ -80,13 +81,13 @@ 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.
-    IMPORTANT: it important to underline a couple of things regarding this function:
-    - installing using the command 'python -m pip install cupy-cuda12x' does not allow, for some reason,
-      to import cupyx.scipy.sparse.linalg, and it necessary to import the
-      function manually form the source code. The problem can be observed using python3.10, while for
-      python3.12 things seem to work.
-    - the eighs 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).
+    IMPORTANT: it important to underline a couple of things regarding this function. The first one is that,
+    installing using the command 'python -m pip install cupy-cuda12x', does not allow, for some reason,
+    to import cupyx.scipy.sparse.linalg, and it necessary to import the function manually form the source
+    code. The problem can be observed using python3.10, while for python3.12 things seem to work.
+    The second one is that the 'eighs' 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).
 
     Args:
         A (cpsp.spmatrix): A square sparse matrix whose eigenvalues are to be computed.
@@ -99,7 +100,7 @@ def eigenvalues_cp(A):
         ValueError: If number of rows != number of columns.
     """
     check_symm_square(A)
-    k = 5 if A.shape[0] > 5 else A.shape[0] - 2
+    k = 6 if A.shape[0] > 5 else A.shape[0] - 2
     eigenvalues, _ = cp_eigsh(A, k=k)
     return eigenvalues