def test_referenceToSinglet(self): from nPYc.utilities._calibratePPMscale import referenceToSinglet spectrum = numpy.array([0, 5, 6, 9, 6, 5, 0, 0, 0, 7, 8, 6, 0, 0, 0, 0, 0, 0, 0, 0]) ppm = numpy.linspace(-10, 10, 20) with self.subTest(msg='Using whole spectrum'): obtainedPPM = referenceToSinglet(spectrum, ppm, (-10, 10)) expectedDeltaPPM = 3 self.assertEqual(obtainedPPM, expectedDeltaPPM) with self.subTest(msg='Using masked spectrum'): obtainedPPM = referenceToSinglet(spectrum, ppm, (-2, 8)) expectedDeltaPPM = 10 self.assertEqual(obtainedPPM, expectedDeltaPPM)
def test_calibratePPM(self):
from nPYc.utilities._calibratePPMscale import calibratePPM, referenceToSinglet, referenceToResolvedMultiplet
with self.subTest(msg='Singlet'):
specSize = numpy.random.randint(100, 1000)
ppm = numpy.linspace(-1, 10, specSize)
shift = ppm[numpy.random.randint(specSize - 20) + 10]
targetShift = ppm[numpy.random.randint(specSize - 20) + 10]
spectrum = L(ppm, shift, 0.001)
spectrum = spectrum + L(ppm, shift + 3, 0.001) * 2
(alignedSpectrum, alignedPPM, ppmShift) = calibratePPM('Singlet', targetShift, (shift - 1, shift + 1), ppm, spectrum, spectrumType='1D')
obtainedPPM = referenceToSinglet(alignedSpectrum, alignedPPM, (targetShift - 1, targetShift + 1))
self.assertEqual(alignedPPM[obtainedPPM], targetShift)
with self.subTest(msg='Singlet, reversed'):
specSize = numpy.random.randint(100, 1000)
ppm = numpy.linspace(10, -1, specSize)
shift = ppm[numpy.random.randint(specSize -20) + 10]
targetShift = ppm[numpy.random.randint(specSize - 20) + 10]
spectrum = L(ppm, shift, 0.001)
spectrum = spectrum + L(ppm, shift + 3, 0.001) * 2
(alignedSpectrum, alignedPPM, ppmShift) = calibratePPM('Singlet', targetShift, (shift - 1, shift + 1), ppm, spectrum, spectrumType='1D')
obtainedPPM = referenceToSinglet(alignedSpectrum, alignedPPM, (targetShift - 1, targetShift + 1))
self.assertEqual(alignedPPM[obtainedPPM], targetShift)
with self.subTest(msg='Doublet'):
specSize = numpy.random.randint(500, 1000)
ppm = numpy.linspace(4.8, 5.7, specSize)
# Reserve below 5 ppm for decoy peaks
shift = ppm[numpy.random.randint(numpy.max(numpy.where(ppm<5.1)), high=numpy.min(numpy.where(ppm>5.5)), size=1)[0]]
targetShift = ppm[numpy.random.randint(numpy.max(numpy.where(ppm<5.1)), high=numpy.min(numpy.where(ppm>5.5)), size=1)[0]]
baseline = L(ppm, 5.3, .09)
peakOne = L(ppm, shift, 0.001)
peakTwo = L(ppm, shift + 0.01, 0.001)
peakThree = L(ppm, 4.81, 0.001)
peakFour = L(ppm, 4.83, 0.001)
spectrum = (baseline * 300) + peakOne + peakTwo + (peakThree + peakFour) * 5
(alignedSpectrum, alignedPPM, ppmShift) = calibratePPM('Doublet', targetShift, (shift - 0.2, shift + 0.2), ppm, spectrum, spectrumType='1D')
obtainedPPM = referenceToResolvedMultiplet(alignedSpectrum, alignedPPM, (targetShift - 0.2, targetShift + 0.2), 2)
obtainedPPM = int(round(numpy.mean(obtainedPPM)))
# Use all close because midpoint of pleaks may fall between the ppm grid
numpy.testing.assert_allclose(alignedPPM[obtainedPPM], targetShift, atol=ppm[1]-ppm[0])