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#include "CoreWrappers.h"
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#include "pywrappers_common.h"
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#include <Data/DataSeriesType.h>
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#include <Data/IDataProvider.h>
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#include <Data/OptionalAxis.h>
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#include <Data/ScalarSeries.h>
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#include <Data/SpectrogramSeries.h>
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#include <Data/Unit.h>
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#include <Data/VectorSeries.h>
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#include <Network/Downloader.h>
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#include <Time/TimeController.h>
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#include <Variable/Variable2.h>
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#include <Variable/VariableController2.h>
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#include <pybind11/chrono.h>
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#include <pybind11/embed.h>
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#include <pybind11/functional.h>
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#include <pybind11/numpy.h>
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#include <pybind11/operators.h>
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#include <pybind11/pybind11.h>
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#include <pybind11/stl.h>
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#include <pybind11/stl_bind.h>
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#include <sstream>
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#include <string>
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namespace py = pybind11;
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using namespace std::chrono;
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template<typename T, typename U, bool row_major = true>
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void copy_vector(py::array_t<double>& t, py::array_t<double>& values, T& dest_t,
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U& dest_values)
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{
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auto t_view = t.unchecked<1>();
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auto values_view = values.unchecked<2>();
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if constexpr(row_major)
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{
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for(std::size_t i = 0; i < t.size(); i++)
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{
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dest_t[i] = t_view[i];
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dest_values[i] = {values_view(i, 0), values_view(i, 1),
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values_view(i, 2)};
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}
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}
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else
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{
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for(std::size_t i = 0; i < t.size(); i++)
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{
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dest_t[i] = t_view[i];
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dest_values[i] = {values_view(0, i), values_view(1, i),
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values_view(2, i)};
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}
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}
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}
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template<typename T, typename U>
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void copy_scalar(py::array_t<double>& t, py::array_t<double>& values, T& dest_t,
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U& dest_values)
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{
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auto t_view = t.unchecked<1>();
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auto values_view = values.unchecked<1>();
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for(std::size_t i = 0; i < t.size(); i++)
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{
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dest_t[i] = t_view[i];
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dest_values[i] = values_view[i];
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}
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}
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template<typename T, typename U>
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void copy_spectro(py::array_t<double>& t, py::array_t<double>& values,
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T& dest_t, U& dest_values)
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{
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auto t_view = t.unchecked<1>();
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auto values_view = values.unchecked<2>();
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const auto width = values.shape(0);
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std::cout << "WIDTH" << width << std::endl;
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for(std::size_t i = 0; i < t.size(); i++)
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{
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dest_t[i] = t_view[i];
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for(int j = 0; j < width; j++)
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{
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dest_values[i * width + j] = values_view(j, i);
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std::cout << "dest_values[" << i * width + j << "] = values_view(" << j
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<< ", " << i << ") = " << values_view(j, i) << std::endl;
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}
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}
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}
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PYBIND11_MODULE(pysciqlopcore, m)
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{
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pybind11::bind_vector<std::vector<double>>(m, "VectorDouble");
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py::enum_<DataSeriesType>(m, "DataSeriesType")
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.value("SCALAR", DataSeriesType::SCALAR)
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.value("SPECTROGRAM", DataSeriesType::SPECTROGRAM)
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.value("VECTOR", DataSeriesType::VECTOR)
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.value("NONE", DataSeriesType::NONE)
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.export_values();
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py::class_<Unit>(m, "Unit")
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.def_readwrite("name", &Unit::m_Name)
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.def_readwrite("time_unit", &Unit::m_TimeUnit)
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.def(py::self == py::self)
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.def(py::self != py::self)
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.def("__repr__", __repr__<Unit>);
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py::class_<Response>(m, "Response")
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.def("status_code", &Response::status_code);
