Create standard/schema for Problem

doc/examples/model_selection/model_space.tsv

@@ -1,4 +1,4 @@
-model_subspace_id	petab_yaml	k1	k2	k3
+model_subspace_id	model_subspace_petab_yaml	k1	k2	k3
 M1_0	petab_problem.yaml	0	0	0
 M1_1	petab_problem.yaml	0.2	0.1	estimate
 M1_2	petab_problem.yaml	0.2	estimate	0

doc/examples/model_selection/petab_select_problem.yaml

@@ -1,5 +1,6 @@
-version: beta_1
+format_version: 1.0.0
 criterion: AIC
 method: forward
 model_space_files:
 - model_space.tsv
+candidate_space_arguments: {}

doc/problem_definition.rst

@@ -7,8 +7,8 @@ Model selection problems for PEtab Select are defined by the following files:
 #. a specification of the model space, and
 #. (optionally) a specification of the initial candidate model.
 
-The different file formats are described below. Each file format is a YAML file
-and comes with a YAML-formatted JSON schema, such that these files can be
+The different file formats are described below. The YAML file formats
+come with a YAML-formatted JSON schema, such that these files can be
 easily worked with independently of the PEtab Select library.
 
 1. Selection problem
@@ -34,14 +34,23 @@ A YAML file with a description of the model selection problem.
 - ``candidate_space_arguments``: Additional arguments used to generate
   candidate models during model selection. For example, an initial candidate
   model can be specified with the following code, where
-  ``predecessor_model.yaml`` is a valid model file. Additional arguments are
-  provided in the documentation of the ``CandidateSpace`` class.
+  ``predecessor_model.yaml`` is a valid :ref:`model file <section-model-yaml>`. Additional arguments are
+  provided in the documentation of the ``CandidateSpace`` class, and an example is provided in
+  `test case 0009 <https://github.com/PEtab-dev/petab_select/blob/main/test_cases/0009/petab_select_problem.yaml>`_.
 
 .. code-block:: yaml
 
    candidate_space_arguments:
      predecessor_model: predecessor_model.yaml
 
+Schema
+^^^^^^
+
+The schema is provided as `YAML-formatted JSON schema <_static/problem.yaml>`_, which enables easy validation with various third-party tools.
+
+.. literalinclude:: standard/problem.yaml
+   :language: yaml
+
 2. Model space
 --------------
 
@@ -54,7 +63,7 @@ all parameters.
    :header-rows: 1
 
    * - ``model_subspace_id``
-     - ``petab_yaml``
+     - ``model_subspace_petab_yaml``
      - ``parameter_id_1``
      - ...
      - ``parameter_id_n``
@@ -65,7 +74,7 @@ all parameters.
      - ...
 
 - ``model_subspace_id``: An ID for the model subspace.
-- ``petab_yaml``: The PEtab YAML filename that serves as the basis of all
+- ``model_subspace_petab_yaml``: The YAML filename of the PEtab problem that serves as the basis of all
   models in this subspace.
 - ``parameter_id_1`` ... ``parameter_id_n``: Specify the values that a
   parameter can take in the model subspace. For example, this could be:
@@ -81,6 +90,9 @@ all parameters.
     - ``0.0;1.1;estimate`` (the parameter can take the values ``0.0`` or
       ``1.1``, or be estimated)
 
+Example of concise specification
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
 Using the ``;``-delimited list format, a model subspace that has two parameters
 (``p1, p2``) and six models:
 
@@ -105,6 +117,8 @@ can be specified like
      - 0;estimate
      - 10;20;estimate
 
+.. _section-model-yaml:
+
 3. Model(s) (Predecessor models / model interchange / report)
 -------------------------------------------------------------
 

doc/standard/make_schemas.py

@@ -1,5 +1,7 @@
 from petab_select.model import ModelStandard
 from petab_select.models import ModelsStandard
+from petab_select.problem import ProblemStandard
 
 ModelStandard.save_schema("model.yaml")
 ModelsStandard.save_schema("models.yaml")
+ProblemStandard.save_schema("problem.yaml")

doc/standard/problem.yaml

@@ -0,0 +1,35 @@
+description: "Handle everything related to the model selection problem.\n\nAttributes:\n\
+  \    model_space:\n        The model space.\n    calibrated_models:\n        Calibrated\
+  \ models. Will be used to augment the model selection\n        problem (e.g. by\
+  \ excluding them from the model space).\n    candidate_space_arguments:\n      \
+  \  Arguments are forwarded to the candidate space constructor.\n    compare:\n \
+  \       A method that compares models by selection criterion. See\n        :func:`petab_select.model.default_compare`\
+  \ for an example.\n    criterion:\n        The criterion used to compare models.\n\
+  \    method:\n        The method used to search the model space.\n    version:\n\
+  \        The version of the PEtab Select format.\n    yaml_path:\n        The location\
+  \ of the selection problem YAML file. Used for relative\n        paths that exist\
+  \ in e.g. the model space files."
+properties:
+  format_version:
+    default: 1.0.0
+    title: Format Version
+    type: string
+  criterion:
+    type: string
+  method:
+    type: string
+  model_space_files:
+    items:
+      format: path
+      type: string
+    title: Model Space Files
+    type: array
+  candidate_space_arguments:
+    title: Candidate Space Arguments
+    type: object
+required:
+- criterion
+- method
+- model_space_files
+title: Problem
+type: object

