refactor: replace os.path with pathlib in workspace scripts

plotting_alignment/imaging_delaunay.py

@@ -34,7 +34,6 @@
 import numpy as np
 import jax
 from jax import grad
-from os import path
 
 import autofit as af
 import autolens as al
@@ -79,9 +78,9 @@
 dataset_path = Path("dataset", "imaging", dataset_type, dataset_name)
 
 dataset = al.Imaging.from_fits(
-    data_path=path.join(dataset_path, "data.fits"),
-    psf_path=path.join(dataset_path, "psf.fits"),
-    noise_map_path=path.join(dataset_path, "noise_map.fits"),
+    data_path=Path(dataset_path) / "data.fits",
+    psf_path=Path(dataset_path) / "psf.fits",
+    noise_map_path=Path(dataset_path) / "noise_map.fits",
     pixel_scales=pixel_scale,
     over_sample_size_lp=sub_size,
     over_sample_size_pixelization=sub_size,
@@ -250,7 +249,7 @@
 import autolens.plot as aplt
 import os
 
-file_path = os.path.join(al.__version__)
+file_path = Path(al.__version__)
 
 instance = model.instance_from_prior_medians()
 

plotting_alignment/imaging_rectangular.py

@@ -34,7 +34,6 @@
 import numpy as np
 import jax
 from jax import grad
-from os import path
 
 import autofit as af
 import autolens as al
@@ -78,9 +77,9 @@
 dataset_path = Path("dataset", "imaging", dataset_type, dataset_name)
 
 dataset = al.Imaging.from_fits(
-    data_path=path.join(dataset_path, "data.fits"),
-    psf_path=path.join(dataset_path, "psf.fits"),
-    noise_map_path=path.join(dataset_path, "noise_map.fits"),
+    data_path=Path(dataset_path) / "data.fits",
+    psf_path=Path(dataset_path) / "psf.fits",
+    noise_map_path=Path(dataset_path) / "noise_map.fits",
     pixel_scales=pixel_scale,
     over_sample_size_lp=sub_size,
     over_sample_size_pixelization=sub_size,
@@ -246,7 +245,7 @@
 import autolens.plot as aplt
 import os
 
-file_path = os.path.join(al.__version__)
+file_path = Path(al.__version__)
 
 instance = model.instance_from_prior_medians()
 

plotting_alignment/imaging_rectangular_no_interp.py

@@ -34,7 +34,6 @@
 import numpy as np
 import jax
 from jax import grad
-from os import path
 
 import autofit as af
 import autolens as al
@@ -78,9 +77,9 @@
 dataset_path = Path("dataset", "imaging", dataset_type, dataset_name)
 
 dataset = al.Imaging.from_fits(
-    data_path=path.join(dataset_path, "data.fits"),
-    psf_path=path.join(dataset_path, "psf.fits"),
-    noise_map_path=path.join(dataset_path, "noise_map.fits"),
+    data_path=Path(dataset_path) / "data.fits",
+    psf_path=Path(dataset_path) / "psf.fits",
+    noise_map_path=Path(dataset_path) / "noise_map.fits",
     pixel_scales=pixel_scale,
     over_sample_size_lp=sub_size,
     over_sample_size_pixelization=sub_size,
@@ -244,7 +243,7 @@
 import autolens.plot as aplt
 import os
 
-file_path = os.path.join(al.__version__)
+file_path = Path(al.__version__)
 
 instance = model.instance_from_prior_medians()
 

plotting_alignment/plot/imaging/orientation/parametric.py

@@ -15,9 +15,9 @@
 # %cd $workspace_path
 # print(f"Working Directory has been set to `{workspace_path}`")
 
-from os import path
 import autolens as al
 import autolens.plot as aplt
+from pathlib import Path
 
 """
 __Dataset__
@@ -26,12 +26,12 @@
 """
 dataset_type = "imaging"
 dataset_name = "orientation"
-dataset_path = path.join("dataset", dataset_type, dataset_name)
+dataset_path = Path("dataset") / dataset_type / dataset_name
 
 dataset = al.Imaging.from_fits(
-    data_path=path.join(dataset_path, "data.fits"),
-    psf_path=path.join(dataset_path, "psf.fits"),
-    noise_map_path=path.join(dataset_path, "noise_map.fits"),
+    data_path=Path(dataset_path) / "data.fits",
+    psf_path=Path(dataset_path) / "psf.fits",
+    noise_map_path=Path(dataset_path) / "noise_map.fits",
     pixel_scales=0.1,
 )
 
@@ -78,7 +78,7 @@
 __Output__
 """
 output = aplt.Output(
-    path=path.join("plot", "imaging", "orientation", "plots", "parametric"),
+    path=Path("plot") / "imaging" / "orientation" / "plots" / "parametric",
     format="png",
 )
 

plotting_alignment/plot/imaging/orientation/pix.py

@@ -15,9 +15,9 @@
 # %cd $workspace_path
 # print(f"Working Directory has been set to `{workspace_path}`")
 
