feature/fits interface

autogalaxy/__init__.py

@@ -107,6 +107,11 @@
 from .gui.scribbler import Scribbler
 
 from autoconf import conf
+from autoconf.fitsable import ndarray_via_hdu_from
+from autoconf.fitsable import ndarray_via_fits_from
+from autoconf.fitsable import header_obj_from
+from autoconf.fitsable import output_to_fits
+from autoconf.fitsable import hdu_list_for_output_from
 
 conf.instance.register(__file__)
 

autogalaxy/aggregator/agg_util.py

@@ -1,25 +1,68 @@
 from __future__ import annotations
 from typing import List, Optional
 
+from autoconf.fitsable import ndarray_via_hdu_from
+
 import autofit as af
 import autoarray as aa
 
+from autoarray.mask.mask_2d import Mask2DKeys
+
 from autogalaxy.analysis.adapt_images.adapt_images import AdaptImages
 
 
+def mask_header_from(fit):
+    """
+    Returns the mask, header and pixel scales of the `PyAutoFit` `Fit` object.
+
+    These quantities are commonly loaded during the aggregator interface therefore this method is used to
+    avoid code duplication.
+
+    Parameters
+    ----------
+    fit
+        A `PyAutoFit` `Fit` object which contains the results of a model-fit as an entry which has been loaded from
+        an output directory or from an sqlite database.
+
+
+    Returns
+    -------
+    The mask, header and pixel scales of the `PyAutoFit` `Fit` object.
+    """
+
+    header = aa.Header(header_sci_obj=fit.value(name="dataset")[0].header)
+    pixel_scales = (
+        header.header_sci_obj[Mask2DKeys.PIXSCAY.value],
+        header.header_sci_obj[Mask2DKeys.PIXSCAY.value],
+    )
+    origin = (
+        header.header_sci_obj[Mask2DKeys.ORIGINY.value],
+        header.header_sci_obj[Mask2DKeys.ORIGINX.value],
+    )
+    mask = aa.Mask2D(
+        mask=ndarray_via_hdu_from(fit.value(name="dataset")[0]),
+        pixel_scales=pixel_scales,
+        origin=origin,
+    )
+
+    return mask, header
+
+
 def adapt_images_from(
     fit: af.Fit,
 ) -> List[AdaptImages]:
     """
-    Updates adaptive images when loading the galaxies from a `PyAutoFit` sqlite database `Fit` object.
+    Updates adaptive images when loading the galaxies from a `PyAutoFit` loaded directory `Fit` or sqlite
+    database `Fit` object.
 
     This function ensures that if adaptive features (e.g. an `Hilbert` image-mesh) are used in a model-fit,
     they work when using the database to load and inspect the results of the model-fit.
 
     Parameters
     ----------
     fit
-        A `PyAutoFit` `Fit` object which contains the results of a model-fit as an entry in a sqlite database.
+        A `PyAutoFit` `Fit` object which contains the results of a model-fit as an entry which has been loaded from
+        an output directory or from an sqlite database.
     galaxies
         A list of galaxies corresponding to a sample of a non-linear search and model-fit.
 
@@ -30,31 +73,26 @@ def adapt_images_from(
 
     fit_list = [fit] if not fit.children else fit.children
 
-    if fit.value(name="adapt_images.adapt_images") is None:
+    if fit.value(name="adapt_images") is None:
         return [None] * len(fit_list)
 
     adapt_images_list = []
 
     for fit in fit_list:
-        try:
-            mask = aa.Mask2D.from_primary_hdu(
-                primary_hdu=fit.value(name="dataset.mask")[0]
-            )
-        except TypeError:
-            mask = aa.Mask2D.from_primary_hdu(
-                primary_hdu=fit.value(name="dataset.real_space_mask")[0]
-            )
+        mask, header = mask_header_from(fit=fit)
 
         galaxy_name_image_dict = {}
 
-        adapt_image_name_list = fit.value(name="adapt_images.adapt_images")
-
-        for name in adapt_image_name_list:
-            adapt_image = aa.Array2D.from_primary_hdu(
-                primary_hdu=fit.value(name=f"adapt_images.{name}")[0]
+        for i, value in enumerate(fit.value(name="adapt_images")[1:]):
+            adapt_image = aa.Array2D.no_mask(
+                values=ndarray_via_hdu_from(value),
+                pixel_scales=mask.pixel_scales,
+                header=header,
+                origin=mask.origin,
             )
             adapt_image = adapt_image.apply_mask(mask=mask)
-            galaxy_name_image_dict[name] = adapt_image
+
+            galaxy_name_image_dict[value.header["EXTNAME"].lower()] = adapt_image
 
         instance = fit.model.instance_from_prior_medians(ignore_prior_limits=True)
 
