From da50cddd22e8b651f40395bb696da8f20dcc90f6 Mon Sep 17 00:00:00 2001
From: Tiago Freitas Pereira <tiagofrepereira@gmail.com>
Date: Fri, 5 Dec 2014 22:57:02 +0800
Subject: [PATCH] Fixed some documentation issues and changed the bind of
operators. Now is more clean.
---
bob/learn/misc/gmm_stats.cpp | 138 +++++++++++++++--------------------
1 file changed, 58 insertions(+), 80 deletions(-)
diff --git a/bob/learn/misc/gmm_stats.cpp b/bob/learn/misc/gmm_stats.cpp
index 6409945..88e9419 100644
--- a/bob/learn/misc/gmm_stats.cpp
+++ b/bob/learn/misc/gmm_stats.cpp
@@ -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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