Patch/m4

configs/cuda.toml

@@ -33,6 +33,7 @@ latent_dim = 1024
 [model.loss]
 loss = "nll"
 sigma_regularisation_factor = 1
+components = {primary = 1.0, weather = 1.0}
 
 [model.ssm]
 kernel = "s6"

notebooks/00_data_preparation.ipynb

@@ -7,8 +7,7 @@
    "source": [
     "# S4Casting: Data Preparation\n",
     "\n",
-	"This Source Code Form is subject to the terms of the Mozilla Public  License, v. 2.0. If a copy of the MPL was not distributed with this file, You can obtain one at http://mozilla.org/MPL/2.0/.",
-    "\n",
+    "This Source Code Form is subject to the terms of the Mozilla Public  License, v. 2.0. If a copy of the MPL was not distributed with this file, You can obtain one at http://mozilla.org/MPL/2.0/.\n",
     "This notebook contains scripts and utilities for preparing and formatting datasets for use with the S4Casting framework. Proper data formatting is crucial for effective model training and evaluation.\n",
     "\n",
     "## Overview\n",

notebooks/01_train_model.ipynb

@@ -7,8 +7,7 @@
    "source": [
     "# S4Casting: Training Pipeline\n",
     "\n",
-	"This Source Code Form is subject to the terms of the Mozilla Public  License, v. 2.0. If a copy of the MPL was not distributed with this file, You can obtain one at http://mozilla.org/MPL/2.0/.",
-    "\n",
+    "This Source Code Form is subject to the terms of the Mozilla Public  License, v. 2.0. If a copy of the MPL was not distributed with this file, You can obtain one at http://mozilla.org/MPL/2.0/.\n",
     "This notebook demonstrates the **training pipeline**, as in *scripts/train.py*.\n",
     "It walks through loading the configuration, setting up the model, optimizer, trainer, and running the training loop.\n",
     "\n",

notebooks/02_inference.ipynb

@@ -7,8 +7,7 @@
    "source": [
     "# Inference Pipeline\n",
     "\n",
-	"This Source Code Form is subject to the terms of the Mozilla Public  License, v. 2.0. If a copy of the MPL was not distributed with this file, You can obtain one at http://mozilla.org/MPL/2.0/.",
-    "\n",
+    "This Source Code Form is subject to the terms of the Mozilla Public  License, v. 2.0. If a copy of the MPL was not distributed with this file, You can obtain one at http://mozilla.org/MPL/2.0/.\n",
     "This notebook demonstrates how to perform **inference** using the previously trained S4Casting model.  \n",
     "The goal is to take recent time-series data (e.g., energy measurements) and generate short- or medium-term forecasts.\n",
     "\n",

notebooks/03_evaluation.ipynb

@@ -7,8 +7,7 @@
    "source": [
     "# Evaluation and Benchmarking of Model Forecasts\n",
     "\n",
-	"This Source Code Form is subject to the terms of the Mozilla Public  License, v. 2.0. If a copy of the MPL was not distributed with this file, You can obtain one at http://mozilla.org/MPL/2.0/.",
-    "\n",
+    "This Source Code Form is subject to the terms of the Mozilla Public  License, v. 2.0. If a copy of the MPL was not distributed with this file, You can obtain one at http://mozilla.org/MPL/2.0/.\n",
     "This notebook demonstrates how to evaluate and visualize the results of a previously trained **S4Casting** model.  \n",
     "It covers:\n",
     "1. Loading the saved inference output from disk.  \n",

notebooks/04_train_with_weather_time_location.ipynb

@@ -7,8 +7,7 @@
    "source": [
     "# Training with extra features: weather, time, and location\n",
     "\n",
-	"This Source Code Form is subject to the terms of the Mozilla Public  License, v. 2.0. If a copy of the MPL was not distributed with this file, You can obtain one at http://mozilla.org/MPL/2.0/.",
-    "\n",
+    "This Source Code Form is subject to the terms of the Mozilla Public  License, v. 2.0. If a copy of the MPL was not distributed with this file, You can obtain one at http://mozilla.org/MPL/2.0/.\n",
     "This notebook demonstrates how to train a model with additional contextual features:\n",
     "\n",
     "* Weather data aligned to your time series locations  \n",