diff --git a/docs/source/conf.py b/docs/source/conf.py index a1b76b493..84c69c6bf 100644 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -14,12 +14,11 @@ import os import sys +from typing import Any, Dict import sphinx_fontawesome # noqa: F401 from sphinx.ext.autodoc import between -from typing import Any, Dict - # sys.path.insert(0, os.path.abspath('.')) sys.path.insert(0, os.path.abspath("../..")) diff --git a/docs/source/how-to-guides/feature-guides/global_local_modeling.ipynb b/docs/source/how-to-guides/feature-guides/global_local_modeling.ipynb index c72f97803..a317a1f39 100644 --- a/docs/source/how-to-guides/feature-guides/global_local_modeling.ipynb +++ b/docs/source/how-to-guides/feature-guides/global_local_modeling.ipynb @@ -787,7 +787,7 @@ "source": [ "m = NeuralProphet(\n", " trend_global_local=\"local\",\n", - " season_global_local=\"local\",\n", + " season_global_localcal\",\n", " changepoints_range=0.8,\n", " epochs=20,\n", " trend_reg=5,\n", diff --git a/docs/source/how-to-guides/feature-guides/global_local_modeling_fut_regr.ipynb b/docs/source/how-to-guides/feature-guides/global_local_modeling_fut_regr.ipynb new file mode 100644 index 000000000..973a0455a --- /dev/null +++ b/docs/source/how-to-guides/feature-guides/global_local_modeling_fut_regr.ipynb @@ -0,0 +1,3795 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "try:\n", + " # it already installed dependencies\n", + " from torchsummary import summary\n", + " from torchviz import make_dot\n", + "except:\n", + " # install graphviz on system\n", + " import platform\n", + "\n", + " if \"Darwin\" == platform.system():\n", + " !brew install graphviz\n", + " elif \"Linux\" == platform.system():\n", + " !sudo apt install graphviz\n", + " else:\n", + " print(\"go to https://www.graphviz.org/download/\")\n", + " # Next we need to install the following dependencies:\n", + " !pip install torchsummary\n", + " !pip install torch-summary\n", + " !pip install torchviz\n", + " !pip install graphviz\n", + " # import\n", + " from torchsummary import summary\n", + " from torchviz import make_dot" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "if None:\n", + " print(2)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "Ywzhdfn2uqLf", + "outputId": "95decf15-d410-45c9-b703-91fd68891e7f" + }, + "outputs": [], + "source": [ + "if \"google.colab\" in str(get_ipython()):\n", + " !pip install git+https://github.com/ourownstory/neural_prophet.git # may take a while\n", + " #!pip install neuralprophet # much faster, but may not have the latest upgrades/bugfixes\n", + "\n", + "import pandas as pd\n", + "from neuralprophet import NeuralProphet, set_log_level\n", + "from neuralprophet import set_random_seed\n", + "\n", + "set_random_seed(10)\n", + "set_log_level(\"ERROR\", \"INFO\")" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ourownstory/neural_prophet/blob/main/tutorials/feature-use/global_local_modeling.ipynb)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "0Krto6fIvHit" + }, + "source": [ + "# Global Local Model\n", + "When fitting a single forecasting model with shared weights using a dataset composed of many time series, we can achieve what is known as a **global model**. It is specially useful in cases in which a single time series may not reflect the entire time series dynamics. In addition, global models provide better generalization and model size saving. In this notebook, we will build a global model using data from the hourly load of the ERCOT region.\n", + "\n", + "When many time series share only \"some behaviour\" we will need a **global local model**. In the following notebook we will see an example of time series sharing behaviour/weights on all the components except from the trend and seasonality. Therefore, we will also build a global local model using data from the hourly load of the ERCOT region.\n", + "\n", + "This notebook is an adaptation of `global_modeling.ipynb`." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "First, we load the data:" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 140 + }, + "id": "TvrgKVWIuxFJ", + "outputId": "99908203-2022-456a-9d05-73c3d0e6731e" + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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dsCOASTEASTFAR_WESTNORTHNORTH_CSOUTHERNSOUTH_CWEST
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" + ], + "text/plain": [ + " ds COAST EAST FAR_WEST NORTH NORTH_C SOUTHERN \\\n", + "0 2004-01-01 01:00:00 7225.09 877.79 1044.89 745.79 7124.21 1660.45 \n", + "1 2004-01-01 02:00:00 6994.25 850.75 1032.04 721.34 6854.58 1603.52 \n", + "2 2004-01-01 03:00:00 6717.42 831.63 1021.10 699.70 6639.48 1527.99 \n", + "3 2004-01-01 04:00:00 6554.27 823.56 1015.41 691.84 6492.39 1473.89 \n", + "4 2004-01-01 05:00:00 6511.19 823.38 1009.74 686.76 6452.26 1462.76 \n", + "\n", + " SOUTH_C WEST \n", + "0 3639.12 654.61 \n", + "1 3495.16 639.88 \n", + "2 3322.70 623.42 \n", + "3 3201.72 613.49 \n", + "4 3163.74 613.32 " + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data_location = \"https://raw.githubusercontent.com/ourownstory/neuralprophet-data/main/datasets/\"\n", + "df_ercot = pd.read_csv(data_location + \"multivariate/load_ercot_regions.csv\")\n", + "df_ercot.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We extract the name of the regions which will be later used in the model creation." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "regions = list(df_ercot)[1:]" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'2004-03-12 07:00:00'" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(set(df_ercot.ds))[0]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Global models can be enabled when the `df` input of the function has an additional column 'ID', which identifies the different time-series (besides the typical column 'ds', which has the timestamps, and column 'y', which contains the observed values of the time series). We select data from a three-year interval in our example (from 2004 to 2007)." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "df_global = pd.DataFrame()\n", + "for col in regions:\n", + " aux = df_ercot[[\"ds\", col]].copy(deep=True) # select column associated with region\n", + " aux = aux.iloc[:26301, :].copy(deep=True) # selects data up to 26301 row (2004 to 2007 time stamps)\n", + " aux = aux.rename(columns={col: \"y\"}) # rename column of data to 'y' which is compatible with Neural Prophet\n", + " aux[\"ID\"] = col\n", + " df_global = pd.concat((df_global, aux))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We will modify one time series trend and one time series seasonality" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING - (py.warnings._showwarnmsg) - /var/folders/g5/gjgtytcx0zb3tysnmlfdy0jr0000gn/T/ipykernel_81136/3315405602.py:5: FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError. Select only valid columns before calling the reduction.\n", + " + 2 * df_global[df_global[\"ID\"] == \"COAST\"].mean().y\n", + "\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 43, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import numpy as np\n", + "\n", + "df_global[\"y\"] = (\n", + " np.where(df_global[\"ID\"] == \"COAST\", -df_global[\"y\"], df_global[\"y\"])\n", + " + 2 * df_global[df_global[\"ID\"] == \"COAST\"].mean().y\n", + ")\n", + "# df_global[\"y\"] = np.where(df_global[\"ID\"] == \"NORTH\", df_global[\"y\"] + 0.1 * df_global.index, df_global[\"y\"])\n", + "\n", + "df_global[df_global[\"ID\"] == \"NORTH\"].plot()\n", + "df_global[df_global[\"ID\"] == \"COAST\"].plot()" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [], + "source": [ + "df_global[\"regressor_id\"] = (0.5 + np.random.rand(len(df_global))).astype(int) # df_global[\"y\"]\n", + "df_global[\"regressor_id1\"] = (0.5 + np.random.rand(len(df_global))).astype(int) # df_global[\"y\"]\n", + "\n", + "df_global[\"regressor_id2\"] = (0.5 + np.random.rand(len(df_global))).astype(int) # df_global[\"y\"]\n", + "df_global[\"regressor_id3\"] = df_global[\"y\"]\n", + "df_global[\"regressor_id4\"] = (0.1 + np.random.rand(len(df_global))).astype(int) # df_global[\"y\"]" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [], + "source": [ + "df_local = df_global[df_global[\"ID\"] == \"COAST\"]\n", + "df_local = df_local[[\"ds\", \"y\"]]" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [], + "source": [ + "df_local = df_global[df_global[\"ID\"] == \"COAST\"]\n", + "df_local = df_local[[\"ds\", \"y\"]]" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [], + "source": [ + "# import neuralprophet.configure as configure" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "# from dataclasses import dataclass, field\n", + "# from typing import Callable, List, Optional\n", + "# from typing import OrderedDict as OrderedDictType\n", + "# from typing import Type, Union\n", + "# from collections import OrderedDict\n", + "\n", + "# @dataclass\n", + "# class Regressor:\n", + "# reg_lambda: Optional[float]\n", + "# normalize: str\n", + "# mode: str\n", + "\n", + "# @dataclass\n", + "# class ConfigFutureRegressors:\n", + "# model: str\n", + "# regressors: OrderedDict = field(init=False) # contains SeasonConfig objects\n", + "\n", + "# def __post_init__(self):\n", + "# self.regressors = OrderedDictType[str, Regressor]" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + "# ConfigFutureRegressors(\n", + "# model='linear',\n", + "# ) # Opti" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "# m.config_regressors" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "m = NeuralProphet()\n", + "df_train, df_test = m.split_df(df_global, valid_p=0.33, local_split=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Global Modeling" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Remark:**\n", + "- Training a time series only with trend and seasonality components can result in poor performance. The following example is used just to show the new local modelling of multiple time series functionallity.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### DIFFERENT SEASONALITY MODELLING" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": {}, + "outputs": [], + "source": [ + "m = NeuralProphet(\n", + " # quantiles=[0.2, 0.6],\n", + " # trend_global_local=\"local\",\n", + " # season_global_local=\"local\",\n", + " growth=\"off\",\n", + " weekly_seasonality=False,\n", + " yearly_seasonality=False,\n", + " daily_seasonality=False,\n", + " # trend_local_reg=1.1,\n", + " # seasonality_local_reg=0.001,\n", + " # yearly_seasonality_glocal_mode=\"global\",\n", + " # changepoints_range=0.8,\n", + " # n_lags=2,\n", + " epochs=1,\n", + " # trend_reg=1,\n", + " future_regressors_model=\"neural_nets\",\n", + " # future_regressors_d_hidden=10,\n", + " # future_regressors_num_hidden_layers=3,\n", + " # quantiles=[0.1,0.9]\n", + " # drop_missing=True,\n", + " # future_regressors_model=\"neural_nets\",\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": {}, + "outputs": [], + "source": [ + "m = m.add_future_regressor(name=\"regressor_id\", mode=\"additive\")\n", + "m = m.add_future_regressor(name=\"regressor_id1\", mode=\"additive\")\n", + "\n", + "m = m.add_future_regressor(name=\"regressor_id2\", mode=\"multiplicative\")\n", + "m = m.add_future_regressor(name=\"regressor_id3\", mode=\"multiplicative\")\n", + "\n", + "m = m.add_future_regressor(name=\"regressor_id4\", mode=\"multiplicative\")" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [ + { + "data": { + "application/json": { + "ascii": false, + "bar_format": null, + "colour": null, + "elapsed": 0.03169679641723633, + "initial": 0, + "n": 0, + "ncols": null, + "nrows": 14, + "postfix": null, + "prefix": "Finding best initial lr", + "rate": null, + "total": 283, + "unit": "it", + "unit_divisor": 1000, + "unit_scale": false + }, + "application/vnd.jupyter.widget-view+json": { + "model_id": "33f41780b5f04bae8a3c2069b5a1816e", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Finding best initial lr: 0%| | 0/283 [00:00┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n", + "┃ Test metric ┃ DataLoader 0 ┃\n", + "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n", + "│ Loss_test │ 0.032875239849090576 │\n", + "│ RegLoss_test │ 0.0 │\n", + "└───────────────────────────┴───────────────────────────┘\n", + "\n" + ], + "text/plain": [ + "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n", + "┃\u001b[1m \u001b[0m\u001b[1m Test metric \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m DataLoader 0 \u001b[0m\u001b[1m \u001b[0m┃\n", + "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n", + "│\u001b[36m \u001b[0m\u001b[36m Loss_test \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m 0.032875239849090576 \u001b[0m\u001b[35m \u001b[0m│\n", + "│\u001b[36m \u001b[0m\u001b[36m RegLoss_test \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m 0.0 \u001b[0m\u001b[35m \u001b[0m│\n", + "└───────────────────────────┴───────────────────────────┘\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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a/docs/source/how-to-guides/feature-guides/glocal_trend.ipynb b/docs/source/how-to-guides/feature-guides/glocal_trend.ipynb new file mode 100644 index 000000000..df05a5d4e --- /dev/null +++ b/docs/source/how-to-guides/feature-guides/glocal_trend.ipynb @@ -0,0 +1,1728 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "try:\n", + " # it already installed dependencies\n", + " from torchsummary import summary\n", + " from torchviz import make_dot\n", + "except:\n", + " # install graphviz on system\n", + " import platform\n", + "\n", + " if \"Darwin\" == platform.system():\n", + " !brew install graphviz\n", + " elif \"Linux\" == platform.system():\n", + " !sudo apt install graphviz\n", + " else:\n", + " print(\"go to https://www.graphviz.org/download/\")\n", + " # Next we need to install the following dependencies:\n", + " !pip install torchsummary\n", + " !pip install torch-summary\n", + " !pip install torchviz\n", + " !pip install graphviz\n", + " # import\n", + " from torchsummary import summary\n", + " from torchviz import make_dot" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ourownstory/neural_prophet/blob/main/tutorials/feature-use/global_local_modeling.ipynb)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "0Krto6fIvHit" + }, + "source": [ + "# Global Local Model\n", + "When fitting a single forecasting model with shared weights using a dataset composed of many time series, we can achieve what is known as a **global model**. It is specially useful in cases in which a single time series may not reflect the entire time series dynamics. In addition, global models provide better generalization and model size saving. In this notebook, we will build a global model using data from the hourly load of the ERCOT region.\n", + "\n", + "When many time series share only \"some behaviour\" we will need a **global local model**. In the following notebook we will see an example of time series sharing behaviour/weights on all the components except from the trend and seasonality. Therefore, we will also build a global local model using data from the hourly load of the ERCOT region.\n", + "\n", + "This notebook is an adaptation of `global_modeling.ipynb`." