Spellcheck (#399)

* update spellings and rebind.

_typos.toml

@@ -0,0 +1,13 @@
+[default.extend-words]
+preconditioner = "preconditioner"
+MIS = "MIS"
+Cleary = "Cleary"
+ser = "ser"
+[default.extend-identifiers]
+[default]
+extend-ignore-identifiers-re = [
+"sort_2nd",
+".*_fiter",
+]
+[type.cpp]
+extend-glob = ["*.h"]

docs/paper/common.py

@@ -21,7 +21,7 @@ def set_figure(fontsize=9, width=251.0, heightratio=None, height=None):
     alternatively, '\message{Column width: \the\columnwidth}' will print to the log
 
     \linewidth should be used in place of \columnwidth if the figure is used
-    within special enviroments (e.g. minipage)
+    within special environments (e.g. minipage)
 
     https://matplotlib.org/stable/tutorials/introductory/customizing.html
     https://scipy-cookbook.readthedocs.io/items/Matplotlib_LaTeX_Examples.html

pyamg/aggregation/tests/test_smooth.py

@@ -619,7 +619,7 @@ def test_prefilter(self):
             assert_equal(ml_nofilter.levels[0].P.nnz
                          > ml_filter.levels[0].P.nnz, True)
 
-# class TestSatisfyConstaints(TestCase):
+# class TestSatisfyConstraints(TestCase):
 #    def test_scalar(self):
 #
 #        U = bsr_matrix([[1,2],[2,1]], blocksize=(1,1))

pyamg/amg_core/air.h

@@ -128,7 +128,7 @@ void approx_ideal_restriction_pass1(      I Rp[], const int Rp_size,
     I nnz = 0;
     Rp[0] = 0;
 
-    // Deterimine number of nonzeros in each row of R.
+    // Determine number of nonzeros in each row of R.
     for (I row=0; row<Cpts_size; row++) {
         I cpoint = Cpts[row];
 
@@ -288,7 +288,7 @@ void approx_ideal_restriction_pass2(const I Rp[], const int Rp_size,
         std::vector<T> b0(size_N, 0);
         for (I i=Rp[row]; i<ind; i++) {
             // Search for indice in row of A. If indice not found, b0 has been
-            // intitialized to zero.
+            // initialized to zero.
             for (I k=Ap[cpoint]; k<Ap[cpoint+1]; k++) {
                 if (Rj[i] == Aj[k]) {
                     b0[temp_b] = -Ax[k];

pyamg/amg_core/air_bind.cpp

@@ -207,7 +207,6 @@ PYBIND11_MODULE(air, m) {
     Methods
     -------
     one_point_interpolation
-    sort_2nd
     approx_ideal_restriction_pass1
     approx_ideal_restriction_pass2
     block_approx_ideal_restriction_pass2
@@ -322,7 +321,7 @@ Rx[] must be passed in initialized to zero.)pbdoc");
         py::arg("Rp").noconvert(), py::arg("Rj").noconvert(), py::arg("Rx").noconvert(), py::arg("Ap").noconvert(), py::arg("Aj").noconvert(), py::arg("Ax").noconvert(), py::arg("Cp").noconvert(), py::arg("Cj").noconvert(), py::arg("Cx").noconvert(), py::arg("Cpts").noconvert(), py::arg("splitting").noconvert(), py::arg("blocksize"), py::arg("distance"), py::arg("use_gmres"), py::arg("maxiter"), py::arg("precondition"),
 R"pbdoc(
 Build column indices and data array for approximate ideal restriction
-in CSR format.
+in BSR format.
 
 Parameters
 ----------

pyamg/amg_core/evolution_strength.h

@@ -131,9 +131,9 @@ void apply_absolute_distance_filter(const I n_row,
  * >>> indices = array([0,1,2,0,1,2,0,1,2])
  * >>> data = array([1.,2.,3.,4.,1.,2.,3.,9.,1.])
  * >>> S = csr_matrix( (data,indices,indptr), shape=(3,3) )
- * >>> print "Matrix BEfore Applying Filter\n" + str(S.todense())
+ * >>> print "Matrix before Applying Filter\n" + str(S.todense())
  * >>> apply_distance_filter(3, 1.9, S.indptr, S.indices, S.data)
- * >>> print "Matrix AFter Applying Filter\n" + str(S.todense())
+ * >>> print "Matrix after Applying Filter\n" + str(S.todense())
  */
 template<class I, class T>
 void apply_distance_filter(const I n_row,
@@ -207,10 +207,10 @@ void apply_distance_filter(const I n_row,
  * >>> data = round(10*rand(6,2,2), decimals=1)
  * >>> S = bsr_matrix( (data,col,row), shape=(6,6) )
  * >>> T = zeros(data.shape[0])
- * >>> print "Matrix BEfore\n" + str(S.todense())
+ * >>> print "Matrix before\n" + str(S.todense())
  * >>> min_blocks(6, 4, ravel(S.data), T)
  * >>> S2 = csr_matrix((T, S.indices, S.indptr), shape=(3,3))
- * >>> print "Matrix AFter\n" + str(S2.todense())
+ * >>> print "Matrix after\n" + str(S2.todense())
  */
 template<class I, class T>
 void min_blocks(const I n_blocks,
@@ -541,7 +541,7 @@ void evolution_strength_helper(      T Sx[], const int Sx_size,
 
