Refactor model.from_dict to parse megacomplex_type from dict and add simple_generator for testing

.pre-commit-config.yaml

@@ -77,7 +77,7 @@ repos:
     rev: 6.1.1
     hooks:
       - id: pydocstyle
-        files: "^glotaran/(plugin_system|utils|deprecation)"
+        files: "^glotaran/(plugin_system|utils|deprecation|testing)"
         exclude: "docs|tests?"
         # this is needed due to the following issue:
         # https://github.com/PyCQA/pydocstyle/issues/368
@@ -87,14 +87,14 @@ repos:
     rev: v1.8.0
     hooks:
       - id: darglint
-        files: "^glotaran/(plugin_system|utils|deprecation)"
+        files: "^glotaran/(plugin_system|utils|deprecation|testing)"
         exclude: "docs|tests?"
 
   - repo: https://github.com/pre-commit/mirrors-mypy
     rev: v0.910
     hooks:
       - id: mypy
-        files: "^glotaran/(plugin_system|utils|deprecation)"
+        files: "^glotaran/(plugin_system|utils|deprecation|testing)"
         exclude: "docs"
         additional_dependencies: [types-all]
 

glotaran/builtin/io/yml/yml.py

@@ -16,7 +16,6 @@
 from glotaran.io import save_dataset
 from glotaran.io import save_parameters
 from glotaran.model import Model
-from glotaran.model import get_megacomplex
 from glotaran.parameter import ParameterGroup
 from glotaran.project import SavingOptions
 from glotaran.project import Scheme
@@ -66,18 +65,7 @@ def load_model(self, file_name: str) -> Model:
         if "megacomplex" not in spec:
             raise ValueError("No megacomplex defined in model")
 
-        megacomplex_types = {
-            m["type"]: get_megacomplex(m["type"])
-            for m in spec["megacomplex"].values()
-            if "type" in m
-        }
-        if default_megacomplex is not None:
-            megacomplex_types[default_megacomplex] = get_megacomplex(default_megacomplex)
-            del spec["default-megacomplex"]
-
-        return Model.from_dict(
-            spec, megacomplex_types=megacomplex_types, default_megacomplex_type=default_megacomplex
-        )
+        return Model.from_dict(spec, megacomplex_types=None, default_megacomplex_type=None)
 
     def load_parameters(self, file_name: str) -> ParameterGroup:
 

glotaran/builtin/megacomplexes/decay/test/test_decay_megacomplex.py

@@ -6,11 +6,10 @@
 
 from glotaran.analysis.optimize import optimize
 from glotaran.analysis.simulation import simulate
-from glotaran.builtin.megacomplexes.decay import DecayMegacomplex
-from glotaran.model import Megacomplex
 from glotaran.model import Model
 from glotaran.parameter import ParameterGroup
 from glotaran.project import Scheme
+from glotaran.testing.simple_generator import SimpleGenerator
 
 
 def _create_gaussian_clp(labels, amplitudes, centers, widths, axis):
@@ -28,20 +27,9 @@ class DecayModel(Model):
     def from_dict(
         cls,
         model_dict,
-        *,
-        megacomplex_types: dict[str, type[Megacomplex]] | None = None,
-        default_megacomplex_type: str | None = None,
     ):
-        defaults: dict[str, type[Megacomplex]] = {
-            "decay": DecayMegacomplex,
-        }
-        if megacomplex_types is not None:
-            defaults.update(megacomplex_types)
-        return super().from_dict(
-            model_dict,
-            megacomplex_types=defaults,
-            default_megacomplex_type=default_megacomplex_type,
-        )
+        model_dict = {**model_dict, "default-megacomplex": "decay"}
+        return super().from_dict(model_dict)
 
 
 class OneComponentOneChannel:
@@ -136,62 +124,16 @@ class OneComponentOneChannelGaussianIrf:
 
