All scatter tests are now passing

xbob/math/main.cpp

@@ -266,9 +266,7 @@ Reference: `<http://home.online.no/~pjacklam/notes/invnorm/>`_\n\
 
 PyDoc_STRVAR(s_scatter_str, "scatter");
 PyDoc_STRVAR(s_scatter_doc,
-"scatter(a) -> (array, array)\n\
-scatter(a, s) -> array\n\
-scatter(a, s, m) -> None\n\
+"scatter(a, [s, [m]]) -> tuple\n\
 \n\
 Computes the scatter matrix of a 2D array *considering data is organized\n\
 row-wise* (each sample is a row, each feature is a column). The\n\
@@ -302,9 +300,7 @@ float arrays as input.\n\
 
 PyDoc_STRVAR(s_scatters_str, "scatters");
 PyDoc_STRVAR(s_scatters_doc,
-"scatters(data) -> (array, array, array)\n\
-scatters(data, sw, sb) -> array\n\
-scatters(data, sw, sb, m) -> None\n\
+"scatters(data, [sw, [sb, [m]]]) -> tuple\n\
 \n\
 Computes the within-class (``sw``) and between-class (``sb``) scatter\n\
 matrices of a set of 2D arrays considering data is organized row-wise\n\

xbob/math/scatter.cpp

@@ -22,7 +22,7 @@ PyObject* py_scatter (PyObject*, PyObject* args, PyObject* kwds) {
   PyBlitzArrayObject* m = 0;
 
   if (!PyArg_ParseTupleAndKeywords(args, kwds, "O&|O&O&",
-        kwlist, 
+        kwlist,
         &PyBlitzArray_Converter, &a,
         &PyBlitzArray_OutputConverter, &s,
         &PyBlitzArray_OutputConverter, &m
@@ -99,23 +99,12 @@ PyObject* py_scatter (PyObject*, PyObject* args, PyObject* kwds) {
 
   int returns = 2 - (user_s + user_m);
 
-  if (!returns) {
-    Py_DECREF(s);
-    Py_DECREF(m);
-    Py_RETURN_NONE;
-  }
-
-  // if you get here, it means the user is interested on stuff to be returned
   PyObject* retval = PyTuple_New(returns);
-  if (!retval) {
-    Py_DECREF(s);
-    Py_DECREF(m);
-  }
 
   // fill from the back
-  if (!user_m) PyTuple_SET_ITEM(--retval, returns, (PyObject*)m);
+  if (!user_m) PyTuple_SET_ITEM(retval, --returns, (PyObject*)m);
   else Py_DECREF(m);
-  if (!user_s) PyTuple_SET_ITEM(--retval, returns, (PyObject*)s);
+  if (!user_s) PyTuple_SET_ITEM(retval, --returns, (PyObject*)s);
   else Py_DECREF(s);
 
   return retval;
@@ -341,7 +330,7 @@ PyObject* py_scatters (PyObject*, PyObject* args, PyObject* kwds) {
       case NPY_FLOAT32:
         {
           std::vector<blitz::Array<float,2>> cxxdata;
-          for (Py_ssize_t i=1; i<PyTuple_GET_SIZE(data); ++i) {
+          for (Py_ssize_t i=0; i<PyTuple_GET_SIZE(data); ++i) {
             cxxdata.push_back(*PyBlitzArrayCxx_AsBlitz<float,2>
                 ((PyBlitzArrayObject*)PyTuple_GET_ITEM(data,i)));
             bob::math::scatters(cxxdata,
@@ -356,7 +345,7 @@ PyObject* py_scatters (PyObject*, PyObject* args, PyObject* kwds) {
       case NPY_FLOAT64:
         {
           std::vector<blitz::Array<double,2>> cxxdata;
-          for (Py_ssize_t i=1; i<PyTuple_GET_SIZE(data); ++i) {
+          for (Py_ssize_t i=0; i<PyTuple_GET_SIZE(data); ++i) {
             cxxdata.push_back(*PyBlitzArrayCxx_AsBlitz<double,2>
                 ((PyBlitzArrayObject*)PyTuple_GET_ITEM(data,i)));
             bob::math::scatters(cxxdata,
@@ -389,27 +378,14 @@ PyObject* py_scatters (PyObject*, PyObject* args, PyObject* kwds) {
 
   int returns = 3 - (user_sw + user_sb + user_m);
 
-  if (!returns) {
-    Py_DECREF(sw);
-    Py_DECREF(sb);
-    Py_DECREF(m);
-    Py_RETURN_NONE;
-  }
-
-  // if you get here, it means the user is interested on stuff to be returned
   PyObject* retval = PyTuple_New(returns);
-  if (!retval) {
-    Py_DECREF(sw);
-    Py_DECREF(sb);
-    Py_DECREF(m);
-  }
 
   // fill from the back
-  if (!user_m) PyTuple_SET_ITEM(--retval, returns, (PyObject*)m);
+  if (!user_m) PyTuple_SET_ITEM(retval, --returns, (PyObject*)m);
   else Py_DECREF(m);
-  if (!user_sb) PyTuple_SET_ITEM(--retval, returns, (PyObject*)sb);
+  if (!user_sb) PyTuple_SET_ITEM(retval, --returns, (PyObject*)sb);
   else Py_DECREF(sb);
-  if (!user_sw) PyTuple_SET_ITEM(--retval, returns, (PyObject*)sw);
+  if (!user_sw) PyTuple_SET_ITEM(retval, --returns, (PyObject*)sw);
   else Py_DECREF(sw);
 
   return retval;

xbob/math/test/test_scatter.py

@@ -44,6 +44,8 @@ def test_scatter():
 
   # This test demonstrates how to use the scatter matrix function of bob.
   S, M = scatter(data.T)
+  S = S.as_ndarray()
+  M = M.as_ndarray()
   S /= (data.shape[1]-1)
 
   # Do the same with numpy and compare. Note that with numpy we are computing