-from os import path
 import autolens as al
 import autolens.plot as aplt
+from pathlib import Path
 
 """
 __Dataset__
@@ -26,12 +26,12 @@
 """
 dataset_type = "imaging"
 dataset_name = "orientation"
-dataset_path = path.join("dataset", dataset_type, dataset_name)
+dataset_path = Path("dataset") / dataset_type / dataset_name
 
 dataset = al.Imaging.from_fits(
-    data_path=path.join(dataset_path, "data.fits"),
-    psf_path=path.join(dataset_path, "psf.fits"),
-    noise_map_path=path.join(dataset_path, "noise_map.fits"),
+    data_path=Path(dataset_path) / "data.fits",
+    psf_path=Path(dataset_path) / "psf.fits",
+    noise_map_path=Path(dataset_path) / "noise_map.fits",
     pixel_scales=0.1,
 )
 
@@ -76,7 +76,7 @@
 __Output__
 """
 output = aplt.Output(
-    path=path.join("plot", "imaging", "orientation", "plots", "pix_delaunay"),
+    path=Path("plot") / "imaging" / "orientation" / "plots" / "pix_delaunay",
     format="png",
 )
 

plotting_alignment/plot/imaging/orientation/simulator.py

@@ -26,9 +26,9 @@
 # %cd $workspace_path
 # print(f"Working Directory has been set to `{workspace_path}`")
 
-from os import path
 import autolens as al
 import autolens.plot as aplt
+from pathlib import Path
 
 """
 __Dataset Paths__
@@ -37,7 +37,7 @@
 """
 dataset_type = "imaging"
 dataset_name = "orientation"
-dataset_path = path.join("dataset", dataset_type, dataset_name)
+dataset_path = Path("dataset") / dataset_type / dataset_name
 
 """
 __Simulate__
@@ -122,9 +122,9 @@
 Output the simulated dataset to the dataset path as .fits files.
 """
 dataset.output_to_fits(
-    data_path=path.join(dataset_path, "data.fits"),
-    psf_path=path.join(dataset_path, "psf.fits"),
-    noise_map_path=path.join(dataset_path, "noise_map.fits"),
+    data_path=Path(dataset_path) / "data.fits",
+    psf_path=Path(dataset_path) / "psf.fits",
+    noise_map_path=Path(dataset_path) / "noise_map.fits",
     overwrite=True,
 )
 
@@ -146,7 +146,7 @@
 """
 al.output_to_json(
     obj=tracer,
-    file_path=path.join(dataset_path, "tracer.json"),
+    file_path=Path(dataset_path) / "tracer.json",
 )
 
 """

plotting_alignment/plot/interferometer/orientation/parametric.py

@@ -15,10 +15,10 @@
 # %cd $workspace_path
 # print(f"Working Directory has been set to `{workspace_path}`")
 
-from os import path
 import numpy as np
 import autolens as al
 import autolens.plot as aplt
+from pathlib import Path
 
 """
 __Dataset__
@@ -27,16 +27,16 @@
 """
 dataset_type = "interferometer"
 dataset_name = "orientation"
-dataset_path = path.join("dataset", dataset_type, dataset_name)
+dataset_path = Path("dataset") / dataset_type / dataset_name
 
 real_space_mask = al.Mask2D.circular(
     shape_native=(200, 200), pixel_scales=0.05, radius=4.0, centre=(0.5, 0.5)
 )
 
 dataset = al.Interferometer.from_fits(
-    data_path=path.join(dataset_path, "data.fits"),
-    noise_map_path=path.join(dataset_path, "noise_map.fits"),
-    uv_wavelengths_path=path.join(dataset_path, "uv_wavelengths.fits"),
+    data_path=Path(dataset_path) / "data.fits",
+    noise_map_path=Path(dataset_path) / "noise_map.fits",
+    uv_wavelengths_path=Path(dataset_path) / "uv_wavelengths.fits",
     real_space_mask=real_space_mask,
     transformer_class=al.TransformerNUFFT,
 )
@@ -75,7 +75,7 @@
 __Output__
 """
 output = aplt.Output(
-    path=path.join("plot", "interferometer", "orientation", "plots", "parametric"),
+    path=Path("plot") / "interferometer" / "orientation" / "plots" / "parametric",
     format="png",
 )
 

plotting_alignment/plot/interferometer/orientation/pix.py

@@ -15,10 +15,10 @@
 # %cd $workspace_path
 # print(f"Working Directory has been set to `{workspace_path}`")
 
-from os import path
 import numpy as np
 import autolens as al
 import autolens.plot as aplt
+from pathlib import Path
 
