update

1 files changed, 84 insertions, 83 deletions

diff --git a/experiment/analysis/analysis.ipynb b/experiment/analysis/analysis.ipynb
index 83a92c0..e7b93d6 100644
--- a/experiment/analysis/analysis.ipynb
+++ b/experiment/analysis/analysis.ipynb
@@ -33,7 +33,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "data_path = Path(\"/home/niclas/repos/uni/master_thesis/experiment/data\")\n",
+    "data_path = Path(\"/home/niclas/repos/uni/thesis/experiment/data\")\n",
     "\n",
     "procedures = [\"1\", \"2\", \"3\", \"4\", \"5\", \"6\", \"overall\"]\n"
    ]
@@ -47,7 +47,7 @@
     {
      "data": {
       "text/plain": [
-       "['random', 'fixed', 'blocked']"
+       "['random', 'blocked', 'fixed']"
       ]
      },
      "execution_count": 3,
@@ -128,13 +128,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 12,
    "id": "eb3f2e96-2246-4b08-a7d1-999161ab3fd3",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 1500x500 with 2 Axes>"
       ]
@@ -162,6 +162,7 @@
     "axes[1].set_xlabel(\"Block\")\n",
     "plt.ylabel(\"RTsum\")\n",
     "plt.legend()\n",
+    "fig.tight_layout()\n",
     "plt.savefig(\"RT.png\")\n",
     "plt.show()"
    ]
@@ -199,14 +200,14 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>vp12</th>\n",
-       "      <td>0.822222</td>\n",
-       "      <td>0.820000</td>\n",
+       "      <th>vp14</th>\n",
+       "      <td>0.982222</td>\n",
+       "      <td>0.986667</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>vp19</th>\n",
-       "      <td>0.966667</td>\n",
-       "      <td>0.800000</td>\n",
+       "      <th>vp18</th>\n",
+       "      <td>0.962222</td>\n",
+       "      <td>0.970000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>vp15</th>\n",
@@ -214,11 +215,6 @@
        "      <td>0.980000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>vp17</th>\n",
-       "      <td>0.911111</td>\n",
-       "      <td>0.960000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
        "      <th>vp20</th>\n",
        "      <td>0.906667</td>\n",
        "      <td>0.980000</td>\n",
@@ -229,24 +225,29 @@
        "      <td>0.943333</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>vp16</th>\n",
-       "      <td>0.957778</td>\n",
-       "      <td>0.926667</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
        "      <th>vp13</th>\n",
        "      <td>0.857778</td>\n",
        "      <td>0.946667</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>vp18</th>\n",
-       "      <td>0.962222</td>\n",
-       "      <td>0.970000</td>\n",
+       "      <th>vp17</th>\n",
+       "      <td>0.911111</td>\n",
+       "      <td>0.960000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>vp14</th>\n",
-       "      <td>0.982222</td>\n",
-       "      <td>0.986667</td>\n",
+       "      <th>vp12</th>\n",
+       "      <td>0.822222</td>\n",
+       "      <td>0.820000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>vp19</th>\n",
+       "      <td>0.966667</td>\n",
+       "      <td>0.800000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>vp16</th>\n",
+       "      <td>0.957778</td>\n",
+       "      <td>0.926667</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -254,16 +255,16 @@
       ],
       "text/plain": [
        "         train      test\n",
-       "vp12  0.822222  0.820000\n",
-       "vp19  0.966667  0.800000\n",
+       "vp14  0.982222  0.986667\n",
+       "vp18  0.962222  0.970000\n",
        "vp15  0.973333  0.980000\n",
-       "vp17  0.911111  0.960000\n",
        "vp20  0.906667  0.980000\n",
        "vp10  0.924444  0.943333\n",
-       "vp16  0.957778  0.926667\n",
        "vp13  0.857778  0.946667\n",
-       "vp18  0.962222  0.970000\n",
-       "vp14  0.982222  0.986667"
+       "vp17  0.911111  0.960000\n",
+       "vp12  0.822222  0.820000\n",
+       "vp19  0.966667  0.800000\n",
+       "vp16  0.957778  0.926667"
       ]
      },
      "execution_count": 10,
@@ -315,24 +316,24 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>vp12</th>\n",
+       "      <th>vp14</th>\n",
        "      <td>0.992</td>\n",
-       "      <td>0.592</td>\n",
-       "      <td>0.392</td>\n",
        "      <td>0.976</td>\n",
-       "      <td>0.960</td>\n",
-       "      <td>1.000</td>\n",
-       "      <td>0.016</td>\n",
+       "      <td>0.992</td>\n",
+       "      <td>0.976</td>\n",
+       "      <td>0.400</td>\n",
+       "      <td>0.600</td>\n",
+       "      <td>0.968</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>vp19</th>\n",
