From 0b42274e90c7932476f27b53f206b47f4b51c348 Mon Sep 17 00:00:00 2001 From: Tony Bagnall Date: Mon, 25 Nov 2024 14:05:56 +0000 Subject: [PATCH 1/4] remove shapelet notebook (#2391) --- examples/transformations/shapelets.ipynb | 4164 ---------------------- 1 file changed, 4164 deletions(-) delete mode 100644 examples/transformations/shapelets.ipynb diff --git a/examples/transformations/shapelets.ipynb b/examples/transformations/shapelets.ipynb deleted file mode 100644 index 1928e5bb4b..0000000000 --- a/examples/transformations/shapelets.ipynb +++ /dev/null @@ -1,4164 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "%load_ext autoreload\n", - "%autoreload 2" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Introduction" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This notebook explores the shapelet transformers implemented within aeon.\n", - "\n", - "Here you'll learn about the theory behind the shapelet transforms and get a first hand look at how shapelets can boost interpretability using our visualisation module.\n", - "\n", - "We will:\n", - "- Highlight differences between the four transformers, in order of publishment\n", - "- Explain the Gun/No gun problem, this will give the necessary domain knowledge to help with interpreting shapelets \n", - "- Visualise the time series from both classes\n", - "- for each transformer:\n", - " - Time how long it takes to fit the data\n", - " - Show what the data is transformed into\n", - " - Explore how different classifiers rank shapelets (only for first transformer)\n", - " - Visualise the extracted shapelets and group them by class\n", - " - Show the best and worst shapelet for each class using Viz module\n", - "- Interpret the shapelets, try get some insight to the problem to understand classifications.\n", - "- Summarise the findings provided by each transform\n", - "\n", - "If you want to learn about shapelets then go to one of our other shapelet notebooks found in [examples\\classification\\shapelet_based.ipynb](https://www.aeon-toolkit.org/en/stable/examples/classification/shapelet_based.html)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# A little bit about each transformer" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "RSAST: \n", - "RandomDilatedShapeletTransform: \n", - "RandomShapeletTransform: \n", - "SAST: \n" - ] - } - ], - "source": [ - "import warnings\n", - "\n", - "warnings.filterwarnings(\"ignore\")\n", - "from aeon.utils.discovery import all_estimators\n", - "\n", - "for k, v in all_estimators(\"transformer\", tag_filter={\"algorithm_type\": \"shapelet\"}):\n", - " print(f\"{k}: {v}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We have four transforms, which can be grouped into two categories. Two that focus on improving accuracy and two for improving scalability (reducing computation time). ST and RDST focus on classification accuracy while RSAST and SAST focus on reducing the shapelet generation time." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Shapelet Transform\n", - "The STC [1] introduced a groundbreaking concept by decoupling shapelet generation from the classification process. It achieved this by transforming time series data into a separate feature space that can be used with any supervised classifier - such as those available in scikit-learn. This significantly improved the accuracy compared to the initial shapelet tree algorithm [2], which was limited to using shapelets as splitting nodes. The STC iteratively initialises new shapelets, assesses their discriminative power, and removes self-similar ones, ensuring a robust selection of shapelets. Each step contains several novel contributions to the field, but for now, we will focus on the notion of transform.\n", - "\n", - "However, this approach comes with relatively high time complexity due to the need to evaluate a large number of shapelet candidates during the search for the most effective shapelets. This limitation inspired a future branch of transforms — to be covered later in this mini-series." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Scalable and Accurate Subsequence Transform\n", - "\n", - "SAST [3] streamlines shapelet learning by focusing on the idea that shapelets are shared among instances of the same class, thereby avoiding redundant candidates. Unlike previous methods that relied on generating and evaluating shapelet candidates from the entire training set, SAST bypasses this step, arguing that the classifier will inherently assess feature importance during training. This means shapelet selection is more relevant for post hoc interpretability rather than boosting classifier performance. \n", - "\n", - "Drawing inspiration from 'core object recognition' — where the brain requires only a few instances to recognize objects — SAST asserts that the best shapelets for a class are present in all its instances. \n", - "\n", - "While performance improves with more reference time series, there's a risk of overfitting. SAST reduces the search space by selecting only a few reference time series per class, thus avoiding the generation of variant shapelets that essentially represent the same pattern. By transforming the data using all subsequences, the classifier learns to focus on the most discriminative features, though this approach may lead to the curse of dimensionality and could be seen as lacking interpretability 'by design'.\n", - "\n", - "One limitation of this transform is its inability to handle multi-variate datasets." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Random Dilated Shapelet Transform\n", - "\n", - "RDST [4] boosts the discriminative power of shapelet-based classification by introducing two additional features for each shapelet within the transformed feature space:\n", - "\n", - "- the location where the shapelet best matches the time series,\n", - "- the frequency of its occurrence.\n", - "\n", - "A key innovation in RDST is dilation, which allows shapelets to stretch and become non-contiguous, effectively downsampling the data and mitigating noise. Shapelet candidates are randomly selected and then evaluated from the training data, balancing the prospects of improved accuracy with scalability and interpretability.\n", - "A possible limitation is that dilation makes the non-contiguous patterns more abstract and harder to be related back to the domain by experts." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Random Scalable and Accurate Subsequence Transform\n", - "\n", - "RSAST [5] builds on the SAST framework by employing a stratified sampling strategy for subsequence selection, further reducing the search space of shapelets, particularly for longer time series. RSAST starts by pre-computing weights using ANOVA, which guides the selection of initial points for subsequences. It then randomly selects a few time series per class and uses ACF and PACF to identify highly correlated lagged values, which serve as potential lengths for the shapelets. Shapelets are then extracted based on a predefined number of admissible starting points, transforming the original dataset into a feature space where each time series is represented by its distance to each selected subsequence. \n", - "\n", - "Along with SAST this transform is limited to univariate datasets." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# The Gunpoint classification problem" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The Gun/NoGun motion capture dataset is perhaps the most studied time\n", - "series classification problem in the literature. It is also univariate making it comaptible with all four of our transforms.\n", - "\n", - "The dataset consists of one female actor and one male actor making a motion with their hand, sometimes holding a gun and sometimes not. The classification problem is determining whether they were holding a gun or just miming the action. The problem is complicated by the fact the two actors differ in height (by 12 inches) and “style”, which you will notice when we visualise the time series.\n", - "\n", - "The two classes are:\n", - "\n", - "Gun-Draw: \n", - "\n", - "- the actors have their hands by their sides. They draw a replica gun from a hip-mounted holster, point it at a target for approximately one second, and then return it to the holster and place their hands to their sides.\n", - "\n", - "Point:\n", - "- the actors have their guns by their sides. They point their index fingers to a target for approximately one second and then return their hands to their sides. \n", - "\n", - "For both classes, the researchers tracked the centroid of the actor’s performing hand in both X- and Y-axes, which appeared to be highly correlated. Because of this, the data in the archive is only the X-axis — making this a univariate time series. In the dataset, Class 1 is “gun” and Class 2 is “no gun” (pointing)." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "---\n", - "Before we get into it, lets make some guesses about what we may notice. How would you distinguish someone pointing a gun from someone pointing their finger at you? What are the main differences?\n", - "\n", - "Firstly, a gun has noticeable weight, which could cause the arm to shake slightly when pointing. In contrast, when there’s no gun involved, the absence of a holster is significant. Without a holster, the actor has no designated place to return their hand after the movement, potentially leading to more variability in the final position. Additionally, the presence of a holster might cause a delay during the initial raising of the gun, making it a two-step motion as the gun is extracted from the holster." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "---" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Shape of the dataset: (200, 1, 150)\n", - "Number of channels = 1\n", - "Length of each time series = 150\n", - "Number of training samples = 50\n", - "Number of testing samples = 150\n" - ] - } - ], - "source": [ - "import numpy as np\n", - "\n", - "from aeon.datasets import load_classification\n", - "\n", - "X_gun_train, y_gun_train = load_classification(\"GunPoint\", split=\"train\")\n", - "X_gun_test, y_gun_test = load_classification(\"GunPoint\", split=\"test\")\n", - "\n", - "X_gun_full = np.concatenate(\n", - " (X_gun_train, X_gun_test), axis=0\n", - ") # Look at the entire dataset\n", - "\n", - "print(f\"Shape of the dataset: {X_gun_full.shape}\")\n", - "print(f\"Number of channels = {X_gun_train.shape[1]}\")\n", - "print(f\"Length of each time series = {X_gun_train.shape[2]}\")\n", - "print(f\"Number of training samples = {X_gun_train.shape[0]}\")\n", - "print(f\"Number of testing samples = {X_gun_test.shape[0]}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "As you can see, we have 200 different time series, each 150 data points long. The train/test split follows the original paper, with 50 samples taken for training and the rest for testing, with each actor and class equally represented.\n", - "\n", - "Note: Time series classification follows its own train/test split rather than the more general 70/30 found in wider ML. When the archive was set up, it was decided to make the train sets smaller so that the classification problems would be even more challenging to solve!\n", - "\n", - "I couldn’t find the frequency of the recorded time points, but knowing that they must be at uniform intervals and that actors point for around one second; we can estimate that the whole movement lasts no longer than 8 seconds." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "---\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The two graphs below have the time series from the dataset plotted for each class.\n", - "\n", - "*Can we find a difference between class 1 and 2 so that we can classify a given time series?* " - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "\n", - "class_1_indices = []\n", - "class_2_indices = []\n", - "\n", - "# Populate the class-specific lists with training set\n", - "for i in range(0, 50):\n", - " if y_gun_train[i] == \"1\":\n", - " class_1_indices.append(i)\n", - " elif y_gun_train[i] == \"2\":\n", - " class_2_indices.append(i)\n", - "\n", - "\n", - "fig, axs = plt.subplots(1, 2, figsize=(15, 6), sharey=True)\n", - "\n", - "# Plot the Gun class\n", - "for i in class_1_indices:\n", - " axs[0].plot(X_gun_train[i][0])\n", - "axs[0].set_title(\"Time series with Gun in the dataset.\")\n", - "axs[0].set_ylim(-3, 2.5) # Set the y-axis range for comparability\n", - "axs[0].legend([\"Class 1\"])\n", - "\n", - "# Plot the No Gun class\n", - "for i in class_2_indices:\n", - " axs[1].plot(X_gun_train[i][0])\n", - "axs[1].set_title(\"Time series with No Gun in the dataset.\")\n", - "axs[1].set_ylim(-3, 2.5) # Set the y-axis range for comparability\n", - "axs[1].legend([\"Class 2\"])\n", - "\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The two plots side by side are hard to look at and the time series as a whole look pretty similar between the two classes.\n", - "\n", - "In both classes we can roughly make out the groups of time series for the female and male actor, one is taller and points for shorter than the other. Unfortunately we aren't trying to classify the actor but the presence of a gun, a much more subtle difference. \n", - "\n", - "Looking at the whole pattern seems impractical.." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Exploring each transform's shapelets" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Lets take a look at a dataframe representing the testing data, each row is a time series and each column is the value at each time point. " - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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What the shapelet transforms achieve is mapping this data into a form that can be fed to any supervised classifier. They each achieve this slightly differently with their own takes on the transformed output." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In scientific tables, the convention is to have the independent variable in the columns and the dependent variables in the rows. In a time series dataset, time is considered the independent variable because it provides the reference point across which measurements are taken. Each column represents a specific time point. The different time series (or the variables within a time series) —represent the observed values at each time point—are the dependent variables, which are naturally placed in the rows." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Random Shapelet Transform" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In our exploration of RST we will use the same parameters as the published paper []. \n", - "\n", - "The aeon implementation matches the experimental parameters explored in the Gunpoint problem, the only parameter which is required to be set is max_shapelets to be 10. MAXLEN is set to the length of\n", - "the shortest time series in the training set. For MINLEN, they hardcoded the shortest possible length to three which is the minimum meaningful length. \n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "You can use the transform directly in aeon, but we will mostly explore it via the transform classifier because it lets play around with the ranking of shapelets." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Time taken to fit: 13.9589 seconds\n" - ] - }, - { - "data": { - "text/html": [ - "
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As you can see, we still have the 150 time series - the rows. But now, instead of the columns representing the value at each time point, the columns contain the shortest distance between each of the 10 best shapelets and the time series. This space is no longer a time series and can be treated as a typical classification problem.\n", - "\n", - "If you’re wondering how we decided on the 10 best shapelets, great! That’s a worthy question. During the shapelet generation process, we evaluate the discriminative power of each candidate using a quality measure, in this case, information gain. With all candidates measured, we chose the 10 most discriminative candidates, 5 for each class. For a deeper understanding I recommend reading the publish paper.\n", - "\n", - "The data frame isn’t very informative about the shapelets themselves… Let’s plot the 10 best shapelets found — the above columns." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "\n", - "gun_class = \"1\"\n", - "nogun_class = \"2\"\n", - "\n", - "shapelets = rst.shapelets\n", - "\n", - "shapelet_gun_vals = []\n", - "shapelet_gun_pos = []\n", - "shapelet_gun_indices = []\n", - "\n", - "shapelet_nogun_vals = []\n", - "shapelet_nogun_pos = []\n", - "shapelet_nogun_indices = []\n", - "\n", - "for idx, shapelet in enumerate(shapelets):\n", - " if shapelet[5] == gun_class:\n", - " shapelet_gun_vals.append(shapelet[6])\n", - " shapelet_gun_pos.append(shapelet[2])\n", - " shapelet_gun_indices.append(idx) # Store the original index\n", - "\n", - "for idx, shapelet in enumerate(shapelets):\n", - " if shapelet[5] == nogun_class:\n", - " shapelet_nogun_vals.append(shapelet[6])\n", - " shapelet_nogun_pos.append(shapelet[2])\n", - " shapelet_nogun_indices.append(idx) # Store the original index\n", - "\n", - "fig, axs = plt.subplots(1, 2, figsize=(15, 6), sharey=True)\n", - "\n", - "# Plot the first set of shapelets (Gun class)\n", - "for i in range(len(shapelet_gun_vals)):\n", - " x_values = [x + shapelet_gun_pos[i] for x in range(len(shapelet_gun_vals[i]))]\n", - " axs[0].plot(\n", - " x_values, shapelet_gun_vals[i], label=f\"Shapelet {shapelet_gun_indices[i]}\"\n", - " )\n", - "\n", - "axs[0].set_title(\"Shapelets from Gun class\")\n", - "axs[0].set_xlabel(\"Position\")\n", - "axs[0].set_ylabel(\"Values\")\n", - "axs[0].legend()\n", - "\n", - "# Plot the second set of shapelets (No Gun class)\n", - "for i in range(len(shapelet_nogun_vals)):\n", - " x_values = [x + shapelet_nogun_pos[i] for x in range(len(shapelet_nogun_vals[i]))]\n", - " axs[1].plot(\n", - " x_values, shapelet_nogun_vals[i], label=f\"Shapelet {shapelet_nogun_indices[i]}\"\n", - " )\n", - "\n", - "axs[1].set_title(\"Shapelets from No Gun class\")\n", - "axs[1].set_xlabel(\"Position\")\n", - "axs[1].set_ylabel(\"Values\")\n", - "axs[1].legend()\n", - "\n", - "\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Isn’t this much nicer than the complicated time series graph?\n", - "\n", - "We can more easily look for the essential differences between the two classes now. By generating the best 10 shapelets, we have already learned that there is something of interest during the lifting movement and the descending one; the two distinct groups of shapelets correspond to each class. This means there is a small pattern specific to raising the gun and one for lowering the empty hand. What could they be?\n", - "\n", - "A property of ST worth noting is that each class must have the same number of shapelets. This might leave out informative shapelets from one class to enforce this balance. But on the bright side, it lets us pay equal attention to the possible discriminating patterns of each class." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Counter({'1': 5, '2': 5})" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from collections import Counter\n", - "\n", - "shapelets = rst.shapelets\n", - "classes = []\n", - "for shapelet in shapelets:\n", - " classes.append(shapelet[5])\n", - "Counter(classes)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "A property of the Shapelet Transform worth noting is that each class must have the same number of shapelets. This might leave out informative shapelets from one class to enforce for this balance. But on the bright side, it lets us pay equal attention to the possible discriminating patterns of each class." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "---\n", - "Now, let’s look at how classifiers rank these shapelets relative to one another. Tree-based and linear classifiers are inherently interpretable, as you can study the weights in the model to understand which feature is more or less important. So let’s explore an example of each — a Logistic Regression and a Random Forest.\n", - "\n", - "I emphasise that the purpose is not to evaluate classification performance but to use the feature importance provided by the classifiers to aid in comparing shapelets later down the line. We will explore these two because the rankings are simple to understand; in practice, the Ridge Classifier may lead to better performance than the Logistic Regressor, but the regularisation can make understanding the shapelet rankings less intuitive." - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "from sklearn.ensemble import RandomForestClassifier\n", - "from sklearn.linear_model import LogisticRegression\n", - "\n", - "from aeon.classification.shapelet_based import ShapeletTransformClassifier\n", - "\n", - "rst_rf = ShapeletTransformClassifier(\n", - " estimator=RandomForestClassifier(ccp_alpha=0.01),\n", - " max_shapelets=10,\n", - " random_state=99, # Same random state as for the individual transform from above\n", - ").fit(X_gun_train, y_gun_train)\n", - "\n", - "\n", - "rst_lr = ShapeletTransformClassifier(\n", - " estimator=LogisticRegression(),\n", - " max_shapelets=10,\n", - " random_state=99, # Same random state as for the individual transform from above\n", - ").fit(X_gun_train, y_gun_train)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "With both STC variants fit, lets make sure that they have the same 10 shapelets as above." - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "\n", - "# First set of shapelets (from rst_lr)\n", - "shapelets_lr = rst_lr._transformer.shapelets\n", - "shapelet_vals_lr = []\n", - "shapelet_pos_lr = []\n", - "\n", - "for shapelet in shapelets_lr:\n", - " shapelet_vals_lr.append(shapelet[6])\n", - " shapelet_pos_lr.append(shapelet[2])\n", - "\n", - "# Second set of shapelets (from st_rf)\n", - "shapelets_rf = rst_rf._transformer.shapelets\n", - "shapelet_vals_rf = []\n", - "shapelet_pos_rf = []\n", - "\n", - "for shapelet in shapelets_rf:\n", - " shapelet_vals_rf.append(shapelet[6])\n", - " shapelet_pos_rf.append(shapelet[2])\n", - "\n", - "# Create a figure with 2 subplots arranged horizontally\n", - "fig, axs = plt.subplots(1, 2, figsize=(15, 6), sharey=True)\n", - "\n", - "# Plot the first set of shapelets (rst_lr)\n", - "for i in range(len(shapelet_vals_lr)):\n", - " x_values = [x + shapelet_pos_lr[i] for x in range(len(shapelet_vals_lr[i]))]\n", - " axs[0].plot(x_values, shapelet_vals_lr[i])\n", - "\n", - "axs[0].set_title(\"Shapelets from rst_lr\")\n", - "axs[0].set_xlabel(\"Position\")\n", - "axs[0].set_ylabel(\"Values\")\n", - "\n", - "# Plot the second set of shapelets (st_rf)\n", - "for i in range(len(shapelet_vals_rf)):\n", - " x_values = [x + shapelet_pos_rf[i] for x in range(len(shapelet_vals_rf[i]))]\n", - " axs[1].plot(x_values, shapelet_vals_rf[i])\n", - "\n", - "axs[1].set_title(\"Shapelets from st_rf\")\n", - "axs[1].set_xlabel(\"Position\")\n", - "\n", - "# Adjust layout to prevent overlap\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Great, now we can safely compare their rankings. We will use our shapelet visualisation module made specifically for aiding the interpretability of the transforms." - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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\n", - "
" - ], - "text/plain": [ - " Random forest Gun Random forest No Gun Logistic Regression Gun \\\n", - "Rank \n", - "0 0 0 5 \n", - "1 4 4 4 \n", - "2 2 2 1 \n", - "3 3 3 9 \n", - "4 7 7 0 \n", - "5 6 6 2 \n", - "6 1 1 7 \n", - "7 5 5 6 \n", - "8 8 8 8 \n", - "9 9 9 3 \n", - "\n", - " Logistic Regression No Gun \n", - "Rank \n", - "0 3 \n", - "1 8 \n", - "2 6 \n", - "3 7 \n", - "4 2 \n", - "5 0 \n", - "6 9 \n", - "7 1 \n", - "8 4 \n", - "9 5 " - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import pandas as pd\n", - "\n", - "from aeon.visualisation import ShapeletClassifierVisualizer\n", - "\n", - "rst_lr_vis = ShapeletClassifierVisualizer(rst_lr)\n", - "rst_rf_vis = ShapeletClassifierVisualizer(rst_rf)\n", - "\n", - "rst_rf_vis_index_0 = rst_rf_vis._get_shp_importance(0)[0] # gun\n", - "rst_rf_vis_index_1 = rst_rf_vis._get_shp_importance(1)[0] # no gun\n", - "rst_lr_vis_index_0 = rst_lr_vis._get_shp_importance(0)[0] # gun\n", - "rst_lr_vis_index_1 = rst_lr_vis._get_shp_importance(1)[0] # no gun\n", - "\n", - "# Store the elements at each position in the lists\n", - "elements_in_position = {\n", - " \"Rank\": list(range(10)),\n", - " \"Random forest Gun\": rst_rf_vis_index_0,\n", - " \"Random forest No Gun\": rst_rf_vis_index_1,\n", - " \"Logistic Regression Gun\": rst_lr_vis_index_0,\n", - " \"Logistic Regression No Gun\": rst_lr_vis_index_1,\n", - "}\n", - "\n", - "# Convert the dictionary to a DataFrame\n", - "pd.DataFrame(elements_in_position).set_index(\"Rank\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "As you can see, the different classifiers find the same shapelets to be of different importance.\n", - "\n", - "Two patterns emerge in the importance ranking; the Random Forest finds the same shapelets equally important for both classes, while the Logistic Regressor flips the importance for each class.\n", - "\n", - "This makes sense, given that RFs are tree-based and use information gain as the quality measure; the most discriminative shapelet is the best at distinguishing the two classes, so it’s just as important for both. While the importance of the Logistic Regressor is found using the coefficients assigned to the features (in this case, shapelets), a linear model assigns positive or negative coefficients to features based on how strongly they correlate with each class. This means a shapelet contributing positively to one class will contribute negatively to another, resulting in a flip in importance across classes. In the case of a multiclass problem, there wouldn’t be this flip in importance, instead a one-vs-all approach is implemented for shapelet importance.\n", - "\n", - "In our case, because distance is the metric, our visualisation module flips the coefficients to determine class importance. A positive weight means that as a value increases, the chance of being class 1 increases, but distance is inversely correlated to a class — the closer a shapelet fits a time series, the more likely it is class 1.\n", - "\n", - "This is a good time to remind you of an argument made by SAST. Ranking shapelets independently to the classifier may harm performance. We have just first hand seen how different classifier families rate the shapelets. What if the Logistic Regression Classifier really liked a shapelet ranked 15th according to information gain?" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "---\n", - "Lets take a look at each classifier's most important shapelet. \n", - "\n", - "But first we should understand how they are represented in our visalisation module.\n", - "\n", - "- Boxplot of Min (Top Left): The distribution of the minimum distances between the shapelet and each class. As expected, the shapelet fits class 0 more consistently than the other.\n", - "\n", - "- Shapelet Params (Bottom Left): This graph displays the shapelet’s pattern and length and states that normalisation was used.\n", - "\n", - "- Distance Vectors of Examples (Bottom Right): This graph compares how well the shapelet fits the two time series from the ‘Best Match on Examples’ graph, at each point.\n", - "\n", - "- Best Match on Examples (Top Right): This graph shows how the shapelet fits a time series from each class. The shapelet should, and does, align more closely with the time series of class 0.\n", - "\n", - "Due to label encoding Class 0 related to '1' which is Gun & Class 1 related to '2' which is No Gun." - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = rst_lr_vis.visualize_shapelets_one_class( # this is worst for other class\n", - " X_gun_test,\n", - " y_gun_test,\n", - " 0, # Gun\n", - " id_example_class=1,\n", - " id_example_other=1,\n", - " figure_options={\"figsize\": (18, 12), \"nrows\": 2, \"ncols\": 2},\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "If you’re wondering why the same shapelet looks different when fit to the orange and green time series, that is due to the normalisation parameter; this will become even more apparent in later graphs.\n", - "\n", - "This parameter normalises the distance between the shapelet and the subseries enabling scale invariance.\n", - "This means, no matter the amplitude of the pattern, it will be noticed if it’s present. Think of the two actors who have different heights, if they both shrug their shoulders when holding the gun the change in height will be different but normalisation abstracts the pattern to be found in them both." - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = rst_rf_vis.visualize_shapelets_one_class(\n", - " X_gun_test,\n", - " y_gun_test,\n", - " 0, # Gun but RF rankes irrespective to class\n", - " id_example_class=1,\n", - " id_example_other=1,\n", - " figure_options={\"figsize\": (18, 12), \"nrows\": 2, \"ncols\": 2},\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Here, we learn that for the Logistic Regressor, the most important shapelet for discriminating the Gun class is found during the raise action rather than descent. This seems intuitive enough; the best shapelet for a class should come from that class. The shapelet’s fit to the time series from the Gun class is consistent. At the same time, there is relatively more variation in its fit for the other, which is why it’s not very discriminative for the No Gun class. Again, a shapelet from one class, by definition, should not fit the other better.\n", - "\n", - "Interestingly, for the Random Forest, the best shapelet is related to the raise, which comes from the Gun Class. This is interesting because the first paper using shapelets found a shapelet from the No Gun class to be the most discriminative. This goes to show the impact classifiers have on ranked shapelets.\n", - "\n", - "Remember, the importance of the Random Forest’s feature is independent of class. The boxplot reemphasises that the shapelet is ranked first for both classes by the slight distance variance. There is a clear separation between the two, which relates to reducing entropy.\n", - "\n", - "By seeing the shapelet’s best fit on the opposing class, we identify the pattern in its class and not in the other. By the definition of shapelets, we know that the pattern of a class’ shapelet won’t be found in the other class’ time series — we don’t need to plot this shapelet against all instances of the other class to validate the claim.\n", - "\n", - "In both shapelets, a unique two-step raise is highlighted when superposed on top of a time series from the No Gun class, which rises in one go. This could be explained by the idea that the gun in the holster takes some time to get out, whereas the basic point action requires the actor to raise their hand.\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "---\n", - "Having looked at the best shapelets, maybe we can get additional insight from the worst ones too." - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = rst_lr_vis.visualize_shapelets_one_class( # this is best for other class\n", - " X_gun_test,\n", - " y_gun_test,\n", - " 0, # Gun\n", - " best=False, # Showing worst shapelet for Gun which should be best for No Gun\n", - " id_example_class=2,\n", - " id_example_other=2,\n", - " figure_options={\"figsize\": (18, 12), \"nrows\": 2, \"ncols\": 2},\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = rst_rf_vis.visualize_shapelets_one_class(\n", - " X_gun_test,\n", - " y_gun_test,\n", - " 0, # Gun but RF rankes irrespective to class\n", - " best=False,\n", - " id_example_class=2,\n", - " id_example_other=2,\n", - " figure_options={\"figsize\": (18, 12), \"nrows\": 2, \"ncols\": 2},\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "It seems intuitive to think that the worst shapelet will be further from its class time series than the best. But this is an erroneous generalisation; what makes a shapelet valuable to an RF classifier is not how well it fits its own class but how differently it fits the other. The perfect shapelet will fit its class while completely incompatible with the other. That’s why if you compare the distance plots of the best and worst shapelets, they’re not that different; also, take into account these are the 10 best out of the 10,000 candidates. We should really be saying ‘least best’.\n", - "\n", - "Observing the best No Gun shapelet superposed on top of a Gun time series shows us that the described pattern isn’t present anywhere. The best match is still far off (and in the wrong place). I know shapelets are phase invariant, but for this problem, the location of a pattern matters. Instead of observing the Best match plot, we can speculate how the descent differs between the Gun and No Gun classes by comparing the best shapelet for the No Gun class according to the Logistic Regressor and the worst overall shapelet according to the Random Forest, which also comes from the No Gun class — we see that the better discriminating shapelet has a deeper dip.\n", - "\n", - "In fact, looking at the Best match plot for the Random Forest shapelet, we see that the No Gun time series has a dip, unlike the Gun series. Let’s call this ‘overshoot’; maybe because the actor isn’t holding a prop, they swing their arm past the holster.\n", - "\n", - "The reason the worst shapelet is the worst for the Random forest is shown in the box plots of the distance distribution for both very similar classes. This means there is a less clear threshold for splitting the two classes." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Random Dilated Shapelet Transform" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Time taken to fit: 73.4681 seconds\n" - ] - }, - { - "data": { - "text/html": [ - "