@@ -91,7 +129,8 @@ def mesh_grids_of_planes_list_from(
     Parameters
     ----------
     fit
-        A `PyAutoFit` `Fit` object which contains the results of a model-fit as an entry in a sqlite database.
+        A `PyAutoFit` `Fit` object which contains the results of a model-fit as an entry which has been loaded from
+        an output directory or from an sqlite database..
     total_fits
         The total number of `Analysis` objects summed to create the fit.
     use_preloaded_grid

autogalaxy/aggregator/dataset_model.py

@@ -12,9 +12,10 @@ def _dataset_model_from(
     fit: af.Fit, instance: af.ModelInstance
 ) -> List[aa.DatasetModel]:
     """
-    Returns a `DatasetModel` object from a `PyAutoFit` sqlite database `Fit` object.
+    Returns a `DatasetModel` object from a `PyAutoFit` loaded directory `Fit` or sqlite database `Fit` object.
 
-    The results of a model-fit can be stored in a sqlite database, including the following attributes of the fit:
+    The results of a model-fit can be loaded from hard-disk or stored in a sqlite database, including the following
+    attributes of the fit:
 
     - The model and its best fit parameters (e.g. `model.json`).
 
@@ -30,7 +31,8 @@ def _dataset_model_from(
     Parameters
     ----------
     fit
-        A `PyAutoFit` `Fit` object which contains the results of a model-fit as an entry in a sqlite database.
+        A `PyAutoFit` `Fit` object which contains the results of a model-fit as an entry which has been loaded from
+        an output directory or from an sqlite database..
     instance
         A manual instance that overwrites the max log likelihood instance in fit (e.g. for drawing the instance
         randomly from the PDF).

autogalaxy/aggregator/ellipse/ellipses.py

@@ -13,9 +13,10 @@
 
 def _ellipses_from(fit: af.Fit, instance: af.ModelInstance) -> List[List[Ellipse]]:
     """
-    Returns a list of `Ellipse` objects from a `PyAutoFit` sqlite database `Fit` object.
+    Returns a list of `Ellipse` objects from a `PyAutoFit` loaded directory `Fit` or sqlite database `Fit` object.
 
-    The results of a model-fit can be stored in a sqlite database, including the following attributes of the fit:
+    The results of a model-fit can be loaded from hard-disk or stored in a sqlite database, including the following
+    attributes of the fit:
 
     - The model and its best fit parameters (e.g. `model.json`).
 
@@ -31,7 +32,8 @@ def _ellipses_from(fit: af.Fit, instance: af.ModelInstance) -> List[List[Ellipse
     Parameters
     ----------
     fit
-        A `PyAutoFit` `Fit` object which contains the results of a model-fit as an entry in a sqlite database.
+        A `PyAutoFit` `Fit` object which contains the results of a model-fit as an entry which has been loaded from
+        an output directory or from an sqlite database..
     instance
         A manual instance that overwrites the max log likelihood instance in fit (e.g. for drawing the instance
         randomly from the PDF).
@@ -63,7 +65,8 @@ class EllipsesAgg(af.AggBase):
     Interfaces with an `PyAutoFit` aggregator object to create instances of `Ellipse` objects from the results
     of a model-fit.
 
-    The results of a model-fit can be stored in a sqlite database, including the following attributes of the fit:
+    The results of a model-fit can be loaded from hard-disk or stored in a sqlite database, including the following
+    attributes of the fit:
 
     - The model and its best fit parameters (e.g. `model.json`).
 
@@ -100,7 +103,8 @@ def object_via_gen_from(
         Parameters
         ----------
         fit
-            A `PyAutoFit` `Fit` object which contains the results of a model-fit as an entry in a sqlite database.
+            A `PyAutoFit` `Fit` object which contains the results of a model-fit as an entry which has been loaded from
+        an output directory or from an sqlite database..
         instance
             A manual instance that overwrites the max log likelihood instance in fit (e.g. for drawing the instance
             randomly from the PDF).

autogalaxy/aggregator/ellipse/fit_ellipse.py

@@ -16,12 +16,13 @@ def _fit_ellipse_from(
     instance: Optional[af.ModelInstance] = None,
 ) -> List[List[FitEllipse]]:
     """
-    Returns a list of `FitEllipse` objects from a `PyAutoFit` sqlite database `Fit` object.
+    Returns a list of `FitEllipse` objects from a `PyAutoFit` loaded directory `Fit` or sqlite database `Fit` object.
 
