feature/fits interface

autoarray/__init__.py

@@ -89,6 +89,11 @@
 from .structures.visibilities import VisibilitiesNoiseMap
 
 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__)
 

autoarray/abstract_ndarray.py

@@ -6,14 +6,15 @@
 from abc import abstractmethod
 import numpy as np
 
+from autoconf.fitsable import output_to_fits
+
 from autoarray.numpy_wrapper import numpy as npw, register_pytree_node, Array
 
 from typing import TYPE_CHECKING
 
 if TYPE_CHECKING:
     from autoarray.structures.abstract_structure import Structure
 
-from autoarray.structures.arrays import array_2d_util
 from autoconf import conf
 
 
@@ -280,8 +281,11 @@ def output_to_fits(self, file_path: str, overwrite: bool = False):
         overwrite
             If a file already exists at the path, if overwrite=True it is overwritten else an error is raised.
         """
-        array_2d_util.numpy_array_2d_to_fits(
-            array_2d=self.native.array, file_path=file_path, overwrite=overwrite
+        output_to_fits(
+            values=self.native.array,
+            file_path=file_path,
+            overwrite=overwrite,
+            header_dict=self.mask.header_dict,
         )
 
     @property

autoarray/dataset/imaging/dataset.py

@@ -108,7 +108,7 @@ def __init__(
                         kernel_shape=psf.shape_native, mask_pad_value=1
                     )
                 )
-                print(over_sample_size_lp.shape_native)
+
                 over_sample_size_pixelization = (
                     over_sample_util.over_sample_size_convert_to_array_2d_from(
                         over_sample_size=over_sample_size_pixelization, mask=data.mask

autoarray/dataset/interferometer/dataset.py

@@ -2,9 +2,9 @@
 import logging
 import numpy as np
 from pathlib import Path
-from typing import Optional
 
 from autoconf import cached_property
+from autoconf.fitsable import ndarray_via_fits_from, output_to_fits
 
 from autoarray.dataset.abstract.dataset import AbstractDataset
 from autoarray.dataset.interferometer.w_tilde import WTildeInterferometer
@@ -14,8 +14,6 @@
 from autoarray.structures.visibilities import Visibilities
 from autoarray.structures.visibilities import VisibilitiesNoiseMap
 
-from autoarray.structures.arrays import array_2d_util
-
 from autoarray.inversion.inversion.interferometer import inversion_interferometer_util
 
 logger = logging.getLogger(__name__)
@@ -91,7 +89,11 @@ def __init__(
             uv_wavelengths=uv_wavelengths, real_space_mask=real_space_mask
         )
 
-        self.preprocessing_directory = Path(preprocessing_directory) if preprocessing_directory is not None else None
+        self.preprocessing_directory = (
+            Path(preprocessing_directory)
+            if preprocessing_directory is not None
+            else None
+        )
 
     @cached_property
     def grids(self):
@@ -127,7 +129,7 @@ def from_fits(
             file_path=noise_map_path, hdu=noise_map_hdu
         )
 
-        uv_wavelengths = array_2d_util.numpy_array_2d_via_fits_from(
+        uv_wavelengths = ndarray_via_fits_from(
             file_path=uv_wavelengths_path, hdu=uv_wavelengths_hdu
         )
 
@@ -140,15 +142,11 @@ def from_fits(
         )
 
     def w_tilde_preprocessing(self):
-
         if self.preprocessing_directory.is_dir():
-
             filename = "{}/curvature_preload.fits".format(self.preprocessing_directory)
 
             if not self.preprocessing_directory.isfile(filename):
-                print(
-                    "The file {} does not exist".format(filename)
-                )
+                print("The file {} does not exist".format(filename))
                 logger.info("INTERFEROMETER - Computing W-Tilde... May take a moment.")
 
                 curvature_preload = inversion_interferometer_util.w_tilde_curvature_preload_interferometer_from(
@@ -271,8 +269,8 @@ def output_to_fits(
             self.noise_map.output_to_fits(file_path=noise_map_path, overwrite=overwrite)
 
         if self.uv_wavelengths is not None and uv_wavelengths_path is not None:
-            array_2d_util.numpy_array_2d_to_fits(
-                array_2d=self.uv_wavelengths,
+            output_to_fits(
+                values=self.uv_wavelengths,
                 file_path=uv_wavelengths_path,
                 overwrite=overwrite,
             )