Add nilearn/nibabel/scipy; add get_fmri and beta_std to HTTPDynaDiffLoader

Dockerfile

@@ -24,7 +24,10 @@ RUN pip install --no-cache-dir \
     google-genai \
     h5py \
     timm \
-    overcomplete
+    overcomplete \
+    nilearn \
+    nibabel \
+    scipy
 
 # ── Explorer code ─────────────────────────────────────────────────────────────
 COPY scripts/explorer/          /app/scripts/explorer/

scripts/dynadiff_loader.py

@@ -452,6 +452,7 @@ class HTTPDynaDiffLoader:
         self._status    = "loading"
         self._error     = ""
         self._n_samples = None
+        self._beta_std  = None
         self._lock      = threading.Lock()
         self._nsd_cache: dict[int, list[int]] = {}
 
@@ -473,6 +474,7 @@ class HTTPDynaDiffLoader:
                     self._status    = data.get("status", "ok")
                     self._error     = data.get("error",  "")
                     self._n_samples = data.get("n_samples")
+                    self._beta_std  = data.get("beta_std")
                 return
             except Exception:
                 _time.sleep(interval)
@@ -498,8 +500,22 @@ class HTTPDynaDiffLoader:
         with self._lock:
             return self._n_samples
 
+    @property
+    def beta_std(self):
+        with self._lock:
+            return self._beta_std
+
     # ── remote calls ──────────────────────────────────────────────────────────
 
+    def get_fmri(self, sample_idx: int) -> 'np.ndarray | None':
+        """Fetch raw fMRI (N_VOXELS,) float32 from the remote endpoint, or None."""
+        result = self._post("get_fmri", {"sample_idx": int(sample_idx)})
+        raw = result.get("fmri")
+        if raw is None:
+            return None
+        import base64 as _b64
+        return np.frombuffer(_b64.b64decode(raw), dtype=np.float32).copy()
+
     def sample_idxs_for_nsd_img(self, nsd_img_idx: int) -> list[int]:
         nsd_idx = int(nsd_img_idx)
         with self._lock: