test: write test output to tmp_path, untrack generated FITS artifacts

.gitignore

@@ -6,8 +6,10 @@ test_autoarray/mask/files/mask/mask_out.fits
 test_autoarray/plot/wrap/base/files/
 test_autoarray/structures/grids/files/grid_2d.fits
 
-test_autoarray/dataset/files/array/output_test/uv_wavelengths.fits
-test_autoarray/dataset/files/array/output_test/visibilities.fits
+# Test output: tests write results into output_test/ dirs and read them back.
+# Never track them -- a change to the autonerves FITS writer would otherwise
+# rewrite a committed binary and dirty every contributor's tree (PyAutoArray#483).
+test_autoarray/**/output_test/
 test_autoarray/dataset/plot/files/
 test_autoarray/fit/plot/files/
 test_autoarray/structures/arrays/one_d/files/array/

test_autoarray/dataset/imaging/test_dataset.py

@@ -1,9 +1,7 @@
 import copy
-import os
 
 import numpy as np
 import pytest
-import shutil
 
 import autoarray as aa
 
@@ -13,18 +11,6 @@
 test_data_path = Path(Path(__file__).resolve().parent) / "files"
 
 
-@pytest.fixture(name="test_data_path")
-def make_test_data_path():
-    test_data_path = Path(__file__).resolve().parent / "files" / "array" / "output_test"
-
-    if test_data_path.exists():
-        shutil.rmtree(test_data_path)
-
-    os.makedirs(test_data_path)
-
-    return test_data_path
-
-
 def test__grid__uses_mask_and_settings__lp_grid_matches_grid_2d_7x7(
     image_7x7,
     noise_map_7x7,
@@ -162,27 +148,25 @@ def test__from_fits__all_data_in_one_fits_file_multiple_hdus__loads_data_psf_noi
     assert dataset.noise_map.mask.pixel_scales == (0.1, 0.1)
 
 
-def test__from_fits__small_datasets_env_caps_data_and_noise_map(
-    test_data_path, monkeypatch
-):
+def test__from_fits__small_datasets_env_caps_data_and_noise_map(tmp_path, monkeypatch):
     """When PYAUTO_SMALL_DATASETS=1, Imaging.from_fits center-crops data and
     noise_map to (15, 15) at pixel_scales=0.6 so they stay shape-consistent
     with masks built via Mask2D.circular under the same env var. PSF is left
     alone."""
     from astropy.io import fits
 
     fits.writeto(
-        Path(test_data_path) / "data_30x30.fits",
+        tmp_path / "data_30x30.fits",
         data=np.ones((30, 30), dtype=np.float64),
         overwrite=True,
     )
     fits.writeto(
-        Path(test_data_path) / "noise_map_30x30.fits",
+        tmp_path / "noise_map_30x30.fits",
         data=2.0 * np.ones((30, 30), dtype=np.float64),
         overwrite=True,
     )
     fits.writeto(
-        Path(test_data_path) / "psf_5x5.fits",
+        tmp_path / "psf_5x5.fits",
         data=(1.0 / 25.0) * np.ones((5, 5), dtype=np.float64),
         overwrite=True,
     )
@@ -191,9 +175,9 @@ def test__from_fits__small_datasets_env_caps_data_and_noise_map(
 
     dataset = aa.Imaging.from_fits(
         pixel_scales=0.08,
-        data_path=Path(test_data_path) / "data_30x30.fits",
-        psf_path=Path(test_data_path) / "psf_5x5.fits",
-        noise_map_path=Path(test_data_path) / "noise_map_30x30.fits",
+        data_path=tmp_path / "data_30x30.fits",
+        psf_path=tmp_path / "psf_5x5.fits",
+        noise_map_path=tmp_path / "noise_map_30x30.fits",
     )
 
     assert dataset.data.shape_native == (16, 16)
@@ -202,20 +186,18 @@ def test__from_fits__small_datasets_env_caps_data_and_noise_map(
     assert dataset.psf.kernel.shape_native == (5, 5)
 
