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    "# Import to be able to import python package from src\n",
    "import sys\n",
    "sys.path.insert(0, '../src')"
   ]
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      "The `LightGBM` module could not be imported. To enable LightGBM support in Darts, follow the detailed instructions in the installation guide: https://github.com/unit8co/darts/blob/master/INSTALL.md\n",
      "The `Prophet` module could not be imported. To enable Prophet support in Darts, follow the detailed instructions in the installation guide: https://github.com/unit8co/darts/blob/master/INSTALL.md\n"
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    "import ontime as on\n",
    "import pandas as pd"
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    "# Getting Started\n",
    "\n",
    "The library is divided in three parts : \n",
    "\n",
    "1. `core` for all basic features\n",
    "2. `module` for all features using core features. E.g. benchmarking, ml preprocessing, etc.\n",
    "3. `context` for all features related to the usage of onTime in an applied scenario"
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    "## `core` Features\n",
    "\n",
    "This is a low level API. Most objects and functions are accessible in the base object : \n",
    "    \n",
    "    ontime\n",
    "    ├── detectors\n",
    "    ├── generators\n",
    "    ├── Model\n",
    "    ├── plots\n",
    "    ├── processors\n",
    "    └── TimeSeries\n",
    "\n",
    "For instance : "
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       "</style><pre class='xr-text-repr-fallback'>&lt;TimeSeries (DataArray) (time: 5, component: 1, sample: 1)&gt;\n",
       "array([[[-1.37205979]],\n",
       "\n",
       "       [[-0.65182852]],\n",
       "\n",
       "       [[ 0.29932213]],\n",
       "\n",
       "       [[-0.94618418]],\n",
       "\n",
       "       [[-0.67047005]]])\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 2023-01-01 2023-01-02 ... 2023-01-05\n",
       "  * component  (component) object &#x27;random_walk&#x27;\n",
       "Dimensions without coordinates: sample\n",
       "Attributes:\n",
       "    static_covariates:  None\n",
       "    hierarchy:          None</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>TimeSeries (DataArray)</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 5</li><li><span class='xr-has-index'>component</span>: 1</li><li><span>sample</span>: 1</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-ba9522f2-524f-4870-8df9-eb0d0614d1a9' class='xr-array-in' type='checkbox' checked><label for='section-ba9522f2-524f-4870-8df9-eb0d0614d1a9' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>-1.372 -0.6518 0.2993 -0.9462 -0.6705</span></div><div class='xr-array-data'><pre>array([[[-1.37205979]],\n",
       "\n",
       "       [[-0.65182852]],\n",
       "\n",
       "       [[ 0.29932213]],\n",
       "\n",
       "       [[-0.94618418]],\n",
       "\n",
       "       [[-0.67047005]]])</pre></div></div></li><li class='xr-section-item'><input id='section-815d90c1-1a57-4a09-9d75-bb15918d7279' class='xr-section-summary-in' type='checkbox'  checked><label for='section-815d90c1-1a57-4a09-9d75-bb15918d7279' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2023-01-01 ... 2023-01-05</div><input id='attrs-67472ae5-4119-40a4-9360-f55828989f13' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-67472ae5-4119-40a4-9360-f55828989f13' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4ec16e45-f661-4c56-b556-5f692be423d5' class='xr-var-data-in' type='checkbox'><label for='data-4ec16e45-f661-4c56-b556-5f692be423d5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2023-01-01T00:00:00.000000000&#x27;, &#x27;2023-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-03T00:00:00.000000000&#x27;, &#x27;2023-01-04T00:00:00.000000000&#x27;,\n",
       "       &#x27;2023-01-05T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>component</span></div><div class='xr-var-dims'>(component)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;random_walk&#x27;</div><input id='attrs-60da1830-b873-40c8-8af7-0f694b427890' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-60da1830-b873-40c8-8af7-0f694b427890' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44accb6f-c973-44b1-8ffb-dd0c70558f47' class='xr-var-data-in' type='checkbox'><label for='data-44accb6f-c973-44b1-8ffb-dd0c70558f47' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;random_walk&#x27;], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fdeef670-72ec-4d48-aa20-19c0589bed0e' class='xr-section-summary-in' type='checkbox'  ><label for='section-fdeef670-72ec-4d48-aa20-19c0589bed0e' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4b4ba404-02a8-4208-a8bd-137ffd50e231' class='xr-index-data-in' type='checkbox'/><label for='index-4b4ba404-02a8-4208-a8bd-137ffd50e231' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2023-01-01&#x27;, &#x27;2023-01-02&#x27;, &#x27;2023-01-03&#x27;, &#x27;2023-01-04&#x27;,\n",
