void pydynd::array_no_dim_broadcast_assign_from_py(
const dynd::ndt::type &dst_tp, const char *dst_arrmeta, char *dst_data,
PyObject *value, const dynd::eval::eval_context *ectx)
{
// TODO: This is a hack, need a proper way to pass this dst param
dynd::nd::array tmp_dst(
dynd::make_array_memory_block(dst_tp.get_arrmeta_size()));
tmp_dst.get()->tp = dst_tp;
tmp_dst.get()->flags =
dynd::nd::read_access_flag | dynd::nd::write_access_flag;
if (dst_tp.get_arrmeta_size() > 0) {
dst_tp.extended()->arrmeta_copy_construct(
tmp_dst.get()->metadata(), dst_arrmeta,
dynd::intrusive_ptr<dynd::memory_block_data>());
}
tmp_dst.get()->data = dst_data;
dynd::ndt::type src_tp = dynd::ndt::type::make<void>();
const char *src_arrmeta = NULL;
char *src_data = reinterpret_cast<char *>(&value);
const char *kwd_names[1] = {"broadcast"};
dynd::nd::array kwd_values[1] = {false};
(*pydynd::nd::copy_from_pyobject.get().get())(
tmp_dst.get_type(), tmp_dst.get()->metadata(), tmp_dst.data(), 1, &src_tp,
&src_arrmeta, &src_data, 1, kwd_values,
std::map<std::string, dynd::ndt::type>());
tmp_dst.get()->tp = dynd::ndt::type();
}
std::string pydynd::ndt_type_repr(const dynd::ndt::type& d)
{
std::stringstream ss;
if (d.is_builtin() && d.get_type_id() != dynd::complex_float32_type_id &&
d.get_type_id() != dynd::complex_float64_type_id) {
ss << "ndt." << d;
} else {
switch (d.get_type_id()) {
case complex_float32_type_id:
ss << "ndt.complex_float32";
break;
case complex_float64_type_id:
ss << "ndt.complex_float64";
break;
case date_type_id:
ss << "ndt.date";
break;
case time_type_id:
if (d.tcast<time_type>()->get_timezone() == tz_abstract) {
ss << "ndt.time";
} else {
print_generic_type_repr(ss, d);
}
break;
case datetime_type_id:
if (d.tcast<datetime_type>()->get_timezone() == tz_abstract) {
ss << "ndt.datetime";
} else if (d.tcast<datetime_type>()->get_timezone() == tz_utc) {
ss << "ndt.datetimeutc";
} else {
print_generic_type_repr(ss, d);
}
break;
case json_type_id:
ss << "ndt.json";
break;
case bytes_type_id:
if (d.tcast<bytes_type>()->get_target_alignment() == 1) {
ss << "ndt.bytes";
} else {
print_generic_type_repr(ss, d);
}
break;
case string_type_id:
if (d.tcast<string_type>()->get_encoding() == string_encoding_utf_8) {
ss << "ndt.string";
} else {
print_generic_type_repr(ss, d);
}
break;
default:
print_generic_type_repr(ss, d);
break;
}
}
return ss.str();
}
bool pydynd::broadcast_as_scalar(const dynd::ndt::type &tp, PyObject *obj)
{
intptr_t obj_ndim = 0;
// Estimate the number of dimensions in ``obj`` by repeatedly indexing
// along zero
pyobject_ownref v(obj);
Py_INCREF(v);
for (;;) {
// Don't treat these types as sequences
if (PyDict_Check(v)) {
if (tp.get_dtype().get_kind() == struct_kind) {
// If the object to assign to a dynd struct ends in a dict, apply
// the dict as the struct's value
return (tp.get_ndim() > obj_ndim);
}
break;
}
else if (PyUnicode_Check(v) || PyBytes_Check(v)) {
break;
}
PyObject *iter = PyObject_GetIter(v);
if (iter != NULL) {
++obj_ndim;
if (iter == v.get()) {
// This was already an iterator, don't do any broadcasting,
// because we have no visibility into it.
