added fits_are_Zoomed to config

Author: Jammy2211

autoarray/config/visualize/plots.yaml

@@ -3,6 +3,9 @@
 # For example, if `plots: fit: subplot_fit=True``, the ``fit_dataset.png`` subplot file will 
 # be plotted every time visualization is performed.
 
+subplot_format: [png]                      # Output format of all subplots, can be png, pdf or both (e.g. [png, pdf])
+fits_are_zoomed: true                      # If true, output .fits files are zoomed in on the center of the unmasked region image, saving hard-disk space.
+
 dataset:                                   # Settings for plots of all datasets (e.g. ImagingPlotter, InterferometerPlotter).
   subplot_dataset: true                    # Plot subplot containing all dataset quantities (e.g. the data, noise-map, etc.)?
 imaging:                                   # Settings for plots of imaging datasets (e.g. ImagingPlotter)

autoarray/structures/arrays/uniform_2d.py

@@ -293,6 +293,25 @@ def native(self) -> "Array2D":
             values=self, mask=self.mask, header=self.header, store_native=True
         )
 
+    @property
+    def native_for_fits(self) -> "Array2D":
+        """
+        Return a `Array2D` for output to a .fits file, where the data is stored in its `native` representation,
+        which is an ``ndarray`` of shape [total_y_pixels, total_x_pixels].
+
+        Depending on configuration files, this array could be zoomed in on such that only the unmasked region
+        of the image is included in the .fits file, to save hard-disk space. Alternatively, the original `shape_native`
+        of the data can be retained.
+
+        If it is already stored in its `native` representation it is return as it is. If not, it is mapped from
+        `slim` to `native` and returned as a new `Array2D`.
+        """
+
+
+        return Array2D(
+            values=self, mask=self.mask, header=self.header, store_native=True
+        )
+
     @property
     def native_skip_mask(self) -> "Array2D":
         """