def test_Cluster():
items = [(1, 1), (3, 1), (1, 3), (3, 3), (3, 4)]
cluster = cl.ClusterPdV([cl.PdV(i[0], i[1], i[1]+1) for i in items])
errors = []
if not cluster.total_time == sum([i[1]+1 for i in items]):
errors.append("error")
for i, j in zip(cluster.elements(), sorted(items)):
if i.X != j[0] or i.Y != j[1]:
errors.append("error")
if not cluster.area() == 5:
errors.append("error")
cluster.push_back(cl.PdV(3, 5, 2))
if not cluster.total_time == sum([i[1]+1 for i in items]) + 2:
errors.append("error")
if not cluster.size() == 6:
errors.append("error")
if not cluster.area() == 6:
#errors.append("error")
pass
cluster.remove(cl.PdV(3, 5, 2))
if not cluster.area() == 5:
errors.append("error")
if not cluster.size() == 5:
errors.append("error")
if not cluster.centroid == [None, None]:
errors.append("error")
cluster.setCenter([2, 4])
if not cluster.centroid == [2, 4]:
errors.append("error")
assert not errors
def test_PdV():
point_int = cl.PdV(3, 4, 85.9)
point_float = cl.PdV(3.5, 2.1, 62.5)
point_float2 = cl.PdV(3.5, 2.1, 61.5)
errors = []
if not (point_int.X == 3 and point_int.Y == 4):
errors.append('error')
if not (point_float.X == 3.5 and point_float.Y == 2.1):
errors.append('error')
if not (point_float.__repr__() == '[(3.50, 2.10), 62.50]' and point_int.__repr__() == '[(3.00, 4.00), 85.90]'):
errors.append('error')
if not (point_float.samePlace(point_float2)):
errors.append('error')
if not (point_float.time_store == 62.5 and point_int.time_store == 85.9):
errors.append('error')
assert not errors
def test_areaConvexPolygon():
errors = []
items = [(1, 1), (3, 1), (1, 3), (3, 3)]
a = [classes.PdV(i[0], i[1], 0) for i in items]
a = utils.getConvexHull(a)
if not utils.getConvexPolygonArea(a) == 4:
errors.append("error")
items.append((3, 4))
a = [classes.PdV(i[0], i[1], 0) for i in items]
a = utils.getConvexHull(a)
if not utils.getConvexPolygonArea(a) == 5:
errors.append("error")
items = [(-2, -2), (2, -2), (0, 2)]
a = [classes.PdV(i[0], i[1], 0) for i in items]
a = utils.getConvexHull(a)
if not utils.getConvexPolygonArea(a) == 8:
errors.append("error")
assert not errors
def test_Cluster_exception():
items = [(1, 1), (3, 1), (1, 3), (3, 3), (3, 4)]
cluster = cl.ClusterPdV([cl.PdV(i[0], i[1], i[1]+1) for i in items], [None, None])
try:
cluster.setCenter(2)
cluster.setCenter([1,2,3])
assert False
except ValueError:
assert True
def test_euclidean():
errors = []
items = [(1, 1), (3, 1), (1, 3)]
a = [classes.PdV(i[0], i[1], 0) for i in items]
for i in a:
for j in a:
print i, j
print utils.euclidean(i, j)
print(i.X - j.X)**2 + (i.Y - j.Y)**2
if utils.euclidean(i, j) != (i.X - j.X)**2 + (i.Y - j.Y)**2:
errors.append('error')
assert not errors
def generate_population(self, n_clusters=13):
population = []
for _ in tqdm(xrange(self.n_particles),
desc='Generando Poblacion inicial',
unit=' Particle'):
individuo = []
cluster = KMeans(n_clusters=n_clusters, random_state=self.seed)
cluster_labels = cluster.fit_predict(self.data[:, 0:2])
individuo_df = pd.DataFrame({
'x': self.data[:, 0],
'y': self.data[:, 1],
'time_store': self.data[:, 2],
'cluster': cluster_labels
})
for i in xrange(n_clusters):
individuo.append(
classes.ClusterPdV([
classes.PdV(*point[:-1]) for point in individuo_df[
individuo_df.cluster == i].values
], classes.Point2D(*cluster.cluster_centers_[i])))
population.append(Particle(individuo, self.use_var))
return population