Py_DECREF(iter);
return false;
}
else {
pyobject_ownref iter_owner(iter);
PyObject *item = PyIter_Next(iter);
if (item == NULL) {
if (PyErr_ExceptionMatches(PyExc_StopIteration)) {
PyErr_Clear();
break;
}
else {
throw exception();
}
}
else {
v.reset(item);
}
}
}
else {
PyErr_Clear();
break;
}
}
return (get_leading_dim_count(tp) > obj_ndim);
}
void pydynd::nd::array_copy_from_numpy(const dynd::ndt::type &dst_tp,
const char *dst_arrmeta, char *dst_data,
PyArrayObject *src_arr,
const dynd::eval::eval_context *ectx)
{
intptr_t src_ndim = PyArray_NDIM(src_arr);
strided_of_numpy_arrmeta src_am_holder;
const char *src_am = reinterpret_cast<const char *>(
&src_am_holder.sdt[NPY_MAXDIMS - src_ndim]);
// Fill in metadata for a multi-dim strided array, corresponding
// to the numpy array, with a void type at the end for the numpy
// specific data.
uintptr_t src_alignment = reinterpret_cast<uintptr_t>(PyArray_DATA(src_arr));
for (intptr_t i = 0; i < src_ndim; ++i) {
dynd::fixed_dim_type_arrmeta &am =
src_am_holder.sdt[NPY_MAXDIMS - src_ndim + i];
am.dim_size = PyArray_DIM(src_arr, (int)i);
am.stride = am.dim_size != 1 ? PyArray_STRIDE(src_arr, (int)i) : 0;
src_alignment |= static_cast<uintptr_t>(am.stride);
}
dynd::ndt::type src_tp = dynd::ndt::make_type(
src_ndim, PyArray_SHAPE(src_arr), dynd::ndt::type::make<void>());
src_am_holder.am.src_dtype = PyArray_DTYPE(src_arr);
src_am_holder.am.src_alignment = src_alignment;
// TODO: This is a hack, need a proper way to pass this dst param
dynd::nd::array tmp_dst(
dynd::make_array_memory_block(dst_tp.get_arrmeta_size()));
tmp_dst.get()->tp = dst_tp;
tmp_dst.get()->flags =
dynd::nd::read_access_flag | dynd::nd::write_access_flag;
if (dst_tp.get_arrmeta_size() > 0) {
dst_tp.extended()->arrmeta_copy_construct(
tmp_dst.get()->metadata(), dst_arrmeta,
dynd::intrusive_ptr<dynd::memory_block_data>());
}
tmp_dst.get()->data = dst_data;
char *src_data = reinterpret_cast<char *>(PyArray_DATA(src_arr));
const char *kwd_names[1] = {"broadcast"};
dynd::nd::array kwd_values[1] = {true};
(*pydynd::nd::copy_from_numpy::get().get())(
tmp_dst.get_type(), tmp_dst.get()->metadata(), tmp_dst.data(), 1, &src_tp,
&src_am, &src_data, 1, kwd_values,
std::map<std::string, dynd::ndt::type>());
tmp_dst.get()->tp = dynd::ndt::type();
}
inline ::testing::AssertionResult MatchNdtTypes(const char *expr1, const char *expr2, const dynd::ndt::type &pattern,
const dynd::ndt::type &candidate)
{
if (pattern.match(candidate)) {
return ::testing::AssertionSuccess();
}
else {
return ::testing::AssertionFailure() << "The type of candidate " << expr2 << " does not match pattern " << expr1
<< "\n" << expr1 << " has value " << pattern << ",\n" << expr2 << " has value "
<< candidate << ".";
}
}
void pydynd::array_copy_to_numpy(PyArrayObject *dst_arr,
const dynd::ndt::type &src_tp,
const char *src_arrmeta, const char *src_data)
{
intptr_t dst_ndim = PyArray_NDIM(dst_arr);
intptr_t src_ndim = src_tp.get_ndim();
uintptr_t dst_alignment = reinterpret_cast<uintptr_t>(PyArray_DATA(dst_arr));
strided_of_numpy_arrmeta dst_am_holder;
const char *dst_am = reinterpret_cast<const char *>(
&dst_am_holder.sdt[NPY_MAXDIMS - dst_ndim]);
// Fill in metadata for a multi-dim strided array, corresponding
// to the numpy array, with a void type at the end for the numpy
// specific data.
