diff --git a/README.md b/README.md index 09b4d9c..913db6d 100644 --- a/README.md +++ b/README.md @@ -2,4 +2,5 @@ Here are some of [dida](https://dida.do/)'s public projects. * [Handwriting app](https://github.com/dida-do/public/tree/master/handwriting_app) -* [Labeling tool](https://github.com/dida-do/public/tree/master/labelingtool) \ No newline at end of file +* [Labeling tool](https://github.com/dida-do/public/tree/master/labelingtool) +* [Explainable ROCKET](https://github.com/dida-do/public/tree/master/xrocket) \ No newline at end of file diff --git a/xrocket/.gitignore b/xrocket/.gitignore new file mode 100644 index 0000000..b73bf11 --- /dev/null +++ b/xrocket/.gitignore @@ -0,0 +1,7 @@ +# ignore contents of these directories +.venv/* + +# ignore these extensions +*.csv +*.zip +*.pyc \ No newline at end of file diff --git a/xrocket/README.md b/xrocket/README.md new file mode 100644 index 0000000..f3ac2b5 --- /dev/null +++ b/xrocket/README.md @@ -0,0 +1,31 @@ +# X-ROCKET code repository + +To use the X-rocket encoder for timeseries embeddings install the dependencies in `requirements.txt` and import as follows: +```python +from xrocket.encoder import XRocket +``` + +Then initialize the encoder with the desired hyperparameters: +```python +XRocket( + in_channels: int, + max_kernel_span: int, + combination_order: int = 1, + combination_method: str = "additive", + feature_cap: int = 10_000, + kernel_length: int = 9, + max_dilations: int = 32, +) +``` + +The following hyperparameters can be chosen: +- in_channels: The number of channels in the data. +- max_kernel_span: Maximum length to be considered for patter search, + usually set to the number of time-observations in a typical timeseries. +- combination_order: The maximum number of channels to be interacted, default=1. +- combination_method: Keyword for the channel mixing method, default='additive'. +- feature_cap: Maximum number of embedding values to be considered, default=10,000. +- kernel_length: The length of the 1D convolutional kernels, default=9. +- max_dilations: The maximum number of distinct dilation values, default=32. + +If the encoder thresholds are not explicitly fit to a data example before encoding, the first example will automatically define the thresholds. \ No newline at end of file diff --git a/xrocket/example.ipynb b/xrocket/example.ipynb new file mode 100644 index 0000000..d1fb160 --- /dev/null +++ b/xrocket/example.ipynb @@ -0,0 +1,217 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Data & preprocessing" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from aeon.datasets import load_classification\n", + "from sklearn.model_selection import train_test_split\n", + "\n", + "X, y, meta_data = load_classification(\"AsphaltPavementTypeCoordinates\")\n", + "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.5, random_state=0)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## X-ROCKET encoder" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "from xrocket import XRocket\n", + "from torch import Tensor\n", + "\n", + "encoder = XRocket(in_channels=3, max_kernel_span=100, combination_order=1, feature_cap=10_000)\n", + "encoder.fit(Tensor(X_train[0]).unsqueeze(0))" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "embed_train, embed_test = [], []\n", + "for x in X_train:\n", + " embed_train.append(encoder(Tensor(x).unsqueeze(0)))\n", + "for x in X_test:\n", + " embed_test.append(encoder(Tensor(x).unsqueeze(0)))" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "from torch import concat\n", + "import pandas as pd\n", + "\n", + "feature_names = pd.Index(encoder.feature_names).rename([\"pattern\", \"dilation\", \"channel\", \"threshold\"])\n", + "embed_train = pd.DataFrame(data=concat(embed_train), columns=feature_names)\n", + "embed_test = pd.DataFrame(data=concat(embed_test), columns=feature_names)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Prediction head" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
RandomForestClassifier()
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