-    The results of a model-fit can be stored in a sqlite database, including the following attributes of the fit:
+    The results of a model-fit can be loaded from hard-disk or stored in a sqlite database, including the following
+    attributes of the fit:
 
     - The imaging data, noise-map, PSF and settings as .fits files (e.g. `dataset/data.fits`).
-    - The mask used to mask the `Imaging` data structure in the fit (`dataset/mask.fits`).
+    - The mask used to mask the `Imaging` data structure in the fit (`dataset.fits[hdu=0]`).
 
     Each individual attribute can be loaded from the database via the `fit.value()` method.
 
@@ -38,7 +39,8 @@ def _fit_ellipse_from(
     Parameters
     ----------
     fit
-        A `PyAutoFit` `Fit` object which contains the results of a model-fit as an entry in a sqlite database.
+        A `PyAutoFit` `Fit` object which contains the results of a model-fit as an entry which has been loaded from
+        an output directory or from an sqlite database..
     instance
         A manual instance that overwrites the max log likelihood instance in fit (e.g. for drawing the instance
         randomly from the PDF).
@@ -78,34 +80,35 @@ def __init__(
         aggregator: af.Aggregator,
     ):
         """
-        Interfaces with an `PyAutoFit` aggregator object to create instances of `FitEllipse` objects from the results
-        of a model-fit.
+            Interfaces with an `PyAutoFit` aggregator object to create instances of `FitEllipse` objects from the results
+            of a model-fit.
 
-        The results of a model-fit can be stored in a sqlite database, including the following attributes of the fit:
+            The results of a model-fit can be loaded from hard-disk or stored in a sqlite database, including the following
+        attributes of the fit:
 
-        - The imaging data, noise-map, PSF and settings as .fits files (e.g. `dataset/data.fits`).
-        - The mask used to mask the `Imaging` data structure in the fit (`dataset/mask.fits`).
+            - The imaging data, noise-map, PSF and settings as .fits files (e.g. `dataset/data.fits`).
+            - The mask used to mask the `Imaging` data structure in the fit (`dataset.fits[hdu=0]`).
 
-        The `aggregator` contains the path to each of these files, and they can be loaded individually. This class
-        can load them all at once and create an `FitEllipse` object via the `_fit_ellipse_from` method.
+            The `aggregator` contains the path to each of these files, and they can be loaded individually. This class
+            can load them all at once and create an `FitEllipse` object via the `_fit_ellipse_from` method.
 
-        This class's methods returns generators which create the instances of the `FitEllipse` objects. This ensures
-        that large sets of results can be efficiently loaded from the hard-disk and do not require storing all
-        `FitEllipse` instances in the memory at once.
+            This class's methods returns generators which create the instances of the `FitEllipse` objects. This ensures
+            that large sets of results can be efficiently loaded from the hard-disk and do not require storing all
+            `FitEllipse` instances in the memory at once.
 
-        For example, if the `aggregator` contains 3 model-fits, this class can be used to create a generator which
-        creates instances of the corresponding 3 `FitEllipse` objects.
+            For example, if the `aggregator` contains 3 model-fits, this class can be used to create a generator which
+            creates instances of the corresponding 3 `FitEllipse` objects.
 
-        If multiple `Ellipse` objects were fitted simultaneously via analysis summing, the `fit.child_values()` method
-        is instead used to load lists of the data, noise-map, PSF and mask and combine them into a list of
-        `FitEllipse` objects.
+            If multiple `Ellipse` objects were fitted simultaneously via analysis summing, the `fit.child_values()` method
+            is instead used to load lists of the data, noise-map, PSF and mask and combine them into a list of
+            `FitEllipse` objects.
 
-        This can be done manually, but this object provides a more concise API.
+            This can be done manually, but this object provides a more concise API.
 
