diff --git a/nodes/batch.py b/nodes/batch.py
index 1d4abc1..d301a84 100644
--- a/nodes/batch.py
+++ b/nodes/batch.py
@@ -206,8 +206,8 @@ class BatchFloat:
                     {"default": "Steps"},
                 ),
                 "count": ("INT", {"default": 1}),
-                "min": ("FLOAT", {"default": 0.0}),
-                "max": ("FLOAT", {"default": 1.0}),
+                "min": ("FLOAT", {"default": 0.0, "step": 0.001}),
+                "max": ("FLOAT", {"default": 1.0, "step": 0.001}),
                 "easing": (
                     [
                         "Linear",
@@ -276,7 +276,7 @@ class BatchMerge:
     FUNCTION = "merge_batches"
     CATEGORY = "mtb/batch"
 
-    def merge_batches(self, fusion_mode, fill, **kwargs):
+    def merge_batches(self, fusion_mode: str, fill: str, **kwargs):
         images = kwargs.values()
         max_frames = max(img.shape[0] for img in images)
 
@@ -340,9 +340,12 @@ class Batch2dTransform:
     FUNCTION = "transform_batch"
     CATEGORY = "mtb/batch"
 
-    def get_num_elements(self, param) -> int:
+    def get_num_elements(
+        self, param: None | torch.Tensor | list[torch.Tensor] | list[float]
+    ) -> int:
         if isinstance(param, torch.Tensor):
             return torch.numel(param)
+
         elif isinstance(param, list):
             return len(param)
 
@@ -351,13 +354,13 @@ class Batch2dTransform:
     def transform_batch(
         self,
         image: torch.Tensor,
-        border_handling,
-        constant_color,
-        x=None,
-        y=None,
-        zoom=None,
-        angle=None,
-        shear=None,
+        border_handling: str,
+        constant_color: str,
+        x: list[float] | None = None,
+        y: list[float] | None = None,
+        zoom: list[float] | None = None,
+        angle: list[float] | None = None,
+        shear: list[float] | None = None,
     ):
         if all(
             self.get_num_elements(param) <= 0
@@ -367,19 +370,25 @@ class Batch2dTransform:
                 "At least one transform parameter must be provided"
             )
 
-        keyframes = {"x": [], "y": [], "zoom": [], "angle": [], "shear": []}
+        keyframes: dict[str, list[float]] = {
+            "x": [],
+            "y": [],
+            "zoom": [],
+            "angle": [],
+            "shear": [],
+        }
 
         default_vals = {"x": 0, "y": 0, "zoom": 1.0, "angle": 0, "shear": 0}
 
-        if self.get_num_elements(x) > 0:
+        if x and self.get_num_elements(x) > 0:
             keyframes["x"] = x
-        if self.get_num_elements(y) > 0:
+        if y and self.get_num_elements(y) > 0:
             keyframes["y"] = y
-        if self.get_num_elements(zoom) > 0:
+        if zoom and self.get_num_elements(zoom) > 0:
             keyframes["zoom"] = zoom
-        if self.get_num_elements(angle) > 0:
+        if angle and self.get_num_elements(angle) > 0:
             keyframes["angle"] = angle
-        if self.get_num_elements(shear) > 0:
+        if shear and self.get_num_elements(shear) > 0:
             keyframes["shear"] = shear
 
         for name, values in keyframes.items():
@@ -585,10 +594,12 @@ class BatchShake:
             interpolant: The interpolation function, defaults to
                 t*t*t*(t*(t*6 - 15) + 10).
 
-        Returns:
+        Returns
+        -------
             A numpy array of shape shape with the generated noise.
 
-        Raises:
+        Raises
+        ------
             ValueError: If shape is not a multiple of res.
         """
         interpolant = interpolant or DEFAULT_INTERPOLANT
@@ -651,11 +662,13 @@ class BatchShake:
             interpolant: The, interpolation function, defaults to
                 t*t*t*(t*(t*6 - 15) + 10).
 
-        Returns:
+        Returns
+        -------
             A numpy array of fractal noise and of shape shape generated by
             combining several octaves of perlin noise.
 
-        Raises:
+        Raises
+        ------
             ValueError: If shape is not a multiple of
                 (lacunarity**(octaves-1)*res).
         """