Initial documentation for python interface

Documentation/DeveloperHelpSources/Interfaces.docu

@@ -207,6 +207,13 @@ This page shows interfaces for other operations.
 Interface to call functions across plugins ( \ref RPCInterfacePage  )
 \n
 
+\subpage pythonInterfacePage
+\n
+\image html ScriptInterface.png
+\n
+For plugins which provide python scriptable functions ( \ref pythonInterfacePage  )
+\n
+
 \subpage scriptInterfacePage
 \n
 \image html ScriptInterface.png
@@ -214,6 +221,7 @@ Interface to call functions across plugins ( \ref RPCInterfacePage  )
 For plugins which provide scriptable functions ( \ref scriptInterfacePage  )
 \n
 
+
 \subpage pluginConnectionInterfacePage
 \n
 \image html PluginConnectionInterface.png

Documentation/DeveloperHelpSources/mainpage.docu

@@ -21,7 +21,7 @@
  * - \subpage dataFlow "Dataflow"
  * - \subpage options "Command line options and config files"
  * - \subpage scripting
- * - \subpage python_scripting "OpenFlipper Scripting with python"
+ * - \subpage python_scripting
  *
  * \subpage misc
  * - \ref changelog

Documentation/DeveloperHelpSources/python-scripting.docu

 /*!
-\page python-scripting OpenFlipper Python Scripting and Batch Mode
+\page python_scripting OpenFlipper Python Scripting and Batch Mode
 
   \section python_scripting_batch_mode OpenFlipper Batch mode with python
     OpenFlipper can be started in batch mode without a graphical user interface by providing "-b" 
@@ -10,5 +10,15 @@
     or graphical functionality will be loaded. You can see on the command line (when "-c" is given),
     which plugins are activated and which are skipped in batch mode.
 
-
+  
+    \section python_scripting_datattypes DataTypes
+      \subsection  python_scripting_matrixtype Matrix4x4 data type
+        The Matrix4x4T type used in the C++ code is mapped from python. Details can be found here:
+        \subpage python_scripting_matrix4x4_type
+  
+      \subsection  python_scripting_vectortype 3 Dimensional vector type
+        The Vector type used in the C++ code is mapped from python. Details can be found here:
+        \subpage python_scripting_vector_type
+  
+  
  */

PythonInterpreter/PythonTypeConversions.hh

@@ -96,7 +96,23 @@ namespace pybind11 { namespace detail {
     };
 }} // namespace pybind11::detail
 
-
+/** \page python_scripting_vector_type Vector data type used for python scripting
+ *
+ *   The matrix type Vector is mapped to python to handle Vector operations.
+ *
+ *   The integrated conversion can map the C++ Vector type to and from a tuple, a list or a numpy array.
+ *   The preferred choice is the numpy array. Tuple and list have to contain 3 elements. A numpy array
+ *   has to have a dimension of 1, with 3 elements.
+ *
+ *   Creating a matrix in python is the done like in the following example:
+ *   \code
+ *     import numpy as np
+ *
+ *     vector = np.array([1.0,0.0,0.0]);
+ *   \endcode
+ *
+ *   The conversion from C++ to python will always create a numpy array on the python side.
+ */
 namespace pybind11 { namespace detail {
     template <> struct type_caster<Vector> {
     public:
@@ -192,7 +208,24 @@ namespace pybind11 { namespace detail {
     };
 }} // namespace pybind11::detail
 
-
+/** \page python_scripting_matrix4x4_type Matrix4x4 data type used for python scripting
+ *
+ *   The matrix type Matrix4x4 is mapped to python to handle matrix operations.
+ *
+ *   The integrated conversion can map the C++ Matrix4x4 type to and from a tuple, a list or a numpy array.
+ *   The preferred choice is the numpy array. Tuple and list have to contain 16 elements. A numpy array
+ *   has to have a dimension of 2, with 4x4 elements. All data is assumed to be given column major. Therefore
+ *   the first for elements define the first column and so on.
+ *
+ *   Creating a matrix in python is the done like in the following example:
+ *   \code
+ *     import numpy as np
+ *
+ *     matr = np.array( [[1.0,0.0,0.0,0.0],[0.0,1.0,0.0,0.0],[0.0,0.0,1.0,0.0],[0.0,0.0,0.0,1.0]])
+ *   \endcode
+ *
+ *   The conversion from C++ to python will always create a numpy array on the python side.
+ */
 namespace pybind11 { namespace detail {
     template <> struct type_caster<Matrix4x4> {
     public:
@@ -235,7 +268,8 @@ namespace pybind11 { namespace detail {
                                        PyFloat_AsDouble(PyList_GetItem(source,11)),
                                        PyFloat_AsDouble(PyList_GetItem(source,12)),
                                        PyFloat_AsDouble(PyList_GetItem(source,13)),
-                                       PyFloat_AsDouble(PyList_GetItem(source,14))};
+                                       PyFloat_AsDouble(PyList_GetItem(source,14)),
+                                       PyFloat_AsDouble(PyList_GetItem(source,15))};
 
                /* Now convert into a C++ Matrix4x4 */
                value = Matrix4x4(convert);
@@ -257,11 +291,12 @@ namespace pybind11 { namespace detail {
                                        PyFloat_AsDouble(PyTuple_GetItem(source,7)),
                                        PyFloat_AsDouble(PyTuple_GetItem(source,8)),
                                        PyFloat_AsDouble(PyTuple_GetItem(source,9)),
-                                       PyFloat_AsDouble(PyTuple_GetItem(source,0)),
+                                       PyFloat_AsDouble(PyTuple_GetItem(source,10)),
                                        PyFloat_AsDouble(PyTuple_GetItem(source,11)),
                                        PyFloat_AsDouble(PyTuple_GetItem(source,12)),
                                        PyFloat_AsDouble(PyTuple_GetItem(source,13)),
-                                       PyFloat_AsDouble(PyTuple_GetItem(source,14)) };
+                                       PyFloat_AsDouble(PyTuple_GetItem(source,14)),
+                                       PyFloat_AsDouble(PyTuple_GetItem(source,15))};
 
                /* Now convert into a C++ Matrix4x4 */
                value = Matrix4x4(convert);