def test_importBrukerSpectra_malformederetic(self):
from nPYc.utilities._importBrukerSpectrum import importBrukerSpectra
Attributes = dict()
Attributes['variableSize'] = numpy.random.randint(10000, high=50000, size=None)
Attributes['bounds'] = [-0.5, 10]
Attributes['alignTo'] = 'singlet'
Attributes['calibrateTo'] = 0
Attributes['ppmSearchRange'] = [-0.3, 0.3]
Attributes['LWpeakRange'] = [-0.3, 0.3]
Attributes['LWpeakMultiplicity'] = 'singlet'
Attributes['LWpeakIntesityFraction'] = 1e-4
with self.assertWarnsRegex(UserWarning, 'Error parsing `QuantFactorSample`'):
intensityData, ppm, metadata = importBrukerSpectra(os.path.join('..', '..', 'npc-standard-project',
'Raw_Data', 'nmr', 'UnitTest1',
'UnitTest1_Urine_Rack1_SLL_270814', '10'),
'noesypr1d', 1, Attributes)
expectedWarningText = 'Error calculating ERETIC integral'
self.assertEqual(metadata.loc[0, 'Warnings'], expectedWarningText)
expectedERETIC = numpy.nan
numpy.testing.assert_allclose(metadata.loc[0, 'ERETIC Integral'], expectedERETIC)
def test_importBrukerSpectra_pdata(self):
from nPYc.utilities._importBrukerSpectrum import importBrukerSpectra
Attributes = dict()
Attributes['variableSize'] = numpy.random.randint(10000,
high=50000,
size=None)
lowBound = (-0.5 - -2) * numpy.random.random_sample() + -2
highBound = (14.5 - 10) * numpy.random.random_sample() + 10
Attributes['bounds'] = [lowBound, highBound]
Attributes['alignTo'] = 'singlet'
Attributes['calibrateTo'] = (
0.5 - -0.5) * numpy.random.random_sample() + -0.5
offset = Attributes['calibrateTo']
Attributes['ppmSearchRange'] = [-0.5, -0.5]
Attributes['LWpeakRange'] = [-0.5 + offset, 0.5 + offset]
Attributes['LWpeakMultiplicity'] = 'singlet'
Attributes['LWpeakIntesityFraction'] = 1e-4
with warnings.catch_warnings():
warnings.simplefilter("ignore")
intensityData, ppm, metadata = importBrukerSpectra(
os.path.join('..', '..', 'npc-standard-project', 'Raw_Data',
'nmr', 'UnitTest1'), 'noesygppr1d', 2, Attributes)
##
# Sort to account for filesystem ordering
##
metadata.sort_values('Sample File Name', inplace=True)
sortIndex = metadata.index.values
intensityData = intensityData[sortIndex, :]
metadata = metadata.reset_index(drop=True)
warningsCol = pandas.Series([''], name='Warnings', dtype='str')
pandas.util.testing.assert_series_equal(metadata['Warnings'],
warningsCol)
sampleName = pandas.Series(['UnitTest1_Urine_Rack1_SLL_270814/30'],
name='Sample File Name',
dtype='str')
pandas.util.testing.assert_series_equal(metadata['Sample File Name'],
sampleName)
self.assertEqual(len(ppm), Attributes['variableSize'])
numpy.testing.assert_allclose(numpy.min(ppm), Attributes['bounds'][0])
numpy.testing.assert_allclose(numpy.max(ppm), Attributes['bounds'][1])
expectedLW = 0.7083017156078231
numpy.testing.assert_allclose(metadata.loc[0, 'Line Width (Hz)'],
expectedLW,
atol=0.01)
expectedERETIC = 152106691.42761227
numpy.testing.assert_allclose(metadata.loc[0, 'ERETIC Integral'],
expectedERETIC)
def test_importBrukerSpectra(self):
from nPYc.utilities._importBrukerSpectrum import importBrukerSpectra
Attributes = dict()
Attributes['variableSize'] = numpy.random.randint(10000, high=50000, size=None)
lowBound = (-0.5 - -5) * numpy.random.random_sample() + -5
highBound = (19 - 10) * numpy.random.random_sample() + 10
Attributes['bounds'] = [lowBound, highBound]
Attributes['alignTo'] = 'doublet'
Attributes['calibrateTo'] = (6 - 4.5) * numpy.random.random_sample() + 4.5
offset = 5.233 - Attributes['calibrateTo']
Attributes['ppmSearchRange'] = [4.9, 5.733]
Attributes['LWpeakRange'] = [4.08 - offset, 4.14 - offset]
Attributes['LWpeakMultiplicity'] = 'quartet'
Attributes['LWpeakIntesityFraction'] = 1e-4
with warnings.catch_warnings():
warnings.simplefilter("ignore")
intensityData, ppm, metadata = importBrukerSpectra(os.path.join('..', '..', 'npc-standard-project',
'Raw_Data', 'nmr', 'UnitTest3',
'UnitTest3_Serum_Rack01_RCM_190116'),
'noesygppr1d', 1, Attributes)
##
# Sort to account for filesystem ordering
##
metadata.sort_values('Sample File Name', inplace=True)
sortIndex = metadata.index.values
intensityData = intensityData[sortIndex, :]
metadata = metadata.reset_index(drop=True)
warningsCol = pandas.Series(['',
'Error loading file',
'Error loading file',
'Error loading file',
'Error loading file',
'Error loading file',
'Error loading file',
'Error loading file',
'Error loading file',
'Error loading file'],
name='Warnings',
dtype='str')
pandas.util.testing.assert_series_equal(metadata['Warnings'], warningsCol)
sampleName = pandas.Series(['UnitTest3_Serum_Rack01_RCM_190116/10',
'UnitTest3_Serum_Rack01_RCM_190116/100',
'UnitTest3_Serum_Rack01_RCM_190116/110',
'UnitTest3_Serum_Rack01_RCM_190116/120',
'UnitTest3_Serum_Rack01_RCM_190116/130',
'UnitTest3_Serum_Rack01_RCM_190116/140',
'UnitTest3_Serum_Rack01_RCM_190116/150',
'UnitTest3_Serum_Rack01_RCM_190116/160',
'UnitTest3_Serum_Rack01_RCM_190116/170',
'UnitTest3_Serum_Rack01_RCM_190116/180'],
name='Sample File Name',
dtype='str')
pandas.util.testing.assert_series_equal(metadata['Sample File Name'], sampleName)
sumFailedImports = numpy.sum(intensityData[1:, :])
numpy.testing.assert_allclose(sumFailedImports, 0)
self.assertEqual(len(ppm), Attributes['variableSize'])
numpy.testing.assert_allclose(numpy.min(ppm), Attributes['bounds'][0])
numpy.testing.assert_allclose(numpy.max(ppm), Attributes['bounds'][1])
expectedLW = 0.97083128379560091
numpy.testing.assert_allclose(metadata.loc[0, 'Line Width (Hz)'], expectedLW)
expectedERETIC = 181331824.09952235
numpy.testing.assert_allclose(metadata.loc[0, 'ERETIC Integral'], expectedERETIC)