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/*
* SPDX-FileCopyrightText: All Contributors to the PyTango project
*
* SPDX-License-Identifier: LGPL-3.0-or-later
*/
#pragma once
#include "common_header.h"
#include "types_structs_macros.h"
#include "convertors/attributes/extract_value.h"
#include "convertors/type_casters.h"
namespace PyDeviceAttribute {
template <int tangoTypeConst>
static inline void array_value_from_cpp_into_python_as_bin_or_str(Tango::DeviceAttribute &self,
PyTango::ExtractAs extract_as,
py::object &read_value,
py::object &written_value) {
using TangoScalarType = typename TANGO_const2type(tangoTypeConst);
using TangoArrayType = typename TANGO_const2arraytype(tangoTypeConst);
Py_ssize_t nb_bytes_read = static_cast<Py_ssize_t>(self.get_nb_read()) *
static_cast<Py_ssize_t>(sizeof(TangoScalarType));
Py_ssize_t nb_bytes_written = static_cast<Py_ssize_t>(self.get_nb_written()) *
static_cast<Py_ssize_t>(sizeof(TangoScalarType));
// Extract the actual data from Tango::DeviceAttribute (self)
TangoArrayType *value_ptr = nullptr;
EXTRACT_VALUE(self, value_ptr)
std::unique_ptr<TangoArrayType> guard_value_ptr(value_ptr);
if(value_ptr == nullptr) {
// Empty device attribute
value_ptr = new TangoArrayType;
}
TangoScalarType *buffer = value_ptr->get_buffer();
const char *ch_ptr = reinterpret_cast<const char *>(buffer);
switch(extract_as) {
case PyTango::ExtractAsBytes: {
read_value = py::bytes(ch_ptr, nb_bytes_read);
written_value = py::bytes(ch_ptr + nb_bytes_read, nb_bytes_written);
break;
}
case PyTango::ExtractAsByteArray: {
read_value = py::bytearray(ch_ptr, nb_bytes_read);
written_value = py::bytearray(ch_ptr + nb_bytes_read, nb_bytes_written);
break;
}
case PyTango::ExtractAsString: {
read_value = py::str(ch_ptr, nb_bytes_read);
written_value = py::str(ch_ptr + nb_bytes_read, nb_bytes_written);
break;
}
default:
throw std::invalid_argument("Unsupported extract_as");
}
}
template <>
inline void array_value_from_cpp_into_python_as_bin_or_str<Tango::DEV_STRING>([[maybe_unused]] Tango::DeviceAttribute &self,
[[maybe_unused]] PyTango::ExtractAs extract_as,
[[maybe_unused]] py::object &read_value,
[[maybe_unused]] py::object &written_value) {
assert(false);
}
template <int tangoTypeConst>
static void array_value_from_cpp_into_python_as_tuple_or_list(Tango::DeviceAttribute &self,
bool is_image,
PyTango::ExtractAs extract_as,
py::object &read_value,
py::object &written_value) {
using TangoScalarType = typename TANGO_const2type(tangoTypeConst);
using TangoArrayType = typename TANGO_const2arraytype(tangoTypeConst);
// Extract the actual data from Tango::DeviceAttribute (self)
TangoArrayType *value_ptr = nullptr;
EXTRACT_VALUE(self, value_ptr)
std::unique_ptr<TangoArrayType> guard_value_ptr(value_ptr);
if(value_ptr == nullptr) {
// Empty device attribute
switch(extract_as) {
case PyTango::ExtractAsTuple: {
read_value = py::tuple();
written_value = py::tuple();
break;
}
case PyTango::ExtractAsList: {
read_value = py::list();
written_value = py::list();
break;
}
default:
throw std::invalid_argument("Unsupported extract_as");
}
return;
}
TangoScalarType *buffer = value_ptr->get_buffer();
int total_length = static_cast<int>(value_ptr->length());
// Determine if the attribute is AttrWriteType.WRITE
int read_size = 0, write_size = 0;
if(is_image) {
read_size = self.get_dim_x() * self.get_dim_y();
write_size = self.get_written_dim_x() * self.get_written_dim_y();
} else {
read_size = self.get_dim_x();
write_size = self.get_written_dim_x();
}
bool is_write_type = (read_size + write_size) > total_length;
// Convert to a tuple of tuples
unsigned int offset = 0;
for(int it = 1; it >= 0; --it) { // 2 iterations: read part/write part
if((!it) && is_write_type) {
written_value = read_value;
continue;
}
unsigned int dim_x = static_cast<unsigned int>(it ? self.get_dim_x() : self.get_written_dim_x());
unsigned int dim_y = static_cast<unsigned int>(it ? self.get_dim_y() : self.get_written_dim_y());
py::tuple array(is_image ? dim_y : dim_x);
if(is_image) {
for(unsigned int y = 0; y < dim_y; ++y) {
py::tuple row_vec(dim_x);
for(unsigned int x = 0; x < dim_x; ++x) {
row_vec[x] = cpp_to_python_scalar<tangoTypeConst>::convert(buffer[offset + x + (y * dim_x)]);
}
switch(extract_as) {
case PyTango::ExtractAsTuple:
array[y] = row_vec;
break;
