diff --git a/B_rework.ipynb b/B_rework.ipynb
index d7508d7..110c371 100644
--- a/B_rework.ipynb
+++ b/B_rework.ipynb
@@ -346,7 +346,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -374,12 +374,14 @@
     "\n",
     "sf_energy_found = ak.to_numpy(scifi_found[\"energy\"])\n",
     "sf_eph_found = ak.to_numpy(ak.sum(scifi_found[\"brem_photons_pe\"], axis=-1, keepdims=False))\n",
-    "sf_vtx_type_found = ak.to_numpy(scifi_found[\"endvtx_type\"])\n",
+    "sf_vtx_type_found = scifi_found[\"all_endvtx_types\"]\n",
+    "\n",
+    "\n",
     "brem_vtx_type_found = scifi_found[scifi_found[\"endvtx_type\"]==101]\n",
     "\n",
     "sf_energy_lost = ak.to_numpy(scifi_lost[\"energy\"])\n",
     "sf_eph_lost = ak.to_numpy(ak.sum(scifi_lost[\"brem_photons_pe\"], axis=-1, keepdims=False))\n",
-    "sf_vtx_type_lost = ak.to_numpy(scifi_lost[\"endvtx_type\"])\n",
+    "sf_vtx_type_lost = scifi_lost[\"all_endvtx_types\"]\n",
     "brem_vtx_type_lost = scifi_lost[scifi_lost[\"endvtx_type\"]==101]\n",
     "\n",
     "\n",
@@ -390,32 +392,48 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
      "data": {
+      "text/html": [
+       "<pre>[101,\n",
+       " 101,\n",
+       " 101,\n",
+       " 101,\n",
+       " 101,\n",
+       " 101,\n",
+       " 101,\n",
+       " 101,\n",
+       " 101,\n",
+       " 101,\n",
+       " 0]\n",
+       "------------------\n",
+       "type: 11 * float32</pre>"
+      ],
       "text/plain": [
-       "9056"
+       "<Array [101, 101, 101, 101, 101, ..., 101, 101, 101, 0] type='11 * float32'>"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "ak.num(scifi_found[\"energy\"], axis=0)\n",
-    "scifi_found[\"\"]"
+    "scifi_found[\"all_endvtx_types\"][1,:]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 48,
    "metadata": {},
    "outputs": [],
    "source": [
     "scifi_fitpars_found = ak.ArrayBuilder()\n",
+    "vtx_types_found = ak.ArrayBuilder()\n",
     "\n",
     "for i in range(0,ak.num(scifi_found, axis=0)):\n",
     "    popt, pcov = curve_fit(scifi_track,ak.to_numpy(scifi_z_found[i,:]),ak.to_numpy(scifi_x_found[i,:]))\n",
@@ -428,11 +446,16 @@
     "    scifi_fitpars_found.real(sf_energy_found[i])\n",
     "    #[:,5] -> photon energy\n",
     "    scifi_fitpars_found.real(sf_eph_found[i])\n",
-    "    #[:,6] -> endvtx_type\n",
-    "    scifi_fitpars_found.real(sf_vtx_type_found[i])\n",
     "    scifi_fitpars_found.end_list()\n",
+    "    \n",
+    "    vtx_types_found.begin_list()\n",
+    "    #[:,0] -> endvtx_type\n",
+    "    vtx_types_found.extend(sf_vtx_type_found[i,:])\n",
+    "    vtx_types_found.end_list()\n",
+    "    \n",
     "\n",
     "scifi_fitpars_lost = ak.ArrayBuilder()\n",
+    "vtx_types_lost = ak.ArrayBuilder()\n",
     "\n",
     "for i in range(0,ak.num(scifi_lost, axis=0)):\n",
     "    popt, pcov = curve_fit(scifi_track,ak.to_numpy(scifi_z_lost[i,:]),ak.to_numpy(scifi_x_lost[i,:]))\n",
@@ -445,37 +468,71 @@
     "    scifi_fitpars_lost.real(sf_energy_lost[i])\n",
     "    #[:,5] -> photon energy\n",
     "    scifi_fitpars_lost.real(sf_eph_lost[i])\n",
-    "    #[:,6] -> endvtx_type\n",
-    "    scifi_fitpars_lost.real(sf_vtx_type_lost[i])\n",
     "    scifi_fitpars_lost.end_list()\n",
+    "    \n",
+    "    vtx_types_lost.begin_list()\n",
+    "    #[:,6] -> endvtx_type\n",
+    "    vtx_types_lost.extend(sf_vtx_type_lost[i,:])\n",
+    "    vtx_types_lost.end_list()\n",
+    "    \n",
     "\n",
     "\n",
-    "scifi_fitpars_lost = scifi_fitpars_lost.to_numpy()\n",
-    "scifi_fitpars_found = scifi_fitpars_found.to_numpy()\n",