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" - ], - "text/plain": [ - " 0 1 2 3 4 5 6 7 8 \\\n", - "0 5.853639 10.0 0.0 0.764625 79.0 6.0 3.088977 44.0 9.0 \n", - "1 0.762688 19.0 13.0 0.495214 64.0 6.0 4.329565 106.0 0.0 \n", - "2 10.948034 17.0 0.0 5.498243 109.0 0.0 1.098997 34.0 9.0 \n", - "3 4.886783 16.0 8.0 0.788170 78.0 6.0 2.858796 52.0 6.0 \n", - "4 1.179179 17.0 16.0 0.481140 64.0 6.0 2.946776 53.0 4.0 \n", - ".. ... ... ... ... ... ... ... ... ... \n", - "145 0.809235 13.0 19.0 0.872016 57.0 6.0 1.924077 117.0 4.0 \n", - "146 2.668172 19.0 9.0 0.586673 72.0 7.0 2.104301 60.0 6.0 \n", - "147 1.689218 19.0 13.0 0.606392 68.0 7.0 3.185737 55.0 6.0 \n", - "148 8.345075 4.0 0.0 0.714840 92.0 5.0 2.370086 32.0 8.0 \n", - "149 7.117408 13.0 0.0 0.454250 90.0 6.0 2.002410 49.0 11.0 \n", - "\n", - " 9 ... 20 21 22 23 24 25 26 \\\n", - "0 7.462829 ... 12.0 2.090639 29.0 11.0 0.873707 32.0 5.0 \n", - "1 11.238291 ... 14.0 1.275651 16.0 12.0 0.584034 50.0 11.0 \n", - "2 0.322451 ... 1.0 1.761859 87.0 7.0 1.073433 22.0 4.0 \n", - "3 8.607380 ... 13.0 1.433407 9.0 15.0 0.468660 39.0 8.0 \n", - "4 10.832423 ... 14.0 2.500612 42.0 9.0 0.678392 45.0 19.0 \n", - ".. ... ... ... ... ... ... ... ... ... \n", - "145 11.111689 ... 13.0 2.319362 37.0 12.0 0.420155 42.0 17.0 \n", - "146 10.939275 ... 14.0 2.359284 47.0 7.0 0.625460 52.0 10.0 \n", - "147 10.847575 ... 14.0 2.062507 41.0 7.0 0.714770 107.0 9.0 \n", - "148 1.622089 ... 5.0 2.061232 20.0 6.0 1.282659 25.0 4.0 \n", - "149 6.014640 ... 7.0 2.127951 31.0 10.0 0.755017 35.0 5.0 \n", - "\n", - " 27 28 29 \n", - "0 0.708693 10.0 12.0 \n", - "1 3.946019 21.0 0.0 \n", - "2 7.946710 19.0 0.0 \n", - "3 0.709317 15.0 12.0 \n", - "4 3.049049 19.0 0.0 \n", - ".. ... ... ... \n", - "145 3.625309 17.0 0.0 \n", - "146 2.915027 25.0 1.0 \n", - "147 2.913775 21.0 1.0 \n", - "148 3.439877 3.0 0.0 \n", - "149 1.522178 13.0 9.0 \n", - "\n", - "[150 rows x 30 columns]" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import time\n", - "\n", - "from aeon.transformations.collection.shapelet_based import (\n", - " RandomDilatedShapeletTransform,\n", - ")\n", - "\n", - "shapelet_lengths = array = [9, 11, 13]\n", - "\n", - "start_time = time.time()\n", - "rdst = RandomDilatedShapeletTransform(\n", - " max_shapelets=10, shapelet_lengths=shapelet_lengths, random_state=99\n", - ").fit(X_gun_train, y_gun_train)\n", - "end_time = time.time()\n", - "\n", - "# Show the elapsed transform time\n", - "rdst_elapsed_time = end_time - start_time\n", - "print(f\"Time taken to fit: {rdst_elapsed_time:.4f} seconds\")\n", - "\n", - "pd.DataFrame(rdst.transform(X_gun_test))" - ] - }, - { - "attachments": { - "image.png": { - "image/png": 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" - } - }, - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The RDST has 3 times more features than ST for the same number of shapelets. That is because, along with the shortest distance to each time series, every shapelet's number of occurrences (SO) and the position of the closest fit (argmin) are used as features. Because of these two additional features, we now have the ability to discriminate time series in the following four ways:\n", - "- If a shapelet is present in one class and not the other.\n", - "- If a shapelet is present in both classes but in different locations.\n", - "- If a shapelet is present in both classes but in different scales.\n", - "- If a shapelet is present in both classes but occurs a different number of times.\n", - "\n", - "![image.png](attachment:image.png)\n", - "\n", - "Looking back to the data frame, we see that the features aren't grouped nor ordered; we don't need to tell the classifier which features relate to which shapelet because it will learn these implicit relations during training. Shuffling the columns would have no impact on performance." - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [], - "source": [ - "from sklearn.linear_model import LogisticRegression\n", - "\n", - "from aeon.classification.shapelet_based import RDSTClassifier\n", - "\n", - "rdst_lr = RDSTClassifier(\n", - " estimator=LogisticRegression(max_iter=500),\n", - " max_shapelets=10,\n", - " save_transformed_data=True,\n", - " shapelet_lengths=[9, 11, 13],\n", - " random_state=99,\n", - ").fit(X_gun_train, y_gun_train)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "While STC, by default, explores the whole possible range of shapelet lengths, for RDST it can be a good idea to restrict the lengths to give more room for dilation for the GunPoint problem. Lengths 9, 11, and 13 can be used following the convention set in the paper.\n", - "\n", - "With our transformer (and classifier) fit, let's examine which 10 shapelets were extracted using RDST." - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "\n", - "shapelets_lr = rdst_lr._transformer.shapelets_\n", - "shapelet_vals_lr = shapelets_lr[0]\n", - "shapelet_pos_lr = shapelets_lr[1]\n", - "shapelet_dilation = shapelets_lr[3]\n", - "shapelet_classes = shapelets_lr[8]\n", - "\n", - "fig, axs = plt.subplots(1, 2, figsize=(15, 6), sharey=True)\n", - "\n", - "for idx, shapelet in enumerate(shapelet_vals_lr):\n", - " dilation = shapelet_dilation[idx]\n", - " startpoint = shapelet_pos_lr[idx]\n", - " x_values = [startpoint + i * dilation for i in range(len(shapelet[0]))]\n", - "\n", - " if shapelet_classes[idx] == 0:\n", - " axs[0].plot(x_values, shapelet[0], label=f\"S: {idx}, D: {dilation}\")\n", - " else:\n", - " axs[1].plot(x_values, shapelet[0], label=f\"S: {idx}, D: {dilation}\")\n", - "\n", - "\n", - "axs[0].set_title(\"Shapelets from Gun class\")\n", - "axs[0].set_xlabel(\"Time point\")\n", - "axs[0].set_ylabel(\"Value\")\n", - "axs[0].legend()\n", - "axs[0].set_xlim(0, 150)\n", - "\n", - "axs[1].set_title(\"Shapelets from No Gun class\")\n", - "axs[1].set_xlabel(\"TIme point\")\n", - "axs[1].legend()\n", - "axs[1].set_xlim(0, 150)\n", - "\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "As you can see we have very different shapelets extracted with RDST. Some look jagged because of the dilation - comment out the random state parameter and run this cell a few times. The generated shapelets appear a little more chaotic because the shapelet candidate space is much larger and is no longer limited to contiguous subseries due to dilation. Using the same number of shapelet candidates (10,000) but in a larger space leads to more potential shapelets not being considered. This is the trade-off to maintain a degree of scalability; if you desire better accuracy, by all means, increase the max_shapelets parameter.\n", - "\n", - "At this point, dilation does appear to harm interpretability since dilated shapelets are less familiar to domain experts and plotting them on top of time series often leads to them not fitting as perfectly as the other transforms. But we have more interpretable power through exploring both global and local patterns, as you'll see later." - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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Logistic Regression classifier GunLogistic Regression classifier No Gun
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" - ], - "text/plain": [ - " Logistic Regression classifier Gun \\\n", - "Rank \n", - "0 9 \n", - "1 0 \n", - "2 1 \n", - "3 7 \n", - "4 5 \n", - "5 3 \n", - "6 2 \n", - "7 8 \n", - "8 4 \n", - "9 6 \n", - "\n", - " Logistic Regression classifier No Gun \n", - "Rank \n", - "0 6 \n", - "1 4 \n", - "2 8 \n", - "3 2 \n", - "4 3 \n", - "5 5 \n", - "6 7 \n", - "7 1 \n", - "8 0 \n", - "9 9 " - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import pandas as pd\n", - "\n", - "from aeon.visualisation import ShapeletClassifierVisualizer\n", - "\n", - "rdst_lr_vis = ShapeletClassifierVisualizer(rdst_lr)\n", - "\n", - "rdst_lr_vis_index_0 = pd.Series(rdst_lr_vis._get_shp_importance(0)[0]).to_list()\n", - "rdst_lr_vis_index_1 = pd.Series(rdst_lr_vis._get_shp_importance(1)[0]).to_list()\n", - "\n", - "elements_in_position = {\n", - " \"Rank\": list(range(len(rdst_lr_vis_index_0))),\n", - " \"Logistic Regression classifier Gun\": rdst_lr_vis_index_0,\n", - " \"Logistic Regression classifier No Gun\": rdst_lr_vis_index_1,\n", - "}\n", - "\n", - "df = pd.DataFrame(elements_in_position).set_index(\"Rank\")\n", - "df" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Ranking RDST shapelets is a bit trickier than ST because there are three separate features for each shapelet, we find a shapelet's importance by summing the importance of the three features corresponding to it.\n", - "\n", - "Remember how distance is inversely correlated to the class? For simplicity, we assume that SO and argmin are directly correlated to it. However, in practice, too many appearances of a shapelet could mean it's too generic, and a larger argmin value just means that the shapelet occurred further down in the time series. Naturally, the trained classifier will find the most important distance features, so our crude estimation of importance can hold up." - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = rdst_lr_vis.visualize_shapelets_one_class(\n", - " X_gun_test,\n", - " y_gun_test,\n", - " 0, # Gun\n", - " id_example_class=1,\n", - " id_example_other=1,\n", - " figure_options={\"figsize\": (18, 12), \"nrows\": 2, \"ncols\": 3},\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = rdst_lr_vis.visualize_shapelets_one_class(\n", - " X_gun_test,\n", - " y_gun_test,\n", - " 0, # Gun\n", - " best=False, # This is best for No Gun\n", - " id_example_class=10,\n", - " id_example_other=4,\n", - " figure_options={\"figsize\": (18, 12), \"nrows\": 2, \"ncols\": 3},\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Look at that, we have even more angles to help us understand the Gunpoint problem.\n", - "These plots introduce three new pieces of information:\n", - "- A box plot of the best match positions for each class.\n", - "- A box plot of the number of occurrences for each class.\n", - "- The threshold value for accepting a subseries as a shapelet match.\n", - "\n", - "We also get the see how the extracted shapelet looks prior to the dilation." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The above two plots show the best shapelet for each class according to the Logistic Regressor. Looking at the Shapelet Params graph (bottom middle), we can still distinguish the patterns described in the STC shapelets, the two-stage lift for Gun and the 'overshoot' for No Gun. However, I should admit that the dilation in this particular time series problem makes the interpretation a bit convoluted. Looking at the best No Gun shapelet, it is missing the critical 'overshoot' which leads to it fitting both classes pretty similarly; it is really thanks to the argmin & SO features that we can somewhat distinguish the two classes - the shapelet tends to fit the No Gun class earlier in the time series while occurring less often. The accuracy would be poor if the classification was based purely on this individual shapelet. Thankfully, the decisions were based on a conjunction of all 10 shapelets.\n", - "\n", - "Suppose you consider dilation as a means of downsampling the data. The more abstract representation makes sense. In that case, these two shapelets capture the general pattern with less noise - making them more generalisable. For this problem, where the time series are relatively short and not recorded at a high frequency, there isn't much need to mitigate noise.\n", - "\n", - "We can further understand the best Gun shapelet by using the additional box plots. We can see that the shapelet, pre-dilation, is extracted from the raise in two steps. Dilating it by 5 stretches this pattern out, allowing it to fit the different styles of the actors. It kind of enables a partial scale invariance in the x-axis. However, all this is useful only after analysing the box plots.\n", - "\n", - "Initially, we see that the pattern fits the Gun class with quite some variance; this can be explained by the abstraction caused by the dilation. Curiously, after this level of abstraction, there is still a clear divide in fit between the two classes. This level of abstraction appears suitable for generalising to the Gun class while still not capturing the No Gun pattern. The shapelet still contains that 'step' in the middle of the raise.\n", - "\n", - "We then learn that the shapelet is first found later than it is for the No Gun class; I speculate that's because it never truly fits the No Gun time series, so the best fit is as good as any. This idea is supported by the last box plot showing the SO distribution. The shapelet is never found for No Gun while being present up to 12 times for some Gun time series. If you recall the time series plot in my GunPoint article, the raise takes around 30 time points, so there is much room for the shapelet to closely match several times. Looking at the Distance vectors plot we see that, in this example, the 14 occurrences come in two clusters. I'm curious to experiment with changing SO to only count non-adjacent occurrences.\n", - "I think not normalising the shapelet gave it a more discriminative ability than the Gun shapelet, which is one of the benefits of RDST. It randomly assigns the normalisation parameter according to an input probability; you don't need to know what you seek in advance.\n", - "\n", - "The fact that it's more straightforward to understand how it is the best for the Gun shapelet than the No Gun shapelet may suggest that it's more useful. It would make sense for the more interpretable shapelets to be more discriminative for ML algorithms. The RF ranked the No Gun shapelet as most useful in the last post; perhaps reinforcing that notion." - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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Random Forest Ranking
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" - ], - "text/plain": [ - " Random Forest Ranking\n", - "Rank \n", - "0 9\n", - "1 2\n", - "2 5\n", - "3 8\n", - "4 0\n", - "5 4\n", - "6 3\n", - "7 7\n", - "8 6\n", - "9 1" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import pandas as pd\n", - "from sklearn.ensemble import RandomForestClassifier\n", - "\n", - "from aeon.classification.shapelet_based import RDSTClassifier\n", - "from aeon.visualisation import ShapeletClassifierVisualizer\n", - "\n", - "rdst_rf = RDSTClassifier(\n", - " estimator=RandomForestClassifier(ccp_alpha=0.01),\n", - " max_shapelets=10,\n", - " save_transformed_data=True,\n", - " shapelet_lengths=[9, 11, 13],\n", - " random_state=99,\n", - ").fit(X_gun_train, y_gun_train)\n", - "\n", - "rdst_rf_vis = ShapeletClassifierVisualizer(rdst_rf)\n", - "\n", - "rdst_rf_vis_index_0 = pd.Series(rdst_rf_vis._get_shp_importance(0)[0]).to_list()\n", - "\n", - "elements_in_position = {\n", - " \"Rank\": list(range(len(rdst_rf_vis_index_0))),\n", - " \"Random Forest Ranking\": rdst_rf_vis_index_0,\n", - "}\n", - "\n", - "df = pd.DataFrame(elements_in_position).set_index(\"Rank\")\n", - "df" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Cross referencing the shapelet to its label we see that it is shapelet 6…\n", - "\n", - "Look at that! It is the 2nd worst shapelet according to the RF." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Scalable and Accurate Subsequence Transform" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Time taken to fit: 0.1421 seconds\n" - ] - }, - { - "data": { - "text/html": [ - "
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Then, SAST generates all the subsequences of the specified lengths from these reference time series. So, all lengths from every starting point. These subsequences are then used to transform a time series dataset, replacing each time series with its distance vector to each subsequence.\n", - "\n", - "Unlike the previous two transforms, SAST doesn’t select the best subseries, so we need to choose 10 to visualise ourselves before we plot." - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [], - "source": [ - "from sklearn.linear_model import LogisticRegression\n", - "\n", - "from aeon.classification.shapelet_based import SASTClassifier\n", - "\n", - "sast_lr = SASTClassifier(\n", - " classifier=LogisticRegression(),\n", - " seed=0,\n", - " nb_inst_per_class=10,\n", - ").fit(X_gun_train, y_gun_train)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We need to fit the SAST classifier to obtain the Logistic Regressor’s feature rankings. Rather than only using one reference time series, 10 will drive extra insight. In the case where subsampling completely\n", - "removes one actor from the training data, the performance on the test set, where the two\n", - "actors are present, could be reduced." - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [], - "source": [ - "from operator import itemgetter\n", - "\n", - "feature_importance = abs(sast_lr._pipeline[-1].coef_[0])\n", - "\n", - "subseries = sast_lr._transformer._kernel_orig\n", - "norm_subseries = sast_lr._transformer._kernels\n", - "start_pos = sast_lr._transformer._start_points\n", - "classes = sast_lr._transformer._classes\n", - "time_series_indexes = sast_lr._transformer._source_series\n", - "# Combine shapelets with their feature importance, start positions, and class info\n", - "features = zip(\n", - " subseries,\n", - " norm_subseries,\n", - " feature_importance,\n", - " start_pos,\n", - " classes,\n", - " time_series_indexes,\n", - ")\n", - "\n", - "# Sort features by importance (descending order)\n", - "sorted_features = sorted(features, key=itemgetter(2), reverse=True)\n", - "\n", - "# Extract sorted shapelets, start positions, and class info\n", - "subseries = [feature[0] for feature in sorted_features]\n", - "norm_subseries = [feature[1] for feature in sorted_features]\n", - "start_positions = [feature[3] for feature in sorted_features]\n", - "shapelet_classes = [feature[4] for feature in sorted_features]\n", - "time_series_indices = [feature[5] for feature in sorted_features]\n", - "shapelet_lengths = [len(feature[0]) for feature in sorted_features]\n", - "\n", - "num_shapelets = 10\n", - "# Get the top 10 shapelets with their start positions and class information\n", - "top_subseries = [\n", - " (subseries, norm_subseries, start_pos, cls)\n", - " for subseries, norm_subseries, start_pos, cls in zip(\n", - " subseries, norm_subseries, start_positions, shapelet_classes\n", - " )\n", - "]\n", - "shapelets = top_subseries[:num_shapelets]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now we can select the top 10 shapelets. Those which are most strongly correlated to each class." - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n" - ] - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "\n", - "# Separate the shapelets by class\n", - "class_1_shapelets = [\n", - " (norm_shapelet, start_pos)\n", - " for shapelet, norm_shapelet, start_pos, cls in shapelets\n", - " if cls == \"1\"\n", - "]\n", - "class_2_shapelets = [\n", - " (norm_shapelet, start_pos)\n", - " for shapelet, norm_shapelet, start_pos, cls in shapelets\n", - " if cls == \"2\"\n", - "]\n", - "\n", - "# Create a figure with two subplots side by side\n", - "fig, axes = plt.subplots(1, 2, figsize=(20, 8), sharey=True)\n", - "\n", - "# Plot shapelets for Gun\n", - "for i, (shapelet, start_pos) in enumerate(class_1_shapelets, start=1):\n", - " axes[0].plot(\n", - " range(start_pos, start_pos + len(shapelet)),\n", - " shapelet,\n", - " label=f\"Class 1 Shapelet {i}\",\n", - " linewidth=2,\n", - " )\n", - "axes[0].set_xlabel(\"Time\")\n", - "axes[0].set_ylabel(\"Value\")\n", - "axes[0].set_title(\"Top Shapelets for Gun\")\n", - "axes[0].legend()\n", - "axes[0].grid(True)\n", - "\n", - "# Plot shapelets for No Gun\n", - "for i, (shapelet, start_pos) in enumerate(class_2_shapelets, start=1):\n", - " axes[1].plot(\n", - " range(start_pos, start_pos + len(shapelet)),\n", - " shapelet,\n", - " label=f\"Class 2 Shapelet {i}\",\n", - " linewidth=2,\n", - " )\n", - "axes[1].set_xlabel(\"Time\")\n", - "axes[1].set_ylabel(\"Value\")\n", - "axes[1].set_title(\"Top Shapelets for No Gun\")\n", - "axes[1].grid(True)\n", - "\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Unlike before, we aren’t plotting the original shapelets but the shapelets once they’re normalised. Visualising them wouldn’t be helpful because many of them come from the same time series; there would be much overlap. Instead, the normalised version shows us the specific patterns the shapelet represents. It lets us distinguish each individual shapelet in our following plot. Also, SAST uses the normalised shapelet for the distance computations, so it’s appropriate to see them in this form.\n", - "\n", - "Looking at the shapelet plot, we learn that the 10 best shapelets from SAST are all from the No Gun class and appear to be coming from three out of the ten reference time series at around the same point with a roughly similar length. Let’s verify this by summarising their characteristics in a table." - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "import pandas as pd\n", - "\n", - "# Create a DataFrame for the top 10 shapelets\n", - "data = {\n", - " \"Time Series Index\": time_series_indices[:num_shapelets],\n", - " \"Start Position\": start_positions[:num_shapelets],\n", - " \"Shapelet Length\": shapelet_lengths[:num_shapelets],\n", - " \"Class\": shapelet_classes[:num_shapelets], # New column for shapelet classes\n", - "}\n", - "df = pd.DataFrame(data)\n", - "\n", - "# Define the priority order for sorting\n", - "priority_order = [\"Time Series Index\", \"Start Position\", \"Shapelet Length\", \"Class\"]\n", - "\n", - "# Sort the DataFrame by the priority columns\n", - "df_sorted = df.sort_values(by=priority_order, ascending=True)\n", - "\n", - "# Plot the table\n", - "fig, ax = plt.subplots(figsize=(12, 6)) # Adjust the figure size as needed\n", - "ax.axis(\"off\") # Hide the axis\n", - "\n", - "# Create the table\n", - "table = ax.table(\n", - " cellText=df_sorted.values,\n", - " colLabels=df_sorted.columns,\n", - " cellLoc=\"center\",\n", - " loc=\"center\",\n", - " bbox=[0, 0, 1, 1],\n", - ")\n", - "\n", - "table.auto_set_font_size(False)\n", - "table.set_fontsize(10)\n", - "table.auto_set_column_width(df_sorted.columns)\n", - "\n", - "plt.title(\"Top 10 Shapelets Information\")\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Yes, just as we thought.\n", - "\n", - "The first of the stwo figures show the importance of scale & phase invariance in the shapelets; we can see that they all share the pattern, just at different heights & points in time.\n", - "\n", - "SAST has provided us with a new insight into GunPoint. However, it feels contradictory to the findings from the past two transforms. Given how similar all 10 shapelets are in position & length, this problem only has one particularly correlated pattern — the overshoot found in No Gun. You may wonder where those shapelets that we previously discovered from to the Gun class lie…" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sast_lr_vis = ShapeletClassifierVisualizer(sast_lr)\n", - "\n", - "fig = sast_lr_vis.visualize_shapelets_one_class(\n", - " X_gun_test,\n", - " y_gun_test,\n", - " 0, # Gun\n", - " id_example_class=1,\n", - " id_example_other=1,\n", - " figure_options={\"figsize\": (18, 12), \"nrows\": 2, \"ncols\": 2},\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Why doesn’t this look familiar? Shouldn’t it show a two step ascent?\n", - "\n", - "Looking at the boxplot of min (top left plot), the distance distribution for Gun has variance and overlaps with the other class. Technically, we can’t call this a shapelet since it isn’t highly discriminative. So, let’s not focus on it for now; it won’t give us any insight like the previous examples. Looks like, SAST didn’t find (or doesn’t agree with) the two-step raise being discriminative to the Gun class." - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Best class one shapelet is ranked 357\n" - ] - } - ], - "source": [ - "# Filter shapelets by class\n", - "best_class_one_shp = [\n", - " (shapelet, start_pos, index)\n", - " for index, (shapelet, start_pos, cls) in enumerate(\n", - " zip(top_subseries, start_positions, shapelet_classes)\n", - " )\n", - " if cls == \"1\"\n", - "][0]\n", - "\n", - "print(\"Best class one shapelet is ranked\", best_class_one_shp[2])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "According to SAST, there are 356 more strongly correlated shapelets from the No Gun class. This is a little misleading because SAST does not have an equivalent to eliminating self-similar shapelets like ST and RDST. Nevertheless, We can question our previous theory, that the Gun shapelets are more important. Despite this small obstacle in our reasoning, atleast we are still encountering the recurring theme that the two classes are distinguished during the descent. Let’s see if the (not-so-great) Gun shapelet still looks the same as what we have seen up until now." - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = sast_lr_vis.visualize_shapelets_one_class(\n", - " X_gun_test,\n", - " y_gun_test,\n", - " 0, # Gun\n", - " best=False, # Will show best No Gun\n", - " id_example_class=1,\n", - " id_example_other=4,\n", - " figure_options={\"figsize\": (18, 12), \"nrows\": 2, \"ncols\": 2},\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Looking at the boxplot of min plot, this shapelet consistently fits the the Gun class much worse than the No Gun class. The variance in the No Gun class can be caused by noise, such as the fact that there are two different actors with different styles. Still, we can be confident that ‘overshoot’ doesn’t occur for the Gun class; especially when seeing the ‘best’ match on the Gun class, it is entirely in the wrong place and is only considered a fit because normalisation reveals that the flat datapoints following the dip are similar to when the actor holds the gun in place while pointing." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Random and Scalable Subsequence Transform" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Time taken to fit: 1.9341 seconds\n" - ] - } - ], - "source": [ - "import time\n", - "\n", - "from aeon.transformations.collection.shapelet_based import RSAST\n", - "\n", - "start_time = time.time()\n", - "rsast = RSAST().fit(X_gun_train, y_gun_train)\n", - "end_time = time.time()\n", - "\n", - "# Calculate and print the elapsed time\n", - "rsast_elapsed_time = end_time - start_time\n", - "print(f\"Time taken to fit: {rsast_elapsed_time:.4f} seconds\")" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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Remember how all the shapelets came from around the same place and were of a similar length? Using statistical methods RSAST reduces this redundancy, rather than conducting an exhaustive search for the candiate shapelets within the reference timeseries." - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": {}, - "outputs": [], - "source": [ - "from sklearn.linear_model import LogisticRegression\n", - "\n", - "from aeon.classification.shapelet_based import RSASTClassifier\n", - "\n", - "rsast_lr = RSASTClassifier(\n", - " classifier=LogisticRegression(),\n", - " seed=0,\n", - " nb_inst_per_class=10,\n", - ").fit(X_gun_train, y_gun_train)" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "metadata": {}, - "outputs": [], - "source": [ - "from operator import itemgetter\n", - "\n", - "feature_importance = abs(rsast_lr._pipeline[-1].coef_[0])\n", - "\n", - "subseries = rsast_lr._transformer._kernel_orig\n", - "norm_subseries = rsast_lr._transformer._kernels\n", - "start_pos = rsast_lr._transformer._start_points\n", - "classes = rsast_lr._transformer._classes\n", - "time_series_indexes = rsast_lr._transformer._source_series\n", - "# Combine shapelets with their feature importance, start positions, and class info\n", - "features = zip(\n", - " subseries,\n", - " norm_subseries,\n", - " feature_importance,\n", - " start_pos,\n", - " classes,\n", - " time_series_indexes,\n", - ")\n", - "\n", - "# Sort features by importance (descending order)\n", - "sorted_features = sorted(features, key=itemgetter(2), reverse=True)\n", - "\n", - "# Extract sorted shapelets, start positions, and class info\n", - "subseries = [feature[0] for feature in sorted_features]\n", - "norm_subseries = [feature[1] for feature in sorted_features]\n", - "start_positions = [feature[3] for feature in sorted_features]\n", - "shapelet_classes = [feature[4] for feature in sorted_features]\n", - "time_series_indices = [feature[5] for feature in sorted_features]\n", - "shapelet_lengths = [len(feature[0]) for feature in sorted_features]\n", - "\n", - "num_shapelets = 10\n", - "# Get the top 10 shapelets with their start positions and class information\n", - "top_subseries = [\n", - " (subseries, norm_subseries, start_pos, cls)\n", - " for subseries, norm_subseries, start_pos, cls in zip(\n", - " subseries, norm_subseries, start_positions, shapelet_classes\n", - " )\n", - "]\n", - "shapelets = top_subseries[:num_shapelets]" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "\n", - "# Separate the shapelets by class\n", - "class_1_shapelets = [\n", - " (norm_shapelet, start_pos)\n", - " for shapelet, norm_shapelet, start_pos, cls in shapelets\n", - " if cls == \"1\"\n", - "]\n", - "class_2_shapelets = [\n", - " (norm_shapelet, start_pos)\n", - " for shapelet, norm_shapelet, start_pos, cls in shapelets\n", - " if cls == \"2\"\n", - "]\n", - "# Create a figure with two subplots side by side\n", - "fig, axes = plt.subplots(1, 2, figsize=(20, 8), sharey=True)\n", - "\n", - "# Plot shapelets for Class 1\n", - "for i, (shapelet, start_pos) in enumerate(class_1_shapelets, start=1):\n", - " axes[0].plot(\n", - " range(start_pos, start_pos + len(shapelet)),\n", - " shapelet,\n", - " label=f\"Class 1 Shapelet {i}\",\n", - " linewidth=2,\n", - " )\n", - "axes[0].set_xlabel(\"Time\")\n", - "axes[0].set_ylabel(\"Value\")\n", - "axes[0].set_title(\"Top Shapelets for Gun\")\n", - "axes[0].grid(True)\n", - "\n", - "# Plot shapelets for Class 2\n", - "for i, (shapelet, start_pos) in enumerate(class_2_shapelets, start=1):\n", - " axes[1].plot(\n", - " range(start_pos, start_pos + len(shapelet)),\n", - " shapelet,\n", - " label=f\"Class 2 Shapelet {i}\",\n", - " linewidth=2,\n", - " )\n", - "axes[1].set_xlabel(\"Time\")\n", - "axes[1].set_ylabel(\"Value\")\n", - "axes[1].set_title(\"Top Shapelets for No Gun\")\n", - "axes[1].grid(True)\n", - "\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Like for SAST we aren't plotting the original shapelets but the shapelets once theyre normalised." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The 10 shapelets for RSAST are evenly split between the two classes. They mostly look familiar, those from Gun we were recently introduced to by SAST and the 4 from the No Gun class we have repeatedly encountered and termed ‘overshoot’. It looks like those Gun shapelets are found during the descent of the movement, maybe they are representing the actor putting the gun back into the holster.\n", - "\n", - "One funky-looking shapelet is left from the start of a No Gun time series." - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "\n", - "class_2_shapelets = [\n", - " (shapelet, start_pos)\n", - " for shapelet, norm_shapelet, start_pos, cls in shapelets\n", - " if cls == \"2\"\n", - "]\n", - "\n", - "# Plot shapelets for Class 2\n", - "for i, (shapelet, start_pos) in enumerate(class_2_shapelets, start=1):\n", - " plt.plot(\n", - " range(start_pos, start_pos + len(shapelet)),\n", - " shapelet,\n", - " label=f\"Class 2 Shapelet {i}\",\n", - " linewidth=2,\n", - " )\n", - "plt.xlabel(\"Time\")\n", - "plt.ylabel(\"Value\")\n", - "plt.title(\"Not normalised Shapelets for No Gun\")\n", - "plt.grid(True)\n", - "\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Looking at the same No Gun shapelets exactly as they appear in their reference time series (prior to normalisation), the funky gold shapelet is easier to understand. There may be a very subtle difference in the movement of the actors’ arm before raising it. However, this is more likely an artefact of stratified sampling." - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "import pandas as pd\n", - "\n", - "# Create a DataFrame for the top 10 shapelets\n", - "data = {\n", - " \"Time Series Index\": time_series_indices[:num_shapelets],\n", - " \"Start Position\": start_positions[:num_shapelets],\n", - " \"Shapelet Length\": shapelet_lengths[:num_shapelets],\n", - " \"Class\": shapelet_classes[:num_shapelets], # New column for shapelet classes\n", - "}\n", - "df = pd.DataFrame(data)\n", - "\n", - "# Define the priority order for sorting\n", - "priority_order = [\"Time Series Index\", \"Start Position\", \"Shapelet Length\", \"Class\"]\n", - "\n", - "# Sort the DataFrame by the priority columns\n", - "df_sorted = df.sort_values(by=priority_order, ascending=True)\n", - "\n", - "# Plot the table\n", - "fig, ax = plt.subplots(figsize=(12, 6)) # Adjust the figure size as needed\n", - "ax.axis(\"off\") # Hide the axis\n", - "\n", - "# Create the table\n", - "table = ax.table(\n", - " cellText=df_sorted.values,\n", - " colLabels=df_sorted.columns,\n", - " cellLoc=\"center\",\n", - " loc=\"center\",\n", - " bbox=[0, 0, 1, 1],\n", - ")\n", - "\n", - "table.auto_set_font_size(False)\n", - "table.set_fontsize(10)\n", - "table.auto_set_column_width(df_sorted.columns)\n", - "\n", - "plt.title(\"Top 10 Shapelets Information\")\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Interestingly, only five of the ten reference time series provided shapelets, and neither class shares the same reference time series. Time series 34 and 48 appear most frequently, implying that they best represent each class. That gold funky shapelet from the start of the No Gun movement comes from a reference time series appearing only once; my confidence in this being an artefact is growing.