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "First, we load the data:" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "Ywzhdfn2uqLf", + "outputId": "95decf15-d410-45c9-b703-91fd68891e7f" + }, + "outputs": [], + "source": [ + "if \"google.colab\" in str(get_ipython()):\n", + " !pip install git+https://github.com/ourownstory/neural_prophet.git # may take a while\n", + " #!pip install neuralprophet # much faster, but may not have the latest upgrades/bugfixes\n", + "\n", + "import pandas as pd\n", + "from neuralprophet import NeuralProphet, set_log_level\n", + "from neuralprophet import set_random_seed\n", + "\n", + "set_random_seed(10)\n", + "set_log_level(\"ERROR\", \"INFO\")" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 140 + }, + "id": "TvrgKVWIuxFJ", + "outputId": "99908203-2022-456a-9d05-73c3d0e6731e" + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " ds COAST EAST FAR_WEST NORTH NORTH_C SOUTHERN \\\n", + "0 2004-01-01 01:00:00 7225.09 877.79 1044.89 745.79 7124.21 1660.45 \n", + "1 2004-01-01 02:00:00 6994.25 850.75 1032.04 721.34 6854.58 1603.52 \n", + "2 2004-01-01 03:00:00 6717.42 831.63 1021.10 699.70 6639.48 1527.99 \n", + "3 2004-01-01 04:00:00 6554.27 823.56 1015.41 691.84 6492.39 1473.89 \n", + "4 2004-01-01 05:00:00 6511.19 823.38 1009.74 686.76 6452.26 1462.76 \n", + "\n", + " SOUTH_C WEST \n", + "0 3639.12 654.61 \n", + "1 3495.16 639.88 \n", + "2 3322.70 623.42 \n", + "3 3201.72 613.49 \n", + "4 3163.74 613.32 " + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data_location = \"https://raw.githubusercontent.com/ourownstory/neuralprophet-data/main/datasets/\"\n", + "df_ercot = pd.read_csv(data_location + \"multivariate/load_ercot_regions.csv\")\n", + "df_ercot.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We extract the name of the regions which will be later used in the model creation." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "regions = list(df_ercot)[1:]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Global models can be enabled when the `df` input of the function has an additional column 'ID', which identifies the different time-series (besides the typical column 'ds', which has the timestamps, and column 'y', which contains the observed values of the time series). We select data from a three-year interval in our example (from 2004 to 2007)." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "df_global = pd.DataFrame()\n", + "for col in regions:\n", + " aux = df_ercot[[\"ds\", col]].copy(deep=True) # select column associated with region\n", + " aux = aux.iloc[:26301, :].copy(deep=True) # selects data up to 26301 row (2004 to 2007 time stamps)\n", + " aux = aux.rename(columns={col: \"y\"}) # rename column of data to 'y' which is compatible with Neural Prophet\n", + " aux[\"ID\"] = col\n", + " df_global = pd.concat((df_global, aux))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We will modify one time series trend and one time series seasonality" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING - (py.warnings._showwarnmsg) - /var/folders/g5/gjgtytcx0zb3tysnmlfdy0jr0000gn/T/ipykernel_12635/3026129503.py:5: FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError. Select only valid columns before calling the reduction.\n", + " + 2 * df_global[df_global[\"ID\"] == \"COAST\"].mean().y\n", + "\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import numpy as np\n", + "\n", + "df_global[\"y\"] = (\n", + " np.where(df_global[\"ID\"] == \"COAST\", -df_global[\"y\"], df_global[\"y\"])\n", + " + 2 * df_global[df_global[\"ID\"] == \"COAST\"].mean().y\n", + ")\n", + "df_global[\"y\"] = np.where(df_global[\"ID\"] == \"NORTH\", df_global[\"y\"] + 0.1 * df_global.index, df_global[\"y\"])\n", + "\n", + "df_global[df_global[\"ID\"] == \"NORTH\"].plot()\n", + "df_global[df_global[\"ID\"] == \"COAST\"].plot()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "df_local = df_global[df_global[\"ID\"] == \"COAST\"]\n", + "df_local = df_local[[\"ds\", \"y\"]]" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "m = NeuralProphet()\n", + "df_train, df_test = m.split_df(df_global, valid_p=0.33, local_split=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Global Modeling" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Remark:**\n", + "- Training a time series only with trend and seasonality components can result in poor performance. The following example is used just to show the new local modelling of multiple time series functionallity.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### DIFFERENT SEASONALITY MODELLING" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [], + "source": [ + "m = NeuralProphet(\n", + " trend_global_local=\"global\",\n", + " season_global_local=\"local\",\n", + " yearly_seasonality_glocal_mode=\"global\",\n", + " changepoints_range=0.8,\n", + " epochs=1,\n", + " trend_reg=5,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "m.add_seasonality(period=30, name=\"monthly\", fourier_order=8)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "When a pd.DataFrame with an 'ID' column is the input for the `split_df` function, train and validation data are provided in a similar format. For global models, the input data is typically split according to a fraction of the time encompassing all time series (default when there is more than one 'ID' and when `local_split=False`). If the user wants to split each time series locally, the `local_split` parameter must be set to True. In this example, we will split our data into train and test (with a 33% test proportion - 2 years train and 1 year test)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "After creating an object of the `NeuralProphet`, a model can be created by calling the `fit` function." + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 148, + "referenced_widgets": [ + "4ac0917121f8498698e087259b787dcf", + "94108fe9090f47c7ba2216479e0d3fac", + "2d8235496ec642af8192f52d9f2692b1", + "c94a8ae41b994c55a96ad44806b0f1c7", + "24bf564f55644476911a6cf004a395e7", + "87c170d1e00742a29e7f797e98c49cc2", + "8a192ccc35e94e9f8be85898ed583e2c", + "9467345334da47a8beadc770feef952a", + "dc468cd35d2b4f0e8eb287689ac15412", + "f35fc9cbd82c4187a4cdc08c3ac26998", + "aab682cd3df24821a80331720f7c24e5" + ] + }, + "id": "s7faUgnrvGFN", + "outputId": "50da2450-767f-4e3b-f03d-d03226d24ff8" + }, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "d212e6377ec24967bb7815570c6a1d60", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Finding best initial lr: 0%| | 0/278 [00:00" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = m.plot(forecast[forecast[\"ID\"] == \"NORTH\"])\n", + "fig_param = m.plot_parameters(df_name=\"NORTH\")" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = m.plot(forecast[forecast[\"ID\"] == \"COAST\"])\n", + "fig_param = m.plot_parameters(df_name=\"COAST\")" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", 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Loss_testRegLoss_test
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" + ], + "text/plain": [ + " Loss_test RegLoss_test\n", + "0 0.043408 0.0" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "test_metrics_global = m.test(df_test)\n", + "test_metrics_global" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### GLOCAL TREND " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We will repeat the process above, but for local modelling of trend and seasonality." + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [], + "source": [ + "m = NeuralProphet(\n", + " trend_global_local=\"local\",\n", + " # season_global_localcal\",\n", + " trend_local_reg=3,\n", + " changepoints_range=0.8,\n", + " epochs=2,\n", + " trend_reg=1,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "ef80cc96f3c041e7a1ccc1de29b3e47c", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Finding best initial lr: 0%| | 0/278 [00:00" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = m.plot(forecast[forecast[\"ID\"] == \"NORTH\"])\n", + "fig_param = m.plot_parameters(df_name=\"NORTH\")" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = m.plot(forecast[forecast[\"ID\"] == \"COAST\"])\n", + "fig_param = m.plot_parameters(df_name=\"COAST\")" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = m.plot(forecast[forecast[\"ID\"] == \"EAST\"])\n", + "fig_param = m.plot_parameters(df_name=\"EAST\")" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "396ae7d4b6de455caf0d89ca81c939ae", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Testing: 0it [00:00, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
+       "┃        Test metric        ┃       DataLoader 0        ┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
+       "│         Loss_test         │    0.04433564841747284    │\n",
+       "│       RegLoss_test        │            0.0            │\n",
+       "└───────────────────────────┴───────────────────────────┘\n",
+       "
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Loss_testRegLoss_test
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" + ], + "text/plain": [ + " Loss_test RegLoss_test\n", + "0 0.044336 0.0" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "test_metrics_local = m.test(df_test)\n", + "test_metrics_local" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "ename": "ValueError", + "evalue": "Invalid frequency: NaT", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", + "Input \u001b[0;32mIn [27]\u001b[0m, in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m future \u001b[38;5;241m=\u001b[39m m\u001b[38;5;241m.\u001b[39mmake_future_dataframe(df_test)\n\u001b[0;32m----> 2\u001b[0m forecast \u001b[38;5;241m=\u001b[39m \u001b[43mm\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpredict\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfuture\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3\u001b[0m metrics \u001b[38;5;241m=\u001b[39m m\u001b[38;5;241m.\u001b[39mtest(df_test)\n\u001b[1;32m 4\u001b[0m forecast_trend \u001b[38;5;241m=\u001b[39m m\u001b[38;5;241m.\u001b[39mpredict_trend(df_test)\n", + "File \u001b[0;32m~/Desktop/code/neural_prophet/neuralprophet/forecaster.py:831\u001b[0m, in \u001b[0;36mNeuralProphet.predict\u001b[0;34m(self, df, decompose, raw)\u001b[0m\n\u001b[1;32m 829\u001b[0m df, received_ID_col, received_single_time_series, _ \u001b[38;5;241m=\u001b[39m df_utils\u001b[38;5;241m.\u001b[39mprep_or_copy_df(df)\n\u001b[1;32m 830\u001b[0m \u001b[38;5;66;03m# to get all forecasteable values with df given, maybe extend into future:\u001b[39;00m\n\u001b[0;32m--> 831\u001b[0m df, periods_added \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_maybe_extend_df\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdf\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 832\u001b[0m df \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_prepare_dataframe_to_predict(df)\n\u001b[1;32m 833\u001b[0m \u001b[38;5;66;03m# normalize\u001b[39;00m\n", + "File \u001b[0;32m~/Desktop/code/neural_prophet/neuralprophet/forecaster.py:2773\u001b[0m, in \u001b[0;36mNeuralProphet._maybe_extend_df\u001b[0;34m(self, df)\u001b[0m\n\u001b[1;32m 2771\u001b[0m extended_df \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mDataFrame()\n\u001b[1;32m 2772\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m df_name, df_i \u001b[38;5;129;01min\u001b[39;00m df\u001b[38;5;241m.\u001b[39mgroupby(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mID\u001b[39m\u001b[38;5;124m\"\u001b[39m):\n\u001b[0;32m-> 2773\u001b[0m _ \u001b[38;5;241m=\u001b[39m \u001b[43mdf_utils\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minfer_frequency\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdf_i\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mn_lags\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmax_lags\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfreq\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdata_freq\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2774\u001b[0m \u001b[38;5;66;03m# to get all forecasteable values with df given, maybe extend into future:\u001b[39;00m\n\u001b[1;32m 2775\u001b[0m periods_add[df_name] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_get_maybe_extend_periods(df_i)\n", + "File \u001b[0;32m~/Desktop/code/neural_prophet/neuralprophet/df_utils.py:1324\u001b[0m, in \u001b[0;36minfer_frequency\u001b[0;34m(df, freq, n_lags, min_freq_percentage)\u001b[0m\n\u001b[1;32m 1322\u001b[0m freq_df \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m()\n\u001b[1;32m 1323\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m df_name, df_i \u001b[38;5;129;01min\u001b[39;00m df\u001b[38;5;241m.\u001b[39mgroupby(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mID\u001b[39m\u001b[38;5;124m\"\u001b[39m):\n\u001b[0;32m-> 1324\u001b[0m freq_df\u001b[38;5;241m.\u001b[39mappend(\u001b[43m_infer_frequency\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdf_i\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfreq\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmin_freq_percentage\u001b[49m\u001b[43m)\u001b[49m)\n\u001b[1;32m 1325\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(\u001b[38;5;28mset\u001b[39m(freq_df)) \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m1\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m n_lags \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m 1326\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 1327\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mOne or more dataframes present different major frequencies, please make sure all dataframes present the same major frequency for auto-regression\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 1328\u001b[0m )\n", + "File \u001b[0;32m~/Desktop/code/neural_prophet/neuralprophet/df_utils.py:1252\u001b[0m, in \u001b[0;36m_infer_frequency\u001b[0;34m(df, freq, min_freq_percentage)\u001b[0m\n\u001b[1;32m 1250\u001b[0m dominant_freq_percentage \u001b[38;5;241m=\u001b[39m distribution\u001b[38;5;241m.\u001b[39mmax() \u001b[38;5;241m/\u001b[39m \u001b[38;5;28mlen\u001b[39m(df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mds\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n\u001b[1;32m 1251\u001b[0m num_freq \u001b[38;5;241m=\u001b[39m frequencies[np\u001b[38;5;241m.\u001b[39margmax(distribution)] \u001b[38;5;66;03m# get value of most common diff\u001b[39;00m\n\u001b[0;32m-> 1252\u001b[0m inferred_freq \u001b[38;5;241m=\u001b[39m \u001b[43mconvert_num_to_str_freq\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnum_freq\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdf\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mds\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43miloc\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1254\u001b[0m log\u001b[38;5;241m.\u001b[39minfo(\n\u001b[1;32m 1255\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMajor frequency \u001b[39m\u001b[38;5;132;01m{\u001b[39;00minferred_freq\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m corresponds to \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnp\u001b[38;5;241m.\u001b[39mround(dominant_freq_percentage \u001b[38;5;241m*\u001b[39m \u001b[38;5;241m100\u001b[39m, \u001b[38;5;241m3\u001b[39m)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m% of the data.