def setUpTestData(cls):
d1 = Dataset(name='Dataset1')
d1.save()
m1 = Molecule(sum_formula='H2O')
m1.save()
m2 = Molecule(sum_formula='O2')
m2.save()
s1 = Standard(molecule=m1)
s1.save()
s2 = Standard(molecule=m1)
s2.save()
s3 = Standard(molecule=m2)
s3.save()
FragmentationSpectrum.objects.create(precursor_mz='123.456',
spec_num=0,
dataset=d1,
standard=s1)
FragmentationSpectrum.objects.create(precursor_mz='123.45',
spec_num=0,
dataset=d1,
standard=s2)
FragmentationSpectrum.objects.create(precursor_mz='123.4',
spec_num=0,
dataset=d1,
standard=s3)
cls.m_onespectrum = m2
cls.m_twospectra = m1
def test_is_not_empty_if_annotated(self):
m1 = Molecule(name='test', sum_formula="C1H2O3")
m1.save()
s1 = Standard(molecule=m1)
s1.save()
d1 = Dataset()
d1.save()
fs1 = FragmentationSpectrum(ms1_intensity=42, dataset=d1, standard=s1)
fs1.save()
molecule_table, molecules_with_spectra = self.get_table_and_count()
self.assertEqual(len(molecule_table.rows), 1)
self.assertEqual(molecules_with_spectra, 1)
def test_xic_and_standard_and_adduct(self):
# create some datasets
d1 = Dataset(name='Dataset1')
d1.save()
a1 = Adduct(nM=1, delta_formula='-H', charge=-1)
a1.save()
m1 = Molecule(name='TestMolecule1', sum_formula="C1H2O3")
m1.save()
s1 = Standard(molecule=m1, inventory_id="0")
s1.save()
# create some xics
x1 = Xic(mz=60.993, dataset=d1)
xic = [1.0, 2.0, 3.0, 4.0, 5.0]
x1.set_xic(xic)
x1.standard = s1
x1.adduct = a1
x1.save()
self.assertEqual(Xic.objects.all().count(), 1)
self.assertEqual(Dataset.objects.all().count(), 1)
self.assertEqual(Standard.objects.all().count(), 1)
# mass check
with self.assertRaises(ValueError):
x1.mz = 123.993
x1.save()
x1.check_mass()
def test_xic_mass_filter(self):
d1 = Dataset(name='dataset')
d1.save()
mz = 60.993
# three larger
Xic(mz=mz + 5., dataset=d1).save()
Xic(mz=mz + 10., dataset=d1).save()
Xic(mz=mz + 15., dataset=d1).save()
# three approx equal
Xic(mz=mz + 0.005, dataset=d1).save()
Xic(mz=mz + 0.0, dataset=d1).save()
Xic(mz=mz - 0.0015, dataset=d1).save()
# three smaller
Xic(mz=mz - 5., dataset=d1).save()
Xic(mz=mz - 10., dataset=d1).save()
Xic(mz=mz - 15., dataset=d1).save()
# three approx equal from another dataset
d2 = Dataset(name='dataset2')
d2.save()
Xic(mz=mz + 0.005, dataset=d2).save()
Xic(mz=mz + 0.0, dataset=d2).save()
Xic(mz=mz - 0.0015, dataset=d2).save()
self.assertEqual(Xic.objects.all().count(), 12)
xics = Xic.objects.all().filter(dataset=d1).filter(
mz__gte=mz + 0.01).filter(mz__lte=mz - 0.01)
self.assertEqual(xics.objects.all().count(), 3)
def test_make_FragmentationSpectrum_with_centroids(self):
d1 = Dataset(name='Dataset1')
d1.save()
f1 = FragmentationSpectrum(precursor_mz='123.456',
spec_num=0,
dataset=d1)
mzs = [10., 20, 50]
ints = [1., 1., 1.]
