motion tweaks.

src/conf/scenario2-image-motion.yaml

@@ -20,7 +20,7 @@ ignore_patterns:
 
 sim_params:
   sim_tr: 0.1
-  sim_time: 300
+  sim_time: 1
   shape: [-1,-1,-1] # shape will be determined with the bbox and the brainweb phantom.
   fov: [-1,-1,-1]
   n_coils: 8
@@ -41,11 +41,11 @@ handlers:
     bold_strength: 0.02
 
   motion-image:
-    ts_std_mm: [1.0, 1.0, 1.0]
-    rs_std_mm: [0.1, 0.1, 0.1]
+    ts_std_mms: [0.3, 0.1, 0.1]
+    rs_std_mms: [0.0115, 0.0277, 0.033]
 
   noise-gaussian:
-    snr: 30
+    snr: 1000
   acquisition-sos:
     shot_time_ms: 50
     acsz: 0.125
@@ -79,6 +79,7 @@ reconstructors:
   #   algorithm: otazo
 
 stats:
+  disabled: true
   contrast_name: block_on
 
 

src/snkf/cli/main.py

@@ -99,9 +99,14 @@ def main_app(cfg: ConfigSnakeFMRI) -> None:
         np.save(f"data_rec_{rec_str}.npy", data_test)
 
         logger.debug("Current simulation state: %s", sim)
-        with PerfLogger(logger, name="Analysis " + str(rec_str)):
-            zscore = contrast_zscore(data_test, sim, cfg.stats.contrast_name)
-            stats = get_scores(zscore, sim.roi)
+        if not cfg.stats.disabled:
+
+            with PerfLogger(logger, name="Analysis " + str(rec_str)):
+                zscore = contrast_zscore(data_test, sim, cfg.stats.contrast_name)
+                stats = get_scores(zscore, sim.roi)
+        else:
+            stats = {}
+            zscore = None
 
         np.save(f"data_zscore_{rec_str}.npy", zscore)
         results.append(

src/snkf/handlers/motion/image.py

@@ -42,27 +42,29 @@ class RandomMotionImageHandler(AbstractHandler):
 
     __handler_name__ = "motion-image"
 
-    ts_std_mm: tuple[float, float, float] = None
-    rs_std_mm: tuple[float, float, float] = None
+    ts_std_mms: tuple[float, float, float] | None = None
+    rs_std_mms: tuple[float, float, float] | None = None
 
-    motion_file: str = None
-    motion_file_tr: float = None
+    motion_file: str | None = None
+    motion_file_tr: float | None = None
 
     def __post_init__(self):
-        if (self.ts_std_mm is None or self.rs_std_mm is None) and (
+        super().__post_init__()
+        if (self.ts_std_mms is None or self.rs_std_mms is None) and (
             self.motion_file is None or self.motion_file_tr is None
         ):
             raise ValueError(
                 "At least one of ts_std_mm, rs_std_mm or motion_file must be provided."
             )
+        self._motion_data = None
         if self.motion_file is not None:
             # load the motion file
             self._motion_data = np.loadtxt(self.motion_file)
 
     def _handle(self, sim: SimData) -> SimData:
         n_frames = sim.data_acq.shape[0]
         # update the translation to be in voxel units
-        ts_std_pix = np.array(self.ts_std_mm) / np.array(sim.res_mm)
+        ts_std_pix = np.array(self.ts_std_mms) / np.array(sim.res_mm)
 
         if self._motion_data is not None:
             # resample the motion data to match the simulation framerate.
@@ -76,7 +78,7 @@ def _handle(self, sim: SimData) -> SimData:
             motion = motion_generator(
                 n_frames,
                 ts_std_pix,
-                self.rs_std_mm,
+                self.rs_std_mms,
                 sim.sim_tr,
                 sim.rng,
             )