\n", - "\n", - "As in SAST, we again see that most shapelets come from a similar start point and have similar lengths. They are all slight variations of the same pattern; maybe we could get away with using just one shapelet." - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sast_lr_vis = ShapeletClassifierVisualizer(sast_lr)\n", - "\n", - "fig = sast_lr_vis.visualize_shapelets_one_class(\n", - " X_gun_test,\n", - " y_gun_test,\n", - " 0,\n", - " id_example_class=1,\n", - " id_example_other=1,\n", - " figure_options={\"figsize\": (18, 12), \"nrows\": 2, \"ncols\": 2},\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Best class one shapelet is ranked 3\n" - ] - } - ], - "source": [ - "# Filter shapelets by class\n", - "best_class_one_shp = [\n", - " (shapelet, start_pos, index)\n", - " for index, (shapelet, start_pos, cls) in enumerate(\n", - " zip(top_subseries, start_positions, shapelet_classes)\n", - " )\n", - " if cls == \"1\"\n", - "][0]\n", - "\n", - "print(\"Best class one shapelet is ranked\", best_class_one_shp[2])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The same shapelet from SAST has crept up again only its considered to be in the top 10 thanks to RSAST's stratified sampling." - ] - }, - { - "cell_type": "code", - "execution_count": 40, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "sast_lr_vis = ShapeletClassifierVisualizer(sast_lr)\n", - "\n", - "fig = sast_lr_vis.visualize_shapelets_one_class(\n", - " X_gun_test,\n", - " y_gun_test,\n", - " 0,\n", - " best=False,\n", - " id_example_class=1,\n", - " id_example_other=4,\n", - " figure_options={\"figsize\": (18, 12), \"nrows\": 2, \"ncols\": 2},\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The plots for the best shapelet for each class for RSAST are the same as for SAST, giving us no new insights — other than that funky shapelet not being the best for No Gun. We can conclude it was an artefact." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# What we've learned" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Talk about shapelet extraction times. Summarise the types of shapelets found, and go over the ways to interpret." - ] - }, - { - "cell_type": "code", - "execution_count": 42, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Transformer | Value\n", - "---------------------------------------------\n", - "RST | 13.958854913711548\n", - "RDST | 73.46805095672607\n", - "SAST | 0.1421210765838623\n", - "RSAST | 1.93412446975708\n" - ] - } - ], - "source": [ - "time_values = {\n", - " \"RST\": rst_elapsed_time,\n", - " \"RDST\": rdst_elapsed_time,\n", - " \"SAST\": sast_elapsed_time,\n", - " \"RSAST\": rsast_elapsed_time,\n", - "}\n", - "\n", - "print(f\"{'Transformer':<10} | {'Value'}\")\n", - "print(\"-\" * 45)\n", - "\n", - "for transformer, time_value in time_values.items():\n", - " time_var = f\"{transformer.lower()}_time\"\n", - " print(f\"{transformer:<10} | {time_value}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Time to wrap up our exploration of GunPoint. Using only information available in the dataset, we developed an expert-level understanding of the problem. The GunPoint example is intuitive and doesn’t require domain knowledge. Still, it helps us show the power of shapelets which could help us understand more intricate scenarios." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The **shapelet transform** perfectly highlighted the value of shapelets. It directed our focus to the raise and descent parts of the whole movement. We started to realise that there was a difference between the two classes during these particular movements. In fact, rather conveniently, the shapelets were grouped by the two classes.\n", - "\n", - "ST extracts the shapelets from the training data and doesn’t manipulate them, only making them phase and scale-invariant. This kept them straightforward to understand as we could intuitively relate them to the physical motion.\n", - "\n", - "By utilising aeon’s visualisation module, we were able to strengthen our initial speculation that the holster has a significant effect on the motion.\n", - "\n", - "Seeing that the Gun shapelet has a shelf that is not present in the No Gun motion can be related back to the actor taking some time to remove the Gun from the holster, something not done when simply pointing their finger.\n", - "\n", - "Using the same method, we learned that the best No Gun shapelet has a dip; we related this back to the notion of ‘overshoot’, which is when the actor swung their arm back past to where the holster is positioned — since they had nothing to put back in there why would they need to aim for it? They wouldn’t and didn’t." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "---\n", - "Unlike with ST, the **RDST** shapelets were no longer perfectly grouped into the two classes. We have shapelets from the ascent in the No Gun class and a global pattern in the Gun class.\n", - "\n", - "This emphasized a subtle yet important difference to the previous transform. Randomness plays a larger role in the selected shapelets for RDST because sampling is from a larger candidate space.\n", - "\n", - "Alongside dilation, RDST incorporates two additional features which are particularly relevant to our problem. Until now, we assumed that the shapelets from the ascent and descent were related to those motions, but due to normalisation and phase invariance, we couldn’t safely conclude that the best match was always from that same point in time. Maybe the actor sneezed while pointing the Gun, making that ‘overshoot’ appear in the middle of the series…\n", - "\n", - "The argmin feature of RDST showed us that the two-step raise (representative of taking the gun out of the holster) was constantly found between time points 5 to 25 across the whole training set. With every time series having a length of 150, this is clearly the start of the movement. Scarily, for No Gun, the shapelet was found in a similar range, but the SO feature exposed that the best match was rarely within the threshold to be considered a match. Or, at the very least, it was present once, which, when contrasted to the average of five occurrences for Gun, signified it’s present in a very specific part rather than generally fitting like for the Gun time series." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "---\n", - "For **SAST**, we faced our first hiccup in our line of reasoning. We were hoping to see a less redundant version of the above plots. Yes, all 10 shapelets here look redundant; this doesn’t disprove the argument. In fact, it reinforces it; we could’ve just used one reference time series for each class; in this case, 10 gives us the same pattern found slightly earlier and later.\n", - "\n", - "By not pre-filtering shapelet candidates using information gain, we ranked them using the weights assigned by a linear model. This is a very different performance metric; in fact, information gain had a preference towards the Gun shapelets, which aren’t to be found here… I guess it’s not so bad; we are still seeing familiar patterns; we just learned that estimators rank feature importance differently to information gain. Information gain isn’t the universal metric to be used for shapelet selection. In defence of the ST, the authors explored F-STAT as an alternative. The important difference between SAST and SAST is their belief in supervised shapelet extraction." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "--- \n", - "**RSAST** introduced some statistical heuristics into the sampling has a pretty dramatic effect on the extracted shapelets. Once again, we see shapelets grouped by the two classes. Only during this time are the Gun shapelets, and also during descent. We have unlocked another pattern that discriminates against the Gun class.\n", - "\n", - "These Gun shapelets can be explained just as intuitively as those we already found. The actor swings their arm down past the holster, returns their arm to put the gun in it, and then returns their hand to rest. This is similar to the overshoot concept for No Gun but with some additional steps. Perhaps that’s why they aren’t considered as discriminative according to ST. Our decision to ignore the best Gun shapelet was a bit hasty because it was ranked 356 . There were just 356 versions of the same, with no Gun shapelet extracted." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "---\n", - "In sum, the holster is the dead giveaway. We found three patterns describing a class, all encapsulating the motion surrounding an action interacting with the holster. The best part is that we came up with this theory; that’s the beauty of interpretable AI. ML can make sense." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# References" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "[1] J. Lines et al. A shapelet transform for time series classification. In Proc. 18th ACM SIGKDD, 2012.\n", - "\n", - "[2] L. Ye and E. Keogh. Time series shapelets: A new primitive for data mining. In Proc. 15th ACM SIGKDD, 2009\n", - "\n", - "[3] Mbouopda, Michael Franklin, and Engelbert Mephu Nguifo. Scalable and accurate subsequence transform for time series classification. Pattern Recognition 147, 2023.\n", - "\n", - "[4] Antoine Guillaume et al. Random Dilated Shapelet Transform: A New Approach for Time Series Shapelet. ICPRAI 2021.\n", - "\n", - "[5] Varela, N. R., Mbouopda, M. F., & Nguifo, E. M. RSAST: Sampling Shapelets for Time Series Classificatio. 2023." - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "aeon_dev", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.4" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} From 262c1eda6193b03d455648c40adbb611a99000e6 Mon Sep 17 00:00:00 2001 From: Tony Bagnall Date: Mon, 25 Nov 2024 14:30:09 +0000 Subject: [PATCH 2/4] [ENH] Refactor num_kernels (#2373) * rocket unequal length * typo * typo * num_kernels * switch to mock * examples * examples and typos * handle mismatch it fit and transform * handle mismatch it fit and transform * notebook * tests * remove minirocketmultivariatevariable * num_kernels -> n_kernels * update from main * remove unequal cap * minirocket notebook * change test_all_estimators_list_tag_lookup * tag * tags * minrocket notebook * minirocket notebook --- aeon/classification/compose/_pipeline.py | 2 +- .../compose/tests/test_pipeline.py | 6 +- .../convolution_based/_arsenal.py | 20 +- .../convolution_based/_minirocket.py | 18 +- .../convolution_based/_multirocket.py | 18 +- .../convolution_based/_rocket.py | 35 +- .../convolution_based/tests/test_arsenal.py | 12 +- aeon/classification/hybrid/_hivecote_v2.py | 8 +- aeon/classification/hybrid/tests/test_hc.py | 2 +- .../clustering/compose/tests/test_pipeline.py | 4 +- .../regression/compose/tests/test_pipeline.py | 6 +- .../convolution_based/_minirocket.py | 16 +- .../convolution_based/_multirocket.py | 16 +- aeon/regression/convolution_based/_rocket.py | 16 +- .../collection/convolution_based/__init__.py | 2 - .../collection/convolution_based/_hydra.py | 5 + .../convolution_based/_minirocket.py | 18 +- .../convolution_based/_minirocket_mv.py | 1158 --------- .../convolution_based/_multirocket.py | 312 ++- .../collection/convolution_based/_rocket.py | 181 +- .../rocketGPU/_rocket_gpu.py | 21 +- .../convolution_based/rocketGPU/base.py | 6 +- .../rocketGPU/tests/test_base_rocketGPU.py | 24 +- .../tests/test_all_rockets.py | 26 +- .../tests/test_minirocket.py | 86 +- aeon/utils/tests/test_discovery.py | 2 +- examples/classification/classification.ipynb | 37 +- .../classification/convolution_based.ipynb | 10 +- examples/transformations/minirocket.ipynb | 2211 ++++++++++++++--- 29 files changed, 2306 insertions(+), 1972 deletions(-) delete mode 100644 aeon/transformations/collection/convolution_based/_minirocket_mv.py diff --git a/aeon/classification/compose/_pipeline.py b/aeon/classification/compose/_pipeline.py index e9c2383fa6..e917b6a088 100644 --- a/aeon/classification/compose/_pipeline.py +++ b/aeon/classification/compose/_pipeline.py @@ -68,7 +68,7 @@ class ClassifierPipeline(BaseCollectionPipeline, BaseClassifier): >>> X_train, y_train = load_unit_test(split="train") >>> X_test, y_test = load_unit_test(split="test") >>> pipeline = ClassifierPipeline( - ... Resizer(length=10), RocketClassifier(num_kernels=50) + ... Resizer(length=10), RocketClassifier(n_kernels=50) ... ) >>> pipeline.fit(X_train, y_train) ClassifierPipeline(...) diff --git a/aeon/classification/compose/tests/test_pipeline.py b/aeon/classification/compose/tests/test_pipeline.py index 9dea384eb5..c104a3f339 100644 --- a/aeon/classification/compose/tests/test_pipeline.py +++ b/aeon/classification/compose/tests/test_pipeline.py @@ -16,7 +16,7 @@ make_example_3d_numpy, make_example_3d_numpy_list, ) -from aeon.testing.mock_estimators import MockCollectionTransformer +from aeon.testing.mock_estimators import MockClassifier, MockCollectionTransformer from aeon.transformations.collection import ( AutocorrelationFunctionTransformer, HOG1DTransformer, @@ -126,7 +126,7 @@ def test_unequal_tag_inference(): assert not t4.get_tag("capability:unequal_length") c1 = DummyClassifier() - c2 = RocketClassifier(num_kernels=5) + c2 = MockClassifier() c3 = RandomForestClassifier(n_estimators=2) assert c1.get_tag("capability:unequal_length") @@ -190,7 +190,7 @@ def test_missing_tag_inference(): assert not t2.get_tag("capability:missing_values") c1 = DummyClassifier() - c2 = RocketClassifier(num_kernels=5) + c2 = RocketClassifier(n_kernels=5) c3 = RandomForestClassifier(n_estimators=2) assert c1.get_tag("capability:missing_values") diff --git a/aeon/classification/convolution_based/_arsenal.py b/aeon/classification/convolution_based/_arsenal.py index a24a57d9ab..4a232e7a1e 100644 --- a/aeon/classification/convolution_based/_arsenal.py +++ b/aeon/classification/convolution_based/_arsenal.py @@ -35,7 +35,7 @@ class Arsenal(BaseClassifier): Parameters ---------- - num_kernels : int, default=2,000 + n_kernels : int, default=2,000 Number of kernels for each ROCKET transform. n_estimators : int, default=25 Number of estimators to build for the ensemble. @@ -114,7 +114,7 @@ class Arsenal(BaseClassifier): >>> from aeon.datasets import load_unit_test >>> X_train, y_train = load_unit_test(split="train") >>> X_test, y_test =load_unit_test(split="test") - >>> clf = Arsenal(num_kernels=100, n_estimators=5) + >>> clf = Arsenal(n_kernels=100, n_estimators=5) >>> clf.fit(X_train, y_train) Arsenal(...) >>> y_pred = clf.predict(X_test) @@ -130,7 +130,7 @@ class Arsenal(BaseClassifier): def __init__( self, - num_kernels=2000, + n_kernels=2000, n_estimators=25, rocket_transform="rocket", max_dilations_per_kernel=32, @@ -141,7 +141,7 @@ def __init__( n_jobs=1, random_state=None, ): - self.num_kernels = num_kernels + self.n_kernels = n_kernels self.n_estimators = n_estimators self.rocket_transform = rocket_transform self.max_dilations_per_kernel = max_dilations_per_kernel @@ -281,15 +281,15 @@ def _fit_arsenal(self, X, y, keep_transformed_data=False): train_time = 0 if self.rocket_transform == "rocket": - base_rocket = Rocket(num_kernels=self.num_kernels) + base_rocket = Rocket(n_kernels=self.n_kernels) elif self.rocket_transform == "minirocket": base_rocket = MiniRocket( - num_kernels=self.num_kernels, + n_kernels=self.n_kernels, max_dilations_per_kernel=self.max_dilations_per_kernel, ) elif self.rocket_transform == "multirocket": base_rocket = MultiRocket( - num_kernels=self.num_kernels, + n_kernels=self.n_kernels, max_dilations_per_kernel=self.max_dilations_per_kernel, n_features_per_kernel=self.n_features_per_kernel, ) @@ -419,12 +419,12 @@ def _get_test_params(cls, parameter_set="default"): `MyClass(**params)` or `MyClass(**params[i])` creates a valid test instance. """ if parameter_set == "results_comparison": - return {"num_kernels": 20, "n_estimators": 5} + return {"n_kernels": 20, "n_estimators": 5} elif parameter_set == "contracting": return { "time_limit_in_minutes": 5, - "num_kernels": 10, + "n_kernels": 10, "contract_max_n_estimators": 2, } else: - return {"num_kernels": 10, "n_estimators": 2} + return {"n_kernels": 10, "n_estimators": 2} diff --git a/aeon/classification/convolution_based/_minirocket.py b/aeon/classification/convolution_based/_minirocket.py index dc3ef18a7a..6025121354 100644 --- a/aeon/classification/convolution_based/_minirocket.py +++ b/aeon/classification/convolution_based/_minirocket.py @@ -27,7 +27,7 @@ class MiniRocketClassifier(BaseClassifier): Parameters ---------- - num_kernels : int, default=10,000 + n_kernels : int, default=10,000 The number of kernels for the Rocket transform. max_dilations_per_kernel : int, default=32 The maximum number of dilations per kernel. @@ -71,13 +71,13 @@ class MiniRocketClassifier(BaseClassifier): Examples -------- - >>> from aeon.classification.convolution_based import RocketClassifier + >>> from aeon.classification.convolution_based import MiniRocketClassifier >>> from aeon.datasets import load_unit_test >>> X_train, y_train = load_unit_test(split="train") >>> X_test, y_test = load_unit_test(split="test") - >>> clf = RocketClassifier(num_kernels=500) + >>> clf = MiniRocketClassifier(n_kernels=500) >>> clf.fit(X_train, y_train) - RocketClassifier(...) + MiniRocketClassifier(...) >>> y_pred = clf.predict(X_test) """ @@ -89,14 +89,14 @@ class MiniRocketClassifier(BaseClassifier): def __init__( self, - num_kernels=10000, + n_kernels=10000, max_dilations_per_kernel=32, estimator=None, class_weight=None, n_jobs=1, random_state=None, ): - self.num_kernels = num_kernels + self.n_kernels = n_kernels self.max_dilations_per_kernel = max_dilations_per_kernel self.estimator = estimator @@ -129,7 +129,7 @@ def _fit(self, X, y): self.n_cases_, self.n_channels_, self.n_timepoints_ = X.shape self._transformer = MiniRocket( - num_kernels=self.num_kernels, + n_kernels=self.n_kernels, max_dilations_per_kernel=self.max_dilations_per_kernel, n_jobs=self.n_jobs, random_state=self.random_state, @@ -215,6 +215,6 @@ def _get_test_params(cls, parameter_set="default"): `MyClass(**params)` or `MyClass(**params[i])` creates a valid test instance. """ if parameter_set == "results_comparison": - return {"num_kernels": 100} + return {"n_kernels": 100} else: - return {"num_kernels": 20, "max_dilations_per_kernel": 6} + return {"n_kernels": 20, "max_dilations_per_kernel": 6} diff --git a/aeon/classification/convolution_based/_multirocket.py b/aeon/classification/convolution_based/_multirocket.py index a0c1767eff..0da780c76d 100644 --- a/aeon/classification/convolution_based/_multirocket.py +++ b/aeon/classification/convolution_based/_multirocket.py @@ -27,7 +27,7 @@ class MultiRocketClassifier(BaseClassifier): Parameters ---------- - num_kernels : int, default=10,000 + n_kernels : int, default=10,000 The number of kernels for the Rocket transform. max_dilations_per_kernel : int, default=32 The maximum number of dilations per kernel. @@ -72,13 +72,13 @@ class MultiRocketClassifier(BaseClassifier): Examples -------- - >>> from aeon.classification.convolution_based import RocketClassifier + >>> from aeon.classification.convolution_based import MultiRocketClassifier >>> from aeon.datasets import load_unit_test >>> X_train, y_train = load_unit_test(split="train") >>> X_test, y_test = load_unit_test(split="test") - >>> clf = RocketClassifier(num_kernels=500) + >>> clf = MultiRocketClassifier(n_kernels=500) >>> clf.fit(X_train, y_train) - RocketClassifier(...) + MultiRocketClassifier(...) >>> y_pred = clf.predict(X_test) """ @@ -90,7 +90,7 @@ class MultiRocketClassifier(BaseClassifier): def __init__( self, - num_kernels=10000, + n_kernels=10000, max_dilations_per_kernel=32, n_features_per_kernel=4, estimator=None, @@ -98,7 +98,7 @@ def __init__( n_jobs=1, random_state=None, ): - self.num_kernels = num_kernels + self.n_kernels = n_kernels self.max_dilations_per_kernel = max_dilations_per_kernel self.n_features_per_kernel = n_features_per_kernel self.estimator = estimator @@ -132,7 +132,7 @@ def _fit(self, X, y): self.n_cases_, self.n_channels_, self.n_timepoints_ = X.shape self._transformer = MultiRocket( - num_kernels=self.num_kernels, + n_kernels=self.n_kernels, max_dilations_per_kernel=self.max_dilations_per_kernel, n_features_per_kernel=self.n_features_per_kernel, n_jobs=self.n_jobs, @@ -219,10 +219,10 @@ def _get_test_params(cls, parameter_set="default"): `MyClass(**params)` or `MyClass(**params[i])` creates a valid test instance. """ if parameter_set == "results_comparison": - return {"num_kernels": 100} + return {"n_kernels": 100} else: return { - "num_kernels": 200, + "n_kernels": 200, "max_dilations_per_kernel": 8, "n_features_per_kernel": 4, } diff --git a/aeon/classification/convolution_based/_rocket.py b/aeon/classification/convolution_based/_rocket.py index 8509fde22a..152397a940 100644 --- a/aeon/classification/convolution_based/_rocket.py +++ b/aeon/classification/convolution_based/_rocket.py @@ -27,7 +27,7 @@ class RocketClassifier(BaseClassifier): Parameters ---------- - num_kernels : int, default=10,000 + n_kernels : int, default=10,000 The number of kernels for the Rocket transform. estimator : sklearn compatible classifier or None, default=None The estimator used. If None, a RidgeClassifierCV(alphas=np.logspace(-3, 3, 10)) @@ -78,27 +78,28 @@ class RocketClassifier(BaseClassifier): >>> from aeon.datasets import load_unit_test >>> X_train, y_train = load_unit_test(split="train") >>> X_test, y_test = load_unit_test(split="test") - >>> clf = RocketClassifier(num_kernels=500) + >>> clf = RocketClassifier(n_kernels=500) >>> clf.fit(X_train, y_train) RocketClassifier(...) >>> y_pred = clf.predict(X_test) """ _tags = { - "capability:multithreading": True, "capability:multivariate": True, + "capability:multithreading": True, "algorithm_type": "convolution", + "X_inner_type": "numpy3D", } def __init__( self, - num_kernels=10000, + n_kernels=10000, estimator=None, class_weight=None, n_jobs=1, random_state=None, ): - self.num_kernels = num_kernels + self.n_kernels = n_kernels self.estimator = estimator self.class_weight = class_weight @@ -112,8 +113,8 @@ def _fit(self, X, y): Parameters ---------- - X : 3D np.ndarray - The training data of shape = (n_cases, n_channels, n_timepoints). + X : 3D np.ndarray or list + Collection of time series. y : 3D np.ndarray The class labels, shape = (n_cases,). @@ -127,10 +128,8 @@ def _fit(self, X, y): Changes state by creating a fitted model that updates attributes ending in "_" and sets is_fitted flag to True. """ - self.n_cases_, self.n_channels_, self.n_timepoints_ = X.shape - self._transformer = Rocket( - num_kernels=self.num_kernels, + n_kernels=self.n_kernels, n_jobs=self.n_jobs, random_state=self.random_state, ) @@ -160,8 +159,8 @@ def _predict(self, X) -> np.ndarray: Parameters ---------- - X : 3D np.ndarray of shape = (n_cases, n_channels, n_timepoints) - The data to make predictions for. + X : 3D np.ndarray or list + Collection of time series. Returns ------- @@ -175,8 +174,8 @@ def _predict_proba(self, X) -> np.ndarray: Parameters ---------- - X : 3D np.ndarray of shape = (n_cases, n_channels, n_timepoints) - The data to make predict probabilities for. + X : 3D np.ndarray or list + Collection of time series. Returns ------- @@ -187,9 +186,9 @@ def _predict_proba(self, X) -> np.ndarray: if callable(m): return self.pipeline_.predict_proba(X) else: - dists = np.zeros((X.shape[0], self.n_classes_)) + dists = np.zeros((len(X), self.n_classes_)) preds = self.pipeline_.predict(X) - for i in range(0, X.shape[0]): + for i in range(0, len(X)): dists[i, np.where(self.classes_ == preds[i])] = 1 return dists @@ -215,6 +214,6 @@ def _get_test_params(cls, parameter_set="default"): `MyClass(**params)` or `MyClass(**params[i])` creates a valid test instance. """ if parameter_set == "results_comparison": - return {"num_kernels": 100} + return {"n_kernels": 100} else: - return {"num_kernels": 20} + return {"n_kernels": 20} diff --git a/aeon/classification/convolution_based/tests/test_arsenal.py b/aeon/classification/convolution_based/tests/test_arsenal.py index b811ee22c0..cfb59bb5fd 100644 --- a/aeon/classification/convolution_based/tests/test_arsenal.py +++ b/aeon/classification/convolution_based/tests/test_arsenal.py @@ -22,7 +22,7 @@ def test_contracted_arsenal(): arsenal = Arsenal( time_limit_in_minutes=0.25, contract_max_n_estimators=3, - num_kernels=20, + n_kernels=20, ) arsenal.fit(X_train, y_train) assert len(arsenal.estimators_) > 1 @@ -31,13 +31,13 @@ def test_contracted_arsenal(): def test_arsenal(): """Test correct rocket variant is selected.""" X_train, y_train = make_example_2d_numpy_collection(n_cases=20, n_timepoints=50) - afc = Arsenal(num_kernels=20, n_estimators=2) + afc = Arsenal(n_kernels=20, n_estimators=2) afc.fit(X_train, y_train) for i in range(afc.n_estimators): assert isinstance(afc.estimators_[i].steps[0][1], Rocket) assert len(afc.estimators_) == 2 afc = Arsenal( - num_kernels=100, + n_kernels=100, rocket_transform="minirocket", max_dilations_per_kernel=2, n_estimators=2, @@ -46,7 +46,7 @@ def test_arsenal(): for i in range(afc.n_estimators): assert isinstance(afc.estimators_[i].steps[0][1], MiniRocket) afc = Arsenal( - num_kernels=100, + n_kernels=100, rocket_transform="multirocket", max_dilations_per_kernel=2, n_estimators=2, @@ -56,7 +56,7 @@ def test_arsenal(): assert isinstance(afc.estimators_[i].steps[0][1], MultiRocket) X_train, y_train = make_example_3d_numpy(n_cases=20, n_timepoints=50, n_channels=4) afc = Arsenal( - num_kernels=100, + n_kernels=100, rocket_transform="minirocket", max_dilations_per_kernel=2, n_estimators=2, @@ -65,7 +65,7 @@ def test_arsenal(): for i in range(afc.n_estimators): assert isinstance(afc.estimators_[i].steps[0][1], MiniRocket) afc = Arsenal( - num_kernels=100, + n_kernels=100, rocket_transform="multirocket", max_dilations_per_kernel=2, n_estimators=2, diff --git a/aeon/classification/hybrid/_hivecote_v2.py b/aeon/classification/hybrid/_hivecote_v2.py index 53cd94ef30..f53167cc8a 100644 --- a/aeon/classification/hybrid/_hivecote_v2.py +++ b/aeon/classification/hybrid/_hivecote_v2.py @@ -181,7 +181,7 @@ def _fit(self, X, y): self._drcif_params = {"n_estimators": HIVECOTEV2._DEFAULT_N_TREES} if self.arsenal_params is None: self._arsenal_params = { - "num_kernels": HIVECOTEV2._DEFAULT_N_KERNELS, + "n_kernels": HIVECOTEV2._DEFAULT_N_KERNELS, "n_estimators": HIVECOTEV2._DEFAULT_N_ESTIMATORS, } if self.tde_params is None: @@ -365,7 +365,7 @@ def _get_test_params(cls, parameter_set="default"): "n_intervals": 2, "att_subsample_size": 2, }, - "arsenal_params": {"num_kernels": 50, "n_estimators": 3}, + "arsenal_params": {"n_kernels": 50, "n_estimators": 3}, "tde_params": { "n_parameter_samples": 5, "max_ensemble_size": 3, @@ -386,7 +386,7 @@ def _get_test_params(cls, parameter_set="default"): "n_intervals": 2, "att_subsample_size": 2, }, - "arsenal_params": {"num_kernels": 5, "contract_max_n_estimators": 1}, + "arsenal_params": {"n_kernels": 5, "contract_max_n_estimators": 1}, "tde_params": { "contract_max_n_parameter_samples": 1, "max_ensemble_size": 1, @@ -406,7 +406,7 @@ def _get_test_params(cls, parameter_set="default"): "n_intervals": 2, "att_subsample_size": 2, }, - "arsenal_params": {"num_kernels": 5, "n_estimators": 1}, + "arsenal_params": {"n_kernels": 5, "n_estimators": 1}, "tde_params": { "n_parameter_samples": 1, "max_ensemble_size": 1, diff --git a/aeon/classification/hybrid/tests/test_hc.py b/aeon/classification/hybrid/tests/test_hc.py index 23861f4f01..651e10556f 100644 --- a/aeon/classification/hybrid/tests/test_hc.py +++ b/aeon/classification/hybrid/tests/test_hc.py @@ -45,7 +45,7 @@ def test_hc2_defaults_and_verbosity(): hc2.fit(X, y) assert hc2._stc_params == {"n_shapelet_samples": 10} assert hc2._drcif_params == {"n_estimators": 10} - assert hc2._arsenal_params == {"num_kernels": 100, "n_estimators": 5} + assert hc2._arsenal_params == {"n_kernels": 100, "n_estimators": 5} assert hc2._tde_params == { "n_parameter_samples": 10, "max_ensemble_size": 5, diff --git a/aeon/clustering/compose/tests/test_pipeline.py b/aeon/clustering/compose/tests/test_pipeline.py index 73f751944b..2b54ee3f24 100644 --- a/aeon/clustering/compose/tests/test_pipeline.py +++ b/aeon/clustering/compose/tests/test_pipeline.py @@ -126,7 +126,7 @@ def test_unequal_tag_inference(): # todo revisit with mock clusterer # c1 = DummyClassifier() - # c2 = RocketClassifier(num_kernels=5) + # c2 = RocketClassifier(n_kernels=5) c3 = KMeans(n_clusters=2, max_iter=3, random_state=0) # assert c1.get_tag("capability:unequal_length") @@ -189,7 +189,7 @@ def test_missing_tag_inference(): # todo revisit with mock clusterer # c1 = DummyClassifier() - # c2 = RocketClassifier(num_kernels=5) + # c2 = RocketClassifier(n_kernels=5) c3 = KMeans(n_clusters=2, max_iter=3, random_state=0) # assert c1.get_tag("capability:missing_values") diff --git a/aeon/regression/compose/tests/test_pipeline.py b/aeon/regression/compose/tests/test_pipeline.py index edafa9eecc..7d8360966c 100644 --- a/aeon/regression/compose/tests/test_pipeline.py +++ b/aeon/regression/compose/tests/test_pipeline.py @@ -16,7 +16,7 @@ make_example_3d_numpy, make_example_3d_numpy_list, ) -from aeon.testing.mock_estimators import MockCollectionTransformer +from aeon.testing.mock_estimators import MockCollectionTransformer, MockRegressor from aeon.transformations.collection import ( AutocorrelationFunctionTransformer, HOG1DTransformer, @@ -126,7 +126,7 @@ def test_unequal_tag_inference(): assert not t4.get_tag("capability:unequal_length") c1 = DummyRegressor() - c2 = RocketRegressor(num_kernels=5) + c2 = MockRegressor() c3 = RandomForestRegressor(n_estimators=2) assert c1.get_tag("capability:unequal_length") @@ -188,7 +188,7 @@ def test_missing_tag_inference(): assert not t2.get_tag("capability:missing_values") c1 = DummyRegressor() - c2 = RocketRegressor(num_kernels=5) + c2 = RocketRegressor(n_kernels=5) c3 = RandomForestRegressor(n_estimators=2) assert c1.get_tag("capability:missing_values") diff --git a/aeon/regression/convolution_based/_minirocket.py b/aeon/regression/convolution_based/_minirocket.py index 3e79965bba..5ffccdad04 100644 --- a/aeon/regression/convolution_based/_minirocket.py +++ b/aeon/regression/convolution_based/_minirocket.py @@ -27,7 +27,7 @@ class MiniRocketRegressor(BaseRegressor): Parameters ---------- - num_kernels : int, default=10,000 + n_kernels : int, default=10,000 The number of kernels for the Rocket transform. max_dilations_per_kernel : int, default=32 The maximum number of dilations per kernel. @@ -51,13 +51,13 @@ class MiniRocketRegressor(BaseRegressor): Examples -------- - >>> from aeon.regression.convolution_based import RocketRegressor + >>> from aeon.regression.convolution_based import MiniRocketRegressor >>> from aeon.datasets import load_covid_3month >>> X_train, y_train = load_covid_3month(split="train") >>> X_test, y_test = load_covid_3month(split="test") - >>> reg = RocketRegressor(num_kernels=500) + >>> reg = MiniRocketRegressor(n_kernels=500) >>> reg.fit(X_train, y_train) - RocketRegressor(num_kernels=500) + MiniRocketRegressor(n_kernels=500) >>> y_pred = reg.predict(X_test) """ @@ -69,13 +69,13 @@ class MiniRocketRegressor(BaseRegressor): def __init__( self, - num_kernels=10000, + n_kernels=10000, max_dilations_per_kernel=32, estimator=None, random_state=None, n_jobs=1, ): - self.num_kernels = num_kernels + self.n_kernels = n_kernels self.max_dilations_per_kernel = max_dilations_per_kernel self.random_state = random_state self.estimator = estimator @@ -106,7 +106,7 @@ def _fit(self, X, y): self.n_cases_, self.n_channels_, self.n_timepoints_ = X.shape self._transformer = MiniRocket( - num_kernels=self.num_kernels, + n_kernels=self.n_kernels, max_dilations_per_kernel=self.max_dilations_per_kernel, n_jobs=self.n_jobs, random_state=self.random_state, @@ -160,4 +160,4 @@ def _get_test_params(cls, parameter_set="default"): dict or list of dict Parameters to create testing instances of the class. """ - return {"num_kernels": 20, "max_dilations_per_kernel": 6} + return {"n_kernels": 20, "max_dilations_per_kernel": 6} diff --git a/aeon/regression/convolution_based/_multirocket.py b/aeon/regression/convolution_based/_multirocket.py index 4cdf782cdb..b62942502e 100644 --- a/aeon/regression/convolution_based/_multirocket.py +++ b/aeon/regression/convolution_based/_multirocket.py @@ -27,7 +27,7 @@ class MultiRocketRegressor(BaseRegressor): Parameters ---------- - num_kernels : int, default=10,000 + n_kernels : int, default=10,000 The number of kernels for the Rocket transform. max_dilations_per_kernel : int, default=32 