def test_compression_average2(): partition = (10,5) tod = np.empty((2,15), float) tod[0,:] = [1,1,1,1,1,3,3,3,3,3,4,4,4,4,4] tod[1,:] = [1,2,1.,0.5,0.5,5,0,0,0,0,1,2,1,2,1.5] compression = CompressionAverageOperator(5, partitionin=partition) tod2 = compression(tod) assert tod2.shape == (2,3) assert_equal(tod2, [[1.,3.,4.],[1.,1.,1.5]]) tod3 = compression.T(tod2) assert tod3.shape == (2,15) assert_almost_equal(tod3[0,:], (0.2,0.2,0.2,0.2,0.2,0.6,0.6,0.6,0.6,0.6,0.8,0.8,0.8,0.8,0.8)) tod = np.array([1,2,2,3,3,3,4,4,4,4]) compression = CompressionAverageOperator([1,2,3,4], partitionin=[1,2,3,4]) tod2 = compression(tod) assert_almost_equal(tod2, [1,2,3,4]) tod3 = compression.T(tod2) assert_almost_equal(tod3, 10*[1])
def test_compression_average1(): data = np.array([1., 2., 2., 3.]) compression = CompressionAverageOperator(2) compressed = compression(data) assert_equal(compressed, [1.5, 2.5]) assert_equal(compression.T(compressed), [0.75, 0.75, 1.25, 1.25])
def test_downsampling2(): a = CompressionAverageOperator(3) assert_almost_equal(a.todense(9).T, a.T.todense(3))
def test_compression_average3(): a = CompressionAverageOperator(3) assert_almost_equal(a.todense(9).T, a.T.todense(3))