From 13418b86eee30c2fa5c6ee0f325056b803171330 Mon Sep 17 00:00:00 2001
From: Fabian Pedregosa <fabian.pedregosa@inria.fr>
Date: Tue, 20 Apr 2010 09:02:25 +0000
Subject: [PATCH] Preliminary support for probability estimate in SVM.
Added method prob_predict() that does probability estimates. It's only
tested for SVC (classification), so it's untested for SVR/OneClass.
To be able to do probability estimates, you have to specify parameter
probability=True (now on by default). Turning off this parameter might
speed up calculations, althougth I did not notice any significant
difference.
git-svn-id: https://scikit-learn.svn.sourceforge.net/svnroot/scikit-learn/trunk@658 22fbfee3-77ab-4535-9bad-27d1bd3bc7d8
---
scikits/learn/benchmarks/bench_svm.py | 4 +-
scikits/learn/src/libsvm.c | 1050 ++++++++++++++++---------
scikits/learn/src/libsvm.pyx | 34 +-
scikits/learn/src/libsvm_helper.c | 30 +-
scikits/learn/svm.py | 21 +-
scikits/learn/tests/test_svm.py | 4 +-
6 files changed, 739 insertions(+), 404 deletions(-)
diff --git a/scikits/learn/benchmarks/bench_svm.py b/scikits/learn/benchmarks/bench_svm.py
index 6c966e57da..638badf705 100644
--- a/scikits/learn/benchmarks/bench_svm.py
+++ b/scikits/learn/benchmarks/bench_svm.py
@@ -93,8 +93,8 @@ def bench_pymvpa(X, Y, T):
if __name__ == '__main__':
- from scikits.learn.datasets import load
- iris = load('iris')
+ from scikits.learn.datasets import load_iris
+ iris = load_iris()
X = iris.data
Y = iris.target
diff --git a/scikits/learn/src/libsvm.c b/scikits/learn/src/libsvm.c
index 8dff8c5c70..cf738fa994 100644
--- a/scikits/learn/src/libsvm.c
+++ b/scikits/learn/src/libsvm.c
@@ -1,4 +1,4 @@
-/* Generated by Cython 0.12 on Mon Apr 19 16:22:05 2010 */
+/* Generated by Cython 0.12 on Tue Apr 20 10:48:01 2010 */
#define PY_SSIZE_T_CLEAN
#include "Python.h"
@@ -657,10 +657,10 @@ static char __pyx_k_6[] = "unknown dtype code in numpy.pxd (%d)";
static char __pyx_k_7[] = "Format string allocated too short, see comment in numpy.pxd";
static char __pyx_k_8[] = "Format string allocated too short.";
static char __pyx_k_9[] = "\nBinding for libsvm[1]\n---------------------\nWe do not use the binding that ships with libsvm because we need to\naccess svm_model.sv_coeff (and other fields), but libsvm does not\nprovide an accessor. Our solution is to export svm_model and access it\nmanually, this is done un function see svm_train_wrap.\n\nlibsvm uses an sparse representation for the training vectors. In\nmethod dense_to_sparse we translate a dense matrix representation as\nthose produced by NumPy to a sparse representation that libsvm can\nunderstand.\n\nWe define arrays to be the same type as those in libsvm, usually of \ntype C double and C int.\n\nLow-level memory management is done in libsvm_helper.c. If we happen\nto run out of memory a MemoryError will be raised. In practice this is\nnot very helpful since hight changes are malloc fails inside svm.cpp,\nwhere no sort of memory checks are done.\n\nThese are low-level routines, not meant to be used directly. See\nscikits.learn.svm for a higher-level API.\n\n[1] http://www.csie.ntu.edu.tw/~cjlin/libsvm/\n\nNotes\n-----\nMaybe we could speed it a bit further by decorating functions with\n@cython.boundscheck(False), but probably it is not worth since all\nwork is done in lisvm_helper.c\nAlso, the signature mode='c' is somewhat superficial, since we already\ncheck that arrays are C-contiguous in svm.py\n\nAuthors\n-------\n2010: Fabian Pedregosa <fabian.pedregosa@inria.fr>\n Gael Varoquaux <gael.varoquaux@normalesup.org>\n";
-static char __pyx_k_10[] = "train_wrap (line 83)";
-static char __pyx_k_11[] = "predict_from_model_wrap (line 178)";
+static char __pyx_k_10[] = "train_wrap (line 85)";
+static char __pyx_k_11[] = "predict_from_model_wrap (line 191)";
static char __pyx_k_12[] = "predict_from_model_wrap";
-static char __pyx_k_13[] = "predict_prob_from_model_wrap (line 237)";
+static char __pyx_k_13[] = "predict_prob_from_model_wrap (line 252)";
static char __pyx_k_14[] = "predict_prob_from_model_wrap";
static char __pyx_k__B[] = "B";
static char __pyx_k__C[] = "C";
@@ -704,6 +704,8 @@ static char __pyx_k__gamma[] = "gamma";
static char __pyx_k__label[] = "label";
static char __pyx_k__names[] = "names";
static char __pyx_k__numpy[] = "numpy";
+static char __pyx_k__probA[] = "probA";
+static char __pyx_k__probB[] = "probB";
static char __pyx_k__range[] = "range";
static char __pyx_k__shape[] = "shape";
static char __pyx_k__zeros[] = "zeros";
@@ -711,6 +713,7 @@ static char __pyx_k__degree[] = "degree";
static char __pyx_k__fields[] = "fields";
static char __pyx_k__format[] = "format";
static char __pyx_k__weight[] = "weight";
+static char __pyx_k__float64[] = "float64";
static char __pyx_k__strides[] = "strides";
static char __pyx_k__sv_coef[] = "sv_coef";
static char __pyx_k____main__[] = "__main__";
@@ -767,6 +770,7 @@ static PyObject *__pyx_n_s__dtype;
static PyObject *__pyx_n_s__empty;
static PyObject *__pyx_n_s__eps;
static PyObject *__pyx_n_s__fields;
+static PyObject *__pyx_n_s__float64;
static PyObject *__pyx_n_s__format;
static PyObject *__pyx_n_s__gamma;
static PyObject *__pyx_n_s__int;
@@ -783,6 +787,8 @@ static PyObject *__pyx_n_s__nu;
static PyObject *__pyx_n_s__numpy;
static PyObject *__pyx_n_s__obj;
static PyObject *__pyx_n_s__p;
+static PyObject *__pyx_n_s__probA;
+static PyObject *__pyx_n_s__probB;
static PyObject *__pyx_n_s__probability;
static PyObject *__pyx_n_s__range;
static PyObject *__pyx_n_s__readonly;
@@ -800,7 +806,7 @@ static PyObject *__pyx_n_s__weight_label;
static PyObject *__pyx_n_s__zeros;
static PyObject *__pyx_int_15;
-/* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":83
+/* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":85
* # Wrapper functions
*
* def train_wrap ( np.ndarray[np.float64_t, ndim=2, mode='c'] X, # <<<<<<<<<<<<<<
@@ -839,12 +845,20 @@ static PyObject *__pyx_pf_6libsvm_train_wrap(PyObject *__pyx_self, PyObject *__p
PyArrayObject *__pyx_v_SV;
PyArrayObject *__pyx_v_nclass_SV;
PyArrayObject *__pyx_v_label;
+ PyArrayObject *__pyx_v_probA;
+ PyArrayObject *__pyx_v_probB;
Py_buffer __pyx_bstruct_weight;
Py_ssize_t __pyx_bstride_0_weight = 0;
Py_ssize_t __pyx_bshape_0_weight = 0;
Py_buffer __pyx_bstruct_weight_label;
Py_ssize_t __pyx_bstride_0_weight_label = 0;
Py_ssize_t __pyx_bshape_0_weight_label = 0;
+ Py_buffer __pyx_bstruct_probA;
+ Py_ssize_t __pyx_bstride_0_probA = 0;
+ Py_ssize_t __pyx_bshape_0_probA = 0;
+ Py_buffer __pyx_bstruct_probB;
+ Py_ssize_t __pyx_bstride_0_probB = 0;
+ Py_ssize_t __pyx_bshape_0_probB = 0;
Py_buffer __pyx_bstruct_label;
Py_ssize_t __pyx_bstride_0_label = 0;
Py_ssize_t __pyx_bshape_0_label = 0;
@@ -890,6 +904,8 @@ static PyObject *__pyx_pf_6libsvm_train_wrap(PyObject *__pyx_self, PyObject *__p
PyObject *__pyx_t_15 = NULL;
PyArrayObject *__pyx_t_16 = NULL;
PyArrayObject *__pyx_t_17 = NULL;
+ PyArrayObject *__pyx_t_18 = NULL;
+ PyArrayObject *__pyx_t_19 = NULL;
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__X,&__pyx_n_s__Y,&__pyx_n_s__svm_type,&__pyx_n_s__kernel_type,&__pyx_n_s__degree,&__pyx_n_s__gamma,&__pyx_n_s__coef0,&__pyx_n_s__eps,&__pyx_n_s__C,&__pyx_n_s__nr_weight,&__pyx_n_s__weight_label,&__pyx_n_s__weight,&__pyx_n_s__nu,&__pyx_n_s__cache_size,&__pyx_n_s__p,&__pyx_n_s__shrinking,&__pyx_n_s__probability,0};
__Pyx_RefNannySetupContext("train_wrap");
__pyx_self = __pyx_self;
@@ -926,143 +942,143 @@ static PyObject *__pyx_pf_6libsvm_train_wrap(PyObject *__pyx_self, PyObject *__p
values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__Y);
if (likely(values[1])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 85; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 2:
values[2] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__svm_type);
if (likely(values[2])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 85; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 3:
values[3] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__kernel_type);
if (likely(values[3])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 3); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 3); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 85; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 4:
values[4] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__degree);
if (likely(values[4])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 4); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 4); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 85; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 5:
values[5] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__gamma);
if (likely(values[5])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 5); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 5); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 85; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 6:
values[6] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__coef0);
if (likely(values[6])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 6); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 6); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 85; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 7:
values[7] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__eps);
if (likely(values[7])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 7); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 7); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 85; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 8:
values[8] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__C);
if (likely(values[8])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 8); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 8); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 85; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 9:
values[9] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__nr_weight);
if (likely(values[9])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 9); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 9); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 85; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 10:
values[10] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__weight_label);
if (likely(values[10])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 10); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 10); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 85; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 11:
values[11] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__weight);
if (likely(values[11])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 11); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 11); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 85; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 12:
values[12] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__nu);
if (likely(values[12])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 12); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 12); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 85; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 13:
values[13] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__cache_size);
if (likely(values[13])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 13); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 13); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 85; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 14:
