Merge pull request #212 from jhlegarreta/enh/plot-gt-motion-pet-notebook

ENH: Plot ground truth motion in PET notebook

Author: jhlegarreta

docs/notebooks/pet_motion_estimation.ipynb

@@ -2480,19 +2480,19 @@
     "    motion_parameters.append([tx, ty, tz, rx, ry, rz])\n",
     "\n",
     "motion_parameters = np.array(motion_parameters)\n",
-    "fd = compute_fd(motion_parameters)\n",
+    "estimated_fd = compute_fd(motion_parameters)\n",
     "\n",
     "# Creating a DataFrame for better visualization\n",
     "df_motion = pd.DataFrame(\n",
     "    {\n",
-    "        \"Frame\": np.arange(len(fd)),\n",
+    "        \"Frame\": np.arange(len(estimated_fd)),\n",
     "        \"Translation X\": motion_parameters[:, 0],\n",
     "        \"Translation Y\": motion_parameters[:, 1],\n",
     "        \"Translation Z\": motion_parameters[:, 2],\n",
     "        \"Rotation X\": motion_parameters[:, 3],\n",
     "        \"Rotation Y\": motion_parameters[:, 4],\n",
     "        \"Rotation Z\": motion_parameters[:, 5],\n",
-    "        \"Framewise Displacement (mm)\": fd,\n",
+    "        \"Framewise Displacement (mm)\": estimated_fd,\n",
     "    }\n",
     ")"
    ]
@@ -2549,6 +2549,51 @@
     "plt.show()"
    ]
   },
+  {
+   "metadata": {},
+   "cell_type": "markdown",
+   "source": "For the dataset used in this example, we have access to the ground truth motion parameters that were used to corrupt the motion-free dataset. Let's now plot the ground truth motion to enable a visual comparison with the estimated motion.",
+   "id": "e3f45164598d16f0"
+  },
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "outputs": [],
+   "execution_count": null,
+   "source": [
+    "from nifreeze.viz.motion_viz import plot_volumewise_motion\n",
+    "\n",
+    "%matplotlib inline\n",
+    "\n",
+    "motion_gt_fname = (\n",
+    "    DATA_PATH\n",
+    "    / \"pet_data\"\n",
+    "    / \"sub-02\"\n",
+    "    / \"ses-baseline\"\n",
+    "    / \"pet\"\n",
+    "    / \"sub-02_ses-baseline_ground_truth_motion.csv\"\n",
+    ")\n",
+    "motion_gt_df = pd.read_csv(motion_gt_fname)\n",
+    "\n",
+    "frames = motion_gt_df[\"frame\"].to_numpy()\n",
+    "\n",
+    "# Construct motion_params array with shape (n_frames, 6): [trans_x, trans_y, trans_z, rot_x, rot_y, rot_z]\n",
+    "motion_cols = [\"trans_x\", \"trans_y\", \"trans_z\", \"rot_x\", \"rot_y\", \"rot_z\"]\n",
+    "motion_params = motion_gt_df[motion_cols].to_numpy()\n",
+    "\n",
+    "plot_volumewise_motion(frames, motion_params)\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ],
+   "id": "1009ea77e1bdd0ee"
+  },
+  {
+   "metadata": {},
+   "cell_type": "markdown",
+   "source": "Let's plot the estimated and the ground truth framewise displacement.",
+   "id": "113b4b4d1361b5ec"
+  },
   {
    "cell_type": "code",
    "execution_count": 18,
@@ -2565,9 +2610,10 @@
     }
    ],
    "source": [
-    "plt.figure(figsize=(18, 10))\n",
-    "sns.lineplot(x=\"Frame\", y=\"Framewise Displacement (mm)\", data=df_motion)\n",
-    "plt.title(\"Framewise Displacement (mm)\")\n",
+    "from nifreeze.viz.motion_viz import plot_framewise_displacement\n",
+    "\n",
+    "fd = pd.DataFrame({\"estimated\": estimated_fd, \"gt\": motion_gt_df[\"framewise_displacement\"].values})\n",
+    "plot_framewise_displacement(fd, labels=[\"Estimated\", \"Ground truth\"])\n",
     "\n",
     "plt.tight_layout()\n",
     "plt.show()"