class ArfMAin:
"""
This class is a simple implementation of the ARF. It is not suppose to be a scalable implementation.
Args :
:param dim: int that represent the dimension of the vector space.
:param domain: int that represent the domain of the vector space.
:param size: int that is the size of the ARF in bits.
"""
def __init__(self,
path_file_feed,
path_file_test,
dim=1,
domain=1000,
size=1000,
delta_error=1,
methode_discretize=Constants.DIS_TESTS):
self.discretizor = RectangleDiscretisator(delta_error,
methode_discretize)
# get data for feed
self.data_vector_feed = DataVector(dim, path_file_feed)
# get data for test
self.data_vector_test = DataVector(dim, path_file_test)
if methode_discretize == Constants.DIS_DOUBLE:
min_range_size = delta_error
else:
min_range_size = 2 * delta_error
self.arf = ARF(dim, domain, min_range_size, size)
def feed(self):
"""
:return:
"""
points = self.data_vector_feed.get_points()
d_points = self.discretizor.discretise_points_to_insert(points)
self.arf.insert_set_of_points(d_points)
self.arf.erase()
def test(self):
"""
:return:
"""
points = self.data_vector_test.get_points()
d_points = self.discretizor.discretise_points_to_test(points)
return self.arf.test_set_of_points(d_points)
def test_arf_dim3_or(self):
arf1 = ARF(dim=3, domain=32, min_range_size=4)
arf1.insert_one_point(Point([3, 5, 3]))
res, _ = arf1.test_set_of_points([[Point([3, 5, 3]), Point([8, 5, 3])]])
self.assertEqual(res, [True], "Problem with ARF dim = 3")
def test_arf_dim4(self):
arf1 = ARF(dim=4, domain=32, min_range_size=4)
arf1.insert_one_point(Point([3, 5, 3, 5]))
res, _ = arf1.test_set_of_points([[Point([3, 5, 3, 5])], [Point([7, 12, 3, 5])]])
self.assertEqual(res, [True, False], "Problem with ARF dim = 4")