diff --git a/manimlib/mobject/functions.py b/manimlib/mobject/functions.py
index 6d55b395..adc9c455 100644
--- a/manimlib/mobject/functions.py
+++ b/manimlib/mobject/functions.py
@@ -11,38 +11,30 @@ from manimlib.utils.config_ops import digest_config
 from typing import TYPE_CHECKING
 
 if TYPE_CHECKING:
-    from typing import Callable, Sequence
+    from typing import Callable, Sequence, Tuple
+    from manimlib.constants import ManimColor, np_vector
 
 
 class ParametricCurve(VMobject):
-    CONFIG = {
-        "t_range": [0, 1, 0.1],
-        "epsilon": 1e-8,
-        # TODO, automatically figure out discontinuities
-        "discontinuities": [],
-        "use_smoothing": True,
-    }
-
     def __init__(
         self,
-        t_func: Callable[[float], np.ndarray],
-        t_range: Sequence[float] | None = None,
+        t_func: Callable[[float], Sequence[float]],
+        t_range: Tuple[float, float, float] = (0, 1, 0.1),
+        epsilon: float = 1e-8,
+        # TODO, automatically figure out discontinuities
+        discontinuities: Sequence[float] = [],
+        use_smoothing: bool = True,
         **kwargs
     ):
-        digest_config(self, kwargs)
-        if t_range is not None:
-            self.t_range[:len(t_range)] = t_range
-        # To be backward compatible with all the scenes specifying t_min, t_max, step_size
-        self.t_range = [
-            kwargs.get("t_min", self.t_range[0]),
-            kwargs.get("t_max", self.t_range[1]),
-            kwargs.get("step_size", self.t_range[2]),
-        ]
         self.t_func = t_func
-        VMobject.__init__(self, **kwargs)
+        self.t_range = t_range
+        self.epsilon = epsilon
+        self.discontinuities = discontinuities
+        self.use_smoothing = use_smoothing
+        super().__init__(**kwargs)
 
-    def get_point_from_function(self, t: float) -> np.ndarray:
-        return self.t_func(t)
+    def get_point_from_function(self, t: float) -> np_vector:
+        return np.array(self.t_func(t))
 
     def init_points(self):
         t_min, t_max, step = self.t_range
@@ -59,7 +51,7 @@ class ParametricCurve(VMobject):
         if self.use_smoothing:
             self.make_approximately_smooth()
         if not self.has_points():
-            self.set_points([self.t_func(t_min)])
+            self.set_points(np.array([self.t_func(t_min)]))
         return self
 
     def get_t_func(self):
@@ -77,22 +69,15 @@ class ParametricCurve(VMobject):
 
 
 class FunctionGraph(ParametricCurve):
-    CONFIG = {
-        "color": YELLOW,
-        "x_range": [-8, 8, 0.25],
-    }
-
     def __init__(
         self,
         function: Callable[[float], float],
-        x_range: Sequence[float] | None = None,
+        x_range: Tuple[float, float, float] = (-8, 8, 0.25),
+        color: ManimColor = YELLOW,
         **kwargs
     ):
-        digest_config(self, kwargs)
         self.function = function
-
-        if x_range is not None:
-            self.x_range[:len(x_range)] = x_range
+        self.x_range = x_range
 
         def parametric_function(t):
             return [t, function(t), 0]
@@ -101,34 +86,28 @@ class FunctionGraph(ParametricCurve):
 
 
 class ImplicitFunction(VMobject):
-    CONFIG = {
-        "x_range": [-FRAME_X_RADIUS, FRAME_X_RADIUS],
-        "y_range": [-FRAME_Y_RADIUS, FRAME_Y_RADIUS],
-        "min_depth": 5,
-        "max_quads": 1500,
-        "use_smoothing": True
-    }
-
     def __init__(
         self,
         func: Callable[[float, float], float],
+        x_range: Tuple[float, float] = (-FRAME_X_RADIUS, FRAME_X_RADIUS),
+        y_range: Tuple[float, float] = (-FRAME_Y_RADIUS, FRAME_Y_RADIUS),
+        min_depth: int = 5,
+        max_quads: int = 1500,
+        use_smoothing: bool = True,
         **kwargs
     ):
-        digest_config(self, kwargs)
-        self.function = func
         super().__init__(**kwargs)
 
-    def init_points(self):
         p_min, p_max = (
-            np.array([self.x_range[0], self.y_range[0]]),
-            np.array([self.x_range[1], self.y_range[1]]),
+            np.array([x_range[0], y_range[0]]),
+            np.array([x_range[1], y_range[1]]),
         )
         curves = plot_isoline(
-            fn=lambda u: self.function(u[0], u[1]),
+            fn=lambda u: func(u[0], u[1]),
             pmin=p_min,
             pmax=p_max,
-            min_depth=self.min_depth,
-            max_quads=self.max_quads,
+            min_depth=min_depth,
+            max_quads=max_quads,
         )  # returns a list of lists of 2D points
         curves = [
             np.pad(curve, [(0, 0), (0, 1)]) for curve in curves if curve != []
@@ -136,6 +115,5 @@ class ImplicitFunction(VMobject):
         for curve in curves:
             self.start_new_path(curve[0])
             self.add_points_as_corners(curve[1:])
-        if self.use_smoothing:
+        if use_smoothing:
             self.make_smooth()
-        return self