doc: Fix references

doc/implementation_discontinuities.rst

@@ -36,9 +36,9 @@ Solution Jump Discontinuities
 
 SUNDIALS by itself does not support solution jump discontinuities. We
 implement support by accessing private SUNDIALS API in
-:cpp:func:`amici::Solver::resetState`,
-:cpp:func:`amici::Solver::reInitPostProcess` and
-:cpp:func:`amici::Solver::reInitPostProcessB`. These functions reset interval
+:cpp:func:`amici::Solver::reset_tate`,
+:cpp:func:`amici::Solver::reinit_post_process` and
+:cpp:func:`amici::Solver::reinit_post_process_b`. These functions reset interval
 variables to initial values to simulate a fresh integration start, but
 keep/update the solution history, which is important for adjoint solutions.
 

include/amici/model.h

@@ -884,8 +884,8 @@ class Model : public AbstractModel, public ModelDimensions {
     /**
      * @brief Sets the estimated lower boundary for sigma_y.
      *
-     * When :meth:`setAddSigmaResiduals` is activated, this lower boundary must
-     * ensure that log(sigma) + min_sigma > 0.
+     * When :meth:`set_add_sigma_residuals` is activated, this lower boundary
+     * must ensure that log(sigma) + min_sigma > 0.
      *
      * @param min_sigma lower boundary
      */

python/sdist/amici/importers/petab/_petab_importer.py

@@ -634,7 +634,7 @@ def rdatas_to_measurement_df(
     ``rdatas`` and own information.
 
     :param rdatas:
-        A sequence of :class:`amici.ReturnData`.
+        A sequence of :class:`amici.sim.sundials.ReturnData`.
     :param model:
         AMICI model used to generate ``rdatas``.
     :param petab_problem:
@@ -693,7 +693,7 @@ def rdatas_to_simulation_df(
     ``rdatas`` and own information.
 
     :param rdatas:
-        A sequence of :class:`amici.ReturnData`.
+        A sequence of :class:`amici.sim.sundials.ReturnData`.
     :param model:
         AMICI model used to generate ``rdatas``.
     :param petab_problem:

python/sdist/amici/importers/pysb/__init__.py

@@ -89,7 +89,7 @@ def pysb2jax(
         simulations.
 
     :param model:
-        pysb model, :attr:`pysb.Model.name` will determine the name of the
+        pysb model, :attr:`pysb.core.Model.name` will determine the name of the
         generated module
 
     :param output_dir:
@@ -98,12 +98,12 @@ def pysb2jax(
     :param observation_model:
         The different measurement channels that make up the observation
         model, see also :class:`amici.importers.utils.MeasurementChannel`.
-        The ID is expected to be the name of a :class:`pysb.Expression` or
-        :class:`pysb.Observable` in the provided model that should be mapped to
-        an observable.
-        ``sigma`` is expected to be the name of a :class:`pysb.Expression` to
-        be mapped to the scale parameter of the noise distribution.
-        ``MeasurementChannel.formula`` is expected to be
+        The ID is expected to be the name of a :class:`pysb.core.Expression` or
+        :class:`pysb.core.Observable` in the provided model that should be
+        mapped to an observable.
+        ``sigma`` is expected to be the name of a :class:`pysb.core.Expression`
+        to be mapped to the scale parameter of the noise distribution.
+        :attr:`MeasurementChannel.formula` is expected to be
         ``None``. Event-observables are not supported.
 
     :param verbose: verbosity level for logging, True/False default to
@@ -124,11 +124,12 @@ def pysb2jax(
         https://github.com/AMICI-dev/AMICI/pull/1672
 
     :param model_name:
-        Name for the generated model module. If None, :attr:`pysb.Model.name`
-        will be used.
+        Name for the generated model module.
+        If None, :attr:`pysb.core.Model.name` will be used.
 
     :param pysb_model_has_obs_and_noise:
-        if set to ``True``, the pysb model is expected to have extra observables and noise variables added
+        If set to ``True``, the pysb model is expected to have extra
+        observables and noise variables added.
     """
     model_name = model_name or model.name
 
@@ -199,15 +200,16 @@ def pysb2amici(
         The different measurement channels that make up the observation
         model, see also :class:`amici.importers.utils.MeasurementChannel`.
         The ID is expected to be the name of a :class:`pysb.core.Expression` or
-        :class:`pysb.Observable` in the provided model that should be mapped to
-        an observable.
-        ``sigma`` is expected to be the name of a :class:`pysb.Expression` to
-        be mapped to the scale parameter of the noise distribution.
-        ``MeasurementChannel.formula`` is expected to be
+        :class:`pysb.core.Observable` in the provided model that should be
+        mapped to an observable.
+        ``sigma`` is expected to be the name of a :class:`pysb.core.Expression`
+        to be mapped to the scale parameter of the noise distribution.
+        :attr:`MeasurementChannel.formula` is expected to be
         ``None``. Event-observables are not supported.
 
     :param fixed_parameters:
-        list of :class:`pysb.core.Parameter` to be excluded from sensitivity analysis
+        list of :class:`pysb.core.Parameter` to be excluded from sensitivity
+        analysis.
 
