Refactored examples

docs/source/notebooks/quickstart/quickstart.ipynb

@@ -54,7 +54,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from glotaran.examples.sequential import dataset\n",
+    "from glotaran.examples.sequential_spectral_decay import DATASET as dataset\n",
     "\n",
     "dataset"
    ]

glotaran/examples/__init__.py

@@ -1 +0,0 @@
-from glotaran.examples import sequential

glotaran/examples/parallel_spectral_decay.py

@@ -0,0 +1,67 @@
+import numpy as np
+
+from glotaran.analysis.simulation import simulate
+from glotaran.io import load_model
+from glotaran.io import load_parameters
+from glotaran.project import Scheme
+from glotaran.project.generators import generate_model_yml
+
+SIMULATION_MODEL_YML = generate_model_yml(
+    "spectral-decay-parallel", **{"nr_compartments": 3, "irf": True}
+)
+SIMULATION_MODEL = load_model(SIMULATION_MODEL_YML, format_name="yml_str")
+
+MODEL_YML = generate_model_yml("decay-parallel", **{"nr_compartments": 3, "irf": True})
+MODEL = load_model(MODEL_YML, format_name="yml_str")
+
+WANTED_PARAMETER_YML = """
+rates:
+  - [species_1, 0.5]
+  - [species_2, 0.3]
+  - [species_3, 0.1]
+
+irf:
+  - [center, 0.3]
+  - [width, 0.1]
+
+shapes:
+  species_1:
+    - [amplitude, 30]
+    - [location, 620]
+    - [width, 40]
+  species_2:
+    - [amplitude, 20]
+    - [location, 630]
+    - [width, 20]
+  species_3:
+    - [amplitude, 60]
+    - [location, 650]
+    - [width, 60]
+"""
+WANTED_PARAMETER = load_parameters(WANTED_PARAMETER_YML, format_name="yml_str")
+
+PARAMETER_YML = """
+rates:
+  - [species_1, 0.5]
+  - [species_2, 0.3]
+  - [species_3, 0.1]
+
+irf:
+  - [center, 0.3]
+  - [width, 0.1]
+"""
+PARAMETER = load_parameters(PARAMETER_YML, format_name="yml_str")
+
+TIME_AXIS = np.arange(-1, 20, 0.01)
+SPECTRAL_AXIS = np.arange(600, 700, 1.4)
+
+DATASET = simulate(
+    SIMULATION_MODEL,
+    "dataset_1",
+    WANTED_PARAMETER,
+    {"time": TIME_AXIS, "spectral": SPECTRAL_AXIS},
+    noise=True,
+    noise_std_dev=1e-2,
+)
+
+SCHEME = Scheme(model=MODEL, parameters=PARAMETER, data={"dataset1": DATASET})

glotaran/examples/sequential_spectral_decay.py

@@ -0,0 +1,67 @@
+import numpy as np
+
+from glotaran.analysis.simulation import simulate
+from glotaran.io import load_model
+from glotaran.io import load_parameters
+from glotaran.project import Scheme
+from glotaran.project.generators import generate_model_yml
+
+SIMULATION_MODEL_YML = generate_model_yml(
+    "spectral-decay-sequential", **{"nr_compartments": 3, "irf": True}
+)
+SIMULATION_MODEL = load_model(SIMULATION_MODEL_YML, format_name="yml_str")
+
+MODEL_YML = generate_model_yml("decay-sequential", **{"nr_compartments": 3, "irf": True})
+MODEL = load_model(MODEL_YML, format_name="yml_str")
+
+WANTED_PARAMETER_YML = """
+rates:
+  - [species_1, 0.5]
+  - [species_2, 0.3]
+  - [species_3, 0.1]
+
+irf:
+  - [center, 0.3]
+  - [width, 0.1]
+
+shapes:
+  species_1:
+    - [amplitude, 30]
+    - [location, 620]
+    - [width, 40]
+  species_2:
+    - [amplitude, 20]
+    - [location, 630]
+    - [width, 20]
+  species_3:
+    - [amplitude, 60]
+    - [location, 650]
+    - [width, 60]
+"""
+WANTED_PARAMETER = load_parameters(WANTED_PARAMETER_YML, format_name="yml_str")
+
+PARAMETER_YML = """
+rates:
+  - [species_1, 0.5]
+  - [species_2, 0.3]
+  - [species_3, 0.1]
+
+irf:
+  - [center, 0.3]
+  - [width, 0.1]
+"""
+PARAMETER = load_parameters(PARAMETER_YML, format_name="yml_str")
+
+TIME_AXIS = np.arange(-1, 20, 0.01)
+SPECTRAL_AXIS = np.arange(600, 700, 1.4)
+
+DATASET = simulate(
+    SIMULATION_MODEL,
+    "dataset_1",
+    WANTED_PARAMETER,
+    {"time": TIME_AXIS, "spectral": SPECTRAL_AXIS},
+    noise=True,
+    noise_std_dev=1e-2,
+)
+
+SCHEME = Scheme(model=MODEL, parameters=PARAMETER, data={"dataset1": DATASET})

glotaran/examples/test/test_example.py

@@ -1,7 +1,9 @@
 import xarray as xr
 
-from glotaran.examples.sequential import dataset
+from glotaran.examples.parallel_spectral_decay import DATASET as parallel_dataset
+from glotaran.examples.sequential_spectral_decay import DATASET as sequential_dataset
 
 
 def test_dataset():
-    assert isinstance(dataset, xr.Dataset)
+    assert isinstance(parallel_dataset, xr.Dataset)
+    assert isinstance(sequential_dataset, xr.Dataset)

glotaran/project/generators/__init__.py

@@ -1 +1,4 @@
 """The glotaran generator package."""
+
+from glotaran.project.generators.generator import generate_model
+from glotaran.project.generators.generator import generate_model_yml

glotaran/project/generators/generator.py

@@ -30,7 +30,7 @@ def _generate_decay_model(
         The generated model dictionary.
     """
     compartments = [f"species_{i+1}" for i in range(nr_compartments)]
-    rates = [f"decay.species_{i+1}" for i in range(nr_compartments)]
+    rates = [f"rates.species_{i+1}" for i in range(nr_compartments)]
     model = {
         "megacomplex": {
             f"megacomplex_{decay_type}_decay": {

glotaran/project/generators/test/test_genenerate_decay_model.py

@@ -25,7 +25,7 @@ def test_generate_parallel_model(megacomplex_type: str, irf: bool, spectral: boo
     assert megacomplex.type == f"decay-{megacomplex_type}"
     assert megacomplex.compartments == expected_compartments
     assert [r.full_label for r in megacomplex.rates] == [
-        f"decay.species_{i+1}" for i in range(nr_compartments)
+        f"rates.species_{i+1}" for i in range(nr_compartments)
     ]
 
     assert "dataset_1" in model.dataset  # type:ignore[attr-defined]