 
-def test__from_fits__small_datasets_env_unset__shape_unchanged(
-    test_data_path, monkeypatch
-):
+def test__from_fits__small_datasets_env_unset__shape_unchanged(tmp_path, monkeypatch):
     """Sanity: with the env var unset, from_fits returns the on-disk shape
     unchanged, even for files larger than the cap."""
     from astropy.io import fits
 
     fits.writeto(
-        Path(test_data_path) / "data_30x30.fits",
+        tmp_path / "data_30x30.fits",
         data=np.ones((30, 30), dtype=np.float64),
         overwrite=True,
     )
     fits.writeto(
-        Path(test_data_path) / "noise_map_30x30.fits",
+        tmp_path / "noise_map_30x30.fits",
         data=2.0 * np.ones((30, 30), dtype=np.float64),
         overwrite=True,
     )
@@ -224,34 +206,32 @@ def test__from_fits__small_datasets_env_unset__shape_unchanged(
 
     dataset = aa.Imaging.from_fits(
         pixel_scales=0.08,
-        data_path=Path(test_data_path) / "data_30x30.fits",
-        noise_map_path=Path(test_data_path) / "noise_map_30x30.fits",
+        data_path=tmp_path / "data_30x30.fits",
+        noise_map_path=tmp_path / "noise_map_30x30.fits",
     )
 
     assert dataset.data.shape_native == (30, 30)
     assert dataset.noise_map.shape_native == (30, 30)
     assert dataset.pixel_scales == (0.08, 0.08)
 
 
-def test__output_to_fits__round_trips_data_psf_noise_map_correctly(
-    imaging_7x7, test_data_path
-):
+def test__output_to_fits__round_trips_data_psf_noise_map_correctly(imaging_7x7, tmp_path):
 
     from autoarray.dataset.plot.imaging_plots import fits_imaging
 
     fits_imaging(
         dataset=imaging_7x7,
-        data_path=Path(test_data_path) / "data.fits",
-        psf_path=Path(test_data_path) / "psf.fits",
-        noise_map_path=Path(test_data_path) / "noise_map.fits",
+        data_path=tmp_path / "data.fits",
+        psf_path=tmp_path / "psf.fits",
+        noise_map_path=tmp_path / "noise_map.fits",
         overwrite=True,
     )
 
     dataset = aa.Imaging.from_fits(
         pixel_scales=0.1,
-        data_path=Path(test_data_path) / "data.fits",
-        psf_path=Path(test_data_path) / "psf.fits",
-        noise_map_path=Path(test_data_path) / "noise_map.fits",
+        data_path=tmp_path / "data.fits",
+        psf_path=tmp_path / "psf.fits",
+        noise_map_path=tmp_path / "noise_map.fits",
     )
 
     assert (dataset.data.native == np.ones((7, 7))).all()

test_autoarray/dataset/interferometer/test_dataset.py

@@ -1,6 +1,4 @@
 import numpy as np
-import os
-import shutil
 
 import autoarray as aa
 import pytest
@@ -127,7 +125,7 @@ def test__from_fits__all_files_in_one_fits__load_using_different_hdus(mask_2d_7x
     assert (dataset.uv_wavelengths[:, 1] == 3.0 * np.ones(3)).all()
 
 
-def test__output_all_arrays(mask_2d_7x7):
+def test__output_all_arrays(mask_2d_7x7, tmp_path):
     test_data_path = Path(Path(__file__).resolve().parent) / "files"
 
     dataset = aa.Interferometer.from_fits(
@@ -137,28 +135,21 @@ def test__output_all_arrays(mask_2d_7x7):
         uv_wavelengths_path=Path(test_data_path) / "3x2_fives_sixes.fits",
     )
 