values[14] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__p);
if (likely(values[14])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 14); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 14); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 85; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 15:
values[15] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__shrinking);
if (likely(values[15])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 15); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 15); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 85; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 16:
values[16] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__probability);
if (likely(values[16])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 16); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, 16); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 85; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
}
if (unlikely(kw_args > 0)) {
- if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "train_wrap") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "train_wrap") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 85; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
__pyx_v_X = ((PyArrayObject *)values[0]);
__pyx_v_Y = ((PyArrayObject *)values[1]);
- __pyx_v_svm_type = __Pyx_PyInt_AsInt(values[2]); if (unlikely((__pyx_v_svm_type == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 84; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_kernel_type = __Pyx_PyInt_AsInt(values[3]); if (unlikely((__pyx_v_kernel_type == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 85; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_degree = __Pyx_PyInt_AsInt(values[4]); if (unlikely((__pyx_v_degree == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 85; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_gamma = __pyx_PyFloat_AsDouble(values[5]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 85; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_coef0 = __pyx_PyFloat_AsDouble(values[6]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 86; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_eps = __pyx_PyFloat_AsDouble(values[7]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 86; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_C = __pyx_PyFloat_AsDouble(values[8]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 86; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_nr_weight = __Pyx_PyInt_AsInt(values[9]); if (unlikely((__pyx_v_nr_weight == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 86; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_svm_type = __Pyx_PyInt_AsInt(values[2]); if (unlikely((__pyx_v_svm_type == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 86; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_kernel_type = __Pyx_PyInt_AsInt(values[3]); if (unlikely((__pyx_v_kernel_type == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 87; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_degree = __Pyx_PyInt_AsInt(values[4]); if (unlikely((__pyx_v_degree == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 87; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_gamma = __pyx_PyFloat_AsDouble(values[5]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 87; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_coef0 = __pyx_PyFloat_AsDouble(values[6]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 88; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_eps = __pyx_PyFloat_AsDouble(values[7]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 88; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_C = __pyx_PyFloat_AsDouble(values[8]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 88; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_nr_weight = __Pyx_PyInt_AsInt(values[9]); if (unlikely((__pyx_v_nr_weight == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 88; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_weight_label = ((PyArrayObject *)values[10]);
__pyx_v_weight = ((PyArrayObject *)values[11]);
- __pyx_v_nu = __pyx_PyFloat_AsDouble(values[12]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 88; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_cache_size = __pyx_PyFloat_AsDouble(values[13]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 89; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_p = __pyx_PyFloat_AsDouble(values[14]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 89; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_shrinking = __Pyx_PyInt_AsInt(values[15]); if (unlikely((__pyx_v_shrinking == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 89; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_probability = __Pyx_PyInt_AsInt(values[16]); if (unlikely((__pyx_v_probability == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 89; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_nu = __pyx_PyFloat_AsDouble(values[12]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 90; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_cache_size = __pyx_PyFloat_AsDouble(values[13]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 91; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_p = __pyx_PyFloat_AsDouble(values[14]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 91; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_shrinking = __Pyx_PyInt_AsInt(values[15]); if (unlikely((__pyx_v_shrinking == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 91; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_probability = __Pyx_PyInt_AsInt(values[16]); if (unlikely((__pyx_v_probability == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 91; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
} else if (PyTuple_GET_SIZE(__pyx_args) != 17) {
goto __pyx_L5_argtuple_error;
} else {
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__pyx_v_Y = ((PyArrayObject *)PyTuple_GET_ITEM(__pyx_args, 1));
- __pyx_v_svm_type = __Pyx_PyInt_AsInt(PyTuple_GET_ITEM(__pyx_args, 2)); if (unlikely((__pyx_v_svm_type == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 84; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_kernel_type = __Pyx_PyInt_AsInt(PyTuple_GET_ITEM(__pyx_args, 3)); if (unlikely((__pyx_v_kernel_type == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 85; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_degree = __Pyx_PyInt_AsInt(PyTuple_GET_ITEM(__pyx_args, 4)); if (unlikely((__pyx_v_degree == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 85; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_gamma = __pyx_PyFloat_AsDouble(PyTuple_GET_ITEM(__pyx_args, 5)); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 85; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_coef0 = __pyx_PyFloat_AsDouble(PyTuple_GET_ITEM(__pyx_args, 6)); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 86; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_eps = __pyx_PyFloat_AsDouble(PyTuple_GET_ITEM(__pyx_args, 7)); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 86; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_C = __pyx_PyFloat_AsDouble(PyTuple_GET_ITEM(__pyx_args, 8)); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 86; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_nr_weight = __Pyx_PyInt_AsInt(PyTuple_GET_ITEM(__pyx_args, 9)); if (unlikely((__pyx_v_nr_weight == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 86; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_svm_type = __Pyx_PyInt_AsInt(PyTuple_GET_ITEM(__pyx_args, 2)); if (unlikely((__pyx_v_svm_type == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 86; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_kernel_type = __Pyx_PyInt_AsInt(PyTuple_GET_ITEM(__pyx_args, 3)); if (unlikely((__pyx_v_kernel_type == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 87; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_degree = __Pyx_PyInt_AsInt(PyTuple_GET_ITEM(__pyx_args, 4)); if (unlikely((__pyx_v_degree == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 87; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_gamma = __pyx_PyFloat_AsDouble(PyTuple_GET_ITEM(__pyx_args, 5)); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 87; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
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+ __pyx_v_eps = __pyx_PyFloat_AsDouble(PyTuple_GET_ITEM(__pyx_args, 7)); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 88; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_C = __pyx_PyFloat_AsDouble(PyTuple_GET_ITEM(__pyx_args, 8)); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 88; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_nr_weight = __Pyx_PyInt_AsInt(PyTuple_GET_ITEM(__pyx_args, 9)); if (unlikely((__pyx_v_nr_weight == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 88; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_weight_label = ((PyArrayObject *)PyTuple_GET_ITEM(__pyx_args, 10));
__pyx_v_weight = ((PyArrayObject *)PyTuple_GET_ITEM(__pyx_args, 11));
- __pyx_v_nu = __pyx_PyFloat_AsDouble(PyTuple_GET_ITEM(__pyx_args, 12)); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 88; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_cache_size = __pyx_PyFloat_AsDouble(PyTuple_GET_ITEM(__pyx_args, 13)); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 89; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_p = __pyx_PyFloat_AsDouble(PyTuple_GET_ITEM(__pyx_args, 14)); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 89; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
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+ __pyx_v_nu = __pyx_PyFloat_AsDouble(PyTuple_GET_ITEM(__pyx_args, 12)); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 90; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
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__pyx_L5_argtuple_error:;
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+ __Pyx_RaiseArgtupleInvalid("train_wrap", 1, 17, 17, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 85; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("libsvm.train_wrap");
return NULL;
@@ -1076,45 +1092,49 @@ static PyObject *__pyx_pf_6libsvm_train_wrap(PyObject *__pyx_self, PyObject *__p
__pyx_v_SV = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None);
__pyx_v_nclass_SV = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None);
__pyx_v_label = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None);
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__pyx_bstruct_rho.buf = NULL;
__pyx_bstruct_SV.buf = NULL;
__pyx_bstruct_nclass_SV.buf = NULL;
__pyx_bstruct_label.buf = NULL;
+ __pyx_bstruct_probA.buf = NULL;
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__pyx_bstruct_X.buf = NULL;
__pyx_bstruct_Y.buf = NULL;
__pyx_bstruct_weight_label.buf = NULL;
__pyx_bstruct_weight.buf = NULL;
- if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_X), __pyx_ptype_5numpy_ndarray, 1, "X", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
