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Update stencil2coo kernels for shifts > 1 #442

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merged 5 commits into from
Sep 27, 2024
Merged

Update stencil2coo kernels for shifts > 1 #442

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7e621bb
Fixed the indexing in stencil2coo_1d_C and stencil2coo_1d_F so that t…
max-models Sep 26, 2024
4826aab
removed the unneccesary unit test, added parameters to test_stencil_m…
max-models Sep 26, 2024
d09d59a
Update psydac/linalg/tests/test_stencil_matrix.py
max-models Sep 27, 2024
78bffd6
Update psydac/linalg/tests/test_stencil_matrix.py
max-models Sep 27, 2024
68d079c
Added a shift of 2 to test_stencil_matrix_1d_parallel_toarray
max-models Sep 27, 2024
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4 changes: 2 additions & 2 deletions psydac/linalg/kernels/stencil2coo_kernels.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,7 +19,7 @@ def stencil2coo_1d_C(A:'T[:,:]', data:'T[:]', rows:'int64[:]', cols:'int64[:]',
for j1 in range(ncl1):
value = A[i1+pp1,j1]
if abs(value) == 0.0:continue
J = ((I//cm1)*dm1+j1-dp1)%nc1
J = ((I*dm1//cm1)+j1-dp1)%nc1
rows[nnz] = I
cols[nnz] = J
data[nnz] = value
Expand All @@ -38,7 +38,7 @@ def stencil2coo_1d_F(A:'T[:,:]', data:'T[:]', rows:'int64[:]', cols:'int64[:]',
for j1 in range(ncl1):
value = A[i1+pp1,j1]
if abs(value) == 0.0:continue
J = ((I//cm1)*dm1+j1-dp1)%nc1
J = ((I*dm1//cm1)+j1-dp1)%nc1
rows[nnz] = I
cols[nnz] = J
data[nnz] = value
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44 changes: 44 additions & 0 deletions psydac/linalg/tests/test_stencil_matrix.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3154,6 +3154,50 @@ def test_stencil_matrix_2d_parallel_backend_dot(dtype, n1, n2, p1, p2, sh1, sh2,
assert (M + M).backend is M.backend
assert (2 * M).backend is M.backend

@pytest.mark.parametrize('dtype', [float])#, complex])
@pytest.mark.parametrize('n1', [4,6,10])
@pytest.mark.parametrize('p1', [3,4])
@pytest.mark.parametrize('s1', [1,2,3])
def test_stencil_matrix_1d_toarray(dtype, n1, p1, s1, P1=True):
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npts = [n1]
pads = [p1]
shifts = [s1]
ndim = len(npts)

# Create domain decomposition
D = DomainDecomposition(npts, periods=[P1])

# Partition the points
global_starts, global_ends = compute_global_starts_ends(D, npts, pads)
cart = CartDecomposition(D, npts, global_starts, global_ends, pads=pads, shifts=shifts)

# Create a vector space V and a matrix M from V to V
V = StencilVectorSpace(cart, dtype=dtype)
M = StencilMatrix(V, V)

sub = 1
diag = 2
sup = 3

M[:,-1] = sub
M[:,0] = diag
M[:,1] = sup

M_toarray = M.toarray()

# Create equivalent matrix with numpy
n = np.prod(npts)

matrix = np.identity(n) * diag
matrix[np.arange(1, n), np.arange(n-1)] = sub
matrix[np.arange(n-1), np.arange(1, n)] = sup

# Fill the first and last element of the secondary diagonals
matrix[0, n-1] = sub
matrix[n-1, 0] = sup

assert np.allclose(M.toarray(), matrix)

# ===============================================================================
# SCRIPT FUNCTIONALITY
# ===============================================================================
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