" + ], + "text/plain": [ + "RandomForestClassifier()" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from sklearn.ensemble import RandomForestClassifier\n", + "\n", + "model = RandomForestClassifier()\n", + "model.fit(embed_train, y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.metrics import accuracy_score\n", + "\n", + "pred_train, pred_test = model.predict(embed_train), model.predict(embed_test)\n", + "acc_train, acc_test = accuracy_score(y_train, pred_train), accuracy_score(y_test, pred_test)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Feature importances" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "feature_importances = pd.Series(data=model.feature_importances_, index=feature_names)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "channel_importances = feature_importances.abs().groupby(\"channel\").sum()\n", + "ax = channel_importances.plot(kind=\"barh\")" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "dilation_importances = feature_importances.groupby(\"dilation\").sum().sort_values()\n", + "ax = dilation_importances.plot(kind=\"barh\")" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pattern_importances = feature_importances.groupby(\"pattern\").sum().sort_values()\n", + "ax = pattern_importances.plot(kind=\"barh\", figsize=(6,20))\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "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": "3.9.17" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/xrocket/requirements.txt b/xrocket/requirements.txt new file mode 100644 index 0000000..9870240 --- /dev/null +++ b/xrocket/requirements.txt @@ -0,0 +1,114 @@ +# +# This file is autogenerated by pip-compile with Python 3.9 +# by the following command: +# +# pip-compile requirements.in +# +aeon==0.4.0 + # via -r requirements.in +attrs==23.1.0 + # via aeon +cmake==3.27.4.1 + # via triton +deprecated==1.2.14 + # via aeon +filelock==3.12.4 + # via + # torch + # triton +jinja2==3.1.2 + # via torch +joblib==1.3.2 + # via scikit-learn +lit==16.0.6 + # via triton +llvmlite==0.40.1 + # via numba +markupsafe==2.1.3 + # via jinja2 +mpmath==1.3.0 + # via sympy +networkx==3.1 + # via torch +numba==0.57.1 + # via aeon +numpy==1.24.4 + # via + # -r requirements.in + # aeon + # numba + # pandas + # scikit-learn + # scipy +nvidia-cublas-cu11==11.10.3.66 + # via + # nvidia-cudnn-cu11 + # nvidia-cusolver-cu11 + # torch +nvidia-cuda-cupti-cu11==11.7.101 + # via torch +nvidia-cuda-nvrtc-cu11==11.7.99 + # via torch +nvidia-cuda-runtime-cu11==11.7.99 + # via torch +nvidia-cudnn-cu11==8.5.0.96 + # via torch +nvidia-cufft-cu11==10.9.0.58 + # via torch +nvidia-curand-cu11==10.2.10.91 + # via torch +nvidia-cusolver-cu11==11.4.0.1 + # via torch +nvidia-cusparse-cu11==11.7.4.91 + # via torch +nvidia-nccl-cu11==2.14.3 + # via torch +nvidia-nvtx-cu11==11.7.91 + # via torch +packaging==23.1 + # via aeon +pandas==2.0.3 + # via + # -r requirements.in + # aeon +python-dateutil==2.8.2 + # via pandas +pytz==2023.3.post1 + # via pandas +scikit-learn==1.2.2 + # via + # -r requirements.in + # aeon +scipy==1.11.2 + # via + # aeon + # scikit-learn +six==1.16.0 + # via python-dateutil +sympy==1.12 + # via torch +threadpoolctl==3.2.0 + # via scikit-learn +torch==2.0.1 + # via + # -r requirements.in + # triton +triton==2.0.0 + # via torch +typing-extensions==4.7.1 + # via torch +tzdata==2023.3 + # via pandas +wheel==0.41.2 + # via + # nvidia-cublas-cu11 + # nvidia-cuda-cupti-cu11 + # nvidia-cuda-runtime-cu11 + # nvidia-curand-cu11 + # nvidia-cusparse-cu11 + # nvidia-nvtx-cu11 +wrapt==1.15.0 + # via deprecated + +# The following packages are considered to be unsafe in a requirements file: +# setuptools diff --git a/xrocket/setup.py b/xrocket/setup.py new file mode 100644 index 0000000..8de0d68 --- /dev/null +++ b/xrocket/setup.py @@ -0,0 +1,19 @@ +from setuptools import find_packages, setup + +with open("README.md", "r") as fh: + long_description = fh.read() + +setup( + name="xrocket", + version="0.1", + description="explainable rocket implementation", + long_description=long_description, + long_description_content_type="text/markdown", + author="dida Datenschmiede GmbH", + author_email="info@dida.do", + packages=find_packages(), + install_requires=[ + "pytorch" + ], + python_requires=">=3.6", +) diff --git a/xrocket/xrocket/__init__.py b/xrocket/xrocket/__init__.py new file mode 100644 index 0000000..5a107e1 --- /dev/null +++ b/xrocket/xrocket/__init__.py @@ -0,0 +1 @@ +from xrocket.encoder import XRocket \ No newline at end of file diff --git a/xrocket/xrocket/block.py b/xrocket/xrocket/block.py new file mode 100644 index 0000000..27487f4 --- /dev/null +++ b/xrocket/xrocket/block.py @@ -0,0 +1,159 @@ +import torch +from torch import nn +from xrocket.convolutions import RocketConv +from xrocket.multichannel import ChannelMix +from xrocket.pooling import PPVThresholds + +class DilationBlock(nn.Module): + """MiniRocket block for transformation of timeseries at a single dilation value. + + This layer serves to perform the encoding of an input timeseries with a fixed + dilation value. + A DilationBlock consists of the following three sublayers: + - RocketConv + - ChannelMix + - PPVThresholds + A forward pass transforms a tensor of shape (Batch * Channels * Timeobs) + into a tensor of shape (Batch * (Features/Dilation)). + + This implementation is based on the descriptions in: + Dempster, Angus, Daniel F. Schmidt, and Geoffrey I. Webb. + "Minirocket: A very fast (almost) deterministic transform for time series classification." + Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data mining. 