def test_dict_like(self):
hp = HydrationParameter()
hp['field'] = 300
hp['spin_C'] = 200
hp['ksigma_bulk'] = 95
hp['T10'] = 1
hp['T100'] = 2
hp['tcorr_bulk'] = 50
hp['D_H2O'] = 3e-10
hp['D_SL'] = 5e-10
hp['klow_bulk'] = 350
hp['smax_model'] = 'free'
hp['t1_interp_method'] = 'second_order'
self.assertEqual(hp['field'], hp.field)
self.assertEqual(hp['spin_C'], hp.spin_C)
self.assertEqual(hp['ksigma_bulk'], hp.ksigma_bulk)
self.assertEqual(hp['T10'], hp.T10)
self.assertEqual(hp['T100'], hp.T100)
self.assertEqual(hp['tcorr_bulk'], hp.tcorr_bulk)
self.assertEqual(hp['D_H2O'], hp.D_H2O)
self.assertEqual(hp['D_SL'], hp.D_SL)
self.assertEqual(hp['klow_bulk'], hp.klow_bulk)
self.assertEqual(hp['smax_model'], hp.smax_model)
self.assertEqual(hp['t1_interp_method'], hp.t1_interp_method)
with self.assertRaises(ValueError):
hp['smax_model'] = 'notinlist'
with self.assertRaises(ValueError):
hp['t1_interp_method'] = 'notinlist'
def test_dict_like(self):
hp = HydrationParameter()
hp["field"] = 300
hp["spin_C"] = 200
hp["ksigma_bulk"] = 95
hp["T10"] = 1
hp["T100"] = 2
hp["tcorr_bulk"] = 50
hp["D_H2O"] = 3e-10
hp["D_SL"] = 5e-10
hp["klow_bulk"] = 350
hp["smax_model"] = "free"
hp["t1_interp_method"] = "second_order"
self.assertEqual(hp["field"], hp.field)
self.assertEqual(hp["spin_C"], hp.spin_C)
self.assertEqual(hp["ksigma_bulk"], hp.ksigma_bulk)
self.assertEqual(hp["T10"], hp.T10)
self.assertEqual(hp["T100"], hp.T100)
self.assertEqual(hp["tcorr_bulk"], hp.tcorr_bulk)
self.assertEqual(hp["D_H2O"], hp.D_H2O)
self.assertEqual(hp["D_SL"], hp.D_SL)
self.assertEqual(hp["klow_bulk"], hp.klow_bulk)
self.assertEqual(hp["smax_model"], hp.smax_model)
self.assertEqual(hp["t1_interp_method"], hp.t1_interp_method)
with self.assertRaises(ValueError):
hp["smax_model"] = "notinlist"
with self.assertRaises(ValueError):
hp["t1_interp_method"] = "notinlist"
def test_default_values(self):
hp = HydrationParameter()
self.assertEqual(hp.field, None)
self.assertEqual(hp.spin_C, None)
self.assertEqual(hp.T10, None)
self.assertEqual(hp.T100, None)
self.assertEqual(hp.smax_model, 'tethered')
self.assertEqual(hp.ksigma_bulk, 95.4)
self.assertEqual(hp.tcorr_bulk, 54)
self.assertEqual(hp.D_H2O, 2.3e-9)
self.assertEqual(hp.D_SL, 4.1e-10)
self.assertEqual(hp.klow_bulk, 366)
self.assertEqual(hp.t1_interp_method, 'second_order')
def set_par(ppar: ProcParameter, hpar: HydrationParameter):
"""Prompt for users to choose parameters
Returns: tuple(ProcParameter, HydrationParameter)
"""
# Defaults
ppar.eiw = 20
hpar.field = 348.5
hpar.t1_interp_method = 'second_order'
# st.sidebar.markdown('**Experiments**')
hpar.spin_C = st.sidebar.number_input("Spin label concentration (uM)",
min_value=0.01,
value=500.0,
step=1.0,
key='spin_C')
hpar.T100 = st.sidebar.number_input("T1,0(0) (s)",
min_value=0.1,
max_value=3.0,
value=2.5,
step=0.05,
key='t100')
hpar.smax_model = st.sidebar.radio('The spin is ',
options=['tethered', 'free'],
key='smax_model')
if st.sidebar.checkbox("More"):
ppar.eiw = st.sidebar.number_input("Integration Width",
min_value=10,
max_value=500,
value=20,
step=10,
key='eiw')
hpar.field = st.sidebar.number_input("Field (mT)",
value=348.5,
step=1.0,
key='field')
hpar.t1_interp_method = st.sidebar.radio(
'T1 interpolation method',
options=['linear', 'second_order'],
index=1,
key='t1_interp_method')
return ppar, hpar
-2.4709892163826400, -2.5184316153191200, -2.556110148443770,
-2.576413132701720, -2.675593912859120, -2.8153300703866400,
-2.897475156648710, -3.0042154567120800, -3.087886507216510
]),
'E_power':
np.array([
0.0006454923080882520, 0.004277023425898170, 0.004719543572446050,
0.00909714298712173, 0.01344187403986090, 0.01896059941058610,
0.02101937603827090, 0.022335737104727900, 0.026029715703921800,
0.02917012237740640, 0.0338523245243911, 0.03820738749745440,
0.04733370907740660, 0.05269608016472140, 0.053790874615060400,
0.05697639350179900, 0.06435487925718170, 0.07909179437004270,
0.08958910066880800, 0.1051813598911370, 0.11617812912435900
])
}
TESTSET_PARAM = HydrationParameter()
TESTSET_PARAM.field = 348.5
TESTSET_PARAM.spin_C = 125
TESTSET_PARAM.T100 = 2.0
TESTSET_PARAM.T10 = 1.5
class TestHydration(unittest.TestCase):
def setUp(self):
ws = create_workspace()
hydration = {
k: TESTSET.get(k)
for k in ['T1', 'T1_power', 'E', 'E_power']
}
hydration.update({
k: TESTSET_PARAM.__dict__.get(k)
"""
drop_es, drop_t1s = {}, {}
if len(drop_e_powers) + len(drop_t1_powers) > 0:
drop_es = st.sidebar.multiselect('Drop Enhancements at power(s):',
drop_e_powers,
key='drop_es')
drop_t1s = st.sidebar.multiselect('Drop T1 at power(s):',
drop_t1_powers,
key='drop_t1s')
return drop_es, drop_t1s
# =======THE APP=======
ss = stss.get(
ppar=ProcParameter(drop_e_powers=[], drop_t1_powers=[]),
hpar=HydrationParameter(),
results={},
expname='',
old_expname='',
data={},
epowers=[], # E_power from the data
t1powers=[], # T1_power from the data
b_run=False)
st.markdown('<style>' + open('app.css').read() + '</style>',
unsafe_allow_html=True)
st.title(
f'ODNPLab: One-Step ODNP Processing \n {VERSION} \t Powered by [DNPLab]({DNPLAB_DOC_LINK}) '
)
st.markdown("## Upload a Zip file")