for (intptr_t i = 0; i < dst_ndim; ++i) {
dynd::fixed_dim_type_arrmeta &am =
dst_am_holder.sdt[NPY_MAXDIMS - dst_ndim + i];
am.stride = PyArray_STRIDE(dst_arr, (int)i);
dst_alignment |= static_cast<uintptr_t>(am.stride);
am.dim_size = PyArray_DIM(dst_arr, (int)i);
}
dynd::ndt::type dst_tp = dynd::ndt::make_type(
dst_ndim, PyArray_SHAPE(dst_arr), dynd::ndt::make_type<void>());
dst_am_holder.am.dst_dtype = PyArray_DTYPE(dst_arr);
dst_am_holder.am.dst_alignment = dst_alignment;
// TODO: This is a hack, need a proper way to pass this dst param
intptr_t tmp_dst_arrmeta_size =
dst_ndim * sizeof(dynd::fixed_dim_type_arrmeta) +
sizeof(copy_to_numpy_arrmeta);
dynd::nd::array tmp_dst(
reinterpret_cast<dynd::array_preamble *>(
dynd::make_array_memory_block(tmp_dst_arrmeta_size).get()),
true);
tmp_dst.get()->tp = dst_tp;
tmp_dst.get()->flags =
dynd::nd::read_access_flag | dynd::nd::write_access_flag;
if (dst_tp.get_arrmeta_size() > 0) {
memcpy(tmp_dst.get()->metadata(), dst_am, tmp_dst_arrmeta_size);
}
tmp_dst.get()->data = (char *)PyArray_DATA(dst_arr);
char *src_data_nonconst = const_cast<char *>(src_data);
copy_to_numpy::get()->call(tmp_dst.get_type(), tmp_dst.get()->metadata(),
tmp_dst.data(), 1, &src_tp, &src_arrmeta,
&src_data_nonconst, 1, NULL,
std::map<std::string, dynd::ndt::type>());
}
dynd::ndt::type pydynd::ndt_type_getitem(const dynd::ndt::type& d, PyObject *subscript)
{
// Convert the pyobject into an array of iranges
intptr_t size;
shortvector<irange> indices;
if (!PyTuple_Check(subscript)) {
// A single subscript
size = 1;
indices.init(1);
indices[0] = pyobject_as_irange(subscript);
} else {
size = PyTuple_GET_SIZE(subscript);
// Tuple of subscripts
indices.init(size);
for (Py_ssize_t i = 0; i < size; ++i) {
indices[i] = pyobject_as_irange(PyTuple_GET_ITEM(subscript, i));
}
}
// Do an indexing operation
return d.at_array((int)size, indices.get());
}
/**
* Gets the number of dimensions at index 0, including tuple
* and struct as dimensions.
*/
static intptr_t get_leading_dim_count(const dynd::ndt::type &tp)
{
intptr_t ndim = tp.get_ndim();
if (ndim) {
return ndim + get_leading_dim_count(tp.get_dtype());
}
else if (tp.get_kind() == expr_kind) {
return get_leading_dim_count(tp.value_type());
}
else if (tp.get_kind() == tuple_kind || tp.get_kind() == struct_kind) {
if (tp.extended<ndt::tuple_type>()->get_field_count() == 0) {
return 1;
}
else {
return 1 + get_leading_dim_count(
tp.extended<ndt::tuple_type>()->get_field_type(0));
}
}
else {
return 0;
}
}
/**
* This sets up a ckernel to copy from a dynd array
* to a numpy array. The destination numpy array is
* represented by dst_tp being ``void`` and the dst_arrmeta
* being a pointer to the ``PyArray_Descr *`` of the type for the destination.
