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import math |
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from evalidate import Expr, EvalException, base_eval_model |
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from .categories import * |
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from .err import on_error |
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from .shared import hashed_as_strings |
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class DreamCalculation: |
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NODE_NAME = "Calculation" |
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ICON = "🖩" |
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@classmethod |
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def INPUT_TYPES(cls): |
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return { |
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"required": { |
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"expression": ("STRING", {"default": "a + b + c - (r * s * t)", "multiline": True}) |
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}, |
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"optional": { |
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"a_int": ("INT", {"default": 0, "multiline": False}), |
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"b_int": ("INT", {"default": 0, "multiline": False}), |
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"c_int": ("INT", {"default": 0, "multiline": False}), |
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"r_float": ("FLOAT", {"default": 0.0, "multiline": False}), |
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"s_float": ("FLOAT", {"default": 0.0, "multiline": False}), |
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"t_float": ("FLOAT", {"default": 0.0, "multiline": False}) |
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} |
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} |
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CATEGORY = NodeCategories.UTILS |
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RETURN_TYPES = ("FLOAT", "INT") |
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RETURN_NAMES = ("FLOAT", "INT") |
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FUNCTION = "result" |
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@classmethod |
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def IS_CHANGED(cls, *values): |
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return hashed_as_strings(*values) |
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def _make_model(self): |
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funcs = self._make_functions() |
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m = base_eval_model.clone() |
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m.nodes.append('Mult') |
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m.nodes.append('Call') |
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for funname in funcs.keys(): |
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m.allowed_functions.append(funname) |
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return (m, funcs) |
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def _make_functions(self): |
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return { |
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"round": round, |
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"float": float, |
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"int": int, |
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"abs": abs, |
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"min": min, |
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"max": max, |
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"tan": math.tan, |
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"tanh": math.tanh, |
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"sin": math.sin, |
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"sinh": math.sinh, |
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"cos": math.cos, |
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"cosh": math.cosh, |
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"pow": math.pow, |
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"sqrt": math.sqrt, |
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"ceil": math.ceil, |
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"floor": math.floor, |
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"pi": math.pi, |
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"log": math.log, |
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"log2": math.log2, |
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"acos": math.acos, |
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"asin": math.asin, |
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"acosh": math.acosh, |
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"asinh": math.asinh, |
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"atan": math.atan, |
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"atanh": math.atanh, |
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"exp": math.exp, |
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"fmod": math.fmod, |
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"factorial": math.factorial, |
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"dist": math.dist, |
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"atan2": math.atan2, |
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"log10": math.log10 |
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} |
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def result(self, expression, **values): |
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model, funcs = self._make_model() |
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vars = funcs |
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for key in ("a_int", "b_int", "c_int", "r_float", "s_float", "t_float"): |
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nm = key.split("_")[0] |
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v = values.get(key, None) |
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if v is not None: |
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vars[nm] = v |
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try: |
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data = Expr(expression, model=model).eval(vars) |
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if isinstance(data, (int, float)): |
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return float(data), int(round(data)) |
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else: |
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return 0.0, 0 |
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except EvalException as e: |
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on_error(DreamCalculation, str(e)) |
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