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 1256\u001b[0m )\n\u001b[1;32m 1257\u001b[0m ideal_freq_exists \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m \u001b[38;5;28;01mif\u001b[39;00m dominant_freq_percentage \u001b[38;5;241m>\u001b[39m\u001b[38;5;241m=\u001b[39m min_freq_percentage \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;01mFalse\u001b[39;00m\n", + "File \u001b[0;32m~/Desktop/code/neural_prophet/neuralprophet/df_utils.py:1159\u001b[0m, in \u001b[0;36mconvert_num_to_str_freq\u001b[0;34m(freq_num, initial_time_stamp)\u001b[0m\n\u001b[1;32m 1144\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mconvert_num_to_str_freq\u001b[39m(freq_num, initial_time_stamp):\n\u001b[1;32m 1145\u001b[0m \u001b[38;5;124;03m\"\"\"Convert numeric frequencies into frequency tags\u001b[39;00m\n\u001b[1;32m 1146\u001b[0m \n\u001b[1;32m 1147\u001b[0m \u001b[38;5;124;03m Parameters\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1157\u001b[0m \u001b[38;5;124;03m frequency tag\u001b[39;00m\n\u001b[1;32m 1158\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m-> 1159\u001b[0m aux_ts \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdate_range\u001b[49m\u001b[43m(\u001b[49m\u001b[43minitial_time_stamp\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mperiods\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m100\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfreq\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto_timedelta\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfreq_num\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1160\u001b[0m freq_str \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39minfer_freq(aux_ts)\n\u001b[1;32m 1161\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m freq_str\n", + "File \u001b[0;32m~/Desktop/code/neural_prophet/env/lib/python3.8/site-packages/pandas/core/indexes/datetimes.py:1070\u001b[0m, in \u001b[0;36mdate_range\u001b[0;34m(start, end, periods, freq, tz, normalize, name, closed, inclusive, **kwargs)\u001b[0m\n\u001b[1;32m 1067\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m freq \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m com\u001b[38;5;241m.\u001b[39many_none(periods, start, end):\n\u001b[1;32m 1068\u001b[0m freq \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mD\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m-> 1070\u001b[0m dtarr \u001b[38;5;241m=\u001b[39m \u001b[43mDatetimeArray\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_generate_range\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1071\u001b[0m \u001b[43m \u001b[49m\u001b[43mstart\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstart\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1072\u001b[0m \u001b[43m \u001b[49m\u001b[43mend\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mend\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1073\u001b[0m \u001b[43m \u001b[49m\u001b[43mperiods\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mperiods\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1074\u001b[0m \u001b[43m \u001b[49m\u001b[43mfreq\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfreq\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1075\u001b[0m \u001b[43m \u001b[49m\u001b[43mtz\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtz\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1076\u001b[0m \u001b[43m \u001b[49m\u001b[43mnormalize\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnormalize\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1077\u001b[0m \u001b[43m \u001b[49m\u001b[43minclusive\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minclusive\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1078\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1079\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1080\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m DatetimeIndex\u001b[38;5;241m.\u001b[39m_simple_new(dtarr, name\u001b[38;5;241m=\u001b[39mname)\n", + "File \u001b[0;32m~/Desktop/code/neural_prophet/env/lib/python3.8/site-packages/pandas/core/arrays/datetimes.py:409\u001b[0m, in \u001b[0;36mDatetimeArray._generate_range\u001b[0;34m(cls, start, end, periods, freq, tz, normalize, ambiguous, nonexistent, inclusive)\u001b[0m\n\u001b[1;32m 404\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m com\u001b[38;5;241m.\u001b[39mcount_not_none(start, end, periods, freq) \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m3\u001b[39m:\n\u001b[1;32m 405\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 406\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mOf the four parameters: start, end, periods, \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 407\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mand freq, exactly three must be specified\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 408\u001b[0m )\n\u001b[0;32m--> 409\u001b[0m freq \u001b[38;5;241m=\u001b[39m \u001b[43mto_offset\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfreq\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 411\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m start \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 412\u001b[0m start \u001b[38;5;241m=\u001b[39m Timestamp(start)\n", + "File \u001b[0;32mpandas/_libs/tslibs/offsets.pyx:3580\u001b[0m, in \u001b[0;36mpandas._libs.tslibs.offsets.to_offset\u001b[0;34m()\u001b[0m\n", + "File \u001b[0;32mpandas/_libs/tslibs/offsets.pyx:3682\u001b[0m, in \u001b[0;36mpandas._libs.tslibs.offsets.to_offset\u001b[0;34m()\u001b[0m\n", + "\u001b[0;31mValueError\u001b[0m: Invalid frequency: NaT" + ] + } + ], + "source": [ + "future = m.make_future_dataframe(df_test)\n", + "forecast = m.predict(future)\n", + "metrics = m.test(df_test)\n", + "forecast_trend = m.predict_trend(df_test)\n", + "forecast_seasonal_componets = m.predict_seasonal_components(df_test)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "fig = make_dot(m.model.train_epoch_prediction, params=dict(m.model.named_parameters()))\n", + "# fig_glob.render(filename='img/fig_glob')\n", + "display(fig)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + 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")\n", "m.set_plotting_backend(\"plotly-static\")\n", "metrics = m.fit(df, freq=\"H\")\n", diff --git a/neuralprophet/components/future_regressors/linear.py b/neuralprophet/components/future_regressors/linear.py index e8434384c..dbf9dd0ff 100644 --- a/neuralprophet/components/future_regressors/linear.py +++ b/neuralprophet/components/future_regressors/linear.py @@ -1,6 +1,7 @@ import torch import torch.nn as nn +from neuralprophet import utils from neuralprophet.components.future_regressors import FutureRegressors from neuralprophet.utils_torch import init_parameter @@ -17,6 +18,7 @@ def __init__(self, config, id_list, quantiles, n_forecasts, device, config_trend device=device, config_trend_none_bool=config_trend_none_bool, ) + if self.regressors_dims is not None: # Regresors params self.regressor_params = nn.ParameterDict( diff --git a/neuralprophet/components/future_regressors/neural_nets.py b/neuralprophet/components/future_regressors/neural_nets.py new file mode 100644 index 000000000..8ed580aa3 --- /dev/null +++ b/neuralprophet/components/future_regressors/neural_nets.py @@ -0,0 +1,131 @@ +from collections import OrderedDict + +import torch.nn as nn + +from neuralprophet.components.future_regressors import FutureRegressors +from neuralprophet.utils_torch import init_parameter, interprete_model + +# from neuralprophet.utils_torch import init_parameter + + +class NeuralNetsFutureRegressors(FutureRegressors): + def __init__(self, config, id_list, quantiles, n_forecasts, device, config_trend_none_bool): + super().__init__( + config=config, + n_forecasts=n_forecasts, + quantiles=quantiles, + id_list=id_list, + device=device, + config_trend_none_bool=config_trend_none_bool, + ) + if self.regressors_dims is not None: + # Regresors params + self.regressor_nets = nn.ModuleDict({}) + # TO DO: if no hidden layers, then just a as legacy + self.d_hidden_regressors = config.d_hidden + self.num_hidden_layers_regressors = config.num_hidden_layers + # one net per regressor. to be adapted to combined network + for regressor in self.regressors_dims.keys(): + # Nets for both additive and multiplicative regressors + regressor_net = nn.ModuleList() + # This will be later 1 + static covariates + d_inputs = 1 + for i in range(self.num_hidden_layers_regressors): + regressor_net.append(nn.Linear(d_inputs, self.d_hidden_regressors, bias=True)) + d_inputs = self.d_hidden_regressors + # final layer has input size d_inputs and output size equal to no. of forecasts * no. of quantiles + regressor_net.append(nn.Linear(d_inputs, self.n_forecasts * len(self.quantiles), bias=False)) + for lay in regressor_net: + nn.init.kaiming_normal_(lay.weight, mode="fan_in") + self.regressor_nets[regressor] = regressor_net + + def get_reg_weights(self, name): + """ + Get attributions of regressors component network w.r.t. the model input. + + Parameters + ---------- + name : string + Regressor name + + Returns + ------- + torch.tensor + Weight corresponding to the given regressor + """ + + reg_attributions = interprete_model( + self, + net="regressor_nets", + forward_func="regressor", + _num_in_features=self.regressor_nets[name][0].in_features, + _num_out_features=self.regressor_nets[name][-1].out_features, + additional_forward_args=name, + ) + + return reg_attributions + + def regressor(self, regressor_input, name): + """Compute single regressor component. + Parameters + ---------- + regressor_input : torch.Tensor, float + regressor values at corresponding, dims: (batch, n_forecasts, 1) + nam : str + Name of regressor, for attribution to corresponding model weights + Returns + ------- + torch.Tensor + Forecast component of dims (batch, n_forecasts, num_quantiles) + """ + x = regressor_input + for i in range(self.num_hidden_layers_regressors + 1): + if i > 0: + x = nn.functional.relu(x) + x = self.regressor_nets[name][i](x) + + # segment the last dimension to match the quantiles + x = x.reshape(x.shape[0], self.n_forecasts, len(self.quantiles)) + return x + + def all_regressors(self, regressor_inputs, mode): + """Compute all regressors components. + Parameters + ---------- + regressor_inputs : torch.Tensor, float + regressor values at corresponding, dims: (batch, n_forecasts, num_regressors) + Returns + ------- + torch.Tensor + Forecast component of dims (batch, n_forecasts, num_quantiles) + """ + # Select only elements from OrderedDict that have the value mode == 'mode_of_interest' + regressors_dims_filtered = OrderedDict((k, v) for k, v in self.regressors_dims.items() if v["mode"] == mode) + for i, name in enumerate(regressors_dims_filtered.keys()): + regressor_index = regressors_dims_filtered[name]["regressor_index"] + regressor_input = regressor_inputs[:, :, regressor_index].unsqueeze(dim=2) + if i == 0: + x = self.regressor(regressor_input, name=name) + if i > 0: + x = x + self.regressor(regressor_input, name=name) + return x + + def forward(self, inputs, mode, indeces=None): + """Compute all seasonality components. + Parameters + ---------- + f_r : torch.Tensor, float + future regressors inputs + mode: string, either "additive" or "multiplicative" + mode of the regressors + Returns + ------- + torch.Tensor + Forecast component of dims (batch, n_forecasts, no_quantiles) + """ + + if "additive" == mode: + f_r = self.all_regressors(inputs, mode="additive") + if "multiplicative" == mode: + f_r = self.all_regressors(inputs, mode="multiplicative") + return f_r diff --git a/neuralprophet/components/future_regressors/shared_neural_nets.py b/neuralprophet/components/future_regressors/shared_neural_nets.py new file mode 100644 index 000000000..eae2f96d7 --- /dev/null +++ b/neuralprophet/components/future_regressors/shared_neural_nets.py @@ -0,0 +1,112 @@ +from collections import Counter, OrderedDict + +import torch +import torch.nn as nn + +from neuralprophet.components.future_regressors import FutureRegressors +from neuralprophet.utils_torch import init_parameter, interprete_model + +# from neuralprophet.utils_torch import init_parameter + + +class SharedNeuralNetsFutureRegressors(FutureRegressors): + def __init__(self, config, id_list, quantiles, n_forecasts, device, config_trend_none_bool): + super().__init__( + config=config, + n_forecasts=n_forecasts, + quantiles=quantiles, + id_list=id_list, + device=device, + config_trend_none_bool=config_trend_none_bool, + ) + if self.regressors_dims is not None: + # Regresors params + self.regressor_nets = nn.ModuleDict({}) + # TO DO: if no hidden layers, then just a as legacy + self.d_hidden_regressors = config.d_hidden + self.num_hidden_layers_regressors = config.num_hidden_layers + # Combined network + for net_i, size_i in Counter([x["mode"] for x in self.regressors_dims.values()]).items(): + # Nets for both additive and multiplicative regressors + regressor_net = nn.ModuleList() + # This will be later size_i(1 + static covariates) + d_inputs = size_i + for i in range(self.num_hidden_layers_regressors): + regressor_net.append(nn.Linear(d_inputs, self.d_hidden_regressors, bias=True)) + d_inputs = self.d_hidden_regressors + # final layer has input size d_inputs and output size equal to no. of forecasts * no. of quantiles + regressor_net.append(nn.Linear(d_inputs, self.n_forecasts * len(self.quantiles), bias=False)) + for lay in regressor_net: + nn.init.kaiming_normal_(lay.weight, mode="fan_in") + self.regressor_nets[net_i] = regressor_net + + def get_reg_weights(self, name): + """ + Get attributions of regressors component network w.r.t. the model input. + + Parameters + ---------- + name : string + Regressor name + + Returns + ------- + torch.tensor + Weight corresponding to the given regressor + """ + + mode = self.config_regressors.regressors[name].mode + reg_attributions = interprete_model( + self, + net="regressor_nets", + forward_func="regressors_net", + _num_in_features=self.regressor_nets[mode][0].in_features, + _num_out_features=self.regressor_nets[mode][-1].out_features, + additional_forward_args=mode, + ) + + regressor_index = self.regressors_dims[name]["regressor_index"] + return reg_attributions[:, regressor_index].unsqueeze(-1) + + def regressors_net(self, regressor_inputs, mode): + """Compute single regressor component. + Parameters + ---------- + regressor_input : torch.Tensor, float + regressor values at corresponding, dims: (batch, n_forecasts, 1) + nam : str + Name of regressor, for attribution to corresponding model weights + Returns + ------- + torch.Tensor + Forecast component of dims (batch, n_forecasts, num_quantiles) + """ + x = regressor_inputs + for i in range(self.num_hidden_layers_regressors + 1): + if i > 0: + x = nn.functional.relu(x) + x = self.regressor_nets[mode][i](x) + + # segment the last dimension to match the quantiles + x = x.reshape(x.shape[0], self.n_forecasts, len(self.quantiles)) + return x + + def forward(self, inputs, mode, indeces=None): + """Compute all seasonality components. + Parameters + ---------- + f_r : torch.Tensor, float + future regressors inputs + mode: string, either "additive" or "multiplicative" + mode of the regressors + Returns + ------- + torch.Tensor + Forecast component of dims (batch, n_forecasts, no_quantiles) + """ + + if "additive" == mode: + f_r = self.regressors_net(inputs, mode="additive") + if "multiplicative" == mode: + f_r = self.regressors_net(inputs, mode="multiplicative") + return f_r diff --git a/neuralprophet/components/future_regressors/shared_neural_nets_coef.py b/neuralprophet/components/future_regressors/shared_neural_nets_coef.py new file mode 100644 index 000000000..c5cbe9107 --- /dev/null +++ b/neuralprophet/components/future_regressors/shared_neural_nets_coef.py @@ -0,0 +1,114 @@ +from collections import Counter, OrderedDict + +import torch +import torch.nn as nn + +from neuralprophet.components.future_regressors import FutureRegressors +from neuralprophet.utils_torch import init_parameter, interprete_model + +# from neuralprophet.utils_torch import init_parameter + + +class SharedNeuralNetsCoefFutureRegressors(FutureRegressors): + def __init__(self, config, id_list, quantiles, n_forecasts, device, config_trend_none_bool): + super().