*/
intptr_t pydynd::copy_to_numpy_ck::instantiate(
char *DYND_UNUSED(static_data), char *DYND_UNUSED(data), void *ckb,
intptr_t ckb_offset, const dynd::ndt::type &dst_tp, const char *dst_arrmeta,
intptr_t nsrc, const dynd::ndt::type *src_tp,
const char *const *src_arrmeta, dynd::kernel_request_t kernreq,
intptr_t nkwd, const dynd::nd::array *kwds,
const std::map<std::string, dynd::ndt::type> &tp_vars)
{
if (dst_tp.get_type_id() != dynd::void_type_id) {
stringstream ss;
ss << "Cannot instantiate dynd::nd::callable with signature (";
ss << src_tp[0] << ") -> " << dst_tp;
throw dynd::type_error(ss.str());
}
PyObject *dst_obj = *reinterpret_cast<PyObject *const *>(dst_arrmeta);
uintptr_t dst_alignment = reinterpret_cast<const uintptr_t *>(dst_arrmeta)[1];
PyArray_Descr *dtype = reinterpret_cast<PyArray_Descr *>(dst_obj);
if (!PyDataType_FLAGCHK(dtype, NPY_ITEM_HASOBJECT)) {
// If there is no object type in the numpy type, get the dynd equivalent
// type and use it to do the copying
dynd::ndt::type dst_view_tp = _type_from_numpy_dtype(dtype, dst_alignment);
return dynd::make_assignment_kernel(ckb, ckb_offset, dst_view_tp, NULL,
src_tp[0], src_arrmeta[0], kernreq,
&dynd::eval::default_eval_context);
}
else if (PyDataType_ISOBJECT(dtype)) {
dynd::nd::base_callable *af = const_cast<dynd::nd::base_callable *>(
nd::copy_to_pyobject::get().get());
return af->instantiate(af->static_data(), NULL, ckb, ckb_offset,
dynd::ndt::make_type<void>(), NULL, nsrc, src_tp,
src_arrmeta, kernreq, 0, NULL, tp_vars);
}
else if (PyDataType_HASFIELDS(dtype)) {
if (src_tp[0].get_kind() != dynd::struct_kind &&
src_tp[0].get_kind() != dynd::tuple_kind) {
stringstream ss;
pyobject_ownref dtype_str(PyObject_Str((PyObject *)dtype));
ss << "Cannot assign from source dynd type " << src_tp[0]
<< " to numpy type " << pydynd::pystring_as_string(dtype_str.get());
throw invalid_argument(ss.str());
}
// Get the fields out of the numpy dtype
vector<PyArray_Descr *> field_dtypes_orig;
vector<string> field_names_orig;
vector<size_t> field_offsets_orig;
pydynd::extract_fields_from_numpy_struct(
dtype, field_dtypes_orig, field_names_orig, field_offsets_orig);
intptr_t field_count = field_dtypes_orig.size();
if (field_count !=
src_tp[0].extended<dynd::ndt::tuple_type>()->get_field_count()) {
stringstream ss;
pyobject_ownref dtype_str(PyObject_Str((PyObject *)dtype));
ss << "Cannot assign from source dynd type " << src_tp[0]
<< " to numpy type " << pydynd::pystring_as_string(dtype_str.get());
throw invalid_argument(ss.str());
}
// Permute the numpy fields to match with the dynd fields
vector<PyArray_Descr *> field_dtypes;
vector<size_t> field_offsets;
if (src_tp[0].get_kind() == dynd::struct_kind) {
field_dtypes.resize(field_count);
field_offsets.resize(field_count);
for (intptr_t i = 0; i < field_count; ++i) {
intptr_t src_i =
src_tp[0].extended<dynd::ndt::struct_type>()->get_field_index(
field_names_orig[i]);
if (src_i >= 0) {
field_dtypes[src_i] = field_dtypes_orig[i];
field_offsets[src_i] = field_offsets_orig[i];
}
else {
stringstream ss;
pyobject_ownref dtype_str(PyObject_Str((PyObject *)dtype));
ss << "Cannot assign from source dynd type " << src_tp[0]