f1.set_centroid_mzs(mzs)
f1.set_centroid_ints(ints)
f1.save()
np.testing.assert_array_almost_equal(mzs, f1.centroid_mzs)
np.testing.assert_array_almost_equal(ints, f1.centroid_ints)
def test_xic_mass_filter(self):
d1 = Dataset(name='dataset')
d1.save()
mz = 60.993
# three larger
Xic(mz=mz + 5., dataset=d1).save()
Xic(mz=mz + 10., dataset=d1).save()
Xic(mz=mz + 15., dataset=d1).save()
# three approx equal
Xic(mz=mz + 0.005, dataset=d1).save()
Xic(mz=mz + 0.0, dataset=d1).save()
Xic(mz=mz - 0.0015, dataset=d1).save()
# three smaller
Xic(mz=mz - 5., dataset=d1).save()
Xic(mz=mz - 10., dataset=d1).save()
Xic(mz=mz - 15., dataset=d1).save()
# three approx equal from another dataset
d2 = Dataset(name='dataset2')
d2.save()
Xic(mz=mz + 0.005, dataset=d2).save()
Xic(mz=mz + 0.0, dataset=d2).save()
Xic(mz=mz - 0.0015, dataset=d2).save()
self.assertEqual(Xic.objects.all().count(), 12)
xics = Xic.objects.all().filter(dataset=d1).filter(
mz__gte=mz + 0.01).filter(mz__lte=mz - 0.01)
self.assertEqual(xics.objects.all().count(), 3)
def setUpTestData(cls):
csv_filepath = join(settings.MEDIA_ROOT, "Standard_Library_MCF_Inhouse_metabolites.csv")
add_batch_standard({}, csv_filepath)
Adduct.objects.create(nM=1, delta_formula='-H', charge=-1)
cls.mzml_filepath = join(settings.MEDIA_ROOT, "sample.mzML")
cls.d1 = Dataset(name='foo')
cls.d1.save()
cls.lc1 = LcInfo.objects.create(content='LC1')
def test_add_xic(self):
m1 = Molecule(name='TestMolecule1', sum_formula="C1H2O3")
m1.save()
s1 = Standard(molecule=m1, inventory_id="0")
s1.save()
a1 = Adduct(nM=1, delta_formula='+H+K', charge=-2)
a1.save()
d1 = Dataset(name='Dataset1')
d1.save()
d1.standards_present.add(s1)
d1.adducts_present.add(a1)
x1 = Xic(mz='0.0', dataset=d1)
xic = [1.0, 2.0, 3.0, 4.0, 5.0]
x1.set_xic(xic)
x1.save()
self.assertEqual(Xic.objects.all().count(), 1)
np.testing.assert_array_almost_equal(xic, x1.xic)
def test_add_dataset(self):
# create standards
m1 = Molecule(name='TestMolecule1', sum_formula="C1H2O3")
m1.save()
m2 = Molecule(name='TestMolecule1', sum_formula="C2H2O3")
m2.save()
s1 = Standard(molecule=m1, inventory_id="0")
s1.save()
s2 = Standard(molecule=m2, inventory_id="1")
s2.save()
# create adduct
a1 = Adduct(nM=1, delta_formula='+H+K', charge=-2)
a1.save()
# create a dataset
d1 = Dataset(name='Dataset1')
d1.save()
d1.standards_present.add(s1)
d1.standards_present.add(s2)
d1.adducts_present.add(a1)
self.assertEqual(Dataset.objects.all().count(), 1)
self.assertEqual(Dataset.objects.all()[0].standards_present.count(), 2)
def dataset_upload(request):
if request.method == 'POST':
form = UploadFileForm(request.POST, request.FILES)
if form.is_valid():
post_dict = dict(request.POST)
files_dict = dict(request.FILES)
logging.debug(files_dict)
logging.debug(post_dict)
data = {"adducts": post_dict['adducts'],
"standards": post_dict['standards'],
"mass_accuracy_ppm": post_dict['mass_accuracy_ppm'][0],
"quad_window_mz": post_dict['quad_window_mz'][0],
"lc_info": post_dict['lc_info'][0],
"ms_info": post_dict['ms_info'][0],
"ionization_method": post_dict['ionization_method'][0],
"ion_analyzer": post_dict['ion_analyzer'][0]}
uploaded_file = request.FILES['mzml_file']
base_name, extension = os.path.splitext(uploaded_file.name)
d = Dataset(name=uploaded_file.name, processing_finished=False)
d.save()
mzml_filename = "{}-{}{}".format(base_name, d.id, extension)
mzml_filepath = os.path.join(settings.MEDIA_ROOT, mzml_filename)
logging.debug("mzML filepath: " + mzml_filepath)
logging.debug("original mzML filename: " + uploaded_file.name)
with open(mzml_filepath, 'wb') as destination:
for chunk in uploaded_file.chunks():
destination.write(chunk)
d.path = mzml_filepath
d.save()
tasks.handle_uploaded_files.delay(data, mzml_filepath, d)
return redirect('dataset-list')
else:
form = UploadFileForm(initial={"mass_accuracy_ppm": 10.0, 'quad_window_mz': 1.0, 'ion_analyzer': 'QFT',
'ionization_method': 'ESI'})
autocomplete = {
'lc_info': [str(info.content) for info in LcInfo.objects.all()],
'ms_info': [str(info.content) for info in MsInfo.objects.all()],
'ionization_method': json.dumps(
list(set(Dataset.objects.values_list('ionization_method', flat=True).distinct()).union(
['APCI', 'APPI', 'EI', 'ESI', 'FAB', 'MALDI']))),
'ion_analyzer': json.dumps(list(set(Dataset.objects.values_list('ion_analyzer', flat=True).distinct()).union(
tools.sum_of_2_perms(['B', 'E', 'FT', 'IT', 'Q', 'TOF']))))
}
return render(request, 'mcf_standards_browse/dataset_upload.html', {'form': form, 'autocomplete': autocomplete})
def setUpTestData(cls):
cls.d1 = Dataset(name='foo')
cls.d1.save()
def test_make_FragmentationSpectrum(self):
d1 = Dataset(name='Dataset1')
d1.save()
FragmentationSpectrum(precursor_mz='123.456', spec_num=0,
dataset=d1).save()
self.assertEqual(FragmentationSpectrum.objects.all().count(), 1)