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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def bootstrap_noise(data, func, n=10000, std=1, symmetric=True):
 """ Bootstrap by adding noise """

    boot_dist = []
    arr = N.zeros(data.shape)
    for i in range(n):
        if symmetric:
            # Noise on all three axes
            arr = N.random.randn(*data.shape)*std
        else:
            # Only z-coordinate noise
            arr[:,-1] = N.random.randn(data.shape[0])*std
        boot_dist.append(func(data+arr))
    return N.array(boot_dist)