-    test_data_path = Path(Path(__file__).resolve().parent) / "files" / "array" / "output_test"
-
-    if Path(test_data_path).exists():
-        shutil.rmtree(test_data_path)
-
-    os.makedirs(test_data_path)
-
     from autoarray.dataset.plot.interferometer_plots import fits_interferometer
 
     fits_interferometer(
         dataset=dataset,
-        data_path=Path(test_data_path) / "data.fits",
-        noise_map_path=Path(test_data_path) / "noise_map.fits",
-        uv_wavelengths_path=Path(test_data_path) / "uv_wavelengths.fits",
+        data_path=tmp_path / "data.fits",
+        noise_map_path=tmp_path / "noise_map.fits",
+        uv_wavelengths_path=tmp_path / "uv_wavelengths.fits",
         overwrite=True,
     )
 
     dataset = aa.Interferometer.from_fits(
         real_space_mask=mask_2d_7x7,
-        data_path=Path(test_data_path) / "data.fits",
-        noise_map_path=Path(test_data_path) / "noise_map.fits",
-        uv_wavelengths_path=Path(test_data_path) / "uv_wavelengths.fits",
+        data_path=tmp_path / "data.fits",
+        noise_map_path=tmp_path / "noise_map.fits",
+        uv_wavelengths_path=tmp_path / "uv_wavelengths.fits",
     )
 
     assert (dataset.data == np.array([1.0 + 2.0j, 1.0 + 2.0j, 1.0 + 2.0j])).all()

test_autoarray/mask/test_mask_2d.py

@@ -1,8 +1,6 @@
 from astropy.io import fits
-import os
 import numpy as np
 import pytest
-import shutil
 
 import autoarray as aa
 from autoarray import exc
@@ -407,30 +405,25 @@ def test__from_pixel_coordinates__two_coordinates_buffer_1__two_separate_unmaske
 # ---------------------------------------------------------------------------
 
 
-def test__from_fits__output_to_fits__roundtrip_preserves_values_pixel_scales_and_header():
+def test__from_fits__output_to_fits__roundtrip_preserves_values_pixel_scales_and_header(
+    tmp_path,
+):
     mask = aa.Mask2D.from_fits(
         file_path=Path(test_data_path) / "3x3_ones.fits",
         hdu=0,
         pixel_scales=(1.0, 1.0),
     )
 
-    output_path = Path(Path(__file__).resolve().parent) / "files" / "array" / "output_test"
-
-    if Path(output_path).exists():
-        shutil.rmtree(output_path)
-
-    os.makedirs(output_path)
-
     from autonerves.fitsable import output_to_fits
     output_to_fits(
         values=mask.astype("float"),
-        file_path=Path(output_path) / "mask.fits",
+        file_path=tmp_path / "mask.fits",
         header_dict=mask.header_dict,
         ext_name="mask",
     )
 
     mask = aa.Mask2D.from_fits(
-        file_path=Path(output_path) / "mask.fits",
+        file_path=tmp_path / "mask.fits",
         hdu=0,
         pixel_scales=(1.0, 1.0),
         origin=(2.0, 2.0),
@@ -440,7 +433,7 @@ def test__from_fits__output_to_fits__roundtrip_preserves_values_pixel_scales_and
     assert mask.pixel_scales == (1.0, 1.0)
     assert mask.origin == (2.0, 2.0)
 
-    header = aa.header_obj_from(file_path=Path(output_path) / "mask.fits", hdu=0)
+    header = aa.header_obj_from(file_path=tmp_path / "mask.fits", hdu=0)
 
     assert header["PIXSCAY"] == 1.0
     assert header["PIXSCAX"] == 1.0

test_autoarray/structures/arrays/test_uniform_1d.py

@@ -9,8 +9,6 @@
 
 fits_path = Path(__file__).resolve().parent / "files" / "array_1d"
 
-test_data_path = Path(__file__).resolve().parent / "files" / "array" / "output_test"
-
 
 def create_fits(
     fits_path,
@@ -154,25 +152,20 @@ def test__from_fits__4_element_fits__header_bitpix_is_minus_64():
     clean_fits(fits_path=fits_path)
 
 
-def test__output_to_fits__ones_array__fits_file_has_correct_values_and_header():
+def test__output_to_fits__ones_array__fits_file_has_correct_values_and_header(tmp_path):
     arr = aa.Array1D.ones(shape_native=(3,), pixel_scales=1.0)
 