       "               &#x27;2023-01-05&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=&#x27;D&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>component</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-25196440-7c80-4392-ba4c-b30b290a72cd' class='xr-index-data-in' type='checkbox'/><label for='index-25196440-7c80-4392-ba4c-b30b290a72cd' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;random_walk&#x27;], dtype=&#x27;object&#x27;, name=&#x27;component&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5b0d82af-1baf-4b9a-b0dc-bccc0ef83a03' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5b0d82af-1baf-4b9a-b0dc-bccc0ef83a03' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>static_covariates :</span></dt><dd>None</dd><dt><span>hierarchy :</span></dt><dd>None</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<TimeSeries (DataArray) (time: 5, component: 1, sample: 1)>\n",
       "array([[[-1.37205979]],\n",
       "\n",
       "       [[-0.65182852]],\n",
       "\n",
       "       [[ 0.29932213]],\n",
       "\n",
       "       [[-0.94618418]],\n",
       "\n",
       "       [[-0.67047005]]])\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 2023-01-01 2023-01-02 ... 2023-01-05\n",
       "  * component  (component) object 'random_walk'\n",
       "Dimensions without coordinates: sample\n",
       "Attributes:\n",
       "    static_covariates:  None\n",
       "    hierarchy:          None"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts = on.generators.random_walk().generate(start=pd.Timestamp('01-01-2023'), end=pd.Timestamp('12-31-2023'))\n",
    "ts[0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6b9959a6-489a-4c80-a53e-e65cad57fe62",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-04-27T10:05:32.472025Z",
     "start_time": "2024-04-27T10:05:32.234524Z"
    },
    "papermill": {
     "duration": 0.181859,
     "end_time": "2024-01-31T17:49:10.093904",
     "exception": false,
     "start_time": "2024-01-31T17:49:09.912045",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ts.plot();"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2487b267-ec4a-49bc-9bda-33e4bc39194c",
   "metadata": {
    "papermill": {
     "duration": 0.004476,
     "end_time": "2024-01-31T17:49:10.107412",
     "exception": false,
     "start_time": "2024-01-31T17:49:10.102936",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## `module` and `context` features"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0904039a-4cb4-4795-9656-8c48a919dfee",
   "metadata": {
    "papermill": {
     "duration": 0.003459,
     "end_time": "2024-01-31T17:49:10.125625",
     "exception": false,
     "start_time": "2024-01-31T17:49:10.122166",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "High level API with various features. Let's load some data for an example :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4c906526-20c4-47b5-8023-8216c6af18d1",
   "metadata": {
    "papermill": {
     "duration": 0.095086,
     "end_time": "2024-01-31T17:49:10.252726",
     "exception": false,
     "start_time": "2024-01-31T17:49:10.157640",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "from darts.datasets import EnergyDataset\n",
    "ts = EnergyDataset().load()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "15724cb7-d0d6-40ab-a240-57df7e8f3c21",
   "metadata": {
    "papermill": {
     "duration": 0.017408,
     "end_time": "2024-01-31T17:49:10.273465",
     "exception": false,
     "start_time": "2024-01-31T17:49:10.256057",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "df = ts.pd_dataframe()\n",
    "df = df.interpolate()\n",
    "cols = ['generation biomass', 'generation solar', 'generation nuclear']\n",
    "df = df[cols]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "401cf66e-f0eb-48e0-ac7c-adf2bef92a3c",
   "metadata": {
    "papermill": {
     "duration": 0.007854,
     "end_time": "2024-01-31T17:49:10.284420",
     "exception": false,
     "start_time": "2024-01-31T17:49:10.276566",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "ts = on.TimeSeries.from_dataframe(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3013d9e8-d7cd-4caf-be3f-607eab84647e",
   "metadata": {
    "papermill": {
     "duration": 0.0091,
     "end_time": "2024-01-31T17:49:10.296540",
     "exception": false,
     "start_time": "2024-01-31T17:49:10.287440",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "ts_uni = ts['generation solar'].slice(pd.Timestamp('2015'), pd.Timestamp('2016'))\n",