 
 /* For use in incomplete_mat_mult_csr(...)
- * Calcuate <A_{row,:}, B_{:, col}>
+ * Calculate <A_{row,:}, B_{:, col}>
  *
  * Parameters
  * ----------

pyamg/amg_core/evolution_strength_bind.cpp

@@ -287,9 +287,9 @@ Examples
 >>> indices = array([0,1,2,0,1,2,0,1,2])
 >>> data = array([1.,2.,3.,4.,1.,2.,3.,9.,1.])
 >>> S = csr_matrix( (data,indices,indptr), shape=(3,3) )
->>> print "Matrix BEfore Applying Filter\n" + str(S.todense())
+>>> print "Matrix before Applying Filter\n" + str(S.todense())
 >>> apply_distance_filter(3, 1.9, S.indptr, S.indices, S.data)
->>> print "Matrix AFter Applying Filter\n" + str(S.todense()))pbdoc");
+>>> print "Matrix after Applying Filter\n" + str(S.todense()))pbdoc");
 
     m.def("min_blocks", &_min_blocks<int, float>,
         py::arg("n_blocks"), py::arg("blocksize"), py::arg("Sx").noconvert(), py::arg("Tx").noconvert());
@@ -333,10 +333,10 @@ Examples
 >>> data = round(10*rand(6,2,2), decimals=1)
 >>> S = bsr_matrix( (data,col,row), shape=(6,6) )
 >>> T = zeros(data.shape[0])
->>> print "Matrix BEfore\n" + str(S.todense())
+>>> print "Matrix before\n" + str(S.todense())
 >>> min_blocks(6, 4, ravel(S.data), T)
 >>> S2 = csr_matrix((T, S.indices, S.indptr), shape=(3,3))
->>> print "Matrix AFter\n" + str(S2.todense()))pbdoc");
+>>> print "Matrix after\n" + str(S2.todense()))pbdoc");
 
     m.def("evolution_strength_helper", &_evolution_strength_helper<int, float, float>,
         py::arg("Sx").noconvert(), py::arg("Sp").noconvert(), py::arg("Sj").noconvert(), py::arg("nrows"), py::arg("x").noconvert(), py::arg("y").noconvert(), py::arg("b").noconvert(), py::arg("BDBCols"), py::arg("NullDim"), py::arg("tol"));

pyamg/amg_core/graph-todo.md

@@ -1,4 +1,4 @@
-check for non-negative weigths in A
+check for non-negative weights in A
 
 tests:
 - 6 node undirected, unit length

pyamg/amg_core/linalg.h

@@ -1060,7 +1060,7 @@ void csc_scale_rows(const I n_row,
  * num_rows : int
  *     number of rows in A
  * theta : float
- *     stength of connection tolerance
+ *     strength of connection tolerance
  * Ap : array
  *     CSR row pointer
  * Aj : array
@@ -1176,7 +1176,7 @@ std::vector<T> QR(T A[],
                   const I &n,
                   const I is_col_major)
 {
-    // Funciton pointer for row or column major matrices
+    // Function pointer for row or column major matrices
     I (*get_ind)(const I, const I, const I);
     const I *C;
     if (is_col_major) {
@@ -1429,7 +1429,7 @@ void lower_tri_solve(const T L[],
  * Returns
  * -------
  * x : vector<double>
- *    Solution to constrained least sqaures problem.
+ *    Solution to constrained least squares problem.
  *
  * Notes
  * -----
@@ -1458,7 +1458,7 @@ void least_squares(T A[],
     // Take QR of A
     std::vector<T> Q = QR(A,m,n,is_col_major);
 
