def test_normalisation_case_A(self):
lib = sqio.Standards(fp=self.tmp_dir)
lib.set_active_standards(['Ti', 'Ni'])
lib.set_spectrum_range(400.0, 1000.0)
lib.normalise(logscale=False)
def test_load(self):
# loads a test directory which contains Cu, Ni, Ti and V
lib = sqio.Standards(fp=self.tmp_dir)
expected = ['Cu', 'Ni', 'Ti', 'V']
actual = list(lib.data.keys())
actual.sort()
assert expected == actual
def test_MLLSmodel_point(self):
lib = sqio.Standards(fp=self.ref_dir)
SI = sqio.Data(fp=os.path.join(self.dat_dir, 'deconv.dm3'))
SI.set_data_range(400.0, 500.0)
tofit = [
'Ti',
]
lib.set_spectrum_range(400.0, 500.0)
model = sqq.MLLSmodel(SI, lib)
def test_active(self):
lib = sqio.Standards(fp=self.tmp_dir)
lib.set_active_standards(['Ti', 'V'])
expected = [False, False, True, True]
actual = []
for item in ['Cu', 'Ni', 'Ti', 'V']:
actual.append(lib.active[item])
assert expected == actual
def test_MLLSmodel_creation(self):
lib = sqio.Standards(fp=self.ref_dir)
SI = sqio.Data(fp=os.path.join(self.dat_dir, 'deconv.dm3'))
model = sqq.MLLSmodel(SI, lib)
def test_model_creation(self):
lib = sqio.Standards(fp=self.ref_dir)
SI = sqio.Data(fp=os.path.join(self.dat_dir, 'deconv.dm3'))
model = sqb.BayesModel(SI, lib, ['Ti'], (400.0, 480.0))
def test_range_crop_case_D(self):
# crop when both limits are beyond data range
lib = sqio.Standards(fp=self.tmp_dir)
lib.set_active_standards(['Ti'])
lib.set_spectrum_range(300.0, 1500.0)
def test_range_crop_case_C(self):
# crop when right limit is beyond data range
lib = sqio.Standards(fp=self.tmp_dir)
lib.set_active_standards(['Ti'])
lib.set_spectrum_range(500.0, 1500.0)
def test_range_crop_case_A(self):
# crop when both limits are within data range
lib = sqio.Standards(fp=self.tmp_dir)
lib.set_active_standards(['Ti'])
lib.set_spectrum_range(500.0, 600.0)