Doc: Show typehints in description

doc/conf.py

@@ -56,6 +56,8 @@
     'sphinxcontrib.bibtex',
     # ensure that jQuery is installed
     'sphinxcontrib.jquery',
+    # type hint formatting
+    'sphinx_autodoc_typehints',
 ]
 
 # default autodoc options
@@ -84,6 +86,10 @@
     'fides': ('https://fides-optimizer.readthedocs.io/en/latest/', None),
 }
 
+
+typehints_document_rtype = True
+autodoc_typehints = "description"
+
 bibtex_bibfiles = ["using_pypesto.bib"]
 
 # Add any paths that contain templates here, relative to this directory.

pypesto/C.py

@@ -5,7 +5,7 @@
 """
 
 from enum import Enum
-from typing import Callable, Literal, Tuple, Union
+from typing import Literal, Tuple, Union
 
 ###############################################################################
 # ENSEMBLE
@@ -275,13 +275,6 @@ class InnerParameterType(str, Enum):
 CSV = 'csv'  # return file format
 H5 = 'h5'  # return file format
 
-
-###############################################################################
-# SELECT
-
-TYPE_POSTPROCESSOR = Callable[["ModelProblem"], None]  # noqa: F821
-
-
 ###############################################################################
 # VISUALIZE
 

pypesto/history/util.py

@@ -1,6 +1,7 @@
 """History utility functions."""
 
 import numbers
+from functools import wraps
 from typing import Dict, Sequence, Union
 
 import numpy as np
@@ -38,6 +39,7 @@ def trace_wrap(f):
     integer `ix` the output to a single value.
     """
 
+    @wraps(f)
     def wrapped_f(
         self, ix: Union[Sequence[int], int, None] = None, trim: bool = False
     ) -> Union[Sequence[Union[float, MaybeArray]], Union[float, MaybeArray]]:

pypesto/optimize/optimizer.py

@@ -5,6 +5,7 @@
 import re
 import time
 import warnings
+from functools import wraps
 from typing import TYPE_CHECKING, Dict, Optional
 
 import numpy as np
@@ -46,6 +47,7 @@ def history_decorator(minimize):
     Default decorator for the minimize() method.
     """
 
+    @wraps(minimize)
     def wrapped_minimize(
         self,
         problem: Problem,
@@ -129,6 +131,7 @@ def time_decorator(minimize):
     the wall-clock time.
     """
 
+    @wraps(minimize)
     def wrapped_minimize(
         self,
         problem: Problem,
@@ -160,6 +163,7 @@ def fix_decorator(minimize):
     derivatives).
     """
 
+    @wraps(minimize)
     def wrapped_minimize(
         self,
         problem: Problem,

pypesto/predict/task.py

@@ -28,7 +28,7 @@ class PredictorTask(Task):
 
     def __init__(
         self,
-        predictor: 'pypesto.predict.Predictor',  # noqa: F821
+        predictor,  #: 'pypesto.predict.Predictor',  # noqa: F821
         x: Sequence[float],
         sensi_orders: Tuple[int, ...],
         mode: ModeType,
@@ -41,7 +41,7 @@ def __init__(
         self.mode = mode
         self.id = id
 
-    def execute(self) -> 'pypesto.predict.PredictionResult':  # noqa: F821
+    def execute(self):  # -> 'pypesto.predict.PredictionResult':  # noqa: F821
         """Execute and return the prediction."""
         logger.debug(f"Executing task {self.id}.")
         prediction = self.predictor(self.x, self.sensi_orders, self.mode)

pypesto/select/method.py

@@ -14,9 +14,8 @@
     Model,
 )
 
-from ..C import TYPE_POSTPROCESSOR
 from ..problem import Problem
-from .model_problem import ModelProblem
+from .model_problem import TYPE_POSTPROCESSOR, ModelProblem
 
 
 class MethodSignalProceed(str, Enum):

pypesto/select/model_problem.py

@@ -4,15 +4,14 @@
 
 from petab_select import Criterion, Model
 
-from ..C import TYPE_POSTPROCESSOR
 from ..objective import ObjectiveBase
 from ..optimize import minimize
 from ..problem import Problem
 from ..result import OptimizerResult, Result
 from .misc import model_to_pypesto_problem
 
