Added structure test written in Python.

tests/python_frontend/structures/structure_test.py

@@ -0,0 +1,38 @@
+# Copyright 2019-2023 ETH Zurich and the DaCe authors. All rights reserved.
+import dace
+import numpy as np
+
+from scipy import sparse
+
+
+def test_read_structure():
+
+    M, N, nnz = (dace.symbol(s) for s in ('M', 'N', 'nnz'))
+    CSR = dace.data.Structure(dict(indptr=dace.int32[M + 1], indices=dace.int32[nnz], data=dace.float32[nnz]),
+                              name='CSRMatrix')
+
+    @dace.program
+    def csr_to_dense_python(A: CSR, B: dace.float32[M, N]):
+        for i in dace.map[0:M]:
+            for idx in dace.map[A.indptr[i]:A.indptr[i + 1]]:
+                B[i, A.indices[idx]] = A.data[idx]
+
+    rng = np.random.default_rng(42)
+    A = sparse.random(20, 20, density=0.1, format='csr', dtype=np.float32, random_state=rng)
+    B = np.zeros((20, 20), dtype=np.float32)
+
+    inpA = CSR.dtype._typeclass.as_ctypes()(indptr=A.indptr.__array_interface__['data'][0],
+                                            indices=A.indices.__array_interface__['data'][0],
+                                            data=A.data.__array_interface__['data'][0])
+
+    # TODO: The following doesn't work because we need to create a Structure data descriptor from the ctypes class.
+    # csr_to_dense_python(inpA, B)
+    func = csr_to_dense_python.compile()
+    func(A=inpA, B=B, M=A.shape[0], N=A.shape[1], nnz=A.nnz)
+    ref = A.toarray()
+
+    assert np.allclose(B, ref)
+
+
+if __name__ == '__main__':
+    test_read_structure()