-    if test_data_path.exists():
-        shutil.rmtree(test_data_path)
-
-    os.makedirs(test_data_path)
-
     from autonerves.fitsable import output_to_fits
-    output_to_fits(values=arr.native.array.astype("float"), file_path=test_data_path / "array.fits", header_dict=arr.mask.header_dict)
+    output_to_fits(values=arr.native.array.astype("float"), file_path=tmp_path / "array.fits", header_dict=arr.mask.header_dict)
 
     array_from_out = aa.Array1D.from_fits(
-        file_path=test_data_path / "array.fits", hdu=0, pixel_scales=1.0
+        file_path=tmp_path / "array.fits", hdu=0, pixel_scales=1.0
     )
 
     assert (array_from_out.native == np.ones((3,))).all()
 
     header_load = aa.header_obj_from(
-        file_path=test_data_path / "array.fits", hdu=0
+        file_path=tmp_path / "array.fits", hdu=0
     )
 
     assert header_load["PIXSCA"] == 1.0

test_autoarray/structures/arrays/test_uniform_2d.py

@@ -1,10 +1,8 @@
 from astropy.io import fits
-import os
 from pathlib import Path
 
 import numpy as np
 import pytest
-import shutil
 
 import autoarray as aa
 
@@ -191,24 +189,20 @@ def test__from_yx_and_values__3x2_grid__native_matches_expected_pixel_layout():
     assert (array_2d.native == np.array([[3.0, 2.0], [6.0, 4.0], [5.0, 1.0]])).all()
 
 
-def test__output_to_fits__3x3_ones__fits_file_has_ones_and_correct_pixel_scale_header():
+def test__output_to_fits__3x3_ones__fits_file_has_ones_and_correct_pixel_scale_header(
+    tmp_path,
+):
     files_path = Path(__file__).resolve().parent / "files"
 
     array_2d = aa.Array2D.from_fits(
         file_path=files_path / "3x3_ones.fits", hdu=0, pixel_scales=1.0
     )
 
-    output_test_path = files_path / "array" / "output_test"
-    if output_test_path.exists():
-        shutil.rmtree(output_test_path)
-
-    os.makedirs(output_test_path)
-
     from autonerves.fitsable import output_to_fits
-    output_to_fits(values=array_2d.native.array.astype("float"), file_path=output_test_path / "array.fits", header_dict=array_2d.mask.header_dict)
+    output_to_fits(values=array_2d.native.array.astype("float"), file_path=tmp_path / "array.fits", header_dict=array_2d.mask.header_dict)
 
     array_from_fits = aa.Array2D.from_fits(
-        file_path=output_test_path / "array.fits", hdu=0, pixel_scales=1.0
+        file_path=tmp_path / "array.fits", hdu=0, pixel_scales=1.0
     )
 
     assert (array_from_fits.native == np.ones((3, 3))).all()

test_autoarray/structures/test_visibilities.py

@@ -1,8 +1,6 @@
-import os
 from pathlib import Path
 import numpy as np
 import pytest
-import shutil
 
 import autoarray as aa
 from autoarray.structures import visibilities as vis
@@ -86,25 +84,18 @@ def test__from_fits__makes_visibilities_without_other_inputs():
     assert (visibilities.slim == np.array([2.0 + 2.0j, 2.0 + 2.0j, 2.0 + 2.0j])).all()
 
 
-def test__output_to_fits():
+def test__output_to_fits(tmp_path):
     files_path = Path(__file__).resolve().parent / "files"
 
     visibilities = aa.Visibilities.from_fits(
         file_path=files_path / "3x2_ones.fits", hdu=0
     )
 
-    output_test_path = files_path / "output_test"
-
-    if output_test_path.exists():
-        shutil.rmtree(output_test_path)
-
-    os.makedirs(output_test_path)
-
     from autonerves.fitsable import output_to_fits
-    output_to_fits(values=visibilities.in_array, file_path=output_test_path / "data.fits")
+    output_to_fits(values=visibilities.in_array, file_path=tmp_path / "data.fits")
 
     visibilities_from_out = aa.Visibilities.from_fits(
-        file_path=output_test_path / "data.fits", hdu=0
+        file_path=tmp_path / "data.fits", hdu=0
     )
     assert (
         visibilities_from_out.slim == np.array([1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j])