    "ts_multi = ts.slice(pd.Timestamp('2015'), pd.Timestamp('2016'))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a1a81ffb-dca7-4ee5-93e9-836223ae6956",
   "metadata": {
    "papermill": {
     "duration": 0.003024,
     "end_time": "2024-01-31T17:49:10.302556",
     "exception": false,
     "start_time": "2024-01-31T17:49:10.299532",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### `module` Features"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "adb031b1-74bc-4ed2-ae54-bc16681f0363",
   "metadata": {
    "papermill": {
     "duration": 0.002959,
     "end_time": "2024-01-31T17:49:10.308461",
     "exception": false,
     "start_time": "2024-01-31T17:49:10.305502",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "High level API with features related to data processing, ML/AI, etc."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "79fd0990-dac4-461e-98b0-29f1e579b11a",
   "metadata": {
    "papermill": {
     "duration": 0.007087,
     "end_time": "2024-01-31T17:49:10.318529",
     "exception": false,
     "start_time": "2024-01-31T17:49:10.311442",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "train, test = on.module.processing.common.train_test_split(ts_uni, test_split=0.3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0641d9e6-c5b8-49a1-a3db-9df1927d62be",
   "metadata": {
    "papermill": {
     "duration": 0.003068,
     "end_time": "2024-01-31T17:49:10.324885",
     "exception": false,
     "start_time": "2024-01-31T17:49:10.321817",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### `context` Features"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2982c551-1607-40c8-911d-154a3493e4b1",
   "metadata": {
    "papermill": {
     "duration": 0.003102,
     "end_time": "2024-01-31T17:49:10.331104",
     "exception": false,
     "start_time": "2024-01-31T17:49:10.328002",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "High level API with features related to a physical machine or process."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f7fe172e-588a-4f7e-aa0e-1cdc07dd8aca",
   "metadata": {
    "papermill": {
     "duration": 0.002994,
     "end_time": "2024-01-31T17:49:10.337191",
     "exception": false,
     "start_time": "2024-01-31T17:49:10.334197",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "#### Profiler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "ad40696c-c5fa-4b5f-8f49-92c4fc0a9941",
   "metadata": {
    "papermill": {
     "duration": 0.005962,
     "end_time": "2024-01-31T17:49:10.346226",
     "exception": false,
     "start_time": "2024-01-31T17:49:10.340264",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "profiler = on.context.common.Profiler()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a304607-7ccb-4d2b-9796-dd80bce76b6c",
   "metadata": {
    "papermill": {
     "duration": 0.003121,
     "end_time": "2024-01-31T17:49:10.352586",
     "exception": false,
     "start_time": "2024-01-31T17:49:10.349465",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "What does the common week looks like ?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "bac9e224-c12a-4d7a-b7ca-db2a9acff278",
   "metadata": {
    "papermill": {
     "duration": 0.136216,
     "end_time": "2024-01-31T17:49:10.491926",
     "exception": false,
     "start_time": "2024-01-31T17:49:10.355710",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "week_mean = profiler.profile(ts_uni, profiler.Period.WEEKLY, profiler.Aggregation.MEAN)\n",
    "week_median = profiler.profile(ts_uni, profiler.Period.WEEKLY, profiler.Aggregation.MEDIAN)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e8474db3-5e1e-4d08-bdc1-30f88bfd5f28",
   "metadata": {
    "papermill": {
     "duration": 0.136824,
     "end_time": "2024-01-31T17:49:10.631997",
     "exception": false,
     "start_time": "2024-01-31T17:49:10.495173",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "week_mean.plot();\n",
    "week_median.plot();"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3abbc2e7-a631-40b0-878c-36a552f95dc8",
   "metadata": {
    "papermill": {
     "duration": 0.00339,
     "end_time": "2024-01-31T17:49:10.639004",
     "exception": false,
     "start_time": "2024-01-31T17:49:10.635614",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "#### Generic Predictor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c775b740-fe78-4c0c-87fe-a51af3d42993",
   "metadata": {
    "papermill": {
     "duration": 0.006444,
     "end_time": "2024-01-31T17:49:10.648812",
     "exception": false,
     "start_time": "2024-01-31T17:49:10.642368",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "model = on.context.common.GenericPredictor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "a633dce3-27d8-4deb-bb0f-d40e3af96f8a",
   "metadata": {
    "papermill": {
     "duration": 1.179973,