- if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_Y), __pyx_ptype_5numpy_ndarray, 1, "Y", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 84; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+ if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_weight), __pyx_ptype_5numpy_ndarray, 1, "weight", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 90; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
{
__Pyx_BufFmt_StackElem __pyx_stack[1];
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__pyx_bstride_0_X = __pyx_bstruct_X.strides[0]; __pyx_bstride_1_X = __pyx_bstruct_X.strides[1];
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{
__Pyx_BufFmt_StackElem __pyx_stack[1];
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{
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}
__pyx_bstride_0_weight_label = __pyx_bstruct_weight_label.strides[0];
__pyx_bshape_0_weight_label = __pyx_bstruct_weight_label.shape[0];
{
__Pyx_BufFmt_StackElem __pyx_stack[1];
- if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_weight, (PyObject*)__pyx_v_weight, &__Pyx_TypeInfo_nn___pyx_t_5numpy_float64_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_weight, (PyObject*)__pyx_v_weight, &__Pyx_TypeInfo_nn___pyx_t_5numpy_float64_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 85; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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__pyx_bshape_0_weight = __pyx_bstruct_weight.shape[0];
- /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":122
+ /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":124
*
* # set libsvm problem
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@@ -1123,7 +1143,7 @@ static PyObject *__pyx_pf_6libsvm_train_wrap(PyObject *__pyx_self, PyObject *__p
*/
__pyx_v_problem = set_problem(__pyx_v_X->data, __pyx_v_Y->data, __pyx_v_X->dimensions);
- /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":128
+ /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":130
* coef0, nu, cache_size,
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*/
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- /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":131
+ /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":133
*
* # check parameters
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@@ -1148,29 +1168,29 @@ static PyObject *__pyx_pf_6libsvm_train_wrap(PyObject *__pyx_self, PyObject *__p
}
if (__pyx_t_3) {
- /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":132
+ /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":134
* # check parameters
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*/
- __pyx_t_4 = PyTuple_New(1); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 132; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __pyx_t_4 = PyTuple_New(1); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 134; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
__Pyx_INCREF(((PyObject *)__pyx_kp_s_1));
PyTuple_SET_ITEM(__pyx_t_4, 0, ((PyObject *)__pyx_kp_s_1));
__Pyx_GIVEREF(((PyObject *)__pyx_kp_s_1));
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+ __pyx_t_5 = PyObject_Call(__pyx_builtin_MemoryError, __pyx_t_4, NULL); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 134; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_5);
__Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0;
__Pyx_Raise(__pyx_t_5, 0, 0);
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
- {__pyx_filename = __pyx_f[0]; __pyx_lineno = 132; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ {__pyx_filename = __pyx_f[0]; __pyx_lineno = 134; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
goto __pyx_L6;
}
__pyx_L6:;
- /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":133
+ /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":135
* if (param == NULL or problem == NULL):
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@@ -1179,7 +1199,7 @@ static PyObject *__pyx_pf_6libsvm_train_wrap(PyObject *__pyx_self, PyObject *__p
*/
__pyx_v_error_msg = svm_check_parameter(__pyx_v_problem, __pyx_v_param);
- /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":134
+ /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":136
* raise MemoryError("Seems we've run out of of memory")
* error_msg = svm_check_parameter(problem, param);
* if error_msg: # <<<<<<<<<<<<<<
@@ -1189,7 +1209,7 @@ static PyObject *__pyx_pf_6libsvm_train_wrap(PyObject *__pyx_self, PyObject *__p
__pyx_t_3 = (__pyx_v_error_msg != 0);
if (__pyx_t_3) {
- /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":135
+ /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":137
* error_msg = svm_check_parameter(problem, param);
* if error_msg:
* free_problem(problem) # <<<<<<<<<<<<<<
@@ -1198,7 +1218,7 @@ static PyObject *__pyx_pf_6libsvm_train_wrap(PyObject *__pyx_self, PyObject *__p
*/
free_problem(__pyx_v_problem);
- /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":136
+ /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":138
* if error_msg:
* free_problem(problem)
* free_param(param) # <<<<<<<<<<<<<<
@@ -1207,31 +1227,31 @@ static PyObject *__pyx_pf_6libsvm_train_wrap(PyObject *__pyx_self, PyObject *__p
*/
free_param(__pyx_v_param);
- /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":137
+ /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":139
* free_problem(problem)
* free_param(param)
* raise ValueError(error_msg) # <<<<<<<<<<<<<<
*
* # call svm_train, this does the real work
*/
- __pyx_t_5 = __Pyx_PyBytes_FromString(__pyx_v_error_msg); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 137; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __pyx_t_5 = __Pyx_PyBytes_FromString(__pyx_v_error_msg); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 139; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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- __pyx_t_4 = PyTuple_New(1); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 137; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __pyx_t_4 = PyTuple_New(1); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 139; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_5);
__Pyx_GIVEREF(__pyx_t_5);
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+ __pyx_t_5 = PyObject_Call(__pyx_builtin_ValueError, __pyx_t_4, NULL); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 139; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_5);
__Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0;
__Pyx_Raise(__pyx_t_5, 0, 0);
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
- {__pyx_filename = __pyx_f[0]; __pyx_lineno = 137; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ {__pyx_filename = __pyx_f[0]; __pyx_lineno = 139; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
goto __pyx_L7;
}
__pyx_L7:;
- /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":140
+ /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":142
*
* # call svm_train, this does the real work
* model = svm_train(problem, param) # <<<<<<<<<<<<<<
@@ -1240,7 +1260,7 @@ static PyObject *__pyx_pf_6libsvm_train_wrap(PyObject *__pyx_self, PyObject *__p
*/
__pyx_v_model = svm_train(__pyx_v_problem, __pyx_v_param);
- /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":142
+ /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":144
* model = svm_train(problem, param)
*
* cdef int nSV = get_l(model) # <<<<<<<<<<<<<<
@@ -1249,7 +1269,7 @@ static PyObject *__pyx_pf_6libsvm_train_wrap(PyObject *__pyx_self, PyObject *__p
*/
__pyx_v_nSV = get_l(__pyx_v_model);
- /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":143
+ /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":145
*
* cdef int nSV = get_l(model)
* cdef int nr = get_nr(model) # <<<<<<<<<<<<<<
@@ -1258,23 +1278,23 @@ static PyObject *__pyx_pf_6libsvm_train_wrap(PyObject *__pyx_self, PyObject *__p
*/
__pyx_v_nr = get_nr(__pyx_v_model);
- /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":147
+ /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":149
* # copy model.sv_coef
* cdef np.ndarray[np.float64_t, ndim=2, mode='c'] sv_coef
* sv_coef = np.empty((nr-1, nSV)) # <<<<<<<<<<<<<<
* copy_sv_coef(sv_coef.data, model, sv_coef.strides)
*
*/
- __pyx_t_5 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 147; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __pyx_t_5 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 149; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+ __pyx_t_4 = PyObject_GetAttr(__pyx_t_5, __pyx_n_s__empty); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 149; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
- __pyx_t_5 = PyInt_FromLong((__pyx_v_nr - 1)); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 147; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __pyx_t_5 = PyInt_FromLong((__pyx_v_nr - 1)); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 149; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_5);
- __pyx_t_6 = PyInt_FromLong(__pyx_v_nSV); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 147; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __pyx_t_6 = PyInt_FromLong(__pyx_v_nSV); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 149; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_6);
- __pyx_t_7 = PyTuple_New(2); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 147; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __pyx_t_7 = PyTuple_New(2); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 149; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_7);
PyTuple_SET_ITEM(__pyx_t_7, 0, __pyx_t_5);
__Pyx_GIVEREF(__pyx_t_5);
@@ -1282,16 +1302,16 @@ static PyObject *__pyx_pf_6libsvm_train_wrap(PyObject *__pyx_self, PyObject *__p
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__pyx_t_6 = 0;
- __pyx_t_6 = PyTuple_New(1); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 147; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __pyx_t_6 = PyTuple_New(1); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 149; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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PyTuple_SET_ITEM(__pyx_t_6, 0, __pyx_t_7);
__Pyx_GIVEREF(__pyx_t_7);
__pyx_t_7 = 0;
- __pyx_t_7 = PyObject_Call(__pyx_t_4, __pyx_t_6, NULL); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 147; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __pyx_t_7 = PyObject_Call(__pyx_t_4, __pyx_t_6, NULL); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 149; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_7);
__Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0;
__Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0;
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+ if (!(likely(((__pyx_t_7) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_7, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 149; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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{
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@@ -1308,14 +1328,14 @@ static PyObject *__pyx_pf_6libsvm_train_wrap(PyObject *__pyx_self, PyObject *__p
}
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__pyx_bshape_0_sv_coef = __pyx_bstruct_sv_coef.shape[0]; __pyx_bshape_1_sv_coef = __pyx_bstruct_sv_coef.shape[1];
- if (unlikely(__pyx_t_9 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 147; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ if (unlikely(__pyx_t_9 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 149; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
}