+    "scifi_fitpars_lost = ak.to_numpy(scifi_fitpars_lost)\n",
+    "scifi_fitpars_found = ak.to_numpy(scifi_fitpars_found)\n",
+    "\n",
+    "vtx_types_lost = ak.Array(vtx_types_lost)\n",
+    "vtx_types_found = ak.Array(vtx_types_found)\n",
     "\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 101,
+   "execution_count": 49,
    "metadata": {},
    "outputs": [
     {
      "data": {
+      "text/html": [
+       "<pre>[101,\n",
+       " 101,\n",
+       " 101,\n",
+       " 101,\n",
+       " 101,\n",
+       " 101,\n",
+       " 101,\n",
+       " 101,\n",
+       " 101,\n",
+       " 101,\n",
+       " 0]\n",
+       "------------------\n",
+       "type: 11 * float64</pre>"
+      ],
       "text/plain": [
-       "array(2)"
+       "<Array [101, 101, 101, 101, 101, ..., 101, 101, 101, 0] type='11 * float64'>"
       ]
      },
-     "execution_count": 101,
+     "execution_count": 49,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
-   "source": []
+   "source": [
+    "vtx_types_found[0]"
+   ]
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
    "metadata": {},
    "outputs": [
     {
@@ -502,8 +559,15 @@
     "brem_energy_lost = scifi_fitpars_lost[:,5]\n",
     "\n",
     "\n",
-    "vtx_type_found = scifi_fitpars_found[:,6]\n",
-    "vtx_type_lost = scifi_fitpars_lost[:,6]\n",
+    "bs_found, vtx_types_found = ak.broadcast_arrays(b_found, vtx_types_found)\n",
+    "bs_found = ak.to_numpy(ak.ravel(bs_found))\n",
+    "vtx_types_found = ak.to_numpy(ak.ravel(vtx_types_found))\n",
+    "\n",
+    "bs_lost, vtx_types_lost = ak.broadcast_arrays(b_lost, vtx_types_lost)\n",
+    "bs_lost = ak.to_numpy(ak.ravel(bs_lost))\n",
+    "vtx_types_lost = ak.to_numpy(ak.ravel(vtx_types_lost))\n",
+    "\n",
+    "\n",
     "\n",
     "\n",
     "#Erste Annahme ist Bremsstrahlung\n",
@@ -541,32 +605,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 52,
    "metadata": {},
    "outputs": [
     {
-     "data": {
-      "text/plain": [
-       "array([], dtype=float64)"
-      ]
-     },
-     "execution_count": 24,
-     "metadata": {},
-     "output_type": "execute_result"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.08902698999847938   101.0\n"
+     ]
     }
    ],
-   "source": [
-    "vtx_type_found[vtx_type_found!=0]"
-   ]
+   "source": []
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 55,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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       "text/plain": [
        "<Figure size 1800x600 with 3 Axes>"
       ]
@@ -578,12 +637,12 @@
    "source": [
     "fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(18,6))\n",
     "\n",
-    "a0=ax[0].hist2d(b_found, vtx_type_found, bins=50, cmap=plt.cm.jet, cmin=1)\n",
+    "a0=ax[0].hist2d(b_found, vtx_types_found, bins=100, cmap=plt.cm.jet, cmin=1)\n",
     "ax[0].set_xlabel(\"b\")\n",
     "ax[0].set_ylabel(\"endvtx id\")\n",
     "ax[0].set_title(\"found endvtx id wrt b parameter\")\n",
     "\n",
-    "a1=ax[1].hist2d(b_lost, vtx_type_lost, bins=50, cmap=plt.cm.jet, cmin=1) \n",
+    "a1=ax[1].hist2d(b_lost, vtx_types_lost, bins=100, cmap=plt.cm.jet, cmin=1) \n",
     "ax[1].set_xlabel(\"b\")\n",
     "ax[1].set_ylabel(\"endvtx id\")\n",
     "ax[1].set_title(\"lost endvtx id wrt b paraneter\")\n",
@@ -592,7 +651,7 @@
     "B:\n",
     "\n",
     "\"\"\"\n",
-    "fig.colorbar(a0[3], ax=ax.ravel().tolist(), orientation='vertical')\n",
+    "fig.colorbar(a0[3], ax=ax, orientation='vertical')\n",
     "plt.show()"
    ]
   },