diff --git a/src/nodes/float_image_combine.py b/src/nodes/float_image_combine.py
deleted file mode 100644
index 967b10a..0000000
--- a/src/nodes/float_image_combine.py
+++ /dev/null
@@ -1,23 +0,0 @@
-import typing as t
-
-from ..base import BasePlotNode, Image
-
-
-class FloatImageCombineNode(BasePlotNode):
-    RETURN_TYPES: t.Tuple[str] = ("IMAGES",)
-
-    @classmethod
-    def INPUT_TYPES(cls) -> t.Dict[str, t.Any]:
-        return {
-            "required": {
-                "float_image_1": ("IMAGES",),
-                "float_image_2": ("IMAGES",),
-            },
-        }
-
-    def execute(
-        self,
-        float_image_1: t.List[Image],
-        float_image_2: t.List[Image],
-    ) -> t.Tuple[t.List[Image]]:
-        return (float_image_1 + float_image_2,)
diff --git a/src/nodes/image_set_area.py b/src/nodes/image_set_area.py
deleted file mode 100644
index 41355d1..0000000
--- a/src/nodes/image_set_area.py
+++ /dev/null
@@ -1,18 +0,0 @@
-import typing as t
-
-from ..base import BasePlotNode, Image
-
-
-class ImageSetAreaNode(BasePlotNode):
-    RETURN_TYPES: t.Tuple[str] = ("IMAGES",)
-
-    @classmethod
-    def INPUT_TYPES(cls) -> t.Dict[str, t.Any]:
-        return {
-            "required": {
-                "image": ("IMAGE",),
-            },
-        }
-
-    def execute(self, image: Image) -> t.Tuple[t.List[Image]]:
-        return ([image],)
diff --git a/src/nodes/k_sampler_xy_plot.py b/src/nodes/k_sampler_xy_plot.py
deleted file mode 100644
index e4c52eb..0000000
--- a/src/nodes/k_sampler_xy_plot.py
+++ /dev/null
@@ -1,62 +0,0 @@
-import typing as t
-
-from nodes import KSamplerAdvanced  # type: ignore
-
-from ..base import BasePlotNode, Image, KSamplerXYPlotInput
-
-
-class KSamplerXYPlotNode(BasePlotNode):
-    RETURN_TYPES: t.Tuple[str] = ("IMAGES",)
-
-    def __init__(self) -> None:
-        self._sampler = KSamplerAdvanced()
-
-    @classmethod
-    def INPUT_TYPES(cls):
-        result = KSamplerAdvanced.INPUT_TYPES()
-        result["required"]["vae"] = ("VAE", )
-        #result["required"]["x_items"] = ("XYPlotItem",)
-        #result["required"]["y_items"] = ("XYPlotItem",)
-        return result
-
-    def execute(
-        self,
-        vae,
-        #x_items,
-        #y_items,
-        **sampler_kw,
-    ) -> tuple[t.List[Image]]:
-        x_items = [
-            KSamplerXYPlotInput(value=1, setting="cfg"),
-            KSamplerXYPlotInput(value=2, setting="cfg"),
-        ]
-        y_items = [
-            KSamplerXYPlotInput(value=1, setting="noise_seed"),
-            KSamplerXYPlotInput(value=2, setting="noise_seed"),
-        ]
-
-        latents = self._sample_latents(
-            x_items=x_items,
-            y_items=y_items,
-            sampler_kw=sampler_kw,
-        )
-        result = list(self._decode_latents(latents=latents, vae=vae))
-        print(result)
-        print(type(result[0]))
-
-        return (result,)
-
-    def _sample_latents(self, x_items, y_items, sampler_kw):
-        for x in x_items:
-            for y in y_items:
-                sampler_settings = sampler_kw.copy()
-                sampler_settings[x.setting] = x.value
-                sampler_settings[y.setting] = y.value
-
-                yield self._sampler.sample(**sampler_settings)[0]
-
-    def _decode_latents(self, latents, vae) -> t.Iterable[Image]:
-        return (
-            vae.decode(i["samples"])
-            for i in latents
-        )
diff --git a/src/nodes/xy_plot.py b/src/nodes/xy_plot.py
index 94ecbc9..f63cc00 100644
--- a/src/nodes/xy_plot.py
+++ b/src/nodes/xy_plot.py
@@ -13,18 +13,18 @@ class XYPlotNode(BasePlotNode):
             "required": {
                 "images": ("IMAGE",),
                 "gap": ("INT", {"default": 0, "min": 0}),
-                "nrow": ("INT", {"default": 1, "min": 1}),
+                "ncol": ("INT", {"default": 1, "min": 1}),
             },
         }
 
     def execute(
         self,
         images: Image,
-        nrow: int,
+        ncol: int,
         gap: int
     ) -> tuple[Image]:
         pillow_images = [tensor_to_pillow(i) for i in images]
-        pillow_grid = create_image_grid(pillow_images, nrow=nrow, gap=gap)
+        pillow_grid = create_image_grid(pillow_images, ncol=ncol, gap=gap)
         tensor_grid = pillow_to_tensor(pillow_grid)
 
         return (tensor_grid,)