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https://github.com/NGSolve/netgen.git
synced 2025-01-12 22:20:35 +05:00
pickling of Array
This commit is contained in:
Christopher Lackner
parent
e5056dcd57
commit
3b29d03227
@ -156,165 +156,7 @@ namespace ngcore
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{ return std::string("sp_")+GetPyName<T>(); }
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};
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template<typename T>
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Array<T> makeCArray(const py::object& obj)
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{
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Array<T> arr;
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if(py::isinstance<py::list>(obj))
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for(auto& val : py::cast<py::list>(obj))
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arr.Append(py::cast<T>(val));
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else if(py::isinstance<py::tuple>(obj))
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for(auto& val : py::cast<py::tuple>(obj))
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arr.Append(py::cast<T>(val));
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else
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throw py::type_error("Cannot convert Python object to C Array");
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return arr;
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}
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template <typename T, typename TIND=typename FlatArray<T>::index_type>
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void ExportArray (py::module &m)
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{
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using TFlat = FlatArray<T, TIND>;
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using TArray = Array<T, TIND>;
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std::string suffix = GetPyName<T>() + "_" +
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GetPyName<TIND>();
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std::string fname = std::string("FlatArray_") + suffix;
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auto flatarray_class = py::class_<TFlat>(m, fname.c_str(),
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py::buffer_protocol())
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.def ("__len__", [] ( TFlat &self ) { return self.Size(); } )
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.def ("__getitem__",
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[](TFlat & self, TIND i) -> T&
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{
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static constexpr int base = IndexBASE<TIND>();
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if (i < base || i >= self.Size()+base)
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throw py::index_error();
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return self[i];
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},
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py::return_value_policy::reference)
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.def ("__setitem__",
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[](TFlat & self, TIND i, T val) -> T&
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{
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static constexpr int base = IndexBASE<TIND>();
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if (i < base || i >= self.Size()+base)
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throw py::index_error();
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self[i] = val;
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return self[i];
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},
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py::return_value_policy::reference)
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.def ("__setitem__",
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[](TFlat & self, py::slice slice, T val)
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{
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size_t start, stop, step, slicelength;
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if (!slice.compute(self.Size(), &start, &stop, &step, &slicelength))
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throw py::error_already_set();
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static constexpr int base = IndexBASE<TIND>();
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if (start < base || start+(slicelength-1)*step >= self.Size()+base)
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throw py::index_error();
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for (size_t i = 0; i < slicelength; i++, start+=step)
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self[start] = val;
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})
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.def("__iter__", [] ( TFlat & self) {
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return py::make_iterator (self.begin(),self.end());
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}, py::keep_alive<0,1>()) // keep array alive while iterator is used
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.def("__str__", [](TFlat& self)
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{
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return ToString(self);
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})
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;
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if constexpr (detail::HasPyFormat<T>::value)
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{
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if(ngcore_have_numpy && !py::detail::npy_format_descriptor<T>::dtype().is_none())
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{
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flatarray_class
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.def_buffer([](TFlat& self)
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{
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return py::buffer_info(
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self.Addr(0),
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sizeof(T),
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py::format_descriptor<T>::format(),
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1,
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{ self.Size() },
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{ sizeof(T) * (self.Addr(1) - self.Addr(0)) });
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})
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.def("NumPy", [](py::object self)
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{
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return py::module::import("numpy")
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.attr("frombuffer")(self, py::detail::npy_format_descriptor<T>::dtype());
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})
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;
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}
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}
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std::string aname = std::string("Array_") + suffix;
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py::class_<TArray, TFlat>(m, aname.c_str())
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.def(py::init([] (size_t n) { return new TArray(n); }),py::arg("n"), "Makes array of given length")
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.def(py::init([] (std::vector<T> const & x)
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{
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size_t s = x.size();
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TArray tmp(s);
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for (size_t i : Range(tmp))
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tmp[TIND(i)] = x[i];
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return tmp;
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}), py::arg("vec"), "Makes array with given list of elements")
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;
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py::implicitly_convertible<std::vector<T>, TArray>();
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}
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template <typename T>
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void ExportTable (py::module &m)
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{
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py::class_<ngcore::Table<T>, std::shared_ptr<ngcore::Table<T>>> (m, ("Table_"+GetPyName<T>()).c_str())
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.def(py::init([] (py::list blocks)
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{
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size_t size = py::len(blocks);
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Array<int> cnt(size);
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size_t i = 0;
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for (auto block : blocks)
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cnt[i++] = py::len(block);
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i = 0;
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Table<T> blocktable(cnt);
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for (auto block : blocks)
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{
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auto row = blocktable[i++];
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size_t j = 0;
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for (auto val : block)
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row[j++] = val.cast<T>();
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}
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// cout << "blocktable = " << *blocktable << endl;
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return blocktable;
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}), py::arg("blocks"), "a list of lists")
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.def ("__len__", [] (Table<T> &self ) { return self.Size(); } )
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.def ("__getitem__",
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[](Table<T> & self, size_t i) -> FlatArray<T>
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{
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if (i >= self.Size())
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throw py::index_error();
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return self[i];
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})
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.def("__str__", [](Table<T> & self)
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{
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return ToString(self);
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})
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;
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}
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void NGCORE_API SetFlag(Flags &flags, std::string s, py::object value);
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// Parse python kwargs to flags
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Flags NGCORE_API CreateFlagsFromKwArgs(const py::kwargs& kwargs, py::object pyclass = py::none(),
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py::list info = py::list());
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// Create python dict from kwargs
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py::dict NGCORE_API CreateDictFromFlags(const Flags& flags);
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// *************** Archiving functionality **************
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// *************** Archiving functionality **************
