diff --git a/mbcp/mp_math/equation.py b/mbcp/mp_math/equation.py
index 85ab9aa..35e5be7 100644
--- a/mbcp/mp_math/equation.py
+++ b/mbcp/mp_math/equation.py
@@ -9,7 +9,7 @@ Copyright (C) 2020-2024 LiteyukiStudio. All Rights Reserved
 @Software: PyCharm
 """
 
-from mbcp.mp_math.mp_math_typing import OneVarFunc, Var, MultiVarFunc, Number
+from mbcp.mp_math.mp_math_typing import OneVarFunc, Var, MultiVarsFunc, Number
 from mbcp.mp_math.point import Point3
 from mbcp.mp_math.const import EPSILON
 
@@ -44,9 +44,9 @@ class CurveEquation:
         return "CurveEquation()"
 
 
-def get_partial_derivative_func(func: MultiVarFunc, var: int | tuple[int, ...], epsilon: Number = EPSILON) -> MultiVarFunc:
+def get_partial_derivative_func(func: MultiVarsFunc, var: int | tuple[int, ...], epsilon: Number = EPSILON) -> MultiVarsFunc:
     """
-    求N元函数偏导函数。
+    求N元函数一阶偏导函数。
     Args:
         func: 函数
         var: 变量位置，可为整数(一阶偏导)或整数元组(高阶偏导)
@@ -64,7 +64,9 @@ def get_partial_derivative_func(func: MultiVarFunc, var: int | tuple[int, ...],
         return partial_derivative_func
     elif isinstance(var, tuple):
         for i in var:
+            print("测试第i个变量：", i)
             func = get_partial_derivative_func(func, i, epsilon)
+            print("测试第i个变量的偏导：", func(1, 2))
         return func
     else:
         raise ValueError("Invalid var type")
diff --git a/mbcp/mp_math/mp_math_typing.py b/mbcp/mp_math/mp_math_typing.py
index 1acc84d..c7285c3 100644
--- a/mbcp/mp_math/mp_math_typing.py
+++ b/mbcp/mp_math/mp_math_typing.py
@@ -20,14 +20,14 @@ OneSingleVarFunc: TypeAlias = Callable[[SingleVar], SingleVar]
 OneArrayFunc: TypeAlias = Callable[[ArrayVar], ArrayVar]
 OneVarFunc: TypeAlias = OneSingleVarFunc | OneArrayFunc
 
-TwoSingleVarFunc: TypeAlias = Callable[[SingleVar, SingleVar], SingleVar]
-TwoArrayFunc: TypeAlias = Callable[[ArrayVar, ArrayVar], ArrayVar]
-TwoVarFunc: TypeAlias = TwoSingleVarFunc | TwoArrayFunc
+TwoSingleVarsFunc: TypeAlias = Callable[[SingleVar, SingleVar], SingleVar]
+TwoArraysFunc: TypeAlias = Callable[[ArrayVar, ArrayVar], ArrayVar]
+TwoVarsFunc: TypeAlias = TwoSingleVarsFunc | TwoArraysFunc
 
-ThreeSingleVarFunc: TypeAlias = Callable[[SingleVar, SingleVar, SingleVar], SingleVar]
-ThreeArrayFunc: TypeAlias = Callable[[ArrayVar, ArrayVar, ArrayVar], ArrayVar]
-ThreeVarFunc: TypeAlias = ThreeSingleVarFunc | ThreeArrayFunc
+ThreeSingleVarsFunc: TypeAlias = Callable[[SingleVar, SingleVar, SingleVar], SingleVar]
+ThreeArraysFunc: TypeAlias = Callable[[ArrayVar, ArrayVar, ArrayVar], ArrayVar]
+ThreeVarsFunc: TypeAlias = ThreeSingleVarsFunc | ThreeArraysFunc
 
-MultiSingleVarFunc: TypeAlias = Callable[..., SingleVar]
-MultiArrayFunc: TypeAlias = Callable[..., ArrayVar]
-MultiVarFunc: TypeAlias = MultiSingleVarFunc | MultiArrayFunc
+MultiSingleVarsFunc: TypeAlias = Callable[..., SingleVar]
+MultiArraysFunc: TypeAlias = Callable[..., ArrayVar]
+MultiVarsFunc: TypeAlias = MultiSingleVarsFunc | MultiArraysFunc
diff --git a/tests/test_partial_derivative.py b/tests/test_partial_derivative.py
index 6afe85e..37896d0 100644
--- a/tests/test_partial_derivative.py
+++ b/tests/test_partial_derivative.py
@@ -20,7 +20,7 @@ class TestPartialDerivative:
         from mbcp.mp_math.utils import Approx
         from mbcp.mp_math.equation import get_partial_derivative_func
 
-        partial_derivative_func = get_partial_derivative_func(three_var_func, (0,))
+        partial_derivative_func = get_partial_derivative_func(three_var_func, 0)
 
         # assert partial_derivative_func(1, 2, 3) == 4.0
         def df_dx(x, y):