..

Author: dweindl

doc/examples/getting_started_extended/GettingStartedExtended.ipynb

@@ -152,46 +152,40 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Observables\n",
+    "### Observation model\n",
     "\n",
-    "Specifying observables is beyond the scope of SBML. Here we define them manually.\n",
+    "Specifying the observation model (i.e., the quantities that are observed, as well as the respective error models) is beyond the scope of SBML. Here we define that manually.\n",
+    "\n",
+    "If you are looking for a more scalable way of defining observables, then checkout [PEtab](https://github.com/PEtab-dev/PEtab). Another possibility is using SBML's [`AssignmentRule`s](https://sbml.org/software/libsbml/5.18.0/docs/formatted/python-api/classlibsbml_1_1_assignment_rule.html) to specify model outputs within the SBML file.\n",
     "\n",
-    "If you are looking for a more scalable way for defining observables, then checkout [PEtab](https://github.com/PEtab-dev/PEtab). Another possibility is using SBML's [`AssignmentRule`s](https://sbml.org/software/libsbml/5.18.0/docs/formatted/python-api/classlibsbml_1_1_assignment_rule.html) to specify model outputs within the SBML file."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Define observables\n",
-    "observables = {\n",
-    "    \"observable_x1\": {\"name\": \"\", \"formula\": \"x1\"},\n",
-    "    \"observable_x2\": {\"name\": \"\", \"formula\": \"x2\"},\n",
-    "    \"observable_x3\": {\"name\": \"\", \"formula\": \"x3\"},\n",
-    "    \"observable_x1_scaled\": {\"name\": \"\", \"formula\": \"scaling_x1 * x1\"},\n",
-    "    \"observable_x2_offsetted\": {\"name\": \"\", \"formula\": \"offset_x2 + x2\"},\n",
-    "    \"observable_x1withsigma\": {\"name\": \"\", \"formula\": \"x1\"},\n",
-    "}"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### $\\sigma$ parameters\n",
     "\n",
-    "To specify measurement noise as a parameter, we simply provide a dictionary with (preexisting) parameter names as keys and a list of observable names as values to indicate which sigma parameter is to be used for which observable."
+    "\n",
+    "For model import in AMICI, the different types of measurements are represented as `MeasurementChannels`.\n",
+    "The measurement channel is characterized by an ID, an optional name, the observation function (`MeasurementChannels.formula`), the type of noise distribution (`MeasurementChannels.noise_distribution`, defaults to a normal distribution), and the scale parameter of that distribution (`MeasurementChannels.sigma`).\n",
+    "The symbols used in the observation function and for the scale parameter must already be defined in the model."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
-    "sigmas = {\"observable_x1withsigma\": \"observable_x1withsigma_sigma\"}"
+    "# Define observation model\n",
+    "from amici import MeasurementChannel as MC\n",
+    "\n",
+    "observation_model = [\n",
+    "    MC(id_=\"observable_x1\", formula=\"x1\"),\n",
+    "    MC(id_=\"observable_x2\", formula=\"x2\"),\n",
+    "    MC(id_=\"observable_x3\", formula=\"x3\"),\n",
+    "    MC(id_=\"observable_x1_scaled\", formula=\"scaling_x1 * x1\"),\n",
+    "    MC(id_=\"observable_x2_offsetted\", formula=\"offset_x2 + x2\"),\n",
+    "    MC(\n",
+    "        id_=\"observable_x1withsigma\",\n",
+    "        formula=\"x1\",\n",
+    "        sigma=\"observable_x1withsigma_sigma\",\n",
+    "    ),\n",
+    "]"
    ]
   },
   {
@@ -340,9 +334,8 @@
     "    model_name,\n",
     "    model_output_dir,\n",
     "    verbose=logging.INFO,\n",
-    "    observables=observables,\n",
+    "    observation_model=observation_model,\n",
     "    constant_parameters=constant_parameters,\n",
-    "    sigmas=sigmas,\n",
     ")"
    ]
   },

python/benchmark/benchmark_pysb.py

@@ -75,7 +75,11 @@
                 pysb_model,
                 outdir,
                 compute_conservation_laws=compute_conservation_laws,
-                observables=list(pysb_model.observables.keys()),
+                observation_model=list(
+                    map(
+                        amici.MeasurementChannel, pysb_model.observables.keys()
+                    )
+                ),
             )
 
             amici_model_module = amici.import_model_module(

python/sdist/amici/petab/pysb_import.py

@@ -283,7 +283,7 @@ def import_model_pysb(
                 id_=observable.name,
                 sigma=f"{observable.name}_sigma",
                 noise_distribution=petab_noise_distribution_to_amici(
-                    observable.get_name(NOISE_DISTRIBUTION)
+                    observable.get(NOISE_DISTRIBUTION)
                 ),
             )
             for _, observable in petab_problem.observable_df.iterrows()

