Rename & fix notebooks

pypesto/hierarchical/inner_calculator_collector.py

@@ -49,9 +49,9 @@
 
 from .ordinal import OrdinalCalculator, OrdinalInnerSolver, OrdinalProblem
 from .semiquantitative import (
-    SemiquantitativeCalculator,
-    SemiquantitativeInnerProblem,
-    SemiquantitativeInnerSolver,
+    SemiquantCalculator,
+    SemiquantInnerSolver,
+    SemiquantProblem,
 )
 
 AmiciModel = Union['amici.Model', 'amici.ModelPtr']
@@ -146,15 +146,13 @@ def construct_inner_calculators(
                 if key in SPLINE_APPROXIMATION_OPTIONS
             }
             spline_ratio = spline_inner_options.pop(SPLINE_RATIO, None)
-            spline_inner_problem = (
-                SemiquantitativeInnerProblem.from_petab_amici(
-                    petab_problem, model, edatas, spline_ratio
-                )
+            spline_inner_problem = SemiquantProblem.from_petab_amici(
+                petab_problem, model, edatas, spline_ratio
             )
-            spline_inner_solver = SemiquantitativeInnerSolver(
+            spline_inner_solver = SemiquantInnerSolver(
                 options=spline_inner_options
             )
-            spline_calculator = SemiquantitativeCalculator(
+            spline_calculator = SemiquantCalculator(
                 spline_inner_problem, spline_inner_solver
             )
             self.noise_dummy_values = (

pypesto/hierarchical/semiquantitative/__init__.py

@@ -10,7 +10,7 @@
 hierarchical optimization problem.
 """
 
-from .calculator import SemiquantitativeCalculator
-from .parameter import SemiquantitativeInnerParameter
-from .problem import SemiquantitativeInnerProblem
-from .solver import SemiquantitativeInnerSolver
+from .calculator import SemiquantCalculator
+from .parameter import SplineInnerParameter
+from .problem import SemiquantProblem
+from .solver import SemiquantInnerSolver

pypesto/hierarchical/semiquantitative/calculator.py

@@ -27,8 +27,8 @@
     filter_return_dict,
     init_return_values,
 )
-from .problem import SemiquantitativeInnerProblem
-from .solver import SemiquantitativeInnerSolver
+from .problem import SemiquantProblem
+from .solver import SemiquantInnerSolver
 
 try:
     import amici
@@ -37,7 +37,7 @@
     pass
 
 
-class SemiquantitativeCalculator(AmiciCalculator):
+class SemiquantCalculator(AmiciCalculator):
     """A calculator is passed as `calculator` to the pypesto.AmiciObjective.
 
     The object is called by :func:`pypesto.AmiciObjective.call_unprocessed`
@@ -46,8 +46,8 @@ class SemiquantitativeCalculator(AmiciCalculator):
 
     def __init__(
         self,
-        inner_problem: SemiquantitativeInnerProblem,
-        inner_solver: SemiquantitativeInnerSolver = None,
+        inner_problem: SemiquantProblem,
+        inner_solver: SemiquantInnerSolver = None,
     ):
         """Initialize the calculator from the given problem.
 
@@ -63,7 +63,7 @@ def __init__(
         self.inner_problem = inner_problem
 
         if inner_solver is None:
-            inner_solver = SemiquantitativeInnerSolver()
+            inner_solver = SemiquantInnerSolver()
         self.inner_solver = inner_solver
 
     def initialize(self):

pypesto/hierarchical/semiquantitative/parameter.py

@@ -6,7 +6,7 @@
 logger = logging.getLogger(__name__)
 
 
-class SemiquantitativeInnerParameter(InnerParameter):
+class SplineInnerParameter(InnerParameter):
     """A spline (inner) parameter of the spline hierarchical optimization problem.
 
     Attributes

pypesto/hierarchical/semiquantitative/problem.py

@@ -28,7 +28,7 @@
     ix_matrices_from_arrays,
     scale_value,
 )
-from .parameter import SemiquantitativeInnerParameter
+from .parameter import SplineInnerParameter
 
 try:
     import amici
@@ -45,7 +45,7 @@
     pass
 
 
-class SemiquantitativeInnerProblem(AmiciInnerProblem):
+class SemiquantProblem(AmiciInnerProblem):
     """Inner optimization problem for semi-quantitative data.
 
