text: #!/usr/bin/env python
  
  from ctypes import *
  from ctypes.util import find_library
  from os import path
  import sys
  
  if sys.version_info[0] >= 3:
  	xrange = range
  
  __all__ = ['libsvm', 'svm_problem', 'svm_parameter',
             'toPyModel', 'gen_svm_nodearray', 'print_null', 'svm_node', 'C_SVC',
             'EPSILON_SVR', 'LINEAR', 'NU_SVC', 'NU_SVR', 'ONE_CLASS',
             'POLY', 'PRECOMPUTED', 'PRINT_STRING_FUN', 'RBF',
             'SIGMOID', 'c_double', 'svm_model']
  
  try:
  	dirname = path.dirname(path.abspath(__file__))
  	if sys.platform == 'win32':
  		libsvm = CDLL(path.join(dirname, r'..\windows\libsvm.dll'))
  	else:
  		libsvm = CDLL(path.join(dirname, '../libsvm.so.2'))
  except:
  # For unix the prefix 'lib' is not considered.
  	if find_library('svm'):
  		libsvm = CDLL(find_library('svm'))
  	elif find_library('libsvm'):
  		libsvm = CDLL(find_library('libsvm'))
  	else:
  		raise Exception('LIBSVM library not found.')
  
  C_SVC = 0
  NU_SVC = 1
  ONE_CLASS = 2
  EPSILON_SVR = 3
  NU_SVR = 4
  
  LINEAR = 0
  POLY = 1
  RBF = 2
  SIGMOID = 3
  PRECOMPUTED = 4
  
  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 __str__(self):
  		return '%d:%g' % (self.index, self.value)
  
  def gen_svm_nodearray(xi, feature_max=None, isKernel=None):
  	if isinstance(xi, dict):
  		index_range = xi.keys()
  	elif isinstance(xi, (list, tuple)):
  		if not isKernel:
  			xi = [0] + xi  # idx should start from 1
  		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 not isKernel:
  		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, isKernel=None):
  		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,isKernel=isKernel)
  			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 __str__(self):
  		s = ''
  		attrs = svm_parameter._names + list(self.__dict__.keys())
  		values = map(lambda attr: getattr(self, attr), attrs)
  		for attr, val in zip(attrs, values):
  			s += (' %s: %s\n' % (attr, val))
  		s = s.strip()
  
  		return s
  
  	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 = None
  		self.weight = None
  		self.cross_validation = False
  		self.nr_fold = 0
  		self.print_func = cast(None, PRINT_STRING_FUN)
  
  	def parse_options(self, options):
  		if isinstance(options, list):
  			argv = options
  		elif isinstance(options, str):
  			argv = options.split()
  		else:
  			raise TypeError("arg 1 should be a list or a str.")
  		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
  				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):
  	_names = ['param', 'nr_class', 'l', 'SV', 'sv_coef', 'rho',
  			'probA', 'probB', 'sv_indices', 'label', 'nSV', 'free_sv']
  	_types = [svm_parameter, c_int, c_int, POINTER(POINTER(svm_node)),
  			POINTER(POINTER(c_double)), POINTER(c_double),
  			POINTER(c_double), POINTER(c_double), POINTER(c_int),
  			POINTER(c_int), POINTER(c_int), c_int]
  	_fields_ = genFields(_names, _types)
  
  	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 get_sv_indices(self):
  		total_sv = self.get_nr_sv()
  		sv_indices = (c_int * total_sv)()
  		libsvm.svm_get_sv_indices(self, sv_indices)
  		return sv_indices[:total_sv]
  
  	def get_nr_sv(self):
  		return libsvm.svm_get_nr_sv(self)
  
  	def is_probability_model(self):
  		return (libsvm.svm_check_probability_model(self) == 1)
  
  	def get_sv_coef(self):
  		return [tuple(self.sv_coef[j][i] for j in xrange(self.nr_class - 1))
  				for i in xrange(self.l)]
  
  	def get_SV(self):
  		result = []
  		for sparse_sv in self.SV[:self.l]:
  			row = dict()
  
  			i = 0
  			while True:
  				row[sparse_sv[i].index] = sparse_sv[i].value
  				if sparse_sv[i].index == -1:
  					break
  				i += 1
  
  			result.append(row)
  		return result
  
  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_sv_indices, None, [POINTER(svm_model), POINTER(c_int)])
  fillprototype(libsvm.svm_get_nr_sv, c_int, [POINTER(svm_model)])
  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])
  