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py::class_<Downloader>(m, "Downloader")
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.def_static("get", Downloader::get)
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.def_static("getAsync", Downloader::getAsync)
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.def_static("downloadFinished", Downloader::downloadFinished);
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py::class_<ArrayDataIteratorValue>(m, "ArrayDataIteratorValue")
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.def_property_readonly("value", &ArrayDataIteratorValue::first);
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py::class_<OptionalAxis>(m, "OptionalAxis")
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.def("__len__", &OptionalAxis::size)
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.def_property_readonly("size", &OptionalAxis::size)
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.def("__getitem__",
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[](OptionalAxis& ax, int key) {
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return (*(ax.begin() + key)).first();
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},
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py::is_operator())
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.def("__iter__",
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[](OptionalAxis& ax) {
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return py::make_iterator(ax.begin(), ax.end());
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},
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py::keep_alive<0, 1>());
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py::class_<DataSeriesIteratorValue>(m, "DataSeriesIteratorValue")
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.def_property_readonly("x", &DataSeriesIteratorValue::x)
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.def_property_readonly("y", &DataSeriesIteratorValue::y)
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.def("value",
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py::overload_cast<>(&DataSeriesIteratorValue::value, py::const_))
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.def("value",
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py::overload_cast<int>(&DataSeriesIteratorValue::value, py::const_))
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.def("values", &DataSeriesIteratorValue::values);
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py::class_<IDataSeries, std::shared_ptr<IDataSeries>>(m, "IDataSeries")
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.def("nbPoints", &IDataSeries::nbPoints)
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.def_property_readonly("xAxisUnit", &IDataSeries::xAxisUnit)
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.def_property_readonly("yAxisUnit", &IDataSeries::yAxisUnit)
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.def_property_readonly("valuesUnit", &IDataSeries::valuesUnit)
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.def("__getitem__",
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[](IDataSeries& serie, int key) { return *(serie.begin() + key); },
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py::is_operator())
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.def("__len__", &IDataSeries::nbPoints)
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.def("__iter__",
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[](IDataSeries& serie) {
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return py::make_iterator(serie.begin(), serie.end());
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},
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py::keep_alive<0, 1>())
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.def("__repr__", __repr__<IDataSeries>);
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py::class_<ArrayData<1>, std::shared_ptr<ArrayData<1>>>(m, "ArrayData1d")
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.def("cdata", [](ArrayData<1>& array) { return array.cdata(); });
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py::class_<ScalarSeries, std::shared_ptr<ScalarSeries>, IDataSeries>(
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m, "ScalarSeries")
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.def("nbPoints", &ScalarSeries::nbPoints);
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py::class_<VectorSeries, std::shared_ptr<VectorSeries>, IDataSeries>(
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m, "VectorSeries")
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.def("nbPoints", &VectorSeries::nbPoints);
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py::class_<DataSeries<2>, std::shared_ptr<DataSeries<2>>, IDataSeries>(
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m, "DataSeries2d")
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.def_property_readonly(
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"xAxis", py::overload_cast<>(&DataSeries<2>::xAxisData, py::const_))
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.def_property_readonly(
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"yAxis", py::overload_cast<>(&DataSeries<2>::yAxis, py::const_));
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py::class_<SpectrogramSeries, std::shared_ptr<SpectrogramSeries>,
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DataSeries<2>>(m, "SpectrogramSeries")
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.def("nbPoints", &SpectrogramSeries::nbPoints)
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.def("xRes", &SpectrogramSeries::xResolution);
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py::class_<IDataProvider, std::shared_ptr<IDataProvider>>(m, "IDataProvider");
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py::class_<Variable, std::shared_ptr<Variable>>(m, "Variable")
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.def(py::init<const QString&>())
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.def_property("name", &Variable::name, &Variable::setName)
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.def_property("range", &Variable::range, &Variable::setRange)
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.def_property("cacheRange", &Variable::cacheRange,
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&Variable::setCacheRange)
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.def_property_readonly("nbPoints", &Variable::nbPoints)
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.def_property_readonly("dataSeries", &Variable::dataSeries)
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.def("__len__",
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[](Variable& variable) {
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auto rng = variable.dataSeries()->xAxisRange(
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variable.range().m_TStart, variable.range().m_TEnd);
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return std::distance(rng.first, rng.second);
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})
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.def("__iter__",
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[](Variable& variable) {
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auto rng = variable.dataSeries()->xAxisRange(
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variable.range().m_TStart, variable.range().m_TEnd);
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return py::make_iterator(rng.first, rng.second);
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},
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py::keep_alive<0, 1>())
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.def("__getitem__",
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[](Variable& variable, int key) {
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// insane and slow!
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auto rng = variable.dataSeries()->xAxisRange(
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variable.range().m_TStart, variable.range().m_TEnd);
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if(key < 0)
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return *(rng.second + key);
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else
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return *(rng.first + key);
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})
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.def("__repr__", __repr__<Variable>);
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py::class_<TimeSeries::ITimeSerie>(m, "ITimeSerie")
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.def_property_readonly(
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"size", [](const TimeSeries::ITimeSerie& ts) { return ts.size(); })
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.def("__len__",
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[](const TimeSeries::ITimeSerie& ts) { return ts.size(); })
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.def_property_readonly(
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"shape", [](const TimeSeries::ITimeSerie& ts) { return ts.shape(); })
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.def_property_readonly(
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"t",
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[](TimeSeries::ITimeSerie& ts) -> decltype(ts.axis(0))& {
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return ts.axis(0);
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},
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py::return_value_policy::reference);
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py::class_<ScalarTimeSerie, TimeSeries::ITimeSerie>(m, "ScalarTimeSerie")
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.def(py::init<>())
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.def(py::init<std::size_t>())
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.def(py::init([](py::array_t<double> t, py::array_t<double> values) {
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assert(t.size() == values.size());
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ScalarTimeSerie::axis_t _t(t.size());
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ScalarTimeSerie::axis_t _values(t.size());
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copy_scalar(t, values, _t, _values);
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return ScalarTimeSerie(_t, _values);
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}))
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.def("__getitem__",
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[](ScalarTimeSerie& ts, std::size_t key) { return ts[key]; })
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.def("__setitem__", [](ScalarTimeSerie& ts, std::size_t key,
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double value) { *(ts.begin() + key) = value; });
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py::class_<VectorTimeSerie::raw_value_type>(m, "vector")
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.def(py::init<>())
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.def(py::init<double, double, double>())
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.def("__repr__", __repr__<VectorTimeSerie::raw_value_type>)
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.def_readwrite("x", &VectorTimeSerie::raw_value_type::x)
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.def_readwrite("y", &VectorTimeSerie::raw_value_type::y)
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.def_readwrite("z", &VectorTimeSerie::raw_value_type::z);
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py::class_<VectorTimeSerie, TimeSeries::ITimeSerie>(m, "VectorTimeSerie")
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.def(py::init<>())
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.def(py::init<std::size_t>())
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.def(py::init([](py::array_t<double> t, py::array_t<double> values) {
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assert(t.size() * 3 == values.size());
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VectorTimeSerie::axis_t _t(t.size());
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VectorTimeSerie::container_type<VectorTimeSerie::raw_value_type>
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_values(t.size());
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if(values.shape()[0] == 3 && values.shape(1) != 3)
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{
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copy_vector<decltype(_t), decltype(_values), false>(t, values, _t,
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_values);
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}
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else
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{
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copy_vector(t, values, _t, _values);
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}
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return VectorTimeSerie(_t, _values);
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}))
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.def("__getitem__",
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[](VectorTimeSerie& ts, std::size_t key)
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-> VectorTimeSerie::raw_value_type& { return ts[key]; },
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py::return_value_policy::reference)
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.def("__setitem__", [](VectorTimeSerie& ts, std::size_t key,
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VectorTimeSerie::raw_value_type value) {
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*(ts.begin() + key) = value;
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});
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py::class_<SpectrogramTimeSerie::item_t>(m, "SpectrogramTimeSerieItem")
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.def("__getitem__", [](SpectrogramTimeSerie::item_t& self,
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std::size_t key) { return self[key]; });
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py::class_<SpectrogramTimeSerie, TimeSeries::ITimeSerie>(
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m, "SpectrogramTimeSerie")
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.def(py::init<>())
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.def(py::init<const std::vector<std::size_t>>())
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.def(py::init([](py::array_t<double> t, py::array_t<double> values) {
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assert(t.size() < values.size()); // TODO check geometry
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SpectrogramTimeSerie::axis_t _t(t.size());
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SpectrogramTimeSerie::container_type<
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SpectrogramTimeSerie::raw_value_type>
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_values(values.size());
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copy_spectro(t, values, _t, _values);
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std::vector<std::size_t> shape;
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shape.push_back(values.shape(1));
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shape.push_back(values.shape(0));
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return SpectrogramTimeSerie(_t, _values, shape);
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}))
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.def("__getitem__",
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[](SpectrogramTimeSerie& ts, std::size_t key) { return ts[key]; });
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py::class_<Variable2, std::shared_ptr<Variable2>>(m, "Variable2")
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.def(py::init<const QString&>())
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.def_property("name", &Variable2::name, &Variable2::setName)
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.def_property_readonly("range", &Variable2::range)
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.def_property_readonly("nbPoints", &Variable2::nbPoints)
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.def_property_readonly(
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"data",
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[](const Variable2& var) -> TimeSeries::ITimeSerie* {
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auto data = var.data();
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if(data) return data->base();
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return nullptr;
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})
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.def("set_data",
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[](Variable2& var, std::vector<TimeSeries::ITimeSerie*> ts_list,
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const DateTimeRange& range) { var.setData(ts_list, range); })
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.def("__len__", &Variable2::nbPoints)
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.def("__repr__", __repr__<Variable2>);
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py::class_<DateTimeRange>(m, "SqpRange")
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//.def("fromDateTime", &DateTimeRange::fromDateTime,
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// py::return_value_policy::move)
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.def(py::init([](double start, double stop) {
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return DateTimeRange{start, stop};
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}))
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.def(py::init(
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[](system_clock::time_point start, system_clock::time_point stop) {
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double start_ =
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0.001 *
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duration_cast<milliseconds>(start.time_since_epoch()).count();
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double stop_ =
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0.001 *
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duration_cast<milliseconds>(stop.time_since_epoch()).count();
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return DateTimeRange{start_, stop_};
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}))
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.def_property_readonly("start",
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[](const DateTimeRange& range) {
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return system_clock::from_time_t(range.m_TStart);
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})
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.def_property_readonly("stop",
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[](const DateTimeRange& range) {
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return system_clock::from_time_t(range.m_TEnd);
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})
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.def("__repr__", __repr__<DateTimeRange>);
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}
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