remoe output_to_Fits from mask to abstract mask

Author: Jammy2211

autoarray/mask/abstract_mask.py

@@ -6,9 +6,10 @@
 from pathlib import Path
 from typing import Dict, Union
 
+from autoconf.fitsable import output_to_fits
+
 from autoarray.abstract_ndarray import AbstractNDArray
 
-from autoarray import exc
 from autoarray import type as ty
 
 logging.basicConfig()
@@ -92,10 +93,38 @@ def pixel_scale_header(self) -> Dict:
     def dimensions(self) -> int:
         return len(self.shape)
 
-    def output_to_fits(self, file_path: Union[Path, str], overwrite: bool = False):
-        """
-        Overwrite with method to output the mask to a `.fits` file.
+    def output_to_fits(self, file_path, overwrite=False):
         """
+        Write the Mask to a .fits file.
+
+        Before outputting a 2D NumPy array mask, the array may be flipped upside-down using np.flipud depending on
+        the project config files. This is for Astronomy projects so that structures appear the same orientation
+        as `.fits` files loaded in DS9.
+
+        Parameters
+        ----------
+        file_path
+            The full path of the file that is output, including the file name and `.fits` extension.
+        overwrite
+            If `True` and a file already exists with the input file_path the .fits file is overwritten. If `False`, an
+            error is raised.
+
+        Returns
+        -------
+        None
+
+        Examples
+        --------
+        mask = Mask2D(mask=np.full(shape=(5,5), fill_value=False))
+        mask.output_to_fits(file_path='/path/to/file/filename.fits', overwrite=True)
+        """
+        output_to_fits(
+            values=self.astype("float"),
+            file_path=file_path,
+            overwrite=overwrite,
+            header_dict=self.pixel_scale_header,
+            ext_name="mask"
+        )
 
     @property
     def pixels_in_mask(self) -> int:

autoarray/mask/mask_1d.py

@@ -1,13 +1,10 @@
 from __future__ import annotations
 
-from astropy.io import fits
 import logging
 import numpy as np
 from pathlib import Path
 from typing import Dict, List, Tuple, Union
 
-from autoconf.fitsable import output_to_fits
-
 from autoarray.mask.abstract_mask import Mask
 
 from autoarray.mask.derive.grid_1d import DeriveGrid1D
@@ -177,50 +174,4 @@ def pixel_scale_header(self) -> Dict:
         """
         return {
             "PIXSCA": self.pixel_scales[0],
-        }
-
-    @property
-    def hdu_for_output(self) -> fits.PrimaryHDU:
-        """
-        The mask as a HDU object, which can be output to a .fits file.
-
-        The header of the HDU is used to store the `pixel_scale` of the array, which is used by the `Array1D.from_hdu`.
-
-        This method is used in other projects (E.g. PyAutoGalaxy, PyAutoLens) to conveniently output the array to .fits
-        files.
-
-        Returns
-        -------
-        The HDU containing the data and its header which can then be written to .fits.
-        """
-        return array_1d_util.hdu_for_output_from(
-            array_1d=self.astype("float"), header_dict=self.pixel_scale_header
-        )
-
-    def output_to_fits(self, file_path: Union[Path, str], overwrite: bool = False):
-        """
-        Write the 1D mask to a .fits file.
-
-        Parameters
-        ----------
-        file_path
-            The full path of the file that is output, including the file name and .fits extension.
-        overwrite
-            If `True` and a file already exists with the input file_path the .fits file is overwritten. If `False`,
-            an error is raised.
-
-        Returns
-        -------
-        None
-
-        Examples
-        --------
-        mask = Mask1D(mask=np.full(shape=(5,), fill_value=False))
-        mask.output_to_fits(file_path='/path/to/file/filename.fits', overwrite=True)
-        """
-        output_to_fits(
-            values=self.astype("float"),
-            file_path=file_path,
-            overwrite=overwrite,
-            header_dict=self.pixel_scale_header,
-        )
+        }

autoarray/mask/mask_2d.py

@@ -1,5 +1,4 @@
 from __future__ import annotations
-from astropy.io import fits
 import logging
 import numpy as np
 from pathlib import Path
@@ -11,7 +10,7 @@
     from autoarray.structures.arrays.uniform_2d import Array2D
 
 from autoconf import cached_property
-from autoconf.fitsable import ndarray_via_fits_from, output_to_fits
+from autoconf.fitsable import ndarray_via_fits_from
 
 from autoarray.mask.abstract_mask import Mask
 
@@ -722,57 +721,6 @@ def pixel_scale_header(self) -> Dict:
             "PIXSCAX": self.pixel_scales[1],
         }
 
-    @property
-    def hdu_for_output(self) -> fits.PrimaryHDU:
-        """
-        The mask as a HDU object, which can be output to a .fits file.
-
-        The header of the HDU is used to store the `pixel_scale` of the array, which is used by the `Array2D.from_hdu`.
-
-        This method is used in other projects (E.g. PyAutoGalaxy, PyAutoLens) to conveniently output the array to .fits
-        files.
-
-        Returns
-        -------
-        The HDU containing the data and its header which can then be written to .fits.
-        """
-        return array_2d_util.hdu_for_output_from(
-            array_2d=self.astype("float"), header_dict=self.pixel_scale_header
-        )
-
-    def output_to_fits(self, file_path, overwrite=False):
-        """
-        Write the 2D Mask to a .fits file.
-
-        Before outputting a NumPy array, the array may be flipped upside-down using np.flipud depending on the project
-        config files. This is for Astronomy projects so that structures appear the same orientation as `.fits` files
-        loaded in DS9.
-
-        Parameters
-        ----------
-        file_path
-            The full path of the file that is output, including the file name and `.fits` extension.
-        overwrite
-            If `True` and a file already exists with the input file_path the .fits file is overwritten. If `False`, an
-            error is raised.
-
-        Returns
-        -------
-        None
-
-        Examples
-        --------
-        mask = Mask2D(mask=np.full(shape=(5,5), fill_value=False))
-        mask.output_to_fits(file_path='/path/to/file/filename.fits', overwrite=True)
-        """
-        output_to_fits(
-            values=self.astype("float"),
-            file_path=file_path,
-            overwrite=overwrite,
-            header_dict=self.pixel_scale_header,
-            ext_name="mask"
-        )
-
     @property
     def mask_centre(self) -> Tuple[float, float]:
         grid = grid_2d_util.grid_2d_slim_via_mask_from(

autoarray/structures/arrays/uniform_1d.py

@@ -268,21 +268,3 @@ def grid_radial(self) -> Grid1D:
             shape_native=self.shape_native,
             pixel_scales=self.pixel_scales,
         )
-
-    @property
-    def hdu_for_output(self) -> fits.PrimaryHDU:
-        """
-        The array as an HDU object, which can be output to a .fits file.
-
-        The header of the HDU is used to store the `pixel_scale` of the array, which is used by the `Array1D.from_hdu`.
-
-        This method is used in other projects (E.g. PyAutoGalaxy, PyAutoLens) to conveniently output the array to .fits
-        files.
-
-        Returns
-        -------
-        The HDU containing the data and its header which can then be written to .fits.
-        """
-        return array_2d_util.hdu_for_output_from(
-            array_2d=self.native, header_dict=self.pixel_scale_header
-        )

autoarray/structures/arrays/uniform_2d.py

@@ -610,28 +610,6 @@ def trimmed_after_convolution_from(
             store_native=self.store_native,
         )
 
-    def hdu_for_output_from(
-        self, ext_name: Optional[str] = None, return_as_primary: bool = False
-    ) -> Union[fits.PrimaryHDU, fits.ImageHDU]:
-        """
-        The array as an HDU object, which can be output to a .fits file.
-
-        The header of the HDU is used to store the `pixel_scale` of the array, which is used by the `Array2D.from_hdu`.
-
-        This method is used in other projects (E.g. PyAutoGalaxy, PyAutoLens) to conveniently output the array to .fits
-        files.
-
-        Returns
-        -------
-        The HDU containing the data and its header which can then be written to .fits.
-        """
-        return array_2d_util.hdu_for_output_from(
-            array_2d=np.array(self.native),
-            header_dict=self.pixel_scale_header,
-            ext_name=ext_name,
-            return_as_primary=return_as_primary,
-        )
-
 
 class Array2D(AbstractArray2D):
     @classmethod

autoarray/structures/visibilities.py

@@ -1,7 +1,5 @@
 from abc import ABC
 
-from astropy.io import fits
-
 import logging
 import numpy as np
 from pathlib import Path
@@ -13,8 +11,6 @@
 from autoarray.structures.abstract_structure import Structure
 from autoarray.structures.grids.irregular_2d import Grid2DIrregular
 
-from autoarray.structures.arrays import array_2d_util
-
 logging.basicConfig()
 logger = logging.getLogger(__name__)
 
@@ -103,22 +99,6 @@ def amplitudes(self) -> np.ndarray:
     def phases(self) -> np.ndarray:
         return np.arctan2(self.imag, self.real)
 
-    @property
-    def hdu_for_output(self) -> fits.PrimaryHDU:
-        """
-        The visibilities as an HDU object, which can be output to a .fits file.
-
-        This method is used in other projects (E.g. PyAutoGalaxy, PyAutoLens) to conveniently output the array to .fits
-        files.
-
-        Returns
-        -------
-        The HDU containing the data which can then be written to .fits.
-        """
-        return array_2d_util.hdu_for_output_from(
-            array_2d=self.in_array,
-        )
-
     def output_to_fits(self, file_path: Union[Path, str], overwrite: bool = False):
         """
         Output the visibilities to a .fits file.