The maximum number of dilations per kernel. @@ -52,13 +52,13 @@ class MultiRocketRegressor(BaseRegressor): Examples -------- - >>> from aeon.regression.convolution_based import RocketRegressor + >>> from aeon.regression.convolution_based import MultiRocketRegressor >>> from aeon.datasets import load_covid_3month >>> X_train, y_train = load_covid_3month(split="train") >>> X_test, y_test = load_covid_3month(split="test") - >>> reg = RocketRegressor(num_kernels=500) + >>> reg = MultiRocketRegressor(n_kernels=500) >>> reg.fit(X_train, y_train) - RocketRegressor(num_kernels=500) + MultiRocketRegressor(n_kernels=500) >>> y_pred = reg.predict(X_test) """ @@ -70,7 +70,7 @@ class MultiRocketRegressor(BaseRegressor): def __init__( self, - num_kernels=10000, + n_kernels=10000, rocket_transform="rocket", max_dilations_per_kernel=32, n_features_per_kernel=4, @@ -78,7 +78,7 @@ def __init__( random_state=None, n_jobs=1, ): - self.num_kernels = num_kernels + self.n_kernels = n_kernels self.rocket_transform = rocket_transform self.max_dilations_per_kernel = max_dilations_per_kernel self.n_features_per_kernel = n_features_per_kernel @@ -111,7 +111,7 @@ def _fit(self, X, y): self.n_cases_, self.n_channels_, self.n_timepoints_ = X.shape self._transformer = MultiRocket( - num_kernels=self.num_kernels, + n_kernels=self.n_kernels, max_dilations_per_kernel=self.max_dilations_per_kernel, n_features_per_kernel=self.n_features_per_kernel, n_jobs=self.n_jobs, @@ -167,7 +167,7 @@ def _get_test_params(cls, parameter_set="default"): Parameters to create testing instances of the class. """ return { - "num_kernels": 200, + "n_kernels": 200, "max_dilations_per_kernel": 8, "n_features_per_kernel": 4, } diff --git a/aeon/regression/convolution_based/_rocket.py b/aeon/regression/convolution_based/_rocket.py index 5bee6b5150..f522763bed 100644 --- a/aeon/regression/convolution_based/_rocket.py +++ b/aeon/regression/convolution_based/_rocket.py @@ -27,7 +27,7 @@ class RocketRegressor(BaseRegressor): Parameters ---------- - num_kernels : int, default=10,000 + n_kernels : int, default=10,000 The number of kernels for the Rocket transform. estimator : sklearn compatible regressor or None, default=None The estimator used. If None, a RidgeCV(alphas=np.logspace(-3, 3, 10)) is used. @@ -58,9 +58,9 @@ class RocketRegressor(BaseRegressor): >>> from aeon.datasets import load_covid_3month >>> X_train, y_train = load_covid_3month(split="train") >>> X_test, y_test = load_covid_3month(split="test") - >>> reg = RocketRegressor(num_kernels=500) + >>> reg = RocketRegressor(n_kernels=500) >>> reg.fit(X_train, y_train) - RocketRegressor(num_kernels=500) + RocketRegressor(n_kernels=500) >>> y_pred = reg.predict(X_test) """ @@ -72,12 +72,12 @@ class RocketRegressor(BaseRegressor): def __init__( self, - num_kernels=10000, + n_kernels=10000, estimator=None, random_state=None, n_jobs=1, ): - self.num_kernels = num_kernels + self.n_kernels = n_kernels self.random_state = random_state self.estimator = estimator self.n_jobs = n_jobs @@ -104,10 +104,8 @@ def _fit(self, X, y): Changes state by creating a fitted model that updates attributes ending in "_" and sets is_fitted flag to True. """ - self.n_cases_, self.n_channels_, self.n_timepoints_ = X.shape - self._transformer = Rocket( - num_kernels=self.num_kernels, + n_kernels=self.n_kernels, n_jobs=self.n_jobs, random_state=self.random_state, ) @@ -160,4 +158,4 @@ def _get_test_params(cls, parameter_set="default"): dict or list of dict Parameters to create testing instances of the class. """ - return {"num_kernels": 20} + return {"n_kernels": 20} diff --git a/aeon/transformations/collection/convolution_based/__init__.py b/aeon/transformations/collection/convolution_based/__init__.py index 7a3ac916cb..48244e11a0 100644 --- a/aeon/transformations/collection/convolution_based/__init__.py +++ b/aeon/transformations/collection/convolution_based/__init__.py @@ -3,13 +3,11 @@ __all__ = [ "Rocket", "MiniRocket", - "MiniRocketMultivariateVariable", "MultiRocket", "HydraTransformer", ] from ._hydra import HydraTransformer from ._minirocket import MiniRocket -from ._minirocket_mv import MiniRocketMultivariateVariable from ._multirocket import MultiRocket from ._rocket import Rocket diff --git a/aeon/transformations/collection/convolution_based/_hydra.py b/aeon/transformations/collection/convolution_based/_hydra.py index 235508fcfa..34ae1ced0d 100644 --- a/aeon/transformations/collection/convolution_based/_hydra.py +++ b/aeon/transformations/collection/convolution_based/_hydra.py @@ -1,3 +1,8 @@ +"""Hydra Transformer.""" + +__maintainer__ = ["TonyBagnall"] +__all__ = ["HydraTransformer"] + import numpy as np from aeon.transformations.collection import BaseCollectionTransformer diff --git a/aeon/transformations/collection/convolution_based/_minirocket.py b/aeon/transformations/collection/convolution_based/_minirocket.py index 9d8e248bd2..603c381fb7 100644 --- a/aeon/transformations/collection/convolution_based/_minirocket.py +++ b/aeon/transformations/collection/convolution_based/_minirocket.py @@ -22,7 +22,7 @@ class MiniRocket(BaseCollectionTransformer): Parameters ---------- - num_kernels : int, default=10,000 + n_kernels : int, default=10,000 Number of random convolutional kernels. The number of kernels used is rounded down to the nearest multiple of 84, unless a value of less than 84 is passec, in which case it is set to 84. @@ -63,9 +63,9 @@ class MiniRocket(BaseCollectionTransformer): >>> from aeon.datasets import load_unit_test >>> X_train, y_train = load_unit_test(split="train") >>> X_test, y_test = load_unit_test(split="test") - >>> trf = MiniRocket(num_kernels=512) + >>> trf = MiniRocket(n_kernels=512) >>> trf.fit(X_train) - MiniRocket(num_kernels=512) + MiniRocket(n_kernels=512) >>> X_train = trf.transform(X_train) >>> X_test = trf.transform(X_test) """ @@ -81,12 +81,12 @@ class MiniRocket(BaseCollectionTransformer): def __init__( self, - num_kernels=10_000, + n_kernels=10_000, max_dilations_per_kernel=32, n_jobs=1, random_state=None, ): - self.num_kernels = num_kernels + self.n_kernels = n_kernels self.max_dilations_per_kernel = max_dilations_per_kernel self.n_jobs = n_jobs self.random_state = random_state @@ -115,12 +115,12 @@ def _fit(self, X, y=None): " zero pad shorter series so that n_timepoints == 9" ) X = X.astype(np.float32) - if self.num_kernels < 84: - self.num_kernels_ = 84 + if self.n_kernels < 84: + self.n_kernels_ = 84 else: - self.num_kernels_ = self.num_kernels + self.n_kernels_ = self.n_kernels self.parameters = _static_fit( - X, self.num_kernels_, self.max_dilations_per_kernel, random_state + X, self.n_kernels_, self.max_dilations_per_kernel, random_state ) return self diff --git a/aeon/transformations/collection/convolution_based/_minirocket_mv.py b/aeon/transformations/collection/convolution_based/_minirocket_mv.py deleted file mode 100644 index 01d926cb18..0000000000 --- a/aeon/transformations/collection/convolution_based/_minirocket_mv.py +++ /dev/null @@ -1,1158 +0,0 @@ -"""Multivariate MiniRocket transformer.""" - -__maintainer__ = [] -__all__ = ["MiniRocketMultivariateVariable"] - -import multiprocessing -import warnings -from typing import Union - -import numpy as np -import pandas as pd -from numba import get_num_threads, njit, prange, set_num_threads, vectorize - -from aeon.transformations.collection import BaseCollectionTransformer - - -class MiniRocketMultivariateVariable(BaseCollectionTransformer): - """MINIROCKET (Multivariate, unequal length). - - MINImally RandOm Convolutional KErnel Transform. [1]_ - - **Multivariate** and **unequal length** - - A provisional and naive extension of MINIROCKET to multivariate input - with unequal length provided by the authors [2]_. For better - performance, use the aeon class MiniRocket for univariate input, - and MiniRocketMultivariate for equal-length multivariate input. - - Parameters - ---------- - num_kernels : int, default=10,000 - Number of random convolutional kernels. The calculated number of features is the - nearest multiple of ``n_features_per_kernel(default 4)*84=336 < 50,000`` - (``2*n_features_per_kernel(default 4)*num_kernels(default 10,000)``). - max_dilations_per_kernel : int, default=32 - Maximum number of dilations per kernel. - reference_length : int or str, default = `'max'` - Series-length of reference, str defines how to infer from `X` during `fit`. - Options are `'max'`, `'mean'`, `'median'`, `'min'`. - pad_value_short_series : float or None, default=None - Whether padding series with length less than 9 to value. If None, no - padding is performed. - n_jobs : int, default=1 - The number of jobs to run in parallel for `transform`. ``-1`` means using all - processors. - random_state : None or int, default = None - Seed for random number generation. - - Examples - -------- - >>> from aeon.transformations.collection.convolution_based import ( - ... MiniRocketMultivariateVariable - ... ) - >>> from aeon.datasets import load_japanese_vowels - >>> # load multivariate and unequal length dataset - >>> X_train, _ = load_japanese_vowels(split="train") - >>> X_test, _ = load_japanese_vowels(split="test") - >>> pre_clf = MiniRocketMultivariateVariable(pad_value_short_series=0.0) - >>> pre_clf.fit(X_train, y=None) - MiniRocketMultivariateVariable(pad_value_short_series=0.0) - >>> X_transformed = pre_clf.transform(X_test) - >>> X_transformed.shape - (370, 9996) - - Raises - ------ - ValueError - If any multivariate n_timepoints in X is < 9 and - pad_value_short_series is set to None - - See Also - -------- - MultiRocket, MiniRocket, MiniRocketMultivariate, Rocket - - References - ---------- - .. [1] Angus Dempster, Daniel F Schmidt, Geoffrey I Webb - MINIROCKET: A Very Fast (Almost) Deterministic Transform for - Time Series Classification, 2020, arXiv:2012.08791 - - .. [2] Angus Dempster, Daniel F Schmidt, Geoffrey I Webb - https://github.com/angus924/minirocket - - """ - - _tags = { - "output_data_type": "Tabular", - "capability:multivariate": True, - "capability:unequal_length": True, - "capability:multithreading": True, - "X_inner_type": "np-list", - "algorithm_type": "convolution", - } - - def __init__( - self, - num_kernels=10000, - max_dilations_per_kernel=32, - reference_length="max", - pad_value_short_series=None, - n_jobs=1, - random_state=None, - ): - self.num_kernels = num_kernels - self.max_dilations_per_kernel = max_dilations_per_kernel - self.reference_length = reference_length - self._fitted_reference_length = None - self.pad_value_short_series = pad_value_short_series - - self.n_jobs = n_jobs - self.random_state = random_state - - if random_state is None: - self.random_state_ = random_state - elif isinstance(random_state, int): - self.random_state_ = np.int32(random_state) - else: - raise ValueError( - f"random_state in MiniRocketMultivariateVariable must be int or None, " - f"but found <{type(random_state)} {random_state}>" - ) - - self._reference_modes = ["max", "mean", "median", "min"] - if not (isinstance(reference_length, int) and reference_length >= 9) and not ( - isinstance(reference_length, str) - and (reference_length in self._reference_modes) - ): - raise ValueError( - "reference_length in MiniRocketMultivariateVariable must be int>=9 or " - "'max', 'mean', 'median', but found reference_length=" - f"{reference_length}" - ) - - super().__init__() - - def _fit(self, X, y=None): - """Fits dilations and biases to input time series. - - Parameters - ---------- - X : List of 2D np.ndarray - y : ignored argument for interface compatibility - - Returns - ------- - self - - Raises - ------ - ValueError - If any multivariate n_timepoints in X is < 9 and - pad_value_short_series is set to None - """ - X_2d_t, lengths_1darray = _np_list_transposed2D_array_and_len_list( - X, pad=self.pad_value_short_series - ) - - if isinstance(self.reference_length, int): - _reference_length = self.reference_length - elif self.reference_length in self._reference_modes: - # np.mean, np.max, np.median, np.min .. - _reference_length = getattr(np, self.reference_length)(lengths_1darray) - else: - raise ValueError( - "reference_length in MiniRocketMultivariateVariable must be int>=9 or " - "'max', 'mean', 'median', but found reference_length=" - f"{self.reference_length}" - ) - self._fitted_reference_length = int(max(9, _reference_length)) - - if lengths_1darray.min() < 9: - failed_index = np.where(lengths_1darray < 9)[0] - raise ValueError( - f"X must be >= 9 for all samples, but found miniumum to be " - f"{lengths_1darray.min()}; at index {failed_index}, pad shorter " - "series so that n_timepoints >= 9 for all samples." - ) - - if lengths_1darray.min() == lengths_1darray.max(): - warnings.warn( - "X is of equal length, consider using MiniRocketMultivariate for " - "speedup and stability instead.", - stacklevel=2, - ) - if X_2d_t.shape[0] == 1: - warnings.warn( - "X is univariate, consider using the univariate MiniRocket for " - "speedup and stability instead.", - stacklevel=2, - ) - - self.parameters = _fit_multi_var( - X_2d_t, - L=lengths_1darray, - reference_length=self._fitted_reference_length, - num_features=self.num_kernels, - max_dilations_per_kernel=self.max_dilations_per_kernel, - seed=self.random_state_, - ) - return self - - def _transform(self, X, y=None): - """Transform input time series. - - Parameters - ---------- - X : 2D list on np.ndarray - y : ignored argument for interface compatibility - - Returns - ------- - np.ndarray, size (n_cases, num_kernels) - - Raises - ------ - ValueError - If any multivariate n_timepoints in X is < 9 and - pad_value_short_series is set to None - """ - X_2d_t, L = _np_list_transposed2D_array_and_len_list( - X, pad=self.pad_value_short_series - ) - # change n_jobs dependend on value and existing cores - prev_threads = get_num_threads() - if self.n_jobs < 1 or self.n_jobs > multiprocessing.cpu_count(): - n_jobs = multiprocessing.cpu_count() - else: - n_jobs = self.n_jobs - set_num_threads(n_jobs) - X_ = _transform_multi_var(X_2d_t, L, self.parameters) - set_num_threads(prev_threads) - return X_ - - -def _np_list_transposed2D_array_and_len_list( - X: list[pd.DataFrame], pad: Union[int, float, None] = 0 -): - """Convert a list of 2D numpy to a 2D array and a list of lengths. - - Parameters - ---------- - X : List of dataframes - List of length n_cases, with - dataframes of n_timepoints-rows and n_channels-columns - pad : float or None. if float/int,pads multivariate series with 'pad', - so that each series has at least length 9. - if None, no padding is applied. - - Returns - ------- - np.ndarray: 2D array of shape = - [n_channels, sum(length_series(i) for i in n_cases)], - np.float32 - np.ndarray: 1D array of shape = [n_cases] - with length of each series, np.int32 - - Raises - ------ - ValueError - If any multivariate n_timepoints in X is < 9 and - pad_value_short_series is set to None - """ - vec = [] - lengths = [] - - for _x in X: - _x_shape = _x.shape - if _x_shape[1] < 9: - if pad is not None: - # emergency: pad with zeros up to 9. - lengths.append(9) - padding_width = ((0, 0), (0, 9 - _x_shape[1])) - x_pad = np.pad(_x, padding_width, mode="constant", constant_values=pad) - vec.append(np.transpose(x_pad)) - else: - raise ValueError( - "X n_timepoints must be >= 9 for all samples" - f"but sample with n_timepoints {_x_shape[1]} found. Consider" - " padding, discard, or setting a pad_value_short_series value" - ) - else: - lengths.append(_x_shape[1]) - vec.append(np.transpose(_x)) - - X_2d_t = np.vstack(vec).T.astype(dtype=np.float32) - lengths = np.array(lengths, dtype=np.int32) - - if not lengths.sum() == X_2d_t.shape[1]: - raise ValueError("X_new and lengths do not match. check input dimension") - - return X_2d_t, lengths - - -# code below from the orignal authors: https://github.com/angus924/minirocket - - -@njit( - "float32[:](float32[:,:],int32[:],int32[:],int32[:],int32[:],int32[:],float32[:]," - "optional(int32))", - fastmath=True, - parallel=False, - cache=True, -) -def _fit_biases_multi_var( - X, - L, - num_channels_per_combination, - channel_indices, - dilations, - num_features_per_dilation, - quantiles, - seed, -): - if seed is not None: - np.random.seed(seed) - n_cases = len(L) - - num_channels, _ = X.shape - - # equivalent to: - # >>> from itertools import combinations - # >>> indices = np.array( - # >>> [_ for _ in combinations(np.arange(9), 3)], dtype = np.int32 - # >>> ) - indices = np.array( - ( - 0, - 1, - 2, - 0, - 1, - 3, - 0, - 1, - 4, - 0, - 1, - 5, - 0, - 1, - 6, - 0, - 1, - 7, - 0, - 1, - 8, - 0, - 2, - 3, - 0, - 2, - 4, - 0, - 2, - 5, - 0, - 2, - 6, - 0, - 2, - 7, - 0, - 2, - 8, - 0, - 3, - 4, - 0, - 3, - 5, - 0, - 3, - 6, - 0, - 3, - 7, - 0, - 3, - 8, - 0, - 4, - 5, - 0, - 4, - 6, - 0, - 4, - 7, - 0, - 4, - 8, - 0, - 5, - 6, - 0, - 5, - 7, - 0, - 5, - 8, - 0, - 6, - 7, - 0, - 6, - 8, - 0, - 7, - 8, - 1, - 2, - 3, - 1, - 2, - 4, - 1, - 2, - 5, - 1, - 2, - 6, - 1, - 2, - 7, - 1, - 2, - 8, - 1, - 3, - 4, - 1, - 3, - 5, - 1, - 3, - 6, - 1, - 3, - 7, - 1, - 3, - 8, - 1, - 4, - 5, - 1, - 4, - 6, - 1, - 4, - 7, - 1, - 4, - 8, - 1, - 5, - 6, - 1, - 5, - 7, - 1, - 5, - 8, - 1, - 6, - 7, - 1, - 6, - 8, - 1, - 7, - 8, - 2, - 3, - 4, - 2, - 3, - 5, - 2, - 3, - 6, - 2, - 3, - 7, - 2, - 3, - 8, - 2, - 4, - 5, - 2, - 4, - 6, - 2, - 4, - 7, - 2, - 4, - 8, - 2, - 5, - 6, - 2, - 5, - 7, - 2, - 5, - 8, - 2, - 6, - 7, - 2, - 6, - 8, - 2, - 7, - 8, - 3, - 4, - 5, - 3, - 4, - 6, - 3, - 4, - 7, - 3, - 4, - 8, - 3, - 5, - 6, - 3, - 5, - 7, - 3, - 5, - 8, - 3, - 6, - 7, - 3, - 6, - 8, - 3, - 7, - 8, - 4, - 5, - 6, - 4, - 5, - 7, - 4, - 5, - 8, - 4, - 6, - 7, - 4, - 6, - 8, - 4, - 7, - 8, - 5, - 6, - 7, - 5, - 6, - 8, - 5, - 7, - 8, - 6, - 7, - 8, - ), - dtype=np.int32, - ).reshape(84, 3) - - num_kernels = len(indices) - num_dilations = len(dilations) - - num_features = num_kernels * np.sum(num_features_per_dilation) - - biases = np.zeros(num_features, dtype=np.float32) - - feature_index_start = 0 - - combination_index = 0 - num_channels_start = 0 - - for dilation_index in range(num_dilations): - dilation = dilations[dilation_index] - padding = ((9 - 1) * dilation) // 2 - - num_features_this_dilation = num_features_per_dilation[dilation_index] - - for kernel_index in range(num_kernels): - feature_index_end = feature_index_start + num_features_this_dilation - - num_channels_this_combination = num_channels_per_combination[ - combination_index - ] - - num_channels_end = num_channels_start + num_channels_this_combination - - channels_this_combination = channel_indices[ - num_channels_start:num_channels_end - ] - - example_index = np.random.randint(n_cases) - - input_length = np.int64(L[example_index]) - - b = np.sum(L[0 : example_index + 1]) - a = b - input_length - - _X = X[channels_this_combination, a:b] - - A = -_X # A = alpha * X = -X - G = _X + _X + _X # G = gamma * X = 3X - - C_alpha = np.zeros( - (num_channels_this_combination, input_length), dtype=np.float32 - ) - C_alpha[:] = A - - C_gamma = np.zeros( - (9, num_channels_this_combination, input_length), dtype=np.float32 - ) - C_gamma[9 // 2] = G - - start = dilation - end = input_length - padding - - for gamma_index in range(9 // 2): - # thanks to Murtaza Jafferji @murtazajafferji for suggesting this fix - if end > 0: - C_alpha[:, -end:] = C_alpha[:, -end:] + A[:, :end] - C_gamma[gamma_index, :, -end:] = G[:, :end] - - end += dilation - - for gamma_index in range(9 // 2 + 1, 9): - if start < input_length: - C_alpha[:, :-start] = C_alpha[:, :-start] + A[:, start:] - C_gamma[gamma_index, :, :-start] = G[:, start:] - - start += dilation - - index_0, index_1, index_2 = indices[kernel_index] - - C = C_alpha + C_gamma[index_0] + C_gamma[index_1] + C_gamma[index_2] - C = np.sum(C, axis=0) - - biases[feature_index_start:feature_index_end] = np.quantile( - C, quantiles[feature_index_start:feature_index_end] - ) - - feature_index_start = feature_index_end - - combination_index += 1 - num_channels_start = num_channels_end - - return biases - - -def _fit_dilations_multi_var(reference_length, num_features, max_dilations_per_kernel): - num_kernels = 84 - - num_features_per_kernel = num_features // num_kernels - true_max_dilations_per_kernel = min( - num_features_per_kernel, max_dilations_per_kernel - ) - multiplier = num_features_per_kernel / true_max_dilations_per_kernel - - max_exponent = np.log2((reference_length - 1) / (9 - 1)) - dilations, num_features_per_dilation = np.unique( - np.logspace(0, max_exponent, true_max_dilations_per_kernel, base=2).astype( - np.int32 - ), - return_counts=True, - ) - num_features_per_dilation = (num_features_per_dilation * multiplier).astype( - np.int32 - ) # this is a vector - - remainder = num_features_per_kernel - np.sum(num_features_per_dilation) - i = 0 - while remainder > 0: - num_features_per_dilation[i] += 1 - remainder -= 1 - i = (i + 1) % len(num_features_per_dilation) - - return dilations, num_features_per_dilation - - -# low-discrepancy sequence to assign quantiles to kernel/dilation combinations -def _quantiles_multi_var(n): - return np.array( - [(_ * ((np.sqrt(5) + 1) / 2)) % 1 for _ in range(1, n + 1)], dtype=np.float32 - ) - - -def _fit_multi_var( - X, - L, - reference_length: int, - num_features=10_000, - max_dilations_per_kernel=32, - seed=None, -): - if seed is not None: - np.random.seed(seed) - # note in relation to dilation: - # * change *reference_length* according to what is appropriate for your - # application, e.g., L.max(), L.mean(), np.median(L) - # * use _fit_multi_var(...) with an appropriate subset of time series, e.g., for - # reference_length = L.mean(), call _fit_multi_var(...) using only time series - # of at least length L.mean() [see filter_by_length(...)] - if reference_length is None: - raise ValueError("reference_length must be specified") - - num_channels, _ = X.shape - - num_kernels = 84 - - dilations, num_features_per_dilation = _fit_dilations_multi_var( - reference_length, num_features, max_dilations_per_kernel - ) - - num_features_per_kernel = np.sum(num_features_per_dilation) - - quantiles = _quantiles_multi_var(num_kernels * num_features_per_kernel) - - num_dilations = len(dilations) - num_combinations = num_kernels * num_dilations - - max_num_channels = min(num_channels, 9) - max_exponent = np.log2(max_num_channels + 1) - - num_channels_per_combination = ( - 2 ** np.random.uniform(0, max_exponent, num_combinations) - ).astype(np.int32) - - channel_indices = np.zeros(num_channels_per_combination.sum(), dtype=np.int32) - - num_channels_start = 0 - for combination_index in range(num_combinations): - num_channels_this_combination = num_channels_per_combination[combination_index] - num_channels_end = num_channels_start + num_channels_this_combination - channel_indices[num_channels_start:num_channels_end] = np.random.choice( - num_channels, num_channels_this_combination, replace=False - ) - - num_channels_start = num_channels_end - - biases = _fit_biases_multi_var( - X, - L, - num_channels_per_combination, - channel_indices, - dilations, - num_features_per_dilation, - quantiles, - seed, - ) - - return ( - num_channels_per_combination, - channel_indices, - dilations, - num_features_per_dilation, - biases, - ) - - -@vectorize("float32(float32,float32)", nopython=True, cache=True) -def _PPV(a, b): - if a > b: - return 1 - else: - return 0 - - -@njit( - "float32[:,:](float32[:,:],int32[:],Tuple((int32[:],int32[:],int32[:],int32[:]," - "float32[:])))", - fastmath=True, - parallel=True, - cache=True, -) -def _transform_multi_var(X, L, parameters): - n_cases = len(L) - - num_channels, _ = X.shape - - ( - num_channels_per_combination, - channel_indices, - dilations, - num_features_per_dilation, - biases, - ) = parameters - - # equivalent to: - # >>> from itertools import combinations - # >>> indices = np.array( - # >>> [_ for _ in combinations(np.arange(9), 3)], dtype = np.int32 - # >>> ) - indices = np.array( - ( - 0, - 1, - 2, - 0, - 1, - 3, - 0, - 1, - 4, - 0, - 1, - 5, - 0, - 1, - 6, - 0, - 1, - 7, - 0, - 1, - 8, - 0, - 2, - 3, - 0, - 2, - 4, - 0, - 2, - 5, - 0, - 2, - 6, - 0, - 2, - 7, - 0, - 2, - 8, - 0, - 3, - 4, - 0, - 3, - 5, - 0, - 3, - 6, - 0, - 3, - 7, - 0, - 3, - 8, - 0, - 4, - 5, - 0, - 4, - 6, - 0, - 4, - 7, - 0, - 4, - 8, - 0, - 5, - 6, - 0, - 5, - 7, - 0, - 5, - 8, - 0, - 6, - 7, - 0, - 6, - 8, - 0, - 7, - 8, - 1, - 2, - 3, - 1, - 2, - 4, - 1, - 2, - 5, - 1, - 2, - 6, - 1, - 2, - 7, - 1, - 2, - 8, - 1, - 3, - 4, - 1, - 3, - 5, - 1, - 3, - 6, - 1, - 3, - 7, - 1, - 3, - 8, - 1, - 4, - 5, - 1, - 4, - 6, - 1, - 4, - 7, - 1, - 4, - 8, - 1, - 5, - 6, - 1, - 5, - 7, - 1, - 5, - 8, - 1, - 6, - 7, - 1, - 6, - 8, - 1, - 7, - 8, - 2, - 3, - 4, - 2, - 3, - 5, - 2, - 3, - 6, - 2, - 3, - 7, - 2, - 3, - 8, - 2, - 4, - 5, - 2, - 4, - 6, - 2, - 4, - 7, - 2, - 4, - 8, - 2, - 5, - 6, - 2, - 5, - 7, - 2, - 5, - 8, - 2, - 6, - 7, - 2, - 6, - 8, - 2, - 7, - 8, - 3, - 4, - 5, - 3, - 4, - 6, - 3, - 4, - 7, - 3, - 4, - 8, - 3, - 5, - 6, - 3, - 5, - 7, - 3, - 5, - 8, - 3, - 6, - 7, - 3, - 6, - 8, - 3, - 7, - 8, - 4, - 5, - 6, - 4, - 5, - 7, - 4, - 5, - 8, - 4, - 6, - 7, - 4, - 6, - 8, - 4, - 7, - 8, - 5, - 6, - 7, - 5, - 6, - 8, - 5, - 7, - 8, - 6, - 7, - 8, - ), - dtype=np.int32, - ).reshape(84, 3) - - num_kernels = len(indices) - num_dilations = len(dilations) - - num_features = num_kernels * np.sum(num_features_per_dilation) - - features = np.zeros((n_cases, num_features), dtype=np.float32) - - for example_index in prange(n_cases): - input_length = np.int64(L[example_index]) - - b = np.sum(L[0 : example_index + 1]) - a = b - input_length - - _X = X[:, a:b] - - A = -_X # A = alpha * X = -X - G = _X + _X + _X # G = gamma * X = 3X - - feature_index_start = 0 - - combination_index = 0 - num_channels_start = 0 - - for dilation_index in range(num_dilations): - dilation = dilations[dilation_index] - padding = ((9 - 1) * dilation) // 2 - - num_features_this_dilation = num_features_per_dilation[dilation_index] - - C_alpha = np.zeros((num_channels, input_length), dtype=np.float32) - C_alpha[:] = A - - C_gamma = np.zeros((9, num_channels, input_length), dtype=np.float32) - C_gamma[9 // 2] = G - - start = dilation - end = input_length - padding - - for gamma_index in range(9 // 2): - # thanks to Murtaza Jafferji @murtazajafferji for suggesting this fix - if end > 0: - C_alpha[:, -end:] = C_alpha[:, -end:] + A[:, :end] - C_gamma[gamma_index, :, -end:] = G[:, :end] - - end += dilation - - for gamma_index in range(9 // 2 + 1, 9): - if start < input_length: - C_alpha[:, :-start] = C_alpha[:, :-start] + A[:, start:] - C_gamma[gamma_index, :, :-start] = G[:, start:] - - start += dilation - - for kernel_index in range(num_kernels): - feature_index_end = feature_index_start + num_features_this_dilation - - num_channels_this_combination = num_channels_per_combination[ - combination_index - ] - - num_channels_end = num_channels_start + num_channels_this_combination - - channels_this_combination = channel_indices[ - num_channels_start:num_channels_end - ] - - index_0, index_1, index_2 = indices[kernel_index] - - C = ( - C_alpha[channels_this_combination] - + C_gamma[index_0][channels_this_combination] - + C_gamma[index_1][channels_this_combination] - + C_gamma[index_2][channels_this_combination] - ) - C = np.sum(C, axis=0) - - for feature_count in range(num_features_this_dilation): - features[example_index, feature_index_start + feature_count] = _PPV( - C, biases[feature_index_start + feature_count] - ).mean() - - feature_index_start = feature_index_end - - combination_index += 1 - num_channels_start = num_channels_end - - return features diff --git a/aeon/transformations/collection/convolution_based/_multirocket.py b/aeon/transformations/collection/convolution_based/_multirocket.py index f9207ecc9b..2b6dcf5a51 100644 --- a/aeon/transformations/collection/convolution_based/_multirocket.py +++ b/aeon/transformations/collection/convolution_based/_multirocket.py @@ -19,10 +19,10 @@ class MultiRocket(BaseCollectionTransformer): Parameters ---------- - num_kernels : int, default = 6,250 + n_kernels : int, default = 6,250 Number of random convolutional kernels. The calculated number of features is the nearest multiple of ``n_features_per_kernel(default 4)*84=336 < 50,000`` - (``2*n_features_per_kernel(default 4)*num_kernels(default 6,250)``). + (``2*n_features_per_kernel(default 4)*n_kernels(default 6,250)``). max_dilations_per_kernel : int, default = 32 Maximum number of dilations per kernel. n_features_per_kernel : int, default = 4 @@ -63,9 +63,9 @@ class MultiRocket(BaseCollectionTransformer): >>> from aeon.datasets import load_unit_test >>> X_train, y_train = load_unit_test(split="train") >>> X_test, y_test = load_unit_test(split="test") - >>> trf = MultiRocket(num_kernels=512) + >>> trf = MultiRocket(n_kernels=512) >>> trf.fit(X_train) - MultiRocket(num_kernels=512) + MultiRocket(n_kernels=512) >>> X_train = trf.transform(X_train) >>> X_test = trf.transform(X_test) """ @@ -81,7 +81,7 @@ class MultiRocket(BaseCollectionTransformer): def __init__( self, - num_kernels=6_250, + n_kernels=6_250, max_dilations_per_kernel=32, n_features_per_kernel=4, normalise=False, @@ -91,7 +91,7 @@ def __init__( self.max_dilations_per_kernel = max_dilations_per_kernel self.n_features_per_kernel = n_features_per_kernel - self.num_kernels = num_kernels + self.n_kernels = n_kernels self.normalise = normalise self.n_jobs = n_jobs @@ -202,80 +202,78 @@ def _transform(self, X, y=None): def _fit_univariate(self, X): _, input_length = X.shape - num_kernels = 84 + n_kernels = 84 - dilations, num_features_per_dilation = _fit_dilations( - input_length, self.num_kernels, self.max_dilations_per_kernel + dilations, n_features_per_dilation = _fit_dilations( + input_length, self.n_kernels, self.max_dilations_per_kernel ) - num_features_per_kernel = np.sum(num_features_per_dilation) + n_features_per_kernel = np.sum(n_features_per_dilation) - quantiles = _quantiles(num_kernels * num_features_per_kernel) + quantiles = _quantiles(n_kernels * n_features_per_kernel) biases = _fit_biases_univariate( X, dilations, - num_features_per_dilation, + n_features_per_dilation, quantiles, MultiRocket._indices, self.random_state_, ) - return dilations, num_features_per_dilation, biases + return dilations, n_features_per_dilation, biases def _fit_multivariate(self, X): - _, num_channels, input_length = X.shape + _, n_channels, input_length = X.shape - num_kernels = 84 + n_kernels = 84 - dilations, num_features_per_dilation = _fit_dilations( - input_length, self.num_kernels, self.max_dilations_per_kernel + dilations, n_features_per_dilation = _fit_dilations( + input_length, self.n_kernels, self.max_dilations_per_kernel ) - num_features_per_kernel = np.sum(num_features_per_dilation) + n_features_per_kernel = np.sum(n_features_per_dilation) - quantiles = _quantiles(num_kernels * num_features_per_kernel) + quantiles = _quantiles(n_kernels * n_features_per_kernel) - num_dilations = len(dilations) - num_combinations = num_kernels * num_dilations + n_dilations = len(dilations) + n_combinations = n_kernels * n_dilations - max_num_channels = min(num_channels, 9) - max_exponent = np.log2(max_num_channels + 1) + max_n_channels = min(n_channels, 9) + max_exponent = np.log2(max_n_channels + 1) - num_channels_per_combination = ( - 2 ** np.random.uniform(0, max_exponent, num_combinations) + n_channels_per_combination = ( + 2 ** np.random.uniform(0, max_exponent, n_combinations) ).astype(np.int32) - channel_indices = np.zeros(num_channels_per_combination.sum(), dtype=np.int32) + channel_indices = np.zeros(n_channels_per_combination.sum(), dtype=np.int32) - num_channels_start = 0 - for combination_index in range(num_combinations): - num_channels_this_combination = num_channels_per_combination[ - combination_index - ] - num_channels_end = num_channels_start + num_channels_this_combination - channel_indices[num_channels_start:num_channels_end] = np.random.choice( - num_channels, num_channels_this_combination, replace=False + n_channels_start = 0 + for combination_index in range(n_combinations): + n_channels_this_combination = n_channels_per_combination[combination_index] + n_channels_end = n_channels_start + n_channels_this_combination + channel_indices[n_channels_start:n_channels_end] = np.random.choice( + n_channels, n_channels_this_combination, replace=False ) - num_channels_start = num_channels_end + n_channels_start = n_channels_end biases = _fit_biases_multivariate( X, - num_channels_per_combination, + n_channels_per_combination, channel_indices, dilations, - num_features_per_dilation, + n_features_per_dilation, quantiles, MultiRocket._indices, self.random_state_, ) return ( - num_channels_per_combination, + n_channels_per_combination, channel_indices, dilations, - num_features_per_dilation, + n_features_per_dilation, biases, ) @@ -294,17 +292,17 @@ def _transform_uni( np.random.seed(seed) n_cases, n_timepoints = X.shape - dilations, num_features_per_dilation, biases = parameters - dilations1, num_features_per_dilation1, biases1 = parameters1 - num_kernels = len(indices) - num_dilations = len(dilations) - num_dilations1 = len(dilations1) + dilations, n_features_per_dilation, biases = parameters + dilations1, n_features_per_dilation1, biases1 = parameters1 + n_kernels = len(indices) + n_dilations = len(dilations) + n_dilations1 = len(dilations1) - num_features = num_kernels * np.sum(num_features_per_dilation) - num_features1 = num_kernels * np.sum(num_features_per_dilation1) + n_features = n_kernels * np.sum(n_features_per_dilation) + n_features1 = n_kernels * np.sum(n_features_per_dilation1) features = np.zeros( - (n_cases, (num_features + num_features1) * n_features_per_kernel), + (n_cases, (n_features + n_features1) * n_features_per_kernel), dtype=np.float32, ) n_features_per_transform = np.int64(features.shape[1] / 2) @@ -318,13 +316,13 @@ def _transform_uni( # Base series feature_index_start = 0 - for dilation_index in range(num_dilations): + for dilation_index in range(n_dilations): _padding0 = dilation_index % 2 dilation = dilations[dilation_index] padding = ((9 - 1) * dilation) // 2 - num_features_this_dilation = num_features_per_dilation[dilation_index] + n_features_this_dilation = n_features_per_dilation[dilation_index] C_alpha = np.zeros(n_timepoints, dtype=np.float32) C_alpha[:] = A @@ -347,8 +345,8 @@ def _transform_uni( start += dilation - for kernel_index in range(num_kernels): - feature_index_end = feature_index_start + num_features_this_dilation + for kernel_index in range(n_kernels): + feature_index_end = feature_index_start + n_features_this_dilation _padding1 = (_padding0 + kernel_index) % 2 @@ -357,7 +355,7 @@ def _transform_uni( C = C_alpha + C_gamma[index_0] + C_gamma[index_1] + C_gamma[index_2] if _padding1 == 0: - for feature_count in range(num_features_this_dilation): + for feature_count in range(n_features_this_dilation): feature_index = feature_index_start + feature_count _bias = biases[feature_index] @@ -383,18 +381,18 @@ def _transform_uni( end = feature_index features[example_index, end] = ppv / C.shape[0] - end = end + num_features + end = end + n_features features[example_index, end] = max_stretch - end = end + num_features + end = end + n_features features[example_index, end] = mean / ppv if ppv > 0 else 0 - end = end + num_features + end = end + n_features features[example_index, end] = ( mean_index / ppv if ppv > 0 else -1 ) else: _c = C[padding:-padding] - for feature_count in range(num_features_this_dilation): + for feature_count in range(n_features_this_dilation): feature_index = feature_index_start + feature_count _bias = biases[feature_index] @@ -420,11 +418,11 @@ def _transform_uni( end = feature_index features[example_index, end] = ppv / _c.shape[0] - end = end + num_features + end = end + n_features features[example_index, end] = max_stretch - end = end + num_features + end = end + n_features features[example_index, end] = mean / ppv if ppv > 0 else 0 - end = end + num_features + end = end + n_features features[example_index, end] = ( mean_index / ppv if ppv > 0 else -1 ) @@ -438,13 +436,13 @@ def _transform_uni( feature_index_start = 0 - for dilation_index in range(num_dilations1): + for dilation_index in range(n_dilations1): _padding0 = dilation_index % 2 dilation = dilations1[dilation_index] padding = ((9 - 1) * dilation) // 2 - num_features_this_dilation = num_features_per_dilation1[dilation_index] + n_features_this_dilation = n_features_per_dilation1[dilation_index] C_alpha = np.zeros(n_timepoints - 1, dtype=np.float32) C_alpha[:] = A1 @@ -467,8 +465,8 @@ def _transform_uni( start += dilation - for kernel_index in range(num_kernels): - feature_index_end = feature_index_start + num_features_this_dilation + for kernel_index in range(n_kernels): + feature_index_end = feature_index_start + n_features_this_dilation _padding1 = (_padding0 + kernel_index) % 2 @@ -477,7 +475,7 @@ def _transform_uni( C = C_alpha + C_gamma[index_0] + C_gamma[index_1] + C_gamma[index_2] if _padding1 == 0: - for feature_count in range(num_features_this_dilation): + for feature_count in range(n_features_this_dilation): feature_index = feature_index_start + feature_count _bias = biases1[feature_index] @@ -503,18 +501,18 @@ def _transform_uni( end = feature_index + n_features_per_transform features[example_index, end] = ppv / C.shape[0] - end = end + num_features + end = end + n_features features[example_index, end] = max_stretch - end = end + num_features + end = end + n_features features[example_index, end] = mean / ppv if ppv > 0 else 0 - end = end + num_features + end = end + n_features features[example_index, end] = ( mean_index / ppv if ppv > 0 else -1 ) else: _c = C[padding:-padding] - for feature_count in range(num_features_this_dilation): + for feature_count in range(n_features_this_dilation): feature_index = feature_index_start + feature_count _bias = biases1[feature_index] @@ -540,11 +538,11 @@ def _transform_uni( end = feature_index + n_features_per_transform features[example_index, end] = ppv / _c.shape[0] - end = end + num_features + end = end + n_features features[example_index, end] = max_stretch - end = end + num_features + end = end + n_features features[example_index, end] = mean / ppv if ppv > 0 else 0 - end = end + num_features + end = end + n_features features[example_index, end] = ( mean_index / ppv if ppv > 0 else -1 ) @@ -568,25 +566,25 @@ def _transform_multi( ): n_cases, n_channels, n_timepoints = X.shape ( - num_channels_per_combination, + n_channels_per_combination, channel_indices, dilations, - num_features_per_dilation, + n_features_per_dilation, biases, ) = parameters if seed is not None: np.random.seed(seed) - _, _, dilations1, num_features_per_dilation1, biases1 = parameters1 - num_kernels = len(indices) - num_dilations = len(dilations) - num_dilations1 = len(dilations1) + _, _, dilations1, n_features_per_dilation1, biases1 = parameters1 + n_kernels = len(indices) + n_dilations = len(dilations) + n_dilations1 = len(dilations1) - num_features = num_kernels * np.sum(num_features_per_dilation) - num_features1 = num_kernels * np.sum(num_features_per_dilation1) + n_features = n_kernels * np.sum(n_features_per_dilation) + n_features1 = n_kernels * np.sum(n_features_per_dilation1) features = np.zeros( - (n_cases, (num_features + num_features1) * n_features_per_kernel), + (n_cases, (n_features + n_features1) * n_features_per_kernel), dtype=np.float32, ) n_features_per_transform = np.int64(features.shape[1] / 2) @@ -600,15 +598,15 @@ def _transform_multi( feature_index_start = 0 combination_index = 0 - num_channels_start = 0 + n_channels_start = 0 - for dilation_index in range(num_dilations): + for dilation_index in range(n_dilations): _padding0 = dilation_index % 2 dilation = dilations[dilation_index] padding = ((9 - 1) * dilation) // 2 - num_features_this_dilation = num_features_per_dilation[dilation_index] + n_features_this_dilation = n_features_per_dilation[dilation_index] C_alpha = np.zeros((n_channels, n_timepoints), dtype=np.float32) C_alpha[:] = A @@ -631,17 +629,17 @@ def _transform_multi( start += dilation - for kernel_index in range(num_kernels): - feature_index_end = feature_index_start + num_features_this_dilation + for kernel_index in range(n_kernels): + feature_index_end = feature_index_start + n_features_this_dilation - num_channels_this_combination = num_channels_per_combination[ + n_channels_this_combination = n_channels_per_combination[ combination_index ] - num_channels_end = num_channels_start + num_channels_this_combination + n_channels_end = n_channels_start + n_channels_this_combination channels_this_combination = channel_indices[ - num_channels_start:num_channels_end + n_channels_start:n_channels_end ] _padding1 = (_padding0 + kernel_index) % 2 @@ -657,7 +655,7 @@ def _transform_multi( C = np.sum(C, axis=0) if _padding1 == 0: - for feature_count in range(num_features_this_dilation): + for feature_count in range(n_features_this_dilation): feature_index = feature_index_start + feature_count _bias = biases[feature_index] @@ -683,18 +681,18 @@ def _transform_multi( end = feature_index features[example_index, end] = ppv / C.shape[0] - end = end + num_features + end = end + n_features features[example_index, end] = max_stretch - end = end + num_features + end = end + n_features features[example_index, end] = mean / ppv if ppv > 0 else 0 - end = end + num_features + end = end + n_features features[example_index, end] = ( mean_index / ppv if ppv > 0 else -1 ) else: _c = C[padding:-padding] - for feature_count in range(num_features_this_dilation): + for feature_count in range(n_features_this_dilation): feature_index = feature_index_start + feature_count _bias = biases[feature_index] @@ -720,11 +718,11 @@ def _transform_multi( end = feature_index features[example_index, end] = ppv / _c.shape[0] - end = end + num_features + end = end + n_features features[example_index, end] = max_stretch - end = end + num_features + end = end + n_features features[example_index, end] = mean / ppv if ppv > 0 else 0 - end = end + num_features + end = end + n_features features[example_index, end] = ( mean_index / ppv if ppv > 0 else -1 ) @@ -732,7 +730,7 @@ def _transform_multi( feature_index_start = feature_index_end combination_index += 1 - num_channels_start = num_channels_end + n_channels_start = n_channels_end # First order difference _X1 = X1[example_index] @@ -742,15 +740,15 @@ def _transform_multi( feature_index_start = 0 combination_index = 0 - num_channels_start = 0 + n_channels_start = 0 - for dilation_index in range(num_dilations1): + for dilation_index in range(n_dilations1): _padding0 = dilation_index % 2 dilation = dilations1[dilation_index] padding = ((9 - 1) * dilation) // 2 - num_features_this_dilation = num_features_per_dilation1[dilation_index] + n_features_this_dilation = n_features_per_dilation1[dilation_index] C_alpha = np.zeros((n_channels, n_timepoints - 1), dtype=np.float32) C_alpha[:] = A1 @@ -773,17 +771,17 @@ def _transform_multi( start += dilation - for kernel_index in range(num_kernels): - feature_index_end = feature_index_start + num_features_this_dilation + for kernel_index in range(n_kernels): + feature_index_end = feature_index_start + n_features_this_dilation - num_channels_this_combination = num_channels_per_combination[ + n_channels_this_combination = n_channels_per_combination[ combination_index ] - num_channels_end = num_channels_start + num_channels_this_combination + n_channels_end = n_channels_start + n_channels_this_combination channels_this_combination = channel_indices[ - num_channels_start:num_channels_end + n_channels_start:n_channels_end ] _padding1 = (_padding0 + kernel_index) % 2 @@ -799,7 +797,7 @@ def _transform_multi( C = np.sum(C, axis=0) if _padding1 == 0: - for feature_count in range(num_features_this_dilation): + for feature_count in range(n_features_this_dilation): feature_index = feature_index_start + feature_count _bias = biases1[feature_index] @@ -825,18 +823,18 @@ def _transform_multi( end = feature_index + n_features_per_transform features[example_index, end] = ppv / C.shape[0] - end = end + num_features + end = end + n_features features[example_index, end] = max_stretch - end = end + num_features + end = end + n_features features[example_index, end] = mean / ppv if ppv > 0 else 0 - end = end + num_features + end = end + n_features features[example_index, end] = ( mean_index / ppv if ppv > 0 else -1 ) else: _c = C[padding:-padding] - for feature_count in range(num_features_this_dilation): + for feature_count in range(n_features_this_dilation): feature_index = feature_index_start + feature_count _bias = biases1[feature_index] @@ -862,11 +860,11 @@ def _transform_multi( end = feature_index + n_features_per_transform features[example_index, end] = ppv / _c.shape[0] - end = end + num_features + end = end + n_features features[example_index, end] = max_stretch - end = end + num_features + end = end + n_features features[example_index, end] = mean / ppv if ppv > 0 else 0 - end = end + num_features + end = end + n_features features[example_index, end] = ( mean_index / ppv if ppv > 0 else -1 ) @@ -883,31 +881,31 @@ def _transform_multi( cache=True, ) def _fit_biases_univariate( - X, dilations, num_features_per_dilation, quantiles, indices, seed + X, dilations, n_features_per_dilation, quantiles, indices, seed ): if seed is not None: np.random.seed(seed) - num_examples, input_length = X.shape - num_kernels = len(indices) - num_dilations = len(dilations) + n_cases, input_length = X.shape + n_kernels = len(indices) + n_dilations = len(dilations) - num_features = num_kernels * np.sum(num_features_per_dilation) + n_features = n_kernels * np.sum(n_features_per_dilation) - biases = np.zeros(num_features, dtype=np.float32) + biases = np.zeros(n_features, dtype=np.float32) feature_index_start = 0 - for dilation_index in range(num_dilations): + for dilation_index in range(n_dilations): dilation = dilations[dilation_index] padding = ((9 - 1) * dilation) // 2 - num_features_this_dilation = num_features_per_dilation[dilation_index] + n_features_this_dilation = n_features_per_dilation[dilation_index] - for kernel_index in range(num_kernels): - feature_index_end = feature_index_start + num_features_this_dilation + for kernel_index in range(n_kernels): + feature_index_end = feature_index_start + n_features_this_dilation - _X = X[np.random.randint(num_examples)] + _X = X[np.random.randint(n_cases)] A = -_X # A = alpha * X = -X G = _X + _X + _X # G = gamma * X = 3X @@ -955,10 +953,10 @@ def _fit_biases_univariate( ) def _fit_biases_multivariate( X, - num_channels_per_combination, + n_channels_per_combination, channel_indices, dilations, - num_features_per_dilation, + n_features_per_dilation, quantiles, indices, seed, @@ -966,51 +964,47 @@ def _fit_biases_multivariate( if seed is not None: np.random.seed(seed) - num_examples, num_channels, input_length = X.shape + n_cases, n_channels, input_length = X.shape - num_kernels = len(indices) - num_dilations = len(dilations) + n_kernels = len(indices) + n_dilations = len(dilations) - num_features = num_kernels * np.sum(num_features_per_dilation) + n_features = n_kernels * np.sum(n_features_per_dilation) - biases = np.zeros(num_features, dtype=np.float32) + biases = np.zeros(n_features, dtype=np.float32) feature_index_start = 0 combination_index = 0 - num_channels_start = 0 + n_channels_start = 0 - for dilation_index in range(num_dilations): + for dilation_index in range(n_dilations): dilation = dilations[dilation_index] padding = ((9 - 1) * dilation) // 2 - num_features_this_dilation = num_features_per_dilation[dilation_index] + n_features_this_dilation = n_features_per_dilation[dilation_index] - for kernel_index in range(num_kernels): - feature_index_end = feature_index_start + num_features_this_dilation + for kernel_index in range(n_kernels): + feature_index_end = feature_index_start + n_features_this_dilation - num_channels_this_combination = num_channels_per_combination[ - combination_index - ] + n_channels_this_combination = n_channels_per_combination[combination_index] - num_channels_end = num_channels_start + num_channels_this_combination + n_channels_end = n_channels_start + n_channels_this_combination - channels_this_combination = channel_indices[ - num_channels_start:num_channels_end - ] + channels_this_combination = channel_indices[n_channels_start:n_channels_end] - _X = X[np.random.randint(num_examples)][channels_this_combination] + _X = X[np.random.randint(n_cases)][channels_this_combination] A = -_X # A = alpha * X = -X G = _X + _X + _X # G = gamma * X = 3X C_alpha = np.zeros( - (num_channels_this_combination, input_length), dtype=np.float32 + (n_channels_this_combination, input_length), dtype=np.float32 ) C_alpha[:] = A C_gamma = np.zeros( - (9, num_channels_this_combination, input_length), dtype=np.float32 + (9, n_channels_this_combination, input_length), dtype=np.float32 ) C_gamma[9 // 2] = G @@ -1041,39 +1035,37 @@ def _fit_biases_multivariate( feature_index_start = feature_index_end combination_index += 1 - num_channels_start = num_channels_end + n_channels_start = n_channels_end return biases -def _fit_dilations(input_length, num_features, max_dilations_per_kernel): - num_kernels = 84 +def _fit_dilations(input_length, n_features, max_dilations_per_kernel): + n_kernels = 84 - num_features_per_kernel = num_features // num_kernels - true_max_dilations_per_kernel = min( - num_features_per_kernel, max_dilations_per_kernel - ) - multiplier = num_features_per_kernel / true_max_dilations_per_kernel + n_features_per_kernel = n_features // n_kernels + true_max_dilations_per_kernel = min(n_features_per_kernel, max_dilations_per_kernel) + multiplier = n_features_per_kernel / true_max_dilations_per_kernel max_exponent = np.log2((input_length - 1) / (9 - 1)) - dilations, num_features_per_dilation = np.unique( + dilations, n_features_per_dilation = np.unique( np.logspace(0, max_exponent, true_max_dilations_per_kernel, base=2).astype( np.int32 ), return_counts=True, ) - num_features_per_dilation = (num_features_per_dilation * multiplier).astype( + n_features_per_dilation = (n_features_per_dilation * multiplier).astype( np.int32 ) # this is a vector - remainder = num_features_per_kernel - np.sum(num_features_per_dilation) + remainder = n_features_per_kernel - np.sum(n_features_per_dilation) i = 0 while remainder > 0: - num_features_per_dilation[i] += 1 + n_features_per_dilation[i] += 1 remainder -= 1 - i = (i + 1) % len(num_features_per_dilation) + i = (i + 1) % len(n_features_per_dilation) - return dilations, num_features_per_dilation + return dilations, n_features_per_dilation # low-discrepancy sequence to assign quantiles to kernel/dilation combinations diff --git a/aeon/transformations/collection/convolution_based/_rocket.py b/aeon/transformations/collection/convolution_based/_rocket.py index e5c4e39ebe..6a7e104d46 100644 --- a/aeon/transformations/collection/convolution_based/_rocket.py +++ b/aeon/transformations/collection/convolution_based/_rocket.py @@ -1,12 +1,12 @@ """Rocket transformer.""" -__maintainer__ = [] +__maintainer__ = ["TonyBagnall"] __all__ = ["Rocket"] import numpy as np from numba import get_num_threads, njit, prange, set_num_threads -from aeon.transformations.collection import BaseCollectionTransformer +from aeon.transformations.collection import BaseCollectionTransformer, Normalizer from aeon.utils.validation import check_n_jobs @@ -26,7 +26,7 @@ class Rocket(BaseCollectionTransformer): Parameters ---------- - num_kernels : int, default=10,000 + n_kernels : int, default=10,000 Number of random convolutional kernels. normalise : bool, default True Whether or not to normalise the input time series per instance. @@ -55,9 +55,9 @@ class Rocket(BaseCollectionTransformer): >>> from aeon.datasets import load_unit_test >>> X_train, y_train = load_unit_test(split="train") >>> X_test, y_test = load_unit_test(split="test") - >>> trf = Rocket(num_kernels=512) + >>> trf = Rocket(n_kernels=512) >>> trf.fit(X_train) - Rocket(num_kernels=512) + Rocket(n_kernels=512) >>> X_train = trf.transform(X_train) >>> X_test = trf.transform(X_test) """ @@ -67,16 +67,17 @@ class Rocket(BaseCollectionTransformer): "capability:multivariate": True, "capability:multithreading": True, "algorithm_type": "convolution", + "X_inner_type": "numpy3D", } def __init__( self, - num_kernels=10_000, + n_kernels=10_000, normalise=True, n_jobs=1, random_state=None, ): - self.num_kernels = num_kernels + self.n_kernels = n_kernels self.normalise = normalise self.n_jobs = n_jobs self.random_state = random_state @@ -102,10 +103,12 @@ def _fit(self, X, y=None): self._random_state = self.random_state else: self._random_state = None + n_channels = X[0].shape[0] - _, n_channels, n_timepoints = X.shape + # The only use of n_timepoints is to set the maximum dilation + self.fit_min_length_ = X[0].shape[1] self.kernels = _generate_kernels( - n_timepoints, self.num_kernels, n_channels, self._random_state + self.fit_min_length_, self.n_kernels, n_channels, self._random_state ) return self @@ -120,35 +123,31 @@ def _transform(self, X, y=None): Returns ------- - np.ndarray (n_cases, num_kernels), transformed features + np.ndarray (n_cases, n_kernels), transformed features """ if self.normalise: - X = (X - X.mean(axis=-1, keepdims=True)) / ( - X.std(axis=-1, keepdims=True) + 1e-8 - ) + norm = Normalizer() + X = norm.fit_transform(X) prev_threads = get_num_threads() n_jobs = check_n_jobs(self.n_jobs) set_num_threads(n_jobs) - X_ = _apply_kernels(X.astype(np.float32), self.kernels) + X_ = _apply_kernels(X, self.kernels) + set_num_threads(prev_threads) return X_ -@njit( - "Tuple((float32[:],int32[:],float32[:],int32[:],int32[:],int32[:]," - "int32[:]))(int32,int32,int32,optional(int32))", - cache=True, -) -def _generate_kernels(n_timepoints, num_kernels, n_channels, seed): +@njit(fastmath=True, cache=True) +def _generate_kernels(n_timepoints, n_kernels, n_channels, seed): if seed is not None: np.random.seed(seed) candidate_lengths = np.array((7, 9, 11), dtype=np.int32) - lengths = np.random.choice(candidate_lengths, num_kernels).astype(np.int32) + lengths = np.random.choice(candidate_lengths, n_kernels).astype(np.int32) - num_channel_indices = np.zeros(num_kernels, dtype=np.int32) - for i in range(num_kernels): + num_channel_indices = np.zeros(n_kernels, dtype=np.int32) + for i in range(n_kernels): limit = min(n_channels, lengths[i]) num_channel_indices[i] = 2 ** np.random.uniform(0, np.log2(limit + 1)) @@ -160,14 +159,14 @@ def _generate_kernels(n_timepoints, num_kernels, n_channels, seed): ), dtype=np.float32, ) - biases = np.zeros(num_kernels, dtype=np.float32) - dilations = np.zeros(num_kernels, dtype=np.int32) - paddings = np.zeros(num_kernels, dtype=np.int32) + biases = np.zeros(n_kernels, dtype=np.float32) + dilations = np.zeros(n_kernels, dtype=np.int32) + paddings = np.zeros(n_kernels, dtype=np.int32) a1 = 0 # for weights a2 = 0 # for channel_indices - for i in range(num_kernels): + for i in range(n_kernels): _length = lengths[i] _num_channel_indices = num_channel_indices[i] @@ -215,8 +214,71 @@ def _generate_kernels(n_timepoints, num_kernels, n_channels, seed): ) +@njit( + parallel=True, + fastmath=True, + cache=True, +) +def _apply_kernels(X, kernels): + ( + weights, + lengths, + biases, + dilations, + paddings, + n_channel_indices, + channel_indices, + ) = kernels + n_cases = len(X) + n_channels, _ = X[0].shape + n_kernels = len(lengths) + + _X = np.zeros((n_cases, n_kernels * 2), dtype=np.float32) # 2 features per kernel + + for i in prange(n_cases): + a1 = 0 # for weights + a2 = 0 # for channel_indices + a3 = 0 # for features + + for j in range(n_kernels): + b1 = a1 + n_channel_indices[j] * lengths[j] + b2 = a2 + n_channel_indices[j] + b3 = a3 + 2 + + if n_channel_indices[j] == 1: + _X[i][a3:b3] = _apply_kernel_univariate( + X[i][channel_indices[a2]], + weights[a1:b1], + lengths[j], + biases[j], + dilations[j], + paddings[j], + ) + + else: + _weights = weights[a1:b1].reshape((n_channel_indices[j], lengths[j])) + + _X[i][a3:b3] = _apply_kernel_multivariate( + X[i], + _weights, + lengths[j], + biases[j], + dilations[j], + paddings[j], + n_channel_indices[j], + channel_indices[a2:b2], + ) + + a1 = b1 + a2 = b2 + a3 = b3 + + return _X.astype(np.float32) + + @njit(fastmath=True, cache=True) def _apply_kernel_univariate(X, weights, length, bias, dilation, padding): + """Apply a single kernel to a univariate series.""" n_timepoints = len(X) output_length = (n_timepoints + (2 * padding)) - ((length - 1) * dilation) @@ -250,6 +312,7 @@ def _apply_kernel_univariate(X, weights, length, bias, dilation, padding): def _apply_kernel_multivariate( X, weights, length, bias, dilation, padding, num_channel_indices, channel_indices ): + """Apply a kernel to a single multivariate time series.""" n_columns, n_timepoints = X.shape output_length = (n_timepoints + (2 * padding)) - ((length - 1) * dilation) @@ -270,67 +333,3 @@ def _apply_kernel_multivariate( if _sum > 0: _ppv += 1 return np.float32(_ppv / output_length), np.float32(_max) - - -@njit( - "float32[:,:](float32[:,:,:],Tuple((float32[::1],int32[:],float32[:]," - "int32[:],int32[:],int32[:],int32[:])))", - parallel=True, - fastmath=True, - cache=True, -) -def _apply_kernels(X, kernels): - ( - weights, - lengths, - biases, - dilations, - paddings, - num_channel_indices, - channel_indices, - ) = kernels - - n_cases, n_channels, _ = X.shape - num_kernels = len(lengths) - - _X = np.zeros((n_cases, num_kernels * 2), dtype=np.float32) # 2 features per kernel - - for i in prange(n_cases): - a1 = 0 # for weights - a2 = 0 # for channel_indices - a3 = 0 # for features - - for j in range(num_kernels): - b1 = a1 + num_channel_indices[j] * lengths[j] - b2 = a2 + num_channel_indices[j] - b3 = a3 + 2 - - if num_channel_indices[j] == 1: - _X[i, a3:b3] = _apply_kernel_univariate( - X[i, channel_indices[a2]], - weights[a1:b1], - lengths[j], - biases[j], - dilations[j], - paddings[j], - ) - - else: - _weights = weights[a1:b1].reshape((num_channel_indices[j], lengths[j])) - - _X[i, a3:b3] = _apply_kernel_multivariate( - X[i], - _weights, - lengths[j], - biases[j], - dilations[j], - paddings[j], - num_channel_indices[j], - channel_indices[a2:b2], - ) - - a1 = b1 - a2 = b2 - a3 = b3 - - return _X.astype(np.float32) diff --git a/aeon/transformations/collection/convolution_based/rocketGPU/_rocket_gpu.py b/aeon/transformations/collection/convolution_based/rocketGPU/_rocket_gpu.py index 547c077aef..8521d18e30 100644 --- a/aeon/transformations/collection/convolution_based/rocketGPU/_rocket_gpu.py +++ b/aeon/transformations/collection/convolution_based/rocketGPU/_rocket_gpu.py @@ -3,6 +3,8 @@ __maintainer__ = ["hadifawaz1999"] __all__ = ["ROCKETGPU"] +import numpy as np + from aeon.transformations.collection.convolution_based.rocketGPU.base import ( BaseROCKETGPU, ) @@ -24,7 +26,7 @@ class ROCKETGPU(BaseROCKETGPU): Parameters ---------- - n_filters : int, default=10,000 + n_kernels : int, default=10000 Number of random convolutional filters. kernel_size : list, default = None The list of possible kernel sizes, default is [7, 9, 11]. @@ -51,7 +53,7 @@ class ROCKETGPU(BaseROCKETGPU): def __init__( self, - n_filters=1000, + n_kernels=10000, kernel_size=None, padding=None, use_dilation=True, @@ -59,9 +61,9 @@ def __init__( batch_size=64, random_state=None, ): - super().__init__(n_filters) + super().__init__(n_kernels) - self.n_filters = n_filters + self.n_kernels = n_kernels self.kernel_size = kernel_size self.padding = padding self.use_dilation = use_dilation @@ -71,8 +73,6 @@ def __init__( def _define_parameters(self): """Define the parameters of ROCKET.""" - import numpy as np - rng = np.random.default_rng(self.random_state) self._list_of_kernels = [] @@ -80,7 +80,7 @@ def _define_parameters(self): self._list_of_paddings = [] self._list_of_biases = [] - for _ in range(self.n_filters): + for _ in range(self.n_kernels): _kernel_size = rng.choice(self._kernel_size, size=1)[0] _convolution_kernel = rng.normal(size=(_kernel_size, self.n_channels, 1)) _convolution_kernel = _convolution_kernel - _convolution_kernel.mean( @@ -175,10 +175,9 @@ def _transform(self, X, y=None): Returns ------- - output_rocket : np.ndarray [n_cases, n_filters * 2] + output_rocket : np.ndarray [n_cases, n_kernels * 2] transformed features. """ - import numpy as np import tensorflow as tf tf.random.set_seed(self.random_state) @@ -189,7 +188,7 @@ def _transform(self, X, y=None): output_features = [] - for f in range(self.n_filters): + for f in range(self.n_kernels): output_features_filter = [] for batch_indices in batch_indices_list: @@ -244,6 +243,6 @@ def _get_test_params(cls, parameter_set="default"): `MyClass(**params)` or `MyClass(**params[i])` creates a valid test instance. """ params = { - "n_filters": 5, + "n_kernels": 5, } return params diff --git a/aeon/transformations/collection/convolution_based/rocketGPU/base.py b/aeon/transformations/collection/convolution_based/rocketGPU/base.py index 232e53e14e..7b3a2b71df 100644 --- a/aeon/transformations/collection/convolution_based/rocketGPU/base.py +++ b/aeon/transformations/collection/convolution_based/rocketGPU/base.py @@ -12,7 +12,7 @@ class BaseROCKETGPU(BaseCollectionTransformer): Parameters ---------- - nb_filters : int, default = 1000 + n_kernels : int, default = 10000 Number of random convolutional kernels. """ @@ -28,10 +28,10 @@ class BaseROCKETGPU(BaseCollectionTransformer): def __init__( self, - n_filters=10000, + n_kernels=10000, ): super().__init__() - self.n_filters = n_filters + self.n_kernels = n_kernels def _get_ppv(self, x): import tensorflow as tf diff --git a/aeon/transformations/collection/convolution_based/rocketGPU/tests/test_base_rocketGPU.py b/aeon/transformations/collection/convolution_based/rocketGPU/tests/test_base_rocketGPU.py index 9695b5b018..9cfa5e1104 100644 --- a/aeon/transformations/collection/convolution_based/rocketGPU/tests/test_base_rocketGPU.py +++ b/aeon/transformations/collection/convolution_based/rocketGPU/tests/test_base_rocketGPU.py @@ -26,8 +26,8 @@ class DummyROCKETGPU(BaseROCKETGPU): - def __init__(self, n_filters=1): - super().__init__(n_filters) + def __init__(self, n_kernels=1): + super().