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More uniform binding of Numpy arrays (#381)
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- Introduce a standard way to bind numpy arrays: py::array_t<T> and
.noconvert() on the argument
- Take py::array_t by value since it's just a small wrapper
- Update bindings
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Erik Fröjdh authored and GitHub committed 2026-09-25 14:40:33 +02:00
1 parent 8579a140f7
commit 941325ea15
26 files changed
+597 -280
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python/src/ctb_raw_file.hpp
+98 -156
View File
@@ -24,177 +24,119 @@
namespace py = pybind11;
using namespace ::aare;
// One binding for the three ADC SAR decoders. Each is registered under
// its original Python name so existing transforms keep working.
template <void (*decode)(NDView<const uint8_t, 2>, NDView<uint16_t, 2>)>
py::array_t<uint16_t> decode64to16(py::array_t<uint8_t> input) {
auto bytes = make_const_view_2d(input);
constexpr ssize_t bytes_per_word = sizeof(uint64_t);
auto output = py::array_t<uint16_t>(
{bytes.shape(0), bytes.shape(1) / bytes_per_word});
decode(bytes, make_view_2d(output));
return output;
}
constexpr auto decode64to16_doc =
"Decode packed 64-bit ADC samples. Takes a two-dimensional, "
"C-contiguous uint8 array whose row length is a multiple of 8 bytes "
"and returns a uint16 array with one value per 64-bit word.";
void define_ctb_raw_file_io_bindings(py::module &m) {
m.def("adc_sar_05_06_07_08decode64to16", [](py::array_t<uint8_t> input) {
if (input.ndim() != 2) {
throw std::runtime_error(
"Only 2D arrays are supported at this moment");
}
m.def("adc_sar_05_06_07_08decode64to16",
&decode64to16<adc_sar_05_06_07_08decode64to16>,
py::arg("input").noconvert(), decode64to16_doc);
// Create a 2D output array with the same shape as the input
std::vector<ssize_t> shape{input.shape(0),
input.shape(1) /
static_cast<ssize_t>(bits_per_byte)};
py::array_t<uint16_t> output(shape);
m.def("adc_sar_05_decode64to16", &decode64to16<adc_sar_05_decode64to16>,
py::arg("input").noconvert(), decode64to16_doc);
// Create a view of the input and output arrays
NDView<uint64_t, 2> input_view(
reinterpret_cast<uint64_t *>(input.mutable_data()),
{output.shape(0), output.shape(1)});
NDView<uint16_t, 2> output_view(output.mutable_data(),
{output.shape(0), output.shape(1)});
m.def("adc_sar_04_decode64to16", &decode64to16<adc_sar_04_decode64to16>,
py::arg("input").noconvert(), decode64to16_doc);
adc_sar_05_06_07_08decode64to16(input_view, output_view);
m.def(
"apply_custom_weights",
[](py::array_t<uint16_t> input, py::array_t<double> weights) {
auto input_view = make_view_1d(input);
auto weights_view = make_view_1d(weights);
auto output = py::array_t<double>(input_view.size());
apply_custom_weights(input_view, make_view_1d(output),
weights_view);
return output;
},
py::arg("input").noconvert(), py::arg("weights").noconvert(),
"Apply per-bit weights to every value of a one-dimensional, "
"C-contiguous uint16 array and return a float64 array.");
return output;
});
m.def(
"expand24to32bit",
[](py::array_t<uint8_t> input, uint32_t offset) {
constexpr ssize_t bytes_per_channel = 3; // 24 bit
auto input_view = make_const_view_1d(input);
auto output =
py::array_t<uint32_t>(input_view.size() / bytes_per_channel);
aare::expand24to32bit(input_view, make_view_1d(output),
aare::BitOffset(offset));
return output;
},
py::arg("input").noconvert(), py::arg("offset"),
"Expand packed 24-bit values from a one-dimensional, C-contiguous "
"uint8 array into a uint32 array.");
m.def("adc_sar_05_decode64to16", [](py::array_t<uint8_t> input) {
if (input.ndim() != 2) {
throw std::runtime_error(
"Only 2D arrays are supported at this moment");
}
m.def(
"expand4to8bit",
[](py::array_t<uint8_t> input) {
auto input_view = make_const_view_1d(input);
auto output = py::array_t<uint8_t>(input_view.size() * 2);
aare::expand4to8bit(input_view, make_view_1d(output));
return output;
},
py::arg("input").noconvert(),
"Expand two 4-bit values per byte of a one-dimensional, C-contiguous "
"uint8 array into a uint8 array of twice the length.");
// Create a 2D output array with the same shape as the input
std::vector<ssize_t> shape{input.shape(0),
input.shape(1) /
static_cast<ssize_t>(bits_per_byte)};
py::array_t<uint16_t> output(shape);
m.def(
"decode_my302",
[](py::array_t<uint8_t> input, uint32_t offset) {
// Physical layout of the chip
constexpr ssize_t channels = 64;
constexpr ssize_t counters = 3;
constexpr ssize_t bytes_per_channel = 3; // 24 bit
constexpr ssize_t n_outputs = 2;
// Create a view of the input and output arrays
NDView<uint64_t, 2> input_view(
reinterpret_cast<uint64_t *>(input.mutable_data()),
{output.shape(0), output.shape(1)});
