diff --git a/bob/learn/em/empca_trainer.cpp b/bob/learn/em/empca_trainer.cpp
index 0a2653b8c622297c444ad01e12a80f84bfd25074..f197713852fe39c13691867f2fa5445d82b62755 100644
--- a/bob/learn/em/empca_trainer.cpp
+++ b/bob/learn/em/empca_trainer.cpp
@@ -155,7 +155,7 @@ PyObject* PyBobLearnEMEMPCATrainer_getRng(PyBobLearnEMEMPCATrainerObject* self,
(PyBoostMt19937Object*)PyBoostMt19937_Type.tp_alloc(&PyBoostMt19937_Type, 0);
retval->rng = self->cxx->getRng().get();
- return Py_BuildValue("O", retval);
+ return Py_BuildValue("N", retval);
BOB_CATCH_MEMBER("Rng method could not be read", 0)
}
int PyBobLearnEMEMPCATrainer_setRng(PyBobLearnEMEMPCATrainerObject* self, PyObject* value, void*) {
diff --git a/bob/learn/em/isv_base.cpp b/bob/learn/em/isv_base.cpp
index 185463bede107b53ba368372b84dce8df00fe3eb..28e86d5df408e4d5dab2bddf787de0bd9f1b3d12 100644
--- a/bob/learn/em/isv_base.cpp
+++ b/bob/learn/em/isv_base.cpp
@@ -267,7 +267,7 @@ PyObject* PyBobLearnEMISVBase_getUBM(PyBobLearnEMISVBaseObject* self, void*){
(PyBobLearnEMGMMMachineObject*)PyBobLearnEMGMMMachine_Type.tp_alloc(&PyBobLearnEMGMMMachine_Type, 0);
retval->cxx = ubm_gmmMachine;
- return Py_BuildValue("O",retval);
+ return Py_BuildValue("N",retval);
BOB_CATCH_MEMBER("ubm could not be read", 0)
}
int PyBobLearnEMISVBase_setUBM(PyBobLearnEMISVBaseObject* self, PyObject* value, void*){
diff --git a/bob/learn/em/isv_machine.cpp b/bob/learn/em/isv_machine.cpp
index 89de14588244f32c402141ca7bd8d24e37d80674..00f4fcdc3286040c7939fd627ad410369f91bbc1 100644
--- a/bob/learn/em/isv_machine.cpp
+++ b/bob/learn/em/isv_machine.cpp
@@ -242,7 +242,7 @@ PyObject* PyBobLearnEMISVMachine_getISVBase(PyBobLearnEMISVMachineObject* self,
(PyBobLearnEMISVBaseObject*)PyBobLearnEMISVBase_Type.tp_alloc(&PyBobLearnEMISVBase_Type, 0);
retval->cxx = isv_base_o;
- return Py_BuildValue("O",retval);
+ return Py_BuildValue("N",retval);
BOB_CATCH_MEMBER("isv_base could not be read", 0)
}
int PyBobLearnEMISVMachine_setISVBase(PyBobLearnEMISVMachineObject* self, PyObject* value, void*){
diff --git a/bob/learn/em/isv_trainer.cpp b/bob/learn/em/isv_trainer.cpp
index 66f99e1a506634dff809fd08db17b0f7b1c9d9d4..dc357b7dac94db7aa6a94462fc274a9e1b4478a2 100644
--- a/bob/learn/em/isv_trainer.cpp
+++ b/bob/learn/em/isv_trainer.cpp
@@ -340,7 +340,7 @@ PyObject* PyBobLearnEMISVTrainer_getRng(PyBobLearnEMISVTrainerObject* self, void
(PyBoostMt19937Object*)PyBoostMt19937_Type.tp_alloc(&PyBoostMt19937_Type, 0);
retval->rng = self->cxx->getRng().get();
- return Py_BuildValue("O", retval);
+ return Py_BuildValue("N", retval);
BOB_CATCH_MEMBER("Rng method could not be read", 0)
}
int PyBobLearnEMISVTrainer_setRng(PyBobLearnEMISVTrainerObject* self, PyObject* value, void*) {
diff --git a/bob/learn/em/jfa_base.cpp b/bob/learn/em/jfa_base.cpp
index d4fd23b3141ff05b8f846110c1cf87f442da8a91..7637cc6c37516c110efe8a05010f245a53cfb863 100644
--- a/bob/learn/em/jfa_base.cpp
+++ b/bob/learn/em/jfa_base.cpp
@@ -302,7 +302,7 @@ PyObject* PyBobLearnEMJFABase_getUBM(PyBobLearnEMJFABaseObject* self, void*){
(PyBobLearnEMGMMMachineObject*)PyBobLearnEMGMMMachine_Type.tp_alloc(&PyBobLearnEMGMMMachine_Type, 0);
retval->cxx = ubm_gmmMachine;