<< " to numpy type "
<< pydynd::pystring_as_string(dtype_str.get());
throw invalid_argument(ss.str());
}
}
}
else {
// In the tuple case, use position instead of name
field_dtypes.swap(field_dtypes_orig);
field_offsets.swap(field_offsets_orig);
}
vector<dynd::ndt::type> dst_fields_tp(field_count,
dynd::ndt::make_type<void>());
vector<copy_to_numpy_arrmeta> dst_arrmeta_values(field_count);
vector<const char *> dst_fields_arrmeta(field_count);
for (intptr_t i = 0; i < field_count; ++i) {
dst_arrmeta_values[i].dst_dtype = field_dtypes[i];
dst_arrmeta_values[i].dst_alignment = dst_alignment | field_offsets[i];
dst_fields_arrmeta[i] =
reinterpret_cast<const char *>(&dst_arrmeta_values[i]);
}
const uintptr_t *src_arrmeta_offsets =
src_tp[0].extended<dynd::ndt::tuple_type>()->get_arrmeta_offsets_raw();
dynd::shortvector<const char *> src_fields_arrmeta(field_count);
for (intptr_t i = 0; i != field_count; ++i) {
src_fields_arrmeta[i] = src_arrmeta[0] + src_arrmeta_offsets[i];
}
// Todo: Remove this
dynd::nd::callable af = dynd::nd::callable::make<copy_to_numpy_ck>(
dynd::ndt::type("(Any) -> void"), 0);
return make_tuple_unary_op_ckernel(
af.get(), af.get_type(), ckb, ckb_offset, field_count,
&field_offsets[0], &dst_fields_tp[0], &dst_fields_arrmeta[0],
src_tp[0].extended<dynd::ndt::tuple_type>()->get_data_offsets(
src_arrmeta[0]),
src_tp[0].extended<dynd::ndt::tuple_type>()->get_field_types_raw(),
src_fields_arrmeta.get(), kernreq);
}
else {
stringstream ss;
ss << "TODO: implement assign from source dynd type " << src_tp[0]
<< " to numpy type " << pyobject_repr((PyObject *)dtype);
throw invalid_argument(ss.str());
}
}
void pydynd::nd::copy_from_numpy_callable::instantiate(char *DYND_UNUSED(data), dynd::nd::kernel_builder *ckb,
const dynd::ndt::type &dst_tp, const char *dst_arrmeta,
intptr_t DYND_UNUSED(nsrc), const dynd::ndt::type *src_tp,
const char *const *src_arrmeta, dynd::kernel_request_t kernreq,
intptr_t nkwd, const dynd::nd::array *kwds,
const std::map<std::string, dynd::ndt::type> &tp_vars)
{
if (src_tp[0].get_id() != dynd::void_id) {
stringstream ss;
ss << "Cannot instantiate dynd::nd::callable copy_from_numpy with "
"signature (";
ss << src_tp[0] << ") -> " << dst_tp;
throw dynd::type_error(ss.str());
}
PyArray_Descr *dtype = *reinterpret_cast<PyArray_Descr *const *>(src_arrmeta[0]);
uintptr_t src_alignment = reinterpret_cast<const uintptr_t *>(src_arrmeta[0])[1];
if (!PyDataType_FLAGCHK(dtype, NPY_ITEM_HASOBJECT)) {
// If there is no object type in the numpy type, get the dynd equivalent
// type and use it to do the copying
dynd::ndt::type src_view_tp = _type_from_numpy_dtype(dtype, src_alignment);
dynd::nd::array error_mode = dynd::assign_error_fractional;
dynd::nd::assign->instantiate(NULL, ckb, dst_tp, dst_arrmeta, 1, &src_view_tp, NULL, kernreq, 1, &error_mode,
std::map<std::string, dynd::ndt::type>());
return;
}
else if (PyDataType_ISOBJECT(dtype)) {
dynd::nd::base_callable *af = dynd::nd::assign.get();
dynd::ndt::type child_src_tp = dynd::ndt::make_type<pyobject_type>();
af->instantiate(NULL, ckb, dst_tp, dst_arrmeta, 1, &child_src_tp, NULL, kernreq, nkwd, kwds, tp_vars);
return;
}
else if (PyDataType_HASFIELDS(dtype)) {
