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Commit da50cddd authored by Tiago de Freitas Pereira's avatar Tiago de Freitas Pereira
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Fixed some documentation issues and changed the bind of operators. Now is more clean.

parent b6d15ad4
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bob/learn/misc/gmm_stats.cpp
+ 58
− 80
View file @ da50cddd
......@@ -33,18 +33,32 @@ static auto GMMStats_doc = bob::extension::ClassDoc(
.add_prototype("hdf5")
.add_prototype("")
//.add_parameter("mean", "array_like<double, 1D>", "Mean of the Gaussian")
.add_parameter("n_gaussians", "int", "Number of gaussians")
.add_parameter("n_inputs", "int", "Dimension of the feature vector")
.add_parameter("other", ":py:class:`bob.learn.misc.GMMStats`", "A GMMStats object to be copied.")
.add_parameter("hdf5", ":py:class:`bob.io.base.HDF5File`", "An HDF5 file open for reading")
);
static int PyBobLearnMiscGMMStats_init_number(PyBobLearnMiscGMMStatsObject* self, PyObject* args, PyObject* kwargs) {
char** kwlist = GMMStats_doc.kwlist(0);
size_t n_inputs=1;
size_t n_gaussians=1;
int n_inputs = 1;
int n_gaussians = 1;
//Parsing the input argments
if (!PyArg_ParseTupleAndKeywords(args, kwargs, "II", kwlist, &n_gaussians, &n_inputs))
if (!PyArg_ParseTupleAndKeywords(args, kwargs, "ii", kwlist, &n_gaussians, &n_inputs))
return -1;
if(n_gaussians < 0){
PyErr_Format(PyExc_TypeError, "gaussians argument must be greater than or equal to zero");
return -1;
}
if(n_inputs < 0){
PyErr_Format(PyExc_TypeError, "input argument must be greater than or equal to zero");
return -1;
}
self->cxx.reset(new bob::learn::misc::GMMStats(n_gaussians, n_inputs));
return 0;
......@@ -55,7 +69,7 @@ static int PyBobLearnMiscGMMStats_init_copy(PyBobLearnMiscGMMStatsObject* self,
char** kwlist = GMMStats_doc.kwlist(1);
PyBobLearnMiscGMMStatsObject* tt;
if (!PyArg_ParseTupleAndKeywords(args, kwargs, "O&", kwlist, &PyBobLearnMiscGMMStats_Type, &tt)) return -1;
if (!PyArg_ParseTupleAndKeywords(args, kwargs, "O!", kwlist, &PyBobLearnMiscGMMStats_Type, &tt)) return -1;
self->cxx.reset(new bob::learn::misc::GMMStats(*tt->cxx));
return 0;
......@@ -67,7 +81,7 @@ static int PyBobLearnMiscGMMStats_init_hdf5(PyBobLearnMiscGMMStatsObject* self,
char** kwlist = GMMStats_doc.kwlist(2);
PyBobIoHDF5FileObject* config = 0;
if (!PyArg_ParseTupleAndKeywords(args, kwargs, "O&", kwlist, &PyBobIoHDF5File_Converter, &config))
if (!PyArg_ParseTupleAndKeywords(args, kwargs, "O&", kwlist, &PyBobIoHDF5File_Converter, &config))
return -1;
try {
......@@ -99,7 +113,6 @@ static int PyBobLearnMiscGMMStats_init(PyBobLearnMiscGMMStatsObject* self, PyObj
self->cxx.reset(new bob::learn::misc::GMMStats());
case 1:{
//Reading the input argument
PyObject* arg = 0;
if (PyTuple_Size(args))
......@@ -115,7 +128,7 @@ static int PyBobLearnMiscGMMStats_init(PyBobLearnMiscGMMStatsObject* self, PyObj
return PyBobLearnMiscGMMStats_init_copy(self, args, kwargs);
/**If the constructor input is a HDF5**/
else if (PyBobIoHDF5File_Check(arg))
return PyBobLearnMiscGMMStats_init_hdf5(self, args, kwargs);
return PyBobLearnMiscGMMStats_init_hdf5(self, args, kwargs);
}
case 2:
return PyBobLearnMiscGMMStats_init_number(self, args, kwargs);
......@@ -166,8 +179,9 @@ int PyBobLearnMiscGMMStats_Check(PyObject* o) {
/***** n *****/