__pyx_t_8 = 0;
__Pyx_DECREF(((PyObject *)__pyx_v_sv_coef));
__pyx_v_sv_coef = ((PyArrayObject *)__pyx_t_7);
__pyx_t_7 = 0;
- /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":148
+ /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":150
* cdef np.ndarray[np.float64_t, ndim=2, mode='c'] sv_coef
* sv_coef = np.empty((nr-1, nSV))
* copy_sv_coef(sv_coef.data, model, sv_coef.strides) # <<<<<<<<<<<<<<
@@ -1324,30 +1344,30 @@ static PyObject *__pyx_pf_6libsvm_train_wrap(PyObject *__pyx_self, PyObject *__p
*/
copy_sv_coef(__pyx_v_sv_coef->data, __pyx_v_model, __pyx_v_sv_coef->strides);
- /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":152
+ /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":154
* # copy model.rho
* cdef np.ndarray[np.float64_t, ndim=1, mode='c'] rho
* rho = np.empty(nr*(nr-1)/2) # <<<<<<<<<<<<<<
* copy_rho(rho.data, model, rho.shape)
*
*/
- __pyx_t_7 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 152; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __pyx_t_7 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 154; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+ __pyx_t_6 = PyObject_GetAttr(__pyx_t_7, __pyx_n_s__empty); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 154; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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__Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0;
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+ __pyx_t_7 = PyInt_FromLong(__Pyx_div_long((__pyx_v_nr * (__pyx_v_nr - 1)), 2)); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 154; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+ __pyx_t_4 = PyTuple_New(1); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 154; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_7);
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- __pyx_t_7 = PyObject_Call(__pyx_t_6, __pyx_t_4, NULL); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 152; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __pyx_t_7 = PyObject_Call(__pyx_t_6, __pyx_t_4, NULL); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 154; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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__Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0;
__Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0;
- if (!(likely(((__pyx_t_7) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_7, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 152; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ if (!(likely(((__pyx_t_7) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_7, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 154; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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{
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@@ -1364,14 +1384,14 @@ static PyObject *__pyx_pf_6libsvm_train_wrap(PyObject *__pyx_self, PyObject *__p
}
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__pyx_bshape_0_rho = __pyx_bstruct_rho.shape[0];
- if (unlikely(__pyx_t_9 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 152; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ if (unlikely(__pyx_t_9 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 154; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
}
__pyx_t_13 = 0;
__Pyx_DECREF(((PyObject *)__pyx_v_rho));
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__pyx_t_7 = 0;
- /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":153
+ /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":155
* cdef np.ndarray[np.float64_t, ndim=1, mode='c'] rho
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*/
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- /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":157
+ /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":159
* # copy model.SV
* cdef np.ndarray[np.float64_t, ndim=2, mode='c'] SV
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*
*/
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+ __pyx_t_7 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 159; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+ __pyx_t_4 = PyObject_GetAttr(__pyx_t_7, __pyx_n_s__zeros); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 159; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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__Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0;
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__Pyx_GOTREF(__pyx_t_7);
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+ __pyx_t_6 = __Pyx_PyInt_to_py_npy_intp((__pyx_v_X->dimensions[1])); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 159; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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*/
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*/
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* free_model(model)
* free_problem(problem)
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__Pyx_SafeReleaseBuffer(&__pyx_bstruct_weight_label);
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__Pyx_DECREF((PyObject *)__pyx_v_nclass_SV);
__Pyx_DECREF((PyObject *)__pyx_v_label);
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int __pyx_v_nr_class;
PyArrayObject *__pyx_v_nSV = 0;
PyArrayObject *__pyx_v_label = 0;
+ PyArrayObject *__pyx_v_probA = 0;
+ PyArrayObject *__pyx_v_probB = 0;
PyArrayObject *__pyx_v_dec_values;
struct svm_parameter *__pyx_v_param;
struct svm_model *__pyx_v_model;
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Py_buffer __pyx_bstruct_weight_label;
Py_ssize_t __pyx_bstride_0_weight_label = 0;
Py_ssize_t __pyx_bshape_0_weight_label = 0;
+ Py_buffer __pyx_bstruct_probA;
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switch (PyTuple_GET_SIZE(__pyx_args)) {
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+ __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 24, 24, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 191; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 2:
values[2] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__sv_coef);
if (likely(values[2])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 22, 22, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 178; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 24, 24, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 191; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 3:
values[3] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__rho);
if (likely(values[3])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 22, 22, 3); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 178; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 24, 24, 3); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 191; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 4:
values[4] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__svm_type);
if (likely(values[4])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 22, 22, 4); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 178; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 24, 24, 4); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 191; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 5:
values[5] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__kernel_type);
if (likely(values[5])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 22, 22, 5); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 178; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 24, 24, 5); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 191; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 6:
values[6] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__degree);
if (likely(values[6])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 22, 22, 6); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 178; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 24, 24, 6); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 191; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 7:
values[7] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__gamma);
if (likely(values[7])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 22, 22, 7); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 178; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 24, 24, 7); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 191; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 8:
values[8] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__coef0);
if (likely(values[8])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 22, 22, 8); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 178; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 24, 24, 8); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 191; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 9:
values[9] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__eps);
if (likely(values[9])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 22, 22, 9); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 178; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 24, 24, 9); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 191; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 10:
values[10] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__C);
if (likely(values[10])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 22, 22, 10); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 178; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 24, 24, 10); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 191; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 11:
values[11] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__nr_weight);
if (likely(values[11])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 22, 22, 11); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 178; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 24, 24, 11); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 191; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 12:
values[12] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__weight_label);
if (likely(values[12])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 22, 22, 12); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 178; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 24, 24, 12); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 191; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 13:
values[13] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__weight);
if (likely(values[13])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 22, 22, 13); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 178; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 24, 24, 13); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 191; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 14:
values[14] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__nu);
if (likely(values[14])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 22, 22, 14); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 178; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 24, 24, 14); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 191; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 15:
values[15] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__cache_size);