if (dst_tp.get_id() != dynd::struct_id && dst_tp.get_id() != dynd::tuple_id) {
stringstream ss;
ss << "Cannot assign from numpy type " << pyobject_repr((PyObject *)dtype) << " to dynd type " << dst_tp;
throw invalid_argument(ss.str());
}
// Get the fields out of the numpy dtype
vector<PyArray_Descr *> field_dtypes_orig;
vector<std::string> field_names_orig;
vector<size_t> field_offsets_orig;
pydynd::extract_fields_from_numpy_struct(dtype, field_dtypes_orig, field_names_orig, field_offsets_orig);
intptr_t field_count = field_dtypes_orig.size();
if (field_count != dst_tp.extended<dynd::ndt::tuple_type>()->get_field_count()) {
stringstream ss;
ss << "Cannot assign from numpy type " << pyobject_repr((PyObject *)dtype) << " to dynd type " << dst_tp;
throw invalid_argument(ss.str());
}
// Permute the numpy fields to match with the dynd fields
vector<PyArray_Descr *> field_dtypes;
vector<size_t> field_offsets;
if (dst_tp.get_id() == dynd::struct_id) {
field_dtypes.resize(field_count);
field_offsets.resize(field_count);
for (intptr_t i = 0; i < field_count; ++i) {
intptr_t src_i = dst_tp.extended<dynd::ndt::struct_type>()->get_field_index(field_names_orig[i]);
if (src_i >= 0) {
field_dtypes[src_i] = field_dtypes_orig[i];
field_offsets[src_i] = field_offsets_orig[i];
}
else {
stringstream ss;
ss << "Cannot assign from numpy type " << pyobject_repr((PyObject *)dtype) << " to dynd type " << dst_tp;
throw invalid_argument(ss.str());
}
}
}
else {
// In the tuple case, use position instead of name
field_dtypes.swap(field_dtypes_orig);
field_offsets.swap(field_offsets_orig);
}
vector<dynd::ndt::type> src_fields_tp(field_count, dynd::ndt::make_type<void>());
vector<copy_from_numpy_arrmeta> src_arrmeta_values(field_count);
vector<const char *> src_fields_arrmeta(field_count);
for (intptr_t i = 0; i < field_count; ++i) {
src_arrmeta_values[i].src_dtype = field_dtypes[i];
src_arrmeta_values[i].src_alignment = src_alignment | field_offsets[i];
src_fields_arrmeta[i] = reinterpret_cast<const char *>(&src_arrmeta_values[i]);
}
const uintptr_t *dst_arrmeta_offsets = dst_tp.extended<dynd::ndt::tuple_type>()->get_arrmeta_offsets_raw();
dynd::shortvector<const char *> dst_fields_arrmeta(field_count);
for (intptr_t i = 0; i != field_count; ++i) {
dst_fields_arrmeta[i] = dst_arrmeta + dst_arrmeta_offsets[i];
}
// Todo: Remove this line
dynd::nd::callable af = dynd::nd::make_callable<copy_from_numpy_callable>();
make_tuple_unary_op_ckernel(af.get(), af.get_type(), ckb, field_count,
dst_tp.extended<dynd::ndt::tuple_type>()->get_data_offsets(dst_arrmeta),
dst_tp.extended<dynd::ndt::tuple_type>()->get_field_types_raw(),
dst_fields_arrmeta.get(), &field_offsets[0], &src_fields_tp[0], &src_fields_arrmeta[0],
kernreq);
return;
}
else {
stringstream ss;
ss << "TODO: implement assign from numpy type " << pyobject_repr((PyObject *)dtype) << " to dynd type " << dst_tp;
throw invalid_argument(ss.str());
}
}
void pydynd::fill_arrmeta_from_numpy_dtype(const dynd::ndt::type &dt,
PyArray_Descr *d, char *arrmeta)
{
switch (dt.get_id()) {
case dynd::struct_id: {
// In DyND, the struct offsets are part of the arrmeta instead of the dtype.
