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def game(word, max_guesses=10):
    '''Given a word and a guess limit, returns a
    coroutine for playing hangman.  Guess letters
    by sending messages to the coroutine.  Returns
    True if you win, False otherwise.
    
    Example
    >>> g = game('jazz', 10)
    >>> next(g) # prime the coroutine
    >>> g.send('e') # guess 'e'

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def predict_over_time(x, y, z, overlay=False):
    "Predicts a quantity at times = 0, 1, ... 14"
    out = np.zeros((x.shape[0], 15))
    for t in range(15):
        out[:, t] = t * x ** 2 + y - 2 * z - 2 * t
    adj = 1.5 if overlay else 1.0
    return adj * out

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from numba import jit


@jit
def jitted_func(x, y, z, overlay=False):
    "Predicts a quantity at times = 0, 1, ... 14"
    out = np.zeros((x.shape[0], 15))
    for t in range(15):
        out[:, t] = t * x ** 2 + y - 2 * z - 2 * t
    adj = 1.5 if overlay else 1.0

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from numba import guvectorize


@guvectorize('i8, f8, f8, b1, f8[:], f8[:]',
             '(), (), (), (), (s) -> (s)')
def fast_predict_over_time(x, y, z, overlay, _, out):
    adj = 1.5 if overlay else 1.0
    for t in range(len(out)):
        out[t] = adj * (t * x ** 2 + y - 2 * z - 2 * t)

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res = np.zeros((n, 15))

%%timeit -n 100
_ = fast_predict_over_time(x, y, z, False, res) # 100 loops, best of 3: 575 µs per loop