if (likely(values[15])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 22, 22, 15); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 178; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 24, 24, 15); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 191; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 16:
values[16] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__p);
if (likely(values[16])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 22, 22, 16); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 178; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 24, 24, 16); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 191; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 17:
values[17] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__shrinking);
if (likely(values[17])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 22, 22, 17); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 178; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 24, 24, 17); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 191; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 18:
values[18] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__probability);
if (likely(values[18])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 22, 22, 18); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 178; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 24, 24, 18); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 191; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 19:
values[19] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__nr_class);
if (likely(values[19])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 22, 22, 19); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 178; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 24, 24, 19); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 191; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 20:
values[20] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__nSV);
if (likely(values[20])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 22, 22, 20); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 178; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 24, 24, 20); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 191; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 21:
values[21] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__label);
if (likely(values[21])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 22, 22, 21); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 178; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 24, 24, 21); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 191; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ }
+ case 22:
+ values[22] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__probA);
+ if (likely(values[22])) kw_args--;
+ else {
+ __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 24, 24, 22); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 191; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ }
+ case 23:
+ values[23] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__probB);
+ if (likely(values[23])) kw_args--;
+ else {
+ __Pyx_RaiseArgtupleInvalid("predict_from_model_wrap", 1, 24, 24, 23); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 191; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
}
if (unlikely(kw_args > 0)) {
- if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "predict_from_model_wrap") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 178; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "predict_from_model_wrap") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 191; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
__pyx_v_T = ((PyArrayObject *)values[0]);
__pyx_v_SV = ((PyArrayObject *)values[1]);
__pyx_v_sv_coef = ((PyArrayObject *)values[2]);
__pyx_v_rho = ((PyArrayObject *)values[3]);
- __pyx_v_svm_type = __Pyx_PyInt_AsInt(values[4]); if (unlikely((__pyx_v_svm_type == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 182; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_kernel_type = __Pyx_PyInt_AsInt(values[5]); if (unlikely((__pyx_v_kernel_type == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 182; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_degree = __Pyx_PyInt_AsInt(values[6]); if (unlikely((__pyx_v_degree == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 182; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_gamma = __pyx_PyFloat_AsDouble(values[7]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 183; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_coef0 = __pyx_PyFloat_AsDouble(values[8]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 183; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_eps = __pyx_PyFloat_AsDouble(values[9]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 183; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_C = __pyx_PyFloat_AsDouble(values[10]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 184; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_nr_weight = __Pyx_PyInt_AsInt(values[11]); if (unlikely((__pyx_v_nr_weight == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 184; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_svm_type = __Pyx_PyInt_AsInt(values[4]); if (unlikely((__pyx_v_svm_type == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 195; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_kernel_type = __Pyx_PyInt_AsInt(values[5]); if (unlikely((__pyx_v_kernel_type == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 195; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_degree = __Pyx_PyInt_AsInt(values[6]); if (unlikely((__pyx_v_degree == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 195; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_gamma = __pyx_PyFloat_AsDouble(values[7]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 196; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_coef0 = __pyx_PyFloat_AsDouble(values[8]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 196; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_eps = __pyx_PyFloat_AsDouble(values[9]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 196; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_C = __pyx_PyFloat_AsDouble(values[10]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 197; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_nr_weight = __Pyx_PyInt_AsInt(values[11]); if (unlikely((__pyx_v_nr_weight == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 197; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_weight_label = ((PyArrayObject *)values[12]);
__pyx_v_weight = ((PyArrayObject *)values[13]);
- __pyx_v_nu = __pyx_PyFloat_AsDouble(values[14]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 187; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_cache_size = __pyx_PyFloat_AsDouble(values[15]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 187; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_p = __pyx_PyFloat_AsDouble(values[16]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 187; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_shrinking = __Pyx_PyInt_AsInt(values[17]); if (unlikely((__pyx_v_shrinking == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 187; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_probability = __Pyx_PyInt_AsInt(values[18]); if (unlikely((__pyx_v_probability == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 188; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_nr_class = __Pyx_PyInt_AsInt(values[19]); if (unlikely((__pyx_v_nr_class == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 188; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_nu = __pyx_PyFloat_AsDouble(values[14]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 200; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_cache_size = __pyx_PyFloat_AsDouble(values[15]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 200; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_p = __pyx_PyFloat_AsDouble(values[16]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 200; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_shrinking = __Pyx_PyInt_AsInt(values[17]); if (unlikely((__pyx_v_shrinking == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 200; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_probability = __Pyx_PyInt_AsInt(values[18]); if (unlikely((__pyx_v_probability == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 201; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_nr_class = __Pyx_PyInt_AsInt(values[19]); if (unlikely((__pyx_v_nr_class == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 201; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_nSV = ((PyArrayObject *)values[20]);
__pyx_v_label = ((PyArrayObject *)values[21]);
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+ __pyx_v_probA = ((PyArrayObject *)values[22]);
+ __pyx_v_probB = ((PyArrayObject *)values[23]);
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goto __pyx_L5_argtuple_error;
} else {
__pyx_v_T = ((PyArrayObject *)PyTuple_GET_ITEM(__pyx_args, 0));
__pyx_v_SV = ((PyArrayObject *)PyTuple_GET_ITEM(__pyx_args, 1));
__pyx_v_sv_coef = ((PyArrayObject *)PyTuple_GET_ITEM(__pyx_args, 2));
__pyx_v_rho = ((PyArrayObject *)PyTuple_GET_ITEM(__pyx_args, 3));
- __pyx_v_svm_type = __Pyx_PyInt_AsInt(PyTuple_GET_ITEM(__pyx_args, 4)); if (unlikely((__pyx_v_svm_type == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 182; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_kernel_type = __Pyx_PyInt_AsInt(PyTuple_GET_ITEM(__pyx_args, 5)); if (unlikely((__pyx_v_kernel_type == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 182; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_degree = __Pyx_PyInt_AsInt(PyTuple_GET_ITEM(__pyx_args, 6)); if (unlikely((__pyx_v_degree == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 182; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
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+ if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_T, (PyObject*)__pyx_v_T, &__Pyx_TypeInfo_nn___pyx_t_5numpy_float64_t, PyBUF_FORMAT| PyBUF_C_CONTIGUOUS, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 191; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+ __pyx_bshape_0_probB = __pyx_bstruct_probB.shape[0];
- /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":223
+ /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":238
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- /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":225
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+ /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":241
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- * sv_coef.data, rho.data, nSV.data, label.data) # <<<<<<<<<<<<<<
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*/
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+ /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":244
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+ __pyx_t_1 = PyTuple_New(1); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 244; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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- {__pyx_filename = __pyx_f[0]; __pyx_lineno = 228; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ {__pyx_filename = __pyx_f[0]; __pyx_lineno = 244; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
