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/*
* SPDX-FileCopyrightText: All Contributors to the PyTango project
*
* SPDX-License-Identifier: LGPL-3.0-or-later
*/
// This header file is just some template functions moved apart from
// attribute.cpp, and should only be included there.
#pragma once
#include "types_structs_macros.h"
#include "convertors/generic_from_py.h"
// cppTango "feature": commands expect, that we allocate memory with "allocbuf", while attributes - new[].
// So.....
enum MemoryAllocation {
ALLOC,
NEW
};
#define MEMORY_ALLOCATOR(TangoScalarType, TangoArrayType, len, allocation) \
TangoScalarType *tg_data; \
switch(allocation) { \
case MemoryAllocation::ALLOC: \
tg_data = TangoArrayType::allocbuf(static_cast<_CORBA_ULong>(len)); \
break; \
case MemoryAllocation::NEW: \
tg_data = new TangoScalarType[len]; \
break; \
default: \
throw std::invalid_argument("Unknown allocation method"); \
}
template <int tangoArrayTypeConst>
inline void buffer_deleter__(typename TANGO_const2scalartype(tangoArrayTypeConst) * tg_data,
MemoryAllocation allocation,
[[maybe_unused]] py::size_t processed_elements) {
using TangoArrayType = typename TANGO_const2type(tangoArrayTypeConst);
switch(allocation) {
case MemoryAllocation::ALLOC:
TangoArrayType::freebuf(tg_data);
break;
case MemoryAllocation::NEW:
delete[] tg_data;
break;
default:
throw std::invalid_argument("Unknown allocation method");
}
}
template <>
inline void buffer_deleter__<Tango::DEVVAR_STRINGARRAY>(Tango::DevString *tg_data,
MemoryAllocation allocation,
py::size_t processed_elements) {
switch(allocation) {
case MemoryAllocation::ALLOC:
Tango::DevVarStringArray::freebuf(tg_data);
break;
case MemoryAllocation::NEW: {
for(py::size_t i = 0; i < processed_elements; ++i) {
delete[] tg_data[i];
}
delete[] tg_data;
break;
}
default:
throw std::invalid_argument("Unknown allocation method");
}
}
template <int tangoArrayTypeConst>
inline typename TANGO_const2scalartype(tangoArrayTypeConst) * python_to_cpp_buffer_generic(py::object &py_val,
MemoryAllocation allocation,
const std::string &fname,
bool isImage,
py::size_t &res_dim_x,
py::size_t &res_dim_y) {
using TangoScalarType = typename TANGO_const2scalartype(tangoArrayTypeConst);
using TangoArrayType = typename TANGO_const2type(tangoArrayTypeConst);
std::string err_msg = isImage
? "Expecting a sequence of sequences (IMAGE attribute)."
: "Expecting a sequence (SPECTRUM attribute).";
if(py::isinstance<py::str>(py_val) || !py::isinstance<py::sequence>(py_val)) {
Tango::Except::throw_exception("PyDs_WrongParameters",
err_msg,
fname + "()");
}
py::list py_list = py::cast<py::list>(py_val);
py::size_t len = py::len(py_val);
if(len > 0 && isImage) {
py::object py_row0 = py_list[0];
if(!py::isinstance<py::sequence>(py_row0)) {
Tango::Except::throw_exception("PyDs_WrongParameters",
err_msg,
fname + "()");
}
res_dim_y = len;
res_dim_x = py::len(py_row0);
len = res_dim_x * res_dim_y;
} else {
res_dim_y = 0;
res_dim_x = len;
}
/// @bug Why not TangoArrayType::allocbuf(len)? Because
/// I will use it in set_value(tg_ptr,...,release=true).
/// Tango API makes delete[] tg_ptr instead of freebuf(tg_ptr).
/// This is usually the same, but for Tango::DevStringArray the
/// behaviour seems different and causes weird troubles..
MEMORY_ALLOCATOR(TangoScalarType, TangoArrayType, len, allocation);
TangoScalarType tg_scalar;
py::size_t idx = 0;
try {
if(isImage) {
for(py::size_t y = 0; y < res_dim_y; y++) {
py::list py_row = py_list[y];
for(py::size_t x = 0; x < res_dim_x; x++) {
array_element_from_py<tangoArrayTypeConst>::convert(py_row[x], tg_scalar);
tg_data[idx] = tg_scalar;
idx++;
}
}
} else {
for(py::size_t x = 0; x < res_dim_x; x++) {
array_element_from_py<tangoArrayTypeConst>::convert(py_list[x], tg_scalar);
tg_data[idx] = tg_scalar;
idx++;
}
}
} catch(...) {
buffer_deleter__<tangoArrayTypeConst>(tg_data, allocation, idx);
throw;
}
return tg_data;
}
template <int tangoArrayTypeConst>
inline typename TANGO_const2scalartype(tangoArrayTypeConst) * python_to_cpp_buffer(py::object &py_val,
MemoryAllocation allocation,
const std::string &fname,
bool isImage,
py::size_t &res_dim_x,
py::size_t &res_dim_y) {
using TangoArrayType = typename TANGO_const2type(tangoArrayTypeConst);
using TangoScalarType = typename TANGO_const2scalartype(tangoArrayTypeConst);
if(!py::isinstance<py::array>(py_val)) {
return python_to_cpp_buffer_generic<tangoArrayTypeConst>(py_val,
allocation,
fname,
isImage,
res_dim_x,
res_dim_y);
}
py::array arr = py_val.cast<py::array>();
long nd = arr.ndim();
const py::ssize_t *signed_dims = arr.shape();
