feat: test prior config + docs for the AdaptPower regularization siblings

docs/api/pixelization.rst

@@ -66,6 +66,8 @@ Regularization [ag.reg]
    ConstantSplit
    Adapt
    AdaptSplit
+   AdaptPower
+   AdaptSplitPower
 
 Settings
 --------

test_autolens/config/priors/regularization.yaml

@@ -37,3 +37,143 @@ constant_zeorth.ConstantZeroth:
     width_modifier:
       type: Relative
       value: 0.5
+adapt_power.AdaptPower:
+  inner_coefficient:
+    limits:
+      lower: 0.0
+      upper: inf
+    lower_limit: 1.0e-06
+    type: LogUniform
+    upper_limit: 1000000.0
+    width_modifier:
+      type: Relative
+      value: 0.5
+  outer_coefficient:
+    limits:
+      lower: 0.0
+      upper: inf
+    lower_limit: 1.0e-06
+    type: LogUniform
+    upper_limit: 1000000.0
+    width_modifier:
+      type: Relative
+      value: 0.5
+  signal_scale:
+    lower_limit: 0.0
+    type: Uniform
+    upper_limit: 1.0
+  power:
+    type: Constant
+    value: 1.0
+adapt_split_power.AdaptSplitPower:
+  inner_coefficient:
+    limits:
+      lower: 0.0
+      upper: inf
+    lower_limit: 1.0e-06
+    type: LogUniform
+    upper_limit: 1000000.0
+    width_modifier:
+      type: Relative
+      value: 0.5
+  outer_coefficient:
+    limits:
+      lower: 0.0
+      upper: inf
+    lower_limit: 1.0e-06
+    type: LogUniform
+    upper_limit: 1000000.0
+    width_modifier:
+      type: Relative
+      value: 0.5
+  signal_scale:
+    lower_limit: 0.0
+    type: Uniform
+    upper_limit: 1.0
+  power:
+    type: Constant
+    value: 1.0
+adapt_split_zeroth_power.AdaptSplitZerothPower:
+  inner_coefficient:
+    limits:
+      lower: 0.0
+      upper: inf
+    lower_limit: 1.0e-06
+    type: LogUniform
+    upper_limit: 1000000.0
+    width_modifier:
+      type: Relative
+      value: 0.5
+  outer_coefficient:
+    limits:
+      lower: 0.0
+      upper: inf
+    lower_limit: 1.0e-06
+    type: LogUniform
+    upper_limit: 1000000.0
+    width_modifier:
+      type: Relative
+      value: 0.5
+  signal_scale:
+    lower_limit: 0.0
+    type: Uniform
+    upper_limit: 1.0
+  zeroth_coefficient:
+    limits:
+      lower: 0.0
+      upper: inf
+    lower_limit: 1.0e-06
+    type: LogUniform
+    upper_limit: 1000000.0
+    width_modifier:
+      type: Relative
+      value: 0.5
+  zeroth_signal_scale:
+    lower_limit: 0.0
+    type: Uniform
+    upper_limit: 1.0
+  power:
+    type: Constant
+    value: 1.0
+matern_adapt_power_kernel.MaternAdaptPowerKernel:
+  inner_coefficient:
+    limits:
+      lower: 0.0
+      upper: inf
+    lower_limit: 1.0e-06
+    type: LogUniform
+    upper_limit: 1000000.0
+    width_modifier:
+      type: Relative
+      value: 0.5
+  outer_coefficient:
+    limits:
+      lower: 0.0
+      upper: inf
+    lower_limit: 1.0e-06
+    type: LogUniform
+    upper_limit: 1000000.0
+    width_modifier:
+      type: Relative
+      value: 0.5
+  signal_scale:
+    lower_limit: 0.0
+    type: Uniform
+    upper_limit: 1.0
+  scale:
+    limits:
+      lower: 0.0
+      upper: inf
+    lower_limit: 1.0e-06
+    type: LogUniform
+    upper_limit: 1000000.0
+    width_modifier:
+      type: Relative
+      value: 0.2
+  nu:
+    lower_limit: 0.5
+    type: Uniform
+    upper_limit: 5.5
+  power:
+    type: Constant
+    value: 1.0

test_autolens/test_regularization_power.py

@@ -0,0 +1,32 @@
+"""
+Model-composition gate for the ``*Power`` regularization siblings added in PyAutoArray, through the
+``al.reg`` namespace.
+
+Mirrors ``test_autogalaxy/test_regularization_power.py``; the prior entries this exercises live in
+``test_autolens/config/priors/regularization.yaml``.
+"""
+
+import autofit as af
+import autolens as al
+
+
+def test__power_classes_are_re_exported():
+    assert al.reg.AdaptPower is not al.reg.Adapt
+    assert al.reg.AdaptSplitPower is not al.reg.AdaptSplit
+    assert al.reg.AdaptSplitZerothPower is not al.reg.AdaptSplitZeroth
+    assert al.reg.MaternAdaptPowerKernel is not al.reg.MaternAdaptKernel
+
+
+def test__model_composition__power_is_a_constant_and_is_not_sampled():
+    model = af.Model(al.reg.AdaptSplitPower)
+
+    assert set(prior_tuple[0] for prior_tuple in model.prior_tuples) == {
+        "inner_coefficient",
+        "outer_coefficient",
+        "signal_scale",
+    }
+    assert model.instance_from_prior_medians().power == 1.0
+
+
+def test__model_identifier__differs_from_the_legacy_class():
+    assert af.Model(al.reg.AdaptSplit).identifier != af.Model(al.reg.AdaptSplitPower).identifier