Fix Sample.kwargs mixed string/tuple key bug

Sample.__init__ previously converted string kwargs to tuple paths only
when the key contained a dot. A model with both nested params (e.g.
'ellipses.11.centre.centre_0') and top-level dotless params (e.g.
'dummy_0') produced a mixed-type kwargs dict. Sample.is_path_kwargs then
inspected only the first key, misclassified the sample, and
parameter_lists_for_paths raised KeyError when looking up dotless keys
as single-element tuples.

The fix is to drop the "." in key guard so every string key is uniformly
converted to a tuple — single-name keys become single-element tuples
that match the path produced by model.all_paths. The dict() / database
JSON round-trip remains symmetric because dict() joins tuples back to
dotted strings on serialize.

Reported by Sam in the aggregator-to-database flow.

Author: Jammy2211

autofit/non_linear/samples/sample.py

@@ -35,7 +35,7 @@ def __init__(
         self.log_prior = log_prior
         self.weight = weight
         self.kwargs = {
-            tuple(key.split(".")) if isinstance(key, str) and "." in key else key: value
+            tuple(key.split(".")) if isinstance(key, str) else key: value
             for key, value in (kwargs or dict()).items()
         }
 

test_autofit/analysis/test_latent_variables.py

@@ -47,7 +47,7 @@ def test_set_database_paths(session, latent_samples):
         latent_samples=latent_samples,
     )
     loaded = database_paths.load_latent_samples()
-    assert loaded.max_log_likelihood_sample.kwargs == {"fwhm": 7.0644601350928475}
+    assert loaded.max_log_likelihood_sample.kwargs == {("fwhm",): 7.0644601350928475}
 
 
 @pytest.fixture(name="latent_samples")
@@ -73,7 +73,7 @@ def make_latent_samples():
 
 
 def test_compute_latent_samples(latent_samples):
-    assert latent_samples.sample_list[0].kwargs == {"fwhm": 7.0644601350928475}
+    assert latent_samples.sample_list[0].kwargs == {("fwhm",): 7.0644601350928475}
     assert latent_samples.model.instance_from_vector([1.0]).fwhm == 1.0
 
 
@@ -113,7 +113,7 @@ def test_compute_latent_samples_skips_fit_exception_samples():
         ),
     )
     assert len(latent_samples.sample_list) == 1
-    assert latent_samples.sample_list[0].kwargs == {"fwhm": 7.0644601350928475}
+    assert latent_samples.sample_list[0].kwargs == {("fwhm",): 7.0644601350928475}
 
 
 def test_info(latent_samples):

test_autofit/database/paths/test_samples.py

@@ -49,7 +49,7 @@ def test_serialise_sample(sample):
     sample = m.Object.from_object(
         sample
     )()
-    assert "centre" in sample.kwargs
+    assert ("centre",) in sample.kwargs
 
 
 def test_load_samples(

test_autofit/non_linear/samples/test_efficient.py

@@ -46,13 +46,13 @@ def test_values(efficient):
 
     sample_1, sample_2 = samples.sample_list
 
-    assert sample_1.kwargs["centre"] == 1.0
-    assert sample_1.kwargs["normalization"] == 2.0
-    assert sample_1.kwargs["sigma"] == 3.0
+    assert sample_1.kwargs[("centre",)] == 1.0
+    assert sample_1.kwargs[("normalization",)] == 2.0
+    assert sample_1.kwargs[("sigma",)] == 3.0
 
-    assert sample_2.kwargs["centre"] == 4.0
-    assert sample_2.kwargs["normalization"] == 5.0
-    assert sample_2.kwargs["sigma"] == 6.0
+    assert sample_2.kwargs[("centre",)] == 4.0
+    assert sample_2.kwargs[("normalization",)] == 5.0
+    assert sample_2.kwargs[("sigma",)] == 6.0
 
 
 def test_database(efficient, session):

test_autofit/non_linear/samples/test_samples.py

@@ -241,3 +241,26 @@ def test__addition_of_samples__raises_error_if_model_mismatch(samples_x5):
 
     with pytest.raises(af.exc.SamplesException):
         samples_x5 + samples_different_model
+
+
+def test__sample_kwargs__mixed_dotted_and_dotless_string_keys():
+    sample = af.Sample(
+        log_likelihood=1.0,
+        log_prior=0.0,
+        weight=1.0,
+        kwargs={
+            "mock_class_1.one": 10.0,
+            "dummy_0": 99.0,
+        },
+    )
+
+    assert all(isinstance(key, tuple) for key in sample.kwargs)
+    assert sample.is_path_kwargs is True
+    assert sample.kwargs[("dummy_0",)] == 99.0
+    assert sample.kwargs[("mock_class_1", "one")] == 10.0
+
+    paths = [
+        [("mock_class_1", "one")],
+        [("dummy_0",)],
+    ]
+    assert sample.parameter_lists_for_paths(paths) == [10.0, 99.0]