std::vector<py::size_t> dims;
for(long i = 0; i < nd; ++i) {
dims.push_back(static_cast<py::size_t>(signed_dims[i]));
}
py::size_t len = 0;
// Retrieve the NumPy array flags
int flags = arr.flags();
// Check if the array is exactly what we need: contiguous, aligned, and correct data type
const bool exact_array = ((flags & NPY_ARRAY_C_CONTIGUOUS) != 0) &&
((flags & NPY_ARRAY_ALIGNED) != 0) &&
arr.dtype().is(pybind11::dtype::of<TangoScalarType>());
// Handle empty arrays first - set dimensions to 0 regardless of actual dimensions
bool is_empty = false;
if(isImage) {
if(nd == 2 && dims[0] == 0) {
// Empty 2D array
is_empty = true;
} else if(nd == 1 && dims[0] == 0) {
// Empty 1D array passed as image - treat as empty 2D
is_empty = true;
} else if(nd != 2) {
Tango::Except::throw_exception("PyDs_WrongNumpyArrayDimensions",
"Expecting a sequence of sequences (IMAGE attribute).",
fname + "()");
}
} else {
if(nd == 1 && dims[0] == 0) {
// Empty 1D array
is_empty = true;
} else if(nd != 1) {
Tango::Except::throw_exception("PyDs_WrongNumpyArrayDimensions",
"Expecting a sequence (SPECTRUM attribute).",
fname + "()");
}
}
if(is_empty) {
len = 0;
res_dim_x = 0;
res_dim_y = 0;
} else if(isImage) {
len = dims[0] * dims[1];
res_dim_x = dims[1];
res_dim_y = dims[0];
} else {
len = dims[0];
res_dim_x = dims[0];
}
MEMORY_ALLOCATOR(TangoScalarType, TangoArrayType, len, allocation);
if(exact_array) {
memcpy(tg_data, arr.data(), len * sizeof(TangoScalarType));
} else {
try {
py::array_t<TangoScalarType, py::array::c_style | py::array::forcecast> arr_casted(arr);
py::size_t processed_elements = static_cast<py::size_t>(arr_casted.size());
if(processed_elements < len) {
buffer_deleter__<tangoArrayTypeConst>(tg_data, allocation, processed_elements);
throw py::value_error("Array size is smaller than expected.");
}
memcpy(tg_data, arr_casted.data(), len * sizeof(TangoScalarType));
} catch(const py::error_already_set &) {
buffer_deleter__<tangoArrayTypeConst>(tg_data, allocation, 0);
throw;
}
}
return tg_data;
}
template <>
inline TANGO_const2scalartype(Tango::DEVVAR_STRINGARRAY) *
python_to_cpp_buffer<Tango::DEVVAR_STRINGARRAY>(py::object &py_val,
MemoryAllocation allocation,
const std::string &fname,
bool isImage,
py::size_t &res_dim_x,
py::size_t &res_dim_y) {
return python_to_cpp_buffer_generic<Tango::DEVVAR_STRINGARRAY>(py_val,
allocation,
fname,
isImage,
res_dim_x,
res_dim_y);
}
template <int tangoArrayTypeConst>
inline typename TANGO_const2type(tangoArrayTypeConst) * fast_convert2array(py::object py_value) {
using TangoScalarType = typename TANGO_const2scalartype(tangoArrayTypeConst);
using TangoArrayType = typename TANGO_const2type(tangoArrayTypeConst);
py::size_t res_dim_x, res_dim_y;
TangoScalarType *array = python_to_cpp_buffer<tangoArrayTypeConst>(py_value,
MemoryAllocation ::ALLOC,
"array_python_data_to_cpp",
false,
res_dim_x,
res_dim_y);
try {
// not a bug: res_dim_y means nothing to us, we are unidimensional
// here we have max_len and current_len = res_dim_x
return new TangoArrayType(static_cast<_CORBA_ULong>(res_dim_x),
static_cast<_CORBA_ULong>(res_dim_x),
array,
true);
} catch(...) {
TangoArrayType::freebuf(array);
throw;
}
}
template <>
inline TANGO_const2type(Tango::DEVVAR_LONGSTRINGARRAY) * fast_convert2array<Tango::DEVVAR_LONGSTRINGARRAY>(py::object py_value) {
py::object py_long, py_str;
__long_double_string_array_helper(py_value,
DevVarNumericStringArray::LONG_STRING,
"fast_convert2array()",
py_long,
py_str);
std::unique_ptr<Tango::DevVarLongArray> a_long(fast_convert2array<Tango::DEVVAR_LONGARRAY>(py_long));
std::unique_ptr<Tango::DevVarStringArray> a_str(fast_convert2array<Tango::DEVVAR_STRINGARRAY>(py_str));
std::unique_ptr<Tango::DevVarLongStringArray> result(new Tango::DevVarLongStringArray());
result->lvalue = *a_long;
result->svalue = *a_str;
return result.release();
}
template <>
inline TANGO_const2type(Tango::DEVVAR_DOUBLESTRINGARRAY) * fast_convert2array<Tango::DEVVAR_DOUBLESTRINGARRAY>(py::object py_value) {
py::object py_double, py_str;
__long_double_string_array_helper(py_value,
DevVarNumericStringArray::LONG_STRING,
"fast_convert2array()",
py_double,
py_str);
std::unique_ptr<Tango::DevVarDoubleArray> a_double(fast_convert2array<Tango::DEVVAR_DOUBLEARRAY>(py_double));
std::unique_ptr<Tango::DevVarStringArray> a_str(fast_convert2array<Tango::DEVVAR_STRINGARRAY>(py_str));
std::unique_ptr<Tango::DevVarDoubleStringArray> result(new Tango::DevVarDoubleStringArray());
result->dvalue = *a_double;
result->svalue = *a_str;
return result.release();
}
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