typos and small errors

README.md

@@ -15,12 +15,6 @@ At the moment, the standard and shifted power method to compute the PageRank wit
 
 Here an example of what's described above.
 
-```bash
-sudo chmod +x main.py
-```
-
-Now we can run the program
-
 ```bash
 ./main.py --dataset Stanford --algo both
 ```

algo.py

@@ -66,6 +66,7 @@ def load_data(dataset: Literal["Stanford", "NotreDame", "BerkStan"]) -> nx.Graph
 
     return G_dataset
 
+
 def google_matrix(G, alpha=0.85, personalization=None, nodelist=None, weight="weight", dangling=None) -> np.matrix:
 
     """Returns the Google matrix of the graph. NetworkX implementation.
@@ -155,6 +156,7 @@ def google_matrix(G, alpha=0.85, personalization=None, nodelist=None, weight="we
 
     return np.asmatrix(alpha * A + (1 - alpha) * p)
 
+
 def google_matrix_sparse(G, alpha=0.85, personalization=None, nodelist=None, weight="weight", dangling=None) -> np.matrix:
 
   """ Revised NetworkX implementation for sparse matrices. Returns the Ptilde matrix of the graph instead of the Google matrix.
@@ -246,6 +248,7 @@ def google_matrix_sparse(G, alpha=0.85, personalization=None, nodelist=None, wei
 
   return A, p
 
+
 def pagerank_numpy(G, alpha=0.85, personalization=None, weight="weight", dangling=None):
     """Returns the PageRank of the nodes in the graph. NetworkX implementation.
 
@@ -307,6 +310,7 @@ def pagerank_numpy(G, alpha=0.85, personalization=None, weight="weight", danglin
     norm = largest.sum()
     return dict(zip(G, map(float, largest / norm)))
 
+
 def pagerank(G, alpha=0.85, personalization=None, max_iter=10000, tol=1.0e-9, nstart=None, weight="weight", dangling=None,):
 
     """
@@ -422,6 +426,7 @@ def pagerank(G, alpha=0.85, personalization=None, max_iter=10000, tol=1.0e-9, ns
     # this is a failure to converges
     raise nx.PowerIterationFailedConvergence(max_iter)
 
+
 def shifted_pow_pagerank(G, alphas=[0.85, 0.9, 0.95, 0.99], max_iter=10000, tol=1.0e-9):
 
     """

testing/arnoldi.ipynb

@@ -136,7 +136,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.8"
+   "version": "3.10.9"
   },
   "orig_nbformat": 4,
   "vscode": {