release v0.3.0

Author: Jammy2211

autoarray/conf.py

@@ -3,6 +3,13 @@
 from copy import deepcopy
 
 
+def get_matplotlib_backend():
+    try:
+        return instance.visualize.get("figures", "backend", str)
+    except Exception:
+        return "TKAgg"
+
+
 def family(current_class):
     yield current_class
     for next_class in current_class.__bases__:

autoarray/dataset/imaging.py

@@ -732,7 +732,9 @@ def simulate(
             )
         else:
             noise_map = arrays.Array.full(
-                fill_value=noise_if_add_noise_false, shape_2d=image.shape_2d, pixel_scales=image.pixel_scales
+                fill_value=noise_if_add_noise_false,
+                shape_2d=image.shape_2d,
+                pixel_scales=image.pixel_scales,
             )
             noise_realization = None
 

autoarray/decorator_util.py

@@ -13,9 +13,14 @@
 @numba.jit(nopython=True, cache=False, parallel=True)
 """
 
-nopython = conf.instance.general.get("numba", "nopython", bool)
-cache = conf.instance.general.get("numba", "cache", bool)
-parallel = conf.instance.general.get("numba", "parallel", bool)
+try:
+    nopython = conf.instance.general.get("numba", "nopython", bool)
+    cache = conf.instance.general.get("numba", "cache", bool)
+    parallel = conf.instance.general.get("numba", "parallel", bool)
+except Exception:
+    nopython = True
+    cache = True
+    parallel = False
 
 
 def jit(nopython=nopython, cache=cache, parallel=parallel):

autoarray/exc.py

@@ -35,4 +35,4 @@ class InversionException(Exception):
 
 
 class PlottingException(Exception):
-    pass
+    pass

autoarray/fit/fit.py

@@ -3,8 +3,12 @@
 from autoarray.masked import masked_dataset as md
 from autoarray.util import fit_util
 
+
 def fit_masked_dataset(masked_dataset, model_data, inversion=None):
-    return fit(masked_dataset=masked_dataset, model_data=model_data, inversion=inversion)
+    return fit(
+        masked_dataset=masked_dataset, model_data=model_data, inversion=inversion
+    )
+
 
 def fit(masked_dataset, model_data, inversion=None):
     if isinstance(masked_dataset, md.MaskedImaging):

autoarray/mask/mask.py

@@ -373,7 +373,15 @@ def elliptical_annular(
         )
 
     @classmethod
-    def from_fits(cls, file_path, pixel_scales, hdu=0, sub_size=1, origin=(0.0, 0.0), resized_mask_shape=None):
+    def from_fits(
+        cls,
+        file_path,
+        pixel_scales,
+        hdu=0,
+        sub_size=1,
+        origin=(0.0, 0.0),
+        resized_mask_shape=None,
+    ):
         """
         Loads the image from a .fits file.
 
@@ -400,7 +408,9 @@ def from_fits(cls, file_path, pixel_scales, hdu=0, sub_size=1, origin=(0.0, 0.0)
 
         if resized_mask_shape is not None:
 
-            mask = mask.mapping.resized_mask_from_new_shape(new_shape=resized_mask_shape)
+            mask = mask.mapping.resized_mask_from_new_shape(
+                new_shape=resized_mask_shape
+            )
 
         return mask
 

autoarray/plotters/array_plotters.py

@@ -2,7 +2,8 @@
 from autoarray import exc
 import matplotlib
 
-backend = conf.instance.visualize.get("figures", "backend", str)
+backend = conf.get_matplotlib_backend()
+
 matplotlib.use(backend)
 import matplotlib.pyplot as plt
 import matplotlib.colors as colors
@@ -203,30 +204,13 @@ def plot_array(
         cb_tick_values=cb_tick_values,
         cb_tick_labels=cb_tick_labels,
     )
-    plot_origin(
-        array=array,
-        include_origin=include_origin,
-    )
-    plot_mask(
-        mask=mask, pointsize=mask_pointsize
-    )
+    plot_origin(array=array, include_origin=include_origin)
+    plot_mask(mask=mask, pointsize=mask_pointsize)
     plotter_util.plot_lines(line_lists=lines)
-    plot_border(
-        mask=mask,
-        include_border=include_border,
-        pointsize=border_pointsize,
-    )
-    plot_points(
-        points=points,
-        pointsize=point_pointsize,
-    )
-    plot_grid(
-        grid=grid,
-        pointsize=grid_pointsize,
-    )
-    plot_centres(
-        centres=centres,
-    )
+    plot_border(mask=mask, include_border=include_border, pointsize=border_pointsize)
+    plot_points(points=points, pointsize=point_pointsize)
+    plot_grid(grid=grid, pointsize=grid_pointsize)
+    plot_centres(centres=centres)
     plotter_util.output_figure(
         array,
         as_subplot=as_subplot,
@@ -306,8 +290,14 @@ def plot_figure(
     )
 
     plt.imshow(array.in_2d, aspect=aspect, cmap=cmap, norm=norm_scale, extent=extent)
-    plotter_util.set_yxticks(array=array, extent=extent, use_scaled_units=use_scaled_units,
-                unit_conversion_factor=unit_conversion_factor, xticks_manual=xticks_manual, yticks_manual=yticks_manual)
+    plotter_util.set_yxticks(
+        array=array,
+        extent=extent,
+        use_scaled_units=use_scaled_units,
+        unit_conversion_factor=unit_conversion_factor,
+        xticks_manual=xticks_manual,
+        yticks_manual=yticks_manual,
+    )
 
     return fig
 
@@ -416,9 +406,8 @@ def plot_centres(centres):
             color = next(colors)
             for centre in centres_of_galaxy:
 