-        Parameters
-        ----------
-        aggregator
-            A `PyAutoFit` aggregator object which can load the results of model-fits.
+            Parameters
+            ----------
+            aggregator
+                A `PyAutoFit` aggregator object which can load the results of model-fits.
         """
         super().__init__(aggregator=aggregator)
 
@@ -120,7 +123,8 @@ def object_via_gen_from(
         Parameters
         ----------
         fit
-            A `PyAutoFit` `Fit` object which contains the results of a model-fit as an entry in a sqlite database.
+            A `PyAutoFit` `Fit` object which contains the results of a model-fit as an entry which has been loaded from
+        an output directory or from an sqlite database..
         instance
             A manual instance that overwrites the max log likelihood instance in fit (e.g. for drawing the instance
             randomly from the PDF).

autogalaxy/aggregator/ellipse/multipoles.py

@@ -15,9 +15,10 @@ def _multipoles_from(
     fit: af.Fit, instance: af.ModelInstance
 ) -> List[List[List[EllipseMultipole]]]:
     """
-    Returns a list of `EllipseMultipole` objects from a `PyAutoFit` sqlite database `Fit` object.
+    Returns a list of `EllipseMultipole` objects from a `PyAutoFit` loaded directory `Fit` or sqlite database `Fit` object.
 
-    The results of a model-fit can be stored in a sqlite database, including the following attributes of the fit:
+    The results of a model-fit can be loaded from hard-disk or stored in a sqlite database, including the following
+    attributes of the fit:
 
     - The model and its best fit parameters (e.g. `model.json`).
 
@@ -33,7 +34,8 @@ def _multipoles_from(
     Parameters
     ----------
     fit
-        A `PyAutoFit` `Fit` object which contains the results of a model-fit as an entry in a sqlite database.
+        A `PyAutoFit` `Fit` object which contains the results of a model-fit as an entry which has been loaded from
+        an output directory or from an sqlite database..
     instance
         A manual instance that overwrites the max log likelihood instance in fit (e.g. for drawing the instance
         randomly from the PDF).
@@ -65,7 +67,8 @@ class MultipolesAgg(af.AggBase):
     Interfaces with an `PyAutoFit` aggregator object to create instances of `EllipseMultipole` objects from the results
     of a model-fit.
 
-    The results of a model-fit can be stored in a sqlite database, including the following attributes of the fit:
+    The results of a model-fit can be loaded from hard-disk or stored in a sqlite database, including the following
+    attributes of the fit:
 
     - The model and its best fit parameters (e.g. `model.json`).
 
@@ -102,7 +105,8 @@ def object_via_gen_from(
         Parameters
         ----------
         fit
-            A `PyAutoFit` `Fit` object which contains the results of a model-fit as an entry in a sqlite database.
+            A `PyAutoFit` `Fit` object which contains the results of a model-fit as an entry which has been loaded from
+        an output directory or from an sqlite database..
         instance
             A manual instance that overwrites the max log likelihood instance in fit (e.g. for drawing the instance
             randomly from the PDF).

autogalaxy/aggregator/galaxies.py

@@ -13,9 +13,10 @@
 
 def _galaxies_from(fit: af.Fit, instance: af.ModelInstance) -> List[Galaxy]:
     """
-    Returns a list of `Galaxy` objects from a `PyAutoFit` sqlite database `Fit` object.
+    Returns a list of `Galaxy` objects from a `PyAutoFit` loaded directory `Fit` or sqlite database `Fit` object.
 
-    The results of a model-fit can be stored in a sqlite database, including the following attributes of the fit:
+    The results of a model-fit can be loaded from hard-disk or stored in a sqlite database, including the following
+    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).
@@ -32,7 +33,8 @@ def _galaxies_from(fit: af.Fit, instance: af.ModelInstance) -> List[Galaxy]:
     Parameters
     ----------
     fit
-        A `PyAutoFit` `Fit` object which contains the results of a model-fit as an entry in a sqlite database.
+        A `PyAutoFit` `Fit` object which contains the results of a model-fit as an entry which has been loaded from
+        an output directory or from an sqlite database..
     instance
         A manual instance that overwrites the max log likelihood instance in fit (e.g. for drawing the instance
         randomly from the PDF).
@@ -73,7 +75,8 @@ class GalaxiesAgg(af.AggBase):
     Interfaces with an `PyAutoFit` aggregator object to create instances of `Galaxy` objects from the results
     of a model-fit.
 
-    The results of a model-fit can be stored in a sqlite database, including the following attributes of the fit:
+    The results of a model-fit can be loaded from hard-disk or stored in a sqlite database, including the following
+    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).
@@ -111,7 +114,8 @@ def object_via_gen_from(
         Parameters
         ----------
         fit
-            A `PyAutoFit` `Fit` object which contains the results of a model-fit as an entry in a sqlite database.
+            A `PyAutoFit` `Fit` object which contains the results of a model-fit as an entry which has been loaded from
+        an output directory or from an sqlite database..
         instance
             A manual instance that overwrites the max log likelihood instance in fit (e.g. for drawing the instance
             randomly from the PDF).