__init__(n_kernels) def _fit(self, X, y=None): """Generate random kernels adjusted to time series shape. @@ -58,7 +58,7 @@ def _transform(self, X, y=None): Returns ------- - output_rocket : np.ndarray [n_cases, n_filters * 2] + output_rocket : np.ndarray [n_cases, n_kernels * 2] transformed features. """ import numpy as np @@ -70,7 +70,7 @@ def _transform(self, X, y=None): _output_convolution = tf.nn.conv1d( input=X, - filters=rng.normal(size=(self.kernel_size, X.shape[-1], self.n_filters)), + filters=rng.normal(size=(self.kernel_size, X.shape[-1], self.n_kernels)), stride=1, padding="VALID", dilations=1, @@ -97,7 +97,7 @@ def test_base_rocketGPU_univariate(): """Test base rocket GPU functionality univariate.""" X, _ = make_example_2d_numpy_collection() - dummy_transform = DummyROCKETGPU(n_filters=1) + dummy_transform = DummyROCKETGPU(n_kernels=1) dummy_transform.fit(X) X_transform = dummy_transform.transform(X) @@ -118,7 +118,7 @@ def test_base_rocketGPU_multivariate(): """Test base rocket GPU functionality multivariate.""" X, _ = make_example_3d_numpy(n_channels=3) - dummy_transform = DummyROCKETGPU(n_filters=1) + dummy_transform = DummyROCKETGPU(n_kernels=1) dummy_transform.fit(X) X_transform = dummy_transform.transform(X) @@ -139,17 +139,15 @@ def test_base_rocketGPU_multivariate(): @pytest.mark.parametrize("n_channels", [1, 3]) def test_rocket_cpu_gpu(n_channels): """Test consistency between CPU and GPU versions of ROCKET.""" - random_seed = 42 - X, _ = make_example_3d_numpy(n_channels=n_channels) + random_state = 42 + X, _ = make_example_3d_numpy(n_channels=n_channels, random_state=random_state) - n_filters = 100 + n_kernels = 100 - rocket_cpu = Rocket( - num_kernels=n_filters, random_state=random_seed, normalise=False - ) + rocket_cpu = Rocket(n_kernels=n_kernels, random_state=random_state, normalise=False) rocket_cpu.fit(X) - rocket_gpu = ROCKETGPU(n_filters=n_filters, random_state=random_seed) + rocket_gpu = ROCKETGPU(n_kernels=n_kernels, random_state=random_state) rocket_gpu.fit(X) X_transform_cpu = rocket_cpu.transform(X) diff --git a/aeon/transformations/collection/convolution_based/tests/test_all_rockets.py b/aeon/transformations/collection/convolution_based/tests/test_all_rockets.py index b9439a1eaa..3140982f3f 100644 --- a/aeon/transformations/collection/convolution_based/tests/test_all_rockets.py +++ b/aeon/transformations/collection/convolution_based/tests/test_all_rockets.py @@ -55,16 +55,16 @@ def test_rocket_on_univariate(transform): # Create random univariate training data X = uni_test_data if transform == "Rocket": - rocket = Rocket(num_kernels=100, random_state=0) + rocket = Rocket(n_kernels=100, random_state=0) elif transform == "MiniRocket": - rocket = MiniRocket(num_kernels=100, random_state=0) + rocket = MiniRocket(n_kernels=100, random_state=0) elif transform == "MultiRocket": - rocket = MultiRocket(num_kernels=100, random_state=0) + rocket = MultiRocket(n_kernels=100, random_state=0) rocket.fit(X) # transform training data X_trans = rocket.transform(X) # test shape of transformed training data -> (number of training - # examples, num_kernels * 2) + # examples, n_kernels * 2) np.testing.assert_equal(X_trans.shape, (len(X), expected_features[transform])) np.testing.assert_almost_equal( np.array(expected_uni[transform]), @@ -84,17 +84,17 @@ def test_rocket_on_multivariate(transform): # Create random univariate training data X = multi_test_data if transform == "Rocket": - rocket = Rocket(num_kernels=100, random_state=0) + rocket = Rocket(n_kernels=100, random_state=0) elif transform == "MiniRocket": - rocket = MiniRocket(num_kernels=100, random_state=0) + rocket = MiniRocket(n_kernels=100, random_state=0) else: - rocket = MultiRocket(num_kernels=100, random_state=0) + rocket = MultiRocket(n_kernels=100, random_state=0) rocket.fit(X) # transform training data X_trans = rocket.transform(X) # test shape of transformed training data -> (number of training - # examples, num_kernels * 2) + # examples, n_kernels * 2) np.testing.assert_equal(X_trans.shape, (len(X), expected_features[transform])) np.testing.assert_almost_equal( np.array(expected_multi[transform]), @@ -110,10 +110,10 @@ def test_rocket_on_multivariate(transform): def test_normalise_rocket(): """Test normalization with Rocket.""" arr = np.random.random(size=(10, 1, 100)) - rocket = Rocket(num_kernels=200, normalise=True) + rocket = Rocket(n_kernels=200, normalise=True) trans = rocket.fit_transform(arr) assert trans.shape == (10, 400) - rocket = MultiRocket(num_kernels=200, normalise=True) + rocket = MultiRocket(n_kernels=200, normalise=True) trans = rocket.fit_transform(arr) assert trans.shape == (10, 1344) @@ -158,9 +158,9 @@ def test_normalise_rocket(): ] ) rockets = [ - Rocket(num_kernels=100), - MultiRocket(num_kernels=100), - MiniRocket(num_kernels=100), + Rocket(n_kernels=100), + MultiRocket(n_kernels=100), + MiniRocket(n_kernels=100), ] types = [np.float32, np.float64, np.int32, np.int64] data = [ diff --git a/aeon/transformations/collection/convolution_based/tests/test_minirocket.py b/aeon/transformations/collection/convolution_based/tests/test_minirocket.py index 954ca45fcf..2fee3781d6 100644 --- a/aeon/transformations/collection/convolution_based/tests/test_minirocket.py +++ b/aeon/transformations/collection/convolution_based/tests/test_minirocket.py @@ -1,24 +1,13 @@ -"""MiniRocketMultivariateVariable test code.""" +"""MinRocket tests.""" import numpy as np import pytest -from sklearn.linear_model import RidgeClassifierCV -from sklearn.metrics import accuracy_score -from sklearn.pipeline import make_pipeline -from sklearn.preprocessing import StandardScaler -from aeon.datasets import load_japanese_vowels -from aeon.transformations.collection.convolution_based import ( - MiniRocketMultivariateVariable, -) from aeon.transformations.collection.convolution_based._minirocket import ( _PPV, MiniRocket, _fit_dilations, ) -from aeon.transformations.collection.convolution_based._minirocket_mv import ( - _np_list_transposed2D_array_and_len_list, -) def test_minirocket_short_series(): @@ -29,79 +18,6 @@ def test_minirocket_short_series(): mini.fit(X) -def test_minirocket_multivariate_variable_on_japanese_vowels(): - """Test of MiniRocketMultivariate on japanese vowels.""" - # load training data - X_training, Y_training = load_japanese_vowels(split="train") - - # 'fit' MINIROCKET -> infer data dimensions, generate random kernels - num_kernels = 10_000 - minirocket_mv_var = MiniRocketMultivariateVariable( - num_kernels=num_kernels, - pad_value_short_series=0, - reference_length="max", - max_dilations_per_kernel=32, - n_jobs=1, - random_state=42, - ) - minirocket_mv_var.fit(X_training) - - # transform training data - X_training_transform = minirocket_mv_var.transform(X_training) - - # test shape of transformed training data -> (number of training - # examples, nearest multiple of 84 < 1000) - np.testing.assert_equal( - X_training_transform.shape, (len(X_training), 84 * (num_kernels // 84)) - ) - - # fit classifier - classifier = make_pipeline( - StandardScaler(with_mean=False), - RidgeClassifierCV(alphas=np.logspace(-3, 3, 10)), - ) - classifier.fit(X_training_transform, Y_training) - - # load test data - X_test, Y_test = load_japanese_vowels(split="test") - - # transform test data - X_test_transform = minirocket_mv_var.transform(X_test) - - # test shape of transformed test data -> (number of test examples, - # nearest multiple of 84 < 10,000) - np.testing.assert_equal( - X_test_transform.shape, (len(X_test), 84 * (num_kernels // 84)) - ) - - # predict (alternatively: 'classifier.score(X_test_transform, Y_test)') - predictions = classifier.predict(X_test_transform) - accuracy = accuracy_score(predictions, Y_test) - - # test accuracy, mean usually .987, and minimum .983 - assert accuracy > 0.97, "Test accuracy should be greater than 0.97" - - -x = np.random.random(size=(2, 9)) -arr2 = [x, x, x] -arr3 = [np.random.random(size=(2, 6)), x, x] -arr4 = [ - np.random.random(size=(2, 7)), - np.random.random(size=(2, 8)), - np.random.random(size=(2, 6)), -] -TEST_DATA = [np.random.random(size=(3, 2, 9)), arr2, arr3, arr4] - - -@pytest.mark.parametrize("data", TEST_DATA) -def test__np_list_transposed2D_array_and_len_list(data): - """Test the concatenation by channel works correctly.""" - trans, lengths = _np_list_transposed2D_array_and_len_list(data) - assert isinstance(trans, np.ndarray) - assert trans.shape == (2, 27) - assert len(lengths) == 3 and sum(lengths) == 27 - - def test__fit_dilations(): """Test for fitting the dilations.""" dilations, features_per_dilation = _fit_dilations(32, 168, 6) diff --git a/aeon/utils/tests/test_discovery.py b/aeon/utils/tests/test_discovery.py index fc4b4a2d41..9a0fcd6ee7 100644 --- a/aeon/utils/tests/test_discovery.py +++ b/aeon/utils/tests/test_discovery.py @@ -177,7 +177,7 @@ def test_all_estimators_list_tag_lookup(): ) assert DummyClassifier in estimators3 - assert len(estimators3) > len(estimators) and len(estimators3) > len(estimators2) + assert len(estimators3) > len(estimators) and len(estimators3) >= len(estimators2) estimators4 = all_estimators( tag_filter={"X_inner_type": "numpy2D"}, diff --git a/examples/classification/classification.ipynb b/examples/classification/classification.ipynb index 64e5d8d27e..3550f565a7 100644 --- a/examples/classification/classification.ipynb +++ b/examples/classification/classification.ipynb @@ -260,29 +260,36 @@ }, { "cell_type": "code", - "execution_count": 5, "metadata": { - "collapsed": false - }, - "outputs": [ - { - "data": { - "text/plain": "0.7885714285714286" - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-11-16T19:16:46.486243Z", + "start_time": "2024-11-16T19:15:42.973051Z" } - ], + }, "source": [ "from aeon.classification.convolution_based import RocketClassifier\n", "\n", - "rocket = RocketClassifier(num_kernels=2000)\n", + "rocket = RocketClassifier(n_kernels=2000)\n", "rocket.fit(arrow, arrow_labels)\n", "y_pred = rocket.predict(arrow_test)\n", "\n", "accuracy_score(arrow_test_labels, y_pred)" - ] + ], + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'arrow' is not defined", + "output_type": "error", + "traceback": [ + "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m", + "\u001B[1;31mNameError\u001B[0m Traceback (most recent call last)", + "Cell \u001B[1;32mIn[1], line 4\u001B[0m\n\u001B[0;32m 1\u001B[0m \u001B[38;5;28;01mfrom\u001B[39;00m \u001B[38;5;21;01maeon\u001B[39;00m\u001B[38;5;21;01m.\u001B[39;00m\u001B[38;5;21;01mclassification\u001B[39;00m\u001B[38;5;21;01m.\u001B[39;00m\u001B[38;5;21;01mconvolution_based\u001B[39;00m \u001B[38;5;28;01mimport\u001B[39;00m RocketClassifier\n\u001B[0;32m 3\u001B[0m rocket \u001B[38;5;241m=\u001B[39m RocketClassifier(n_kernels\u001B[38;5;241m=\u001B[39m\u001B[38;5;241m2000\u001B[39m)\n\u001B[1;32m----> 4\u001B[0m rocket\u001B[38;5;241m.\u001B[39mfit(\u001B[43marrow\u001B[49m, arrow_labels)\n\u001B[0;32m 5\u001B[0m y_pred \u001B[38;5;241m=\u001B[39m rocket\u001B[38;5;241m.\u001B[39mpredict(arrow_test)\n\u001B[0;32m 7\u001B[0m accuracy_score(arrow_test_labels, y_pred)\n", + "\u001B[1;31mNameError\u001B[0m: name 'arrow' is not defined" + ] + } + ], + "execution_count": 1 }, { "cell_type": "markdown", @@ -476,7 +483,7 @@ "cls = ClassifierChannelEnsemble(\n", " classifiers=[\n", " (\"DrCIF0\", DrCIFClassifier(n_estimators=5, n_intervals=2)),\n", - " (\"ROCKET3\", RocketClassifier(num_kernels=1000)),\n", + " (\"ROCKET3\", RocketClassifier(n_kernels=1000)),\n", " ],\n", " channels=[[0], [3, 4]],\n", ")\n", diff --git a/examples/classification/convolution_based.ipynb b/examples/classification/convolution_based.ipynb index 99b2841c89..17d022ed96 100644 --- a/examples/classification/convolution_based.ipynb +++ b/examples/classification/convolution_based.ipynb @@ -279,8 +279,8 @@ } ], "source": [ - "mini_r = MiniRocketClassifier(num_kernels=100)\n", - "multi_r = MultiRocketClassifier(num_kernels=100)\n", + "mini_r = MiniRocketClassifier(n_kernels=100)\n", + "multi_r = MultiRocketClassifier(n_kernels=100)\n", "mini_r.fit(motions, motions_labels)\n", "y_pred = mini_r.predict(motions_test)\n", "print(\" mini acc =\", accuracy_score(motions_test_labels, y_pred))\n", @@ -297,7 +297,7 @@ "method for time series classification using competing convolutional kernels, incorporating aspects \n", "of both Rocket and conventional dictionary methods. Hydra involves transforming \n", "the input time series using a set of random convolutional kernels, arranged into `g`\n", - "groups with `k` kernels per group, and then at each timepoint counting the kernels \n", + "groups with `k` kernels per group, and then at each timepoint counting the kernels\n", "representing the closest match with the input time series for each group." ] }, @@ -365,7 +365,7 @@ }, "source": [ "Convolutional classifiers have three other parameters that may affect performance.\n", - "`num_kernels` (default 10,000) determines the number of convolutions/kernels generated\n", + "`n_kernels` (default 10,000) determines the number of convolutions/kernels generated\n", " and will influence the memory usage. `max_dilations_per_kernel` (default=32) and\n", "`n_features_per_kernel` (default=4) are used in 'MiniROCKET' and 'MultiROCKET'. For\n", "each candidate convolution, `max_dilations_per_kernel` are assessed and\n", @@ -559,7 +559,7 @@ "operators and transformations for fast and effective time series classification\n", "[Journal Paper](https://link.springer.com/article/10.1007/s10618-022-00844-1)\n", "\n", - "[4] Dempster, A., Schmidt, D.F. and Webb, G.I. (2023) Hydra: Competing convolutional \n", + "[4] Dempster, A., Schmidt, D.F. and Webb, G.I. (2023) Hydra: Competing convolutional\n", "kernels for fast and accurate time series classification.\n", "[arXiv:2203.13652](https://arxiv.org/abs/2203.13652),\n", "[Journal Paper](https://link.springer.com/article/10.1007/s10618-023-00939-3)\n" diff --git a/examples/transformations/minirocket.ipynb b/examples/transformations/minirocket.ipynb index 91619248a0..c23d15623a 100644 --- a/examples/transformations/minirocket.ipynb +++ b/examples/transformations/minirocket.ipynb @@ -6,9 +6,9 @@ "source": [ "# MiniRocket\n", "\n", - "MiniRocket transforms input time series using a small, fixed set of convolutional kernels. MiniRocket uses PPV pooling to compute a single feature for each of the resulting feature maps (i.e., the proportion of positive values). The transformed features are used to train a linear classifier.\n", - "\n", - "Dempster A, Schmidt DF, Webb GI (2020) MiniRocket: A Very Fast (Almost) Deterministic Transform for Time Series Classification [arXiv:2012.08791](https://arxiv.org/abs/2012.08791)" + "MiniRocket [1] transforms input time series using a small, fixed set of convolutional\n", + "kernels. MiniRocket uses PPV pooling to compute a single feature for each of the resulting feature maps (i.e., the proportion of positive values). The transformed features are used to train a linear classifier.\n", + "\n" ] }, { @@ -19,108 +19,97 @@ "\n", "### 1.1 Imports\n", "\n", - "Import example data, MiniRocket, `RidgeClassifierCV` (scikit-learn), and NumPy.\n", + "Import example data, `MiniRocket`, `MiniRocketClassifier`, `MiniRocketRegressor`,\n", + "`RidgeClassifierCV` (scikit-learn), and ``numpy``.\n", + "\n", + "You can use the `MiniRocket`transform directly, in a pipeline, or in our baked in `MiniRocketClassifier` or `MiniRocketRegressor`.\n", "\n", - "**Note**: MiniRocket is compiled by Numba on import. The compiled functions are cached, so this should only happen once (i.e., the first time you import MiniRocket)." + "**Note**: ``MiniRocket`` is compiled by ``numba`` on import. The compiled functions are\n", + "cached, so this should only happen once (i.e., the first time you import ``MiniRocket``)." ] }, { "cell_type": "code", - "execution_count": 1, "metadata": { "execution": { "iopub.execute_input": "2020-10-12T17:43:03.214929Z", "iopub.status.busy": "2020-10-12T17:43:03.214184Z", "iopub.status.idle": "2020-10-12T17:43:03.216304Z", "shell.execute_reply": "2020-10-12T17:43:03.216990Z" + }, + "ExecuteTime": { + "end_time": "2024-11-25T11:08:58.368462Z", + "start_time": "2024-11-25T11:08:58.349939Z" } }, - "outputs": [], "source": [ "# !pip install --upgrade numba" - ] + ], + "outputs": [], + "execution_count": 1 }, { + "metadata": { + "ExecuteTime": { + "end_time": "2024-11-25T11:10:18.327182Z", + "start_time": "2024-11-25T11:08:59.095253Z" + } + }, "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], "source": [ "import numpy as np\n", "from sklearn.linear_model import RidgeClassifierCV\n", - "from sklearn.pipeline import make_pipeline\n", "from sklearn.preprocessing import StandardScaler\n", "\n", + "from aeon.classification.convolution_based import MiniRocketClassifier\n", "from aeon.datasets import load_arrow_head # univariate dataset\n", "from aeon.datasets import load_basic_motions # multivariate dataset\n", - "from aeon.datasets import (\n", - " load_japanese_vowels, # multivariate dataset with unequal length\n", - ")\n", - "from aeon.transformations.collection.convolution_based import (\n", - " MiniRocket,\n", - " MiniRocketMultivariateVariable,\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### 1.2 Load the Training Data\n", - "\n", - "For more details on the data set, see the [classification notebook](../classification/classification.ipynb).\n", - "\n", - "**Note**: Input time series must be *at least* of length 9. Pad shorter time series\n", - "using, e.g., `Padder` (`aeon.transformers.collection`)." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### 1.3 Initialise MiniRocket and Transform the Training Data" - ] + "from aeon.regression.convolution_based import MiniRocketRegressor\n", + "from aeon.transformations.collection.convolution_based import MiniRocket" + ], + "outputs": [], + "execution_count": 2 }, { - "cell_type": "code", - "execution_count": 3, "metadata": { - "execution": { - "iopub.execute_input": "2020-10-12T17:43:08.753121Z", - "iopub.status.busy": "2020-10-12T17:43:08.752621Z", - "iopub.status.idle": "2020-10-12T17:43:08.941014Z", - "shell.execute_reply": "2020-10-12T17:43:08.941496Z" + "ExecuteTime": { + "end_time": "2024-11-25T11:10:23.328664Z", + "start_time": "2024-11-25T11:10:23.234728Z" } }, + "cell_type": "code", + "source": [ + "X_train, y_train = load_arrow_head(split=\"train\")\n", + "minirocket = MiniRocket() # by default, MiniRocket uses ~10_000 kernels\n", + "minirocket.fit(X_train)\n", + "X_train_transform = minirocket.transform(X_train)\n", + "# test shape of transformed training data -> (n_cases, 9_996)\n", + "X_train_transform.shape" + ], "outputs": [ { "data": { - "text/plain": "(36, 9996)" + "text/plain": [ + "(36, 9996)" + ] }, - "execution_count": 3, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], - "source": [ - "X_train, y_train = load_arrow_head(split=\"train\")\n", - "minirocket = MiniRocket() # by default, MiniRocket uses ~10_000 kernels\n", - "minirocket.fit(X_train)\n", - "X_train_transform = minirocket.transform(X_train)\n", - "# test shape of transformed training data -> (n_cases, 9_996)\n", - "X_train_transform.shape" - ] + "execution_count": 5 }, { - "cell_type": "markdown", "metadata": {}, + "cell_type": "markdown", "source": [ "### 1.4 Fit a Classifier" ] }, { - "cell_type": "markdown", "metadata": {}, + "cell_type": "markdown", "source": [ "We suggest using `RidgeClassifierCV` (scikit-learn) for smaller datasets (fewer than ~10,000 training examples), and using logistic regression trained using stochastic gradient descent for larger datasets.\n", "\n", @@ -130,71 +119,919 @@ ] }, { - "cell_type": "code", - "execution_count": 4, "metadata": { - "execution": { - "iopub.execute_input": "2020-10-12T17:43:08.993410Z", - "iopub.status.busy": "2020-10-12T17:43:08.947187Z", - "iopub.status.idle": "2020-10-12T17:43:09.066548Z", - "shell.execute_reply": "2020-10-12T17:43:09.067299Z" + "ExecuteTime": { + "end_time": "2024-11-25T11:10:26.380394Z", + "start_time": "2024-11-25T11:10:26.343196Z" } }, + "cell_type": "code", + "source": [ + "scaler = StandardScaler(with_mean=False)\n", + "classifier = RidgeClassifierCV(alphas=np.logspace(-3, 3, 10))\n", + "X_train_scaled_transform = scaler.fit_transform(X_train_transform)\n", + "classifier.fit(X_train_scaled_transform, y_train)" + ], "outputs": [ { "data": { - "text/plain": "RidgeClassifierCV(alphas=array([1.00000000e-03, 4.64158883e-03, 2.15443469e-02, 1.00000000e-01,\n 4.64158883e-01, 2.15443469e+00, 1.00000000e+01, 4.64158883e+01,\n 2.15443469e+02, 1.00000000e+03]))", - "text/html": "
RidgeClassifierCV(alphas=array([1.00000000e-03, 4.64158883e-03, 2.15443469e-02, 1.00000000e-01,\n       4.64158883e-01, 2.15443469e+00, 1.00000000e+01, 4.64158883e+01,\n       2.15443469e+02, 1.00000000e+03]))
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" + "text/plain": [ + "RidgeClassifierCV(alphas=array([1.00000000e-03, 4.64158883e-03, 2.15443469e-02, 1.00000000e-01,\n", + " 4.64158883e-01, 2.15443469e+00, 1.00000000e+01, 4.64158883e+01,\n", + " 2.15443469e+02, 1.00000000e+03]))" + ], + "text/html": [ + "
RidgeClassifierCV(alphas=array([1.00000000e-03, 4.64158883e-03, 2.15443469e-02, 1.00000000e-01,\n",
+       "       4.64158883e-01, 2.15443469e+00, 1.00000000e+01, 4.64158883e+01,\n",
+       "       2.15443469e+02, 1.00000000e+03]))
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" + ] }, - "execution_count": 4, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], + "execution_count": 6 + }, + { + "metadata": {}, + "cell_type": "markdown", "source": [ - "scaler = StandardScaler(with_mean=False)\n", - "classifier = RidgeClassifierCV(alphas=np.logspace(-3, 3, 10))\n", - "\n", - "X_train_scaled_transform = scaler.fit_transform(X_train_transform)\n", - "classifier.fit(X_train_scaled_transform, y_train)" + "Or just use the provide baked in ``MiniRocketClassifier`` which contains\n", + "the scaler and classifier." ] }, { - "cell_type": "markdown", + "metadata": { + "ExecuteTime": { + "end_time": "2024-11-25T11:10:28.558282Z", + "start_time": "2024-11-25T11:10:28.438303Z" + } + }, + "cell_type": "code", + "source": [ + "mr = MiniRocketClassifier()\n", + "mr.fit(X_train, y_train)" + ], + "outputs": [ + { + "data": { + "text/plain": [ + "MiniRocketClassifier()" + ], + "text/html": [ + "
MiniRocketClassifier()
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" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "execution_count": 7 + }, + { "metadata": {}, + "cell_type": "markdown", "source": [ "### 1.5 Load and Transform the Test Data" ] }, { - "cell_type": "code", - "execution_count": 5, "metadata": { - "execution": { - "iopub.execute_input": "2020-10-12T17:43:09.071414Z", - "iopub.status.busy": "2020-10-12T17:43:09.070666Z", - "iopub.status.idle": "2020-10-12T17:43:09.931075Z", - "shell.execute_reply": "2020-10-12T17:43:09.931598Z" + "ExecuteTime": { + "end_time": "2024-11-25T11:10:36.310828Z", + "start_time": "2024-11-25T11:10:36.188643Z" } }, - "outputs": [], + "cell_type": "code", "source": [ "X_test, y_test = load_arrow_head(split=\"test\")\n", "X_test_transform = minirocket.transform(X_test)" - ] + ], + "outputs": [], + "execution_count": 8 }, { - "cell_type": "markdown", "metadata": {}, + "cell_type": "markdown", "source": [ "### 1.6 Classify the Test Data" ] }, { + "metadata": {}, "cell_type": "markdown", - "metadata": { - "collapsed": false - }, "source": [ "## 2 Multivariate Time Series\n", "\n", @@ -202,25 +1039,29 @@ ] }, { + "metadata": { + "ExecuteTime": { + "end_time": "2024-11-25T11:10:40.698690Z", + "start_time": "2024-11-25T11:10:40.561965Z" + } + }, "cell_type": "code", - "execution_count": 6, + "source": [ + "X_test_scaled_transform = scaler.transform(X_test_transform)\n", + "print(\" Score =\", classifier.score(X_test_scaled_transform, y_test))\n", + "print(\" Score = \", mr.score(X_test, y_test))" + ], "outputs": [ { - "data": { - "text/plain": "0.8571428571428571" - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" + "name": "stdout", + "output_type": "stream", + "text": [ + " Score = 0.8514285714285714\n", + " Score = 0.8685714285714285\n" + ] } ], - "source": [ - "X_test_scaled_transform = scaler.transform(X_test_transform)\n", - "classifier.score(X_test_scaled_transform, y_test)" - ], - "metadata": { - "collapsed": false - } + "execution_count": 9 }, { "cell_type": "markdown", @@ -234,19 +1075,23 @@ }, { "cell_type": "code", - "execution_count": 7, "metadata": { "execution": { "iopub.execute_input": "2020-10-12T17:43:10.054652Z", "iopub.status.busy": "2020-10-12T17:43:10.034190Z", "iopub.status.idle": "2020-10-12T17:43:10.394311Z", "shell.execute_reply": "2020-10-12T17:43:10.394905Z" + }, + "ExecuteTime": { + "end_time": "2024-11-25T11:10:43.874489Z", + "start_time": "2024-11-25T11:10:43.846456Z" } }, - "outputs": [], "source": [ "X_train, y_train = load_basic_motions(split=\"train\")" - ] + ], + "outputs": [], + "execution_count": 10 }, { "cell_type": "markdown", @@ -257,21 +1102,25 @@ }, { "cell_type": "code", - "execution_count": 8, "metadata": { "execution": { "iopub.execute_input": "2020-10-12T17:43:10.410718Z", "iopub.status.busy": "2020-10-12T17:43:10.410103Z", "iopub.status.idle": "2020-10-12T17:43:11.186318Z", "shell.execute_reply": "2020-10-12T17:43:11.186801Z" + }, + "ExecuteTime": { + "end_time": "2024-11-25T11:10:45.517801Z", + "start_time": "2024-11-25T11:10:45.415754Z" } }, - "outputs": [], "source": [ "mr = MiniRocket()\n", "mr.fit(X_train)\n", "X_train_transform = mr.transform(X_train)" - ] + ], + "outputs": [], + "execution_count": 11 }, { "cell_type": "markdown", @@ -282,43 +1131,451 @@ }, { "cell_type": "code", - "execution_count": 9, "metadata": { "execution": { "iopub.execute_input": "2020-10-12T17:43:11.190556Z", "iopub.status.busy": "2020-10-12T17:43:11.190017Z", "iopub.status.idle": "2020-10-12T17:43:11.396461Z", "shell.execute_reply": "2020-10-12T17:43:11.397135Z" + }, + "ExecuteTime": { + "end_time": "2024-11-25T11:10:48.940610Z", + "start_time": "2024-11-25T11:10:48.898236Z" } }, + "source": [ + "scaler = StandardScaler(with_mean=False)\n", + "X_train_scaled_transform = scaler.fit_transform(X_train_transform)\n", + "\n", + "classifier = RidgeClassifierCV(alphas=np.logspace(-3, 3, 10))\n", + "classifier.fit(X_train_scaled_transform, y_train)" + ], "outputs": [ { "data": { - "text/html": [ - "
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" - ], "text/plain": [ "RidgeClassifierCV(alphas=array([1.00000000e-03, 4.64158883e-03, 2.15443469e-02, 1.00000000e-01,\n", " 4.64158883e-01, 2.15443469e+00, 1.00000000e+01, 4.64158883e+01,\n", " 2.15443469e+02, 1.00000000e+03]))" + ], + "text/html": [ + "
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+       "       4.64158883e-01, 2.15443469e+00, 1.00000000e+01, 4.64158883e+01,\n",
+       "       2.15443469e+02, 1.00000000e+03]))
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" ] }, - "execution_count": 9, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], - "source": [ - "scaler = StandardScaler(with_mean=False)\n", - "X_train_scaled_transform = scaler.fit_transform(X_train_transform)\n", - "\n", - "classifier = RidgeClassifierCV(alphas=np.logspace(-3, 3, 10))\n", - "classifier.fit(X_train_scaled_transform, y_train)" - ] + "execution_count": 12 }, { "cell_type": "markdown", @@ -329,20 +1586,24 @@ }, { "cell_type": "code", - "execution_count": 10, "metadata": { "execution": { "iopub.execute_input": "2020-10-12T17:43:11.401025Z", "iopub.status.busy": "2020-10-12T17:43:11.400273Z", "iopub.status.idle": "2020-10-12T17:43:12.450777Z", "shell.execute_reply": "2020-10-12T17:43:12.451162Z" + }, + "ExecuteTime": { + "end_time": "2024-11-25T11:10:54.416071Z", + "start_time": "2024-11-25T11:10:54.338117Z" } }, - "outputs": [], "source": [ "X_test, y_test = load_basic_motions(split=\"test\")\n", "X_test_transform = mr.transform(X_test)" - ] + ], + "outputs": [], + "execution_count": 13 }, { "cell_type": "markdown", @@ -353,7 +1614,6 @@ }, { "cell_type": "code", - "execution_count": 11, "metadata": { "execution": { "iopub.execute_input": "2020-10-12T17:43:12.494679Z", @@ -361,8 +1621,16 @@ "iopub.status.idle": "2020-10-12T17:43:12.548017Z", "shell.execute_reply": "2020-10-12T17:43:12.548575Z" }, - "scrolled": true + "scrolled": true, + "ExecuteTime": { + "end_time": "2024-11-25T11:10:57.265809Z", + "start_time": "2024-11-25T11:10:57.240878Z" + } }, + "source": [ + "X_test_scaled_transform = scaler.transform(X_test_transform)\n", + "classifier.score(X_test_scaled_transform, y_test)" + ], "outputs": [ { "data": { @@ -370,15 +1638,12 @@ "1.0" ] }, - "execution_count": 11, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], - "source": [ - "X_test_scaled_transform = scaler.transform(X_test_transform)\n", - "classifier.score(X_test_scaled_transform, y_test)" - ] + "execution_count": 14 }, { "cell_type": "markdown", @@ -388,35 +1653,32 @@ ] }, { - "cell_type": "code", - "execution_count": 1, "metadata": { - "execution": { - "iopub.execute_input": "2020-10-12T17:43:12.552186Z", - "iopub.status.busy": "2020-10-12T17:43:12.551660Z", - "iopub.status.idle": "2020-10-12T17:43:12.553415Z", - "shell.execute_reply": "2020-10-12T17:43:12.553966Z" + "ExecuteTime": { + "end_time": "2024-11-25T11:10:59.040716Z", + "start_time": "2024-11-25T11:10:59.035170Z" } }, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'make_pipeline' is not defined", - "output_type": "error", - "traceback": [ - "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m", - "\u001B[1;31mNameError\u001B[0m Traceback (most recent call last)", - "Cell \u001B[1;32mIn[1], line 1\u001B[0m\n\u001B[1;32m----> 1\u001B[0m minirocket_pipeline \u001B[38;5;241m=\u001B[39m \u001B[43mmake_pipeline\u001B[49m(\n\u001B[0;32m 2\u001B[0m MiniRocket(),\n\u001B[0;32m 3\u001B[0m StandardScaler(with_mean\u001B[38;5;241m=\u001B[39m\u001B[38;5;28;01mFalse\u001B[39;00m),\n\u001B[0;32m 4\u001B[0m RidgeClassifierCV(alphas\u001B[38;5;241m=\u001B[39mnp\u001B[38;5;241m.\u001B[39mlogspace(\u001B[38;5;241m-\u001B[39m\u001B[38;5;241m3\u001B[39m, \u001B[38;5;241m3\u001B[39m, \u001B[38;5;241m10\u001B[39m)),\n\u001B[0;32m 5\u001B[0m )\n", - "\u001B[1;31mNameError\u001B[0m: name 'make_pipeline' is not defined" - ] - } - ], + "cell_type": "code", "source": [ + "from sklearn.linear_model import RidgeClassifierCV\n", + "from sklearn.pipeline import make_pipeline\n", + "from sklearn.preprocessing import StandardScaler\n", + "\n", "minirocket_pipeline = make_pipeline(\n", " MiniRocket(),\n", " StandardScaler(with_mean=False),\n", " RidgeClassifierCV(alphas=np.logspace(-3, 3, 10)),\n", ")" + ], + "outputs": [], + "execution_count": 15 + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": [ + "Or just use the provide baked in ``MiniRocket`` classifier" ] }, { @@ -431,35 +1693,462 @@ }, { "cell_type": "code", - "execution_count": 2, "metadata": { "execution": { "iopub.execute_input": "2020-10-12T17:43:12.557100Z", "iopub.status.busy": "2020-10-12T17:43:12.556478Z", "iopub.status.idle": "2020-10-12T17:43:12.885951Z", "shell.execute_reply": "2020-10-12T17:43:12.886625Z" + }, + "ExecuteTime": { + "end_time": "2024-11-25T11:11:02.046780Z", + "start_time": "2024-11-25T11:11:01.913155Z" } }, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'load_arrow_head' is not defined", - "output_type": "error", - "traceback": [ - "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m", - "\u001B[1;31mNameError\u001B[0m Traceback (most recent call last)", - "Cell \u001B[1;32mIn[2], line 1\u001B[0m\n\u001B[1;32m----> 1\u001B[0m X_train, y_train \u001B[38;5;241m=\u001B[39m \u001B[43mload_arrow_head\u001B[49m(split\u001B[38;5;241m=\u001B[39m\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mtrain\u001B[39m\u001B[38;5;124m\"\u001B[39m)\n\u001B[0;32m 3\u001B[0m \u001B[38;5;66;03m# it is necessary to pass y_train to the pipeline\u001B[39;00m\n\u001B[0;32m 4\u001B[0m \u001B[38;5;66;03m# y_train is not used for the transform, but it is used by the classifier\u001B[39;00m\n\u001B[0;32m 5\u001B[0m minirocket_pipeline\u001B[38;5;241m.\u001B[39mfit(X_train, y_train)\n", - "\u001B[1;31mNameError\u001B[0m: name 'load_arrow_head' is not defined" - ] - } - ], "source": [ "X_train, y_train = load_arrow_head(split=\"train\")\n", "\n", "# it is necessary to pass y_train to the pipeline\n", "# y_train is not used for the transform, but it is used by the classifier\n", "minirocket_pipeline.fit(X_train, y_train)" - ] + ], + "outputs": [ + { + "data": { + "text/plain": [ + "Pipeline(steps=[('minirocket', MiniRocket()),\n", + " ('standardscaler', StandardScaler(with_mean=False)),\n", + " ('ridgeclassifiercv',\n", + " RidgeClassifierCV(alphas=array([1.00000000e-03, 4.64158883e-03, 2.15443469e-02, 1.00000000e-01,\n", + " 4.64158883e-01, 2.15443469e+00, 1.00000000e+01, 4.64158883e+01,\n", + " 2.15443469e+02, 1.00000000e+03])))])" + ], + "text/html": [ + "
Pipeline(steps=[('minirocket', MiniRocket()),\n",
+       "                ('standardscaler', StandardScaler(with_mean=False)),\n",
+       "                ('ridgeclassifiercv',\n",
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+       "       4.64158883e-01, 2.15443469e+00, 1.00000000e+01, 4.64158883e+01,\n",
+       "       2.15443469e+02, 1.00000000e+03])))])
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On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "execution_count": 16 }, { "cell_type": "markdown", @@ -470,196 +2159,88 @@ }, { "cell_type": "code", - "execution_count": 15, "metadata": { "execution": { "iopub.execute_input": "2020-10-12T17:43:12.890535Z", "iopub.status.busy": "2020-10-12T17:43:12.889866Z", "iopub.status.idle": "2020-10-12T17:43:13.897048Z", "shell.execute_reply": "2020-10-12T17:43:13.897624Z" + }, + "ExecuteTime": { + "end_time": "2024-11-25T11:11:31.335457Z", + "start_time": "2024-11-25T11:11:31.003725Z" } }, - "outputs": [ - { - "data": { - "text/plain": [ - "0.8457142857142858" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], "source": [ "X_test, y_test = load_arrow_head(split=\"test\")\n", "\n", - "minirocket_pipeline.score(X_test, y_test)" - ] + "minirocket_pipeline.score(X_test, y_test)\n", + "minirocket_pipeline.fit(X_train, y_train)\n", + "pred = minirocket_pipeline.predict(X_test)\n" + ], + "outputs": [], + "execution_count": 18 }, { - "cell_type": "markdown", "metadata": {}, + "cell_type": "markdown", "source": [ - "***\n", - "\n", - "## 4 Pipeline Example with MiniRocketMultivariateVariable and unequal length time-series data\n", + "### Time series regression\n", "\n", - "For a further pipeline, we use the extended version of MiniRocket, the `MiniRocketMultivariateVariable` for variable / unequal length time series data. Following the code implementation of the original paper of miniRocket, we combine it with `RidgeClassifierCV` in a sklearn pipeline. We can then use the pipeline like a self-contained classifier, with a single call to `fit`, and without having to separately transform the data, etc.\n", - "\n", - "\n", - "### 4.1 Load japanese_vowels as unequal length dataset\n", - "Japanese vowels is a a UCI Archive dataset. 9 Japanese-male speakers were recorded saying the vowels ‘a’ and ‘e’.\n", - "The raw recordings are preprocessed to get a 12-dimensional (multivariate) classification probem. The series lengths are between 7 and 29." + "You can also use MiniRocket for time series regression." ] }, { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "number of samples training: 270\n", - "series length of recoding 0, dimension 5: (20,)\n", - "series length of recoding 1, dimension 0: (26,)\n" - ] + "metadata": { + "ExecuteTime": { + "end_time": "2024-11-25T11:11:35.125060Z", + "start_time": "2024-11-25T11:11:34.966868Z" } - ], + }, + "cell_type": "code", "source": [ - "X_train_jv, y_train_jv = load_japanese_vowels(split=\"train\")\n", - "# lets visualize the first three voice recordings with dimension 0-11\n", + "from aeon.datasets import load_covid_3month\n", "\n", - "print(\"number of samples training: \", len(X_train_jv))\n", - "print(\"series length of recoding 0, dimension 5: \", X_train_jv[0][5].shape)\n", - "print(\"series length of recoding 1, dimension 0: \", X_train_jv[1][0].shape)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### 4.2 Create a pipeline, train on it\n", - "As before, we create a sklearn pipeline.\n", - "MiniRocketMultivariateVariable requires a minimum series length of 9, where missing values are padded up to a length of 9, with the value \"-10.0\".\n", - "Afterwards a scaler and a RidgeClassifierCV are added.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, + "X_train, y_train = load_covid_3month(split=\"train\")\n", + "X_test, y_test = load_covid_3month(split=\"test\")\n", + "mr = MiniRocketRegressor()\n", + "mr.fit(X_train, y_train)\n", + "mr.score(X_test, y_test)" + ], "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Pipeline(steps=[('minirocketmultivariatevariable',\n", - " MiniRocketMultivariateVariable(max_dilations_per_kernel=16,\n", - " pad_value_short_series=-10.0,\n", - " random_state=42)),\n", - " ('standardscaler', StandardScaler(with_mean=False)),\n", - " ('ridgeclassifiercv',\n", - " RidgeClassifierCV(alphas=array([1.00000000e-03, 4.64158883e-03, 2.15443469e-02, 1.00000000e-01,\n", - " 4.64158883e-01, 2.15443469e+00, 1.00000000e+01, 4.64158883e+01,\n", - " 2.15443469e+02, 1.00000000e+03])))])\n" - ] - }, { "data": { - "text/html": [ - "
Pipeline(steps=[('minirocketmultivariatevariable',\n",
-       "                 MiniRocketMultivariateVariable(max_dilations_per_kernel=16,\n",
-       "                                                pad_value_short_series=-10.0,\n",
-       "                                                random_state=42)),\n",
-       "                ('standardscaler', StandardScaler(with_mean=False)),\n",
-       "                ('ridgeclassifiercv',\n",
-       "                 RidgeClassifierCV(alphas=array([1.00000000e-03, 4.64158883e-03, 2.15443469e-02, 1.00000000e-01,\n",
-       "       4.64158883e-01, 2.15443469e+00, 1.00000000e+01, 4.64158883e+01,\n",
-       "       2.15443469e+02, 1.00000000e+03])))])