python/sdist/amici/pysb_import.py

@@ -55,9 +55,7 @@
 def pysb2jax(
     model: pysb.Model,
     output_dir: str | Path | None = None,
-    observables: list[str] = None,
-    sigmas: dict[str, str] = None,
-    noise_distributions: dict[str, str | Callable] | None = None,
+    observation_model: list[MeasurementChannel] = None,
     verbose: int | bool = False,
     compute_conservation_laws: bool = True,
     simplify: Callable = _default_simplify,
@@ -87,20 +85,16 @@ def pysb2jax(
     :param output_dir:
         see :meth:`amici.de_export.ODEExporter.set_paths`
 
-    :param observables:
-        list of :class:`pysb.core.Expression` or :class:`pysb.core.Observable`
-        names in the provided model that should be mapped to observables
-
-    :param sigmas:
-        dict of :class:`pysb.core.Expression` names that should be mapped to
-        sigmas
-
-    :param noise_distributions:
-        dict with names of observable Expressions as keys and a noise type
-        identifier, or a callable generating a custom noise formula string
-        (see :py:func:`amici.import_utils.noise_distribution_to_cost_function`
-        ). If nothing is passed for some observable id, a normal model is
-        assumed as default.
+    :param observation_model:
+        The different measurement channels that make up the observation
+        model, see also :class:`amici.import_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
+        ``None``. Event-observables are not supported.
 
     :param verbose: verbosity level for logging, True/False default to
         :attr:`logging.DEBUG`/:attr:`logging.ERROR`
@@ -126,20 +120,12 @@ def pysb2jax(
     :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 observables is None:
-        observables = []
-
-    if sigmas is None:
-        sigmas = {}
-
     model_name = model_name or model.name
 
     set_log_level(logger, verbose)
     ode_model = ode_model_from_pysb_importer(
         model,
-        observables=observables,
-        sigmas=sigmas,
-        noise_distributions=noise_distributions,
+        observation_model=observation_model,
         compute_conservation_laws=compute_conservation_laws,
         simplify=simplify,
         cache_simplify=cache_simplify,

python/tests/conftest.py

@@ -7,6 +7,8 @@
 import amici
 import pytest
 from pathlib import Path
+
+from amici import MeasurementChannel
 from amici.testing import TemporaryDirectoryWinSafe as TemporaryDirectory
 
 
@@ -78,7 +80,7 @@ def pysb_example_presimulation_module():
             model,
             outdir,
             verbose=True,
-            observables=["pPROT_obs"],
+            observation_model=[MeasurementChannel("pPROT_obs")],
             constant_parameters=constant_parameters,
         )
 

python/tests/test_events.py

@@ -5,7 +5,12 @@
 import amici
 import numpy as np
 import pytest
-from amici import import_model_module, SensitivityMethod, SensitivityOrder
+from amici import (
+    import_model_module,
+    SensitivityMethod,
+    SensitivityOrder,
+    MeasurementChannel as MC,
+)
 from amici.antimony_import import antimony2amici
 from amici.gradient_check import check_derivatives
 from amici.testing import skip_on_valgrind
@@ -1127,11 +1132,7 @@ def test_posteq_events_are_handled(tempdir):
         E1: at time > 1: target = target + bolus
         E2: at some_time >= 2: target = target + bolus
         """,
-        observables={
-            "obs_target": {
-                "formula": "target",
-            }
-        },
+        observation_model=[MC("obs_target", formula="target")],
         model_name=model_name,
         output_dir=tempdir,
         verbose=True,

python/tests/test_pysb.py

@@ -185,7 +185,12 @@ def test_compare_to_pysb_simulation(example):
                     outdir,
                     verbose=logging.INFO,
                     compute_conservation_laws=compute_conservation_laws,
-                    observables=list(pysb_model.observables.keys()),
+                    observation_model=list(
+                        map(
+                            amici.MeasurementChannel,
+                            pysb_model.observables.keys(),
+                        )
+                    ),
                 )
 
                 amici_model_module = amici.import_model_module(
@@ -338,7 +343,12 @@ def test_heavyside_and_special_symbols():
     )
 
     with TemporaryDirectoryWinSafe(prefix=model.name) as outdir:
-        pysb2amici(model, outdir, verbose=True, observables=["a"])
+        pysb2amici(
+            model,
+            outdir,
+            verbose=True,
+            observation_model=[amici.MeasurementChannel("a")],
+        )
 
         model_module = amici.import_model_module(
             module_name=model.name, module_path=outdir