-       "      <td>1.000</td>\n",
-       "      <td>0.992</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>0.576</td>\n",
-       "      <td>0.992</td>\n",
-       "      <td>0.992</td>\n",
-       "      <td>0.848</td>\n",
+       "      <th>vp18</th>\n",
+       "      <td>0.976</td>\n",
+       "      <td>0.976</td>\n",
+       "      <td>0.960</td>\n",
+       "      <td>0.392</td>\n",
+       "      <td>0.600</td>\n",
+       "      <td>0.984</td>\n",
+       "      <td>0.904</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>vp15</th>\n",
@@ -345,16 +346,6 @@
        "      <td>0.928</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>vp17</th>\n",
-       "      <td>0.392</td>\n",
-       "      <td>0.968</td>\n",
-       "      <td>0.584</td>\n",
-       "      <td>1.000</td>\n",
-       "      <td>1.000</td>\n",
-       "      <td>0.992</td>\n",
-       "      <td>0.648</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
        "      <th>vp20</th>\n",
        "      <td>0.992</td>\n",
        "      <td>0.376</td>\n",
@@ -375,16 +366,6 @@
        "      <td>0.712</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>vp16</th>\n",
-       "      <td>0.976</td>\n",
-       "      <td>0.600</td>\n",
-       "      <td>0.376</td>\n",
-       "      <td>0.976</td>\n",
-       "      <td>0.992</td>\n",
-       "      <td>1.000</td>\n",
-       "      <td>0.752</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
        "      <th>vp13</th>\n",
        "      <td>0.384</td>\n",
        "      <td>0.960</td>\n",
@@ -395,24 +376,44 @@
        "      <td>0.568</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>vp18</th>\n",
-       "      <td>0.976</td>\n",
-       "      <td>0.976</td>\n",
-       "      <td>0.960</td>\n",
+       "      <th>vp17</th>\n",
        "      <td>0.392</td>\n",
-       "      <td>0.600</td>\n",
-       "      <td>0.984</td>\n",
-       "      <td>0.904</td>\n",
+       "      <td>0.968</td>\n",
+       "      <td>0.584</td>\n",
+       "      <td>1.000</td>\n",
+       "      <td>1.000</td>\n",
+       "      <td>0.992</td>\n",
+       "      <td>0.648</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>vp14</th>\n",
+       "      <th>vp12</th>\n",
        "      <td>0.992</td>\n",
+       "      <td>0.592</td>\n",
+       "      <td>0.392</td>\n",
        "      <td>0.976</td>\n",
+       "      <td>0.960</td>\n",
+       "      <td>1.000</td>\n",
+       "      <td>0.016</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>vp19</th>\n",
+       "      <td>1.000</td>\n",
        "      <td>0.992</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.576</td>\n",
+       "      <td>0.992</td>\n",
+       "      <td>0.992</td>\n",
+       "      <td>0.848</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>vp16</th>\n",
        "      <td>0.976</td>\n",
-       "      <td>0.400</td>\n",
        "      <td>0.600</td>\n",
-       "      <td>0.968</td>\n",
+       "      <td>0.376</td>\n",
+       "      <td>0.976</td>\n",
+       "      <td>0.992</td>\n",
+       "      <td>1.000</td>\n",
+       "      <td>0.752</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -420,16 +421,16 @@
       ],
       "text/plain": [
        "          1      2      3      4      5      6  overall\n",
-       "vp12  0.992  0.592  0.392  0.976  0.960  1.000    0.016\n",
-       "vp19  1.000  0.992  0.000  0.576  0.992  0.992    0.848\n",
+       "vp14  0.992  0.976  0.992  0.976  0.400  0.600    0.968\n",
+       "vp18  0.976  0.976  0.960  0.392  0.600  0.984    0.904\n",
        "vp15  0.992  0.992  0.960  0.392  0.592  1.000    0.928\n",
-       "vp17  0.392  0.968  0.584  1.000  1.000  0.992    0.648\n",
        "vp20  0.992  0.376  0.952  0.976  0.976  0.560    0.784\n",
        "vp10  0.968  0.360  0.592  0.984  0.984  0.992    0.712\n",
-       "vp16  0.976  0.600  0.376  0.976  0.992  1.000    0.752\n",
        "vp13  0.384  0.960  0.928  0.560  0.992  0.968    0.568\n",
-       "vp18  0.976  0.976  0.960  0.392  0.600  0.984    0.904\n",
-       "vp14  0.992  0.976  0.992  0.976  0.400  0.600    0.968"
+       "vp17  0.392  0.968  0.584  1.000  1.000  0.992    0.648\n",
+       "vp12  0.992  0.592  0.392  0.976  0.960  1.000    0.016\n",
+       "vp19  1.000  0.992  0.000  0.576  0.992  0.992    0.848\n",
+       "vp16  0.976  0.600  0.376  0.976  0.992  1.000    0.752"
       ]
      },
      "execution_count": 11,
@@ -475,7 +476,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.2"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,