__init__( + config=config, + n_forecasts=n_forecasts, + quantiles=quantiles, + id_list=id_list, + device=device, + config_trend_none_bool=config_trend_none_bool, + ) + if self.regressors_dims is not None: + # Regresors params + self.regressor_nets = nn.ModuleDict({}) + # TO DO: if no hidden layers, then just a as legacy + self.d_hidden_regressors = config.d_hidden + self.num_hidden_layers_regressors = config.num_hidden_layers + # Combined network + for net_i, size_i in Counter([x["mode"] for x in self.regressors_dims.values()]).items(): + # Nets for both additive and multiplicative regressors + regressor_net = nn.ModuleList() + # This will be later size_i(1 + static covariates) + d_inputs = size_i + for i in range(self.num_hidden_layers_regressors): + regressor_net.append(nn.Linear(d_inputs, self.d_hidden_regressors, bias=True)) + d_inputs = self.d_hidden_regressors + # final layer has input size d_inputs and output size equal to no. of forecasts * no. of quantiles + regressor_net.append(nn.Linear(d_inputs, size_i * self.n_forecasts * len(self.quantiles), bias=False)) + for lay in regressor_net: + nn.init.kaiming_normal_(lay.weight, mode="fan_in") + self.regressor_nets[net_i] = regressor_net + + def get_reg_weights(self, name): + """ + Get attributions of regressors component network w.r.t. the model input. + + Parameters + ---------- + name : string + Regressor name + + Returns + ------- + torch.tensor + Weight corresponding to the given regressor + """ + + mode = self.config_regressors.regressors[name].mode + reg_attributions = interprete_model( + self, + net="regressor_nets", + forward_func="regressors_net", + _num_in_features=self.regressor_nets[mode][0].in_features, + _num_out_features=self.regressor_nets[mode][-1].out_features + / Counter([x["mode"] for x in self.regressors_dims.values()])[mode], + additional_forward_args=mode, + ) + + regressor_index = self.regressors_dims[name]["regressor_index"] + return reg_attributions[:, regressor_index].unsqueeze(-1) + + def regressors_net(self, regressor_inputs, mode): + """Compute single regressor component. + Parameters + ---------- + regressor_input : torch.Tensor, float + regressor values at corresponding, dims: (batch, n_forecasts, num_regressors) + nam : str + Name of regressor, for attribution to corresponding model weights + Returns + ------- + torch.Tensor + Forecast component of dims (batch, n_forecasts, num_quantiles) + """ + x = regressor_inputs + for i in range(self.num_hidden_layers_regressors + 1): + if i > 0: + x = nn.functional.relu(x) + x = self.regressor_nets[mode][i](x) + + # segment the last dimension to match the quantiles + x = x.reshape(x.shape[0], self.n_forecasts, regressor_inputs.shape[-1], len(self.quantiles)) + x = (regressor_inputs.unsqueeze(-1) * x).sum(-2) + return x + + def forward(self, inputs, mode, indeces=None): + """Compute all seasonality components. + Parameters + ---------- + inputs : torch.Tensor, float + future regressors inputs + mode: string, either "additive" or "multiplicative" + mode of the regressors + Returns + ------- + torch.Tensor + Forecast component of dims (batch, n_forecasts, no_quantiles) + """ + + if "additive" == mode: + f_r = self.regressors_net(inputs, mode="additive") + if "multiplicative" == mode: + f_r = self.regressors_net(inputs, mode="multiplicative") + return f_r diff --git a/neuralprophet/components/router.py b/neuralprophet/components/router.py index ebb839927..09195d5f0 100644 --- a/neuralprophet/components/router.py +++ b/neuralprophet/components/router.py @@ -1,5 +1,12 @@ from neuralprophet.components.future_regressors.linear import LinearFutureRegressors -from neuralprophet.components.seasonality.fourier import GlobalFourierSeasonality, LocalFourierSeasonality +from neuralprophet.components.future_regressors.neural_nets import NeuralNetsFutureRegressors +from neuralprophet.components.future_regressors.shared_neural_nets import SharedNeuralNetsFutureRegressors +from neuralprophet.components.future_regressors.shared_neural_nets_coef import SharedNeuralNetsCoefFutureRegressors +from neuralprophet.components.seasonality.fourier import ( + GlobalFourierSeasonality, + GlocalFourierSeasonality, + LocalFourierSeasonality, +) from neuralprophet.components.trend.linear import GlobalLinearTrend, LocalLinearTrend from neuralprophet.components.trend.piecewise_linear import GlobalPiecewiseLinearTrend, LocalPiecewiseLinearTrend from neuralprophet.components.trend.static import StaticTrend @@ -88,11 +95,21 @@ def get_future_regressors(config, id_list, quantiles, n_forecasts, device, confi "device": device, "config_trend_none_bool": config_trend_none_bool, } - - return LinearFutureRegressors(**args) + if config.model == "linear": + return LinearFutureRegressors(**args) + elif config.model == "neural_nets": + return NeuralNetsFutureRegressors(**args) + elif config.model == "shared_neural_nets": + return SharedNeuralNetsFutureRegressors(**args) + elif config.model == "shared_neural_nets_coef": + return SharedNeuralNetsCoefFutureRegressors(**args) + else: + raise ValueError(f"Model type {config.model} is not supported.") -def get_seasonality(config, id_list, quantiles, num_seasonalities_modelled, n_forecasts, device): +def get_seasonality( + config, id_list, quantiles, num_seasonalities_modelled, num_seasonalities_modelled_dict, n_forecasts, device +): """ Router for all seasonality classes. """ @@ -103,13 +120,31 @@ def get_seasonality(config, id_list, quantiles, num_seasonalities_modelled, n_fo "n_forecasts": n_forecasts, "device": device, "num_seasonalities_modelled": num_seasonalities_modelled, + "num_seasonalities_modelled_dict": num_seasonalities_modelled_dict, } + # if only 1 time series, global strategy + if len(id_list) == 1: + config.global_local = "global" + for season_i in config.periods: + config.periods[season_i].global_local = "global" + + # if all config.periods[season_i] are the same(x), then config.global_local = x + if len(set([config.periods[season_i].global_local for season_i in config.periods])) == 1: + config.global_local = list(set([config.periods[season_i].global_local for season_i in config.periods]))[0] + + # if all config.periods[season_i] are different, then config.global_local = 'glocal' + if len(set([config.periods[season_i].global_local for season_i in config.periods])) > 1: + config.global_local = "glocal" + if config.global_local == "global": # Global seasonality return GlobalFourierSeasonality(**args) elif config.global_local == "local": # Local seasonality return LocalFourierSeasonality(**args) + elif config.global_local == "glocal": + # Glocal seasonality + return GlocalFourierSeasonality(**args) else: raise ValueError(f"Seasonality mode {config.global_local} is not supported.") diff --git a/neuralprophet/components/seasonality/base.py b/neuralprophet/components/seasonality/base.py index 3834e7c20..9c4d9d0ce 100644 --- a/neuralprophet/components/seasonality/base.py +++ b/neuralprophet/components/seasonality/base.py @@ -2,11 +2,17 @@ class Seasonality(BaseComponent): - def __init__(self, config, id_list, quantiles, num_seasonalities_modelled, n_forecasts, device): + def __init__( + self, + config, + id_list, + quantiles, + num_seasonalities_modelled, + num_seasonalities_modelled_dict, + n_forecasts, + device, + ): super().__init__(n_forecasts=n_forecasts, quantiles=quantiles, id_list=id_list, device=device) self.config_seasonality = config self.num_seasonalities_modelled = num_seasonalities_modelled - - # if only 1 time series, global strategy - if len(self.id_list) == 1: - self.config_seasonality.global_local = "global" + self.num_seasonalities_modelled_dict = num_seasonalities_modelled_dict diff --git a/neuralprophet/components/seasonality/fourier.py b/neuralprophet/components/seasonality/fourier.py index 4cfd000c2..80ef0f895 100644 --- a/neuralprophet/components/seasonality/fourier.py +++ b/neuralprophet/components/seasonality/fourier.py @@ -9,11 +9,21 @@ class FourierSeasonality(Seasonality): - def __init__(self, config, id_list, quantiles, num_seasonalities_modelled, n_forecasts, device): + def __init__( + self, + config, + id_list, + quantiles, + num_seasonalities_modelled, + num_seasonalities_modelled_dict, + n_forecasts, + device, + ): super().__init__( config=config, n_forecasts=n_forecasts, num_seasonalities_modelled=num_seasonalities_modelled, + num_seasonalities_modelled_dict=num_seasonalities_modelled_dict, quantiles=quantiles, id_list=id_list, device=device, @@ -25,7 +35,9 @@ def __init__(self, config, id_list, quantiles, num_seasonalities_modelled, n_for { # dimensions - # [no. of quantiles, num_seasonalities_modelled, no. of fourier terms for each seasonality] - name: init_parameter(dims=[len(self.quantiles)] + [self.num_seasonalities_modelled] + [dim]) + name: init_parameter( + dims=[len(self.quantiles)] + [self.num_seasonalities_modelled_dict[name]] + [dim] + ) for name, dim in self.season_dims.items() } ) @@ -79,11 +91,21 @@ def forward(self, s, meta): class GlobalFourierSeasonality(FourierSeasonality): - def __init__(self, config, id_list, quantiles, num_seasonalities_modelled, n_forecasts, device): + def __init__( + self, + config, + id_list, + quantiles, + num_seasonalities_modelled, + num_seasonalities_modelled_dict, + n_forecasts, + device, + ): super().__init__( config=config, n_forecasts=n_forecasts, num_seasonalities_modelled=num_seasonalities_modelled, + num_seasonalities_modelled_dict=num_seasonalities_modelled_dict, quantiles=quantiles, id_list=id_list, device=device, @@ -115,11 +137,21 @@ def compute_fourier(self, features, name, meta=None): class LocalFourierSeasonality(FourierSeasonality): - def __init__(self, config, id_list, quantiles, num_seasonalities_modelled, n_forecasts, device): + def __init__( + self, + config, + id_list, + quantiles, + num_seasonalities_modelled, + num_seasonalities_modelled_dict, + n_forecasts, + device, + ): super().__init__( config=config, n_forecasts=n_forecasts, num_seasonalities_modelled=num_seasonalities_modelled, + num_seasonalities_modelled_dict=num_seasonalities_modelled_dict, quantiles=quantiles, id_list=id_list, device=device, @@ -153,3 +185,60 @@ def compute_fourier(self, features, name, meta=None): # dimensions - batch_size, n_forecasts, quantiles seasonality = torch.sum(features.unsqueeze(2) * season_params_sample.permute(1, 0, 2).unsqueeze(1), dim=-1) return seasonality + + +class GlocalFourierSeasonality(FourierSeasonality): + def __init__( + self, + config, + id_list, + quantiles, + num_seasonalities_modelled, + num_seasonalities_modelled_dict, + n_forecasts, + device, + ): + super().__init__( + config=config, + n_forecasts=n_forecasts, + num_seasonalities_modelled=num_seasonalities_modelled, + num_seasonalities_modelled_dict=num_seasonalities_modelled_dict, + quantiles=quantiles, + id_list=id_list, + device=device, + ) + + def compute_fourier(self, features, name, meta=None): + """Compute single seasonality component. + + Parameters + ---------- + features : torch.Tensor, float + Features related to seasonality component, dims: (batch, n_forecasts, n_features) + name : str + Name of seasonality. for attribution to corresponding model weights. + meta: dict + Metadata about the all the samples of the model input batch. Contains the following: + * ``df_name`` (list, str), time series ID corresponding to each sample of the input batch. + + Returns + ------- + torch.Tensor + Forecast component of dims (batch, n_forecasts) + """ + # From the dataloader meta data, we get the one-hot encoding of the df_name. + if self.config_seasonality.periods[name].global_local == "local": + meta_name_tensor_one_hot = nn.functional.one_hot(meta, num_classes=len(self.id_list)) + # dimensions - quantiles, batch, parameters_fourier + season_params_sample = torch.sum( + meta_name_tensor_one_hot.unsqueeze(dim=0).unsqueeze(dim=-1) * self.season_params[name].unsqueeze(dim=1), + dim=2, + ) + # dimensions - batch_size, n_forecasts, quantiles + seasonality = torch.sum(features.unsqueeze(2) * season_params_sample.permute(1, 0, 2).unsqueeze(1), dim=-1) + elif self.config_seasonality.periods[name].global_local == "global": + # dimensions - batch_size, n_forecasts, quantiles + seasonality = torch.sum( + features.unsqueeze(dim=2) * self.season_params[name].permute(1, 0, 2).unsqueeze(dim=0), dim=-1 + ) + return seasonality diff --git a/neuralprophet/configure.py b/neuralprophet/configure.py index 6ab02d921..0b5d2ce95 100644 --- a/neuralprophet/configure.py +++ b/neuralprophet/configure.py @@ -249,6 +249,7 @@ class Trend: trend_reg: float trend_reg_threshold: Optional[Union[bool, float]] trend_global_local: str + trend_local_reg: Optional[Union[bool, float]] = None def __post_init__(self): if self.growth not in ["off", "linear", "discontinuous"]: @@ -303,6 +304,21 @@ def __post_init__(self): log.error("Invalid growth for global_local mode '{}'. Set to 'global'".format(self.trend_global_local)) self.trend_global_local = "global" + # If trend_local_reg < 0 + if self.trend_local_reg < 0: + log.error("Invalid negative trend_local_reg '{}'. Set to False".format(self.trend_local_reg)) + self.trend_local_reg = False + + # If trend_local_reg = True + if self.trend_local_reg == True: + log.error("trend_local_reg = True. Default trend_local_reg value set to 1") + self.trend_local_reg = 1 + + # If Trend modelling is global. + if self.trend_global_local == "global" and self.trend_local_reg != False: + log.error("Trend modeling is '{}'. Setting the trend_local_reg to False".format(self.trend_global_local)) + self.trend_local_reg = False + @dataclass class Season: @@ -310,6 +326,7 @@ class Season: period: float arg: np_types.SeasonalityArgument condition_name: Optional[str] + global_local: np_types.SeasonGlobalLocalMode = "local" @dataclass @@ -321,28 +338,84 @@ class ConfigSeasonality: weekly_arg: np_types.SeasonalityArgument = "auto" daily_arg: np_types.SeasonalityArgument = "auto" periods: OrderedDict = field(init=False) # contains SeasonConfig objects - global_local: np_types.SeasonGlobalLocalMode = "local" + global_local: np_types.SeasonGlobalLocalMode = "global" + seasonality_local_reg: Optional[Union[bool, float]] = None + yearly_global_local: np_types.SeasonalityArgument = "auto" + weekly_global_local: np_types.SeasonalityArgument = "auto" + daily_global_local: np_types.SeasonalityArgument = "auto" condition_name: Optional[str] = None def __post_init__(self): if self.reg_lambda > 0 and self.computation == "fourier": log.info("Note: Fourier-based seasonality regularization is experimental.") self.reg_lambda = 0.001 * self.reg_lambda - self.periods = OrderedDict( - { - "yearly": Season(resolution=6, period=365.25, arg=self.yearly_arg, condition_name=None), - "weekly": Season(resolution=3, period=7, arg=self.weekly_arg, condition_name=None), - "daily": Season(resolution=6, period=1, arg=self.daily_arg, condition_name=None), - } - ) # If