def test_add_random_variables_and_statements(pheno_path):
model = Model(pheno_path)
rvs = model.random_variables
pset = model.parameters
eta = RandomVariable.normal('ETA_NEW', 'iiv', 0, S('omega'))
rvs.append(eta)
pset.append(Parameter('omega', 0.1))
eps = RandomVariable.normal('EPS_NEW', 'ruv', 0, S('sigma'))
rvs.append(eps)
pset.append(Parameter('sigma', 0.1))
model.random_variables = rvs
model.parameters = pset
sset = model.get_pred_pk_record().statements
statement_new = Assignment(S('X'), 1 + S(eps.name) + S(eta.name))
sset.append(statement_new)
model.get_pred_pk_record().statements = sset
model.update_source()
assert str(model.get_pred_pk_record()).endswith('X = 1 + ETA(3) + EPS(2)\n\n')
def test_remove_iov(testdata):
model = Model(testdata / 'nonmem/pheno_block.mod')
model_str = str(model)
model_with_iov = re.sub(
r'\$OMEGA 0.031128 ; IVV\n\$OMEGA 0.1',
r'$OMEGA BLOCK(1)\n0.1\n$OMEGA BLOCK(1) SAME\n',
model_str,
)
model.control_stream = NMTranParser().parse(model_with_iov)
remove_iov(model)
model.update_source()
assert (str(model.get_pred_pk_record()) == '$PK\n'
'CL=THETA(1)*EXP(ETA(1))\n'
'V = THETA(2)\n'
'S1 = ETA(2) + ETA(3) + V\n\n')
rec_omega = ''.join(
str(rec) for rec in model.control_stream.get_records('OMEGA'))
assert (rec_omega == '$OMEGA 0.0309626 ; IVCL\n'
'$OMEGA BLOCK(2)\n'
'0.0309626\n'
'0.0005 0.031128\n')
model = Model(testdata / 'nonmem/pheno_block.mod')
with pytest.warns(UserWarning):
remove_iov(model)
def test_add_parameters_and_statements(pheno_path, param_new, statement_new, buf_new):
model = Model(pheno_path)
pset = model.parameters
pset.append(param_new)
model.parameters = pset
sset = model.statements
# Insert new statement before ODE system.
new_sset = ModelStatements()
for s in sset:
if isinstance(s, ODESystem):
new_sset.append(statement_new)
new_sset.append(s)
model.statements = new_sset
model.update_source()
rec = (
f'$PK\n'
f'IF(AMT.GT.0) BTIME=TIME\n'
f'TAD=TIME-BTIME\n'
f'TVCL=THETA(1)*WGT\n'
f'TVV=THETA(2)*WGT\n'
f'IF(APGR.LT.5) TVV=TVV*(1+THETA(3))\n'
f'CL=TVCL*EXP(ETA(1))\n'
f'V=TVV*EXP(ETA(2))\n'
f'S1=V\n'
f'{buf_new}\n\n'
)
assert str(model.get_pred_pk_record()) == rec
def test_remove_iiv(testdata, etas, pk_ref, omega_ref):
model = Model(testdata / 'nonmem/pheno_block.mod')
remove_iiv(model, etas)
model.update_source()
assert str(model.get_pred_pk_record()) == pk_ref
rec_omega = ''.join(
str(rec) for rec in model.control_stream.get_records('OMEGA'))
assert rec_omega == omega_ref
def test_block_rvs(testdata, etas, pk_ref, omega_ref):
with ConfigurationContext(conf, parameter_names='comment'):
model = Model(testdata / 'nonmem/pheno_block.mod')
create_rv_block(model, etas)
model.update_source()
assert str(model.get_pred_pk_record()) == pk_ref
