def get_parameter_override_id_to_placeholder_id(
observable_df: pd.DataFrame, measurement_df: pd.DataFrame
) -> Tuple[Dict[str, List[str]], Dict[str, List[str]]]:
"""Get map of parameter overrides from PEtab measurement table to
placeholder parameter IDs from observable table that they are overriding.
Arguments:
observable_df: PEtab observable table
measurement_df: PEtab measurement table
Returns:
Dictionaries mapping parameter overrides to placeholder parameter IDs
that they are overriding, for observable parameters and noise
parameters.
"""
observable_placeholders = \
get_observable_placeholders_by_observable(observable_df)
noise_placeholders = \
get_noise_placeholders_by_observable(observable_df)
observable_parameter_override_id_to_placeholder_id = {}
noise_parameter_override_id_to_placeholder_id = {}
def _add(override_to_placeholders):
"""Add current overrides to destination map"""
assert (len(overrides) == len(placeholders))
for override, placeholder in zip(overrides, placeholders):
if isinstance(override, Number):
# TODO: we ignore numeric overrides, cannot currently use for
# hierarchical optimization
continue
try:
override_to_placeholders[override].append(placeholder)
except KeyError:
override_to_placeholders[override] = [placeholder]
for obs_id, obs_par, noise_par \
in zip(measurement_df[ptc.OBSERVABLE_ID],
measurement_df[ptc.OBSERVABLE_PARAMETERS],
measurement_df[ptc.NOISE_PARAMETERS]):
# observable parameters
overrides = petab.split_parameter_replacement_list(obs_par)
placeholders = observable_placeholders[obs_id]
_add(observable_parameter_override_id_to_placeholder_id)
# noise parameters
overrides = petab.split_parameter_replacement_list(noise_par)
placeholders = noise_placeholders[obs_id]
assert (len(overrides) == len(placeholders))
_add(noise_parameter_override_id_to_placeholder_id)
return observable_parameter_override_id_to_placeholder_id, \
noise_parameter_override_id_to_placeholder_id
def test_split_parameter_replacement_list():
assert petab.split_parameter_replacement_list('') == []
assert petab.split_parameter_replacement_list('param1') == ['param1']
assert petab.split_parameter_replacement_list('param1;param2') \
== ['param1', 'param2']
assert petab.split_parameter_replacement_list('1.0') == [1.0]
assert petab.split_parameter_replacement_list('1.0;2.0') == [1.0, 2.0]
assert petab.split_parameter_replacement_list('param1;2.2') \
== ['param1', 2.2]
assert petab.split_parameter_replacement_list(np.nan) == []
assert petab.split_parameter_replacement_list(1.5) == [1.5]
assert petab.split_parameter_replacement_list(None) == []
def evaluate_noise_formula(measurement: pd.Series, noise_formulas: dict,
parameter_df: pd.DataFrame,
simulation: float) -> float:
"""Fill in parameters for `measurement` and evaluate noise_formula.
Arguments:
measurement: A measurement table row.
noise_formulas: The noise formulas as computed by
`get_symbolic_noise_formulas`.
parameter_df: The parameter table.
simulation: The simulation corresponding to the measurement, scaled.
Returns:
noise_value: The noise value.
"""
# the observable id
observable_id = measurement[OBSERVABLE_ID]
# extract measurement specific overrides
observable_parameter_overrides = petab.split_parameter_replacement_list(
measurement.get(NOISE_PARAMETERS, None))
overrides = {}
# fill in measurement specific parameters
for i_obs_par, obs_par in enumerate(observable_parameter_overrides):
overrides[f"noiseParameter{i_obs_par+1}_{observable_id}"] = obs_par
# fill in observables
overrides[observable_id] = simulation
# fill in general parameters
for row in parameter_df.itertuples():
overrides[row.Index] = row.nominalValue
# replace parametric measurement specific parameters
for key, value in overrides.items():
if not isinstance(value, numbers.Number):
# is parameter
overrides[key] = parameter_df.loc[value, NOMINAL_VALUE]
# replace parameters by values in formula
noise_formula = noise_formulas[observable_id]
noise_value = noise_formula.subs(overrides)
# conversion is possible if all parameters are replaced
try:
noise_value = float(noise_value)
except TypeError:
raise TypeError(
f"Cannot replace all parameters in noise formula {noise_value} "
f"for observable {observable_id}.")
return noise_value
def test_split_parameter_replacement_list():
assert petab.split_parameter_replacement_list('') == []
assert petab.split_parameter_replacement_list('param1') == ['param1']
assert petab.split_parameter_replacement_list('param1;param2') \
== ['param1', 'param2']
assert petab.split_parameter_replacement_list('1.0') == [1.0]
assert petab.split_parameter_replacement_list('1.0;2.0') == [1.0, 2.0]
assert petab.split_parameter_replacement_list('param1;2.2') \
== ['param1', 2.2]
assert petab.split_parameter_replacement_list(np.nan) == []
assert petab.split_parameter_replacement_list(1.5) == [1.5]
assert petab.split_parameter_replacement_list(None) == []
with pytest.raises(ValueError):
assert petab.split_parameter_replacement_list('1.0;')
with pytest.raises(ValueError):
assert petab.split_parameter_replacement_list(';1.0')
def _get_overrides():
return split_parameter_replacement_list(row.noiseParameters)
def _get_overrides():
return split_parameter_replacement_list(row.observableParameters)
