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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 _matrix_integration(q, h, t):
    ''' Returns the dp metric for a single horsetail
    curve at a given value of the epistemic uncertainties'''

    N = len(q)

    # correction if CDF has gone out of trapezium range
    if h[-1] < 0.9: h[-1] = 1.0

    W = np.zeros([N, N])
    for i in range(N):
        W[i, i] = 0.5*(h[min(i+1, N-1)] - h[max(i-1, 0)])

    dp = (q - t).T.dot(W).dot(q - t)

    return dp