// That's why we have to populate them here.
PyObject *d_names = d->names;
const dynd::ndt::struct_type *sdt = dt.extended<dynd::ndt::struct_type>();
const uintptr_t *arrmeta_offsets = sdt->get_arrmeta_offsets_raw();
size_t field_count = sdt->get_field_count();
uintptr_t *offsets = reinterpret_cast<size_t *>(arrmeta);
for (size_t i = 0; i < field_count; ++i) {
PyObject *tup = PyDict_GetItem(d->fields, PyTuple_GET_ITEM(d_names, i));
PyArray_Descr *fld_dtype;
PyObject *title;
int offset = 0;
if (!PyArg_ParseTuple(tup, "Oi|O", &fld_dtype, &offset, &title)) {
throw dynd::type_error("Numpy struct dtype has corrupt data");
}
// Set the field offset in the output arrmeta
offsets[i] = offset;
// Fill the arrmeta for the field, if necessary
const dynd::ndt::type &ft = sdt->get_field_type(i);
if (!ft.is_builtin()) {
fill_arrmeta_from_numpy_dtype(ft, fld_dtype,
arrmeta + arrmeta_offsets[i]);
}
}
break;
}
case dynd::fixed_dim_id: {
// The Numpy subarray becomes a series of fixed_dim types, so we
// need to copy the strides into the arrmeta.
dynd::ndt::type el;
PyArray_ArrayDescr *adescr = d->subarray;
if (adescr == NULL) {
stringstream ss;
ss << "Internal error building dynd arrmeta: Numpy dtype has "
"NULL subarray corresponding to strided_dim type";
throw dynd::type_error(ss.str());
}
if (PyTuple_Check(adescr->shape)) {
int ndim = (int)PyTuple_GET_SIZE(adescr->shape);
dynd::fixed_dim_type_arrmeta *md =
reinterpret_cast<dynd::fixed_dim_type_arrmeta *>(arrmeta);
intptr_t stride = adescr->base->elsize;
el = dt;
for (int i = ndim - 1; i >= 0; --i) {
md[i].dim_size =
pydynd::pyobject_as_index(PyTuple_GET_ITEM(adescr->shape, i));
md[i].stride = stride;
stride *= md[i].dim_size;
el = el.extended<dynd::ndt::fixed_dim_type>()->get_element_type();
}
arrmeta += ndim * sizeof(dynd::fixed_dim_type_arrmeta);
}
else {
dynd::fixed_dim_type_arrmeta *md =
reinterpret_cast<dynd::fixed_dim_type_arrmeta *>(arrmeta);
arrmeta += sizeof(dynd::fixed_dim_type_arrmeta);
md->dim_size = pydynd::pyobject_as_index(adescr->shape);
md->stride = adescr->base->elsize;
el = dt.extended<dynd::ndt::fixed_dim_type>()->get_element_type();
}
// Fill the arrmeta for the array element, if necessary
if (!el.is_builtin()) {
fill_arrmeta_from_numpy_dtype(el, adescr->base, arrmeta);
}
break;
}
default:
break;
}
}
