Hardcopy of pybind11 instead of using git submodules (#552)

* removed pybind as submodule
* added hardcopy of pybind11 2.10.0
* rename pybind11 folder to avoid conflicts when changing branch

Co-authored-by: Dhanya Thattil <dhanya.thattil@psi.ch>

libs/pybind/tests/test_numpy_vectorize.cpp

@@ -0,0 +1,107 @@
+/*
+    tests/test_numpy_vectorize.cpp -- auto-vectorize functions over NumPy array
+    arguments
+
+    Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
+
+    All rights reserved. Use of this source code is governed by a
+    BSD-style license that can be found in the LICENSE file.
+*/
+
+#include <pybind11/numpy.h>
+
+#include "pybind11_tests.h"
+
+#include <utility>
+
+double my_func(int x, float y, double z) {
+    py::print("my_func(x:int={}, y:float={:.0f}, z:float={:.0f})"_s.format(x, y, z));
+    return (float) x * y * z;
+}
+
+TEST_SUBMODULE(numpy_vectorize, m) {
+    try {
+        py::module_::import("numpy");
+    } catch (const py::error_already_set &) {
+        return;
+    }
+
+    // test_vectorize, test_docs, test_array_collapse
+    // Vectorize all arguments of a function (though non-vector arguments are also allowed)
+    m.def("vectorized_func", py::vectorize(my_func));
+
+    // Vectorize a lambda function with a capture object (e.g. to exclude some arguments from the
+    // vectorization)
+    m.def("vectorized_func2", [](py::array_t<int> x, py::array_t<float> y, float z) {
+        return py::vectorize([z](int x, float y) { return my_func(x, y, z); })(std::move(x),
+                                                                               std::move(y));
+    });
+
+    // Vectorize a complex-valued function
+    m.def("vectorized_func3",
+          py::vectorize([](std::complex<double> c) { return c * std::complex<double>(2.f); }));
+
+    // test_type_selection
+    // NumPy function which only accepts specific data types
+    // A lot of these no lints could be replaced with const refs, and probably should at some
+    // point.
+    m.def("selective_func",
+          [](const py::array_t<int, py::array::c_style> &) { return "Int branch taken."; });
+    m.def("selective_func",
+          [](const py::array_t<float, py::array::c_style> &) { return "Float branch taken."; });
+    m.def("selective_func", [](const py::array_t<std::complex<float>, py::array::c_style> &) {
+        return "Complex float branch taken.";
+    });
+
+    // test_passthrough_arguments
+    // Passthrough test: references and non-pod types should be automatically passed through (in
+    // the function definition below, only `b`, `d`, and `g` are vectorized):
+    struct NonPODClass {
+        explicit NonPODClass(int v) : value{v} {}
+        int value;
+    };
+    py::class_<NonPODClass>(m, "NonPODClass")
+        .def(py::init<int>())
+        .def_readwrite("value", &NonPODClass::value);
+    m.def("vec_passthrough",
+          py::vectorize([](const double *a,
+                           double b,
+                           // Changing this broke things
+                           // NOLINTNEXTLINE(performance-unnecessary-value-param)
+                           py::array_t<double> c,
+                           const int &d,
+                           int &e,
+                           NonPODClass f,
+                           const double g) { return *a + b + c.at(0) + d + e + f.value + g; }));
+
+    // test_method_vectorization
+    struct VectorizeTestClass {
+        explicit VectorizeTestClass(int v) : value{v} {};
+        float method(int x, float y) const { return y + (float) (x + value); }
+        int value = 0;
+    };
+    py::class_<VectorizeTestClass> vtc(m, "VectorizeTestClass");
+    vtc.def(py::init<int>()).def_readwrite("value", &VectorizeTestClass::value);
+
+    // Automatic vectorizing of methods
+    vtc.def("method", py::vectorize(&VectorizeTestClass::method));
+
+    // test_trivial_broadcasting
+    // Internal optimization test for whether the input is trivially broadcastable:
+    py::enum_<py::detail::broadcast_trivial>(m, "trivial")
+        .value("f_trivial", py::detail::broadcast_trivial::f_trivial)
+        .value("c_trivial", py::detail::broadcast_trivial::c_trivial)
+        .value("non_trivial", py::detail::broadcast_trivial::non_trivial);
+    m.def("vectorized_is_trivial",
+          [](const py::array_t<int, py::array::forcecast> &arg1,
+             const py::array_t<float, py::array::forcecast> &arg2,
+             const py::array_t<double, py::array::forcecast> &arg3) {
+              py::ssize_t ndim = 0;
+              std::vector<py::ssize_t> shape;
+              std::array<py::buffer_info, 3> buffers{
+                  {arg1.request(), arg2.request(), arg3.request()}};
+              return py::detail::broadcast(buffers, ndim, shape);
+          });
+
+    m.def("add_to", py::vectorize([](NonPODClass &x, int a) { x.value += a; }));
+}