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" - ], "text/plain": [ - "Pipeline(steps=[('minirocketmultivariatevariable',\n", - " MiniRocketMultivariateVariable(max_dilations_per_kernel=16,\n", - " pad_value_short_series=-10.0,\n", - " random_state=42)),\n", - " ('standardscaler', StandardScaler(with_mean=False)),\n", - " ('ridgeclassifiercv',\n", - " RidgeClassifierCV(alphas=array([1.00000000e-03, 4.64158883e-03, 2.15443469e-02, 1.00000000e-01,\n", - " 4.64158883e-01, 2.15443469e+00, 1.00000000e+01, 4.64158883e+01,\n", - " 2.15443469e+02, 1.00000000e+03])))])" + "0.1619927701771796" ] }, - "execution_count": 17, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], - "source": [ - "minirocket_mv_var_pipeline = make_pipeline(\n", - " MiniRocketMultivariateVariable(\n", - " pad_value_short_series=-10.0, random_state=42, max_dilations_per_kernel=16\n", - " ),\n", - " StandardScaler(with_mean=False),\n", - " RidgeClassifierCV(alphas=np.logspace(-3, 3, 10)),\n", - ")\n", - "print(minirocket_mv_var_pipeline)\n", - "\n", - "minirocket_mv_var_pipeline.fit(X_train_jv, y_train_jv)" - ] + "execution_count": 19 }, { - "cell_type": "markdown", "metadata": {}, + "cell_type": "markdown", "source": [ - "### 4.3 Score the Pipeline on japanese vowels\n", - "\n", - "Using the MiniRocketMultivariateVariable, we are able to process also process slightly larger input series than at train time.\n", - "train max series length: 27, test max series length 29" + "### References\n", + "[1] Angus Dempster, Daniel F. Schmidt, Geoffrey I. Webb. A Very Fast (Almost)\n", + "Deterministic Transform for Time Series Classification [arXiv:2012.08791](https://arxiv.org/abs/2012.08791)" ] }, { - "cell_type": "code", - "execution_count": 18, + "cell_type": "markdown", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.9945945945945946" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "X_test_jv, y_test_jv = load_japanese_vowels(split=\"test\")\n", - "\n", - "minirocket_mv_var_pipeline.score(X_test_jv, y_test_jv)" - ] + "source": [] }, { - "cell_type": "markdown", "metadata": {}, - "source": [ - "### References\n", - "[1] Angus Dempster, Daniel F. Schmidt, Geoffrey I. Webb. A Very Fast (Almost) Deterministic Transform for Time Series Classification" - ] + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "" } ], "metadata": { From 993d1d68c33766c72e28e3cc23e52038f18d3ccd Mon Sep 17 00:00:00 2001 From: chrisholder Date: Mon, 25 Nov 2024 17:15:46 +0000 Subject: [PATCH 3/4] [MNT] cluster init_algorithm removed across all clusterers (#2392) * cluster init_algorithm removed across all clusterers * removed deprecation warnings - just removed it * typo --------- Co-authored-by: Tony Bagnall --- aeon/clustering/_clara.py | 12 ++--- aeon/clustering/_clarans.py | 16 +++--- aeon/clustering/_k_medoids.py | 53 +++++++++---------- aeon/clustering/_k_shape.py | 12 ++--- aeon/clustering/tests/test_clara.py | 4 +- aeon/clustering/tests/test_clarans.py | 8 +-- aeon/clustering/tests/test_k_medoids.py | 14 ++--- .../clustering/partitional_clustering.ipynb | 6 +-- 8 files changed, 61 insertions(+), 64 deletions(-) diff --git a/aeon/clustering/_clara.py b/aeon/clustering/_clara.py index dcc0e7a912..66da2e9920 100644 --- a/aeon/clustering/_clara.py +++ b/aeon/clustering/_clara.py @@ -30,8 +30,8 @@ class TimeSeriesCLARA(BaseClusterer): n_clusters : int, default=8 The number of clusters to form as well as the number of centroids to generate. - init_algorithm : str or np.ndarray, default='random' - Method for initializing cluster centers. Any of the following are valid: + init : str or np.ndarray, default='random' + Method for initialising cluster centers. Any of the following are valid: ['kmedoids++', 'random', 'first']. Random is the default as it is very fast and it was found in [2] to perform about as well as the other methods. @@ -118,7 +118,7 @@ class TimeSeriesCLARA(BaseClusterer): def __init__( self, n_clusters: int = 8, - init_algorithm: Union[str, np.ndarray] = "random", + init: Union[str, np.ndarray] = "random", distance: Union[str, Callable] = "msm", n_samples: Optional[int] = None, n_sampling_iters: int = 10, @@ -129,8 +129,8 @@ def __init__( random_state: Optional[Union[int, RandomState]] = None, distance_params: Optional[dict] = None, ): - self.init_algorithm = init_algorithm self.distance = distance + self.init = init self.n_init = n_init self.max_iter = max_iter self.tol = tol @@ -175,7 +175,7 @@ def _fit(self, X: np.ndarray, y=None): ) pam = TimeSeriesKMedoids( n_clusters=self.n_clusters, - init_algorithm=self.init_algorithm, + init=self.init, distance=self.distance, n_init=self.n_init, max_iter=self.max_iter, @@ -228,7 +228,7 @@ def _get_test_params(cls, parameter_set="default"): """ return { "n_clusters": 2, - "init_algorithm": "random", + "init": "random", "distance": "euclidean", "n_init": 1, "max_iter": 1, diff --git a/aeon/clustering/_clarans.py b/aeon/clustering/_clarans.py index f1c9eff87b..71ca1a9284 100644 --- a/aeon/clustering/_clarans.py +++ b/aeon/clustering/_clarans.py @@ -31,8 +31,8 @@ class TimeSeriesCLARANS(TimeSeriesKMedoids): n_clusters : int, default=8 The number of clusters to form as well as the number of centroids to generate. - init_algorithm : str or np.ndarray, default='random' - Method for initializing cluster centers. Any of the following are valid: + init : str or np.ndarray, default='random' + Method for initialising cluster centers. Any of the following are valid: ['kmedoids++', 'random', 'first']. Random is the default as it is very fast and it was found in [2] to perform about as well as the other methods. @@ -104,7 +104,7 @@ class TimeSeriesCLARANS(TimeSeriesKMedoids): def __init__( self, n_clusters: int = 8, - init_algorithm: Union[str, np.ndarray] = "random", + init: Union[str, np.ndarray] = "random", distance: Union[str, Callable] = "msm", max_neighbours: Optional[int] = None, n_init: int = 10, @@ -116,7 +116,7 @@ def __init__( super().__init__( n_clusters=n_clusters, - init_algorithm=init_algorithm, + init=init, distance=distance, n_init=n_init, verbose=verbose, @@ -127,10 +127,10 @@ def __init__( def _fit_one_init(self, X: np.ndarray, max_neighbours: int): j = 0 X_indexes = np.arange(X.shape[0], dtype=int) - if isinstance(self._init_algorithm, Callable): - best_medoids = self._init_algorithm(X) + if isinstance(self._init, Callable): + best_medoids = self._init(X) else: - best_medoids = self._init_algorithm + best_medoids = self._init best_non_medoids = np.setdiff1d(X_indexes, best_medoids) best_cost = ( self._compute_pairwise(X, best_non_medoids, best_medoids).min(axis=1).sum() @@ -203,7 +203,7 @@ def _get_test_params(cls, parameter_set="default"): """ return { "n_clusters": 2, - "init_algorithm": "random", + "init": "random", "distance": "euclidean", "max_neighbours": None, "n_init": 1, diff --git a/aeon/clustering/_k_medoids.py b/aeon/clustering/_k_medoids.py index ea8e860afc..a54220cec2 100644 --- a/aeon/clustering/_k_medoids.py +++ b/aeon/clustering/_k_medoids.py @@ -44,8 +44,8 @@ class TimeSeriesKMedoids(BaseClusterer): ---------- n_clusters : int, default=8 The number of clusters to form as well as the number of centroids to generate. - init_algorithm : str or np.ndarray, default='random' - Method for initializing cluster centers. Any of the following are valid: + init : str or np.ndarray, default='random' + Method for initialising cluster centers. Any of the following are valid: ['kmedoids++', 'random', 'first']. Random is the default as it is very fast and it was found in [2] to perform about as well as the other methods. @@ -152,7 +152,7 @@ class TimeSeriesKMedoids(BaseClusterer): def __init__( self, n_clusters: int = 8, - init_algorithm: Union[str, np.ndarray] = "random", + init: Union[str, np.ndarray] = "random", distance: Union[str, Callable] = "msm", method: str = "pam", n_init: int = 10, @@ -162,8 +162,8 @@ def __init__( random_state: Optional[Union[int, RandomState]] = None, distance_params: Optional[dict] = None, ): - self.init_algorithm = init_algorithm self.distance = distance + self.init = init self.n_init = n_init self.max_iter = max_iter self.tol = tol @@ -179,7 +179,7 @@ def __init__( self.n_iter_ = 0 self._random_state = None - self._init_algorithm = None + self._init = None self._distance_cache = None self._distance_callable = None self._fit_method = None @@ -267,10 +267,10 @@ def _pam_fit(self, X: np.ndarray): old_inertia = np.inf n_cases = X.shape[0] - if isinstance(self._init_algorithm, Callable): - medoids_idxs = self._init_algorithm(X) + if isinstance(self._init, Callable): + medoids_idxs = self._init(X) else: - medoids_idxs = self._init_algorithm + medoids_idxs = self._init not_medoid_idxs = np.arange(n_cases, dtype=int) distance_matrix = self._compute_pairwise(X, not_medoid_idxs, not_medoid_idxs) distance_closest_medoid, distance_second_closest_medoid = np.sort( @@ -388,9 +388,9 @@ def _compute_optimal_swaps( return None def _alternate_fit(self, X) -> tuple[np.ndarray, np.ndarray, float, int]: - cluster_center_indexes = self._init_algorithm - if isinstance(self._init_algorithm, Callable): - cluster_center_indexes = self._init_algorithm(X) + cluster_center_indexes = self._init + if isinstance(self._init, Callable): + cluster_center_indexes = self._init(X) old_inertia = np.inf old_indexes = None for i in range(self.max_iter): @@ -428,24 +428,21 @@ def _assign_clusters( def _check_params(self, X: np.ndarray) -> None: self._random_state = check_random_state(self.random_state) - if isinstance(self.init_algorithm, str): - if self.init_algorithm == "random": - self._init_algorithm = self._random_center_initializer - elif self.init_algorithm == "kmedoids++": - self._init_algorithm = self._kmedoids_plus_plus_center_initializer - elif self.init_algorithm == "first": - self._init_algorithm = self._first_center_initializer - elif self.init_algorithm == "build": - self._init_algorithm = self._pam_build_center_initializer + if isinstance(self.init, str): + if self.init == "random": + self._init = self._random_center_initializer + elif self.init == "kmedoids++": + self._init = self._kmedoids_plus_plus_center_initializer + elif self.init == "first": + self._init = self._first_center_initializer + elif self.init == "build": + self._init = self._pam_build_center_initializer else: - if ( - isinstance(self.init_algorithm, np.ndarray) - and len(self.init_algorithm) == self.n_clusters - ): - self._init_algorithm = self.init_algorithm + if isinstance(self.init, np.ndarray) and len(self.init) == self.n_clusters: + self._init = self.init else: raise ValueError( - f"The value provided for init_algorithm: {self.init_algorithm} is " + f"The value provided for init: {self.init} is " f"invalid. The following are a list of valid init algorithms " f"strings: random, kmedoids++, first. You can also pass a" f"np.ndarray of size (n_clusters, n_channels, n_timepoints)" @@ -469,7 +466,7 @@ def _check_params(self, X: np.ndarray) -> None: else: raise ValueError(f"method {self.method} is not supported") - if isinstance(self.init_algorithm, str) and self.init_algorithm == "build": + if isinstance(self.init, str) and self.init == "build": if self.n_init != 10 and self.n_init > 1: warnings.warn( "When using build n_init does not need to be greater than 1. " @@ -558,7 +555,7 @@ def _get_test_params(cls, parameter_set="default"): """ return { "n_clusters": 2, - "init_algorithm": "random", + "init": "random", "distance": "euclidean", "n_init": 1, "max_iter": 1, diff --git a/aeon/clustering/_k_shape.py b/aeon/clustering/_k_shape.py index ad94a9f10c..aa8d8a3b64 100644 --- a/aeon/clustering/_k_shape.py +++ b/aeon/clustering/_k_shape.py @@ -16,8 +16,8 @@ class TimeSeriesKShape(BaseClusterer): n_clusters: int, default=8 The number of clusters to form as well as the number of centroids to generate. - init_algorithm: str or np.ndarray, default='random' - Method for initializing cluster centres. Any of the following are valid: + init: str or np.ndarray, default='random' + Method for initialising cluster centres. Any of the following are valid: ['random']. Or a np.ndarray of shape (n_clusters, n_channels, n_timepoints) and gives the initial cluster centres. n_init: int, default=10 @@ -76,15 +76,15 @@ class TimeSeriesKShape(BaseClusterer): def __init__( self, n_clusters: int = 8, - init_algorithm: Union[str, np.ndarray] = "random", + init: Union[str, np.ndarray] = "random", n_init: int = 10, max_iter: int = 300, tol: float = 1e-4, verbose: bool = False, random_state: Optional[Union[int, RandomState]] = None, ): - self.init_algorithm = init_algorithm self.n_init = n_init + self.init = init self.max_iter = max_iter self.tol = tol self.verbose = verbose @@ -124,7 +124,7 @@ def _fit(self, X, y=None): random_state=self.random_state, n_init=self.n_init, verbose=self.verbose, - init=self.init_algorithm, + init=self.init, ) _X = X.swapaxes(1, 2) @@ -173,7 +173,7 @@ def _get_test_params(cls, parameter_set="default"): """ return { "n_clusters": 2, - "init_algorithm": "random", + "init": "random", "n_init": 1, "max_iter": 1, "tol": 1e-4, diff --git a/aeon/clustering/tests/test_clara.py b/aeon/clustering/tests/test_clara.py index ebfb3dada5..81d5e8920e 100644 --- a/aeon/clustering/tests/test_clara.py +++ b/aeon/clustering/tests/test_clara.py @@ -23,7 +23,7 @@ def test_clara_uni(): n_samples=10, n_init=2, max_iter=5, - init_algorithm="first", + init="first", distance="euclidean", n_clusters=2, ) @@ -68,7 +68,7 @@ def test_clara_multi(): n_samples=10, n_init=2, max_iter=5, - init_algorithm="first", + init="first", distance="euclidean", n_clusters=2, ) diff --git a/aeon/clustering/tests/test_clarans.py b/aeon/clustering/tests/test_clarans.py index 03e250bdf3..a1da285cf3 100644 --- a/aeon/clustering/tests/test_clarans.py +++ b/aeon/clustering/tests/test_clarans.py @@ -24,7 +24,7 @@ def test_clarans_uni(): clarans = TimeSeriesCLARANS( random_state=1, n_init=2, - init_algorithm="first", + init="first", distance="euclidean", n_clusters=2, ) @@ -67,7 +67,7 @@ def test_clara_multi(): clarans = TimeSeriesCLARANS( random_state=1, n_init=2, - init_algorithm="first", + init="first", distance="euclidean", n_clusters=2, ) @@ -106,7 +106,7 @@ def test_medoids_init(): kmedoids = TimeSeriesCLARANS( random_state=1, n_init=1, - init_algorithm="first", + init="first", distance="euclidean", n_clusters=num_clusters, ) @@ -131,7 +131,7 @@ def test_medoids_init(): kmedoids = TimeSeriesCLARANS( random_state=1, n_init=1, - init_algorithm=custom_init_centres, + init=custom_init_centres, distance="euclidean", n_clusters=num_clusters, ) diff --git a/aeon/clustering/tests/test_k_medoids.py b/aeon/clustering/tests/test_k_medoids.py index 57bd7c1039..0fea3ead19 100644 --- a/aeon/clustering/tests/test_k_medoids.py +++ b/aeon/clustering/tests/test_k_medoids.py @@ -43,7 +43,7 @@ def _pam_uni_medoids(X_train, y_train, X_test, y_test): random_state=1, n_init=2, max_iter=5, - init_algorithm="first", + init="first", distance="euclidean", method="pam", ) @@ -70,7 +70,7 @@ def _alternate_uni_medoids(X_train, y_train, X_test, y_test): n_init=2, max_iter=5, method="alternate", - init_algorithm="first", + init="first", distance="euclidean", ) train_medoids_result = kmedoids.fit_predict(X_train) @@ -95,7 +95,7 @@ def _pam_multi_medoids(X_train, y_train, X_test, y_test): random_state=1, n_init=2, max_iter=5, - init_algorithm="first", + init="first", distance="euclidean", method="pam", ) @@ -121,7 +121,7 @@ def _alternate_multi_medoids(X_train, y_train, X_test, y_test): random_state=1, n_init=2, max_iter=5, - init_algorithm="first", + init="first", method="alternate", distance="euclidean", ) @@ -169,7 +169,7 @@ def test_medoids_init(): random_state=1, n_init=1, max_iter=5, - init_algorithm="first", + init="first", distance="euclidean", n_clusters=num_clusters, ) @@ -194,7 +194,7 @@ def test_medoids_init(): random_state=1, n_init=1, max_iter=5, - init_algorithm=custom_init_centres, + init=custom_init_centres, distance="euclidean", n_clusters=num_clusters, ) @@ -209,7 +209,7 @@ def _get_model_centres(data, distance, method="pam", distance_params=None): method=method, n_init=2, n_clusters=2, - init_algorithm="random", + init="random", distance=distance, distance_params=distance_params, ) diff --git a/examples/clustering/partitional_clustering.ipynb b/examples/clustering/partitional_clustering.ipynb index 817f66bd24..5fd9ac1eec 100644 --- a/examples/clustering/partitional_clustering.ipynb +++ b/examples/clustering/partitional_clustering.ipynb @@ -1374,7 +1374,7 @@ "source": [ "k_medoids = TimeSeriesKMedoids(\n", " n_clusters=2, # Number of desired centers\n", - " init_algorithm=\"random\", # Center initialisation technique\n", + " init=\"random\", # Center initialisation technique\n", " max_iter=10, # Maximum number of iterations for refinement on training set\n", " verbose=False, # Verbose\n", " distance=\"dtw\", # Distance to use\n", @@ -1458,7 +1458,7 @@ "source": [ "k_medoids = TimeSeriesKMedoids(\n", " n_clusters=2, # Number of desired centers\n", - " init_algorithm=\"random\", # Center initialisation technique\n", + " init=\"random\", # Center initialisation technique\n", " max_iter=10, # Maximum number of iterations for refinement on training set\n", " distance=\"msm\", # Distance to use\n", " random_state=1,\n", @@ -1527,7 +1527,7 @@ "source": [ "k_medoids = TimeSeriesKMedoids(\n", " n_clusters=2, # Number of desired centers\n", - " init_algorithm=\"random\", # Center initialisation technique\n", + " init=\"random\", # Center initialisation technique\n", " max_iter=10, # Maximum number of iterations for refinement on training set\n", " distance=\"msm\", # Distance to use\n", " random_state=1,\n", From c8352175e2204f3f73fde55c556f7787596f9855 Mon Sep 17 00:00:00 2001 From: Tony Bagnall Date: Mon, 25 Nov 2024 17:20:19 +0000 Subject: [PATCH 4/4] [ENH] First PR for forecasting module (#2362) * forecaster base and dummy * forecasting tests * forecasting tests * forecasting tests * forecasting tests * regression * notebook * regressor * regressor * regressor * tags * tags * requires_y * forecasting notebook * forecasting notebook * remove tags * fix forecasting testing (they still fail though) * _is_fitted -> is_fitted * _is_fitted -> is_fitted * _forecast * notebook * is_fitted * y_fitted * ETS forecaster * add y checks and conversion * add tag * tidy * _check_is_fitted() * _check_is_fitted() * Add fully functional ETS Forecaster. Modify base to not set default y in forecast. Update tests for ETS Forecaster. Add script to verify ETS Forecaster against statsforecast module using a large number of random parameter inputs. (#2318) Co-authored-by: Alex Banwell * Ajb/forecasting (#2357) * Add fully functional ETS Forecaster. Modify base to not set default y in forecast. Update tests for ETS Forecaster. Add script to verify ETS Forecaster against statsforecast module using a large number of random parameter inputs. * Add faster numba version of ETS forecaster * Seperate out predict code, and add test to test without creating a class - significantly faster! * Modify _verify_ets.py to allow easy switching between statsforecast versions. This confirms that my algorithms without class overheads is significantly faster than nixtla statsforecast, and with class overheads, it is faster than their current algorithm * Add basic gradient decent optimization algorithm for smoothing parameters --------- Co-authored-by: Alex Banwell * first forecasters * beta local * example * example * test regressor * forecasting notebook * base * base * ETS refactor * correct test * private forecast * remove duplicate * fit_is_empty check * fit_is_empty check * fix changed constant name * typo * n_timepoints * forecasting tests --------- Co-authored-by: MatthewMiddlehurst Co-authored-by: alexbanwell1 <31886108+alexbanwell1@users.noreply.github.com> Co-authored-by: Alex Banwell --- aeon/forecasting/__init__.py | 13 + aeon/forecasting/_dummy.py | 27 ++ aeon/forecasting/_ets.py | 416 +++++++++++++++++ aeon/forecasting/_regression.py | 105 +++++ aeon/forecasting/base.py | 159 +++++++ aeon/forecasting/tests/__init__.py | 1 + aeon/forecasting/tests/test_base.py | 16 + aeon/forecasting/tests/test_regressor.py | 16 + .../_yield_forecasting_checks.py | 51 +++ .../mock_estimators/_mock_forecasters.py | 22 + aeon/testing/testing_data.py | 114 +++-- aeon/testing/tests/test_testing_data.py | 3 + aeon/testing/utils/estimator_checks.py | 10 +- aeon/utils/base/_register.py | 2 + aeon/utils/tags/_tags.py | 8 + examples/forecasting/forecasting.ipynb | 417 ++++++++++++++++++ 16 files changed, 1338 insertions(+), 42 deletions(-) create mode 100644 aeon/forecasting/__init__.py create mode 100644 aeon/forecasting/_dummy.py create mode 100644 aeon/forecasting/_ets.py create mode 100644 aeon/forecasting/_regression.py create mode 100644 aeon/forecasting/base.py create mode 100644 aeon/forecasting/tests/__init__.py create mode 100644 aeon/forecasting/tests/test_base.py create mode 100644 aeon/forecasting/tests/test_regressor.py create mode 100644 aeon/testing/estimator_checking/_yield_forecasting_checks.py create mode 100644 aeon/testing/mock_estimators/_mock_forecasters.py create mode 100644 examples/forecasting/forecasting.ipynb diff --git a/aeon/forecasting/__init__.py b/aeon/forecasting/__init__.py new file mode 100644 index 0000000000..de203a0bcd --- /dev/null +++ b/aeon/forecasting/__init__.py @@ -0,0 +1,13 @@ +"""Forecasters.""" + +__all__ = [ + "DummyForecaster", + "BaseForecaster", + "RegressionForecaster", + "ETSForecaster", +] + +from aeon.forecasting._dummy import DummyForecaster +from aeon.forecasting._ets import ETSForecaster +from aeon.forecasting._regression import RegressionForecaster +from aeon.forecasting.base import BaseForecaster diff --git a/aeon/forecasting/_dummy.py b/aeon/forecasting/_dummy.py new file mode 100644 index 0000000000..7525b6ccd0 --- /dev/null +++ b/aeon/forecasting/_dummy.py @@ -0,0 +1,27 @@ +"""DummyForecaster always predicts the last value seen in training.""" + +from aeon.forecasting.base import BaseForecaster + + +class DummyForecaster(BaseForecaster): + """Dummy forecaster always predicts the last value seen in training.""" + + def __init__(self): + """Initialize DummyForecaster.""" + self.last_value_ = None + super().__init__(horizon=1, axis=1) + + def _fit(self, y, exog=None): + """Fit dummy forecaster.""" + y = y.squeeze() + self.last_value_ = y[-1] + return self + + def _predict(self, y=None, exog=None): + """Predict using dummy forecaster.""" + return self.last_value_ + + def _forecast(self, y, exog=None): + """Forecast using dummy forecaster.""" + y = y.squeeze() + return y[-1] diff --git a/aeon/forecasting/_ets.py b/aeon/forecasting/_ets.py new file mode 100644 index 0000000000..b477046895 --- /dev/null +++ b/aeon/forecasting/_ets.py @@ -0,0 +1,416 @@ +"""ETSForecaster class. + +An implementation of the exponential smoothing statistics forecasting algorithm. +Implements additive and multiplicative error models, +None, additive and multiplicative (including damped) trend and +None, additive and multiplicative seasonality +""" + +__maintainer__ = [] +__all__ = ["ETSForecaster", "NONE", "ADDITIVE", "MULTIPLICATIVE"] + +import numpy as np +from numba import njit + +from aeon.forecasting.base import BaseForecaster + +NOGIL = False +CACHE = True + +NONE = 0 +ADDITIVE = 1 +MULTIPLICATIVE = 2 + + +class ETSForecaster(BaseForecaster): + """Exponential Smoothing forecaster. + + An implementation of the exponential smoothing forecasting algorithm. + Implements additive and multiplicative error models, None, additive and + multiplicative (including damped) trend and None, additive and mutliplicative + seasonality. See [1]_ for a description. + + Parameters + ---------- + error_type : int, default = 1 + Either NONE (0), ADDITIVE (1) or MULTIPLICATIVE (2). + trend_type : int, default = 0 + Either NONE (0), ADDITIVE (1) or MULTIPLICATIVE (2). + seasonality_type : int, default = 0 + Either NONE (0), ADDITIVE (1) or MULTIPLICATIVE (2). + seasonal_period : int, default=1 + Length of seasonality period. If seasonality_type is NONE, this is assumed to + be 1 + alpha : float, default = 0.1 + Level smoothing parameter. + beta : float, default = 0.01 + Trend smoothing parameter. If trend_type is NONE, this is assumed to be 0.0. + gamma : float, default = 0.01 + Seasonal smoothing parameter. If seasonality is NONE, this is assumed to be + 0.0. + phi : float, default = 0.99 + Trend damping smoothing parameters + horizon : int, default = 1 + The horizon to forecast to. + + Attributes + ---------- + mean_sq_err_ : float + Mean squared error. + likelihood_ : float + Likelihood of the fitted model based on residuals. + residuals_ : arraylike + List of train set differences between fitted and actual values. + n_timpoints_ : int + Length of the series passed to fit. + + References + ---------- + .. [1] R. J. Hyndman and G. Athanasopoulos, + Forecasting: Principles and Practice. Melbourne, Australia: OTexts, 2014. + + Examples + -------- + >>> from aeon.forecasting import ETSForecaster + >>> from aeon.datasets import load_airline + >>> y = load_airline() + >>> forecaster = ETSForecaster(alpha=0.4, beta=0.2, gamma=0.5, phi=0.8, horizon=1) + >>> forecaster.fit(y) + ETSForecaster(alpha=0.4, beta=0.2, gamma=0.5, phi=0.8) + >>> forecaster.predict() + 449.9435566831507 + """ + + def __init__( + self, + error_type=ADDITIVE, + trend_type=NONE, + seasonality_type=NONE, + seasonal_period=1, + alpha=0.1, + beta=0.01, + gamma=0.01, + phi=0.99, + horizon=1, + ): + self.error_type = error_type + self.trend_type = trend_type + self.seasonality_type = seasonality_type + self.seasonal_period = seasonal_period + self.alpha = alpha + self.beta = beta + self.gamma = gamma + self.phi = phi + self.mean_sq_err_ = 0 + self.likelihood_ = 0 + self.residuals_ = [] + self.n_timpoints_ = 0 + super().__init__(horizon=horizon, axis=1) + + def _fit(self, y, exog=None): + """Fit Exponential Smoothing forecaster to series y. + + Fit a forecaster to predict self.horizon steps ahead using y. + + Parameters + ---------- + y : np.ndarray + A time series on which to learn a forecaster to predict horizon ahead + exog : np.ndarray, default =None + Optional exogenous time series data assumed to be aligned with y + + Returns + ------- + self + Fitted BaseForecaster. + """ + self.n_timepoints_ = len(y) + if self.error_type != MULTIPLICATIVE and self.error_type != ADDITIVE: + raise ValueError("Error must be either additive or multiplicative") + self._seasonal_period = self.seasonal_period + if self.seasonal_period < 1 or self.seasonality_type == NONE: + self._seasonal_period = 1 + self._beta = self.beta + if self.trend_type == NONE: + self._beta = 0 + self._gamma = self.gamma + if self.seasonality_type == NONE: + self._gamma = 0 + data = np.array(y.squeeze(), dtype=np.float64) + ( + self._level, + self._trend, + self._seasonality, + self.residuals_, + self.mean_sq_err_, + self.likelihood_, + ) = _fit_numba( + data, + self.error_type, + self.trend_type, + self.seasonality_type, + self._seasonal_period, + self.alpha, + self._beta, + self._gamma, + self.phi, + ) + return self + + def _predict(self, y=None, exog=None): + """ + Predict the next horizon steps ahead. + + Parameters + ---------- + y : np.ndarray, default = None + A time series to predict the next horizon value for. If None, + predict the next horizon value after series seen in fit. + exog : np.ndarray, default = None + Optional exogenous time series data assumed to be aligned with y + + Returns + ------- + float + single prediction self.horizon steps ahead of y. + """ + return _predict_numba( + self.trend_type, + self.seasonality_type, + self._level, + self._trend, + self._seasonality, + self.phi, + self.horizon, + self.n_timepoints_, + self.seasonal_period, + ) + + +@njit(nogil=NOGIL, cache=CACHE) +def _fit_numba( + data, + error_type, + trend_type, + seasonality_type, + seasonal_period, + alpha, + beta, + gamma, + phi, +): + n_timepoints = len(data) + level, trend, seasonality = _initialise( + trend_type, seasonality_type, seasonal_period, data + ) + mse = 0 + lhood = 0 + mul_likelihood_pt2 = 0 + res = np.zeros(n_timepoints) # 1 Less residual than data points + for t, data_item in enumerate(data[seasonal_period:]): + # Calculate level, trend, and seasonal components + fitted_value, error, level, trend, seasonality[t % seasonal_period] = ( + _update_states( + error_type, + trend_type, + seasonality_type, + level, + trend, + seasonality[t % seasonal_period], + data_item, + alpha, + beta, + gamma, + phi, + ) + ) + res[t] = error + mse += (data_item - fitted_value) ** 2 + lhood += error * error + mul_likelihood_pt2 += np.log(np.fabs(fitted_value)) + mse /= n_timepoints - seasonal_period + lhood = (n_timepoints - seasonal_period) * np.log(lhood) + if error_type == MULTIPLICATIVE: + lhood += 2 * mul_likelihood_pt2 + return level, trend, seasonality, res, mse, lhood + + +def _predict_numba( + trend_type, + seasonality_type, + level, + trend, + seasonality, + phi, + horizon, + n_timepoints, + seasonal_period, +): + # Generate forecasts based on the final values of level, trend, and seasonals + if phi == 1: # No damping case + phi_h = float(horizon) + else: + # Geometric series formula for calculating phi + phi^2 + ... + phi^h + phi_h = phi * (1 - phi**horizon) / (1 - phi) + seasonal_index = (n_timepoints + horizon) % seasonal_period + return _predict_value( + trend_type, + seasonality_type, + level, + trend, + seasonality[seasonal_index], + phi_h, + )[0] + + +@njit(nogil=NOGIL, cache=CACHE) +def _initialise(trend_type, seasonality_type, seasonal_period, data): + """ + Initialize level, trend, and seasonality values for the ETS model. + + Parameters + ---------- + data : array-like + The time series data + (should contain at least two full seasons if seasonality is specified) + """ + # Initial Level: Mean of the first season + level = np.mean(data[:seasonal_period]) + # Initial Trend + if trend_type == ADDITIVE: + # Average difference between corresponding points in the first two seasons + trend = np.mean( + data[seasonal_period : 2 * seasonal_period] - data[:seasonal_period] + ) + elif trend_type == MULTIPLICATIVE: + # Average ratio between corresponding points in the first two seasons + trend = np.mean( + data[seasonal_period : 2 * seasonal_period] / data[:seasonal_period] + ) + else: + # No trend + trend = 0 + # Initial Seasonality + if seasonality_type == ADDITIVE: + # Seasonal component is the difference + # from the initial level for each point in the first season + seasonality = data[:seasonal_period] - level + elif seasonality_type == MULTIPLICATIVE: + # Seasonal component is the ratio of each point in the first season + # to the initial level + seasonality = data[:seasonal_period] / level + else: + # No seasonality + seasonality = np.zeros(1) + return level, trend, seasonality + + +@njit(nogil=NOGIL, cache=CACHE) +def _update_states( + error_type, + trend_type, + seasonality_type, + level, + trend, + seasonality, + data_item: int, + alpha, + beta, + gamma, + phi, +): + """ + Update level, trend, and seasonality components. + + Using state space equations for an ETS model. + + Parameters + ---------- + data_item: float + The current value of the time series. + seasonal_index: int + The index to update the seasonal component. + """ + # Retrieve the current state values + curr_level = level + curr_seasonality = seasonality + fitted_value, damped_trend, trend_level_combination = _predict_value( + trend_type, seasonality_type, level, trend, seasonality, phi + ) + # Calculate the error term (observed value - fitted value) + if error_type == MULTIPLICATIVE: + error = data_item / fitted_value - 1 # Multiplicative error + else: + error = data_item - fitted_value # Additive error + # Update level + if error_type == MULTIPLICATIVE: + level = trend_level_combination * (1 + alpha * error) + trend = damped_trend * (1 + beta * error) + seasonality = curr_seasonality * (1 + gamma * error) + if seasonality_type == ADDITIVE: + level += alpha * error * curr_seasonality # Add seasonality correction + seasonality += gamma * error * trend_level_combination + if trend_type == ADDITIVE: + trend += (curr_level + curr_seasonality) * beta * error + else: + trend += curr_seasonality / curr_level * beta * error + elif trend_type == ADDITIVE: + trend += curr_level * beta * error + else: + level_correction = 1 + trend_correction = 1 + seasonality_correction = 1 + if seasonality_type == MULTIPLICATIVE: + # Add seasonality correction + level_correction *= curr_seasonality + trend_correction *= curr_seasonality + seasonality_correction *= trend_level_combination + if trend_type == MULTIPLICATIVE: + trend_correction *= curr_level + level = trend_level_combination + alpha * error / level_correction + trend = damped_trend + beta * error / trend_correction + seasonality = curr_seasonality + gamma * error / seasonality_correction + return (fitted_value, error, level, trend, seasonality) + + +@njit(nogil=NOGIL, cache=CACHE) +def _predict_value(trend_type, seasonality_type, level, trend, seasonality, phi): + """ + + Generate various useful values, including the next fitted value. + + Parameters + ---------- + trend : float + The current trend value for the model + level : float + The current level value for the model + seasonality : float + The current seasonality value for the model + phi : float + The damping parameter for the model + + Returns + ------- + fitted_value : float + single prediction based on the current state variables. + damped_trend : float + The damping parameter combined with the trend dependant on the model type + trend_level_combination : float + Combination of the trend and level based on the model type. + """ + # Apply damping parameter and + # calculate commonly used combination of trend and level components + if trend_type == MULTIPLICATIVE: + damped_trend = trend**phi + trend_level_combination = level * damped_trend + else: # Additive trend, if no trend, then trend = 0 + damped_trend = trend * phi + trend_level_combination = level + damped_trend + + # Calculate forecast (fitted value) based on the current components + if seasonality_type == MULTIPLICATIVE: + fitted_value = trend_level_combination * seasonality + else: # Additive seasonality, if no seasonality, then seasonality = 0 + fitted_value = trend_level_combination + seasonality + return fitted_value, damped_trend, trend_level_combination diff --git a/aeon/forecasting/_regression.py b/aeon/forecasting/_regression.py new file mode 100644 index 0000000000..79393160b1 --- /dev/null +++ b/aeon/forecasting/_regression.py @@ -0,0 +1,105 @@ +"""Window-based regression forecaster. + +General purpose forecaster to use with any scikit learn or aeon compatible +regressor. Simply forms a collection of windows from the time series and trains to +predict the next +""" + +import numpy as np +from sklearn.linear_model import LinearRegression + +from aeon.forecasting.base import BaseForecaster + + +class RegressionForecaster(BaseForecaster): + """ + Regression based forecasting. + + Container for forecaster that reduces forecasting to regression through a + window. Form a collection of sub series of length `window` through a sliding + winodw to form X, take `horizon` points ahead to form `y`, then apply an aeon or + sklearn regressor. + + + Parameters + ---------- + window : int + The window prior to the current time point to use in forecasting. So if + horizon is one, forecaster will train using points $i$ to $window+i-1$ to + predict value $window+i$. If horizon is 4, forecaster will used points $i$ + to $window+i-1$ to predict value $window+i+3$. If None, the algorithm will + internally determine what data to use to predict `horizon` steps ahead. + horizon : int, default =1 + The number of time steps ahead to forecast. If horizon is one, the forecaster + will learn to predict one point ahead + regressor : object, default =None + Regression estimator that implements BaseRegressor or is otherwise compatible + with sklearn regressors. + """ + + def __init__(self, window, horizon=1, regressor=None): + self.window = window + self.regressor = regressor + super().__init__(horizon=horizon, axis=1) + + def _fit(self, y, exog=None): + """Fit forecaster to time series. + + Split X into windows of length window and train the forecaster on each window + to predict the horizon ahead. + + Parameters + ---------- + X : Time series on which to learn a forecaster + + Returns + ------- + self + Fitted estimator + """ + # Window data + if self.regressor is None: + self.regressor_ = LinearRegression() + else: + self.regressor_ = self.regressor + y = y.squeeze() + X = np.lib.stride_tricks.sliding_window_view(y, window_shape=self.window) + # Ignore the final horizon values: need to store these for pred with empty y + X = X[: -self.horizon] + # Extract y + y = y[self.window + self.horizon - 1 :] + self.last_ = y[-self.window :] + self.last_ = self.last_.reshape(1, -1) + self.regressor_.fit(X=X, y=y) + return self + + def _predict(self, y=None, exog=None): + """Predict values for time series X.""" + if y is None: + return self.regressor_.predict(self.last_) + last = y[:, -self.window :] + return self.regressor_.predict(last) + + def _forecast(self, y, exog=None): + """Forecast values for time series X. + + NOTE: deal with horizons + """ + self.fit(y, exog) + return self.predict() + + @classmethod + def _get_test_params(cls, parameter_set="default"): + """Return testing parameter settings for the estimator. + + Parameters + ---------- + parameter_set : str, default='default' + Name of the parameter set to return. + + Returns + ------- + dict + Dictionary of testing parameter settings. + """ + return {"window": 4} diff --git a/aeon/forecasting/base.py b/aeon/forecasting/base.py new file mode 100644 index 0000000000..e67712c58a --- /dev/null +++ b/aeon/forecasting/base.py @@ -0,0 +1,159 @@ +"""BaseForecaster class. + +A simplified first base class for forecasting models. + +""" + +from abc import abstractmethod + +import numpy as np +import pandas as pd + +from aeon.base import BaseSeriesEstimator +from aeon.base._base_series import VALID_SERIES_INNER_TYPES + + +class BaseForecaster(BaseSeriesEstimator): + """ + Abstract base class for time series forecasters. + + The base forecaster specifies the methods and method signatures that all + forecasters have to implement. Attributes with an underscore suffix are set in the + method fit. + + Parameters + ---------- + horizon : int, default =1 + The number of time steps ahead to forecast. If horizon is one, the forecaster + will learn to predict one point ahead. + """ + + _tags = { + "capability:univariate": True, + "capability:multivariate": False, + "capability:missing_values": False, + "fit_is_empty": False, + "y_inner_type": "np.ndarray", + } + + def __init__(self, horizon, axis): + self.horizon = horizon + self.meta_ = None # Meta data related to y on the last fit + super().__init__(axis) + + def fit(self, y, exog=None): + """Fit forecaster to series y. + + Fit a forecaster to predict self.horizon steps ahead using y. + + Parameters + ---------- + y : np.ndarray + A time series on which to learn a forecaster to predict horizon ahead. + exog : np.ndarray, default =None + Optional exogenous time series data assumed to be aligned with y. + + Returns + ------- + self + Fitted BaseForecaster. + """ + if self.get_tag("fit_is_empty"): + self.is_fitted = True + return self + + self._check_X(y, self.axis) + y = self._convert_y(y, self.axis) + if exog is not None: + raise NotImplementedError("Exogenous variables not yet supported") + self.is_fitted = True + return self._fit(y, exog) + + @abstractmethod + def _fit(self, y, exog=None): ... + + def predict(self, y=None, exog=None): + """Predict the next horizon steps ahead. + + Parameters + ---------- + y : np.ndarray, default = None + A time series to predict the next horizon value for. If None, + predict the next horizon value after series seen in fit. + exog : np.ndarray, default =None + Optional exogenous time series data assumed to be aligned with y. + + Returns + ------- + float + single prediction self.horizon steps ahead of y. + """ + self._check_is_fitted() + if y is not None: + self._check_X(y, self.axis) + y = self._convert_y(y, self.axis) + if exog is not None: + raise NotImplementedError("Exogenous variables not yet supported") + return self._predict(y, exog) + + @abstractmethod + def _predict(self, y=None, exog=None): ... + + def forecast(self, y, exog=None): + """Forecast the next horizon steps ahead. + + By default this is simply fit followed by predict. + + Parameters + ---------- + y : np.ndarray, default = None + A time series to predict the next horizon value for. If None, + predict the next horizon value after series seen in fit. + exog : np.ndarray, default =None + Optional exogenous time series data assumed to be aligned with y. + + Returns + ------- + float + single prediction self.horizon steps ahead of y. + """ + self._check_X(y, self.axis) + y = self._convert_y(y, self.axis) + return self._forecast(y, exog) + + def _forecast(self, y, exog=None): + """Forecast values for time series X.""" + self.fit(y, exog) + return self._predict(y, exog) + + def _convert_y(self, y: VALID_SERIES_INNER_TYPES, axis: int): + """Convert y to self.get_tag("y_inner_type").""" + if axis > 1 or axis < 0: + raise ValueError(f"Input axis should be 0 or 1, saw {axis}") + + inner_type = self.get_tag("y_inner_type") + if not isinstance(inner_type, list): + inner_type = [inner_type] + inner_names = [i.split(".")[-1] for i in inner_type] + + input = type(y).__name__ + if input not in inner_names: + if inner_names[0] == "ndarray": + y = y.to_numpy() + elif inner_names[0] == "DataFrame": + # converting a 1d array will create a 2d array in axis 0 format + transpose = False + if y.ndim == 1 and axis == 1: + transpose = True + y = pd.DataFrame(y) + if transpose: + y = y.T + else: + raise ValueError( + f"Unsupported inner type {inner_names[0]} derived from {inner_type}" + ) + if y.ndim > 1 and self.axis != axis: + y = y.T + elif y.ndim == 1 and isinstance(y, np.ndarray): + y = y[np.newaxis, :] if self.axis == 1 else y[:, np.newaxis] + return y diff --git a/aeon/forecasting/tests/__init__.py b/aeon/forecasting/tests/__init__.py new file mode 100644 index 0000000000..90b32266a4 --- /dev/null +++ b/aeon/forecasting/tests/__init__.py @@ -0,0 +1 @@ +"""Forecaster tests.""" diff --git a/aeon/forecasting/tests/test_base.py b/aeon/forecasting/tests/test_base.py new file mode 100644 index 0000000000..e1a634eba3 --- /dev/null +++ b/aeon/forecasting/tests/test_base.py @@ -0,0 +1,16 @@ +"""Test base forecaster.""" + +import numpy as np + +from aeon.forecasting import DummyForecaster + + +def test_base_forecaster(): + """Test base forecaster functionality.""" + f = DummyForecaster() + y = np.random.rand(50) + f.fit(y) + p1 = f.predict() + assert p1 == y[-1] + p2 = f.forecast(y) + assert p2 == p1 diff --git a/aeon/forecasting/tests/test_regressor.py b/aeon/forecasting/tests/test_regressor.py new file mode 100644 index 0000000000..ec6e273bfd --- /dev/null +++ b/aeon/forecasting/tests/test_regressor.py @@ -0,0 +1,16 @@ +"""Test the regression forecaster.""" + +from aeon.datasets import load_airline +from aeon.forecasting import RegressionForecaster + + +def test_regression_forecaster(): + """Test the regression forecaster.""" + y = load_airline() + f = RegressionForecaster(window=10) + f.fit(y) + p = f.predict() + p2 = f.predict(y) + assert p == p2 + p3 = f.forecast(y) + assert p == p3 diff --git a/aeon/testing/estimator_checking/_yield_forecasting_checks.py b/aeon/testing/estimator_checking/_yield_forecasting_checks.py new file mode 100644 index 0000000000..5c62d2f05d --- /dev/null +++ b/aeon/testing/estimator_checking/_yield_forecasting_checks.py @@ -0,0 +1,51 @@ +"""Tests for all forecasters.""" + +from functools import partial + +import numpy as np + +from aeon.base._base import _clone_estimator +from aeon.base._base_series import VALID_SERIES_INPUT_TYPES + + +def _yield_forecasting_checks(estimator_class, estimator_instances, datatypes): + """Yield all forecasting checks for an aeon forecaster.""" + # only class required + yield partial(check_forecasting_base_functionality, estimator_class=estimator_class) + + # test class instances + for _, estimator in enumerate(estimator_instances): + # no data needed + yield partial(check_forecaster_instance, estimator=estimator) + + +def check_forecasting_base_functionality(estimator_class): + """Test compliance with the base class contract.""" + # Test they dont override final methods, because python does not enforce this + assert "fit" not in estimator_class.__dict__ + assert "predict" not in estimator_class.__dict__ + assert "forecast" not in estimator_class.__dict__ + fit_is_empty = estimator_class.get_class_tag(tag_name="fit_is_empty") + assert not fit_is_empty == "_fit" not in estimator_class.__dict__ + # Test valid tag for X_inner_type + X_inner_type = estimator_class.get_class_tag(tag_name="X_inner_type") + assert X_inner_type in VALID_SERIES_INPUT_TYPES + # Must have at least one set to True + multi = estimator_class.get_class_tag(tag_name="capability:multivariate") + uni = estimator_class.get_class_tag(tag_name="capability:univariate") + assert multi or uni + + +def check_forecaster_instance(estimator): + """Test forecasters.""" + estimator = _clone_estimator(estimator) + pass + # Sort + # Check output correct: predict should return a float + y = np.array([0.5, 0.7, 0.8, 0.9, 1.0]) + estimator.fit(y) + p = estimator.predict() + assert isinstance(p, float) + # forecast should return a float equal to fit/predict + p2 = estimator.forecast(y) + assert p == p2 diff --git a/aeon/testing/mock_estimators/_mock_forecasters.py b/aeon/testing/mock_estimators/_mock_forecasters.py new file mode 100644 index 0000000000..f5bb86d249 --- /dev/null +++ b/aeon/testing/mock_estimators/_mock_forecasters.py @@ -0,0 +1,22 @@ +"""Mock forecasters useful for testing and debugging. + +Used in tests for the forecasting base class. +""" + +from aeon.forecasting.base import BaseForecaster + + +class MockForecaster(BaseForecaster): + """Mock forecaster for testing.""" + + def __init__(self): + super().__init__() + + def _fit(self, y, X=None): + return self + + def _predict(self, y): + return 1.0 + + def _forecast(self, y, X=None): + return 1.0 diff --git a/aeon/testing/testing_data.py b/aeon/testing/testing_data.py index 47b990b220..eb134cddda 100644 --- a/aeon/testing/testing_data.py +++ b/aeon/testing/testing_data.py @@ -7,6 +7,7 @@ from aeon.classification import BaseClassifier from aeon.classification.early_classification import BaseEarlyClassifier from aeon.clustering import BaseClusterer +from aeon.forecasting import BaseForecaster from aeon.regression import BaseRegressor from aeon.segmentation import BaseSegmenter from aeon.similarity_search import BaseSimilaritySearch @@ -22,9 +23,11 @@ ) from aeon.transformations.collection import BaseCollectionTransformer from aeon.transformations.series import BaseSeriesTransformer +from aeon.utils.conversion import convert_collection data_rng = np.random.RandomState(42) +# Collection testing data EQUAL_LENGTH_UNIVARIATE_CLASSIFICATION = { "numpy3D": { @@ -725,39 +728,61 @@ "numpy3D": { "train": (X_classification_missing_train, y_classification_missing_train), "test": (X_classification_missing_test, y_classification_missing_test), - } + }, + "np-list": { + "train": ( + convert_collection(X_classification_missing_train, "np-list"), + y_classification_missing_train, + ), + "test": ( + convert_collection(X_classification_missing_test, "np-list"), + y_classification_missing_test, + ), + }, } -X_classification_missing_train, y_classification_missing_train = make_example_3d_numpy( +X_regression_missing_train, y_regression_missing_train = make_example_3d_numpy( n_cases=10, n_channels=1, n_timepoints=20, random_state=data_rng.randint(np.iinfo(np.int32).max), regression_target=True, ) -X_classification_missing_test, y_classification_missing_test = make_example_3d_numpy( +X_regression_missing_test, y_regression_missing_test = make_example_3d_numpy( n_cases=5, n_channels=1, n_timepoints=20, random_state=data_rng.randint(np.iinfo(np.int32).max), regression_target=True, ) -X_classification_missing_train[:, :, data_rng.choice(20, 2)] = np.nan -X_classification_missing_test[:, :, data_rng.choice(20, 2)] = np.nan +X_regression_missing_train[:, :, data_rng.choice(20, 2)] = np.nan +X_regression_missing_test[:, :, data_rng.choice(20, 2)] = np.nan MISSING_VALUES_REGRESSION = { "numpy3D": { - "train": (X_classification_missing_train, y_classification_missing_train), - "test": (X_classification_missing_test, y_classification_missing_test), - } + "train": (X_regression_missing_train, y_regression_missing_train), + "test": (X_regression_missing_test, y_regression_missing_test), + }, + "np-list": { + "train": ( + convert_collection(X_regression_missing_train, "np-list"), + y_regression_missing_train, + ), + "test": ( + convert_collection(X_regression_missing_test, "np-list"), + y_regression_missing_test, + ), + }, } +# Series testing data + X_series = make_example_1d_numpy( n_timepoints=40, random_state=data_rng.randint(np.iinfo(np.int32).max) ) X_series2 = X_series[20:40] X_series = X_series[:20] -UNIVARIATE_SERIES_NOLABEL = {"train": (X_series, None), "test": (X_series2, None)} +UNIVARIATE_SERIES_NONE = {"train": (X_series, None), "test": (X_series2, None)} X_series_mv = make_example_2d_numpy_series( n_timepoints=40, @@ -767,7 +792,7 @@ ) X_series_mv2 = X_series_mv[:, 20:40] X_series_mv = X_series_mv[:, :20] -MULTIVARIATE_SERIES_NOLABEL = { +MULTIVARIATE_SERIES_NONE = { "train": (X_series_mv, None), "test": (X_series_mv2, None), } @@ -779,7 +804,12 @@ X_series_mi2[data_rng.choice(20, 1)] = np.nan X_series_mi = X_series_mi[:20] X_series_mi[data_rng.choice(20, 2)] = np.nan -MISSING_VALUES_NOLABEL = {"train": (X_series_mi, None), "test": (X_series_mi2, None)} +MISSING_VALUES_SERIES_NONE = { + "train": (X_series_mi, None), + "test": (X_series_mi2, None), +} + +# All testing data FULL_TEST_DATA_DICT = {} # Collection @@ -864,10 +894,11 @@ FULL_TEST_DATA_DICT.update( {f"MissingValues-Regression-{k}": v for k, v in MISSING_VALUES_REGRESSION.items()} ) + # Series -FULL_TEST_DATA_DICT.update({"UnivariateSeries-NoLabel": UNIVARIATE_SERIES_NOLABEL}) -FULL_TEST_DATA_DICT.update({"MultivariateSeries-NoLabel": MULTIVARIATE_SERIES_NOLABEL}) -FULL_TEST_DATA_DICT.update({"MissingValues-NoLabel": MISSING_VALUES_NOLABEL}) +FULL_TEST_DATA_DICT.update({"UnivariateSeries-None": UNIVARIATE_SERIES_NONE}) +FULL_TEST_DATA_DICT.update({"MultivariateSeries-None": MULTIVARIATE_SERIES_NONE}) +FULL_TEST_DATA_DICT.update({"MissingValues-None": MISSING_VALUES_SERIES_NONE}) def _get_datatypes_for_estimator(estimator): @@ -881,17 +912,14 @@ def _get_datatypes_for_estimator(estimator): Returns ------- datatypes : list of tuple - List of valid data types keys for the estimator usable in FULL_TEST_DATA_DICT - and TEST_LABEL_DICT. Each tuple is formatted (data_key, label_key). + List of valid data types keys for the estimator usable in + FULL_TEST_DATA_DICT. Each tuple is formatted (data_key, label_key). """ datatypes = [] - ( - univariate, - multivariate, - unequal_length, - missing_values, - ) = _get_capabilities_for_estimator(estimator) - label_type = _get_label_type_for_estimator(estimator) + univariate, multivariate, unequal_length, missing_values = ( + _get_capabilities_for_estimator(estimator) + ) + task = _get_task_for_estimator(estimator) inner_types = estimator.get_tag("X_inner_type") if not isinstance(inner_types, list): @@ -900,34 +928,34 @@ def _get_datatypes_for_estimator(estimator): if isinstance(estimator, BaseCollectionEstimator): for inner_type in inner_types: if univariate: - s = f"EqualLengthUnivariate-{label_type}-{inner_type}" + s = f"EqualLengthUnivariate-{task}-{inner_type}" if s in FULL_TEST_DATA_DICT: datatypes.append(s) if unequal_length: - s = f"UnequalLengthUnivariate-{label_type}-{inner_type}" + s = f"UnequalLengthUnivariate-{task}-{inner_type}" if s in FULL_TEST_DATA_DICT: datatypes.append(s) if multivariate: - s = f"EqualLengthMultivariate-{label_type}-{inner_type}" + s = f"EqualLengthMultivariate-{task}-{inner_type}" if s in FULL_TEST_DATA_DICT: datatypes.append(s) if unequal_length: - s = f"UnequalLengthMultivariate-{label_type}-{inner_type}" + s = f"UnequalLengthMultivariate-{task}-{inner_type}" if s in FULL_TEST_DATA_DICT: datatypes.append(s) if missing_values: - datatypes.append(f"MissingValues-{label_type}-numpy3D") + datatypes.append(f"MissingValues-{task}-numpy3D") elif isinstance(estimator, BaseSeriesEstimator): if univariate: - datatypes.append("UnivariateSeries-NoLabel") + datatypes.append(f"UnivariateSeries-{task}") if multivariate: - datatypes.append("MultivariateSeries-NoLabel") + datatypes.append(f"MultivariateSeries-{task}") if missing_values: - datatypes.append("MissingValues-NoLabel") + datatypes.append(f"MissingValues-{task}") else: raise ValueError(f"Unknown estimator type: {type(estimator)}") @@ -965,37 +993,41 @@ def _get_capabilities_for_estimator(estimator): return univariate, multivariate, unequal_length, missing_values -def _get_label_type_for_estimator(estimator): - """Get label type for estimator. +def _get_task_for_estimator(estimator): + """Get task string used to select the correct test data for the estimator. Parameters ---------- estimator : BaseAeonEstimator instance or class - Estimator instance or class to check for valid input data types. + Estimator instance or class to find the task string for. Returns ------- - label_type : str - Label type key for the estimator for use in TEST_LABEL_DICT. + data_label : str + Task string for the estimator used in forming a key from FULL_TEST_DATA_DICT. """ + # collection data with class labels if ( isinstance(estimator, BaseClassifier) or isinstance(estimator, BaseEarlyClassifier) or isinstance(estimator, BaseClusterer) or isinstance(estimator, BaseCollectionTransformer) ): - label_type = "Classification" + data_label = "Classification" + # collection data with continuous target labels elif isinstance(estimator, BaseRegressor): - label_type = "Regression" + data_label = "Regression" elif isinstance(estimator, BaseSimilaritySearch): - label_type = "SimilaritySearch" + data_label = "SimilaritySearch" + # series data with no secondary input elif ( isinstance(estimator, BaseAnomalyDetector) or isinstance(estimator, BaseSegmenter) or isinstance(estimator, BaseSeriesTransformer) + or isinstance(estimator, BaseForecaster) ): - label_type = "NoLabel" + data_label = "None" else: raise ValueError(f"Unknown estimator type: {type(estimator)}") - return label_type + return data_label diff --git a/aeon/testing/tests/test_testing_data.py b/aeon/testing/tests/test_testing_data.py index 67d2f885ef..505cb474a8 100644 --- a/aeon/testing/tests/test_testing_data.py +++ b/aeon/testing/tests/test_testing_data.py @@ -411,3 +411,6 @@ def test_missing_values_collection(): assert np.issubdtype( MISSING_VALUES_REGRESSION[key]["test"][1].dtype, np.integer ) or np.issubdtype(MISSING_VALUES_REGRESSION[key]["test"][1].dtype, np.floating) + + +# todo series testing data diff --git a/aeon/testing/utils/estimator_checks.py b/aeon/testing/utils/estimator_checks.py index c78de4bc7a..b2e0973dbf 100644 --- a/aeon/testing/utils/estimator_checks.py +++ b/aeon/testing/utils/estimator_checks.py @@ -16,11 +16,19 @@ def _run_estimator_method(estimator, method_name, datatype, split): method = getattr(estimator, method_name) args = inspect.getfullargspec(method)[0] try: - if "X" in args and "length" in args: # SeriesSearch + # forecasting + if "y" in args and "exog" in args: + return method( + y=FULL_TEST_DATA_DICT[datatype][split][0], + exog=FULL_TEST_DATA_DICT[datatype][split][1], + ) + # similarity search + elif "X" in args and "length" in args: value = method( X=FULL_TEST_DATA_DICT[datatype][split][0], length=3, ) + # general use elif "X" in args and "y" in args: value = method( X=FULL_TEST_DATA_DICT[datatype][split][0], diff --git a/aeon/utils/base/_register.py b/aeon/utils/base/_register.py index 1327d626ef..1d81c2512c 100644 --- a/aeon/utils/base/_register.py +++ b/aeon/utils/base/_register.py @@ -21,6 +21,7 @@ from aeon.classification.base import BaseClassifier from aeon.classification.early_classification import BaseEarlyClassifier from aeon.clustering.base import BaseClusterer +from aeon.forecasting.base import BaseForecaster from aeon.regression.base import BaseRegressor from aeon.segmentation.base import BaseSegmenter from aeon.similarity_search.base import BaseSimilaritySearch @@ -45,6 +46,7 @@ "segmenter": BaseSegmenter, "similarity_searcher": BaseSimilaritySearch, "series-transformer": BaseSeriesTransformer, + "forecaster": BaseForecaster, } # base classes which are valid for estimator to directly inherit from diff --git a/aeon/utils/tags/_tags.py b/aeon/utils/tags/_tags.py index 650a7c4dc4..554584115e 100644 --- a/aeon/utils/tags/_tags.py +++ b/aeon/utils/tags/_tags.py @@ -53,6 +53,14 @@ class : identifier for the base class of objects this tag applies to "description": "What data structure(s) the estimator uses internally for " "fit/predict.", }, + "y_inner_type": { + "class": "forecaster", + "type": [ + ("list||str", SERIES_DATA_TYPES), + ], + "description": "What data structure(s) the estimator uses internally for " + "fit/predict.", + }, "algorithm_type": { "class": "estimator", "type": [ diff --git a/examples/forecasting/forecasting.ipynb b/examples/forecasting/forecasting.ipynb new file mode 100644 index 0000000000..e17b6667dc --- /dev/null +++ b/examples/forecasting/forecasting.ipynb @@ -0,0 +1,417 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "source": [ + "# Time series forecasting with aeon\n", + "\n", + "This notebook describes the new, experimental, forecasting module in aeon. We have\n", + "recently removed a lot of legacy code that was almost entirely wrappers around other\n", + "projects, mostly statsmodels. Most of the contributors to aeon are from a computer\n", + "science/machine learning background rather than stats and forecasting, and our\n", + "objectives for forecasting have changed to reflect this. Our focus is on:\n", + "\n", + "1. not attempting to be a comprehensive forecasting package.\n", + "\n", + "Forecasting is a wide field with lots of specific variants and use cases. The open\n", + "source landscape is crowded with packages that focus primarily or exclusively on\n", + "forecasting. We are not trying to do all things in forecasting. We want to focus on a\n", + " few key use cases that reflect our research interests.\n", + "\n", + "2. fast forecasting with numpy arrays.\n", + "\n", + "Whilst our forecasters will work with data frames, our design principle is to write\n", + "code optimised with numba and numpy. We found that extensive use of data frames in\n", + "the internal calculations of forecasters makes them much slower and harder to\n", + "understand for those not used to using dataframes daily.\n", + "\n", + "3. forecasting using machine learning and deep learning.\n", + "\n", + "we want to implement and assess the latest machine learning and deep learning\n", + "forecasting for scenarios where it makes sense to use them. Our initial experimental\n", + "focus will be on forecasting with long series for a single forecasting horizon.\n" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "markdown", + "source": [ + "## Base Class\n", + "\n", + "Our first design choice for forecasting is to pass the forecasting horizon in the\n", + "constructor (default is 1). This is because we want a simpler use case: a forecaster\n", + "trains to predict so many places in the future, then for unseen data, it predicts the\n", + " same number of steps ahead. We recognise there are other scenarios, but this is the\n", + " cleanest way to start.\n", + "\n", + " The base class for all forecasters is `BaseForecaster`. It inherits from\n", + " `BaseSeriesEstimator`, which is also the base class for the other series estimators\n", + " in aeon: `BaseSegmenter`, `BaseAnomalyDetector` and `BaseSeriesTransformer`. The\n", + " base class `BaseSeriesEstimator` contains a method to validate and possibly convert\n", + " an input series.\n", + "The `BaseForecaster` has three core methods: `fit`, `predict` and `forecast`. It is\n", + "an abstract class, and each of these methods calls a protected method `_fit`,\n", + "`_predict` and `_forecast`.\n" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "source": [ + "import inspect\n", + "\n", + "from aeon.forecasting import BaseForecaster\n", + "\n", + "# List methods\n", + "public_methods = [\n", + " func[0]\n", + " for func in inspect.getmembers(BaseForecaster, predicate=inspect.isfunction)\n", + " if not func[0].startswith(\"_\")\n", + "]\n", + "print(public_methods)" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-11-16T19:20:13.050238Z", + "start_time": "2024-11-16T19:20:13.044254Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['clone', 'fit', 'forecast', 'get_fitted_params', 'get_metadata_routing', 'get_params', 'get_tag', 'get_tags', 'predict', 'reset', 'set_params', 'set_tags']\n" + ] + } + ], + "execution_count": 10 + }, + { + "cell_type": "markdown", + "source": [ + " All estimators in `aeon` have tags. One specific to\n", + "forecasting is `y_inner_type`. This specifies the inner type the sub class of\n", + "BaseForecaster needs to input the method `_fit` and `_predict`. The default is `np\n", + ".ndarray` but it can also be `pd.DataFrame` or `pd.Series`. You can pass\n", + "forecaster and of `SERIES_DATA_TYPES` and it will be converted to `y_inner_type` in\n", + "`fit`, `predict` and `forecast`." + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "source": [ + "from aeon.utils import SERIES_DATA_TYPES\n", + "\n", + "print(\" Possible data structures for input to forecaster \", SERIES_DATA_TYPES)\n", + "print(\"\\n Tags for BaseForecaster: \", BaseForecaster.get_class_tags())" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-11-16T19:20:14.277081Z", + "start_time": "2024-11-16T19:20:14.262132Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Possible data structures for input to forecaster ['pd.Series', 'pd.DataFrame', 'np.ndarray']\n", + "\n", + " Tags for BaseForecaster: {'python_version': None, 'python_dependencies': None, 'cant_pickle': False, 'non_deterministic': False, 'algorithm_type': None, 'capability:missing_values': False, 'capability:multithreading': False, 'capability:univariate': True, 'capability:multivariate': False, 'X_inner_type': 'np.ndarray', 'fit_is_empty': False, 'y_inner_type': 'np.ndarray'}\n" + ] + } + ], + "execution_count": 11 + }, + { + "cell_type": "markdown", + "source": [ + "We use the standard airline dataset for examples. This can be stored as a pd.Series,\n", + "pd.DataFrame or np.ndarray." + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "source": [ + "import pandas as pd\n", + "\n", + "from aeon.datasets import load_airline\n", + "\n", + "y = load_airline()\n", + "print(type(y))\n", + "y2 = pd.Series(y)\n", + "y3 = pd.DataFrame(y)" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-11-16T19:20:15.586960Z", + "start_time": "2024-11-16T19:20:15.578482Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "execution_count": 12 + }, + { + "cell_type": "markdown", + "source": [ + "## DummyForecaster\n", + "\n", + "A dummy forecaster can illustrate the use cases for forecasting. This\n", + "forecaster simply returns the last value of the train data for the forecast. By\n", + "default the horizon is 1. It makes no difference for this forecaster. It's inner type\n", + " is `np.ndarray` so all three allowable input types are internally converted to numpy\n", + " arrays." + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "source": [ + "# Fit then predict\n", + "from aeon.forecasting import DummyForecaster\n", + "\n", + "d = DummyForecaster()\n", + "print(d.get_tag(\"y_inner_type\"))\n", + "d.fit(y)\n", + "p = d.predict()\n", + "print(p)" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-11-16T19:20:17.280150Z", + "start_time": "2024-11-16T19:20:17.270176Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "np.ndarray\n", + "432.0\n" + ] + } + ], + "execution_count": 13 + }, + { + "cell_type": "code", + "source": [ + "# forecast is equivalent to fit_predict in other estimators\n", + "p2 = d.forecast(y)\n", + "print(p2)" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-11-16T19:20:17.997049Z", + "start_time": "2024-11-16T19:20:17.985082Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "432.0\n" + ] + } + ], + "execution_count": 14 + }, + { + "cell_type": "markdown", + "source": [ + "## Regression based forecasting\n", + "\n", + "Our main focus will be forecasting through a sliding window and a regressor. We\n", + "provide a basic implementation of this in `RegressionForecaster`. This class can take\n", + " a regressor as a constructor parameter. It will train the regressor on the windowed\n", + " series, then apply the data to new series. There will be a notebook for more details\n", + " of the use of RegressionForecaster. By default it just uses a linear regressor, but\n", + " our goal is to use it with `aeon` time series regressors." + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "source": [ + "from aeon.forecasting import RegressionForecaster\n", + "\n", + "r = RegressionForecaster(window=20)\n", + "r.fit(y)\n", + "p = r.predict()\n", + "print(p)\n", + "r2 = RegressionForecaster(window=10, horizon=5)\n", + "r2.fit(y)\n", + "p = r2.predict(y)\n", + "print(p)" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-11-16T19:20:19.366693Z", + "start_time": "2024-11-16T19:20:19.356837Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[451.67541971]\n", + "[527.36897094]\n" + ] + } + ], + "execution_count": 15 + }, + { + "cell_type": "markdown", + "source": [ + "With our set up, we can make predictions with previously unseen data, thus more\n", + "closely modelling machine learning approaches. Or we can use the forecast method to\n", + "fit/predict at the same time." + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "source": [ + "p1 = r.forecast(y)\n", + "p2 = r2.forecast(y)\n", + "print(p1, \",\\n\", p2)" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-11-16T19:21:24.486613Z", + "start_time": "2024-11-16T19:21:24.464704Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[451.67541971] ,\n", + " [527.36897094]\n" + ] + } + ], + "execution_count": 19 + }, + { + "cell_type": "markdown", + "source": [ + "## Exponential Smoothing\n", + "\n", + "The base exponential smoothing module is implemented in stripped down code with \n", + "numba, and is very fast" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "source": [ + "from aeon.forecasting import ETSForecaster\n", + "\n", + "ets = ETSForecaster()\n", + "ets.fit(y)\n", + "ets.predict()\n" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-11-16T19:21:26.225501Z", + "start_time": "2024-11-16T19:21:26.204872Z" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "460.302772481884" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "execution_count": 20 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2024-11-16T19:21:27.095665Z", + "start_time": "2024-11-16T19:21:27.077715Z" + } + }, + "cell_type": "code", + "source": "", + "outputs": [], + "execution_count": null + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "" + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +}