

def _generate_high_dimensional_output(D1, D2, D3, s1, s2, s3, sS):
    S1 = _np.hstack([s1, sS])
    S2 = _np.hstack([s2, s3, sS])
    S3 = _np.hstack([s3, sS])
    Y1 = S1.dot(_np.random.randn(S1.shape[1], D1))
    Y2 = S2.dot(_np.random.randn(S2.shape[1], D2))
    Y3 = S3.dot(_np.random.randn(S3.shape[1], D3))
    Y1 += (0.3 * _np.random.randn(*Y1.shape))
    Y2 += (0.2 * _np.random.randn(*Y2.shape))
    Y3 += (0.25 * _np.random.randn(*Y3.shape))
    Y1 -= Y1.mean(0)
    Y2 -= Y2.mean(0)
    Y3 -= Y3.mean(0)
    Y1 /= Y1.std(0)
    Y2 /= Y2.std(0)
    Y3 /= Y3.std(0)
    return (Y1, Y2, Y3, S1, S2, S3)

dataset/ETHPy150Open SheffieldML/GPy/GPy/examples/dimensionality_reduction.py _generate_high_dimensional_output/original