- return Py_BuildValue("O",retval);
+ return Py_BuildValue("N",retval);
BOB_CATCH_MEMBER("ubm could not be read", 0)
}
int PyBobLearnEMJFABase_setUBM(PyBobLearnEMJFABaseObject* self, PyObject* value, void*){
diff --git a/bob/learn/em/jfa_machine.cpp b/bob/learn/em/jfa_machine.cpp
index 2567a956beed58b1699ad6215cec92444d93343f..29f2a34cad34499db09f330907335baf53329383 100644
--- a/bob/learn/em/jfa_machine.cpp
+++ b/bob/learn/em/jfa_machine.cpp
@@ -271,7 +271,7 @@ PyObject* PyBobLearnEMJFAMachine_getJFABase(PyBobLearnEMJFAMachineObject* self,
(PyBobLearnEMJFABaseObject*)PyBobLearnEMJFABase_Type.tp_alloc(&PyBobLearnEMJFABase_Type, 0);
retval->cxx = jfa_base_o;
- return Py_BuildValue("O",retval);
+ return Py_BuildValue("N",retval);
BOB_CATCH_MEMBER("jfa_base could not be read", 0)
}
int PyBobLearnEMJFAMachine_setJFABase(PyBobLearnEMJFAMachineObject* self, PyObject* value, void*){
diff --git a/bob/learn/em/jfa_trainer.cpp b/bob/learn/em/jfa_trainer.cpp
index 5a1734c100ab4e13379523cb939e2014d7c576f4..f0a7a168811da767ef9f30aa31aeccb0045896f6 100644
--- a/bob/learn/em/jfa_trainer.cpp
+++ b/bob/learn/em/jfa_trainer.cpp
@@ -446,7 +446,7 @@ PyObject* PyBobLearnEMJFATrainer_getRng(PyBobLearnEMJFATrainerObject* self, void
(PyBoostMt19937Object*)PyBoostMt19937_Type.tp_alloc(&PyBoostMt19937_Type, 0);
retval->rng = self->cxx->getRng().get();
- return Py_BuildValue("O", retval);
+ return Py_BuildValue("N", retval);
BOB_CATCH_MEMBER("Rng method could not be read", 0)
}
int PyBobLearnEMJFATrainer_setRng(PyBobLearnEMJFATrainerObject* self, PyObject* value, void*) {
diff --git a/bob/learn/em/kmeans_trainer.cpp b/bob/learn/em/kmeans_trainer.cpp
index 92da9c1a096bab332d68bb06163ecaab6a24d04b..ffe7629af0208a7aaca5c9ea7ecd7dcb0886e550 100644
--- a/bob/learn/em/kmeans_trainer.cpp
+++ b/bob/learn/em/kmeans_trainer.cpp
@@ -281,7 +281,7 @@ PyObject* PyBobLearnEMKMeansTrainer_getRng(PyBobLearnEMKMeansTrainerObject* self
(PyBoostMt19937Object*)PyBoostMt19937_Type.tp_alloc(&PyBoostMt19937_Type, 0);
retval->rng = self->cxx->getRng().get();
- return Py_BuildValue("O", retval);
+ return Py_BuildValue("N", retval);
BOB_CATCH_MEMBER("Rng method could not be read", 0)
}
int PyBobLearnEMKMeansTrainer_setRng(PyBobLearnEMKMeansTrainerObject* self, PyObject* value, void*) {
diff --git a/bob/learn/em/plda_machine.cpp b/bob/learn/em/plda_machine.cpp
index 79859c2a7af9caf45fc1796d4c27450b05304756..6f73f4dc4fdef37d73d1fefbd0a4c638738da162 100644
--- a/bob/learn/em/plda_machine.cpp
+++ b/bob/learn/em/plda_machine.cpp
@@ -248,7 +248,7 @@ PyObject* PyBobLearnEMPLDAMachine_getPLDABase(PyBobLearnEMPLDAMachineObject* sel
(PyBobLearnEMPLDABaseObject*)PyBobLearnEMPLDABase_Type.tp_alloc(&PyBobLearnEMPLDABase_Type, 0);
retval->cxx = plda_base_o;
- return Py_BuildValue("O",retval);
+ return Py_BuildValue("N",retval);
BOB_CATCH_MEMBER("plda_base could not be read", 0)
}
int PyBobLearnEMPLDAMachine_setPLDABase(PyBobLearnEMPLDAMachineObject* self, PyObject* value, void*){
@@ -642,21 +642,28 @@ static PyObject* PyBobLearnEMPLDAMachine_computeLogLikelihood(PyBobLearnEMPLDAMa
BOB_TRY
char** kwlist = compute_log_likelihood.kwlist(0);
-
+
PyBlitzArrayObject* samples;
+ PyArrayObject* numpy_samples;