case PyTango::ExtractAsList:
array[y] = py::list(row_vec);
break;
default:
throw std::invalid_argument("Unsupported extract_as");
}
}
offset += dim_x * dim_y;
} else {
for(unsigned int x = 0; x < dim_x; ++x) {
array[x] = cpp_to_python_scalar<tangoTypeConst>::convert(buffer[offset + x]);
}
offset += dim_x;
}
py::object result;
switch(extract_as) {
case PyTango::ExtractAsTuple:
result = array;
break;
case PyTango::ExtractAsList:
result = py::list(array);
break;
default:
throw std::invalid_argument("Unsupported extract_as");
}
if(it) {
read_value = result;
} else {
written_value = result;
}
}
}
template <int tangoTypeConst>
static void array_value_from_cpp_into_python_as_numpy(Tango::DeviceAttribute &self,
bool is_image,
py::object &read_value,
py::object &written_value) {
using TangoScalarType = typename TANGO_const2type(tangoTypeConst);
using TangoArrayType = typename TANGO_const2arraytype(tangoTypeConst);
// Extract the actual data from Tango::DeviceAttribute (self)
TangoArrayType *value_ptr = nullptr;
EXTRACT_VALUE(self, value_ptr)
if(value_ptr == nullptr) {
// Empty device attribute
value_ptr = new TangoArrayType();
}
TangoScalarType *buffer = value_ptr->get_buffer();
std::size_t itemsize = static_cast<std::size_t>(sizeof(TangoScalarType));
std::vector<std::size_t> dims;
std::vector<std::size_t> strides;
size_t write_part_offset = 0;
if(is_image) {
std::size_t dim_x = static_cast<std::size_t>(self.get_dim_x());
std::size_t dim_y = static_cast<std::size_t>(self.get_dim_y());
dims = {dim_y, dim_x};
strides = {dim_x * itemsize, itemsize}; // For C-style (row-major) layout
write_part_offset = dim_y * dim_x;
} else {
std::size_t dim_x = static_cast<std::size_t>(self.get_dim_x());
dims = {dim_x};
strides = {itemsize};
write_part_offset = dim_x;
}
// Create a capsule to manage the lifetime of value_ptr
py::capsule base(value_ptr, dev_var_attribute_array_deleter<tangoTypeConst>);
// Create the numpy array without copying the data, and associate the base object
read_value = py::array(py::dtype::of<TangoScalarType>(),
dims,
strides,
buffer,
base // Associate the capsule as the base object
);
// Handle the write part if present
TangoScalarType *w_buffer = nullptr;
std::vector<std::size_t> w_dims;
std::vector<std::size_t> w_strides;
w_buffer = buffer + write_part_offset;
if(is_image) {
std::size_t w_dim_x = static_cast<std::size_t>(self.get_written_dim_x());
std::size_t w_dim_y = static_cast<std::size_t>(self.get_written_dim_y());
w_dims = {w_dim_y, w_dim_x};
w_strides = {w_dim_x * itemsize, itemsize};
} else {
std::size_t w_dim_x = static_cast<std::size_t>(self.get_written_dim_x());
w_dims = {w_dim_x};
w_strides = {itemsize};
}
written_value = py::array(py::dtype::of<TangoScalarType>(),
w_dims,
w_strides,
w_buffer,
base // Associate the same capsule as the base object
);
}
template <>
inline void array_value_from_cpp_into_python_as_numpy<Tango::DEV_STRING>(Tango::DeviceAttribute &self,
bool is_image,
py::object &read_value,
py::object &written_value) {
array_value_from_cpp_into_python_as_tuple_or_list<Tango::DEV_STRING>(self,
is_image,
PyTango::ExtractAsTuple,
read_value,
written_value);
}
template <int tangoTypeConst>
static inline void array_value_from_cpp_into_python(Tango::DeviceAttribute &self,
py::object &py_value,
bool is_image,
PyTango::ExtractAs extract_as) {
py::object read_value;
py::object written_value;
switch(extract_as) {
default:
case PyTango::ExtractAsNumpy:
array_value_from_cpp_into_python_as_numpy<tangoTypeConst>(self,
is_image,
read_value,
written_value);
break;
case PyTango::ExtractAsTuple:
case PyTango::ExtractAsList:
array_value_from_cpp_into_python_as_tuple_or_list<tangoTypeConst>(self,
is_image,
extract_as,
read_value,
written_value);
break;
case PyTango::ExtractAsBytes:
case PyTango::ExtractAsByteArray:
case PyTango::ExtractAsString:
array_value_from_cpp_into_python_as_bin_or_str<tangoTypeConst>(self,
extract_as,
read_value,
written_value);
break;
}
py_value.attr(value_attr_name) = read_value;
py_value.attr(w_value_attr_name) = written_value;
}
template <>
inline void array_value_from_cpp_into_python<Tango::DEV_ENCODED>([[maybe_unused]] Tango::DeviceAttribute &self,
[[maybe_unused]] py::object &py_value,
[[maybe_unused]] bool is_image,
[[maybe_unused]] PyTango::ExtractAs extract_as) {
/// @todo Sure, it is not necessary?
assert(false);
}
} // namespace PyDeviceAttribute
namespace PyWAttribute {
// General helper template
template <int tangoTypeConst>
struct tango_const2type {
using Type = typename TANGO_const2type(tangoTypeConst);
};
// Specialization for Tango::DEV_STRING
template <>
struct tango_const2type<Tango::DEV_STRING> {
using Type = Tango::ConstDevString;
};
template <int tangoTypeConst>
inline void array_value_from_cpp_into_python_as_list(Tango::WAttribute &att,
py::object &py_value) {
using TangoScalarType = typename tango_const2type<tangoTypeConst>::Type;
const TangoScalarType *buffer = nullptr;
att.get_write_value(buffer);
if(buffer == nullptr) {
py_value = py::list();
return;
}
std::size_t dim_x = static_cast<std::size_t>(att.get_w_dim_x());
std::size_t dim_y = static_cast<std::size_t>(att.get_w_dim_y());
py::list result;
if(att.get_data_format() == Tango::SPECTRUM) {
for(size_t x = 0; x < dim_x; ++x) {
result.append(cpp_to_python_scalar<tangoTypeConst>::convert(buffer[x]));
}
} else {
for(size_t y = 0; y < dim_y; ++y) {
py::list row;
for(size_t x = 0; x < dim_x; ++x) {
row.append(cpp_to_python_scalar<tangoTypeConst>::convert(buffer[x + (y * dim_x)]));
}
result.append(row);
}
}
py_value = result;
}
template <int tangoTypeConst>
inline void array_value_from_cpp_into_python_as_numpy(Tango::WAttribute &att,
py::object &py_value) {
using TangoScalarType = typename TANGO_const2type(tangoTypeConst);
const TangoScalarType *buffer = nullptr;
att.get_write_value(buffer);
std::size_t itemsize = static_cast<std::size_t>(sizeof(TangoScalarType));
std::vector<std::size_t> dims;
std::vector<std::size_t> strides;
std::size_t dim_x = static_cast<std::size_t>(att.get_w_dim_x());
std::size_t dim_y = static_cast<std::size_t>(att.get_w_dim_y());
if(att.get_data_format() == Tango::SPECTRUM) {
dims = {dim_x};
strides = {itemsize};
} else {
dims = {dim_y, dim_x};
strides = {dim_x * itemsize, itemsize}; // For C-style (row-major) layout
}
// Create the numpy array. Note, that pybind11 copy the data automatically,
// if there is no capsule object
// https://github.com/pybind/pybind11/issues/1042#issuecomment-325938098
py_value = py::array(py::dtype::of<TangoScalarType>(),
dims,
strides,
buffer);
}
template <>
inline void array_value_from_cpp_into_python_as_numpy<Tango::DEV_STRING>(Tango::WAttribute &att,
py::object &py_value) {
array_value_from_cpp_into_python_as_list<Tango::DEV_STRING>(att, py_value);
}
template <int tangoTypeConst>
static inline void array_value_from_cpp_into_python(Tango::WAttribute &att,
py::object &py_value,
PyTango::ExtractAs extract_as) {
switch(extract_as) {
case PyTango::ExtractAsPyTango3:
case PyTango::ExtractAsList: {
array_value_from_cpp_into_python_as_list<tangoTypeConst>(att, py_value);
break;
}
case PyTango::ExtractAsNumpy: {
array_value_from_cpp_into_python_as_numpy<tangoTypeConst>(att, py_value);
break;
}
default:
Tango::Except::throw_exception("PyDs_WrongParameterValue",
"This extract method is not supported by the function.",
"PyWAttribute::get_write_value()");
}
}
template <>
inline void array_value_from_cpp_into_python<Tango::DEV_ENCODED>([[maybe_unused]] Tango::WAttribute &att,
[[maybe_unused]] py::object &py_value,
[[maybe_unused]] PyTango::ExtractAs extract_as) {
assert(false);
}
} // namespace PyWAttribute
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