global_local is not in the expected set, set to "global" if self.global_local not in ["global", "local"]: log.error("Invalid global_local mode '{}'. Set to 'global'".format(self.global_local)) self.global_local = "global" - def append(self, name, period, resolution, arg, condition_name): - self.periods[name] = Season(resolution=resolution, period=period, arg=arg, condition_name=condition_name) + self.periods = OrderedDict( + { + "yearly": Season( + resolution=6, + period=365.25, + arg=self.yearly_arg, + global_local=( + self.yearly_global_local + if self.yearly_global_local in ["global", "local"] + else self.global_local + ), + condition_name=None, + ), + "weekly": Season( + resolution=3, + period=7, + arg=self.weekly_arg, + global_local=( + self.weekly_global_local + if self.weekly_global_local in ["global", "local"] + else self.global_local + ), + condition_name=None, + ), + "daily": Season( + resolution=6, + period=1, + arg=self.daily_arg, + global_local=( + self.daily_global_local if self.daily_global_local in ["global", "local"] else self.global_local + ), + condition_name=None, + ), + } + ) + + # If seasonality_local_reg < 0 + if self.seasonality_local_reg < 0: + log.error("Invalid negative seasonality_local_reg '{}'. Set to False".format(self.seasonality_local_reg)) + self.seasonality_local_reg = False + + # If seasonality_local_reg = True + if self.seasonality_local_reg == True: + log.error("seasonality_local_reg = True. Default seasonality_local_reg value set to 1") + self.seasonality_local_reg = 1 + + # If Season modelling is global. + if self.global_local == "global" and self.seasonality_local_reg != False: + log.error( + "Seasonality modeling is '{}'. Setting the seasonality_local_reg to False".format(self.global_local) + ) + self.seasonality_local_reg = False + + def append(self, name, period, resolution, arg, condition_name, global_local="auto"): + self.periods[name] = Season( + resolution=resolution, + period=period, + arg=arg, + global_local=global_local if global_local in ["global", "local"] else self.global_local, + condition_name=condition_name, + ) @dataclass @@ -406,7 +479,15 @@ class Regressor: mode: str -ConfigFutureRegressors = OrderedDictType[str, Regressor] +@dataclass +class ConfigFutureRegressors: + model: str + d_hidden: int + num_hidden_layers: int + regressors: OrderedDict = field(init=False) # contains RegressorConfig objects + + def __post_init__(self): + self.regressors = None @dataclass diff --git a/neuralprophet/data/process.py b/neuralprophet/data/process.py index 9f8861016..a16bd3a8b 100644 --- a/neuralprophet/data/process.py +++ b/neuralprophet/data/process.py @@ -365,8 +365,8 @@ def _validate_column_name( if covariates and config_lagged_regressors is not None: if name in config_lagged_regressors: raise ValueError(f"Name {name!r} already used for an added covariate.") - if regressors and config_regressors is not None: - if name in config_regressors.keys(): + if regressors and config_regressors.regressors is not None: + if name in config_regressors.regressors.keys(): raise ValueError(f"Name {name!r} already used for an added regressor.") @@ -411,17 +411,18 @@ def _check_dataframe( df=df, check_y=check_y, covariates=model.config_lagged_regressors if exogenous else None, - regressors=model.config_regressors if exogenous else None, + regressors=model.config_regressors.regressors if exogenous else None, events=model.config_events if exogenous else None, seasonalities=model.config_seasonality if exogenous else None, future=True if future else None, ) - if model.config_regressors is not None: + + if model.config_regressors.regressors is not None: for reg in regressors_to_remove: log.warning(f"Removing regressor {reg} because it is not present in the data.") - model.config_regressors.pop(reg) - if len(model.config_regressors) == 0: - model.config_regressors = None + model.config_regressors.regressors.pop(reg) + if model.config_regressors.regressors is not None and len(model.config_regressors.regressors) == 0: + model.config_regressors.regressors = None if model.config_lagged_regressors is not None: for reg in lag_regressors_to_remove: log.warning(f"Removing lagged regressor {reg} because it is not present in the data.") @@ -498,9 +499,11 @@ def _handle_missing_data( df = df_grouped.reset_index() log.info(f"Added {n_missing_dates} missing dates.") - if config_regressors is not None: + if config_regressors is not None and config_regressors.regressors is not None: # drop complete row for future regressors that are NaN at the end - last_valid_index = df.groupby("ID")[list(config_regressors.keys())].apply(lambda x: x.last_valid_index()) + last_valid_index = df.groupby("ID")[list(config_regressors.regressors.keys())].apply( + lambda x: x.last_valid_index() + ) df_dropped = df.groupby("ID", group_keys=False).apply(lambda x: x.loc[: last_valid_index[x.name]]) n_dropped = len(df) - len(df_dropped) if n_dropped > 0: @@ -527,8 +530,8 @@ def _handle_missing_data( data_columns.append("y") if config_lagged_regressors is not None: data_columns.extend(config_lagged_regressors.keys()) - if config_regressors is not None: - data_columns.extend(config_regressors.keys()) + if config_regressors is not None and config_regressors.regressors is not None: + data_columns.extend(config_regressors.regressors.keys()) if config_events is not None: data_columns.extend(config_events.keys()) conditional_cols = [] diff --git a/neuralprophet/data/split.py b/neuralprophet/data/split.py index 164c75ef6..93dedcc52 100644 --- a/neuralprophet/data/split.py +++ b/neuralprophet/data/split.py @@ -115,7 +115,7 @@ def _get_maybe_extend_periods( while len(df) > nan_at_end and df["y"].isnull().iloc[-(1 + nan_at_end)]: nan_at_end += 1 if max_lags > 0: - if config_regressors is None: + if config_regressors is not None and config_regressors.regressors is not None: # if dataframe has already been extended into future, # don't extend beyond n_forecasts. periods_add = max(0, n_forecasts - nan_at_end) @@ -199,11 +199,11 @@ def _make_future_dataframe( raise ValueError("Set either history or future to contain more than zero values.") # check for external regressors known in future - if model.config_regressors is not None and periods > 0: + if model.config_regressors.regressors is not None and periods > 0: if regressors_df is None: raise ValueError("Future values of all user specified regressors not provided") else: - for regressor in model.config_regressors.keys(): + for regressor in model.config_regressors.regressors.keys(): if regressor not in regressors_df.columns: raise ValueError(f"Future values of user specified regressor {regressor} not provided") diff --git a/neuralprophet/df_utils.py b/neuralprophet/df_utils.py index 8a4c4dcb5..23d245458 100644 --- a/neuralprophet/df_utils.py +++ b/neuralprophet/df_utils.py @@ -217,11 +217,11 @@ def data_params_definition( norm_type=norm_type_lag, ) - if config_regressors is not None: - for reg in config_regressors.keys(): + if config_regressors is not None and config_regressors.regressors is not None: + for reg in config_regressors.regressors.keys(): if reg not in df.columns: raise ValueError(f"Regressor {reg} not found in DataFrame.") - norm_type = config_regressors[reg].normalize + norm_type = config_regressors.regressors[reg].normalize if local_run_despite_global: if len(df[reg].unique()) < 2: norm_type = "soft" @@ -988,7 +988,7 @@ def make_future_df( if config_events is not None: future_df = convert_events_to_features(future_df, config_events=config_events, events_df=events_df) # set the regressors features - if config_regressors is not None and regressors_df is not None: + if config_regressors.regressors is not None and regressors_df is not None: for regressor in regressors_df: # Todo: iterate over config_regressors instead future_df[regressor] = regressors_df[regressor] diff --git a/neuralprophet/forecaster.py b/neuralprophet/forecaster.py index 977298aa9..9cc6b6f56 100644 --- a/neuralprophet/forecaster.py +++ b/neuralprophet/forecaster.py @@ -108,6 +108,14 @@ class NeuralProphet: Internally it will be set to ``global``, meaning that all the elements(only one in this case) are modelled with the same trend. + trend_local_reg : Optional[Union[bool, float]] = False, + Parameter to regularize weights to induce similarity between global and local trend + + Note + ---- + Large values (~100) will limit the variability of changepoints. + Small values (~0.001) will allow changepoints to change faster. + COMMENT Seasonality Config COMMENT @@ -118,20 +126,36 @@ class NeuralProphet: * ``True`` or ``False`` * ``auto``: set automatically * ``value``: number of Fourier/linear terms to generate + yearly_seasonality_glocal_mode : bool, str + Whether to train the yearly seasonality. Only effective on multiple time series + Options + * ``global`` + * ``local`` + * ``glocal`` weekly_seasonality : bool, int Fit monthly seasonality. - Options * ``True`` or ``False`` * ``auto``: set automatically * ``value``: number of Fourier/linear terms to generate + weekly_seasonality_glocal_mode : bool, str + Whether to train the weekly seasonality. Only effective on multiple time series + Options + * ``global`` + * ``local`` + * ``glocal`` daily_seasonality : bool, int Fit daily seasonality. - Options * ``True`` or ``False`` * ``auto``: set automatically * ``value``: number of Fourier/linear terms to generate + daily_seasonality_glocal_mode : bool, str + Whether to train the daily seasonality. Only effective on multiple time series + Options + * ``global`` + * ``local`` + * ``glocal`` seasonality_mode : str Specifies mode of seasonality @@ -147,7 +171,7 @@ class NeuralProphet: larger values (~1-100) dampen the seasonality. default: None, no regularization season_global_local : str, default 'global' - Modelling strategy of the seasonality when multiple time series are present. + Modelling strategy of the general/default seasonality when multiple time series are present. Options: * ``global``: All the elements are modelled with the same seasonality. * ``local``: Each element is modelled with a different seasonality. @@ -156,6 +180,29 @@ class NeuralProphet: When only one time series is input, this parameter should not be provided. Internally it will be set to ``global``, meaning that all the elements(only one in this case) are modelled with the same seasonality. + seasonality_local_reg : Optional[Union[bool, float]] = False, + Parameter to regularize weights to induce similarity between global and local seasonality + + Note + ---- + Large values (~100) will limit the variability of changepoints. + Small values (~0.001) will allow changepoints to change faster. + + COMMENT + Future Regressors + COMMENT + future_regressors_model: str + Options + * (default) ``linear`` + * ``neural_nets`` + + future_regressors_d_hidden: int + Number of hidden layers in the neural network model for future regressors. + Ignored if ``future_regressors_model`` is ``linear``. + + future_regressors_num_hidden_layers: int + Dimension of hidden layers in the neural network model for future regressors. + Ignored if ``future_regressors_model`` is ``linear``. COMMENT AR Config @@ -346,12 +393,20 @@ def __init__( trend_reg: float = 0, trend_reg_threshold: Optional[Union[bool, float]] = False, trend_global_local: str = "global", + trend_local_reg: Optional[Union[bool, float]] = False, yearly_seasonality: np_types.SeasonalityArgument = "auto", + yearly_seasonality_glocal_mode: np_types.SeasonalityArgument = "auto", weekly_seasonality: np_types.SeasonalityArgument = "auto", + weekly_seasonality_glocal_mode: np_types.SeasonalityArgument = "auto", daily_seasonality: np_types.SeasonalityArgument = "auto", + daily_seasonality_glocal_mode: np_types.SeasonalityArgument = "auto", seasonality_mode: np_types.SeasonalityMode = "additive", seasonality_reg: float = 0, season_global_local: np_types.SeasonGlobalLocalMode = "global", + seasonality_local_reg: Optional[Union[bool, float]] = False, + future_regressors_model: np_types.FutureRegressorsModel = "linear", + future_regressors_d_hidden: int = 4, + future_regressors_num_hidden_layers: int = 2, n_forecasts: int = 1, n_lags: int = 0, ar_layers: Optional[list] = [], @@ -441,6 +496,7 @@ def __init__( trend_reg=trend_reg, trend_reg_threshold=trend_reg_threshold, trend_global_local=trend_global_local, + trend_local_reg=trend_local_reg, ) # Seasonality @@ -451,6 +507,10 @@ def __init__( weekly_arg=weekly_seasonality, daily_arg=daily_seasonality, global_local=season_global_local, + seasonality_local_reg=seasonality_local_reg, + yearly_global_local=yearly_seasonality_glocal_mode, + weekly_global_local=weekly_seasonality_glocal_mode, + daily_global_local=daily_seasonality_glocal_mode, condition_name=None, ) @@ -460,7 +520,11 @@ def __init__( # Extra Regressors self.config_lagged_regressors: Optional[configure.ConfigLaggedRegressors] = None - self.config_regressors: Optional[configure.ConfigFutureRegressors] = None + self.config_regressors = configure.ConfigFutureRegressors( + model=future_regressors_model, + d_hidden=future_regressors_d_hidden, + num_hidden_layers=future_regressors_num_hidden_layers, + ) # Optional[configure.ConfigFutureRegressors] = None # set during fit() self.data_freq = None @@ -620,9 +684,11 @@ def add_future_regressor( config_regressors=self.config_regressors, ) - if self.config_regressors is None: - self.config_regressors = OrderedDict() - self.config_regressors[name] = configure.Regressor(reg_lambda=regularization, normalize=normalize, mode=mode) + if self.config_regressors.regressors is None: + self.config_regressors.regressors = OrderedDict() + self.config_regressors.regressors[name] = configure.Regressor( + reg_lambda=regularization, normalize=normalize, mode=mode + ) return self def add_events( @@ -731,7 +797,14 @@ def add_country_holidays( self.config_country_holidays.init_holidays() return self - def add_seasonality(self, name: str, period: float, fourier_order: int, condition_name: Optional[str] = None): + def add_seasonality( + self, + name: str, + period: float, + fourier_order: int, + global_local: str = "auto", + condition_name: Optional[str] = None, + ): """Add a seasonal component with specified period, number of Fourier components, and regularization. Increasing the number of Fourier components allows the seasonality to change more quickly @@ -751,9 +824,12 @@ def add_seasonality(self, name: str, period: float, fourier_order: int, conditio number of days in one period. fourier_order : int number of Fourier components to use. + global_local : str + glocal modelling mode. condition_name : string string name of the seasonality condition. + Examples -------- Adding a quarterly changing weekly seasonality to the model. First, add columns to df. @@ -802,7 +878,12 @@ def add_seasonality(self, name: str, period: float, fourier_order: int, conditio if fourier_order <= 0: raise ValueError("Fourier Order must be > 0") self.config_seasonality.append( - name=name, period=period, resolution=fourier_order, condition_name=condition_name, arg="custom" + name=name, + period=period, + resolution=fourier_order, + arg="custom", + global_local=global_local, + condition_name=condition_name, ) return self @@ -902,7 +983,7 @@ def fit( reg_enabled = utils.check_for_regularization( [ self.config_seasonality, - self.config_regressors, + self.config_regressors.regressors, self.config_ar, self.config_events, self.config_country_holidays, @@ -949,8 +1030,21 @@ def fit( # Setup for global-local modelling: If there is only a single time series, then self.id_list = ['__df__'] self.num_trends_modelled = len(self.id_list) if self.config_trend.trend_global_local == "local" else 1 - self.num_seasonalities_modelled = len(self.id_list) if self.config_seasonality.global_local == "local" else 1 - self.meta_used_in_model = self.num_trends_modelled != 1 or self.num_seasonalities_modelled != 1 + self.num_seasonalities_modelled = ( + len(self.id_list) if self.config_seasonality.global_local in ["glocal", "local"] else 1 + ) + self.num_seasonalities_modelled_dict = OrderedDict() + for season_i in self.config_seasonality.periods: + self.num_seasonalities_modelled_dict[season_i] = ( + len(self.id_list) if self.config_seasonality.periods[season_i].global_local == "local" else 1 + ) + # check if any of the values of the dictionary self.num_seasonalities_modelled_dict is different from 1 + + self.meta_used_in_model = ( + self.num_trends_modelled != 1 + or self.num_seasonalities_modelled != 1 + or any(value != 1 for value in self.num_seasonalities_modelled_dict.values()) + ) if self.fitted is True and not continue_training: log.error("Model has already been fitted. Re-fitting may break or produce different results.") @@ -1786,7 +1880,7 @@ def predict_seasonal_components(self, df: pd.DataFrame, quantile: float = 0.5): # Meta as a tensor for prediction if self.model.config_seasonality is None: meta_name_tensor = None - elif self.model.config_seasonality.global_local == "local": + elif self.model.config_seasonality.global_local in ["local", "glocal"]: meta = OrderedDict() meta["df_name"] = [df_name for _ in range(inputs["time"].shape[0])] meta_name_tensor = torch.tensor([self.model.id_dict[i] for i in meta["df_name"]]) # type: ignore @@ -2274,7 +2368,7 @@ def plot_components( # Error if local modelling of season and df_name not provided if self.model.config_seasonality is not None: - if self.model.config_seasonality.global_local == "local" and df_name is None: + if self.model.config_seasonality.global_local in ["local", "glocal"] and df_name is None: raise Exception( "df_name parameter is required for multiple time series and local modeling of at least one \ component." @@ -2445,6 +2539,7 @@ def plot_parameters( "events", "future_regressors", ] + valid_plot_configuration = get_valid_configuration( m=self, components=components, @@ -2525,6 +2620,7 @@ def _init_model(self): id_list=self.id_list, num_trends_modelled=self.num_trends_modelled, num_seasonalities_modelled=self.num_seasonalities_modelled, + num_seasonalities_modelled_dict=self.num_seasonalities_modelled_dict, meta_used_in_model=self.meta_used_in_model, ) log.debug(self.model) @@ -2865,10 +2961,13 @@ def _predict_raw(self, df, df_name, include_components=False, prediction_frequen multiplicative = True elif ( "future_regressor_" in name or "future_regressors_" in name - ) and self.config_regressors is not None: + ) and self.config_regressors.regressors is not None: regressor_name = name.split("_")[2] - if self.config_regressors is not None and regressor_name in self.config_regressors: - if self.config_regressors[regressor_name].mode == "multiplicative": + if ( + self.config_regressors.regressors is not None + and regressor_name in self.config_regressors.regressors + ): + if self.config_regressors.regressors[regressor_name].mode == "multiplicative": multiplicative = True elif "multiplicative" in regressor_name: multiplicative = True diff --git a/neuralprophet/np_types.py b/neuralprophet/np_types.py index 3b32f6077..00b1efc9c 100644 --- a/neuralprophet/np_types.py +++ b/neuralprophet/np_types.py @@ -20,6 +20,8 @@ CollectMetricsMode = Union[Dict, bool] -SeasonGlobalLocalMode = Literal["global", "local"] +SeasonGlobalLocalMode = Literal["global", "local", "glocal"] + +FutureRegressorsModel = Literal["linear", "neural_nets", "shared_neural_nets"] Components = Dict[str, torch.Tensor] diff --git a/neuralprophet/plot_utils.py b/neuralprophet/plot_utils.py index ca93e1e57..c468d3210 100644 --- a/neuralprophet/plot_utils.py +++ b/neuralprophet/plot_utils.py @@ -196,7 +196,7 @@ def check_if_configured(m, components, error_flag=False): # move to utils if "events" in components and (m.config_events is None and m.config_country_holidays is None): components.remove("events") invalid_components.append("events") - if "future_regressors" in components and m.config_regressors is None: + if "future_regressors" in components and m.config_regressors.regressors is None: components.remove("future_regressors") invalid_components.append("future_regressors") if "uncertainty" in components and not len(m.model.quantiles) > 1: @@ -294,7 +294,7 @@ def get_valid_configuration( # move to utils if df_name is None: if m.id_list.__len__() > 1: if ( - m.model.config_seasonality.global_local == "local" + m.model.config_seasonality.global_local in ["local", "glocal"] or m.model.config_trend.trend_global_local == "local" ): df_name = m.id_list @@ -471,7 +471,7 @@ def get_valid_configuration( # move to utils additive_future_regressors = [] multiplicative_future_regressors = [] if "future_regressors" in components: - for regressor, configs in m.config_regressors.items(): + for regressor, configs in m.config_regressors.regressors.items(): if validator == "plot_components" and configs.mode == "additive": plot_components.append( { diff --git a/neuralprophet/time_dataset.py b/neuralprophet/time_dataset.py index dca97da79..6388d22d7 100644 --- a/neuralprophet/time_dataset.py +++ b/neuralprophet/time_dataset.py @@ -401,7 +401,7 @@ def _stride_timestamps_for_forecasts(x): inputs["covariates"] = covariates # get the regressors features - if config_regressors is not None: + if config_regressors is not None and config_regressors.regressors is not None: additive_regressors, multiplicative_regressors = make_regressors_features(df, config_regressors) regressors = OrderedDict({}) @@ -667,8 +667,8 @@ def make_regressors_features(df, config_regressors): multiplicative_regressors = pd.DataFrame() for reg in df.columns: - if reg in config_regressors: - mode = config_regressors[reg].mode + if reg in config_regressors.regressors: + mode = config_regressors.regressors[reg].mode if mode == "additive": additive_regressors[reg] = df[reg] else: diff --git a/neuralprophet/time_net.py b/neuralprophet/time_net.py index f2fcbeb80..5a58db9b9 100644 --- a/neuralprophet/time_net.py +++ b/neuralprophet/time_net.py @@ -18,7 +18,9 @@ reg_func_events, reg_func_regressors, reg_func_season, + reg_func_seasonality_glocal, reg_func_trend, + reg_func_trend_glocal, ) from neuralprophet.utils_torch import init_parameter, interprete_model @@ -59,6 +61,7 @@ def __init__( id_list: List[str] = ["__df__"], num_trends_modelled: int = 1, num_seasonalities_modelled: int = 1, + num_seasonalities_modelled_dict: dict = None, meta_used_in_model: bool = False, ): """ @@ -180,6 +183,7 @@ def __init__( self.id_dict = dict((key, i) for i, key in enumerate(id_list)) self.num_trends_modelled = num_trends_modelled self.num_seasonalities_modelled = num_seasonalities_modelled + self.num_seasonalities_modelled_dict = num_seasonalities_modelled_dict self.meta_used_in_model = meta_used_in_model # Regularization @@ -223,6 +227,7 @@ def __init__( id_list=id_list, quantiles=self.quantiles, num_seasonalities_modelled=num_seasonalities_modelled, + num_seasonalities_modelled_dict=num_seasonalities_modelled_dict, n_forecasts=n_forecasts, device=self.device, ) @@ -288,7 +293,7 @@ def __init__( # Regressors self.config_regressors = config_regressors - if self.config_regressors is not None: + if self.config_regressors.regressors is not None: # Initialize future_regressors self.future_regressors = get_future_regressors( config=config_regressors, @@ -299,7 +304,7 @@ def __init__( config_trend_none_bool=self.config_trend is None, ) else: - self.config_regressors = None + self.config_regressors.regressors = None @property def ar_weights(self) -> torch.Tensor: @@ -556,19 +561,18 @@ def forward(self, inputs: Dict, meta: Dict = None, compute_components_flag: bool meta["df_name"] = [name_id_dummy for _ in range(inputs["time"].shape[0])] meta = torch.tensor([self.id_dict[i] for i in meta["df_name"]], device=self.device) + components = {} + additive_components = torch.zeros( + size=(inputs["time"].shape[0], self.n_forecasts, len(self.quantiles)), + device=self.device, + ) additive_components_nonstationary = torch.zeros( size=(inputs["time"].shape[0], inputs["time"].shape[1], len(self.quantiles)), device=self.device ) multiplicative_components_nonstationary = torch.zeros( size=(inputs["time"].shape[0], inputs["time"].shape[1], len(self.quantiles)), device=self.device ) - additive_components = torch.zeros( - size=(inputs["time"].shape[0], self.n_forecasts, len(self.quantiles)), - device=self.device, - ) - components = {} - # non-stationary components trend = self.trend(t=inputs["time"], meta=meta) components["trend"] = trend @@ -606,14 +610,14 @@ def forward(self, inputs: Dict, meta: Dict = None, compute_components_flag: bool multiplicative_components_nonstationary += multiplicative_regressors components["multiplicative_regressors"] = multiplicative_regressors - nonstationary_components = ( # dimensions - [batch, n_lags, median quantile] - trend[:, : self.n_lags, 0] - + additive_components_nonstationary[:, : self.n_lags, 0] - + trend[:, : self.n_lags, 0].detach() * multiplicative_components_nonstationary[:, : self.n_lags, 0] - ) - # stationarized input if "lags" in inputs: + # combinde all non-stationary components over AR input range + nonstationary_components = ( # dimensions - [batch, n_lags, median quantile] + trend[:, : self.n_lags, 0] + + additive_components_nonstationary[:, : self.n_lags, 0] + + trend[:, : self.n_lags, 0].detach() * multiplicative_components_nonstationary[:, : self.n_lags, 0] + ) stationarized_lags = inputs["lags"] - nonstationary_components lags = self.auto_regression(lags=stationarized_lags) additive_components += lags @@ -624,19 +628,14 @@ def forward(self, inputs: Dict, meta: Dict = None, compute_components_flag: bool additive_components += covariates components["covariates"] = covariates + # combine all non-stationary components over forecast range predictions_nonstationary = ( trend[:, self.n_lags : inputs["time"].shape[1], :] + additive_components_nonstationary[:, self.n_lags : inputs["time"].shape[1], :] + trend[:, self.n_lags : inputs["time"].shape[1], :].detach() * multiplicative_components_nonstationary[:, self.n_lags : inputs["time"].shape[1], :] ) - prediction = ( - predictions_nonstationary - + additive_components - # 0 is the median quantile index - # all multiplicative components are multiplied by the median quantile trend (uncomment line below to apply) - # trend + additive_components + trend.detach()[:, :, 0].unsqueeze(dim=2) * multiplicative_components - ) # dimensions - [batch, n_forecasts, no_quantiles] + prediction = predictions_nonstationary + additive_components # dimensions - [batch, n_forecasts, no_quantiles] # check for crossing quantiles and correct them here if "predict_mode" in inputs.keys() and inputs["predict_mode"]: @@ -731,7 +730,7 @@ def compute_components(self, inputs: Dict, components_raw: Dict, meta: Dict) -> components[f"event_{event}"] = self.scalar_features_effects( features=features, params=params, indices=indices ) - if self.config_regressors is not None and "regressors" in inputs: + if self.config_regressors.regressors is not None and "regressors" in inputs: if "additive" in inputs["regressors"].keys(): components["future_regressors_additive"] = components_raw["additive_regressors"][ :, self.n_lags : inputs["time"].shape[1], : @@ -934,11 +933,28 @@ def _add_batch_regularizations(self, loss, epoch, progress): reg_loss += reg_events_loss # Regularize regressors: sparsify regressor features coefficients - if self.config_regressors is not None: - reg_regressor_loss = reg_func_regressors(self.config_regressors, self) + if self.config_regressors.regressors is not None: + reg_regressor_loss = reg_func_regressors(self.config_regressors.regressors, self) reg_loss += reg_regressor_loss - reg_loss = delay_weight * reg_loss + trend_glocal_loss = torch.zeros(1, dtype=torch.float, requires_grad=False) + # Glocal Trend + if self.config_trend is not None: + if self.config_trend.trend_global_local == "local" and self.config_trend.trend_local_reg != False: + trend_glocal_loss = reg_func_trend_glocal( + self.trend.trend_k0, self.trend.trend_deltas, self.config_trend.trend_local_reg + ) + reg_loss += trend_glocal_loss + # Glocal Seasonality + if self.config_seasonality is not None: + if ( + self.config_seasonality.global_local in ["local", "glocal"] + and self.config_seasonality.seasonality_local_reg != False + ): + seasonality_glocal_loss = reg_func_seasonality_glocal( + self.seasonality.season_params, self.config_seasonality.seasonality_local_reg + ) + reg_loss += seasonality_glocal_loss loss = loss + reg_loss return loss, reg_loss diff --git a/neuralprophet/utils.py b/neuralprophet/utils.py index ea245dc7f..d5fabe203 100644 --- a/neuralprophet/utils.py +++ b/neuralprophet/utils.py @@ -143,6 +143,50 @@ def reg_func_trend(weights, threshold=None): return reg +def reg_func_trend_glocal(trend_k0, trend_deltas, trend_local_reg): + """Regularization of weights to induce similarity between global and local trend + Parameters + ---------- + # trend_k0 : torch.Tensor + # Local trend intercept + # trend_deltas : torch.Tensor + # Local trend slopes + # trend_local_reg : float + # glocal trend regularization coefficient + Returns + ------- + torch.Tensor + regularization loss + """ + trend_k0_val = (trend_k0 - trend_k0.mean()).pow(2).mean() + trend_val = (trend_deltas - trend_deltas.mean(-2).unsqueeze(-2)).pow(2).mean() + + return trend_local_reg * (trend_k0_val + trend_val) + + +def reg_func_seasonality_glocal(season_params, seasonality_local_reg): + """Regularization of weights to induce similarity between global and local trend + Parameters + ---------- + # season_params : torch.Tensor + # Local season params + # seasonality_local_reg : float + # glocal season regularization coefficient + Returns + ------- + torch.Tensor + regularization loss + """ + + # Perform the operation on each value and store the results in a list + results = [] + for key, season_params_i in season_params.items(): + result = (season_params_i - season_params_i.mean(-2).unsqueeze(-2)).pow(2).mean() + results.append(result) + + return seasonality_local_reg * sum(results) + + def reg_func_season(weights): return reg_func_abs(weights) @@ -274,6 +318,12 @@ def check_for_regularization(configs: list): if hasattr(config, "reg_lambda"): if config.reg_lambda is not None: reg_sum += config.reg_lambda + if hasattr(config, "trend_local_reg"): + if config.trend_local_reg is not None: + reg_sum += config.trend_local_reg + if hasattr(config, "seasonality_local_reg"): + if config.seasonality_local_reg is not None: + reg_sum += config.seasonality_local_reg return reg_sum > 0 @@ -492,14 +542,14 @@ def config_regressors_to_model_dims(config_regressors): This dictionaries' keys correspond to individual regressor and values in a dict containing the mode and the indices in the input dataframe corresponding to each regressor. """ - if config_regressors is None: + if config_regressors is not None and config_regressors.regressors is None: return None else: additive_regressors = [] multiplicative_regressors = [] - if config_regressors is not None: - for regressor, configs in config_regressors.items(): + if config_regressors is not None and config_regressors.regressors is not None: + for regressor, configs in config_regressors.regressors.items(): mode = configs.mode if mode == "additive": additive_regressors.append(regressor) diff --git a/neuralprophet/utils_torch.py b/neuralprophet/utils_torch.py index 66491289c..0ab9e6a52 100644 --- a/neuralprophet/utils_torch.py +++ b/neuralprophet/utils_torch.py @@ -1,5 +1,6 @@ import inspect import logging +from typing import Any import numpy as np import pytorch_lightning as pl @@ -74,7 +75,15 @@ def create_optimizer_from_config(optimizer_name, optimizer_args): return optimizer, optimizer_args -def interprete_model(target_model: pl.LightningModule, net: str, forward_func: str, _input: torch.Tensor = None): +def interprete_model( + target_model: pl.LightningModule, + net: str, + forward_func: str, + _num_in_features: int = None, + _num_out_features: int = None, + _input: torch.Tensor = None, + additional_forward_args: Any = None, +): """ Returns model input attributions for a given network and forward function. @@ -82,10 +91,8 @@ def interprete_model(target_model: pl.LightningModule, net: str, forward_func: s ---------- target_model : pl.LightningModule The model for which input attributions are to be computed. - net : str Name of the network for which input attributions are to be computed. - forward_func : str Name of the forward function for which input attributions are to be computed. @@ -103,10 +110,12 @@ def interprete_model(target_model: pl.LightningModule, net: str, forward_func: s # Number of quantiles num_quantiles = len(target_model.quantiles) + # Number of input features to the net (aka n_lags) - num_in_features = getattr(target_model, net)[0].in_features + num_in_features = getattr(target_model, net)[0].in_features if _num_in_features is None else _num_in_features # Number of output features from the net (aka n_forecasts) - num_out_features = getattr(target_model, net)[-1].out_features + num_out_features = getattr(target_model, net)[-1].out_features if _num_out_features is None else _num_out_features + num_out_features_without_quantiles = int(num_out_features / num_quantiles) # Create a tensor of ones as model input @@ -116,7 +125,12 @@ def interprete_model(target_model: pl.LightningModule, net: str, forward_func: s attributions = torch.empty((0, num_in_features)) for output_feature in range(num_out_features_without_quantiles): for quantile in range(num_quantiles): - target_attribution = saliency.attribute(model_input, target=[(output_feature, quantile)], abs=False) + target_attribution = saliency.attribute( + model_input, + target=[(output_feature, quantile)], + abs=False, + 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"00c06ddc6f1c3344e572bfea25e3bc45e41336a0515ba95a93dc189be1a2f49b" +content-hash = "e935def28544433f1720a540ca49ccdc1cd795f066bcc6e93333075eb5bd0a16" diff --git a/pyproject.toml b/pyproject.toml index 3723b780a..3a704e3bb 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -46,6 +46,7 @@ pytest = ">=7.2" pytest-cov = ">=4.0" kaleido = "0.2.1" # required for plotly static image export tabulate = "^0.9" # Used in model metrics CI only; md export for github-actions bot +ipykernel = "^6.29.2" [tool.poetry.group.docs] optional = true diff --git a/tests/metrics/debug-yosemite.ipynb b/tests/metrics/debug-yosemite.ipynb new file mode 100644 index 000000000..a7a2b0e56 --- /dev/null +++ b/tests/metrics/debug-yosemite.ipynb @@ -0,0 +1,21168 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import pathlib\n", + "import time\n", + "\n", + "import numpy as np\n", + "import pandas as pd\n", + "import plotly.graph_objects as go\n", + "from plotly.subplots import make_subplots\n", + "from plotly_resampler import unregister_plotly_resampler\n", + "\n", + "from neuralprophet import NeuralProphet, set_random_seed" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# Important to set seed for reproducibility\n", + "set_random_seed(42)\n", + "\n", + "\n", + "def get_system_speed():\n", + " repeats = 5\n", + " benchmarks = np.array([])\n", + " for a in range(0, repeats):\n", + " start = time.time()\n", + " for i in range(0, 1000):\n", + " for x in range(1, 1000):\n", + " 3.141592 * 2**x\n", + " for x in range(1, 1000):\n", + " float(x) / 3.141592\n", + " for x in range(1, 1000):\n", + " float(3.141592) / x\n", + "\n", + " end = time.time()\n", + " duration = end - start\n", + " duration = round(duration, 3)\n", + " benchmarks = np.append(benchmarks, duration)\n", + "\n", + " print(f\"System speed: {round(np.mean(benchmarks), 5)}s\")\n", + " print(f\"Standart deviation: {round(np.std(benchmarks), 5)}s\")\n", + " return benchmarks.mean(), benchmarks.std()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "def create_metrics_plot(metrics):\n", + " # Deactivate the resampler since it is not compatible with kaleido (image export)\n", + " unregister_plotly_resampler()\n", + "\n", + " # Plotly params\n", + " prediction_color = \"#2d92ff\"\n", + " actual_color = \"black\"\n", + " line_width = 2\n", + " xaxis_args = {\"showline\": True, \"mirror\": True, \"linewidth\": 1.5, \"showgrid\": False}\n", + " yaxis_args = {\n", + " \"showline\": True,\n", + " \"mirror\": True,\n", + " \"linewidth\": 1.5,\n", + " \"showgrid\": False,\n", + " \"rangemode\": \"tozero\",\n", + " \"type\": \"log\",\n", + " }\n", + " layout_args = {\n", + " \"autosize\": True,\n", + " \"template\": \"plotly_white\",\n", + " \"margin\": go.layout.Margin(l=0, r=10, b=0, t=30, pad=0),\n", + " \"font\": dict(size=10),\n", + " \"title\": dict(font=dict(size=10)),\n", + " \"width\": 1000,\n", + " \"height\": 200,\n", + " }\n", + "\n", + " metric_cols = [col for col in metrics.columns if not (\"_val\" in col or col == \"RegLoss\" or col == \"epoch\")]\n", + " fig = make_subplots(rows=1, cols=len(metric_cols), subplot_titles=metric_cols)\n", + " for i, metric in enumerate(metric_cols):\n", + " fig.add_trace(\n", + " go.Scatter(\n", + " y=metrics[metric],\n", + " name=metric,\n", + " mode=\"lines\",\n", + " line=dict(color=prediction_color, width=line_width),\n", + " legendgroup=metric,\n", + " ),\n", + " row=1,\n", + " col=i + 1,\n", + " )\n", + " if f\"{metric}_val\" in metrics.columns:\n", + " fig.add_trace(\n", + " go.Scatter(\n", + " y=metrics[f\"{metric}_val\"],\n", + " name=f\"{metric}_val\",\n", + " mode=\"lines\",\n", + " line=dict(color=actual_color, width=line_width),\n", + " legendgroup=metric,\n", + " ),\n", + " row=1,\n", + " col=i + 1,\n", + " )\n", + " if metric == \"Loss\":\n", + " fig.add_trace(\n", + " go.Scatter(\n", + " y=metrics[\"RegLoss\"],\n", + " name=\"RegLoss\",\n", + " mode=\"lines\",\n", + " line=dict(color=actual_color, width=line_width),\n", + " legendgroup=metric,\n", + " ),\n", + " row=1,\n", + " col=i + 1,\n", + " )\n", + " fig.update_xaxes(xaxis_args)\n", + " fig.update_yaxes(yaxis_args)\n", + " fig.update_layout(layout_args)\n", + " return fig" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "DIR = \"~/github/neural_prophet\"\n", + "DATA_DIR = os.path.join(DIR, \"tests\", \"test-data\")\n", + "PEYTON_FILE = os.path.join(DATA_DIR, \"wp_log_peyton_manning.csv\")\n", + "AIR_FILE = os.path.join(DATA_DIR, \"air_passengers.csv\")\n", + "YOS_FILE = os.path.join(DATA_DIR, \"yosemite_temps.csv\")\n", + "ENERGY_PRICE_DAILY_FILE = os.path.join(DATA_DIR, \"tutorial04_kaggle_energy_daily_temperature.csv\")" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.read_csv(YOS_FILE)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "m = NeuralProphet(\n", + " n_lags=36,\n", + " n_forecasts=12,\n", + " changepoints_range=0.9,\n", + " n_changepoints=30,\n", + " weekly_seasonality=False,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO - (NP.df_utils._infer_frequency) - Major frequency 5T corresponds to 99.995% of the data.\n", + "INFO - (NP.df_utils._infer_frequency) - Defined frequency is equal to major frequency - 5min\n", + "WARNING - (NP.data.processing._handle_missing_data) - 12 missing values in column y were detected in total. \n", + "INFO - (NP.data.processing._handle_missing_data) - 12 NaN values in column y were auto-imputed.\n", + "INFO - (NP.df_utils.return_df_in_original_format) - Returning df with no ID column\n", + "INFO - (NP.df_utils.return_df_in_original_format) - Returning df with no ID column\n", + "WARNING - (NP.forecaster.fit) - When Global modeling with local normalization, metrics are displayed in normalized scale.\n", + "INFO - (NP.df_utils._infer_frequency) - Major frequency 5T corresponds to 99.994% of the data.\n", + "INFO - (NP.df_utils._infer_frequency) - Defined frequency is equal to major frequency - 5min\n", + "INFO - (NP.config.init_data_params) - Setting normalization to global as only one dataframe provided for training.\n", + "INFO - (NP.utils.set_auto_seasonalities) - Disabling yearly seasonality. Run NeuralProphet with yearly_seasonality=True to override this.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "System speed: 0.4284s\n", + "Standart deviation: 0.00712s\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO - (NP.config.set_auto_batch_epoch) - Auto-set batch_size to 128\n", + "INFO - (NP.config.set_auto_batch_epoch) - Auto-set epochs to 90\n", + "WARNING - (NP.config.set_lr_finder_args) - Learning rate finder: The number of batches (132) is too small than the required number for the learning rate finder (255). The results might not be optimal.\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "4f7befc94e65472ea53ece2501e58afd", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Finding best initial lr: 0%| | 0/255 [00:00\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
MAE_valRMSE_valLoss_valRegLoss_valepochMAERMSELossRegLoss
890.6386950.8706560.0004430.0890.8121791.4527990.0009110.0
\n", + "" + ], + "text/plain": [ + " MAE_val RMSE_val Loss_val RegLoss_val epoch MAE RMSE \\\n", + "89 0.638695 0.870656 0.000443 0.0 89 0.812179 1.452799 \n", + "\n", + " Loss RegLoss \n", + "89 0.000911 0.0 " + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "metrics.tail(1)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO - (NP.df_utils._infer_frequency) - Major frequency 5T corresponds to 99.995% of the data.\n", + "INFO - (NP.df_utils._infer_frequency) - Defined frequency is equal to major frequency - 5min\n", + "INFO - (NP.df_utils._infer_frequency) - Major frequency 5T corresponds to 99.995% of the data.\n", + "INFO - (NP.df_utils._infer_frequency) - Defined frequency is equal to major frequency - 5min\n", + "WARNING - (NP.data.processing._handle_missing_data) - 12 missing values in column y were detected in total. \n", + "INFO - (NP.data.processing._handle_missing_data) - 12 NaN values in column y were auto-imputed.\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "ff29390e116b4fa3bc7f15bb3477c053", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Predicting: 132it [00:00, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO - (NP.df_utils.return_df_in_original_format) - Returning df with no ID column\n" + ] + } + ], + "source": [ + "forecast = m.predict(df)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.plotly.v1+json": { + "config": { + "plotlyServerURL": "https://plot.ly" + }, + "data": [ + { + "line": { + "color": "#2d92ff", + "width": 2 + }, + "mode": "lines", + "name": "[R] Predicted ~2h", + "type": "scatter", + "uid": 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a/tests/metrics/debug_glocal.py b/tests/metrics/debug_glocal.py new file mode 100644 index 000000000..6cfee5243 --- /dev/null +++ b/tests/metrics/debug_glocal.py @@ -0,0 +1,61 @@ +import os + +import numpy as np +import pandas as pd + + +def read_json(path, metrics_path, branch): + try: + df = pd.read_json(os.path.join(metrics_path, path), orient="index") + df = df.reset_index() + df.rename(columns={0: branch, "index": "Metric"}, inplace=True) + return df + except: # noqa: E722 + return None + + +# Load all metrics paths +metrics_path = os.path.join(os.getcwd(), "tests", "metrics") +metrics_path_main = os.path.join(os.getcwd(), "tests", "metrics-main") +metrics_files = [f for f in os.listdir(metrics_path) if ".json" in f] +all_metrics = pd.DataFrame() + +# Loop through all metrics files +for f in metrics_files: + current = read_json(f, metrics_path, "current") + main = read_json(f, metrics_path_main, "main") + + if main is not None: + df = pd.merge(current, main, on=["Metric"], how="left") + + # Adjust the runtime metrics + time = df.loc[df["Metric"] == "time"] + performance = df.loc[df["Metric"] == "system_performance"] + adjusted_performance = time["main"].values[0] / performance["main"].values[0] * performance["current"].values[0] + df.loc[df["Metric"] == "time", "main"] = adjusted_performance + + df["diff"] = ((df["main"] - df["current"]) / df["main"]) * 100 * -1 + + df = df.round(5) + df[" "] = np.select( + condlist=[(df["diff"] >= 7.0), (df["diff"] >= 3.0), (df["diff"] <= -5.0)], + choicelist=[":x:", ":warning:", ":tada:"], + default=":white_check_mark:", + ) + df["diff"] = df["diff"].fillna(0) + df["diff"] = df["diff"] + 0.0 + df["diff"] = df["diff"].round(2).astype(str) + "%" + else: + df = current.copy() + df["main"] = "-" + df["diff"] = "-" + df[" "] = "" + df = df.round(4) + + # Remove unused metrics + df = df[~df["Metric"].isin(["epoch", "RegLoss", "RegLoss_val", "system_performance", "system_std"])] + df["Benchmark"] = f.split(".")