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template<typename T>
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Archive& Archive :: Shallow(T& val)
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@ -429,6 +271,165 @@ namespace ngcore
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});
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}
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template<typename T>
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Array<T> makeCArray(const py::object& obj)
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{
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Array<T> arr;
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if(py::isinstance<py::list>(obj))
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for(auto& val : py::cast<py::list>(obj))
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arr.Append(py::cast<T>(val));
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else if(py::isinstance<py::tuple>(obj))
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for(auto& val : py::cast<py::tuple>(obj))
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arr.Append(py::cast<T>(val));
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else
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throw py::type_error("Cannot convert Python object to C Array");
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return arr;
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}
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template <typename T, typename TIND=typename FlatArray<T>::index_type>
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void ExportArray (py::module &m)
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{
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using TFlat = FlatArray<T, TIND>;
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using TArray = Array<T, TIND>;
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std::string suffix = GetPyName<T>() + "_" +
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GetPyName<TIND>();
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std::string fname = std::string("FlatArray_") + suffix;
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auto flatarray_class = py::class_<TFlat>(m, fname.c_str(),
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py::buffer_protocol())
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.def ("__len__", [] ( TFlat &self ) { return self.Size(); } )
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.def ("__getitem__",
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[](TFlat & self, TIND i) -> T&
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{
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static constexpr int base = IndexBASE<TIND>();
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if (i < base || i >= self.Size()+base)
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throw py::index_error();
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return self[i];
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},
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py::return_value_policy::reference)
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.def ("__setitem__",
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[](TFlat & self, TIND i, T val) -> T&
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{
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static constexpr int base = IndexBASE<TIND>();
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if (i < base || i >= self.Size()+base)
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throw py::index_error();
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self[i] = val;
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return self[i];
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},
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py::return_value_policy::reference)
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.def ("__setitem__",
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[](TFlat & self, py::slice slice, T val)
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{
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size_t start, stop, step, slicelength;
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if (!slice.compute(self.Size(), &start, &stop, &step, &slicelength))
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throw py::error_already_set();
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static constexpr int base = IndexBASE<TIND>();
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if (start < base || start+(slicelength-1)*step >= self.Size()+base)
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throw py::index_error();
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for (size_t i = 0; i < slicelength; i++, start+=step)
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self[start] = val;
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})
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.def("__iter__", [] ( TFlat & self) {
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return py::make_iterator (self.begin(),self.end());
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}, py::keep_alive<0,1>()) // keep array alive while iterator is used
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.def("__str__", [](TFlat& self)
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{
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return ToString(self);
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})
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;
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if constexpr (detail::HasPyFormat<T>::value)
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{
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if(ngcore_have_numpy && !py::detail::npy_format_descriptor<T>::dtype().is_none())
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{
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flatarray_class
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.def_buffer([](TFlat& self)
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{
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return py::buffer_info(
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self.Addr(0),
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sizeof(T),
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py::format_descriptor<T>::format(),
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1,
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{ self.Size() },
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{ sizeof(T) * (self.Addr(1) - self.Addr(0)) });
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})
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.def("NumPy", [](py::object self)
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{
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return py::module::import("numpy")
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.attr("frombuffer")(self, py::detail::npy_format_descriptor<T>::dtype());
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})
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;
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}
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}
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std::string aname = std::string("Array_") + suffix;
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auto arr = py::class_<TArray, TFlat> (m, aname.c_str())
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.def(py::init([] (size_t n) { return new TArray(n); }),py::arg("n"), "Makes array of given length")
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.def(py::init([] (std::vector<T> const & x)
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{
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size_t s = x.size();
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TArray tmp(s);
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for (size_t i : Range(tmp))
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tmp[TIND(i)] = x[i];
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return tmp;
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}), py::arg("vec"), "Makes array with given list of elements")
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;
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if constexpr(is_archivable<TArray>)
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arr.def(NGSPickle<TArray>());
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py::implicitly_convertible<std::vector<T>, TArray>();
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}
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template <typename T>
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void ExportTable (py::module &m)
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{
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py::class_<ngcore::Table<T>, std::shared_ptr<ngcore::Table<T>>> (m, ("Table_"+GetPyName<T>()).c_str())
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.def(py::init([] (py::list blocks)
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{
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size_t size = py::len(blocks);
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Array<int> cnt(size);
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size_t i = 0;
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for (auto block : blocks)
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cnt[i++] = py::len(block);
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i = 0;
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Table<T> blocktable(cnt);
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for (auto block : blocks)
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{
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auto row = blocktable[i++];
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size_t j = 0;
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for (auto val : block)
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row[j++] = val.cast<T>();
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}
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// cout << "blocktable = " << *blocktable << endl;
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return blocktable;
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}), py::arg("blocks"), "a list of lists")
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.def ("__len__", [] (Table<T> &self ) { return self.Size(); } )
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.def ("__getitem__",
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[](Table<T> & self, size_t i) -> FlatArray<T>
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{
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if (i >= self.Size())
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throw py::index_error();
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return self[i];
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})
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.def("__str__", [](Table<T> & self)
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{
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return ToString(self);
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})
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;
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}
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void NGCORE_API SetFlag(Flags &flags, std::string s, py::object value);
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// Parse python kwargs to flags
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Flags NGCORE_API CreateFlagsFromKwArgs(const py::kwargs& kwargs, py::object pyclass = py::none(),
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py::list info = py::list());
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// Create python dict from kwargs
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py::dict NGCORE_API CreateDictFromFlags(const Flags& flags);
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} // namespace ngcore
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