Difference between the my own implementation of explained variance and scikit-learn's

variance_explained.py

from sklearn.metrics import explained_variance_score

def var_explained(preds, actual):
    """
    Implementation taken directly from the formula on this page:
    http://scikit-learn.org/stable/modules/model_evaluation.html#explained-variance-score
    """
    return 1 - ((preds - actual).var() / actual.var())

y_pred = np.array([3, -0.5, 2, 7])
y_actual = np.array([2.5, 0.0, 2, 8])
var_explained(y_pred, y_actual)             # 0.9644760213143873
explained_variance_score(y_pred, y_actual)  # 0.9571734475374732