 """
 __Dataset__
@@ -27,16 +27,16 @@
 """
 dataset_type = "interferometer"
 dataset_name = "orientation"
-dataset_path = path.join("dataset", dataset_type, dataset_name)
+dataset_path = Path("dataset") / dataset_type / dataset_name
 
 real_space_mask = al.Mask2D.circular(
     shape_native=(800, 800), pixel_scales=0.05, radius=4.0, centre=(0.5, 0.5)
 )
 
 dataset = al.Interferometer.from_fits(
-    data_path=path.join(dataset_path, "data.fits"),
-    noise_map_path=path.join(dataset_path, "noise_map.fits"),
-    uv_wavelengths_path=path.join(dataset_path, "uv_wavelengths.fits"),
+    data_path=Path(dataset_path) / "data.fits",
+    noise_map_path=Path(dataset_path) / "noise_map.fits",
+    uv_wavelengths_path=Path(dataset_path) / "uv_wavelengths.fits",
     real_space_mask=real_space_mask,
     transformer_class=al.TransformerNUFFT,
 )
@@ -73,7 +73,7 @@
 __Output__
 """
 output = aplt.Output(
-    path=path.join("plot", "interferometer", "orientation", "plots", "pix_delaunay"),
+    path=Path("plot") / "interferometer" / "orientation" / "plots" / "pix_delaunay",
     format="png",
 )
 

plotting_alignment/plot/interferometer/orientation/simulator.py

@@ -14,9 +14,9 @@
 # %cd $workspace_path
 # print(f"Working Directory has been set to `{workspace_path}`")
 
-from os import path
 import autolens as al
 import autolens.plot as aplt
+from pathlib import Path
 
 """ 
 The `dataset_type` describes the type of data being simulated (in this case, `Interferometer` data) and `dataset_name` 
@@ -28,7 +28,7 @@
 """
 dataset_type = "interferometer"
 dataset_name = "orientation"
-dataset_path = path.join("dataset", dataset_type, dataset_name)
+dataset_path = Path("dataset") / dataset_type / dataset_name
 
 
 """
@@ -46,9 +46,9 @@
 can be fitted extremely efficiently. The `autolens_workspace` includes ALMA uv_wavelengths files for simulating
 much high resolution datasets (which can be performed by replacing "sma.fits" below with "alma.fits").
 """
-uv_wavelengths_path = path.join("dataset", dataset_type, "uv_wavelengths")
+uv_wavelengths_path = Path("dataset") / dataset_type / "uv_wavelengths"
 uv_wavelengths = al.ndarray_via_fits_from(
-    file_path=path.join(uv_wavelengths_path, "sma.fits"), hdu=0
+    file_path=Path(uv_wavelengths_path) / "sma.fits", hdu=0
 )
 
 """
@@ -123,9 +123,9 @@
 Output the simulated dataset to the dataset path as .fits files.
 """
 dataset.output_to_fits(
-    data_path=path.join(dataset_path, "data.fits"),
-    noise_map_path=path.join(dataset_path, "noise_map.fits"),
-    uv_wavelengths_path=path.join(dataset_path, "uv_wavelengths.fits"),
+    data_path=Path(dataset_path) / "data.fits",
+    noise_map_path=Path(dataset_path) / "noise_map.fits",
+    uv_wavelengths_path=Path(dataset_path) / "uv_wavelengths.fits",
     overwrite=True,
 )
 
@@ -147,7 +147,7 @@
 """
 al.output_to_json(
     obj=tracer,
-    file_path=path.join(dataset_path, "tracer.json"),
+    file_path=Path(dataset_path) / "tracer.json",
 )
 
 """

slam_pipeline/dspl.py

@@ -35,7 +35,6 @@ def fit():
     # print(f"Working Directory has been set to `{workspace_path}`")
 
     import os
-    from os import path
 
     import autofit as af
     import autolens as al
@@ -48,12 +47,12 @@ def fit():
     Load the `Imaging` data, define the `Mask2D` and plot them.
     """
     dataset_name = "with_lens_light"
-    dataset_path = path.join("dataset", "imaging", dataset_name)
+    dataset_path = Path("dataset") / "imaging" / dataset_name
 
     dataset = al.Imaging.from_fits(
-        data_path=path.join(dataset_path, "data.fits"),
-        noise_map_path=path.join(dataset_path, "noise_map.fits"),
-        psf_path=path.join(dataset_path, "psf.fits"),
+        data_path=Path(dataset_path) / "data.fits",
+        noise_map_path=Path(dataset_path) / "noise_map.fits",
+        psf_path=Path(dataset_path) / "psf.fits",
         pixel_scales=0.2,
     )
 
@@ -75,7 +74,7 @@ def fit():
     The settings of autofit, which controls the output paths, parallelization, database use, etc.
     """
     settings_search = af.SettingsSearch(
-        path_prefix=path.join("slam", "source_pix", "mass_total", "base"),
+        path_prefix=Path("slam") / "source_pix" / "mass_total" / "base",
         number_of_cores=1,
         session=None,
     )
@@ -85,6 +84,7 @@ def fit():
 
     The redshifts of the lens and source galaxies, which are used to perform unit converions of the model and data (e.g. 
     from arc-seconds to kiloparsecs, masses to solar masses, etc.).
+from pathlib import Path
     """
     redshift_lens = 0.5
     redshift_source = 1.0