import numpy as np

def compute_slope(series):
    if len(series) < 2:
        return 0.0
    x = np.arange(len(series))
    y = np.array(series)
    return float(np.polyfit(x, y, 1)[0])


def classify_trend(slope, threshold=0.001):
    if slope > threshold:
        return "hausse"
    elif slope < -threshold:
        return "baisse"
    return "stable"


def project_series(series, horizon):
    if len(series) < 2:
        return series

    x = np.arange(len(series))
    slope, intercept = np.polyfit(x, series, 1)

    future_x = np.arange(len(series) + horizon)
    return list(slope * future_x + intercept)


def time_to_threshold(series, threshold):
    slope = compute_slope(series)
    current = series[-1]

    if slope <= 0:
        return None

    t = (threshold - current) / slope

    if t < 0:
        return None

    return int(t)