 
 class ThreeComponentParallel:
-    model = DecayModel.from_dict(
-        {
-            "initial_concentration": {
-                "j1": {"compartments": ["s1", "s2", "s3"], "parameters": ["j.1", "j.1", "j.1"]},
-            },
-            "megacomplex": {
-                "mc1": {"k_matrix": ["k1"]},
-            },
-            "k_matrix": {
-                "k1": {
-                    "matrix": {
-                        ("s2", "s1"): "kinetic.1",
-                        ("s3", "s2"): "kinetic.2",
-                        ("s3", "s3"): "kinetic.3",
-                    }
-                }
-            },
-            "irf": {
-                "irf1": {
-                    "type": "multi-gaussian",
-                    "center": ["irf.center"],
-                    "width": ["irf.width"],
-                },
-            },
-            "dataset": {
-                "dataset1": {
-                    "initial_concentration": "j1",
-                    "irf": "irf1",
-                    "megacomplex": ["mc1"],
-                },
-            },
-        }
+    generator = SimpleGenerator(
+        rates=[300e-3, 500e-4, 700e-5],
+        irf={"center": 1.3, "width": 7.8},
+        k_matrix="parallel",
     )
+    model, initial_parameters = generator.model_and_parameters
+
+    generator.rates = [301e-3, 502e-4, 705e-5]
+    wanted_parameters = generator.parameters
 
-    initial_parameters = ParameterGroup.from_dict(
-        {
-            "kinetic": [
-                ["1", 300e-3],
-                ["2", 500e-4],
-                ["3", 700e-5],
-            ],
-            "irf": [["center", 1.3], ["width", 7.8]],
-            "j": [["1", 1, {"vary": False, "non-negative": False}]],
-        }
-    )
-    wanted_parameters = ParameterGroup.from_dict(
-        {
-            "kinetic": [
-                ["1", 301e-3],
-                ["2", 502e-4],
-                ["3", 705e-5],
-            ],
-            "irf": [["center", 1.3], ["width", 7.8]],
-            "j": [["1", 1, {"vary": False, "non-negative": False}]],
-        }
-    )
     time = np.arange(-10, 100, 1.5)
     pixel = np.arange(600, 750, 10)
 

glotaran/model/model.py

@@ -2,6 +2,7 @@
 from __future__ import annotations
 
 import copy
+from typing import Any
 from typing import List
 from warnings import warn
 
@@ -17,6 +18,7 @@
 from glotaran.model.weight import Weight
 from glotaran.parameter import Parameter
 from glotaran.parameter import ParameterGroup
+from glotaran.plugin_system.megacomplex_registration import get_megacomplex
 from glotaran.utils.ipython import MarkdownStr
 
 default_model_items = {
@@ -56,18 +58,34 @@ def __init__(
     @classmethod
     def from_dict(
         cls,
-        model_dict: dict,
+        model_dict: dict[str, Any],
         *,
-        megacomplex_types: dict[str, type[Megacomplex]],
+        megacomplex_types: dict[str, type[Megacomplex]] | None = None,
         default_megacomplex_type: str | None = None,
     ) -> Model:
         """Creates a model from a dictionary.
 
         Parameters
         ----------
-        model_dict :
+        model_dict: dict[str, Any]
             Dictionary containing the model.
+        megacomplex_types: dict[str, type[Megacomplex]] | None
+            Overwrite 'megacomplex_types' in ``model_dict`` for testing.
+        default_megacomplex_type: str | None
+            Overwrite 'default-megacomplex' in ``model_dict`` for testing.
         """
+        if default_megacomplex_type is None:
+            default_megacomplex_type = model_dict.get("default-megacomplex")
+
+        if megacomplex_types is None:
+            megacomplex_types = {
+                m["type"]: get_megacomplex(m["type"])
+                for m in model_dict["megacomplex"].values()
+                if "type" in m
+            }
+        if default_megacomplex_type is not None:
+            megacomplex_types[default_megacomplex_type] = get_megacomplex(default_megacomplex_type)
+            del model_dict["default-megacomplex"]
 
         model = cls(
             megacomplex_types=megacomplex_types, default_megacomplex_type=default_megacomplex_type

glotaran/testing/__init__.py

@@ -0,0 +1 @@
+"""Testing framework package for glotaran itself and plugins."""