petab_select/cli.py

@@ -12,7 +12,14 @@
 
 from . import ui
 from .candidate_space import CandidateSpace
-from .constants import CANDIDATE_SPACE, MODELS, PETAB_YAML, PROBLEM, TERMINATE
+from .constants import (
+    CANDIDATE_SPACE,
+    MODELS,
+    PETAB_YAML,
+    PROBLEM,
+    TERMINATE,
+    UNCALIBRATED_MODELS,
+)
 from .model import ModelHash
 from .models import Models, models_to_yaml_list
 from .problem import Problem
@@ -183,7 +190,7 @@ def start_iteration(
         ModelHash.from_hash(hash_str) for hash_str in excluded_model_hashes
     ]
 
-    ui.start_iteration(
+    result = ui.start_iteration(
         problem=problem,
         candidate_space=candidate_space,
         limit=limit,
@@ -201,9 +208,8 @@ def start_iteration(
     )
 
     # Save candidate models
-    models_to_yaml_list(
-        models=candidate_space.models,
-        output_yaml=uncalibrated_models_yaml,
+    result[UNCALIBRATED_MODELS].to_yaml(
+        filename=uncalibrated_models_yaml,
         relative_paths=relative_paths,
     )
 
@@ -495,7 +501,7 @@ def get_best(
         models=models,
         criterion=criterion,
     )
-    best_model.to_yaml(output, paths_relative_to=paths_relative_to)
+    best_model.to_yaml(output)
 
 
 cli.add_command(start_iteration)

petab_select/constants.py

@@ -73,7 +73,6 @@ class Criterion(str, Enum):
 # Problem
 MODEL_SPACE_FILES = "model_space_files"
 PROBLEM = "problem"
-PROBLEM_ID = "problem_id"
 VERSION = "version"
 
 # Candidate space
@@ -174,10 +173,6 @@ class Method(str, Enum):
 # PEtab Select model report format.
 HASH = "hash"
 
-# MODEL_SPACE_FILE_NON_PARAMETER_COLUMNS = [MODEL_ID, PETAB_YAML]
-MODEL_SPACE_FILE_NON_PARAMETER_COLUMNS = [MODEL_SUBSPACE_ID, PETAB_YAML]
-
-# COMPARED_MODEL_ID = 'compared_'+MODEL_ID
 YAML_FILENAME = "yaml"
 
 # DISTANCES = {

petab_select/model.py

@@ -5,12 +5,23 @@
 import copy
 import warnings
 from os.path import relpath
-from pathlib import Path
 from typing import TYPE_CHECKING, Any, ClassVar, Literal
 
 import mkstd
 import petab.v1 as petab
+from mkstd import Path
 from petab.v1.C import NOMINAL_VALUE
+from pydantic import (
+    BaseModel,
+    Field,
+    PrivateAttr,
+    ValidationInfo,
+    ValidatorFunctionWrapHandler,
+    field_serializer,
+    field_validator,
+    model_serializer,
+    model_validator,
+)
 
 from .constants import (
     ESTIMATE,
@@ -41,29 +52,14 @@
 if TYPE_CHECKING:
     from .problem import Problem
 
-
-from pydantic import (
-    BaseModel,
-    PrivateAttr,
-    ValidationInfo,
-    ValidatorFunctionWrapHandler,
-)
-
 __all__ = [
     "Model",
     "default_compare",
     "ModelHash",
     "VIRTUAL_INITIAL_MODEL",
+    "ModelStandard",
 ]
 
-from pydantic import (
-    Field,
-    field_serializer,
-    field_validator,
-    model_serializer,
-    model_validator,
-)
-
 
 class ModelHash(BaseModel):
     """The model hash.
@@ -331,9 +327,7 @@ def _fix_relative_paths(
             return data
         model = handler(data)
 
-        root_path = None
-        if ROOT_PATH in data:
-            root_path = data.pop(ROOT_PATH)
+        root_path = data.pop(ROOT_PATH, None)
         if root_path is None:
             return model
 
@@ -685,17 +679,11 @@ def get_parameter_values(
         ]
 
     @staticmethod
-    def from_yaml(
-        filename: str | Path,
-    ) -> Model:
-        """Load a model from a YAML file.
-
-        Args:
-            filename:
-                Location of the YAML file.
-        """
+    def from_yaml(filename: str | Path) -> Model:
+        """Load a model from a YAML file."""
         model = ModelStandard.load_data(
-            filename=filename, root_path=Path(filename).parent
+            filename=filename,
+            root_path=Path(filename).parent,
         )
         return model