     The inner problem for semi-quantitative data consists of spline parameters
@@ -129,7 +129,7 @@ def from_petab_amici(
         amici_model: 'amici.Model',
         edatas: List['amici.ExpData'],
         spline_ratio: float = None,
-    ) -> 'SemiquantitativeInnerProblem':
+    ) -> 'SemiquantProblem':
         """Construct the inner problem from the `petab_problem`."""
         if spline_ratio is None:
             spline_ratio = get_default_options()
@@ -142,9 +142,7 @@ def get_groups_for_xs(self, inner_parameter_type: str) -> List[int]:
         groups = [x.group for x in self.get_xs_for_type(inner_parameter_type)]
         return list(set(groups))
 
-    def get_xs_for_group(
-        self, group: int
-    ) -> List[SemiquantitativeInnerParameter]:
+    def get_xs_for_group(self, group: int) -> List[SplineInnerParameter]:
         r"""Get ``SplineParameter``\s that belong to the given group."""
         return [
             x
@@ -153,9 +151,7 @@ def get_xs_for_group(
             and x.inner_parameter_type == InnerParameterType.SPLINE
         ]
 
-    def get_free_xs_for_group(
-        self, group: int
-    ) -> List[SemiquantitativeInnerParameter]:
+    def get_free_xs_for_group(self, group: int) -> List[SplineInnerParameter]:
         r"""Get ``SplineParameter``\s that are free and belong to the given group."""
         return [
             x
@@ -165,9 +161,7 @@ def get_free_xs_for_group(
             and x.inner_parameter_type == InnerParameterType.SPLINE
         ]
 
-    def get_fixed_xs_for_group(
-        self, group: int
-    ) -> List[SemiquantitativeInnerParameter]:
+    def get_fixed_xs_for_group(self, group: int) -> List[SplineInnerParameter]:
         r"""Get ``SplineParameter``\s that are fixed and belong to the given group."""
         return [
             x
@@ -179,7 +173,7 @@ def get_fixed_xs_for_group(
 
     def get_noise_parameters_for_group(
         self, group: int
-    ) -> SemiquantitativeInnerParameter:
+    ) -> SplineInnerParameter:
         r"""Get the ``SplineParameter``\ that is a noise parameters and belongs to the given group."""
         return [
             x
@@ -267,7 +261,7 @@ def spline_inner_problem_from_petab_problem(
     for par in inner_parameters:
         par.ixs = ix_matrices[par.inner_parameter_id]
 
-    return SemiquantitativeInnerProblem(
+    return SemiquantProblem(
         xs=inner_parameters,
         data=data,
         edatas=edatas,
@@ -279,7 +273,7 @@ def spline_inner_parameters_from_measurement_df(
     df: pd.DataFrame,
     spline_ratio: float,
     amici_model: 'amici.Model',
-) -> List[SemiquantitativeInnerParameter]:
+) -> List[SplineInnerParameter]:
     """Create list of inner free spline parameters from PEtab measurement table."""
     df = df.reset_index()
 
@@ -305,7 +299,7 @@ def spline_inner_parameters_from_measurement_df(
         for par_index in range(n_spline_parameters):
             par_id = f'{par_type}_{observable_id}_{group}_{par_index+1}'
             inner_parameters.append(
-                SemiquantitativeInnerParameter(
+                SplineInnerParameter(
                     inner_parameter_id=par_id,
                     inner_parameter_type=InnerParameterType.SPLINE,
                     scale=LIN,
@@ -326,7 +320,7 @@ def spline_inner_parameters_from_measurement_df(
 def noise_inner_parameters_from_parameter_df(
     petab_problem: 'petab.Problem',
     amici_model: 'amici.Model',
-) -> List[SemiquantitativeInnerParameter]:
+) -> List[SplineInnerParameter]:
     """Create list of inner free noise parameters from PEtab parameter table."""
     # Select the nonlinear monotone measurements.
     measurement_df = petab_problem.measurement_df
@@ -357,7 +351,7 @@ def noise_inner_parameters_from_parameter_df(
         group = observable_ids.index(observable_id) + 1
 
         noise_parameters.append(
-            SemiquantitativeInnerParameter(
+            SplineInnerParameter(
                 inner_parameter_id=row[PARAMETER_ID],
                 inner_parameter_type=InnerParameterType.SIGMA,
                 scale=LIN,
@@ -376,7 +370,7 @@ def noise_inner_parameters_from_parameter_df(
 def spline_ixs_for_measurement_specific_parameters(
     petab_problem: 'petab.Problem',
     amici_model: 'amici.Model',
-    inner_parameters: List[SemiquantitativeInnerParameter],
+    inner_parameters: List[SplineInnerParameter],
 ) -> Dict[str, List[Tuple[int, int, int]]]:
     """Create mapping of parameters to measurements.
 