PyObject* with_enrolled_samples = Py_True;
+
+ /*Convert to PyObject first to access the number of dimensions*/
+ if (!PyArg_ParseTupleAndKeywords(args, kwargs, "O!|O!", kwlist, &PyArray_Type, &numpy_samples,
+ &PyBool_Type, &with_enrolled_samples)) return 0;
+ auto numpy_samples_ = make_safe(numpy_samples);
+ Py_INCREF(numpy_samples);
+ int dim = PyArray_NDIM(numpy_samples);
- if (!PyArg_ParseTupleAndKeywords(args, kwargs, "O&|O!", kwlist, &PyBlitzArray_Converter, &samples,
- &PyBool_Type, &with_enrolled_samples)) return 0;
+ /*Now converting to PyBlitzArrayObject*/
+ samples = reinterpret_cast<PyBlitzArrayObject*>(PyBlitzArray_FromNumpyArray(numpy_samples));
auto samples_ = make_safe(samples);
-
- blitz::Array<double,2> blitz_test = *PyBlitzArrayCxx_AsBlitz<double,2>(samples);
-
- //There are 2 methods in C++, one <double,1> and the another <double,2>
- if (blitz_test.extent(1)==0)
+
+ /*Using the proper method according to the dimension*/
+ if (dim==1)
return Py_BuildValue("d",self->cxx->computeLogLikelihood(*PyBlitzArrayCxx_AsBlitz<double,1>(samples), f(with_enrolled_samples)));
else
return Py_BuildValue("d",self->cxx->computeLogLikelihood(*PyBlitzArrayCxx_AsBlitz<double,2>(samples), f(with_enrolled_samples)));
+
BOB_CATCH_MEMBER("`compute_log_likelihood` could not be read", 0)
}
@@ -678,13 +685,20 @@ static PyObject* PyBobLearnEMPLDAMachine_forward(PyBobLearnEMPLDAMachineObject*
char** kwlist = forward.kwlist(0);
PyBlitzArrayObject* samples;
+ PyArrayObject* numpy_samples;
- if (!PyArg_ParseTupleAndKeywords(args, kwargs, "O&", kwlist, &PyBlitzArray_Converter, &samples)) return 0;
+ /*Convert to PyObject first to access the number of dimensions*/
+ if (!PyArg_ParseTupleAndKeywords(args, kwargs, "O!", kwlist, &PyArray_Type, &numpy_samples)) return 0;
+ auto numpy_samples_ = make_safe(numpy_samples);
+ Py_INCREF(numpy_samples);
+ int dim = PyArray_NDIM(numpy_samples);
+
+ /*Now converting to PyBlitzArrayObject*/
+ samples = reinterpret_cast<PyBlitzArrayObject*>(PyBlitzArray_FromNumpyArray(numpy_samples));
auto samples_ = make_safe(samples);
- blitz::Array<double,2> blitz_test = *PyBlitzArrayCxx_AsBlitz<double,2>(samples);
//There are 2 methods in C++, one <double,1> and the another <double,2>
- if (blitz_test.extent(1)==0)
+ if(dim==1)
return Py_BuildValue("d",self->cxx->forward(*PyBlitzArrayCxx_AsBlitz<double,1>(samples)));
else
return Py_BuildValue("d",self->cxx->forward(*PyBlitzArrayCxx_AsBlitz<double,2>(samples)));
diff --git a/bob/learn/em/test/test_plda.py b/bob/learn/em/test/test_plda.py
index 062857e6aa74ec9206fa72ac905c59773355ff57..6ea34cc64aff12181ad00dc3d38f2c3ed072727f 100644
--- a/bob/learn/em/test/test_plda.py
+++ b/bob/learn/em/test/test_plda.py
@@ -480,6 +480,10 @@ def test_plda_machine_log_likelihood_Python():
ar_s = numpy.vstack([ar_e, ar_p])
assert abs(m.compute_log_likelihood(ar_s, False) - compute_log_likelihood(ar_s, mu, C_F, C_G, sigma)) < 1e-10
ar_p2d = numpy.reshape(ar_p, (1,C_dim_d))
+
+ print ar_p.shape
+ a = m.compute_log_likelihood(ar_p, False)
+
assert abs(m.compute_log_likelihood(ar_p, False) - compute_log_likelihood(ar_p2d, mu, C_F, C_G, sigma)) < 1e-10
# Defines (random) samples and check forward method