goto __pyx_L6;
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free_model(__pyx_v_model);
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free_param(__pyx_v_param);
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__Pyx_DECREF((PyObject *)__pyx_v_nSV);
__Pyx_DECREF((PyObject *)__pyx_v_label);
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PyArrayObject *__pyx_v_nSV = 0;
PyArrayObject *__pyx_v_label = 0;
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PyArrayObject *__pyx_v_dec_values;
struct svm_parameter *__pyx_v_param;
struct svm_model *__pyx_v_model;
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Py_ssize_t __pyx_bshape_0_weight_label = 0;
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Py_ssize_t __pyx_bshape_0_label = 0;
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PyObject *__pyx_t_4 = NULL;
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+ __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 24, 24, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 252; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
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else {
- __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 22, 22, 5); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 237; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 24, 24, 5); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 252; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 6:
values[6] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__degree);
if (likely(values[6])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 22, 22, 6); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 237; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 24, 24, 6); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 252; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 7:
values[7] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__gamma);
if (likely(values[7])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 22, 22, 7); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 237; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 24, 24, 7); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 252; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 8:
values[8] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__coef0);
if (likely(values[8])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 22, 22, 8); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 237; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 24, 24, 8); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 252; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 9:
values[9] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__eps);
if (likely(values[9])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 22, 22, 9); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 237; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 24, 24, 9); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 252; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 10:
values[10] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__C);
if (likely(values[10])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 22, 22, 10); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 237; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 24, 24, 10); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 252; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 11:
values[11] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__nr_weight);
if (likely(values[11])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 22, 22, 11); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 237; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 24, 24, 11); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 252; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 12:
values[12] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__weight_label);
if (likely(values[12])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 22, 22, 12); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 237; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 24, 24, 12); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 252; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 13:
values[13] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__weight);
if (likely(values[13])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 22, 22, 13); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 237; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 24, 24, 13); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 252; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
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case 14:
values[14] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__nu);
if (likely(values[14])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 22, 22, 14); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 237; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 24, 24, 14); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 252; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 15:
values[15] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__cache_size);
if (likely(values[15])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 22, 22, 15); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 237; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 24, 24, 15); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 252; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 16:
values[16] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__p);
if (likely(values[16])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 22, 22, 16); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 237; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 24, 24, 16); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 252; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 17:
values[17] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__shrinking);
if (likely(values[17])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 22, 22, 17); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 237; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 24, 24, 17); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 252; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 18:
values[18] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__probability);
if (likely(values[18])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 22, 22, 18); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 237; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 24, 24, 18); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 252; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 19:
values[19] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__nr_class);
if (likely(values[19])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 22, 22, 19); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 237; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 24, 24, 19); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 252; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 20:
values[20] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__nSV);
if (likely(values[20])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 22, 22, 20); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 237; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 24, 24, 20); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 252; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 21:
values[21] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__label);
if (likely(values[21])) kw_args--;
else {
- __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 22, 22, 21); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 237; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 24, 24, 21); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 252; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ }
+ case 22:
+ values[22] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__probA);
+ if (likely(values[22])) kw_args--;
+ else {
+ __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 24, 24, 22); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 252; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ }
+ case 23:
+ values[23] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__probB);
+ if (likely(values[23])) kw_args--;
+ else {
+ __Pyx_RaiseArgtupleInvalid("predict_prob_from_model_wrap", 1, 24, 24, 23); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 252; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
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if (unlikely(kw_args > 0)) {
- if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "predict_prob_from_model_wrap") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 237; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "predict_prob_from_model_wrap") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 252; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
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__pyx_v_SV = ((PyArrayObject *)values[1]);
__pyx_v_sv_coef = ((PyArrayObject *)values[2]);
__pyx_v_rho = ((PyArrayObject *)values[3]);
- __pyx_v_svm_type = __Pyx_PyInt_AsInt(values[4]); if (unlikely((__pyx_v_svm_type == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 241; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_kernel_type = __Pyx_PyInt_AsInt(values[5]); if (unlikely((__pyx_v_kernel_type == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 241; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_degree = __Pyx_PyInt_AsInt(values[6]); if (unlikely((__pyx_v_degree == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 241; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_gamma = __pyx_PyFloat_AsDouble(values[7]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 242; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_coef0 = __pyx_PyFloat_AsDouble(values[8]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 242; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_eps = __pyx_PyFloat_AsDouble(values[9]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 242; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_C = __pyx_PyFloat_AsDouble(values[10]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 243; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_nr_weight = __Pyx_PyInt_AsInt(values[11]); if (unlikely((__pyx_v_nr_weight == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 243; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_svm_type = __Pyx_PyInt_AsInt(values[4]); if (unlikely((__pyx_v_svm_type == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 256; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_kernel_type = __Pyx_PyInt_AsInt(values[5]); if (unlikely((__pyx_v_kernel_type == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 256; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_degree = __Pyx_PyInt_AsInt(values[6]); if (unlikely((__pyx_v_degree == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 256; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_gamma = __pyx_PyFloat_AsDouble(values[7]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_coef0 = __pyx_PyFloat_AsDouble(values[8]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_eps = __pyx_PyFloat_AsDouble(values[9]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_C = __pyx_PyFloat_AsDouble(values[10]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 258; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_nr_weight = __Pyx_PyInt_AsInt(values[11]); if (unlikely((__pyx_v_nr_weight == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 258; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_weight_label = ((PyArrayObject *)values[12]);
