114 lines
2.1 KiB
Python
114 lines
2.1 KiB
Python
from dataclasses import dataclass
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import numpy as np
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from .types import FunctionType, OperatorType, ValueType
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# Additional functions that are not defined in numpy
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def acot(x: ValueType):
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return np.arctan(1 / x)
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def cot(x: ValueType):
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return 1 / np.tan(x)
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# Function and operation names to evaluators mapping
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functions: dict[str, FunctionType] = {
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"abs": np.abs,
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"acos": np.arccos,
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"acosh": np.arccosh,
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"acot": acot,
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"asin": np.arcsin,
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"asinh": np.arcsinh,
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"atan": np.arctan,
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"avg": np.average,
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"cos": np.cos,
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"cosh": np.cosh,
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"cot": cot,
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"exp": np.exp,
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"inf": np.inf,
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"lg": np.log10,
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"ln": np.log,
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"log10": np.log10,
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"log2": np.log2,
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"max": np.max,
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"min": np.min,
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"prod": np.prod,
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"sgn": np.sign,
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"sign": np.sign,
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"sin": np.sin,
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"sinh": np.sinh,
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"sqrt": np.sqrt,
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"sum": np.sum,
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"sup": np.max,
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"tanh": np.tanh,
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"tan": np.tan,
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}
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operators: dict[str, OperatorType] = {
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"+": np.add,
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"-": np.subtract,
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"*": np.multiply,
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"/": np.divide,
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"%": np.mod,
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"^": np.float_power,
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}
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priorities: dict[str, int] = {
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"(": 0,
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"+": 1,
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"-": 1,
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"*": 2,
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"/": 2,
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"%": 2,
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"^": 3,
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"f": 4, # function
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")": 5,
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}
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@dataclass
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class Operation:
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"""
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Base class for math operation token (function, brace, operator).
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It stores the way it is evaluated, evaluation priority and number
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of arguments it supports.
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"""
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evaluator: (FunctionType | OperatorType | str)
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priority: int
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size: int
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class FunctionOperation(Operation):
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"""
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`Operator` class factory that represents function
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"""
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def __init__(self, name: str):
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super().__init__(functions[name], priorities["f"], 1)
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class BraceOperation(Operation):
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"""
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`Operator` class factory that represents brace
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"""
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def __init__(self, name: str):
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super().__init__(name, priorities[name], 0)
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class OperatorOperation(Operation):
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"""
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`Operator` class factory that represents binary operator
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"""
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def __init__(self, name: str):
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super().__init__(operators[name], priorities[name], 2)
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