





from .balanced_parentheses import balanced_parentheses
from .stack import Stack





def 							__lowerCAmelCase(					_SCREAMING_SNAKE_CASE							)       ->   int:




    """simple docstring"""




    return {"+": 1, "-": 1, "*": 2, "/": 2, "^": 3}.get(_SCREAMING_SNAKE_CASE       ,    -1							)





def 							__lowerCAmelCase(					_SCREAMING_SNAKE_CASE							)       ->   str:




    """simple docstring"""




    if not balanced_parentheses(_SCREAMING_SNAKE_CASE							):
        raise ValueError('Mismatched parentheses'							)
    _A    =       Stack()
    _A    =       []
    for char in expression_str:
        if char.isalpha() or char.isdigit():
            postfix.append(_SCREAMING_SNAKE_CASE							)
        elif char == "(":
            stack.push(_SCREAMING_SNAKE_CASE							)
        elif char == ")":
            while not stack.is_empty() and stack.peek() != "(":
                postfix.append(stack.pop()							)
            stack.pop()
        else:
            while not stack.is_empty() and precedence(_SCREAMING_SNAKE_CASE							) <= precedence(stack.peek()							):
                postfix.append(stack.pop()							)
            stack.push(_SCREAMING_SNAKE_CASE							)
    while not stack.is_empty():
        postfix.append(stack.pop()							)
    return " ".join(_SCREAMING_SNAKE_CASE							)


if __name__ == "__main__":
       from doctest import testmod

       testmod()
       __A       : Optional[int]						    = "a+b*(c^d-e)^(f+g*h)-i"

       print("Infix to Postfix Notation demonstration:\n")
       print("Infix notation: " + expression)
       print("Postfix notation: " + infix_to_postfix(expression))












import numpy as np





def 							__lowerCAmelCase(					_SCREAMING_SNAKE_CASE       ,    _SCREAMING_SNAKE_CASE							)       ->   List[Any]:




    """simple docstring"""




    _A    =       np.array(_SCREAMING_SNAKE_CASE							)
    _A    =       np.array(_SCREAMING_SNAKE_CASE							)

    _A    =       abs(predict - actual							)
    _A    =       difference.mean()

    return score





def 							__lowerCAmelCase(					_SCREAMING_SNAKE_CASE       ,    _SCREAMING_SNAKE_CASE							)       ->   Optional[int]:




    """simple docstring"""




    _A    =       np.array(_SCREAMING_SNAKE_CASE							)
    _A    =       np.array(_SCREAMING_SNAKE_CASE							)

    _A    =       predict - actual
    _A    =       np.square(_SCREAMING_SNAKE_CASE							)

    _A    =       square_diff.mean()
    return score





def 							__lowerCAmelCase(					_SCREAMING_SNAKE_CASE       ,    _SCREAMING_SNAKE_CASE							)       ->   Tuple:




    """simple docstring"""




    _A    =       np.array(_SCREAMING_SNAKE_CASE							)
    _A    =       np.array(_SCREAMING_SNAKE_CASE							)

    _A    =       predict - actual
    _A    =       np.square(_SCREAMING_SNAKE_CASE							)
    _A    =       square_diff.mean()
    _A    =       np.sqrt(_SCREAMING_SNAKE_CASE							)
    return score





def 							__lowerCAmelCase(					_SCREAMING_SNAKE_CASE       ,    _SCREAMING_SNAKE_CASE							)       ->   List[Any]:




    """simple docstring"""




    _A    =       np.array(_SCREAMING_SNAKE_CASE							)
    _A    =       np.array(_SCREAMING_SNAKE_CASE							)

    _A    =       np.log(predict + 1							)
    _A    =       np.log(actual + 1							)

    _A    =       log_predict - log_actual
    _A    =       np.square(_SCREAMING_SNAKE_CASE							)
    _A    =       square_diff.mean()

    _A    =       np.sqrt(_SCREAMING_SNAKE_CASE							)

    return score





def 							__lowerCAmelCase(					_SCREAMING_SNAKE_CASE       ,    _SCREAMING_SNAKE_CASE							)       ->   Optional[int]:




    """simple docstring"""




    _A    =       np.array(_SCREAMING_SNAKE_CASE							)
    _A    =       np.array(_SCREAMING_SNAKE_CASE							)

    _A    =       predict - actual
    _A    =       np.sum(_SCREAMING_SNAKE_CASE							) / len(_SCREAMING_SNAKE_CASE							)
    _A    =       np.sum(_SCREAMING_SNAKE_CASE							) / len(_SCREAMING_SNAKE_CASE							)
    # print(numerator, denumerator)
    _A    =       float(_SCREAMING_SNAKE_CASE							) / denumerator * 100

    return score





def 							__lowerCAmelCase(					_SCREAMING_SNAKE_CASE       ,    _SCREAMING_SNAKE_CASE							)       ->   Dict:




    """simple docstring"""




    return np.mean(np.array(_SCREAMING_SNAKE_CASE							) == np.array(_SCREAMING_SNAKE_CASE							)							)