-    // Multiply right hand side, b:= Q^T*b. Have to make new vetor, rhs.
+    // Multiply right hand side, b:= Q^T*b. Have to make new vector, rhs.
     std::vector<T> rhs(m,0);
     for (I i=0; i<m; i++) {
         for (I k=0; k<m; k++) {

pyamg/amg_core/linalg_bind.cpp

@@ -261,7 +261,7 @@ Parameters
 num_rows : int
     number of rows in A
 theta : float
-    stength of connection tolerance
+    strength of connection tolerance
 Ap : array
     CSR row pointer
 Aj : array

pyamg/amg_core/relaxation.h

@@ -908,7 +908,7 @@ void gauss_seidel_nr(const I Ap[], const int Ap_size,
  * omega : float
  *     damping parameter
  * blocksize int
- *     dimension of sqare blocks in BSR matrix A
+ *     dimension of square blocks in BSR matrix A
  */
 template<class I, class T, class F>
 void block_jacobi(const I Ap[], const int Ap_size,

pyamg/amg_core/relaxation_bind.cpp

@@ -1048,7 +1048,7 @@ x is modified inplace in an additive, not overwriting fashion
 
 Notes
 -----
-Primary calling routine is gass_seidel_ne in relaxation.py)pbdoc");
+Primary calling routine is gauss_seidel_ne in relaxation.py)pbdoc");
 
     m.def("gauss_seidel_nr", &_gauss_seidel_nr<int, float, float>,
         py::arg("Ap").noconvert(), py::arg("Aj").noconvert(), py::arg("Ax").noconvert(), py::arg("x").noconvert(), py::arg("z").noconvert(), py::arg("col_start"), py::arg("col_stop"), py::arg("col_step"), py::arg("Tx").noconvert(), py::arg("omega"));
@@ -1132,7 +1132,7 @@ row_step : int
 omega : float
     damping parameter
 blocksize int
-    dimension of sqare blocks in BSR matrix A)pbdoc");
+    dimension of square blocks in BSR matrix A)pbdoc");
 
     m.def("block_jacobi_indexed", &_block_jacobi_indexed<int, float, float>,
         py::arg("Ap").noconvert(), py::arg("Aj").noconvert(), py::arg("Ax").noconvert(), py::arg("x").noconvert(), py::arg("b").noconvert(), py::arg("Tx").noconvert(), py::arg("indices").noconvert(), py::arg("omega").noconvert(), py::arg("blocksize"));

pyamg/amg_core/ruge_stuben.h

@@ -33,7 +33,7 @@
  * num_rows : int
  *     number of rows in A
  * theta : float
- *     stength of connection tolerance
+ *     strength of connection tolerance
  * Ap : array
  *     CSR row pointer
  * Aj : array

pyamg/amg_core/ruge_stuben_bind.cpp

@@ -471,7 +471,7 @@ Parameters
 num_rows : int
     number of rows in A
 theta : float
-    stength of connection tolerance
+    strength of connection tolerance
 Ap : array
     CSR row pointer
 Aj : array

pyamg/amg_core/smoothed_aggregation.h

@@ -30,7 +30,7 @@
  * num_rows : int
  *     number of rows in A
  * theta : float
- *     stength of connection tolerance
+ *     strength of connection tolerance
  * Ap : array
  *     CSR row pointer
  * Aj : array
@@ -1034,7 +1034,7 @@ void incomplete_mat_mult_bsr(const I Ap[], const int Ap_size,
 
 /* Swap x[i] and x[j], and
  *      y[i] and y[j]
- * Use in the qsort_twoarrays funcion
+ * Use in the qsort_twoarrays function
  */
 template<class I, class T>
 inline void swap(T x[], I y[], I i, I j )

pyamg/amg_core/smoothed_aggregation_bind.cpp

@@ -408,7 +408,7 @@ Parameters
 num_rows : int
     number of rows in A
 theta : float
-    stength of connection tolerance
+    strength of connection tolerance
 Ap : array
     CSR row pointer
 Aj : array

pyamg/blackbox.py

@@ -50,7 +50,7 @@ def make_csr(A):
 
 
 def solver_configuration(A, B=None, verb=True):
-    """Generate a dictionary of SA parameters for an arbitray matrix A.
+    """Generate a dictionary of SA parameters for an arbitrary matrix A.
 
