added more nodes

src/more_math/ImageMathNode.py

@@ -0,0 +1,118 @@
+from inspect import cleandoc
+from math import e
+
+import torch
+
+from .helperFunc import evaluate_tensor_expression, to_tensor, tokenize_expression
+from .parser import Parser
+
+
+class ImageMathNode:
+    """
+    This node enables the use of math expressions on Latents.
+    INPUTS:
+        a, b, c, d:
+            Latent, bound to variables with the same name. Defaults to zero latent if not provided.
+        w, x, y, z:
+            Floats, bound to variables of the expression. Defaults to 0.0 if not provided.
+        Tensor expression:
+            String, describing expression to mix latents. Valid functions are sin, cos, tan, abs, sqrt, min, max, norm. Valid operators are +, -, *, /, ^, %.
+        
+    OUTPUTS:
+        LATENT:
+            Returns a LATENT object that contains the result of the math expression applied to the input conditionings.
+    """
+    def __init__(self):
+        pass
+
+    @classmethod
+    def INPUT_TYPES(s):
+        """
+        """
+        return {
+            "required": {
+                "a": ("IMAGE", {
+
+                }),
+
+                "Tensor": ("STRING", {
+                    "multiline": False, #True if you want the field to look like the one on the ClipTextEncode node
+                    "default": "a*(1-w)+b*w",
+                    "description": "Describes composition of the image. Valid functions are sin,cos,tan,abs,sqrt,min,max. Valid operators are +,-,*,/,^,%"
+
+                }),
+            },
+            "optional": {
+                "b": ("IMAGE", {
+                    "default": 0,
+                }),
+                "c": ("IMAGE", {
+                    "default": 0,
+                }),
+                "d": ("IMAGE", {
+                    "default": 0,
+                }),
+                "w": ("FLOAT", {
+                    "default": 0,
+                    "forceInput":True
+                }),
+                "x": ("FLOAT", {
+                    "default": 0,
+                    "forceInput":True
+                }),
+                "y": ("FLOAT", {
+                    "default": 0,
+                    "forceInput":True
+                }),
+                "z": ("FLOAT", {
+                    "default": 0,
+                    "forceInput":True
+                }),
+
+
+                # "int_field": ("INT", {"default": 0, "min": 0, "max": 100, "step": 1}),
+                # "float_field": ("FLOAT", {"default": 0.5, "min": -10.0, "max": 10.0, "step": 0.001}),
+            }
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    #RETURN_NAMES = ("image_output_name",)
+    DESCRIPTION = cleandoc(__doc__)
+    FUNCTION = "imgMathNode"
+
+    #OUTPUT_NODE = False
+    #OUTPUT_TOOLTIPS = ("",) # Tooltips for the output node
+
+    CATEGORY = "More math"
+
+    def imgMathNode(self, Tensor, a, b=None, c=None, d=None, w=0.0, x=0.0, y=0.0, z=0.0):
+        b = torch.zeros_like(a) if b is None else b
+        c = torch.zeros_like(a) if c is None else c
+        d = torch.zeros_like(a) if d is None else d
+
+        tokens = tokenize_expression(Tensor)
+        parser = Parser(tokens)
+        ast = parser.parse_expression()
+        print(a.shape)
+        print("AST:", ast)
+
+        result1 = evaluate_tensor_expression(
+            ast, {'a': a, 'b': b, 'c': c, 'd': d, 'w': w, 'x': x, 'y': y, 'z': z}
+        )
+
+        result = to_tensor(result1, a)
+
+        print("Result:", result)
+        return (result,)
+
+    """
+        The node will always be re executed if any of the inputs change but
+        this method can be used to force the node to execute again even when the inputs don't change.
+        You can make this node return a number or a string. This value will be compared to the one returned the last time the node was
+        executed, if it is different the node will be executed again.
+        This method is used in the core repo for the LoadImage node where they return the image hash as a string, if the image hash
+        changes between executions the LoadImage node is executed again.
+    """
+    #@classmethod
+    #def IS_CHANGED(s, image, string_field, int_field, float_field, print_to_screen):
+    #    return ""