from sklearn.metrics import mean_squared_error
import numpy as np


def order_qty_rmse(actual, predicted):
    actu = []
    pred = []
    for i, a in enumerate(actual):
        if not a == 0:
            actu.append(actual[i])
            pred.append(predicted[i])
    return np.sqrt(mean_squared_error(actu, pred))