def test_manyways(self):
a = np.array([5, 7, 1, 2, 8])
b = np.array([9, 8, 2, 4, 3, 1, 5])
c1 = setxor1d(a, b)
aux1 = intersect1d(a, b)
aux2 = union1d(a, b)
c2 = setdiff1d(aux2, aux1)
assert_array_equal(c1, c2)
def test_manyways(self):
a = np.array([5, 7, 1, 2, 8])
b = np.array([9, 8, 2, 4, 3, 1, 5])
c1 = setxor1d(a, b)
aux1 = intersect1d(a, b)
aux2 = union1d(a, b)
c2 = setdiff1d(aux2, aux1)
assert_array_equal(c1, c2)
def test_setxor1d(self):
a = np.array([5, 7, 1, 2])
b = np.array([2, 4, 3, 1, 5])
ec = np.array([3, 4, 7])
c = setxor1d(a, b)
assert_array_equal(c, ec)
a = np.array([1, 2, 3])
b = np.array([6, 5, 4])
ec = np.array([1, 2, 3, 4, 5, 6])
c = setxor1d(a, b)
assert_array_equal(c, ec)
a = np.array([1, 8, 2, 3])
b = np.array([6, 5, 4, 8])
ec = np.array([1, 2, 3, 4, 5, 6])
c = setxor1d(a, b)
assert_array_equal(c, ec)
assert_array_equal([], setxor1d([], []))
def test_setxor1d(self):
a = np.array([5, 7, 1, 2])
b = np.array([2, 4, 3, 1, 5])
ec = np.array([3, 4, 7])
c = setxor1d(a, b)
assert_array_equal(c, ec)
a = np.array([1, 2, 3])
b = np.array([6, 5, 4])
ec = np.array([1, 2, 3, 4, 5, 6])
c = setxor1d(a, b)
assert_array_equal(c, ec)
a = np.array([1, 8, 2, 3])
b = np.array([6, 5, 4, 8])
ec = np.array([1, 2, 3, 4, 5, 6])
c = setxor1d(a, b)
assert_array_equal(c, ec)
assert_array_equal([], setxor1d([], []))
def RecursionTree(self, node, x, x_rows, y):
#没有节点
if len(x_rows) <= 0:
return
#叶子节点
if node.HasChildren() == False:
y[x_rows] = node.GetLabel()
# logger.debug('predict 获取标签:%d,x_rows:%s', node.GetLabel(),x_rows)
return
feature = node.GetSplitAttr()
rest_x_row = np.array(x_rows, dtype=np.int)
for (value, child) in node.GetChildren():
new_x_row = np.intersect1d(x_rows,
np.where(x[:, feature] == value)[0])
rest_x_row = arraysetops.setxor1d(rest_x_row, new_x_row, True)
self.RecursionTree(child, x, new_x_row, y)
#训练不充分导致测试集有未知数据不能向下划分预测
y[rest_x_row] = self.Classify(y, x_rows)
