import numpy as np
def calc_upper(c: int, m: float, b: float, period: float) -> float:
    return np.floor(c / period) * period * m + b

def calc_lower(c: int, m: float, b: float, period: float) -> float:
    return np.ceil(c / period) * period * m + b

def calc_mean(c:int , m_u: float, b_u: float, m_l: float, b_l: float, period: float) -> float:
    return (calc_upper(c, m_u, b_u, period) + calc_lower(c, m_l, b_l, period)) / 2


def calc_rect(c:int , m_u: float, b_u: float, m_l: float, b_l: float, step_period: float, rect_period: float) -> float:
    if ((c - 1) % rect_period) < 4:
        return calc_upper(c, m_u, b_u, step_period)
    else:
        return calc_lower(c, m_l, b_l, step_period)


def lin_interpol(x0:float, x1:float, y0:float, y1:float) -> (float, float):
    m = (y1 - y0) / (x1 - x0)
    b = y1 - m * x1
    return m, b

def calculate_deltas(sweep:list[float]):
    deltas = []
    lv = sweep[0]
    for meas in list(sweep)[1:]:
        deltas.append((meas / lv))
        lv = meas
    return deltas

def compute_absolute_percentage_errors(measurements: list[float], guesses: list[float]):
    return [np.abs((guess - meas) / meas) * 100 for guess, meas in zip(guesses, measurements)]