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Refactoring to_numpy methods.

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Rok authored and Antoine Pitrou committed 2019-07-01 11:39:30 +02:00
1 parent 3fcc1929e8
commit e89edc620e
2 files changed
+25 -5
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cpp/src/arrow/python/numpy_convert.cc
+21 -3
View File
@@ -293,8 +293,14 @@ Status SparseTensorCOOToNdarray(const std::shared_ptr<SparseTensorCOO>& sparse_t
PyArray_Descr* dtype_coords = PyArray_DescrNewFromType(type_num_coords);
RETURN_IF_PYERROR();
const int ndim_coords = sparse_tensor->ndim();
std::vector<npy_intp> npy_shape_coords(ndim_coords);
for (int i = 0; i < ndim_coords; ++i) {
npy_shape_coords[i] = sparse_index_coords->shape()[i];
}
std::vector<npy_intp> npy_shape_data({sparse_index.non_zero_length(), 1});
std::vector<npy_intp> npy_shape_coords({sparse_index_coords->shape()[0], 2});
const void* immutable_data = nullptr;
if (sparse_tensor->data()) {
@@ -355,8 +361,20 @@ Status SparseTensorCSRToNdarray(const std::shared_ptr<SparseTensorCSR>& sparse_t
sparse_index.indices();
std::vector<npy_intp> npy_shape_data({sparse_index.non_zero_length(), 1});
std::vector<npy_intp> npy_shape_indptr({sparse_index_indptr->shape()[0], 1});
std::vector<npy_intp> npy_shape_indices({sparse_index_indices->shape()[0], 1});
const int ndim_indptr = sparse_index_indptr->ndim();
std::vector<npy_intp> npy_shape_indptr(ndim_indptr);
for (int i = 0; i < ndim_indptr; ++i) {
npy_shape_indptr[i] = sparse_index_indptr->shape()[i];
}
const int ndim_indices = sparse_index_indices->ndim();
std::vector<npy_intp> npy_shape_indices(ndim_indices);
for (int i = 0; i < ndim_indices; ++i) {
npy_shape_indices[i] = sparse_index_indices->shape()[i];
}
const void* immutable_data = nullptr;
if (sparse_tensor->data()) {
python/pyarrow/tests/test_sparse_tensor.py
+4 -2
View File
@@ -77,11 +77,13 @@ def test_sparse_tensor_equals(sparse_tensor_type):
data = np.random.randn(10, 6)[::, ::2]
sparse_tensor1 = sparse_tensor_type.from_dense_numpy(data)
sparse_tensor2 = sparse_tensor_type.from_dense_numpy(np.ascontiguousarray(data))
sparse_tensor2 = sparse_tensor_type.from_dense_numpy(
np.ascontiguousarray(data))
eq(sparse_tensor1, sparse_tensor2)
data = data.copy()
data[9, 0] = 1.0
sparse_tensor2 = sparse_tensor_type.from_dense_numpy(np.ascontiguousarray(data))
sparse_tensor2 = sparse_tensor_type.from_dense_numpy(
np.ascontiguousarray(data))
ne(sparse_tensor1, sparse_tensor2)