rec_omega = ''.join(
str(rec) for rec in model.control_stream.get_records('OMEGA'))
assert rec_omega == omega_ref
def test_john_draper(pheno_path, etas, etad, buf_new):
model = Model(pheno_path)
john_draper(model, etas)
model.update_source()
rec_ref = (f'$PK\n'
f'{etad}\n'
f'IF(AMT.GT.0) BTIME=TIME\n'
f'TAD=TIME-BTIME\n'
f'TVCL=THETA(1)*WGT\n'
f'TVV=THETA(2)*WGT\n'
f'IF(APGR.LT.5) TVV=TVV*(1+THETA(3))\n'
f'{buf_new}\n'
f'S1=V\n\n')
assert str(model.get_pred_pk_record()) == rec_ref
def test_boxcox(pheno_path, etas, etab, buf_new):
model = Model(pheno_path)
boxcox(model, etas)
model.update_source()
rec_ref = (f'$PK\n'
f'{etab}\n'
f'IF(AMT.GT.0) BTIME=TIME\n'
f'TAD=TIME-BTIME\n'
f'TVCL=THETA(1)*WGT\n'
f'TVV=THETA(2)*WGT\n'
f'IF(APGR.LT.5) TVV=TVV*(1+THETA(3))\n'
f'{buf_new}\n'
f'S1=V\n\n')
assert str(model.get_pred_pk_record()) == rec_ref
assert model.parameters['lambda1'].init == 0.01
def test_add_covariate_effect(pheno_path, effect, covariate, operation,
buf_new):
model = Model(pheno_path)
add_covariate_effect(model, 'CL', covariate, effect, operation)
model.update_source()
rec_ref = (f'$PK\n'
f'IF(AMT.GT.0) BTIME=TIME\n'
f'TAD=TIME-BTIME\n'
f'TVCL=THETA(1)*WGT\n'
f'TVV=THETA(2)*WGT\n'
f'IF(APGR.LT.5) TVV=TVV*(1+THETA(3))\n'
f'CL=TVCL*EXP(ETA(1))\n'
f'{buf_new}\n'
f'V=TVV*EXP(ETA(2))\n'
f'S1=V\n\n')
assert str(model.get_pred_pk_record()) == rec_ref
def test_add_etas(pheno_path, parameter, expression, operation, buf_new):
model = Model(pheno_path)
add_etas(model, parameter, expression, operation)
model.update_source()
rec_ref = (f'$PK\n'
f'IF(AMT.GT.0) BTIME=TIME\n'
f'TAD=TIME-BTIME\n'
f'TVCL=THETA(1)*WGT\n'
f'TVV=THETA(2)*WGT\n'
f'IF(APGR.LT.5) TVV=TVV*(1+THETA(3))\n'
f'CL=TVCL*EXP(ETA(1))\n'
f'{buf_new}\n\n')
assert str(model.get_pred_pk_record()) == rec_ref
last_rec = model.control_stream.get_records('OMEGA')[-1]
assert str(last_rec) == f'$OMEGA 0.09 ; IIV_{parameter}\n'
def test_tdist(pheno_path):
model = Model(pheno_path)
tdist(model, ['ETA(1)'])
model.update_source()
symbol = 'ETAT1'
eta = 'ETA(1)'
theta = 'THETA(4)'
num_1 = f'{eta}**2 + 1'
denom_1 = f'4*{theta}'
num_2 = f'5*{eta}**4 + 16*{eta}**2 + 3'
denom_2 = f'96*{theta}**2'
num_3 = f'3*{eta}**6 + 19*{eta}**4 + 17*{eta}**2 - 15'
denom_3 = f'384*{theta}**3'
expression = (f'(1 + ({num_1})/({denom_1}) + ({num_2})/({denom_2}) + '
f'({num_3})/({denom_3}))*ETA(1)')
rec_ref = (f'$PK\n'
f'{symbol} = {expression}\n'
f'IF(AMT.GT.0) BTIME=TIME\n'
f'TAD=TIME-BTIME\n'
f'TVCL=THETA(1)*WGT\n'
f'TVV=THETA(2)*WGT\n'
f'IF(APGR.LT.5) TVV=TVV*(1+THETA(3))\n'
f'CL = TVCL*EXP(ETAT1)\n'
f'V=TVV*EXP(ETA(2))\n'
f'S1=V\n\n')
assert str(model.get_pred_pk_record()) == rec_ref
assert model.parameters['df1'].init == 80