     :param verbose: verbosity level for logging, True/False default to
         :attr:`logging.DEBUG`/:attr:`logging.ERROR`
@@ -244,8 +246,8 @@ def pysb2amici(
         generated
 
     :param model_name:
-        Name for the generated model module. If None, :attr:`pysb.Model.name`
-        will be used.
+        Name for the generated model module.
+        If None, :attr:`pysb.core.Model.name` will be used.
 
     :param pysb_model_has_obs_and_noise:
         if set to ``True``, the pysb model is expected to have extra
@@ -323,7 +325,7 @@ def ode_model_from_pysb_importer(
     _events: list[Event] = None,
 ) -> DEModel:
     """
-    Creates an :class:`amici.DEModel` instance from a :class:`pysb.Model`
+    Creates an :class:`DEModel` instance from a :class:`pysb.core.Model`
     instance.
 
     :param model:

python/sdist/amici/importers/utils.py

@@ -183,7 +183,7 @@ def __init__(
             Expression representing the scale parameter of the noise
             distribution. This can be a numeric value, a sympy expression,
             or an expression string that will be passed to
-            :func:`sympy.sympify`.
+            :func:`sympy.core.sympify.sympify`.
         :param event_id:
             Identifier of the associated event for event-resolved observables.
             `None` for time-resolved observables.

python/sdist/amici/sim/sundials/_debugging.py

@@ -21,7 +21,7 @@ def get_model_for_preeq(
     During preequilibration, event-handling is disabled. However, when
     simulating the returned model, event-handling will be enabled.
     For events triggered at fixed timepoints, this can be avoided by setting
-    :meth:`t0 <amici.Model.setT0>` to a timepoints after the last trigger
+    :meth:`t0 <amici.Model.set_t0>` to a timepoints after the last trigger
     timepoint.
 
     :param model:

python/sdist/amici/sim/sundials/_swig_wrappers.py

@@ -139,7 +139,7 @@ def read_solver_settings_from_hdf5(
     file: str, solver: AmiciSolver, location: str | None = "solverSettings"
 ) -> None:
     """
-    Convenience wrapper for :py:func:`amici.read_solver_settings_from_hdf5`
+    Apply solver settings from an HDF5 file to a Solver instance.
 
     :param file: hdf5 filename
     :param solver: Solver instance to which settings will be transferred
@@ -154,10 +154,9 @@ def write_solver_settings_to_hdf5(
     location: str | None = "solverSettings",
 ) -> None:
     """
-    Convenience wrapper for :py:func:`amici.amici.writeSolverSettingsToHDF5`
+    Write solver settings from a Solver instance to an HDF5 file.
 
-    :param file: hdf5 filename, can also be an object created by
-        :py:func:`amici.amici.createOrOpenForWriting`
+    :param file: hdf5 filename
     :param solver: Solver instance from which settings will be stored
     :param location: location of solver settings in hdf5 file
     """

python/sdist/amici/sim/sundials/petab/_v2.py

@@ -10,7 +10,6 @@
 
 import numpy as np
 import sympy as sp
-from petab import v1 as v1
 from petab import v2 as v2
 from petab.v2 import ExperimentPeriod
 
@@ -41,7 +40,7 @@ class ExperimentManager:
     Handles the creation of :class:`ExpData` objects for a given model and
     PEtab problem.
 
-    The assumption is that we have a set of :class:`amici.ExpData` objects,
+    The assumption is that we have a set of :class:`ExpData` objects,
     one for each PEtab experiment.
     Those are updated based on a set of global parameters (PEtab
     problem parameters, as opposed to model parameters for a single experiment

python/sdist/amici/sim/sundials/petab/v1/_conditions.py

@@ -242,7 +242,7 @@ def create_parameterized_edatas(
     simulation_conditions: pd.DataFrame | dict = None,
     warn_unused: bool = True,
 ) -> list[ExpData]:
-    """Create list of :class:ExpData objects with parameters filled in.
+    """Create list of :class:`ExpData` objects with parameters filled in.
 
     :param amici_model:
         AMICI Model assumed to be compatible with ``petab_problem``.
@@ -258,9 +258,10 @@ def create_parameterized_edatas(
         If ``False``, they are assumed to be in linear scale.
     :param parameter_mapping:
         Optional precomputed PEtab parameter mapping for efficiency, as
-        generated by :func:`create_parameter_mapping`.
+        generated by
+        :func:`amici.sim.sundials.petab.v1.create_parameter_mapping`.
     :param simulation_conditions:
-        Result of :func:`petab.get_simulation_conditions`. Can be provided to
+        Result of :func:`petab.v1.get_simulation_conditions`. Can be provided to
         save time if this has been obtained before.
     :param warn_unused:
         Whether a warning should be emitted if not all problem parameters

