{
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  {
   "cell_type": "markdown",
   "id": "48faa768",
   "metadata": {},
   "source": [
    "# Arithmetik\n",
    "\n",
    "Arrays ermöglichen euch, Stapeloperationen auf Daten durchzuführen ohne `for`-Schleifen verwenden zu müssen. Dies wird bei NumPy *Vektorisierung* genannt. Bei allen arithmetischen Operationen zwischen Arrays gleicher Größe wird die Operation elementweise angewendet:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "af888012",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-21T17:30:06.535439Z",
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     "shell.execute_reply": "2026-05-21T17:30:06.581778Z",
     "shell.execute_reply.started": "2026-05-21T17:30:06.535414Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.3377999 , 0.37343236, 0.61613397],\n",
       "       [0.71191857, 0.35041942, 0.64726029],\n",
       "       [0.06018761, 0.83997689, 0.31628701],\n",
       "       [0.14621145, 0.26867346, 0.07336511],\n",
       "       [0.22718287, 0.77538148, 0.40654442],\n",
       "       [0.44235763, 0.34000371, 0.53182733],\n",
       "       [0.98246577, 0.08442906, 0.33648811]])"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "\n",
    "rng = np.random.default_rng()\n",
    "data = rng.random((7, 3))\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a68ec8c7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-21T17:30:06.582816Z",
     "iopub.status.busy": "2026-05-21T17:30:06.582652Z",
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     "shell.execute_reply": "2026-05-21T17:30:06.585077Z",
     "shell.execute_reply.started": "2026-05-21T17:30:06.582805Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 2.96033241,  2.6778611 ,  1.62302363],\n",
       "       [ 1.40465503,  2.8537231 ,  1.5449735 ],\n",
       "       [16.6147153 ,  1.19050894,  3.1616853 ],\n",
       "       [ 6.8394097 ,  3.7219903 , 13.63045757],\n",
       "       [ 4.40174025,  1.28968776,  2.45975579],\n",
       "       [ 2.26061434,  2.94114442,  1.88030952],\n",
       "       [ 1.01784717, 11.84426242,  2.97187318]])"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1 / data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4f3ab385",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-21T17:30:06.586699Z",
     "iopub.status.busy": "2026-05-21T17:30:06.586424Z",
     "iopub.status.idle": "2026-05-21T17:30:06.590717Z",
     "shell.execute_reply": "2026-05-21T17:30:06.590381Z",
     "shell.execute_reply.started": "2026-05-21T17:30:06.586688Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.11410877, 0.13945173, 0.37962107],\n",
       "       [0.50682805, 0.12279377, 0.41894589],\n",
       "       [0.00362255, 0.70556118, 0.10003747],\n",
       "       [0.02137779, 0.07218543, 0.00538244],\n",
       "       [0.05161206, 0.60121644, 0.16527837],\n",
       "       [0.19568027, 0.11560252, 0.28284031],\n",
       "       [0.96523899, 0.00712827, 0.11322425]])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data**2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e4492ab",
   "metadata": {},
   "source": [
    "Vergleich zweier Arrays:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5520fe3b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-21T17:30:06.591247Z",
     "iopub.status.busy": "2026-05-21T17:30:06.591161Z",
     "iopub.status.idle": "2026-05-21T17:30:06.593677Z",
     "shell.execute_reply": "2026-05-21T17:30:06.593378Z",
     "shell.execute_reply.started": "2026-05-21T17:30:06.591240Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ True, False,  True],\n",
       "       [ True, False,  True],\n",
       "       [False,  True, False],\n",
       "       [False, False, False],\n",
       "       [ True,  True, False],\n",
       "       [ True, False,  True],\n",
       "       [ True, False, False]])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data2 = rng.random((7, 3))\n",
    "data > data2"
   ]
  }
 ],
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