Check that fitted parameters have reasonable range (#206)

Author: StephenNneji

ratapi/examples/normal_reflectivity/DSPC_standard_layers.ipynb

@@ -85,7 +85,7 @@
     "    Parameter(name=\"SAM Heads Hydration\", min=10.0, value=45.45, max=50.0, fit=True, prior_type=\"gaussian\", mu=30.0, sigma=3.0),\n",
     "    #\n",
     "    Parameter(name=\"CW Thickness\", min=10.0, value=17.12, max=28.0, fit=True, prior_type=\"uniform\"),\n",
-    "    Parameter(name=\"CW SLD\", min=0.0, value=0.0, max=1e-09, fit=False, prior_type=\"uniform\"),\n",
+    "    Parameter(name=\"CW SLD\", min=0.0, value=0.0, max=0.0, fit=False, prior_type=\"uniform\"),\n",
     "    Parameter(name=\"CW Hydration\", min=99.9, value=100.0, max=100.0, fit=False, prior_type=\"uniform\"),\n",
     "    #\n",
     "    Parameter(name=\"Bilayer Heads Thickness\", min=7.0, value=10.7, max=17.0, fit=True, prior_type=\"gaussian\", mu=10.0, sigma=2.0),\n",
@@ -175,8 +175,8 @@
    "outputs": [],
    "source": [
     "del problem.scalefactors[0]\n",
-    "problem.scalefactors.append(name=\"Scalefactor 1\", min=0.05, value=0.10, max=0.2, fit=False)\n",
-    "problem.scalefactors.append(name=\"Scalefactor 2\", min=0.05, value=0.15, max=0.2, fit=False)\n",
+    "problem.scalefactors.append(name=\"Scalefactor 1\", min=0.05, value=0.10, max=0.2, fit=True)\n",
+    "problem.scalefactors.append(name=\"Scalefactor 2\", min=0.05, value=0.15, max=0.2, fit=True)\n",
     "\n",
     "# Now deal with the backgrounds\n",
     "del problem.backgrounds[0]\n",

ratapi/examples/normal_reflectivity/DSPC_standard_layers.py

@@ -22,7 +22,7 @@ def DSPC_standard_layers():
     problem.parameters.append(name="SAM Tails Hydration", min=1.0, value=5.252, max=50.0, fit=True)
     problem.parameters.append(name="SAM Roughness", min=1.0, value=5.64, max=15.0, fit=True)
     problem.parameters.append(name="CW Thickness", min=10.0, value=17.12, max=28.0, fit=True)
-    problem.parameters.append(name="CW SLD", min=0.0, value=0.0, max=1e-09, fit=False)
+    problem.parameters.append(name="CW SLD", min=0.0, value=0.0, max=0.0, fit=False)
 
     problem.parameters.append(
         name="SAM Heads Thickness",
@@ -131,8 +131,8 @@ def DSPC_standard_layers():
 
     # Set the scalefactors - use one for each contrast
     del problem.scalefactors[0]
-    problem.scalefactors.append(name="Scalefactor 1", min=0.05, value=0.10, max=0.2, fit=False)
-    problem.scalefactors.append(name="Scalefactor 2", min=0.05, value=0.15, max=0.2, fit=False)
+    problem.scalefactors.append(name="Scalefactor 1", min=0.05, value=0.10, max=0.2, fit=True)
+    problem.scalefactors.append(name="Scalefactor 2", min=0.05, value=0.15, max=0.2, fit=True)
 
     # Now deal with the backgrounds
     del problem.backgrounds[0]

ratapi/inputs.py

@@ -3,14 +3,15 @@
 import importlib
 import os
 import pathlib
+import warnings
 from collections.abc import Callable
 
 import numpy as np
 
 import ratapi
 import ratapi.wrappers
 from ratapi.rat_core import Checks, Control, NameStore, ProblemDefinition
-from ratapi.utils.enums import Calculations, Languages, LayerModels, TypeOptions
+from ratapi.utils.enums import Calculations, Languages, LayerModels, Procedures, TypeOptions
 
 parameter_field = {
     "parameters": "params",
@@ -137,19 +138,21 @@ def make_input(project: ratapi.Project, controls: ratapi.Controls) -> tuple[Prob
         The controls object used in the compiled RAT code.
 
     """
-    problem = make_problem(project)
+    problem = make_problem(project, controls.procedure != Procedures.Calculate)
     cpp_controls = make_controls(controls)
 
     return problem, cpp_controls
 
 
-def make_problem(project: ratapi.Project) -> ProblemDefinition:
+def make_problem(project: ratapi.Project, validate_range: bool = False) -> ProblemDefinition:
     """Construct the problem input required for the compiled RAT code.
 
