Use numpy arrays as default type for vector in OpenFlipper

Documentation/DeveloperHelpSources/changelog.docu

 /*! \page changelog Changelog
 
 
-- <b>OpenFlipper 4.0 ( ?/?/? )</b>
+- <b>OpenFlipper 4.0 ( 25/02/2019 )</b>
      - <b>Breaking changes</b>
          - Picking functions use size_t instead of unsigned int now (Required to get rid of a lot of warnings during compilation)    
          - Enabled AUTOMOC in cmake for QT ( If you get redefinition errors, guard the corresponding headers with a  #pragma once ; If you get gl.h before glew.h errors, move your widgets not using OpenGL into a subdir and add that to the DIRS macro in your CMakeLists.txt)

PythonInterpreter/PythonTypeConversions.hh

@@ -76,7 +76,6 @@ namespace pybind11 { namespace detail {
                 return NULL;
             }
 
-
             /* Now try to convert into a C++ int */
             value = QString::fromUtf8(ptr, size);
 
@@ -113,7 +112,7 @@ namespace pybind11 { namespace detail {
          * instance or return false upon failure. The second argument
          * indicates whether implicit conversions should be applied.
          */
-        bool load(handle src, bool ) {
+        bool load(handle src, bool convert ) {
 
             /* Extract PyObject from handle */
              PyObject* source = src.ptr();
@@ -139,6 +138,35 @@ namespace pybind11 { namespace detail {
                /* Now try to convert into a C++ int */
                value = Vector(PyFloat_AsDouble(PyTuple_GetItem(source,0)),PyFloat_AsDouble(PyTuple_GetItem(source,1)),PyFloat_AsDouble(PyTuple_GetItem(source,2)));
 
+             } else if ( py::cast<py::array>(source) ) {
+
+               py::array array = py::cast<py::array>(source);
+
+               if (  array.size() != 3) {
+                 PyErr_SetString(PyExc_RuntimeError, "Vector Conversion: Numpy Array size should be 3!");
+                 throw py::error_already_set();
+                 return false;
+               }
+
+               if (!convert && !py::array_t<double>::check_(src)) {
+                 PyErr_SetString(PyExc_RuntimeError, "Vector Conversion: Numpy Array, wrong dtype, conversion disabled");
+                 return false;
+               }
+
+               auto buf = py::array_t<double, py::array::c_style | py::array::forcecast>::ensure(src);
+
+               if (!buf) {
+                 PyErr_SetString(PyExc_RuntimeError, "Vector Conversion: Numpy Array, conversion failed.");
+                 return false;
+               }
+               if (buf.ndim() != 1 || buf.size() != 3) {
+                 PyErr_SetString(PyExc_RuntimeError, "Vector Conversion: Numpy Array dimension or size error. Dimension should be one, size 3!");
+                 return false;
+               }
+
+               value = Vector(buf.data());
+               return true;
+
              } else {
                PyErr_SetString(PyExc_RuntimeError, "Vector Conversion: Not a list or a tuple.");
                throw py::error_already_set();
@@ -156,8 +184,14 @@ namespace pybind11 { namespace detail {
          * ``return_value_policy::reference_internal``) and are generally
          * ignored by implicit casters.
          */
-        static handle cast(Vector src, return_value_policy /* policy */, handle /* parent */) {
-            return PyTuple_Pack(3,  PyFloat_FromDouble(src[0]),PyFloat_FromDouble(src[1]),PyFloat_FromDouble(src[2]));
+        static handle cast(Vector src, return_value_policy /* policy */, handle parent ) {
+          // Create numpy array
+//          py::array a({3,1}, src.data());
+          py::array a(3, src.data());
+          return a.release();
+
+//        return PyTuple_Pack(3,  PyFloat_FromDouble(src[0]),PyFloat_FromDouble(src[1]),PyFloat_FromDouble(src[2]));
+
         }
     };
 }} // namespace pybind11::detail