@@ -448,7 +442,7 @@ def spline_ixs_for_measurement_specific_parameters(
 
 def get_spline_inner_par_ids_for_measurement(
     measurement: Dict,
-    inner_parameters: List[SemiquantitativeInnerParameter],
+    inner_parameters: List[SplineInnerParameter],
 ):
     """Return inner parameter ids of parameters which are related to the measurement."""
     return [

pypesto/hierarchical/semiquantitative/solver.py

@@ -24,16 +24,16 @@
     InnerParameterType,
 )
 from ..base_solver import InnerSolver
-from .parameter import SemiquantitativeInnerParameter
-from .problem import SemiquantitativeInnerProblem
+from .parameter import SplineInnerParameter
+from .problem import SemiquantProblem
 
 try:
     from amici.parameter_mapping import ParameterMapping
 except ImportError:
     pass
 
 
-class SemiquantitativeInnerSolver(InnerSolver):
+class SemiquantInnerSolver(InnerSolver):
     """Solver of the inner subproblem of spline approximation for nonlinear-monotone data.
 
     Options
@@ -76,7 +76,7 @@ def validate_options(self):
 
     def solve(
         self,
-        problem: SemiquantitativeInnerProblem,
+        problem: SemiquantProblem,
         sim: List[np.ndarray],
         amici_sigma: List[np.ndarray],
     ) -> list:
@@ -155,7 +155,7 @@ def calculate_obj_function(x_inner_opt: list):
 
     def calculate_gradients(
         self,
-        problem: SemiquantitativeInnerProblem,
+        problem: SemiquantProblem,
         x_inner_opt: List[Dict],
         sim: List[np.ndarray],
         amici_sigma: List[np.ndarray],
@@ -363,7 +363,7 @@ def get_default_options() -> Dict:
 
     def _optimize_spline(
         self,
-        inner_parameters: List[SemiquantitativeInnerParameter],
+        inner_parameters: List[SplineInnerParameter],
         group_dict: Dict,
     ):
         """Run optimization for the inner problem.
@@ -524,7 +524,7 @@ def _get_minimal_difference(
 
     def _get_inner_optimization_options(
         self,
-        inner_parameters: List[SemiquantitativeInnerParameter],
+        inner_parameters: List[SplineInnerParameter],
         N: int,
         min_meas: float,
         max_meas: float,
@@ -1059,7 +1059,7 @@ def extract_expdata_using_mask(
 
 
 def save_inner_parameters_to_inner_problem(
-    inner_problem: SemiquantitativeInnerProblem,
+    inner_problem: SemiquantProblem,
     s: np.ndarray,
     group: int,
 ) -> None:

pypesto/visualize/spline_approximation.py

@@ -21,11 +21,9 @@
 try:
     import amici
 
-    from ..hierarchical.semiquantitative.calculator import (
-        SemiquantitativeCalculator,
-    )
+    from ..hierarchical.semiquantitative.calculator import SemiquantCalculator
     from ..hierarchical.semiquantitative.solver import (
-        SemiquantitativeInnerSolver,
+        SemiquantInnerSolver,
         _calculate_regularization_for_group,
         get_spline_mapped_simulations,
     )
@@ -107,7 +105,7 @@ def plot_splines_from_pypesto_result(
     for (
         calculator
     ) in pypesto_result.problem.objective.calculator.inner_calculators:
-        if isinstance(calculator, SemiquantitativeCalculator):
+        if isinstance(calculator, SemiquantCalculator):
             spline_calculator = calculator
             break
 
@@ -192,7 +190,7 @@ def plot_splines_from_inner_result(
             delta_c,
             spline_bases,
             n,
-        ) = SemiquantitativeInnerSolver._rescale_spline_bases(
+        ) = SemiquantInnerSolver._rescale_spline_bases(
             self=None,
             sim_all=simulation,
             N=len(inner_parameters),
@@ -357,7 +355,7 @@ def _add_spline_mapped_simulations_to_model_fit(
 
     spline_calculator = None
     for calculator in pypesto_problem.objective.calculator.inner_calculators:
-        if isinstance(calculator, SemiquantitativeCalculator):
+        if isinstance(calculator, SemiquantCalculator):
             spline_calculator = calculator
             break
 
@@ -392,7 +390,7 @@ def _add_spline_mapped_simulations_to_model_fit(
             delta_c,
             spline_bases,
             n,
-        ) = SemiquantitativeInnerSolver._rescale_spline_bases(
+        ) = SemiquantInnerSolver._rescale_spline_bases(
             self=None,
             sim_all=simulation,
             N=len(inner_parameters),
@@ -510,7 +508,7 @@ def _obtain_regularization_for_start(
     for (
         calculator
     ) in pypesto_result.problem.objective.calculator.inner_calculators:
-        if isinstance(calculator, SemiquantitativeCalculator):
+        if isinstance(calculator, SemiquantCalculator):
             spline_calculator = calculator
             break
 
@@ -537,7 +535,7 @@ def _obtain_regularization_for_start(
             delta_c,
             spline_bases,
             n,
-        ) = SemiquantitativeInnerSolver._rescale_spline_bases(
+        ) = SemiquantInnerSolver._rescale_spline_bases(
             self=None,
             sim_all=simulation,
             N=len(inner_parameters),