Class svm_model

pattern/vector/svm/libsvm.py:236–297

			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