Fix typos in documentation and code comments (#225)

- Fix 'qudratic' to 'quadratic' in pyproject.toml keywords
- Fix 'gauranteed' to 'guaranteed' in generic.py docstring
- Fix 'conver' to 'convert' in generic.py comment
- Remove commented-out dead code in generic.py

Author: Ao-chuba

procrustes/generic.py

@@ -55,7 +55,7 @@ def generic(
        \underbrace{\text{min}}_{\mathbf{T}} \quad \|\mathbf{A} \mathbf{T} - \mathbf{B}\|_{F}^2
 
     This Procrustes method requires the :math:`\mathbf{A}` and :math:`\mathbf{B}` matrices to
-    have the same shape, which is gauranteed with the default ``pad`` argument for any given
+    have the same shape, which is guaranteed with the default ``pad`` argument for any given
     :math:`\mathbf{A}` and :math:`\mathbf{B}` matrices. In preparing the :math:`\mathbf{A}` and
     :math:`\mathbf{B}` matrices, the (optional) order of operations is: **1)** unpad zero
     rows/columns, **2)** translate the matrices to the origin, **3)** weight entries of
@@ -124,11 +124,10 @@ def generic(
         a_inv = pinv(np.dot(new_a.T, new_a))
     # add little bit of random noise when the matrix is ill conditioned
     except np.linalg.LinAlgError:
-        # conver new_a to float if it is not
+        # convert new_a to float if it is not
         new_a = new_a.astype(float)
         new_a += 2e-14 * np.random.random_sample((new_a.shape[0], new_a.shape[1])) - 1e-14
         a_inv = pinv(np.dot(new_a.T, new_a))
-    # a_inv = pinv(np.dot(new_a.T, new_a))
 
     array_x = np.linalg.multi_dot([a_inv, new_a.T, new_b])
     # compute one-sided error

pyproject.toml

@@ -33,7 +33,7 @@ authors = [
 keywords = [
     "procrustes analysis",
     "statistical shape analysis",
-    "qudratic assignment problem",
+    "quadratic assignment problem",
     "matrix transformation",
     "generalized procrustes analysis",
     "orthogonal procrustes problem",