[0] + df = df[["Benchmark", "Metric", "main", "current", "diff", " "]] + all_metrics = pd.concat([all_metrics, df]) + +print(str(all_metrics.to_markdown(tablefmt="github", index=False))) diff --git a/tests/test_glocal.py b/tests/test_glocal.py index e4cf8309e..c25a649c3 100644 --- a/tests/test_glocal.py +++ b/tests/test_glocal.py @@ -200,7 +200,339 @@ def test_wrong_option_global_local_modeling(): train_df, test_df = m.split_df(pd.concat((df1_0, df2_0, df3_0)), valid_p=0.33, local_split=True) m.fit(train_df) future = m.make_future_dataframe(test_df) - m.predict(future) - m.test(test_df) - m.predict_trend(test_df) - m.predict_seasonal_components(test_df) + forecast = m.predict(future) + metrics = m.test(test_df) + forecast_trend = m.predict_trend(test_df) + forecast_seasonal_componets = m.predict_seasonal_components(test_df) + + +def test_different_seasonality_modeling(): + ### SEASONALITY GLOBAL LOCAL MODELLING - NO EXOGENOUS VARIABLES + log.info("Global Modeling + Global Normalization") + df = pd.read_csv(PEYTON_FILE, nrows=512) + df1_0 = df.iloc[:128, :].copy(deep=True) + df1_0["ID"] = "df1" + df2_0 = df.iloc[128:256, :].copy(deep=True) + df2_0["ID"] = "df2" + df3_0 = df.iloc[256:384, :].copy(deep=True) + df3_0["ID"] = "df3" + m = NeuralProphet( + n_forecasts=2, + n_lags=10, + epochs=EPOCHS, + batch_size=BATCH_SIZE, + learning_rate=LR, + season_global_local="local", + yearly_seasonality_glocal_mode="global", + ) + train_df, test_df = m.split_df(pd.concat((df1_0, df2_0, df3_0)), valid_p=0.33, local_split=True) + m.fit(train_df) + future = m.make_future_dataframe(test_df) + forecast = m.predict(future) + metrics = m.test(test_df) + forecast_trend = m.predict_trend(test_df) + forecast_seasonal_componets = m.predict_seasonal_components(test_df) + + +def test_adding_new_global_seasonality(): + ### SEASONALITY GLOBAL LOCAL MODELLING - NO EXOGENOUS VARIABLES + log.info("Global Modeling + Global Normalization") + df = pd.read_csv(PEYTON_FILE, nrows=512) + df1_0 = df.iloc[:128, :].copy(deep=True) + df1_0["ID"] = "df1" + df2_0 = df.iloc[128:256, :].copy(deep=True) + df2_0["ID"] = "df2" + df3_0 = df.iloc[256:384, :].copy(deep=True) + df3_0["ID"] = "df3" + m = NeuralProphet( + n_forecasts=2, + n_lags=10, + epochs=EPOCHS, + batch_size=BATCH_SIZE, + learning_rate=LR, + season_global_local="local", + yearly_seasonality_glocal_mode="global", + ) + m.add_seasonality(period=30, fourier_order=8, name="monthly", global_local="global") + train_df, test_df = m.split_df(pd.concat((df1_0, df2_0, df3_0)), valid_p=0.33, local_split=True) + m.fit(train_df) + future = m.make_future_dataframe(test_df) + forecast = m.predict(future) + metrics = m.test(test_df) + forecast_trend = m.predict_trend(test_df) + forecast_seasonal_componets = m.predict_seasonal_components(test_df) + + +def test_adding_new_local_seasonality(): + ### SEASONALITY GLOBAL LOCAL MODELLING - NO EXOGENOUS VARIABLES + log.info("Global Modeling + Global Normalization") + df = pd.read_csv(PEYTON_FILE, nrows=512) + df1_0 = df.iloc[:128, :].copy(deep=True) + df1_0["ID"] = "df1" + df2_0 = df.iloc[128:256, :].copy(deep=True) + df2_0["ID"] = "df2" + df3_0 = df.iloc[256:384, :].copy(deep=True) + df3_0["ID"] = "df3" + m = NeuralProphet(epochs=EPOCHS, batch_size=BATCH_SIZE, season_global_local="global", trend_global_local="local") + m.add_seasonality(period=30, fourier_order=8, name="monthly", global_local="local") + train_df, test_df = m.split_df(pd.concat((df1_0, df2_0, df3_0)), valid_p=0.33, local_split=True) + m.fit(train_df) + future = m.make_future_dataframe(test_df, n_historic_predictions=True) + forecast = m.predict(future) + metrics = m.test(test_df) + forecast_trend = m.predict_trend(test_df) + forecast_seasonal_componets = m.predict_seasonal_components(test_df) + + +def test_trend_local_reg(): + ### SEASONALITY GLOBAL LOCAL MODELLING - NO EXOGENOUS VARIABLES + log.info("Global Modeling + Global Normalization") + df = pd.read_csv(PEYTON_FILE, nrows=512) + df1_0 = df.iloc[:128, :].copy(deep=True) + df1_0["ID"] = "df1" + df2_0 = df.iloc[128:256, :].copy(deep=True) + df2_0["ID"] = "df2" + df3_0 = df.iloc[256:384, :].copy(deep=True) + df3_0["ID"] = "df3" + for coef_i in [-30, 0, False, True]: + m = NeuralProphet( + n_forecasts=1, + epochs=EPOCHS, + batch_size=BATCH_SIZE, + learning_rate=LR, + trend_global_local="local", + trend_local_reg=coef_i, + ) + + m.add_seasonality(period=30, fourier_order=8, name="monthly", global_local="global") + train_df, test_df = m.split_df(pd.concat((df1_0, df2_0, df3_0)), valid_p=0.33, local_split=True) + m.fit(train_df) + future = m.make_future_dataframe(test_df, n_historic_predictions=True) + forecast = m.predict(future) + metrics = m.test(test_df) + forecast_trend = m.predict_trend(test_df) + forecast_seasonal_componets = m.predict_seasonal_components(test_df) + + +def test_glocal_seasonality_reg(): + ### SEASONALITY GLOBAL LOCAL MODELLING - NO EXOGENOUS VARIABLES + log.info("Global Modeling + Global Normalization") + df = pd.read_csv(PEYTON_FILE, nrows=512) + df1_0 = df.iloc[:128, :].copy(deep=True) + df1_0["ID"] = "df1" + df2_0 = df.iloc[128:256, :].copy(deep=True) + df2_0["ID"] = "df2" + df3_0 = df.iloc[256:384, :].copy(deep=True) + df3_0["ID"] = "df3" + for coef_i in [-30, 0, False, True]: + m = NeuralProphet( + n_forecasts=1, + epochs=EPOCHS, + batch_size=BATCH_SIZE, + learning_rate=LR, + season_global_local="local", + yearly_seasonality_glocal_mode="global", + glocal_seasonality_reg=coef_i, + ) + + m.add_seasonality(period=30, fourier_order=8, name="monthly", global_local="global") + train_df, test_df = m.split_df(pd.concat((df1_0, df2_0, df3_0)), valid_p=0.33, local_split=True) + m.fit(train_df) + future = m.make_future_dataframe(test_df, n_historic_predictions=True) + forecast = m.predict(future) + metrics = m.test(test_df) + + +def test_trend_local_reg_if_global(): + ### SEASONALITY GLOBAL LOCAL MODELLING - NO EXOGENOUS VARIABLES + log.info("Global Modeling + Global Normalization") + df = pd.read_csv(PEYTON_FILE, nrows=512) + df1_0 = df.iloc[:128, :].copy(deep=True) + df1_0["ID"] = "df1" + df2_0 = df.iloc[128:256, :].copy(deep=True) + df2_0["ID"] = "df2" + df3_0 = df.iloc[256:384, :].copy(deep=True) + df3_0["ID"] = "df3" + for coef_i in [-30, 0, False, True]: + m = NeuralProphet( + n_forecasts=1, + epochs=EPOCHS, + batch_size=BATCH_SIZE, + learning_rate=LR, + trend_global_local="global", + trend_local_reg=3, + ) + + train_df, test_df = m.split_df(pd.concat((df1_0, df2_0, df3_0)), valid_p=0.33, local_split=True) + m.fit(train_df) + future = m.make_future_dataframe(test_df, n_historic_predictions=True) + forecast = m.predict(future) + metrics = m.test(test_df) + forecast_trend = m.predict_trend(test_df) + forecast_seasonal_componets = m.predict_seasonal_components(test_df) + + +def test_different_seasonality_modeling(): + ### SEASONALITY GLOBAL LOCAL MODELLING - NO EXOGENOUS VARIABLES + log.info("Global Modeling + Global Normalization") + df = pd.read_csv(PEYTON_FILE, nrows=512) + df1_0 = df.iloc[:128, :].copy(deep=True) + df1_0["ID"] = "df1" + df2_0 = df.iloc[128:256, :].copy(deep=True) + df2_0["ID"] = "df2" + df3_0 = df.iloc[256:384, :].copy(deep=True) + df3_0["ID"] = "df3" + m = NeuralProphet( + n_forecasts=2, + n_lags=10, + epochs=EPOCHS, + batch_size=BATCH_SIZE, + learning_rate=LR, + season_global_local="local", + yearly_seasonality_glocal_mode="global", + ) + train_df, test_df = m.split_df(pd.concat((df1_0, df2_0, df3_0)), valid_p=0.33, local_split=True) + m.fit(train_df) + future = m.make_future_dataframe(test_df) + forecast = m.predict(future) + metrics = m.test(test_df) + forecast_trend = m.predict_trend(test_df) + forecast_seasonal_componets = m.predict_seasonal_components(test_df) + + +def test_adding_new_global_seasonality(): + ### SEASONALITY GLOBAL LOCAL MODELLING - NO EXOGENOUS VARIABLES + log.info("Global Modeling + Global Normalization") + df = pd.read_csv(PEYTON_FILE, nrows=512) + df1_0 = df.iloc[:128, :].copy(deep=True) + df1_0["ID"] = "df1" + df2_0 = df.iloc[128:256, :].copy(deep=True) + df2_0["ID"] = "df2" + df3_0 = df.iloc[256:384, :].copy(deep=True) + df3_0["ID"] = "df3" + m = NeuralProphet( + n_forecasts=2, + n_lags=10, + epochs=EPOCHS, + batch_size=BATCH_SIZE, + learning_rate=LR, + season_global_local="local", + yearly_seasonality_glocal_mode="global", + ) + m.add_seasonality(period=30, fourier_order=8, name="monthly", global_local="global") + train_df, test_df = m.split_df(pd.concat((df1_0, df2_0, df3_0)), valid_p=0.33, local_split=True) + m.fit(train_df) + future = m.make_future_dataframe(test_df) + forecast = m.predict(future) + metrics = m.test(test_df) + forecast_trend = m.predict_trend(test_df) + forecast_seasonal_componets = m.predict_seasonal_components(test_df) + + +def test_adding_new_local_seasonality(): + ### SEASONALITY GLOBAL LOCAL MODELLING - NO EXOGENOUS VARIABLES + log.info("Global Modeling + Global Normalization") + df = pd.read_csv(PEYTON_FILE, nrows=512) + df1_0 = df.iloc[:128, :].copy(deep=True) + df1_0["ID"] = "df1" + df2_0 = df.iloc[128:256, :].copy(deep=True) + df2_0["ID"] = "df2" + df3_0 = df.iloc[256:384, :].copy(deep=True) + df3_0["ID"] = "df3" + m = NeuralProphet(epochs=EPOCHS, batch_size=BATCH_SIZE, season_global_local="global", trend_global_local="local") + m.add_seasonality(period=30, fourier_order=8, name="monthly", global_local="local") + train_df, test_df = m.split_df(pd.concat((df1_0, df2_0, df3_0)), valid_p=0.33, local_split=True) + m.fit(train_df) + future = m.make_future_dataframe(test_df, n_historic_predictions=True) + forecast = m.predict(future) + metrics = m.test(test_df) + forecast_trend = m.predict_trend(test_df) + forecast_seasonal_componets = m.predict_seasonal_components(test_df) + + +def test_trend_local_reg(): + ### SEASONALITY GLOBAL LOCAL MODELLING - NO EXOGENOUS VARIABLES + log.info("Global Modeling + Global Normalization") + df = pd.read_csv(PEYTON_FILE, nrows=512) + df1_0 = df.iloc[:128, :].copy(deep=True) + df1_0["ID"] = "df1" + df2_0 = df.iloc[128:256, :].copy(deep=True) + df2_0["ID"] = "df2" + df3_0 = df.iloc[256:384, :].copy(deep=True) + df3_0["ID"] = "df3" + for coef_i in [-30, 0, False, True]: + m = NeuralProphet( + n_forecasts=1, + epochs=EPOCHS, + batch_size=BATCH_SIZE, + learning_rate=LR, + trend_global_local="local", + trend_local_reg=coef_i, + ) + + m.add_seasonality(period=30, fourier_order=8, name="monthly", global_local="global") + train_df, test_df = m.split_df(pd.concat((df1_0, df2_0, df3_0)), valid_p=0.33, local_split=True) + m.fit(train_df) + future = m.make_future_dataframe(test_df, n_historic_predictions=True) + forecast = m.predict(future) + metrics = m.test(test_df) + forecast_trend = m.predict_trend(test_df) + forecast_seasonal_componets = m.predict_seasonal_components(test_df) + + +def test_glocal_seasonality_reg(): + ### SEASONALITY GLOBAL LOCAL MODELLING - NO EXOGENOUS VARIABLES + log.info("Global Modeling + Global Normalization") + df = pd.read_csv(PEYTON_FILE, nrows=512) + df1_0 = df.iloc[:128, :].copy(deep=True) + df1_0["ID"] = "df1" + df2_0 = df.iloc[128:256, :].copy(deep=True) + df2_0["ID"] = "df2" + df3_0 = df.iloc[256:384, :].copy(deep=True) + df3_0["ID"] = "df3" + for coef_i in [-30, 0, False, True]: + m = NeuralProphet( + n_forecasts=1, + epochs=EPOCHS, + batch_size=BATCH_SIZE, + learning_rate=LR, + season_global_local="local", + yearly_seasonality_glocal_mode="global", + seasonality_local_reg=coef_i, + ) + + m.add_seasonality(period=30, fourier_order=8, name="monthly", global_local="global") + train_df, test_df = m.split_df(pd.concat((df1_0, df2_0, df3_0)), valid_p=0.33, local_split=True) + m.fit(train_df) + future = m.make_future_dataframe(test_df, n_historic_predictions=True) + forecast = m.predict(future) + metrics = m.test(test_df) + + +def test_trend_local_reg_if_global(): + ### SEASONALITY GLOBAL LOCAL MODELLING - NO EXOGENOUS VARIABLES + log.info("Global Modeling + Global Normalization") + df = pd.read_csv(PEYTON_FILE, nrows=512) + df1_0 = df.iloc[:128, :].copy(deep=True) + df1_0["ID"] = "df1" + df2_0 = df.iloc[128:256, :].copy(deep=True) + df2_0["ID"] = "df2" + df3_0 = df.iloc[256:384, :].copy(deep=True) + df3_0["ID"] = "df3" + for coef_i in [-30, 0, False, True]: + m = NeuralProphet( + n_forecasts=1, + epochs=EPOCHS, + batch_size=BATCH_SIZE, + learning_rate=LR, + trend_global_local="global", + trend_local_reg=3, + ) + + train_df, test_df = m.split_df(pd.concat((df1_0, df2_0, df3_0)), valid_p=0.33, local_split=True) + m.fit(train_df) + future = m.make_future_dataframe(test_df, n_historic_predictions=True) + forecast = m.predict(future) + metrics = m.test(test_df) + forecast_trend = m.predict_trend(test_df) + forecast_seasonal_componets = m.predict_seasonal_components(test_df) diff --git a/tests/test_integration.py b/tests/test_integration.py index e7a8d3ff5..5772723a9 100644 --- a/tests/test_integration.py +++ b/tests/test_integration.py @@ -515,6 +515,83 @@ def test_future_reg(): plt.show() +def test_future_reg_NNs(): + log.info("testing: Future Regressors modelled with NNs") + df = pd.read_csv(PEYTON_FILE, nrows=NROWS + 50) + m = NeuralProphet(epochs=EPOCHS, batch_size=BATCH_SIZE, learning_rate=LR, future_regressors_model="neural_nets") + df["A"] = df["y"].rolling(7, min_periods=1).mean() + df["B"] = df["y"].rolling(30, min_periods=1).mean() + df["C"] = df["y"].rolling(7, min_periods=1).mean() + df["D"] = df["y"].rolling(30, min_periods=1).mean() + + regressors_df_future = pd.DataFrame( + data={"A": df["A"][-50:], "B": df["B"][-50:], "C": df["C"][-50:], "D": df["D"][-50:]} + ) + df = df[:-50] + m = m.add_future_regressor(name="A") + m = m.add_future_regressor(name="B", mode="additive") + m = m.add_future_regressor(name="C", mode="multiplicative") + m = m.add_future_regressor(name="D", mode="multiplicative") + m.fit(df, freq="D") + future = m.make_future_dataframe(df=df, regressors_df=regressors_df_future, n_historic_predictions=10, periods=50) + forecast = m.predict(df=future) + if PLOT: + m.plot(forecast) + m.plot_components(forecast) + m.plot_parameters() + plt.show() + + m = NeuralProphet( + epochs=EPOCHS, batch_size=BATCH_SIZE, learning_rate=LR, future_regressors_model="shared_neural_nets" + ) + df["A"] = df["y"].rolling(7, min_periods=1).mean() + df["B"] = df["y"].rolling(30, min_periods=1).mean() + df["C"] = df["y"].rolling(7, min_periods=1).mean() + df["D"] = df["y"].rolling(30, min_periods=1).mean() + + regressors_df_future = pd.DataFrame( + data={"A": df["A"][-50:], "B": df["B"][-50:], "C": df["C"][-50:], "D": df["D"][-50:]} + ) + df = df[:-50] + m = m.add_future_regressor(name="A") + m = m.add_future_regressor(name="B", mode="additive") + m = m.add_future_regressor(name="C", mode="multiplicative") + m = m.add_future_regressor(name="D", mode="multiplicative") + m.fit(df, freq="D") + future = m.make_future_dataframe(df=df, regressors_df=regressors_df_future, n_historic_predictions=10, periods=50) + forecast = m.predict(df=future) + if PLOT: + m.plot(forecast) + m.plot_components(forecast) + m.plot_parameters() + plt.show() + + m = NeuralProphet( + epochs=EPOCHS, batch_size=BATCH_SIZE, learning_rate=LR, future_regressors_model="shared_neural_nets_coef" + ) + df["A"] = df["y"].rolling(7, min_periods=1).mean() + df["B"] = df["y"].rolling(30, min_periods=1).mean() + df["C"] = df["y"].rolling(7, min_periods=1).mean() + df["D"] = df["y"].rolling(30, min_periods=1).mean() + + regressors_df_future = pd.DataFrame( + data={"A": df["A"][-50:], "B": df["B"][-50:], "C": df["C"][-50:], "D": df["D"][-50:]} + ) + df = df[:-50] + m = m.add_future_regressor(name="A") + m = m.add_future_regressor(name="B", mode="additive") + m = m.add_future_regressor(name="C", mode="multiplicative") + m = m.add_future_regressor(name="D", mode="multiplicative") + m.fit(df, freq="D") + future = m.make_future_dataframe(df=df, regressors_df=regressors_df_future, n_historic_predictions=10, periods=50) + forecast = m.predict(df=future) + if PLOT: + m.plot(forecast) + m.plot_components(forecast) + m.plot_parameters() + plt.show() + + def test_air_data(): log.info("TEST air_passengers.csv") df = pd.read_csv(AIR_FILE) diff --git a/tests/test_regularization.py b/tests/test_regularization.py index 5a56d09f6..83fa5cb60 100644 --- a/tests/test_regularization.py +++ b/tests/test_regularization.py @@ -68,7 +68,7 @@ def test_regularization_holidays(): daily_seasonality=False, growth="off", ) - m = m.add_country_holidays("US", regularization=REGULARIZATION) + m = m.add_country_holidays("US", regularization=0.001) m.fit(df, freq="D") to_reduce = [] diff --git a/tests/test_unit.py b/tests/test_unit.py index b6cdee783..d9b3931f1 100644 --- a/tests/test_unit.py +++ b/tests/test_unit.py @@ -108,8 +108,10 @@ def test_normalize(): ) df, _, _, _ = df_utils.prep_or_copy_df(df) # with config + m.config_normalization.init_data_params(df, m.config_lagged_regressors, m.config_regressors, m.config_events) _normalize(df=df, config_normalization=m.config_normalization) + m.config_normalization.unknown_data_normalization = True _normalize(df=df, config_normalization=m.config_normalization) m.config_normalization.unknown_data_normalization = False @@ -725,6 +727,7 @@ def test_newer_sample_weight(): learning_rate=LR, newer_samples_weight=newer_bias, newer_samples_start=0.0, + future_regressors_model="linear", # growth='off', n_changepoints=0, daily_seasonality=False,