static auto n = bob::extension::VariableDoc(
"n",
"array_like <double, 1D>",
"For each Gaussian, the accumulated sum of responsibilities, i.e. the sum of P(gaussian_i|x)"
"array_like <double, 1D> "
"For each Gaussian, the accumulated sum of responsibilities, i.e. the sum of P(gaussian_i|x)",
""
);
PyObject* PyBobLearnMiscGMMStats_getN(PyBobLearnMiscGMMStatsObject* self, void*){
BOB_TRY
......@@ -193,8 +207,9 @@ int PyBobLearnMiscGMMStats_setN(PyBobLearnMiscGMMStatsObject* self, PyObject* va
/***** sum_px *****/
static auto sum_px = bob::extension::VariableDoc(
"sum_px",
"array_like <double, 2D>",
"For each Gaussian, the accumulated sum of responsibility times the sample"
"array_like <double, 2D> "
"For each Gaussian, the accumulated sum of responsibility times the sample",
""
);
PyObject* PyBobLearnMiscGMMStats_getSum_px(PyBobLearnMiscGMMStatsObject* self, void*){
BOB_TRY
......@@ -220,8 +235,9 @@ int PyBobLearnMiscGMMStats_setSum_px(PyBobLearnMiscGMMStatsObject* self, PyObjec
/***** sum_pxx *****/
static auto sum_pxx = bob::extension::VariableDoc(
"sum_pxx",
"array_like <double, 2D>",
"For each Gaussian, the accumulated sum of responsibility times the sample squared"
"array_like <double, 2D> "
"For each Gaussian, the accumulated sum of responsibility times the sample squared",
""
);
PyObject* PyBobLearnMiscGMMStats_getSum_pxx(PyBobLearnMiscGMMStatsObject* self, void*){
BOB_TRY
......@@ -247,8 +263,9 @@ int PyBobLearnMiscGMMStats_setSum_pxx(PyBobLearnMiscGMMStatsObject* self, PyObje
/***** t *****/
static auto t = bob::extension::VariableDoc(
"t",
"size_t",
"The accumulated log likelihood of all samples"
"int "
"The accumulated log likelihood of all samples",
""
);
PyObject* PyBobLearnMiscGMMStats_getT(PyBobLearnMiscGMMStatsObject* self, void*){
BOB_TRY
......@@ -277,8 +294,9 @@ int PyBobLearnMiscGMMStats_setT(PyBobLearnMiscGMMStatsObject* self, PyObject* va
/***** log_likelihood *****/
static auto log_likelihood = bob::extension::VariableDoc(
"log_likelihood",
"double",
"The accumulated log likelihood of all samples"
"double "
"The accumulated log likelihood of all samples",
""
);
PyObject* PyBobLearnMiscGMMStats_getLog_likelihood(PyBobLearnMiscGMMStatsObject* self, void*){
BOB_TRY
......@@ -387,7 +405,9 @@ static auto load = bob::extension::FunctionDoc(
" Load the configuration of the GMMStats to a given HDF5 file",
0,
true
);
)
.add_prototype("hdf5")
.add_parameter("hdf5", ":py:class:`bob.io.base.HDF5File`", "An HDF5 file open for reading");
static PyObject* PyBobLearnMiscGMMStats_Load(PyBobLearnMiscGMMStatsObject* self, PyObject* f) {
if (!PyBobIoHDF5File_Check(f)) {
......@@ -425,7 +445,7 @@ static auto is_similar_to = bob::extension::FunctionDoc(
true
)
.add_prototype("other, [r_epsilon], [a_epsilon]","bool")
.add_parameter("other", ":py:class:`bob.learn.misc.GMMStats`", "A gaussian to be compared.")
.add_parameter("other", ":py:class:`bob.learn.misc.GMMStats`", "A GMMStats object to be compared.")
.add_parameter("[r_epsilon]", "float", "Relative precision.")
.add_parameter("[a_epsilon]", "float", "Absolute precision.")
.add_return("bool","","");
......@@ -454,21 +474,22 @@ static PyObject* PyBobLearnMiscGMMStats_IsSimilarTo(PyBobLearnMiscGMMStatsObject
/*** resize ***/
static auto resize = bob::extension::FunctionDoc(
"resize",
"(size_t,size_t)"
" Allocates space for the statistics and resets to zero."
