Clean up example script.

scripts/recon/hyperspectral.py

@@ -16,10 +16,7 @@
 import matplotlib.pyplot as plt
 from lensless.utils.io import load_data
 from lensless import (
-    GradientDescentUpdate,
-    GradientDescent,
-    NesterovGradientDescent,
-    FISTA,
+    HyperSpectralFISTA,
 )
 
 
@@ -60,94 +57,29 @@ def gradient_descent(
     data = np.expand_dims(data, axis=0)
     data = np.expand_dims(data, axis=-1)
 
-    # apply gradient descent
-    from lensless import HyperSpectralFISTA
-
+    # apply FISTA
     save = config["save"]
     if save:
         save = os.getcwd()
 
+    start_time = time.time()
     recon = HyperSpectralFISTA(
         psf,
         mask,
         # norm=None,
         norm="ortho",
     )
     recon.set_data(data)
+    print(f"Setup time : {time.time() - start_time} s")
+
+    start_time = time.time()
     res = recon.apply(
         n_iter=500,
         disp_iter=50,
         save=save,
         gamma=1.0,
         plot=False,
     )
-
-    if config.torch:
-        img = res[0].cpu().numpy()
-    else:
-        img = res[0]
-
-    if config["display"]["plot"]:
-        plt.show()
-    if save:
-        np.save(plib.Path(save) / "final_reconstruction.npy", img)
-        print(f"Files saved to : {save}")
-
-    raise ValueError
-
-    psf, data = load_data(
-        psf_fp=to_absolute_path(config.input.psf),
-        data_fp=to_absolute_path(config.input.data),
-        dtype=config.input.dtype,
-        downsample=config["preprocess"]["downsample"],
-        bayer=config["preprocess"]["bayer"],
-        blue_gain=config["preprocess"]["blue_gain"],
-        red_gain=config["preprocess"]["red_gain"],
-        plot=config["display"]["plot"],
-        flip=config["preprocess"]["flip"],
-        gamma=config["display"]["gamma"],
-        gray=config["preprocess"]["gray"],
-        single_psf=config["preprocess"]["single_psf"],
-        shape=config["preprocess"]["shape"],
-        use_torch=config.torch,
-        torch_device=config.torch_device,
-    )
-
-    disp = config["display"]["disp"]
-    if disp < 0:
-        disp = None
-
-    save = config["save"]
-    if save:
-        save = os.getcwd()
-
-    start_time = time.time()
-
-    if config["gradient_descent"]["method"] == GradientDescentUpdate.VANILLA:
-        recon = GradientDescent(psf)
-    elif config["gradient_descent"]["method"] == GradientDescentUpdate.NESTEROV:
-        recon = NesterovGradientDescent(
-            psf,
-            p=config["gradient_descent"]["nesterov"]["p"],
-            mu=config["gradient_descent"]["nesterov"]["mu"],
-        )
-    else:
-        recon = FISTA(
-            psf,
-            tk=config["gradient_descent"]["fista"]["tk"],
-        )
-
-    recon.set_data(data)
-    print(f"Setup time : {time.time() - start_time} s")
-
-    start_time = time.time()
-    res = recon.apply(
-        n_iter=config["gradient_descent"]["n_iter"],
-        disp_iter=disp,
-        save=save,
-        gamma=config["display"]["gamma"],
-        plot=config["display"]["plot"],
-    )
     print(f"Processing time : {time.time() - start_time} s")
 
     if config.torch: