{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "52af59bb-083c-46c6-989a-bd4c65137a1a", "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# Import to be able to import python package from src\n", "import sys\n", "sys.path.insert(0, '../src')" ] }, { "cell_type": "code", "execution_count": 3, "id": "d6fc731f-3f50-4e9a-a24c-b2ab01d4fa31", "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "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" ] } ], "source": [ "import pandas as pd\n", "import numpy as np\n", "import ontime as on" ] }, { "cell_type": "markdown", "id": "670316b8-460c-4009-a5da-94278f4ac9a9", "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "completed" }, "tags": [] }, "source": [ "# Time Series\n", "\n", "a `TimeSeries` is the basic object in onTime. It is basically an extended version of Darts TimeSeries. Therefore, it is multivariate by default and all Darts methods can be used." ] }, { "cell_type": "markdown", "id": "831f1944-599b-4761-a071-2a682346610a", "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "completed" }, "tags": [] }, "source": [ "## Get some data\n", "\n", "Let's generate a random walk time series" ] }, { "cell_type": "code", "execution_count": 4, "id": "ef3e03e1-c247-4b5a-a27a-a13361e673b0", "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "ts = on.generators.random_walk().generate(start=pd.Timestamp('2022-01-01'), end=pd.Timestamp('2022-12-31'))" ] }, { "cell_type": "markdown", "id": "52f41907-8b48-4427-8a44-5f45ab6196b0", "metadata": {}, "source": [ "The TimeSeries can be sliced and its data structure is an xarray." ] }, { "cell_type": "code", "execution_count": 5, "id": "01962643-33af-4adf-8bfa-7d0163e4e41c", "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
<TimeSeries (DataArray) (time: 5, component: 1, sample: 1)>\n",
       "array([[[-0.36981256]],\n",
       "\n",
       "       [[-1.89552543]],\n",
       "\n",
       "       [[-3.58416814]],\n",
       "\n",
       "       [[-4.19590597]],\n",
       "\n",
       "       [[-3.08642833]]])\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 2022-01-01 2022-01-02 ... 2022-01-05\n",
       "  * component  (component) object 'random_walk'\n",
       "Dimensions without coordinates: sample\n",
       "Attributes:\n",
       "    static_covariates:  None\n",
       "    hierarchy:          None
" ], "text/plain": [ "\n", "array([[[-0.36981256]],\n", "\n", " [[-1.89552543]],\n", "\n", " [[-3.58416814]],\n", "\n", " [[-4.19590597]],\n", "\n", " [[-3.08642833]]])\n", "Coordinates:\n", " * time (time) datetime64[ns] 2022-01-01 2022-01-02 ... 2022-01-05\n", " * component (component) object 'random_walk'\n", "Dimensions without coordinates: sample\n", "Attributes:\n", " static_covariates: None\n", " hierarchy: None" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ts[0:5]" ] }, { "cell_type": "markdown", "id": "0cbd8da5-81fd-4b2d-8b7d-8394ad87348b", "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "completed" }, "tags": [] }, "source": [ "## Plot" ] }, { "cell_type": "markdown", "id": "0ec207a0-f270-4f1b-b362-0ad1c0584d2b", "metadata": {}, "source": [ "As expected, you can call the `plot()` methdod" ] }, { "cell_type": "code", "execution_count": 6, "id": 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", 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