" Allocates space for the statistics and resets to zero.",
""
)
.add_prototype("n_gaussians,n_inputs")
.add_parameter("n_gaussians,n_inputs", "(size_t, size_t)", "Tuple with the new shape");
.add_prototype("n_gaussians,n_inputs","")
.add_parameter("n_gaussians", "int", "Number of gaussians")
.add_parameter("n_inputs", "int", "Dimensionality of the feature vector");
static PyObject* PyBobLearnMiscGMMStats_resize(PyBobLearnMiscGMMStatsObject* self, PyObject* args, PyObject* kwargs) {
BOB_TRY
/* Parses input arguments in a single shot */
char** kwlist = resize.kwlist(0);
Py_ssize_t n_gaussians = 0;
Py_ssize_t n_inputs = 0;
int n_gaussians = 0;
int n_inputs = 0;
if (!PyArg_ParseTupleAndKeywords(args, kwargs, "nn", kwlist, &n_gaussians, &n_inputs)) Py_RETURN_NONE;
if (!PyArg_ParseTupleAndKeywords(args, kwargs, "ii", kwlist, &n_gaussians, &n_inputs)) Py_RETURN_NONE;
self->cxx->resize(n_gaussians, n_inputs);
BOB_CATCH_MEMBER("cannot perform the resize method", 0)
......@@ -480,9 +501,10 @@ static PyObject* PyBobLearnMiscGMMStats_resize(PyBobLearnMiscGMMStatsObject* sel
/*** init ***/
static auto init = bob::extension::FunctionDoc(
"init",
" Resets statistics to zero.",
""
" Resets statistics to zero."
);
)
.add_prototype("","");
static PyObject* PyBobLearnMiscGMMStats_init_method(PyBobLearnMiscGMMStatsObject* self) {
BOB_TRY
......@@ -505,7 +527,7 @@ static PyMethodDef PyBobLearnMiscGMMStats_methods[] = {
{
load.name(),
(PyCFunction)PyBobLearnMiscGMMStats_Load,
METH_VARARGS|METH_KEYWORDS,
METH_O,
load.doc()
},
{
......@@ -523,7 +545,7 @@ static PyMethodDef PyBobLearnMiscGMMStats_methods[] = {
{
init.name(),
(PyCFunction)PyBobLearnMiscGMMStats_init_method,
METH_VARARGS|METH_KEYWORDS,
METH_NOARGS,
init.doc()
},
......@@ -554,54 +576,7 @@ static PyObject* PyBobLearnMiscGMMStats_inplaceadd(PyObject* self, PyObject* oth
return self;
}
static PyNumberMethods PyBobLearnMiscGMMStats_operators[] = {{
0, // nb_add;
0, // nb_subtract;
0, // nb_multiply;
0, // nb_divide;
0, // nb_remainder;
0, // nb_divmod;
0, // nb_power;
0, // nb_negative;
0, // nb_positive;
0, // nb_absolute;
0, // nb_nonzero; /* Used by PyObject_IsTrue */
0, // nb_invert;
0, // nb_lshift;
0, // nb_rshift;
0, // nb_and;
0, // nb_xor;
0, // nb_or;
0, // nb_coerce; /* Used by the coerce() function */
0, // nb_int;
0, // nb_long;
0, // nb_float;
0, // nb_oct;
0, // nb_hex;
/* Added in release 2.0 */
PyBobLearnMiscGMMStats_inplaceadd, // nb_inplace_add;
0, // nb_inplace_subtract;
0, // nb_inplace_multiply;
0, // nb_inplace_divide;
0, // nb_inplace_remainder;
0, // nb_inplace_power;
0, // nb_inplace_lshift;
0, // nb_inplace_rshift;
0, // nb_inplace_and;
0, // nb_inplace_xor;
0, // nb_inplace_or;
/* Added in release 2.2 */
0, // nb_floor_divide;
0, // nb_true_divide;
0, // nb_inplace_floor_divide;
0, // nb_inplace_true_divide;
/* Added in release 2.5 */
0, // nb_index
}};
static PyNumberMethods PyBobLearnMiscGMMStats_operators = {0};
/******************************************************************/
/************ Module Section **************************************/
......@@ -629,7 +604,10 @@ bool init_BobLearnMiscGMMStats(PyObject* module)
PyBobLearnMiscGMMStats_Type.tp_methods = PyBobLearnMiscGMMStats_methods;
PyBobLearnMiscGMMStats_Type.tp_getset = PyBobLearnMiscGMMStats_getseters;
//PyBobLearnMiscGMMStats_Type.tp_call = reinterpret_cast<ternaryfunc>(PyBobLearnMiscGMMStats_loglikelihood);
PyBobLearnMiscGMMStats_Type.tp_as_number = PyBobLearnMiscGMMStats_operators;
PyBobLearnMiscGMMStats_Type.tp_as_number = &PyBobLearnMiscGMMStats_operators;
//set operators
PyBobLearnMiscGMMStats_operators.nb_inplace_add = PyBobLearnMiscGMMStats_inplaceadd;
// check that everything is fine
if (PyType_Ready(&PyBobLearnMiscGMMStats_Type) < 0) return false;
......
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