2021. + + The block structure deviates from the original paper and sublayers have differences as + explained in the respective implementations. + + Attributes: + in_channels: Number of channels in each timeseries. + dilation: The dilation value to apply to the convolutional kernels. + num_thresholds: The number of thresholds per channel combination. + combination_order: The maximum number of channels to be interacted. + combination_method: The channel mixing method, either 'additive' or 'multiplicative'. + kernel_length: Number of paramters in each kernel, default = 9. + num_kernels: The number of kernels considered in the module. + num_combinations: The number of channel combinations considered in the module. + feature_names: (pattern, dilation, channels, threshold) tuples to identify features. + is_fitted: Indicates that thresholds are fitted to a data example. + """ + + def __init__( + self, + in_channels: int, + dilation: int, + num_thresholds: int = 1, + combination_order: int = 1, + combination_method: str = "additive", + kernel_length: int = 9, + ): + """Set up attributes including quantile values for the layer. + + Args: + in_channels: Number of channels in each timeseries. + dilation: The dilation value to apply to the convolutional kernels. + num_thresholds: The number of thresholds per channel combination. + combination_order: The maximum number of channels to be interacted. + combination_method: Keyword for the channel mixing method, default='additive'. + kernel_length: Number of paramters in each kernel, default = 9. + """ + super().__init__() + + # set up constituent layers + self.conv = RocketConv( + in_channels=in_channels, + dilation=dilation, + kernel_length=kernel_length, + ) + self.mix = ChannelMix( + in_channels=self.conv.out_channels, + in_kernels=self.conv.num_kernels, + order=combination_order, + method=combination_method, + ) + self.thresholds = PPVThresholds( + num_thresholds=num_thresholds, + ) + + def forward(self, x: torch.Tensor) -> torch.Tensor: + """Perform a forward pass to calculate a feature vector. + + Pooling thresholds will be fit to the first example if not yet fitted. + + Args: + x: Tensor of shape (Batch * Channels * Timeobs) + + Returns: + x: Tensor of shape (Batch * (Features/Dilations)) + """ + x = self.conv(x) + x = self.mix(x) + x = self.thresholds(x) + x = torch.flatten(x, start_dim=1) + return x + + @property + def in_channels(self) -> int: + """The number of incoming channels.""" + return self.conv.in_channels + + @property + def dilation(self) -> int: + """The value to dilute the kernels with over the time dimension.""" + return self.conv.dilation + + @property + def combination_order(self) -> int: + """The highest number of channels to combine in a feature.""" + return self.mix.order + + @property + def num_kernels(self) -> int: + """The number of kernels in the convolutional block.""" + return self.conv.num_kernels + + @property + def num_combinations(self) -> int: + """The total number of channel combinations.""" + return self.mix.num_combinations + + @property + def num_thresholds(self) -> int: + """The number of thresholds to apply to each channel combinations.""" + return self.thresholds.num_thresholds + + def fit(self, x: torch.Tensor) -> None: + """Obtain pooling threshold values from an input. + + Accepts either a single example or a batch as an input. + + Args: + x: Tensor of shape (Channels * Timeobs) or + Tensor of shape (Batch * Channels * Timeobs) + """ + x = self.conv(x) + x = self.mix(x) + self.thresholds.fit(x) + + @property + def is_fitted(self) -> bool: + """Indicates if module biases were fitted to data.""" + return self.thresholds.is_fitted + + @property + def feature_names(self) -> list[tuple]: + """(pattern, dilation, channels, threshold) tuples to identify features.""" + assert self.is_fitted, "module needs to be fitted for thresholds to be named" + feature_names = [ + ( + str(pattern), + self.dilation, + str(channels), + f"{threshold:.4f}", + ) + for pattern, channels, threshold in zip( + self.conv.patterns * self.num_combinations * self.num_thresholds, + self.mix.combinations * self.num_thresholds, + self.thresholds.thresholds, + ) + ] + return feature_names diff --git a/xrocket/xrocket/convolutions.py b/xrocket/xrocket/convolutions.py new file mode 100644 index 0000000..8a08f6e --- /dev/null +++ b/xrocket/xrocket/convolutions.py @@ -0,0 +1,132 @@ +import torch +from torch import nn + + +class RocketConv(nn.Module): + """Convolutional layer for ROCKET transformation of timeseries. + + This layer serves to transform an observed input time series into a + set of time series of the same length based on 1D convolutional activations. + I.e., a forward pass transforms a tensor of shape (Batch * Channels * Timeobs) + into a tensor of shape (Batch * Kernels * Channels * Timeobs). + + This implementation mostly conforms to the descriptions in: + Dempster, Angus, Daniel F. Schmidt, and Geoffrey I. Webb. + "Minirocket: A very fast (almost) deterministic transform for time series classification." + Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data mining. 2021. + + In contrast to the paper, all convolutional activations are padded such that they + match the length of the input sequence instead of randomly applying paddings. + + Attributes: + in_channels: The number of channels going into the convolutions. + weight: Tensor of shape (Kernels * 1 * Kernel_length) + dilation: The dilation value used by the layer. + padding: The padding widths corresponding to the dilation. + num_kernels: The number of distinct kernels in the module. + out_channels: The number of ouput channels. + patterns: List of the patterns of the convolutional kernels. + kernel_length: Number of paramters in each kernel. + """ + + def __init__( + self, + in_channels: int, + dilation: int, + kernel_length: int = 9, + alpha: float = -1.0, + beta: float = 2.0, + pad: bool = True, + ) -> None: + """Set up attributes including kernels, dilations, and padding values for the layer. + + Args: + in_channels: Number of channels in each timeseries. + max_kernel_span: Number of time-observations in a typical timeseries. + kernel_length: Number of paramters in each kernel, default = 9. + alpha: Parameter value occuring six times per kernel, default = -1.0. + beta: Paramter value occuring three times per kernel, default = 2.0. + max_dilations: Maximum number of distinct dilation values, default = 32. + pad: Indicates if zero padding should be applied to inputs. + """ + super().__init__() + self.in_channels = in_channels + self.dilation = dilation + self.kernel_length = kernel_length + self.pad = pad + self._initialize_weights(alpha=alpha, beta=beta) + + def _initialize_weights(self, alpha: float, beta: float) -> None: + """Create kernel weights following the scheme in the original paper. + + Kernels with kernel_length=9 are created as combinations of values -1 and 2, + where the value 2 occurs three times in each kernel. + """ + beta_indices = torch.combinations( + torch.arange(self.kernel_length), self.kernel_length // 3 + ).unsqueeze(1) + weights = torch.full( + size=[len(beta_indices), 1, self.kernel_length], fill_value=alpha + ).scatter(2, beta_indices, beta) + self.weight = nn.Parameter(data=weights, requires_grad=False) + + @property + def padding(self) -> int: + """The padding length for the set dilation value. + + If padding is set, padding length is set such that each output sequence + has the same length as the input. + """ + if self.pad: + return ((self.kernel_length - 1) * self.dilation) // 2 + else: + return 0 + + @property + def num_kernels(self) -> int: + """The number of distinct kernels in the module.""" + return len(self.weight) + + def forward(self, x: torch.Tensor) -> torch.Tensor: + """Perform a forward pass to calculate channel-wise convolution actications. + + This step is equivalent to depthwise separable convolutions for each channel. + Outputs are always calculated using zero padding to keep the + Timeobs dimesion constant (This deviates from the original authors). + + Args: + x: Tensor of shape (Batch * Channels * Timeobs) + + Returns: + out: Tensor of shape (Batch * Kernels * Channels * Timeobs) + """ + # repeat kernels for each channel + kernels = self.weight.repeat(self.in_channels, 1, 1) + + # calculate convolution activations + x = nn.functional.conv1d( + x, + kernels, + padding=self.padding, + dilation=self.dilation, + groups=self.in_channels, + ) + x = x.reshape( + x.shape[0], + self.num_kernels, + self.in_channels, + -1, + ) + + return x + + @property + def patterns(self) -> list: + """List of the patterns of the convolutional