#!/usr/bin/env python
from ctypes import *
"""
Copyright (c) 2000-2010 Chih-Chung Chang and Chih-Jen Lin
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions
are met:
1. Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
3. Neither name of copyright holders nor the names of its contributors
may be used to endorse or promote products derived from this software
without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE REGENTS OR
CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
"""
from ctypes.util import find_library
import sys
import os
# For unix the prefix 'lib' is not considered.
if sys.platform == 'win32':
libsvm = CDLL(os.path.join(os.path.dirname(__file__), 'libsvm.dll'))
elif find_library('svm'):
libsvm = CDLL(find_library('svm'))
elif find_library('libsvm'):
libsvm = CDLL(find_library('libsvm'))
else:
if sys.platform == 'win32':
libsvm = CDLL('libsvm.dll')
else:
libsvm = CDLL('../libsvm.so.2')
# Construct constants
SVM_TYPE = ['C_SVC', 'NU_SVC', 'ONE_CLASS', 'EPSILON_SVR', 'NU_SVR' ]
KERNEL_TYPE = ['LINEAR', 'POLY', 'RBF', 'SIGMOID', 'PRECOMPUTED']
for i, s in enumerate(SVM_TYPE): exec("%s = %d" % (s , i))
for i, s in enumerate(KERNEL_TYPE): exec("%s = %d" % (s , i))
PRINT_STRING_FUN = CFUNCTYPE(None, c_char_p)
def print_null(s):
return
def genFields(names, types):
return list(zip(names, types))
def fillprototype(f, restype, argtypes):
f.restype = restype
f.argtypes = argtypes
class svm_node(Structure):
_names = ["index", "value"]
_types = [c_int, c_double]
_fields_ = genFields(_names, _types)
def gen_svm_nodearray(xi, feature_max=None, issparse=None):
if isinstance(xi, dict):
index_range = xi.keys()
elif isinstance(xi, (list, tuple)):
index_range = range(len(xi))
else:
raise TypeError('xi should be a dictionary, list or tuple')
if feature_max:
assert(isinstance(feature_max, int))
index_range = filter(lambda j: j <= feature_max, index_range)
if issparse:
index_range = filter(lambda j:xi[j] != 0, index_range)
index_range = sorted(index_range)
ret = (svm_node * (len(index_range)+1))()
ret[-1].index = -1
for idx, j in enumerate(index_range):
ret[idx].index = j
ret[idx].value = xi[j]
max_idx = 0
if index_range:
max_idx = index_range[-1]
return ret, max_idx
class svm_problem(Structure):
_names = ["l", "y", "x"]
_types = [c_int, POINTER(c_double), POINTER(POINTER(svm_node))]
_fields_ = genFields(_names, _types)
def __init__(self, y, x):
if len(y) != len(x):
raise ValueError("len(y) != len(x)")
self.l = l = len(y)
max_idx = 0
x_space = self.x_space = []
for i, xi in enumerate(x):
tmp_xi, tmp_idx = gen_svm_nodearray(xi)
x_space += [tmp_xi]
max_idx = max(max_idx, tmp_idx)
self.n = max_idx
self.y = (c_double * l)()
for i, yi in enumerate(y): self.y[i] = yi
self.x = (POINTER(svm_node) * l)()
for i, xi in enumerate(self.x_space): self.x[i] = xi
class svm_parameter(Structure):
_names = ["svm_type", "kernel_type", "degree", "gamma", "coef0",
"cache_size", "eps", "C", "nr_weight", "weight_label", "weight",
"nu", "p", "shrinking", "probability"]
_types = [c_int, c_int, c_int, c_double, c_double,
c_double, c_double, c_double, c_int, POINTER(c_int), POINTER(c_double),
c_double, c_double, c_int, c_int]
_fields_ = genFields(_names, _types)
def __init__(self, options = None):
if options == None:
options = ''
self.parse_options(options)
def show(self):
attrs = svm_parameter._names + self.__dict__.keys()
values = map(lambda attr: getattr(self, attr), attrs)
for attr, val in zip(attrs, values):
print(' %s: %s' % (attr, val))
def set_to_default_values(self):
self.svm_type = C_SVC;
self.kernel_type = RBF
self.degree = 3
self.gamma = 0
self.coef0 = 0
self.nu = 0.5
self.cache_size = 100
self.C = 1
self.eps = 0.001
self.p = 0.1
self.shrinking = 1
self.probability = 0
self.nr_weight = 0
self.weight_label = (c_int*0)()
self.weight = (c_double*0)()
self.cross_validation = False
self.nr_fold = 0
self.print_func = None
def parse_options(self, options):
argv = options.split()
