feature/graphical_analysis_output

autolens/aggregator/tracer.py

@@ -2,9 +2,14 @@
 from typing import List, Optional
 
 import autofit as af
+import autoarray as aa
+import autogalaxy as ag
 
 from autolens.lens.tracer import Tracer
 
+from autogalaxy.aggregator import agg_util
+from autolens.lens import tracer_util
+
 logger = logging.getLogger(__name__)
 
 
@@ -18,16 +23,15 @@ def _tracer_from(
     attributes of the fit:
 
     - The model and its best fit parameters (e.g. `model.json`).
-    - The adapt images associated with adaptive galaxy features (`adapt` folder).
 
     Each individual attribute can be loaded from the database via the `fit.value()` method.
 
-    This method combines all of these attributes and returns a `Tracer` object for a given non-linear search sample
-    (e.g. the maximum likelihood model). This includes associating adapt images with their respective galaxies.
+    This method combines this attributesand returns a `Tracer` object for a given non-linear search sample
+    (e.g. the maximum likelihood model).
 
-    If multiple `Tracer` objects were fitted simultaneously via analysis summing, the `fit.child_values()` method
-    is instead used to load lists of Tracers. This is necessary if each Tracer has different galaxies (e.g. certain
-    parameters vary across each dataset and `Analysis` object).
+    If multiple `Tracer` objects were fitted simultaneously via multiple analysis, the instance is iterated over as
+    a list such that a list of `Tracer` objects with parameters updated for each analysis are returned. This means
+    fits using a single analysis are wrapped in a list to prodcue a consistent API.
 
     Parameters
     ----------
@@ -39,41 +43,46 @@ def _tracer_from(
         randomly from the PDF).
     """
 
-    if instance is not None:
+    instance_list = agg_util.instance_list_from(fit=fit, instance=instance)
+
+    tracer_list = []
+
+    for instance in instance_list:
+
         galaxies = instance.galaxies
 
         if hasattr(instance, "extra_galaxies"):
-            if fit.instance.extra_galaxies is not None:
-                galaxies = galaxies + fit.instance.extra_galaxies
-
-    else:
-        galaxies = fit.instance.galaxies
-
-        if hasattr(fit.instance, "extra_galaxies"):
-            if fit.instance.extra_galaxies is not None:
-                galaxies = galaxies + fit.instance.extra_galaxies
-
-    try:
-        cosmology = instance.cosmology
-    except AttributeError:
-        cosmology = fit.value(name="cosmology")
-
-    tracer = Tracer(galaxies=galaxies, cosmology=cosmology)
-
-    if fit.children is not None:
-        if len(fit.children) > 0:
-            logger.info(
-                """
-                Using database for a fit with multiple summed Analysis objects.
-
-                Tracer objects do not fully support this yet (e.g. model parameters which vary over analyses may be incorrect)
-                so proceed with caution!
-                """
+            if instance.extra_galaxies is not None:
+                galaxies = galaxies + instance.extra_galaxies
+
+        try:
+            cosmology = instance.cosmology
+        except AttributeError:
+            cosmology = fit.value(name="cosmology")
+
+        if cosmology is None:
+            cosmology = ag.cosmo.Planck15()
+
+        # TODO : These are ugly as hell (>_<)
+
+        if hasattr(instance, "perturb"):
+            galaxies.subhalo = instance.perturb
+
+        if hasattr(instance.galaxies, "subhalo"):
+            subhalo_centre = tracer_util.grid_2d_at_redshift_from(
+                galaxies=instance.galaxies,
+                redshift=instance.galaxies.subhalo.redshift,
+                grid=aa.Grid2DIrregular(values=[instance.galaxies.subhalo.mass.centre]),
+                cosmology=cosmology,
             )
 
-            return [tracer] * len(fit.children)
+            galaxies.subhalo.mass.centre = tuple(subhalo_centre.in_list[0])
+
+        tracer = Tracer(galaxies=galaxies, cosmology=cosmology)
+
+        tracer_list.append(tracer)
 
-    return [tracer]
+    return tracer_list
 
 
 class TracerAgg(af.AggBase):

test_autolens/aggregator/test_aggregator_fit_imaging.py

@@ -35,36 +35,38 @@ def test__fit_imaging_randomly_drawn_via_pdf_gen_from(
     clean(database_file=database_file)
 
 
-def test__fit_imaging_randomly_drawn_via_pdf_gen_from__analysis_multi(
-    analysis_imaging_7x7, samples, model
-):
-    agg = aggregator_from(
-        database_file=database_file,
-        analysis=analysis_imaging_7x7 + analysis_imaging_7x7,
-        model=model,
-        samples=samples,
-    )
-
-    fit_agg = al.agg.FitImagingAgg(aggregator=agg)
-    fit_pdf_gen = fit_agg.randomly_drawn_via_pdf_gen_from(total_samples=2)
-
-    i = 0
-
-    for fit_gen in fit_pdf_gen:
-        for fit_list in fit_gen:
-            i += 1
-
-            assert fit_list[0].tracer.galaxies[0].redshift == 0.5
-            assert fit_list[0].tracer.galaxies[0].light.centre == (10.0, 10.0)
-            assert fit_list[0].tracer.galaxies[1].redshift == 1.0
-
-            assert fit_list[1].tracer.galaxies[0].redshift == 0.5
-            assert fit_list[1].tracer.galaxies[0].light.centre == (10.0, 10.0)
-            assert fit_list[1].tracer.galaxies[1].redshift == 1.0
-
-    assert i == 2
-
-    clean(database_file=database_file)
+# TODO : These need to use FactorGraphModel
+
+# def test__fit_imaging_randomly_drawn_via_pdf_gen_from__analysis_multi(
+#     analysis_imaging_7x7, samples, model
+# ):
+#     agg = aggregator_from(
+#         database_file=database_file,
+#         analysis=analysis_imaging_7x7 + analysis_imaging_7x7,
+#         model=model,
+#         samples=samples,
+#     )
+#
+#     fit_agg = al.agg.FitImagingAgg(aggregator=agg)
+#     fit_pdf_gen = fit_agg.randomly_drawn_via_pdf_gen_from(total_samples=2)
+#
+#     i = 0
+#
+#     for fit_gen in fit_pdf_gen:
+#         for fit_list in fit_gen:
+#             i += 1
+#
+#             assert fit_list[0].tracer.galaxies[0].redshift == 0.5
+#             assert fit_list[0].tracer.galaxies[0].light.centre == (10.0, 10.0)
+#             assert fit_list[0].tracer.galaxies[1].redshift == 1.0
+#
+#             assert fit_list[1].tracer.galaxies[0].redshift == 0.5
+#             assert fit_list[1].tracer.galaxies[0].light.centre == (10.0, 10.0)
+#             assert fit_list[1].tracer.galaxies[1].redshift == 1.0
+#
+#     assert i == 2
+#
+#     clean(database_file=database_file)
 
 
 def test__fit_imaging_all_above_weight_gen(analysis_imaging_7x7, samples, model):

test_autolens/aggregator/test_aggregator_fit_interferometer.py

@@ -35,6 +35,8 @@ def test__fit_interferometer_randomly_drawn_via_pdf_gen_from(
     clean(database_file=database_file)
 
 
+# TODO : These need to use FactorGraphModel
+
 # def test__fit_interferometer_randomly_drawn_via_pdf_gen_from__analysis_multi(analysis_interferometer_7, samples, model):
 #
 #     agg = aggregator_from(