     Parameters
     ----------

pyamg/gallery/fem.py

@@ -39,12 +39,12 @@ def generate_quadratic(V, E, return_edges=False):
         ne2 x 6 list of vertices
 
     Edges : ndarray
-        ned x 2 list of edges where the midpoint is generated
+        nedge x 2 list of edges where the midpoint is generated
 
     Notes
     -----
         - midpoints are introduced and globally numbered at the end of the vertex list
-        - the element list includes the new list beteen v0-v1, v1-v2, and v2-v0
+        - the element list includes the new list between v0-v1, v1-v2, and v2-v0
 
     Examples
     --------
@@ -277,7 +277,7 @@ def refine2dtri(V, E, marked_elements=None):
 
 
 def l2norm(u, mesh):
-    """Calculate the L2 norm of a funciton on mesh (V,E).
+    """Calculate the L2 norm of a function on mesh (V,E).
 
     Parameters
     ----------
@@ -393,7 +393,7 @@ class Mesh:
     """Simple mesh object that holds vertices and mesh functions."""
 
     # pylint: disable=too-many-instance-attributes
-    # This is reasonble for this class
+    # This is reasonable for this class
 
     def __init__(self, V, E, degree=1):
         """Initialize mesh.
@@ -897,7 +897,7 @@ def applybc(A, b, mesh, bc):
             c['var'] = 0
 
     # now extend the BC
-    # for each new id, are the orignal neighboring ids in a bc?
+    # for each new id, are the original neighboring ids in a bc?
     for c in bc:
         if c['degree'] == 2:
             idx = c['id']

pyamg/graph.py

@@ -393,7 +393,7 @@ def pseudo_peripheral_node(A):
     Returns
     -------
     x : int
-        Locaiton of the node
+        Location of the node
     order : array
         BFS ordering
     level : array

pyamg/krylov/_gmres_householder.py

@@ -323,7 +323,7 @@ def gmres_householder(A, b, x0=None, tol=1e-5,
         update = np.zeros(x.shape, dtype=x.dtype)
         # for j in range(inner,-1,-1):
         #    update[j] += y[j]
-        #    # Apply j-th reflector, (I - 2.0*w_j*w_j.T)*upadate
+        #    # Apply j-th reflector, (I - 2.0*w_j*w_j.T)*update
         #    update -= 2.0*dot(conjugate(W[j,:]), update)*W[j,:]
         amg_core.householder_hornerscheme(update, np.ravel(W), np.ravel(y),
                                           n, inner, -1, -1)

pyamg/multilevel.py

@@ -86,7 +86,7 @@ class level(Level):  # noqa: N801
         def __init__(self):
             """Raise deprecation warning on use, not import."""
             super().__init__()
-            warn('level() is deprectated.  use Level()',
+            warn('level() is deprecated.  use Level()',
                  category=DeprecationWarning, stacklevel=2)
 
     def __init__(self, levels, coarse_solver='pinv'):
@@ -444,7 +444,7 @@ def solve(self, b, x0=None, tol=1e-5, maxiter=100, cycle='V', accel=None,
                      'detected, due to presmoother/postsmoother combination. '
                      'CG requires SPD preconditioner, not just SPD matrix.')
 
-            # Check for AMLI compatability
+            # Check for AMLI compatibility
             if (accel != 'fgmres') and (cycle == 'AMLI'):
                 raise ValueError('AMLI cycles require acceleration (accel) '
                                  'to be fgmres, or no acceleration')
@@ -792,5 +792,5 @@ class multilevel_solver(MultilevelSolver):  # noqa: N801
     def __init__(self, *args, **kwargs):
         """Raise deprecation warning on use, not import."""
         super().__init__(*args, **kwargs)
-        warn('multilevel_solver is deprectated.  use MultilevelSolver()',
+        warn('multilevel_solver is deprecated.  use MultilevelSolver()',
              category=DeprecationWarning, stacklevel=2)

pyamg/relaxation/smoothing.py

@@ -478,7 +478,7 @@ def matrix_asformat(lvl, name, format, blocksize=None):
         setattr(lvl, desired_matrix, M)
     elif M.format == format and format == 'bsr':
         # convert to bsr with the right blocksize
-        # tobsr() will not do anything extra if this is uneeded
+        # tobsr() will not do anything extra if this is unneeded
         setattr(lvl, desired_matrix, M.tobsr(blocksize=blocksize))
     else:
         # convert

pyamg/relaxation/tests/test_relaxation.py

@@ -1681,7 +1681,7 @@ def gold(A, x, b, blocksize, sweep):
             assert_almost_equal(x, gold(A, x_copy, b, blocksize, 'symmetric'),
                                 decimal=4)
 
-        # check for aggreement between gauss_seidel and block gauss-seidel
+        # check for agreement between gauss_seidel and block gauss-seidel
         # with blocksize=1
         A = poisson((4, 5), format='csr')
         b = np.random.rand(A.shape[0])