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Merge pull request #536 from JoaquinAmatRodrigo/0.10.x
0.10.x
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,154 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 6, | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "name": "stdout", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "The autoreload extension is already loaded. To reload it, use:\n", | ||
| " %reload_ext autoreload\n" | ||
| ] | ||
| }, | ||
| { | ||
| "data": { | ||
| "text/plain": [ | ||
| "'/home/ubuntu/varios/skforecast'" | ||
| ] | ||
| }, | ||
| "execution_count": 6, | ||
| "metadata": {}, | ||
| "output_type": "execute_result" | ||
| } | ||
| ], | ||
| "source": [ | ||
| "%load_ext autoreload\n", | ||
| "%autoreload 2\n", | ||
| "import sys\n", | ||
| "from pathlib import Path\n", | ||
| "sys.path.insert(1, str(Path.cwd().parent))\n", | ||
| "str(Path.cwd().parent)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 7, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import numpy as np\n", | ||
| "import pandas as pd\n", | ||
| "from skforecast.preprocessing import TimeSeriesDifferentiator" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 8, | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "name": "stdout", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "y : [ 1. 4. 8. 10. 13. 22. 40. 46.]\n", | ||
| "diff 1: [nan 3. 4. 2. 3. 9. 18. 6.]\n", | ||
| "diff 2: [ nan nan 1. -2. 1. 6. 9. -12.]\n", | ||
| "diff 3: [ nan nan nan -3. 3. 5. 3. -21.]\n", | ||
| "last values y : [22. 40. 46.]\n", | ||
| "next window : [55. 70. 71.]\n", | ||
| "next window diff 1: [ 9. 15. 1.]\n", | ||
| "next window diff 2: [ 3. 6. -14.]\n", | ||
| "next window diff 3: [ 15. 3. -20.]\n" | ||
| ] | ||
| } | ||
| ], | ||
| "source": [ | ||
| "series = np.array([ 1, 4, 8, 10, 13, 22, 40, 46, 55, 70 , 71], dtype=float)\n", | ||
| "y = series[:-3]\n", | ||
| "y_diff_1 = np.diff(y, n=1, prepend=np.nan)\n", | ||
| "y_diff_2 = np.diff(y_diff_1, n=1, prepend=np.nan)\n", | ||
| "y_diff_3 = np.diff(y_diff_2, n=1, prepend=np.nan)\n", | ||
| "last_values_y = y[-3:]\n", | ||
| "next_window = series[-3:]\n", | ||
| "next_window_diff_1 = np.diff(series, n=1)[-3:]\n", | ||
| "next_window_diff_2 = np.diff(series, n=2)[-3:]\n", | ||
| "next_window_diff_3 = np.diff(series, n=3)[-3:]\n", | ||
| "\n", | ||
| "print(\"y : \", y)\n", | ||
| "print(\"diff 1: \", y_diff_1)\n", | ||
| "print(\"diff 2: \", y_diff_2)\n", | ||
| "print(\"diff 3: \", y_diff_3)\n", | ||
| "print(\"last values y : \", last_values_y)\n", | ||
| "print(\"next window : \", next_window)\n", | ||
| "print(\"next window diff 1: \", next_window_diff_1)\n", | ||
| "print(\"next window diff 2: \", next_window_diff_2)\n", | ||
| "print(\"next window diff 3: \", next_window_diff_3)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 9, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "diferentiatior_1 = TimeSeriesDifferentiator(order=1)\n", | ||
| "diferentiatior_2 = TimeSeriesDifferentiator(order=2)\n", | ||
| "diferentiatior_3 = TimeSeriesDifferentiator(order=3)\n", | ||
| "\n", | ||
| "y_diff_1_hat = diferentiatior_1.fit_transform(y)\n", | ||
| "y_diff_2_hat = diferentiatior_2.fit_transform(y)\n", | ||
| "y_diff_3_hat = diferentiatior_3.fit_transform(y)\n", | ||
| "\n", | ||
| "y_inverse_1 = diferentiatior_1.inverse_transform(y_diff_1_hat)\n", | ||
| "y_inverse_2 = diferentiatior_2.inverse_transform(y_diff_2_hat)\n", | ||
| "y_inverse_3 = diferentiatior_3.inverse_transform(y_diff_3_hat)\n", | ||
| "\n", | ||
| "next_window_inverse_1 = diferentiatior_1.inverse_transform_next_window(next_window_diff_1)\n", | ||
| "next_window_inverse_2 = diferentiatior_2.inverse_transform_next_window(next_window_diff_2)\n", | ||
| "next_window_inverse_3 = diferentiatior_3.inverse_transform_next_window(next_window_diff_3) \n", | ||
| "\n", | ||
| "np.testing.assert_array_equal(y_diff_1_hat, y_diff_1)\n", | ||
| "np.testing.assert_array_equal(y_diff_2_hat, y_diff_2)\n", | ||
| "np.testing.assert_array_equal(y_diff_3_hat, y_diff_3)\n", | ||
| "\n", | ||
| "np.testing.assert_array_equal(y_inverse_1, y)\n", | ||
| "np.testing.assert_array_equal(y_inverse_2, y)\n", | ||
| "np.testing.assert_array_equal(y_inverse_3, y)\n", | ||
| "\n", | ||
| "np.testing.assert_array_equal(next_window_inverse_1, next_window)\n", | ||
| "np.testing.assert_array_equal(next_window_inverse_2, next_window)\n", | ||
| "np.testing.assert_array_equal(next_window_inverse_3, next_window)" | ||
| ] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "skforecast_py10", | ||
| "language": "python", | ||
| "name": "python3" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 3 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython3", | ||
| "version": "3.11.4" | ||
| }, | ||
| "orig_nbformat": 4, | ||
| "vscode": { | ||
| "interpreter": { | ||
| "hash": "c78d62c1713fdacd99ef7c429003c7324b36fbb551fb8b6860a7ea73e9338235" | ||
| } | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 2 | ||
| } |
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