squeeze extra dims of numpy vectors so no need ravel.

cython/test/test_KalmanFilter.py

@@ -48,23 +48,23 @@ class TestKalmanFilter(unittest.TestCase):
 
         # Run iteration 1
         state = KF.predict(state, F, B, u, modelQ)
-        self.assertTrue(np.allclose(expected1, state.mean().ravel()))
+        self.assertTrue(np.allclose(expected1, state.mean()))
         self.assertTrue(np.allclose(P01, state.covariance()))
         state = KF.update(state, H, z1, modelR)
-        self.assertTrue(np.allclose(expected1, state.mean().ravel()))
+        self.assertTrue(np.allclose(expected1, state.mean()))
         self.assertTrue(np.allclose(I11, state.information()))
 
         # Run iteration 2
         state = KF.predict(state, F, B, u, modelQ)
-        self.assertTrue(np.allclose(expected2, state.mean().ravel()))
+        self.assertTrue(np.allclose(expected2, state.mean()))
         state = KF.update(state, H, z2, modelR)
-        self.assertTrue(np.allclose(expected2, state.mean().ravel()))
+        self.assertTrue(np.allclose(expected2, state.mean()))
 
         # Run iteration 3
         state = KF.predict(state, F, B, u, modelQ)
-        self.assertTrue(np.allclose(expected3, state.mean().ravel()))
+        self.assertTrue(np.allclose(expected3, state.mean()))
         state = KF.update(state, H, z3, modelR)
-        self.assertTrue(np.allclose(expected3, state.mean().ravel()))
+        self.assertTrue(np.allclose(expected3, state.mean()))
 
 if __name__ == "__main__":
     unittest.main()

cython/test/test_Values.py

@@ -43,7 +43,7 @@ class TestValues(unittest.TestCase):
 
         # special cases for Vector and Matrix:
         actualVector = values.atVector(11)
-        self.assertTrue(np.allclose(vec, actualVector.ravel(), tol))
+        self.assertTrue(np.allclose(vec, actualVector, tol))
         actualMatrix = values.atMatrix(12)
         self.assertTrue(np.allclose(mat, actualMatrix, tol))
 

wrap/Module.cpp

@@ -380,6 +380,7 @@ void Module::emit_cython_pyx(FileWriter& pyxFile) const {
   // headers...
   string pxdHeader = name + "_wrapper";
   pyxFile.oss << "cimport numpy as np\n"
+                 "import numpy as npp\n"
                  "cimport " << pxdHeader << " as " << "pxd" << "\n"
                  "from "<< pxdHeader << " cimport shared_ptr\n"
                  "from "<< pxdHeader << " cimport dynamic_pointer_cast\n";
@@ -392,6 +393,13 @@ void Module::emit_cython_pyx(FileWriter& pyxFile) const {
                  "from libcpp.pair cimport pair\n"
                  "from libcpp.string cimport string\n"
                  "from cython.operator cimport dereference as deref\n\n\n";
+  pyxFile.oss << 
+R"rawstr(def Vectorize(*args):
+    ret = npp.squeeze(npp.asarray(args, dtype='float'))
+    if ret.ndim == 0: ret = npp.expand_dims(ret, axis=0)
+    return ret
+)rawstr";
+
   for(const Class& cls: expandedClasses)
     cls.emit_cython_pyx(pyxFile, expandedClasses);
   pyxFile.oss << "\n";

wrap/ReturnType.cpp

@@ -89,8 +89,12 @@ std::string ReturnType::pyx_returnType(bool addShared) const {
 /* ************************************************************************* */
 std::string ReturnType::pyx_casting(const std::string& var,
                                     bool isSharedVar) const {
-  if (isEigen())
-    return "ndarray_copy(" + var + ")";
+  if (isEigen()) { 
+    string s = "ndarray_copy(" + var + ")";
+    if (pyxClassName() == "Vector")
+      return "Vectorize(" + s + ")";
+    else return s;
+  }
   else if (isNonBasicType()) {
     if (isPtr || isSharedVar)
       return pyxClassName() + ".cyCreateFromShared(" + var + ")";