     Parameters
     ----------
     project : RAT.Project
         The project model, which defines the physical system under study.
+    validate_range : bool, default True
+        Whether parameter range should be validated.
 
     Returns
     -------
@@ -351,40 +354,43 @@ def make_problem(project: ratapi.Project) -> ProblemDefinition:
     problem.domainContrastLayers = [
         domain_contrast_model if domain_contrast_model else [] for domain_contrast_model in domain_contrast_models
     ]
-    problem.fitParams = [
-        param.value
-        for class_list in ratapi.project.parameter_class_lists
-        for param in getattr(project, class_list)
-        if param.fit
-    ]
-    problem.fitLimits = [
-        [param.min, param.max]
-        for class_list in ratapi.project.parameter_class_lists
-        for param in getattr(project, class_list)
-        if param.fit
-    ]
-    problem.priorNames = [
-        param.name for class_list in ratapi.project.parameter_class_lists for param in getattr(project, class_list)
-    ]
-    problem.priorValues = [
-        [prior_id[param.prior_type], param.mu, param.sigma]
-        for class_list in ratapi.project.parameter_class_lists
-        for param in getattr(project, class_list)
-    ]
+
+    fit_params = []
+    fit_limits = []
+    prior_names = []
+    prior_values = []
+    problem.checks = Checks()
+    for class_list in ratapi.project.parameter_class_lists:
+        field = parameter_field[class_list]
+        check_list = []
+        for param in getattr(project, class_list):
+            prior_names.append(param.name)
+            prior_values.append([prior_id[param.prior_type], param.mu, param.sigma])
+            check_list.append(int(param.fit))
+            if param.fit:
+                min_range = 1e-6 if param.value == 0 else abs(param.value) * 1e-6
+                if validate_range and (param.max - param.min) < min_range:
+                    warnings.warn(
+                        f'{class_list.replace("_", " ").title()} "{param.name}" was removed from the '
+                        f"fit because its range is too small (< {min_range:g}).",
+                        stacklevel=2,
+                    )
+                    check_list[-1] = 0
+                else:
+                    fit_params.append(param.value)
+                    fit_limits.append([param.min, param.max])
+        setattr(problem.checks, field, check_list)
+    problem.fitParams = fit_params
+    problem.fitLimits = fit_limits
+    problem.priorNames = prior_names
+    problem.priorValues = prior_values
 
     # Names
     problem.names = NameStore()
     for class_list in ratapi.project.parameter_class_lists:
         setattr(problem.names, parameter_field[class_list], [param.name for param in getattr(project, class_list)])
     problem.names.contrasts = [contrast.name for contrast in project.contrasts]
 
-    # Checks
-    problem.checks = Checks()
-    for class_list in ratapi.project.parameter_class_lists:
-        setattr(
-            problem.checks, parameter_field[class_list], [int(element.fit) for element in getattr(project, class_list)]
-        )
-
     check_indices(problem)
 
     return problem

ratapi/run.py

@@ -130,7 +130,9 @@ def run(project, controls):
     # Update parameter values in project
     for class_list in ratapi.project.parameter_class_lists:
         for index, value in enumerate(getattr(problem_definition, parameter_field[class_list])):
-            getattr(project, class_list)[index].value = value
+            param = getattr(project, class_list)[index]
+            param.fit = bool(getattr(problem_definition.checks, parameter_field[class_list])[index])
+            param.value = value
 
     controls.delete_IPC()
 

tests/test_data/R1DSPCBilayer.mat

@@ -483,6 +483,23 @@ def test_make_problem(test_project, test_problem, request) -> None:
     check_problem_equal(problem, test_problem)
 
 
+@pytest.mark.parametrize("value,min_range", [(0, 1e-6), (10, 1e-5)])
+def test_make_problem_validate_range(value, min_range, request) -> None:
+    """The problem should not contain fitted parameters with small range."""
+    test_project = request.getfixturevalue("standard_layers_project")
+
+    test_project.scalefactors.set_fields(0, min=value, value=value, max=value, fit=True)
+    problem = make_problem(test_project)
+    assert problem.checks.scalefactors[0] == 1
+
+    with pytest.warns(
+        UserWarning,
+        match="was removed from the fit because its range is too small {0}(< {1:g}{0})".format("\\", min_range),
+    ):
+        problem = make_problem(test_project, True)
+    assert problem.checks.scalefactors[0] == 0
+
+
 @pytest.mark.parametrize("test_problem", ["standard_layers_problem", "custom_xy_problem", "domains_problem"])
 class TestCheckIndices:
     """Tests for check_indices over a set of three test problems."""