self.set_to_default_values()
self.print_func = cast(None, PRINT_STRING_FUN)
weight_label = []
weight = []
i = 0
while i < len(argv):
if argv[i] == "-s":
i = i + 1
self.svm_type = int(argv[i])
elif argv[i] == "-t":
i = i + 1
self.kernel_type = int(argv[i])
elif argv[i] == "-d":
i = i + 1
self.degree = int(argv[i])
elif argv[i] == "-g":
i = i + 1
self.gamma = float(argv[i])
elif argv[i] == "-r":
i = i + 1
self.coef0 = float(argv[i])
elif argv[i] == "-n":
i = i + 1
self.nu = float(argv[i])
elif argv[i] == "-m":
i = i + 1
self.cache_size = float(argv[i])
elif argv[i] == "-c":
i = i + 1
self.C = float(argv[i])
elif argv[i] == "-e":
i = i + 1
self.eps = float(argv[i])
elif argv[i] == "-p":
i = i + 1
self.p = float(argv[i])
elif argv[i] == "-h":
i = i + 1
self.shrinking = int(argv[i])
elif argv[i] == "-b":
i = i + 1
self.probability = int(argv[i])
elif argv[i] == "-q":
self.print_func = PRINT_STRING_FUN(print_null)
elif argv[i] == "-v":
i = i + 1
self.cross_validation = 1
self.nr_fold = int(argv[i])
if self.nr_fold < 2:
raise ValueError("n-fold cross validation: n must >= 2")
elif argv[i].startswith("-w"):
i = i + 1
self.nr_weight += 1
nr_weight = self.nr_weight
weight_label += [int(argv[i-1][2:])]
weight += [float(argv[i])]
else:
raise ValueError("Wrong options")
i += 1
libsvm.svm_set_print_string_function(self.print_func)
self.weight_label = (c_int*self.nr_weight)()
self.weight = (c_double*self.nr_weight)()
for i in range(self.nr_weight):
self.weight[i] = weight[i]
self.weight_label[i] = weight_label[i]
class svm_model(Structure):
def __init__(self):
self.__createfrom__ = 'python'
def __del__(self):
# free memory created by C to avoid memory leak
if hasattr(self, '__createfrom__') and self.__createfrom__ == 'C':
libsvm.svm_free_and_destroy_model(pointer(self))
def get_svm_type(self):
return libsvm.svm_get_svm_type(self)
def get_nr_class(self):
return libsvm.svm_get_nr_class(self)
def get_svr_probability(self):
return libsvm.svm_get_svr_probability(self)
def get_labels(self):
nr_class = self.get_nr_class()
labels = (c_int * nr_class)()
libsvm.svm_get_labels(self, labels)
return labels[:nr_class]
def is_probability_model(self):
return (libsvm.svm_check_probability_model(self) == 1)
def toPyModel(model_ptr):
"""
toPyModel(model_ptr) -> svm_model
Convert a ctypes POINTER(svm_model) to a Python svm_model
"""
if bool(model_ptr) == False:
raise ValueError("Null pointer")
m = model_ptr.contents
m.__createfrom__ = 'C'
return m
fillprototype(libsvm.svm_train, POINTER(svm_model), [POINTER(svm_problem), POINTER(svm_parameter)])
fillprototype(libsvm.svm_cross_validation, None, [POINTER(svm_problem), POINTER(svm_parameter), c_int, POINTER(c_double)])
fillprototype(libsvm.svm_save_model, c_int, [c_char_p, POINTER(svm_model)])
fillprototype(libsvm.svm_load_model, POINTER(svm_model), [c_char_p])
fillprototype(libsvm.svm_get_svm_type, c_int, [POINTER(svm_model)])
fillprototype(libsvm.svm_get_nr_class, c_int, [POINTER(svm_model)])
fillprototype(libsvm.svm_get_labels, None, [POINTER(svm_model), POINTER(c_int)])
fillprototype(libsvm.svm_get_svr_probability, c_double, [POINTER(svm_model)])
fillprototype(libsvm.svm_predict_values, c_double, [POINTER(svm_model), POINTER(svm_node), POINTER(c_double)])
fillprototype(libsvm.svm_predict, c_double, [POINTER(svm_model), POINTER(svm_node)])
fillprototype(libsvm.svm_predict_probability, c_double, [POINTER(svm_model), POINTER(svm_node), POINTER(c_double)])
fillprototype(libsvm.svm_free_model_content, None, [POINTER(svm_model)])
fillprototype(libsvm.svm_free_and_destroy_model, None, [POINTER(POINTER(svm_model))])
fillprototype(libsvm.svm_destroy_param, None, [POINTER(svm_parameter)])
fillprototype(libsvm.svm_check_parameter, c_char_p, [POINTER(svm_problem), POINTER(svm_parameter)])
fillprototype(libsvm.svm_check_probability_model, c_int, [POINTER(svm_model)])
fillprototype(libsvm.svm_set_print_string_function, None, [PRINT_STRING_FUN])