__pyx_v_weight = ((PyArrayObject *)values[13]);
- __pyx_v_nu = __pyx_PyFloat_AsDouble(values[14]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 246; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_cache_size = __pyx_PyFloat_AsDouble(values[15]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 246; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_p = __pyx_PyFloat_AsDouble(values[16]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 246; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_shrinking = __Pyx_PyInt_AsInt(values[17]); if (unlikely((__pyx_v_shrinking == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 246; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_probability = __Pyx_PyInt_AsInt(values[18]); if (unlikely((__pyx_v_probability == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 247; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_nr_class = __Pyx_PyInt_AsInt(values[19]); if (unlikely((__pyx_v_nr_class == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 247; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_nu = __pyx_PyFloat_AsDouble(values[14]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 261; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_cache_size = __pyx_PyFloat_AsDouble(values[15]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 261; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_p = __pyx_PyFloat_AsDouble(values[16]); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 261; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_shrinking = __Pyx_PyInt_AsInt(values[17]); if (unlikely((__pyx_v_shrinking == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 261; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_probability = __Pyx_PyInt_AsInt(values[18]); if (unlikely((__pyx_v_probability == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 262; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_nr_class = __Pyx_PyInt_AsInt(values[19]); if (unlikely((__pyx_v_nr_class == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 262; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_nSV = ((PyArrayObject *)values[20]);
__pyx_v_label = ((PyArrayObject *)values[21]);
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goto __pyx_L5_argtuple_error;
} else {
__pyx_v_T = ((PyArrayObject *)PyTuple_GET_ITEM(__pyx_args, 0));
__pyx_v_SV = ((PyArrayObject *)PyTuple_GET_ITEM(__pyx_args, 1));
__pyx_v_sv_coef = ((PyArrayObject *)PyTuple_GET_ITEM(__pyx_args, 2));
__pyx_v_rho = ((PyArrayObject *)PyTuple_GET_ITEM(__pyx_args, 3));
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- __pyx_v_kernel_type = __Pyx_PyInt_AsInt(PyTuple_GET_ITEM(__pyx_args, 5)); if (unlikely((__pyx_v_kernel_type == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 241; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_degree = __Pyx_PyInt_AsInt(PyTuple_GET_ITEM(__pyx_args, 6)); if (unlikely((__pyx_v_degree == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 241; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_gamma = __pyx_PyFloat_AsDouble(PyTuple_GET_ITEM(__pyx_args, 7)); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 242; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_coef0 = __pyx_PyFloat_AsDouble(PyTuple_GET_ITEM(__pyx_args, 8)); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 242; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_eps = __pyx_PyFloat_AsDouble(PyTuple_GET_ITEM(__pyx_args, 9)); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 242; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_C = __pyx_PyFloat_AsDouble(PyTuple_GET_ITEM(__pyx_args, 10)); if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 243; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
- __pyx_v_nr_weight = __Pyx_PyInt_AsInt(PyTuple_GET_ITEM(__pyx_args, 11)); if (unlikely((__pyx_v_nr_weight == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 243; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_svm_type = __Pyx_PyInt_AsInt(PyTuple_GET_ITEM(__pyx_args, 4)); if (unlikely((__pyx_v_svm_type == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 256; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_kernel_type = __Pyx_PyInt_AsInt(PyTuple_GET_ITEM(__pyx_args, 5)); if (unlikely((__pyx_v_kernel_type == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 256; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+ __pyx_v_degree = __Pyx_PyInt_AsInt(PyTuple_GET_ITEM(__pyx_args, 6)); if (unlikely((__pyx_v_degree == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 256; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
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__pyx_v_label = ((PyArrayObject *)PyTuple_GET_ITEM(__pyx_args, 21));
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__pyx_L5_argtuple_error:;
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__pyx_L3_error:;
__Pyx_AddTraceback("libsvm.predict_prob_from_model_wrap");
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__Pyx_INCREF((PyObject *)__pyx_v_nSV);
__Pyx_INCREF((PyObject *)__pyx_v_label);
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+ __pyx_bstruct_probB.buf = NULL;
+ if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_T), __pyx_ptype_5numpy_ndarray, 1, "T", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 252; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_SV), __pyx_ptype_5numpy_ndarray, 1, "SV", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 253; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_sv_coef), __pyx_ptype_5numpy_ndarray, 1, "sv_coef", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 254; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_rho), __pyx_ptype_5numpy_ndarray, 1, "rho", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 255; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_weight_label), __pyx_ptype_5numpy_ndarray, 1, "weight_label", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 259; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_weight), __pyx_ptype_5numpy_ndarray, 1, "weight", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 260; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+ if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_T, (PyObject*)__pyx_v_T, &__Pyx_TypeInfo_nn___pyx_t_5numpy_float64_t, PyBUF_FORMAT| PyBUF_C_CONTIGUOUS, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 252; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+ if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_weight_label, (PyObject*)__pyx_v_weight_label, &__Pyx_TypeInfo_nn___pyx_t_5numpy_int_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 252; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+ if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_weight, (PyObject*)__pyx_v_weight, &__Pyx_TypeInfo_nn___pyx_t_5numpy_float_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 252; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+ if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_label, (PyObject*)__pyx_v_label, &__Pyx_TypeInfo_nn___pyx_t_5numpy_int_t, PyBUF_FORMAT| PyBUF_C_CONTIGUOUS, 1, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 252; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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- /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":282
+ /* "/volatile/fabian/dev/scikit-learn/scikits/learn/src/libsvm.pyx":299
* coef0, nu, cache_size, C, eps, p, shrinking,
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* model = set_model(param, nr_class, SV.data, SV.shape, sv_coef.strides,
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+ __pyx_builtin_MemoryError = __Pyx_GetName(__pyx_b, __pyx_n_s__MemoryError); if (!__pyx_builtin_MemoryError) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 134; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __pyx_builtin_ValueError = __Pyx_GetName(__pyx_b, __pyx_n_s__ValueError); if (!__pyx_builtin_ValueError) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 139; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_builtin_range = __Pyx_GetName(__pyx_b, __pyx_n_s__range); if (!__pyx_builtin_range) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 218; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_builtin_RuntimeError = __Pyx_GetName(__pyx_b, __pyx_n_s__RuntimeError); if (!__pyx_builtin_RuntimeError) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 786; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
return 0;
diff --git a/scikits/learn/src/libsvm.pyx b/scikits/learn/src/libsvm.pyx
index 59d5d00a62..84d9f27a17 100644
--- a/scikits/learn/src/libsvm.pyx
+++ b/scikits/learn/src/libsvm.pyx
@@ -61,7 +61,7 @@ cdef extern from "libsvm_helper.c":
double, int, int, int, char *, char *)
svm_problem *set_problem(char *, char *, np.npy_intp *)
svm_model *set_model(svm_parameter *, int, char *, np.npy_intp *, np.npy_intp *,
- char *, char *, char *, char *)
+ char *, char *, char *, char *, char *, char *)
void copy_sv_coef (char *, svm_model *, np.npy_intp *)
void copy_rho (char *, svm_model *, np.npy_intp *)
void copy_SV (char *, svm_model *, np.npy_intp *)
@@ -69,6 +69,8 @@ cdef extern from "libsvm_helper.c":
int copy_prob_predict (char *, svm_model *, np.npy_intp *, char *)
void copy_nSV (char *, svm_model *)
void copy_label (char *, svm_model *)
+ void copy_probA(char *, svm_model *, np.npy_intp *)
+ void copy_probB(char *, svm_model *, np.npy_intp *)
np.npy_intp get_l (svm_model *)
np.npy_intp get_nr (svm_model *)
int free_problem (svm_problem *)
@@ -164,15 +166,26 @@ def train_wrap ( np.ndarray[np.float64_t, ndim=2, mode='c'] X,
nclass_SV = np.empty((nr), dtype=np.int)
copy_nSV(nclass_SV.data, model)
+ # copy label
cdef np.ndarray[np.int_t, ndim=1, mode='c'] label
label = np.empty((nr), dtype=np.int)
copy_label(label.data, model)
+ # copy probabilities
+ cdef np.ndarray[np.float64_t, ndim=1, mode='c'] probA
+ cdef np.ndarray[np.float64_t, ndim=1, mode='c'] probB
+ if probability != 0:
+ # this is only valid for SVC
+ probA = np.empty(nr*(nr-1)/2, dtype=np.float64)
+ probB = np.empty(nr*(nr-1)/2, dtype=np.float64)
+ copy_probA(probA.data, model, probA.shape)
+ copy_probB(probB.data, model, probB.shape)
+
free_model(model)
free_problem(problem)
free_param(param)
- return sv_coef, rho, SV, nr, nclass_SV, label
+ return sv_coef, rho, SV, nr, nclass_SV, label, probA, probB
def predict_from_model_wrap(np.ndarray[np.float64_t, ndim=2, mode='c'] T,
@@ -187,7 +200,9 @@ def predict_from_model_wrap(np.ndarray[np.float64_t, ndim=2, mode='c'] T,
double nu, double cache_size, double p, int
shrinking, int probability, int nr_class,
np.ndarray[np.int_t, ndim=1, mode='c'] nSV,
- np.ndarray[np.int_t, ndim=1, mode='c'] label):
+ np.ndarray[np.int_t, ndim=1, mode='c'] label,
+ np.ndarray[np.float64_t, ndim=1, mode='c'] probA,
+ np.ndarray[np.float64_t, ndim=1, mode='c'] probB):
"""
Predict values T given a pointer to svm_model.
