def callback(msms: PySpectrum, file_name: str):
if msms is not None:
highest = msms.highest_peaks(1)[0]
spectra = msms.convert(msms).spectra
splash = Splash().splash(Spectrum(spectra,
SpectrumType.MS))
out.write("{};{};{};{};{};{}\n".format(
msms.ms_level, highest[0], highest[1],
msms.scan_time[0], splash, spectra))
def test_add_tow_custom_specs(self):
spec1 = Spectrum()
spec2 = Spectrum()
spec1.set_peaks([(100, 200)], "raw")
spec2.set_peaks([(100, 200), (200, 300)], "raw")
spec1 += spec2
centroided_mz = spec1.peaks("centroided")[:, 0]
centroided_i = spec1.peaks("centroided")[:, 1]
assert np.allclose(centroided_mz, [100, 200], rtol=5e-6)
assert np.allclose(centroided_i, [400, 300], atol=0.002)
def callback(msms: Spectrum, file_name: str):
"""
builds our data list
:param msms:
:param file_name:
:return:
"""
data.append(msms.convert(msms))
def toSpectra(self, spectra: Spectrum) -> Spectra:
peaks = spectra.peaks("centroided")
f = lambda x: "{}:{}".format(x[0], x[1])
result = []
for x in peaks:
result.append(f(x))
result = " ".join(result)
return Spectra(spectra=result)
def callback(msms: PySpectrum, file_name: str):
with db.atomic() as transaction:
if msms is None:
self.extract_record(file_name)
else:
# 3. load sample object
record = MZMLSampleRecord.get(
MZMLSampleRecord.file_name == file_name)
# 3. associated msms spectra to it
try:
# 4. commit transaction
highest = msms.highest_peaks(1)[0]
spectra = msms.convert(msms, mode="raw").spectra
precurosr = msms.selected_precursors[0] if len(
msms.selected_precursors) > 0 else {}
scannumber = msms.index
splash = Splash().splash(
Spectrum(spectra, SpectrumType.MS))
spectra = MZMLMSMSSpectraRecord.create(
sample=record,
msms=spectra,
rt=msms.scan_time[0],
splash=splash,
scan_number=scannumber,
level=msms.ms_level,
base_peak=highest[0],
base_peak_intensity=highest[1],
precursor=precurosr['mz']
if 'mz' in precurosr else 0,
precursor_intensity=precurosr['i']
if 'i' in precurosr else 0,
precursor_charge=precurosr['charge']
if 'charge' in precurosr else 0,
ion_count=len(msms.peaks("centroided")))
except IndexError as e:
# not able to find highest peak
pass
def test_add_specs_to_empty_spec(self):
spec1 = Spectrum()
spec2 = Spectrum()
spec2.set_peaks([(100, 200)], 'raw')
spec1 += spec2
centroided_mz = spec1.peaks('centroided')[:,0]
centroided_i = spec1.peaks('centroided')[:,1]
assert np.allclose(
centroided_mz,
[100],
rtol=5e-6
)
assert np.allclose(
centroided_i,
[200],
atol=0.002
)
def callback(msms: Spectrum, file_name: str):
nonlocal count
count = count + 1
converted = msms.convert(msms)
def test_average_spectra(self):
spec0 = Spectrum()
spec1 = Spectrum()
spec2 = Spectrum()
spec1.set_peaks(np.array([(100, 200.0)]), "centroided")
spec2.set_peaks(np.array([(100, 200.0), (200, 300.0)]), "centroided")
scaled1 = spec1 / spec1.peaks("centroided")[:, 1].sum()
spec0 += scaled1
scaled2 = spec2 / spec2.peaks("centroided")[:, 1].sum()
spec0 += scaled2
centroided_peaks = spec0.peaks("centroided")
assert np.allclose(centroided_peaks[:, 0], [100, 200])
assert np.allclose(centroided_peaks[:, 1], [1.4, 0.6], atol=0.0001)
def test_average_spectra(self):
spec0 = Spectrum()
spec1 = Spectrum()
spec2 = Spectrum()
spec1.set_peaks(np.array([(100, 200)]), 'centroided')
spec2.set_peaks(np.array([(100, 200), (200, 300)]), 'centroided')
spec0 += (spec1 / spec1.peaks('centroided')[:,1].sum())
spec0 += (spec2 / spec2.peaks('centroided')[:,1].sum())
centroided_peaks = spec0.peaks('centroided')
assert np.allclose(
centroided_peaks[:,0],
[100, 200]
)
assert np.allclose(
centroided_peaks[:,1],
[1.4, 0.6],
atol=0.0001
)
def callback(msms: Spectrum, file_name: str):
nonlocal data
data.append(msms.convert(msms))
def callback(msms: Spectrum, file_name: str):
nonlocal data
if msms is not None:
data.append(msms.convert(msms))