 OBJECTIVE_CUSTOMIZER_TYPE = Callable[[ObjectiveBase], None]
-POSTPROCESSOR_TYPE = Callable[["ModelProblem"], None]
+TYPE_POSTPROCESSOR = Callable[["ModelProblem"], None]  # noqa: F821
 
 
 class ModelProblem:
@@ -65,7 +64,7 @@ def __init__(
         x_guess: List[float] = None,
         minimize_options: Dict = None,
         objective_customizer: Optional[OBJECTIVE_CUSTOMIZER_TYPE] = None,
-        postprocessor: Optional[TYPE_POSTPROCESSOR] = None,
+        postprocessor: Optional["TYPE_POSTPROCESSOR"] = None,
         model_to_pypesto_problem_method: Callable[[Any], Problem] = None,
     ):
         """Construct then calibrate a model problem.

pypesto/select/postprocessors.py

@@ -7,8 +7,7 @@
 from petab_select.constants import ESTIMATE, TYPE_PATH, Criterion
 
 from .. import store, visualize
-from ..C import TYPE_POSTPROCESSOR
-from .model_problem import ModelProblem
+from .model_problem import TYPE_POSTPROCESSOR, ModelProblem
 
 __all__ = [
     'model_id_binary_postprocessor',

pypesto/select/problem.py

@@ -4,8 +4,8 @@
 import petab_select
 from petab_select import Model
 
-from ..C import TYPE_POSTPROCESSOR
 from .method import MethodCaller
+from .model_problem import TYPE_POSTPROCESSOR, ModelProblem  # noqa: F401
 
 
 class Problem:

pypesto/visualize/ordinal_categories.py

@@ -1,5 +1,8 @@
 import warnings
-from typing import Dict, List, Optional
+from typing import TYPE_CHECKING, Dict, List, Optional
+
+if TYPE_CHECKING:
+    import pypesto
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -14,9 +17,7 @@
     from ..hierarchical.optimal_scaling.parameter import (
         OptimalScalingParameter,
     )
-    from ..hierarchical.optimal_scaling.problem import OptimalScalingProblem
     from ..hierarchical.optimal_scaling.solver import (
-        OptimalScalingInnerSolver,
         compute_interval_constraints,
         get_bounds_for_category,
         undo_inner_parameter_reparameterization,
@@ -155,8 +156,8 @@ def plot_categories_from_pypesto_result(
 
 
 def plot_categories_from_inner_result(
-    inner_problem: 'OptimalScalingProblem',
-    inner_solver: 'OptimalScalingInnerSolver',
+    inner_problem: 'pypesto.hierarchical.optimal_scaling.problem.OptimalScalingProblem',
+    inner_solver: 'pypesto.hierarchical.optimal_scaling.solver.OptimalScalingInnerSolver',
     results: List[Dict],
     simulation: List[np.ndarray],
     timepoints: List[np.ndarray],

pypesto/visualize/spline_approximation.py

@@ -5,6 +5,8 @@
 import matplotlib.pyplot as plt
 import numpy as np
 
+import pypesto
+
 from ..C import AMICI_SIGMAY, AMICI_Y, CURRENT_SIMULATION, DATAPOINTS, SCIPY_X
 from ..problem import Problem
 from ..result import Result
@@ -15,7 +17,6 @@
     from ..hierarchical.spline_approximation.calculator import (
         SplineAmiciCalculator,
     )
-    from ..hierarchical.spline_approximation.problem import SplineInnerProblem
     from ..hierarchical.spline_approximation.solver import (
         SplineInnerSolver,
         get_spline_mapped_simulations,
@@ -114,7 +115,7 @@ def plot_splines_from_pypesto_result(
 
 
 def plot_splines_from_inner_result(
-    inner_problem: 'SplineInnerProblem',
+    inner_problem: 'pypesto.hierarchical.spline_approximation.problem.SplineInnerProblem',
     results: List[Dict],
     observable_ids=None,
     **kwargs,

tox.ini

@@ -167,7 +167,7 @@ description =
 
 [testenv:doc]
 extras =
-    doc,amici,petab,aesara,jax
+    doc,amici,petab,aesara,jax,select
 commands =
     sphinx-build -W -b html doc/ doc/_build/html
 description =