def setUp(self):
data1 = np.c_[[2., 3, 4, 5], [0, 10, 20, 30], [0, 1, 2, 3]]
data2 = np.c_[[1., 2, 3, 4], [0, 5, 10, 20], [0, 1, 2, 3]]
dataset1 = xye.XYEDataset(data1)
dataset2 = xye.XYEDataset(data2)
we1 = DatasetWithWavelength(dataset=dataset1, x=1.5)
we2 = DatasetWithWavelength(dataset=dataset2, x=0.5)
self.data_plus_scale_sets = [we1, we2]
def setUp(self):
data1 = np.c_[[1, 4, 7], [2, 5, 8], [3, 6, 9]]
data2 = np.c_[[10, 13, 16, 19], [11, 14, 18, 20], [12, 15, 17, 21]]
xye1 = xye.XYEDataset(data=data1, name='test_data_0001.xye')
create_datasetui(xye1)
xye1.metadata['ui'].active = True
xye2 = xye.XYEDataset(data=data2, name='test_data_0002.xye')
create_datasetui(xye2)
xye2.metadata['ui'].active = True
self.datasets = [xye1, xye2]
def normalise_data_test(self):
# test that normalisation leaves the x-data untouched and rescales the y and e correctly
DETECTOR_COUNTS = 3.0
COUNT_KEY = 'Integrated Ion Chamber Count(counts)'
data1 = np.c_[[0., 1, 2, 3], [0, 10, 20, 30], [0, 1, 2, 3]]
data2 = np.c_[[1., 2, 3, 4], [0, 5, 10, 20], [0, 1, 2, 3]]
dataset1 = xye.XYEDataset(data1, metadata={COUNT_KEY: 1.0}, name='d1')
dataset2 = xye.XYEDataset(data2,
metadata={COUNT_KEY: 1.0 / DETECTOR_COUNTS},
name='d2')
dataset_pair = (dataset1, dataset2)
result = processing.normalise_dataset(dataset_pair)
print result
print data2
self.assertTrue(np.allclose(result[:, 0], data2[:, 0])) # check x's
self.assertTrue(
np.allclose(result[:, 1],
data2[:, 1] * DETECTOR_COUNTS)) # check y's
self.assertTrue(
np.allclose(result[:, 2],
data2[:, 2] * np.sqrt(DETECTOR_COUNTS))) # check e's