@@ -222,7 +237,8 @@ def predict_from_model_wrap(np.ndarray[np.float64_t, ndim=2, mode='c'] T,
probability, nr_weight, weight_label.data,
weight.data)
model = set_model(param, nr_class, SV.data, SV.shape, sv_coef.strides,
- sv_coef.data, rho.data, nSV.data, label.data)
+ sv_coef.data, rho.data, nSV.data, label.data,
+ probA.data, probB.data)
dec_values = np.empty(T.shape[0])
if copy_predict(T.data, model, T.shape, dec_values.data) < 0:
raise MemoryError("We've run out of of memory")
@@ -233,7 +249,6 @@ def predict_from_model_wrap(np.ndarray[np.float64_t, ndim=2, mode='c'] T,
return dec_values
-
def predict_prob_from_model_wrap(np.ndarray[np.float64_t, ndim=2, mode='c'] T,
np.ndarray[np.float64_t, ndim=2, mode='c'] SV,
np.ndarray[np.float64_t, ndim=2, mode='c'] sv_coef,
@@ -246,7 +261,9 @@ def predict_prob_from_model_wrap(np.ndarray[np.float64_t, ndim=2, mode='c'] T,
double nu, double cache_size, double p, int
shrinking, int probability, int nr_class,
np.ndarray[np.int_t, ndim=1, mode='c'] nSV,
- np.ndarray[np.int_t, ndim=1, mode='c'] label):
+ np.ndarray[np.int_t, ndim=1, mode='c'] label,
+ np.ndarray[np.float64_t, ndim=1, mode='c'] probA,
+ np.ndarray[np.float64_t, ndim=1, mode='c'] probB):
"""
Predict probabilities
@@ -281,10 +298,11 @@ def predict_prob_from_model_wrap(np.ndarray[np.float64_t, ndim=2, mode='c'] T,
probability, nr_weight, weight_label.data,
weight.data)
model = set_model(param, nr_class, SV.data, SV.shape, sv_coef.strides,
- sv_coef.data, rho.data, nSV.data, label.data)
+ sv_coef.data, rho.data, nSV.data, label.data,
+ probA.data, probB.data)
cdef int nr = get_nr(model)
- dec_values = np.empty((T.shape[0], nr))
+ dec_values = np.empty((T.shape[0], nr), dtype=np.float64)
if copy_prob_predict(T.data, model, T.shape, dec_values.data) < 0:
raise MemoryError("We've run out of of memory")
# free model and param
diff --git a/scikits/learn/src/libsvm_helper.c b/scikits/learn/src/libsvm_helper.c
index d86895485d..1223709d19 100644
--- a/scikits/learn/src/libsvm_helper.c
+++ b/scikits/learn/src/libsvm_helper.c
@@ -151,7 +151,8 @@ struct svm_problem * set_problem(char *X,char *Y, npy_intp *dims)
*/
struct svm_model *set_model(struct svm_parameter *param, int nr_class,
char *SV, npy_intp *SV_dims, npy_intp *sv_coef_strides,
- char *sv_coef, char *rho, char *nSV, char *label)
+ char *sv_coef, char *rho, char *nSV, char *label,
+ char *probA, char *probB)
{
int i;
char *t = sv_coef;
@@ -177,6 +178,7 @@ struct svm_model *set_model(struct svm_parameter *param, int nr_class,
memcpy(model->nSV, nSV, model->nr_class * sizeof(int));
memcpy(model->label, label, model->nr_class * sizeof(int));
}
+
for (i=0; i < model->nr_class-1; i++) {
/*
* We cannot squash all this mallocs in a single call since
@@ -192,8 +194,16 @@ struct svm_model *set_model(struct svm_parameter *param, int nr_class,
* just to avoid segfaults, these features are not wrapped but
* svm_destroy_model will try to free them.
*/
- model->probA = (double *) malloc(sizeof(double));
- model->probB = (double *) malloc(sizeof(double));
+
+ if (param->probability) {
+ model->probA = (double *) malloc(m * sizeof(double));
+ memcpy(model->probA, probA, m * sizeof(double));
+ model->probB = (double *) malloc(m * sizeof(double));
+ memcpy(model->probB, probB, m * sizeof(double));
+ } else {
+ model->probA = NULL;
+ model->probB = NULL;
+ }
/* We'll free SV ourselves */
model->free_sv = 0;
@@ -280,6 +290,17 @@ void copy_label(char *data, struct svm_model *model)
memcpy(data, model->label, model->nr_class * sizeof(int));
}
+void copy_probA(char *data, struct svm_model *model, npy_intp * dims)
+{
+ memcpy(data, model->probA, dims[0] * sizeof(double));
+}
+
+
+void copy_probB(char *data, struct svm_model *model, npy_intp * dims)
+{
+ memcpy(data, model->probB, dims[0] * sizeof(double));
+}
+
/*
* Use train to predict using model. Train is expected to be an array
* in the numpy sense.
@@ -315,9 +336,8 @@ int copy_prob_predict(char *predict, struct svm_model *model, npy_intp *predict_
if (predict_nodes == NULL)
return -1;
for(i=0; i<n; ++i) {
- svm_predict_probability(model, predict_nodes[i], t);
+ svm_predict_probability(model, predict_nodes[i], &t[i*predict_dims[1]]);
free(predict_nodes[i]);
- t += predict_dims[1] * sizeof(double);
}
return 0;
}
diff --git a/scikits/learn/svm.py b/scikits/learn/svm.py
index c39f4eddb0..3e1e63fbfa 100644
--- a/scikits/learn/svm.py
+++ b/scikits/learn/svm.py
@@ -59,11 +59,13 @@ class BaseSVM(object):
if X.shape[0] != y.shape[0]: raise ValueError("Incompatible shapes")
if (self.gamma == 0): self.gamma = 1.0/X.shape[0]
- self.coef_, self.rho_, self.support_, self.nclass_, self.nSV_, self.label_ = \
- libsvm.train_wrap(X, y, self.svm, self.kernel, self.degree,
- self.gamma, self.coef0, self.eps, self.C, self.nr_weight,
- np.empty(0, dtype=np.int), np.empty(0, dtype=np.float), self.nu,
- self.cache_size, self.p, self.shrinking, self.probability)
+ self.coef_, self.rho_, self.support_, self.nclass_, self.nSV_, self.label_, \
+ self.probA_, self.probB_ = libsvm.train_wrap(X, y,
+ self.svm, self.kernel, self.degree, self.gamma,
+ self.coef0, self.eps, self.C, self.nr_weight,
+ np.empty(0, dtype=np.int), np.empty(0,
+ dtype=np.float), self.nu, self.cache_size, self.p,
+ self.shrinking, int(self.probability))
return self
def predict(self, T):
@@ -75,8 +77,8 @@ class BaseSVM(object):
np.empty(0, dtype=np.int), np.empty(0,
dtype=np.float), self.nu, self.cache_size,
self.p, self.shrinking, self.probability,
- self.nclass_, self.nSV_, self.label_)
-
+ self.nclass_, self.nSV_, self.label_,
+ self.probA_, self.probB_)
def prob_predict(self, T):
T = np.asanyarray(T, dtype=np.float, order='C')
@@ -87,7 +89,8 @@ class BaseSVM(object):
np.empty(0, dtype=np.int), np.empty(0,
dtype=np.float), self.nu, self.cache_size,
self.p, self.shrinking, self.probability,
- self.nclass_, self.nSV_, self.label_)
+ self.nclass_, self.nSV_, self.label_,
+ self.probA_, self.probB_)
###
# Public API
@@ -165,7 +168,7 @@ class SVC(BaseSVM):
def __init__(self, impl='c_svc', kernel='rbf', degree=3,
gamma=0.0, coef0=0.0, cache_size=100.0, eps=1e-3,
C=1.0, nr_weight=0, nu=0.5, p=0.1, shrinking=True,
- probability=False):
+ probability=True):
BaseSVM.__init__(self, impl, kernel, degree, gamma, coef0,
cache_size, eps, C, nr_weight, nu, p,
shrinking, probability)
diff --git a/scikits/learn/tests/test_svm.py b/scikits/learn/tests/test_svm.py
index 06d9836386..e24c27eaba 100644
--- a/scikits/learn/tests/test_svm.py
+++ b/scikits/learn/tests/test_svm.py
@@ -10,8 +10,10 @@ Y = np.array( [1, 1, 1, 2, 2, 2])
T = np.array( [[-1,-1], [2, 2], [3, 2]] )
-clf = svm.SVC()#probability=True)
+clf = svm.SVC(probability=True)
clf.fit(X, Y)
+# print clf.probA_
+# print clf.probB_
# clf.predict(T)
print clf.prob_predict(T)
--
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