data abstractin renamed to dataset

Author: Jammy2211

autoarray/fit/__init__.py

@@ -1,5 +1,5 @@
 from ..fit.fit import (
-    DataFit as data,
+    DatasetFit as data,
     ImagingFit as imaging,
     InterferometerFit as interferometer,
 )

autoarray/fit/fit.py

@@ -24,7 +24,7 @@ def fit(masked_dataset, model_data, inversion=None):
         )
 
 
-class DataFit(object):
+class DatasetFit(object):
 
     # noinspection PyUnresolvedReferences
     def __init__(self, mask, data, noise_map, model_data, inversion=None):
@@ -136,7 +136,7 @@ def figure_of_merit(self):
             return self.evidence
 
 
-class ImagingFit(DataFit):
+class ImagingFit(DatasetFit):
     def __init__(self, mask, image, noise_map, model_image, inversion=None):
         """Class to fit simulator where the dataset structures are any dimension.
 
@@ -185,7 +185,7 @@ def model_image(self):
         return self.model_data
 
 
-class InterferometerFit(DataFit):
+class InterferometerFit(DatasetFit):
     def __init__(
         self,
         visibilities_mask,

test_autoarray/unit/conftest.py

@@ -288,7 +288,7 @@ def make_masked_interferometer_7(
 
 @pytest.fixture(name="fit_7x7")
 def make_masked_imaging_fit_x1_plane_7x7(masked_imaging_7x7):
-    return fit.DataFit(
+    return fit.DatasetFit(
         mask=masked_imaging_7x7.mask,
         data=masked_imaging_7x7.image,
         noise_map=masked_imaging_7x7.noise_map,

test_autoarray/unit/data/__init__.py test_autoarray/unit/dataset/__init__.pytest_autoarray/unit/data/__init__.py renamed to test_autoarray/unit/dataset/__init__.py

@@ -2,7 +2,6 @@
 import os
 
 import numpy as np
-import shutil
 
 import autoarray as aa
 from autoarray.dataset import abstract_dataset
@@ -19,24 +18,24 @@ def test__image_and_noise_are_values__signal_to_noise_is_ratio_of_each(self):
         array = aa.array.manual_2d([[1.0, 2.0], [3.0, 4.0]])
         noise_map = aa.array.manual_2d([[10.0, 10.0], [30.0, 4.0]])
 
-        data = abstract_dataset.AbstractDataset(data=array, noise_map=noise_map)
+        dataset = abstract_dataset.AbstractDataset(data=array, noise_map=noise_map)
 
         assert (
-            data.signal_to_noise_map.in_2d == np.array([[0.1, 0.2], [0.1, 1.0]])
+            dataset.signal_to_noise_map.in_2d == np.array([[0.1, 0.2], [0.1, 1.0]])
         ).all()
-        assert data.signal_to_noise_max == 1.0
+        assert dataset.signal_to_noise_max == 1.0
 
     def test__same_as_above__but_image_has_negative_values__replaced_with_zeros(self):
         array = aa.array.manual_2d([[-1.0, 2.0], [3.0, -4.0]])
 
         noise_map = aa.array.manual_2d([[10.0, 10.0], [30.0, 4.0]])
 
-        data = abstract_dataset.AbstractDataset(data=array, noise_map=noise_map)
+        dataset = abstract_dataset.AbstractDataset(data=array, noise_map=noise_map)
 
         assert (
-            data.signal_to_noise_map.in_2d == np.array([[0.0, 0.2], [0.1, 0.0]])
+            dataset.signal_to_noise_map.in_2d == np.array([[0.0, 0.2], [0.1, 0.0]])
         ).all()
-        assert data.signal_to_noise_max == 0.2
+        assert dataset.signal_to_noise_max == 0.2
 
 
 class TestAbsoluteSignalToNoise:
@@ -47,13 +46,13 @@ def test__image_and_noise_are_values__signal_to_noise_is_absolute_image_value_ov
 
         noise_map = aa.array.manual_2d([[10.0, 10.0], [30.0, 4.0]])
 
-        data = abstract_dataset.AbstractDataset(data=array, noise_map=noise_map)
+        dataset = abstract_dataset.AbstractDataset(data=array, noise_map=noise_map)
 
         assert (
-            data.absolute_signal_to_noise_map.in_2d
+            dataset.absolute_signal_to_noise_map.in_2d
             == np.array([[0.1, 0.2], [0.1, 1.0]])
         ).all()
-        assert data.absolute_signal_to_noise_max == 1.0
+        assert dataset.absolute_signal_to_noise_max == 1.0
 
 
 class TestPotentialChiSquaredMap:
@@ -63,13 +62,13 @@ def test__image_and_noise_are_values__signal_to_noise_is_absolute_image_value_ov
         array = aa.array.manual_2d([[-1.0, 2.0], [3.0, -4.0]])
         noise_map = aa.array.manual_2d([[10.0, 10.0], [30.0, 4.0]])
 
-        data = abstract_dataset.AbstractDataset(data=array, noise_map=noise_map)
+        dataset = abstract_dataset.AbstractDataset(data=array, noise_map=noise_map)
 
         assert (
-            data.potential_chi_squared_map.in_2d
+            dataset.potential_chi_squared_map.in_2d
             == np.array([[0.1 ** 2.0, 0.2 ** 2.0], [0.1 ** 2.0, 1.0 ** 2.0]])
         ).all()
-        assert data.potential_chi_squared_max == 1.0
+        assert dataset.potential_chi_squared_max == 1.0
 
 
 class TestExposureTimeMap(object):