update some changes

Author: alineyyy

src/cli-conf/scenario2-2d.yaml

@@ -1,4 +1,4 @@
-# This files contains the configuration to reproduce the scenario 1 of the Snkf paper.
+# This files contains the configuration to produce the scenario 2  of the Snkf paper but with a 2D slice acquisition and reconstruction.
 
 defaults:
   - base_config
@@ -35,7 +35,6 @@ handlers:
     block_on: 20 # seconds
     block_off: 20 #seconds
     duration: 360 # seconds
-    #delta_r2s: 1000 # millisecond^-1
 
 sampler:
   stack-of-spiral:

src/snake/mrd_utils/loader.py

@@ -218,7 +218,7 @@ def engine_model(self) -> str:
 
     @property
     def slice_2d(self) -> bool:
-        """Is the slice 2D."""
+        """Is the acquisiton run on 2D slices."""
         return bool(self.header.userParameters.userParameterString[1].value)
 
     #############

src/snake/toolkit/cli/__init__.py

@@ -1 +1 @@
-""" "Command Line Interface for SNAKE."""
+"""Command Line Interface for SNAKE."""

src/snake/toolkit/cli/config.py

@@ -125,5 +125,5 @@ def cleanup_cuda() -> None:
 def make_hydra_cli(fun: callable) -> callable:
     """Create a Hydra CLI for the function."""
     return hydra.main(
-        version_base=None, config_path="../../../cli-conf", config_name="scenario2-2d"
+        version_base=None, config_path="../../../cli-conf", config_name="config"
     )(fun)

src/snake/toolkit/cli/reconstruction.py

@@ -57,7 +57,7 @@ def reconstruction(cfg: DictConfig) -> None:
             data_rec_file = Path(f"data_rec_{rec_str}.npy")
             log.info(f"Using {name} reconstructor")
             rec.setup(sim_conf)
-            rec_data = rec.reconstruct(data_loader, sim_conf, data_loader.slice_2d)
+            rec_data = rec.reconstruct(data_loader, sim_conf)
             log.info(f"Reconstruction done with {name}")
             # Save the reconstruction
             np.save(data_rec_file, rec_data)

src/snake/toolkit/reconstructors/pysap.py

@@ -73,20 +73,18 @@ def setup(self, sim_conf: SimConfig) -> None:
         """Initialize Reconstructor."""
         pass
 
-    def reconstruct(
-        self, data_loader: MRDLoader, sim_conf: SimConfig, slice_2d: bool
-    ) -> NDArray:
+    def reconstruct(self, data_loader: MRDLoader, sim_conf: SimConfig) -> NDArray:
         """Reconstruct data with zero-filled method."""
         with data_loader:
             if isinstance(data_loader, CartesianFrameDataLoader):
-                return self._reconstruct_cartesian(data_loader, sim_conf, slice_2d)
+                return self._reconstruct_cartesian(data_loader, sim_conf)
             elif isinstance(data_loader, NonCartesianFrameDataLoader):
-                return self._reconstruct_nufft(data_loader, sim_conf, slice_2d)
+                return self._reconstruct_nufft(data_loader, sim_conf)
             else:
                 raise ValueError("Unknown dataloader")
 
     def _reconstruct_cartesian(
-        self, data_loader: CartesianFrameDataLoader, sim_conf: SimConfig, slice_2d
+        self, data_loader: CartesianFrameDataLoader, sim_conf: SimConfig
     ) -> NDArray:
         smaps = data_loader.get_smaps()
         if smaps is None and data_loader.n_coils > 1:
@@ -127,7 +125,7 @@ def _reconstruct_cartesian(
         return final_images
 
     def _reconstruct_nufft(
-        self, data_loader: NonCartesianFrameDataLoader, sim_conf: SimConfig, slice_2d
+        self, data_loader: NonCartesianFrameDataLoader, sim_conf: SimConfig
     ) -> NDArray:
         """Reconstruct data with nufft method."""
         from mrinufft import get_operator
@@ -136,7 +134,7 @@ def _reconstruct_nufft(
         shape = data_loader.shape
         traj, kspace_data = data_loader.get_kspace_frame(0)
 
-        if slice_2d:
+        if data_loader.slice_2d:
             shape = data_loader.shape[:2]
             traj = traj.reshape(data_loader.n_shots, -1, traj.shape[-1])[0, :, :2]
 
@@ -165,7 +163,7 @@ def _reconstruct_nufft(
 
         for i in tqdm(range(data_loader.n_frames)):
             traj, data = data_loader.get_kspace_frame(i)
-            if slice_2d:
+            if data_loader.slice_2d:
                 nufft_operator.samples = traj.reshape(
                     data_loader.n_shots, -1, traj.shape[-1]
                 )[0, :, :2]