kernels used to extract features.""" + patterns = self.weight.squeeze().tolist() + return patterns + + @property + def out_channels(self) -> int: + """The number of ouput channels corresponds to the number of input channels.""" + return self.in_channels diff --git a/xrocket/xrocket/encoder.py b/xrocket/xrocket/encoder.py new file mode 100644 index 0000000..ac61b80 --- /dev/null +++ b/xrocket/xrocket/encoder.py @@ -0,0 +1,202 @@ +import math +import torch +from torch import nn +from xrocket.block import DilationBlock + +class XRocket(nn.Module): + """Explainable ROCKET module for timeseries embeddings. + + Serves to encode a (multivariate) timeseries into a fixed-length feature vector. + I.e., a forward pass transforms a tensor of shape (Batch * Channels * Timeobs) + into a tensor of shape (Batch * Features). + The implementation is such that the origin of each feature can be traced. + + This implementation is based on the descriptions in: + Dempster, Angus, Daniel F. Schmidt, and Geoffrey I. Webb. + "Minirocket: A very fast (almost) deterministic transform for time series classification." + Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data mining. 2021. + + The implemented block structure deviates from the original paper but the calculations are + almost identical. Please refer to the sublayer implementations for details. + + Attributes: + in_channels: Number of channels in each timeseries. + max_kernel_span: Number of time-observations in a typical timeseries. + combination_order: The maximum number of channels to be combined. + combination_method: The channel mixing method, either 'additive' or 'multiplicative'. + feature_dims: The number of values in each feature dimension. + num_features: The total number of feature embeddings. + is_fitted: Indicates of the module has been fitted to data. + feature_names: List of feature name tuples (pattern, dilation, channels, threshold). + """ + + def __init__( + self, + in_channels: int, + max_kernel_span: int, + combination_order: int = 1, + combination_method: str = "additive", + feature_cap: int = 10_000, + kernel_length: int = 9, + max_dilations: int = 32, + ): + """Set up attributes for all sub-layers. + + Args: + in_channels: The number of channels in the data. + max_kernel_span: Number of time-observations in a typical timeseries. + combination_order: The maximum number of channels to be interacted. + combination_method: Keyword for the channel mixing method, default='additive'. + feature_cap: Maximum number of features to be considered. + kernel_length: The length of the 1D convolutional kernels. + max_dilations: The maximum number of distinct dilation values. + """ + super().__init__() + self.dilations = self._deduce_dilation_values( + max_kernel_span=max_kernel_span, + kernel_length=kernel_length, + max_dilations=max_dilations, + ) + num_kernels = len( + torch.combinations(torch.arange(kernel_length), kernel_length // 3) + ) + num_combinations = sum( + [ + len(torch.combinations(torch.arange(in_channels), order + 1)) + for order in range(combination_order) + ] + ) + num_mix_channels = self.num_dilations * num_kernels * num_combinations + if feature_cap < num_mix_channels: + raise ValueError( + ( + f"input combinations ({num_mix_channels}) " + f"greater than feature cap ({feature_cap})." + ) + ) + num_thresholds = feature_cap // num_mix_channels + + # set up rocket blocks + self.blocks = nn.ModuleList() + for dilation in self.dilations: + self.blocks.append( + DilationBlock( + in_channels=in_channels, + dilation=dilation, + num_thresholds=num_thresholds, + combination_order=combination_order, + combination_method=combination_method, + ) + ) + + def _deduce_dilation_values( + self, + max_kernel_span: int, + kernel_length: int, + max_dilations: int, + ) -> None: + """Create dilation values following the scheme in the original paper. + + Dilation values are chosen according to the number of observations + with the formula in the paper. + """ + max_exponent = math.log((max_kernel_span - 1) / (kernel_length - 1), 2) + integers = ( + (2 ** torch.linspace(0, max_exponent, max_dilations)).to(dtype=int).tolist() + ) + return list(set(integers)) + + @property + def num_dilations(self) -> int: + """The number of distinct dilation values for each kernel.""" + return len(self.dilations) + + @property + def num_kernels(self) -> int: + """The number of convolutional kernels per dilation.""" + return self.blocks[0].num_kernels + + @property + def num_combinations(self) -> int: + """The number of channel combinations per dilation.""" + return self.blocks[0].num_combinations + + @property + def num_thresholds(self) -> int: + """The number of pooling thresholds per channel combination per dilation.""" + return self.blocks[0].num_thresholds + + @property + def feature_dims(self) -> dict: + """A dictionary with the number of each feature attribute.""" + feature_dims = { + "num_kernels": self.num_kernels, + "num_dilations": self.num_dilations, + "num_combinations": self.num_combinations, + "num_thresholds": self.num_thresholds, + } + return feature_dims + + @property + def num_features(self) -> int: + """The total number of feature encodings used by the layer.""" + num_features = ( + self.num_kernels + * self.num_dilations + * self.num_combinations + * self.num_thresholds + ) + return num_features + + def forward(self, x: torch.Tensor) -> torch.Tensor: + """Perform a forward pass to calculate timeseries feature encodings. + + Args: + x: Tensor of shape (Batch * Channels * Timeobs) + + Returns: + out: Tensor of shape (Batch * Features) + """ + out = torch.cat([block(x) for block in self.blocks], dim=-1) + return out + + def fit(self, x: torch.Tensor) -> None: + """Obtain parameter valies from the first available example. + + Accepts either a single example or a batch as an input. + + Args: + x: Tensor of shape (Channels * Timeobs) or + Tensor of shape (Batch * Channels * Timeobs) + """ + for block in self.blocks: + block.fit(x) + + @property + def is_fitted(self) -> bool: + """Indicates if module biases were fitted to data.""" + return self.blocks[0].is_fitted + + @property + def feature_names(self) -> list: + """(pattern, dilation, channels, threshold) tuples to identify features.""" + assert self.is_fitted, "module needs to be fitted for thresholds to be named" + feature_names = [] + for block in self.blocks: + feature_names += block.feature_names + return feature_names + + @property + def in_channels(self) -> int: + """Number of channels in each timeseries.""" + return self.blocks[0].in_channels + + @property + def combination_order(self) -> int: + """The maximum number of channels to be combined.""" + return self.blocks[0].mix.order + + @property + def device(self) -> torch.device: + """The device the module is loaded on.""" + return next(self.parameters()).device \ No newline at end of file diff --git a/xrocket/xrocket/multichannel.py b/xrocket/xrocket/multichannel.py new file mode 100644 index 0000000..d70233e --- /dev/null +++ b/xrocket/xrocket/multichannel.py @@ -0,0 +1,104 @@ +import torch +from torch import nn + +class ChannelMix(nn.Module): + """Channel mixing layer for ROCKET transformation of timeseries. + + This layer serves to select and interact the input channels to create uni- + and multivariate feature sequences. + I.e., a forward pass transforms a tensor of shape + (Batch * Kernels * Channels * Timeobs) into a tensor of shape + (Batch * Kernels * Combinations * Timeobs). + + This implementation is based on the descriptions in: + Dempster, Angus, Daniel F. Schmidt, and Geoffrey I. Webb. + "Minirocket: A very fast (almost) deterministic transform for time series classification." + Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data mining. 2021. + + In contrast to the paper, all channel combinations will be considered, not only + a randomly selected subset as in the original authors' implementation. + + Attributes: + in_channels: The number of channels in the data. + in_kernels: The number of distinct kernels passed to the module. + order: The maximum number of channels to be interacted. + method: The channel mixing method, either 'additive' or 'multiplicative'. + combinations: List of channel combinations being interacted. + weight: List of parameters for each combination. + num_combinations: The number of channel combinations considered in the module. + """ + + def __init__( + self, + in_channels: int, + in_kernels: int, + order: int = 1, + method: str = "additive", + ) -> None: + """Set up attributes including combinations and combination weights for the layer. + + Args: + in_channels: The number of channels going into the module. + in_kernels: The number of kernel outputs going into the module. + order: The maximum number of channels to be interacted. + method: Keyword to indicate the channel mixing method, default='additive'. + """ + super().__init__() + self.in_channels = in_channels + self.order = order + self.method = method + self._initialize_weights(in_kernels=in_kernels) + + def _initialize_weights(self, in_kernels: int) -> None: + """Set up the channel combinations as weights. + + The created weight tensor will have dimensions + (Kernels * Combinations * Channels). + + Args: + in_kernels: The number of kernel outputs going into the module. + """ + weight = torch.Tensor([]) + for order in range(self.order): + combinations = torch.combinations(torch.arange(self.in_channels), order + 1) + channel_map = torch.zeros(len(combinations), self.in_channels).scatter( + 1, combinations, 1 + ) + weight = torch.cat([weight, channel_map]) + weight = weight.unsqueeze(0).repeat(in_kernels, 1, 1) + self.weight = nn.Parameter(data=weight, requires_grad=False) + + @property + def num_combinations(self) -> int: + """The number of channel combinations to be considered.""" + return self.weight.shape[1] + + def forward(self, x: torch.Tensor) -> torch.Tensor: + """Perform a forward pass to calculate comnbination-wise activations. + + All channel combinations up to the initialized order will be included + (This deviates from the original authors who use only a random selection). + Channel activations can be interacted additively or multiplicatively to + also capture negative correlations (The original authors suggest an + additive implementation, which is the default here and runs faster). + + Args: + x: Tensor of shape (Batch * Kernels * Channels * Timeobs) + + Returns: + out: Tensor of shape (Batch * Kernels * Combinations * Timeobs) + """ + if self.method == "additive": + x = self.weight.matmul(x) + elif self.method == "multiplicative": + x = x[:, :, None, :, :].mul(self.weight[None, :, :, :, None]) + x = x.where(x != 0, torch.ones(1, device=x.device)).prod(dim=-2) + else: + raise ValueError(f"method '{self.method}' not available") + + return x + + @property + def combinations(self) -> list: + """A list of the channel weightings considered.""" + return self.weight.reshape(-1, self.in_channels).tolist() diff --git a/xrocket/xrocket/pooling.py b/xrocket/xrocket/pooling.py new file mode 100644 index 0000000..40634fe --- /dev/null +++ b/xrocket/xrocket/pooling.py @@ -0,0 +1,130 @@ +import math +import warnings +import torch +from torch import nn + +class PPVThresholds(nn.Module): + """Threshold layer for ROCKET transformation of timeseries. + + This layer serves to apply proportion of positive values pooling based on a + set of threshold values from the convolutional outputs. + I.e., a forward pass transforms a tensor of shape + (Batch * Kernels * Combinations * Timeobs) into a tensor of shape + (Batch * Kernels * Combinations * Thresholds). + LAyer needs to be fitted to define the values of the thresholds. + + This implementation conforms to the descriptions in: + Dempster, Angus, Daniel F. Schmidt, and Geoffrey I. Webb. + "Minirocket: A very fast (almost) deterministic transform for time series classification." + Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data mining. 2021. + + Attributes: + num_thresholds: The number of thresholds per channel. + is_fitted: Indicates that thresholds are fitted to a data example. + bias: Tensor of shape (Kernels * Dilations * Combinations * Quantiles) + """ + + def __init__( + self, + num_thresholds: int, + ) -> None: + """Set up attributes including quantile values for the layer. + + Args: + num_thresholds: The number of thresholds to be considered per channel. + """ + super().__init__() + self.num_thresholds = num_thresholds + self.is_fitted: bool = False + + def _select_quantiles( + self, + num_thresholds: int, + uniform: bool = False, + ) -> torch.Tensor: + """Automatically selects the quantile values to initialize threshold values. + + Following the original authors' code, the module uses a "low-discrepancy + sequence to assign quantiles to kernel/dilation combinations", source: + https://github.com/angus924/minirocket/blob/main/code/minirocket_multivariate.py + + Alternatively, quantiles can be choosen to be uniformly spaced in [0, 1]. + + Args: + num_thresholds: The number of thresholds to be considered per channel. + uniform: Indicates if quantiles should be uniformly spaced, default=False. + """ + if uniform: + # uniformly spaced quantiles + quantiles = torch.linspace(0, 1, num_thresholds + 2)[1:-1] + else: + # low-discrepancy sequence to assign quantiles + phi = (math.sqrt(5) + 1) / 2 + quantiles = torch.Tensor( + [((i + 1) * phi) % 1 for i in range(num_thresholds)] + ) + + return quantiles + + def fit(self, x: torch.Tensor, quantiles: list = None) -> None: + """Obtain quantile values from the first available example to use as thresholds. + + Accepts either a single example or a batch as an input. + + Args: + x: Tensor of shape (Batch * Kernels * Combinations * