idth

    # Build quantile interval matrix
    cols = np.arange(lower_min,
                     lower_min + max_dropout_fraction + step_sizes[0] * 1e-9,
                     step_sizes[0])
    cols = np.round(n * cols).astype(int)
    rows = np.arange(0, int(np.round(n * max_width)))
    newX = np.zeros((len(rows), len(cols)))
    for i, c in enumerate(range(len(rows))):
        newX[i] = X[c + cols]

    # subtract baseline value for each interval
    X1 = newX[0, :]
    newX = newX - X1

    opt_val = np.