NDView<uint16_t, 2> output_view(output.mutable_data(),
{output.shape(0), output.shape(1)});
auto input_view = make_const_view_1d(input);
adc_sar_05_decode64to16(input_view, output_view);
ssize_t expected_size = channels * counters * bytes_per_channel;
return output;
});
// If we have an offset we need one extra byte per output
aare::BitOffset bitoff(offset);
if (bitoff.value())
expected_size += n_outputs;
m.def("adc_sar_04_decode64to16", [](py::array_t<uint8_t> input) {
if (input.ndim() != 2) {
throw std::runtime_error(
"Only 2D arrays are supported at this moment");
}
if (input_view.size() != expected_size) {
throw py::value_error(
fmt::format("{} Expected an input size of {} bytes. Called "
"with input size of {}",
LOCATION, expected_size, input_view.size()));
}
// Create a 2D output array with the same shape as the input
std::vector<ssize_t> shape{input.shape(0),
input.shape(1) /
static_cast<ssize_t>(bits_per_byte)};
py::array_t<uint16_t> output(shape);
auto output = py::array_t<uint32_t>(channels * counters);
auto output_view = make_view_1d(output);
// Create a view of the input and output arrays
NDView<uint64_t, 2> input_view(
reinterpret_cast<uint64_t *>(input.mutable_data()),
{output.shape(0), output.shape(1)});
NDView<uint16_t, 2> output_view(output.mutable_data(),
{output.shape(0), output.shape(1)});
const ssize_t in_step = input_view.size() / n_outputs;
const ssize_t out_step = output_view.size() / n_outputs;
for (ssize_t i = 0; i != n_outputs; ++i) {
NDView<const uint8_t, 1> in_part(
input_view.data() + in_step * i, {in_step});
NDView<uint32_t, 1> out_part(output_view.data() + out_step * i,
{out_step});
aare::expand24to32bit(in_part, out_part, bitoff);
}
adc_sar_04_decode64to16(input_view, output_view);
return output;
});
m.def("apply_custom_weights",
[](py::array_t<uint16_t, py::array::c_style | py::array::forcecast>
&input,
py::array_t<double, py::array::c_style | py::array::forcecast>
&weights) {
// Create new array with same shape as the input array
// (uninitialized values)
py::buffer_info buf = input.request();
py::array_t<double> output(buf.shape);
// Use NDViews to call into the C++ library
auto weights_view = make_view_1d(weights);
NDView<uint16_t, 1> input_view(input.mutable_data(),
{input.size()});
NDView<double, 1> output_view(output.mutable_data(),
{output.size()});
apply_custom_weights(input_view, output_view, weights_view);
return output;
});
m.def("expand24to32bit",
[](py::array_t<uint8_t, py::array::c_style | py::array::forcecast>
&input,
uint32_t offset) {
aare::BitOffset bitoff(offset);
py::buffer_info buf = input.request();
constexpr uint32_t bytes_per_channel = 3; // 24 bit
py::array_t<uint32_t> output(buf.size / bytes_per_channel);
NDView<uint8_t, 1> input_view(input.mutable_data(),
{input.size()});
NDView<uint32_t, 1> output_view(output.mutable_data(),
{output.size()});
aare::expand24to32bit(input_view, output_view, bitoff);
return output;
});
m.def("expand4to8bit",
[](py::array_t<uint8_t, py::array::c_style | py::array::forcecast>
&input) {
py::buffer_info buf = input.request();
py::array_t<uint8_t> output(buf.size * 2);
NDView<uint8_t, 1> input_view(input.mutable_data(),
{input.size()});
NDView<uint8_t, 1> output_view(output.mutable_data(),
{output.size()});
aare::expand4to8bit(input_view, output_view);
return output;
});
m.def("decode_my302",
[](py::array_t<uint8_t, py::array::c_style | py::array::forcecast>
&input,
uint32_t offset) {
// Physical layout of the chip
constexpr size_t channels = 64;
constexpr size_t counters = 3;
constexpr size_t bytes_per_channel = 3; // 24 bit
constexpr int n_outputs = 2;
ssize_t expected_size = channels * counters * bytes_per_channel;
// If whe have an offset we need one extra byte per output
aare::BitOffset bitoff(offset);
if (bitoff.value())
expected_size += n_outputs;
if (input.size() != expected_size) {
throw std::runtime_error(fmt::format(
"{} Expected an input size of {} bytes. Called "
"with input size of {}",
LOCATION, expected_size, input.size()));
}
py::buffer_info buf = input.request();
py::array_t<uint32_t> output(channels * counters);
for (int i = 0; i != n_outputs; ++i) {
auto step = input.size() / n_outputs;
auto out_step = output.size() / n_outputs;
NDView<uint8_t, 1> input_view(input.mutable_data() + step * i,
{input.size() / n_outputs});
NDView<uint32_t, 1> output_view(output.mutable_data() +
out_step * i,
{output.size() / n_outputs});
aare::expand24to32bit(input_view, output_view, bitoff);
}
return output;
});
return output;
},
py::arg("input").noconvert(), py::arg("offset"),
"Decode a Mythen 302 readout from a one-dimensional, C-contiguous "
"uint8 array into a uint32 array of 64 channels times 3 counters.");
py::class_<CtbRawFile>(m, "CtbRawFile")
.def(py::init<const std::filesystem::path &>())