def testNormalizeMoreIndices(self):
'''Normalize raises an error if more than two indices are passed as
input'''
x = np.arange(10)
ind = (2, 5, 3)
with self.assertRaises(ValueError):
spectrum_functions.normalize(x, ind)
def testNormalize1IndexTuple(self):
'''Normalize throws an error if a single index inside a sequence
is given'''
x = np.arange(10)
ind = [3]
with self.assertRaises(ValueError):
spectrum_functions.normalize(x, ind)
def Normalize(self, ind=None):
'''Normalize data to integral'''
data_norm = specfun.normalize(self.intensity, ind)
return EELSSpectrum(data_norm,
SpectrumRange=self.SpectrumRange,
dispersion=self.dispersion,
ZLP=self.ZLP,
units=self.units)
def testNormalize2Indices(self):
'''Normalize works as expected when two indices are given'''
x = np.arange(10)
ind = (2, 5)
np.testing.assert_allclose(
x/9.,
spectrum_functions.normalize(x, ind)
)
def testNormalize1Index(self):
'''Normalize works as expected when a single index is given'''
x = np.arange(10)
ind = 2
np.testing.assert_allclose(
x/2.,
spectrum_functions.normalize(x, ind)
)
def testNormalizeFloatIndex(self):
'''Normalize throws an error when given a float index'''
x = np.arange(10)
ind = 2.4
with self.assertRaises(ValueError):
spectrum_functions.normalize(x, ind)