     "end_time": "2024-01-31T17:49:11.832154",
     "exception": false,
     "start_time": "2024-01-31T17:49:10.652181",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<ontime.context.common.generic_predictor.GenericPredictor at 0x2b9906ec0>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(train)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6943aa60-c757-4f54-bf63-854beecfab80",
   "metadata": {
    "papermill": {
     "duration": 0.003431,
     "end_time": "2024-01-31T17:49:11.839240",
     "exception": false,
     "start_time": "2024-01-31T17:49:11.835809",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "What does the future looks like ?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "04dfe189-f736-4fe3-b27c-467c154b2c42",
   "metadata": {
    "papermill": {
     "duration": 0.017863,
     "end_time": "2024-01-31T17:49:11.860424",
     "exception": false,
     "start_time": "2024-01-31T17:49:11.842561",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "pred = model.predict(48)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
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\"zindex\": 0, \"tickCount\": {\"signal\": \"ceil(height/40)\"}, \"orient\": \"left\", \"grid\": false, \"title\": \"value\", \"labelOverlap\": true}], \"style\": \"cell\", \"height\": 300, \"legends\": [{\"stroke\": \"color\", \"symbolType\": \"stroke\", \"title\": \"variable\", \"encode\": {\"symbols\": {\"update\": {\"opacity\": {\"value\": 1}}}}}], \"width\": 500, \"background\": \"white\", \"padding\": 5}, {\"mode\": \"vega\"});\n",
       "</script>"
      ],
      "text/plain": [
       "alt.Chart(...)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "on.plots.prediction(train[-96:], pred, test[:48])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dc965c95-1b5c-43e4-9c4b-57ff73c275c1",
   "metadata": {
    "papermill": {
     "duration": 0.003523,
     "end_time": "2024-01-31T17:49:11.996207",
     "exception": false,
     "start_time": "2024-01-31T17:49:11.992684",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Generic Detector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "9751b373-97d3-45e9-9969-2b4ba224f815",
   "metadata": {
    "papermill": {
     "duration": 0.006672,
     "end_time": "2024-01-31T17:49:12.006362",
     "exception": false,
     "start_time": "2024-01-31T17:49:11.999690",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "model = on.context.common.GenericDetector()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "89be0c48-0ab6-42b4-ab64-611b95d2a76f",
   "metadata": {
    "papermill": {
     "duration": 1.134506,
     "end_time": "2024-01-31T17:49:13.144278",
     "exception": false,
     "start_time": "2024-01-31T17:49:12.009772",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<ontime.context.common.generic_detector.GenericDetector at 0x2b98d03a0>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(train)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "06be738b-8bfd-4c95-8dec-ed52803e5ff9",
   "metadata": {
    "papermill": {
     "duration": 0.003534,
     "end_time": "2024-01-31T17:49:13.151717",
     "exception": false,
     "start_time": "2024-01-31T17:49:13.148183",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Does the current signal has problem ? "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "4650f34a-9cdb-4ea6-9dfe-2c66109b2627",
   "metadata": {
    "papermill": {
     "duration": 0.012201,
     "end_time": "2024-01-31T17:49:13.167405",
     "exception": false,
     "start_time": "2024-01-31T17:49:13.155204",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "detected_test = model.detect(test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "49e09caa-37f1-4201-b79a-4d1d65d86a8c",
   "metadata": {
    "papermill": {
     "duration": 0.03959,
     "end_time": "2024-01-31T17:49:13.210537",
     "exception": false,
     "start_time": "2024-01-31T17:49:13.170947",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
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      "text/plain": [
       "alt.LayerChart(...)"
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     "execution_count": 21,
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   "source": [
    "on.plots.anomalies(test[:72], detected_test[:72])"
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     "start_time": "2024-01-31T17:49:13.214280",
     "status": "completed"
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    "tags": []
   },
   "source": [
    "What if we want to have an idea about the future problems ?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "866533ed-bdab-4b29-bc91-50ed0043e84a",
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   "source": [
    "predetected = model.predetect(72)"
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