-                plt.scatter(
-                    y=centre[0], x=centre[1], s=300, c=color, marker="x"
-                )
+                plt.scatter(y=centre[0], x=centre[1], s=300, c=color, marker="x")
+
 
 def plot_mask(mask, pointsize):
     """Plot the mask of the array on the figure.
@@ -503,9 +492,7 @@ def plot_points(points, pointsize):
 
     if points is not None:
 
-        points = list(
-            map(lambda position_set: np.asarray(position_set), points)
-        )
+        points = list(map(lambda position_set: np.asarray(position_set), points))
         point_colors = itertools.cycle(["m", "y", "r", "w", "c", "b", "g", "k"])
         for point_set in points:
 
@@ -536,8 +523,5 @@ def plot_grid(grid, pointsize):
     if grid is not None:
 
         plt.scatter(
-            y=np.asarray(grid[:, 0]),
-            x=np.asarray(grid[:, 1]),
-            s=pointsize,
-            c="k",
+            y=np.asarray(grid[:, 0]), x=np.asarray(grid[:, 1]), s=pointsize, c="k"
         )

autoarray/plotters/fit_imaging_plotters.py

@@ -1,7 +1,7 @@
 import matplotlib
 from autoarray import conf
 
-backend = conf.instance.visualize.get("figures", "backend", str)
+backend = conf.get_matplotlib_backend()
 matplotlib.use(backend)
 from matplotlib import pyplot as plt
 
@@ -432,6 +432,7 @@ def individuals(
                 output_format=output_format,
             )
 
+
 def image(
     fit,
     mask=None,
@@ -520,8 +521,8 @@ def noise_map(
     mask=None,
     points=None,
     as_subplot=False,
-        use_scaled_units=True,
-        unit_conversion_factor=None,
+    use_scaled_units=True,
+    unit_conversion_factor=None,
     unit_label="scaled",
     figsize=(7, 7),
     aspect="square",
@@ -597,8 +598,8 @@ def signal_to_noise_map(
     mask=None,
     points=None,
     as_subplot=False,
-        use_scaled_units=True,
-        unit_conversion_factor=None,
+    use_scaled_units=True,
+    unit_conversion_factor=None,
     unit_label="scaled",
     figsize=(7, 7),
     aspect="square",
@@ -675,8 +676,8 @@ def model_image(
     lines=None,
     points=None,
     as_subplot=False,
-        use_scaled_units=True,
-        unit_conversion_factor=None,
+    use_scaled_units=True,
+    unit_conversion_factor=None,
     unit_label="scaled",
     figsize=(7, 7),
     aspect="square",
@@ -753,8 +754,8 @@ def residual_map(
     mask=None,
     points=None,
     as_subplot=False,
-        use_scaled_units=True,
-        unit_conversion_factor=None,
+    use_scaled_units=True,
+    unit_conversion_factor=None,
     unit_label="scaled",
     figsize=(7, 7),
     aspect="square",
@@ -830,8 +831,8 @@ def normalized_residual_map(
     mask=None,
     points=None,
     as_subplot=False,
-        use_scaled_units=True,
-        unit_conversion_factor=None,
+    use_scaled_units=True,
+    unit_conversion_factor=None,
     unit_label="scaled",
     figsize=(7, 7),
     aspect="square",
@@ -907,8 +908,8 @@ def chi_squared_map(
     mask=None,
     points=None,
     as_subplot=False,
-        use_scaled_units=True,
-        unit_conversion_factor=None,
+    use_scaled_units=True,
+    unit_conversion_factor=None,
     unit_label="scaled",
     figsize=(7, 7),
     aspect="square",

autoarray/plotters/fit_interferometer_plotters.py

@@ -1,14 +1,13 @@
 from autoarray import conf
 import matplotlib
 
-backend = conf.instance.visualize.get("figures", "backend", str)
+backend = conf.get_matplotlib_backend()
 matplotlib.use(backend)
 from matplotlib import pyplot as plt
 
 from autoarray.plotters import grid_plotters, inversion_plotters, plotter_util
 
 
-
 def subplot(
     fit,
     unit_conversion_factor=None,

autoarray/plotters/grid_plotters.py

@@ -1,7 +1,7 @@
 from autoarray import conf
 import matplotlib
 
-backend = conf.instance.visualize.get("figures", "backend", str)
+backend = conf.get_matplotlib_backend()
 matplotlib.use(backend)
 from matplotlib import pyplot as plt
 import numpy as np
@@ -119,8 +119,14 @@ def plot_grid(
         symmetric_around_centre=symmetric_around_centre,
     )
 
-    plotter_util.set_yxticks(array=None, extent=grid.extent, use_scaled_units=True,
-                             unit_conversion_factor=unit_conversion_factor, xticks_manual=None, yticks_manual=None)
+    plotter_util.set_yxticks(
+        array=None,
+        extent=grid.extent,
+        use_scaled_units=True,
+        unit_conversion_factor=unit_conversion_factor,
+        xticks_manual=None,
+        yticks_manual=None,
+    )
 
     plot_points(grid=grid, points=points, pointcolor=pointcolor)
     plotter_util.plot_lines(line_lists=lines)