def test_no_scaling(self):
"""Test that raw data is returned unscaled when there is no scaling"""
tdms_obj = tdms.TdmsObject("/'group'/'channel'")
expected_data = np.array([1.0, 2.0, 3.0])
tdms_obj._data = expected_data
self.assertIs(expected_data, tdms_obj.data)
def test_scaling_from_group(self):
"""Test linear scaling in a group"""
tdms_file = TestTdmsFile()
tdms_channel = tdms.TdmsObject("/'group'/'channel'", tdms_file)
tdms_channel._data = np.array([1.0, 2.0, 3.0])
tdms_group = tdms.TdmsObject("/'group'", tdms_file)
tdms_group.properties["NI_Number_Of_Scales"] = 1
tdms_group.properties["NI_Scale[1]_Scale_Type"] = "Linear"
tdms_group.properties["NI_Scale[1]_Linear_Slope"] = 2.0
tdms_group.properties["NI_Scale[1]_Linear_Y_Intercept"] = 10.0
tdms_file.objects[tdms_channel.path] = tdms_channel
tdms_file.objects[tdms_group.path] = tdms_group
expected_data = np.array([12.0, 14.0, 16.0])
np.testing.assert_almost_equal(expected_data, tdms_channel.data)
def test_unsupported_scaling_type(self):
"""Raw data is returned unscaled when the scaling type is unsupported.
"""
tdms_obj = tdms.TdmsObject("/'group'/'channel'")
expected_data = np.array([1.0, 2.0, 3.0])
tdms_obj.properties["NI_Number_Of_Scales"] = 1
tdms_obj.properties["NI_Scale[1]_Scale_Type"] = "UnknownScaling"
tdms_obj._data = expected_data
self.assertIs(expected_data, tdms_obj.data)
def test_linear_scaling(self):
"""Test linear scaling"""
tdms_obj = tdms.TdmsObject("/'group'/'channel'")
tdms_obj._data = np.array([1.0, 2.0, 3.0])
tdms_obj.properties["NI_Number_Of_Scales"] = 1
tdms_obj.properties["NI_Scale[1]_Scale_Type"] = "Linear"
tdms_obj.properties["NI_Scale[1]_Linear_Slope"] = 2.0
tdms_obj.properties["NI_Scale[1]_Linear_Y_Intercept"] = 10.0
expected_data = np.array([12.0, 14.0, 16.0])
np.testing.assert_almost_equal(expected_data, tdms_obj.data)
def test_polynomial_scaling(self):
"""Test polynomial scaling"""
tdms_obj = tdms.TdmsObject("/'group'/'channel'")
tdms_obj._data = np.array([1.0, 2.0, 3.0])
tdms_obj.properties["NI_Number_Of_Scales"] = 1
tdms_obj.properties["NI_Scale[1]_Scale_Type"] = "Polynomial"
tdms_obj.properties["NI_Scale[1]_Polynomial_Coefficients[0]"] = 10.0
tdms_obj.properties["NI_Scale[1]_Polynomial_Coefficients[1]"] = 1.0
tdms_obj.properties["NI_Scale[1]_Polynomial_Coefficients[2]"] = 2.0
tdms_obj.properties["NI_Scale[1]_Polynomial_Coefficients[3]"] = 3.0
expected_data = np.array([16.0, 44.0, 112.0])
np.testing.assert_almost_equal(expected_data, tdms_obj.data)
def test_multiple_scalings(self):
"""Test correct scaling selected from multiple scalings"""
tdms_obj = tdms.TdmsObject("/'group'/'channel'")
tdms_obj._data = np.array([1.0, 2.0, 3.0])
tdms_obj.properties["NI_Number_Of_Scales"] = 3
tdms_obj.properties["NI_Scale[0]_Scale_Type"] = "Linear"
tdms_obj.properties["NI_Scale[0]_Linear_Slope"] = 2.0
tdms_obj.properties["NI_Scale[0]_Linear_Y_Intercept"] = 10.0
tdms_obj.properties["NI_Scale[1]_Scale_Type"] = "Linear"
tdms_obj.properties["NI_Scale[1]_Linear_Slope"] = 3.0
tdms_obj.properties["NI_Scale[1]_Linear_Y_Intercept"] = 12.0
tdms_obj.properties["NI_Scale[2]_Scale_Type"] = "Linear"
tdms_obj.properties["NI_Scale[2]_Linear_Slope"] = 4.0
tdms_obj.properties["NI_Scale[2]_Linear_Y_Intercept"] = 2.0
expected_data = np.array([6.0, 10.0, 14.0])
np.testing.assert_almost_equal(expected_data, tdms_obj.data)