python/sdist/amici/sim/sundials/petab/v1/_simulations.py

@@ -97,8 +97,8 @@ def simulate_petab(
         ``nominalValues`` will be used. To be provided as dict, mapping PEtab
         problem parameters to SBML IDs.
     :param simulation_conditions:
-        Result of :py:func:`petab.get_simulation_conditions`. Can be provided
-        to save time if this has be obtained before.
+        Result of :py:func:`petab.v1.get_simulation_conditions`.
+        Can be provided to save time if this has be obtained before.
         Not required if ``edatas`` and ``parameter_mapping`` are provided.
     :param edatas:
         Experimental data. Parameters are inserted in-place for simulation.
@@ -113,7 +113,7 @@ def simulate_petab(
         If `parameter_mapping` is provided, this must match the value of
         `scaled_parameters` used to generate the mapping.
     :param log_level:
-        Log level, see :mod:`amici.logging` module.
+        Log level, see :mod:`logging` module.
     :param num_threads:
         Number of threads to use for simulating multiple conditions
         (only used if compiled with OpenMP).
@@ -128,12 +128,12 @@ def simulate_petab(
         Dictionary of
 
         * cost function value (``LLH``),
-        * list of :class:`amici.amici.ReturnData` (``RDATAS``),
-        * list of :class:`amici.amici.ExpData` (``EDATAS``),
+        * list of :class:`ReturnData` (``RDATAS``),
+        * list of :class:`ExpData` (``EDATAS``),
 
         corresponding to the different simulation conditions.
         For ordering of simulation conditions, see
-        :meth:`petab.Problem.get_simulation_conditions_from_measurement_df`.
+        :meth:`petab.v1.Problem.get_simulation_conditions_from_measurement_df`.
     """
     logger.setLevel(log_level)
 
@@ -418,7 +418,7 @@ def rdatas_to_measurement_df(
 
     :param rdatas:
         A sequence of rdatas with the ordering of
-        :func:`petab.get_simulation_conditions`.
+        :func:`petab.v1.get_simulation_conditions`.
 
     :param model:
         AMICI model used to generate ``rdatas``.

python/sdist/amici/sim/sundials/petab/v1/_simulator.py

@@ -45,8 +45,8 @@ def simulate_without_noise(self, **kwargs) -> pd.DataFrame:
         Additional keyword arguments can be supplied to specify arguments for
         the AMICI PEtab import, simulate, and export methods. See the
         docstrings for the respective methods for argument options:
-        - :py:func:`amici.petab_import.import_petab_problem`, and
-        - :py:func:`amici.petab_objective.simulate_petab`.
+        - :py:func:`import_petab_problem`, and
+        - :py:func:`simulate_petab`.
 
         Note that some arguments are expected to have already been specified
         in the Simulator constructor (including the PEtab problem).

python/sdist/amici/sim/sundials/plotting.py

@@ -40,7 +40,7 @@ def plot_state_trajectories(
     :param state_indices:
         Indices of state variables for which trajectories are to be plotted.
     :param ax:
-        :class:`matplotlib.pyplot.Axes` instance to plot into.
+        :class:`matplotlib.axes.Axes` instance to plot into.
     :param model:
         The model *rdata* was generated from.
     :param prefer_names:
@@ -103,7 +103,7 @@ def plot_observable_trajectories(
     :param observable_indices:
         Indices of observables for which trajectories are to be plotted.
     :param ax:
-        :class:`matplotlib.pyplot.Axes` instance to plot into.
+        :class:`matplotlib.axes.Axes` instance to plot into.
     :param model:
         The model *rdata* was generated from.
     :param prefer_names:

swig/amici.i

@@ -282,7 +282,7 @@ def __repr__(self):
 "Swig-Generated class, which, in contrast to other Vector
 classes, does not allow for simple interoperability with common
 Python types, but must be created using
-:func:`amici.amici.parameter_scaling_from_int_vector`";
+:func:`parameter_scaling_from_int_vector`";
 %{
 namespace amici {
 std::vector<amici::ParameterScaling> parameter_scaling_from_int_vector(std::vector<int> const& int_vec) {

swig/model.i

@@ -177,7 +177,7 @@ def simulate(
     """Simulate model with given solver and experimental data.
 
     :param solver:
-        Solver to use for simulation. Defaults to :meth:`Model.get_solver`.
+        Solver to use for simulation. Defaults to :meth:`Model.create_solver`.
     :param edata:
         Experimental data to use for simulation.
         A single :class:`ExpData` instance or a sequence of such instances.

tests/sbml/utils.py

@@ -2,7 +2,7 @@
 
 from pathlib import Path
 
-import amici
+import amici.sim.sundials as asd
 import libsbml as sbml
 import numpy as np
 import pandas as pd
@@ -12,10 +12,10 @@
 
 def verify_results(
     settings,
-    rdata: amici.ReturnData,
+    rdata: asd.ReturnData,
     expected,
     wrapper,
-    model: amici.Model,
+    model: asd.Model,
     atol,
     rtol,
 ):
@@ -201,7 +201,7 @@ def get_amount_and_variables(settings):
 
 
 def apply_settings(
-    settings, solver: amici.Solver, model: amici.Model, test_id: str
+    settings, solver: asd.Solver, model: asd.Model, test_id: str
 ):
     """Apply model and solver settings as specified in the test case"""
     # start/duration/steps may be empty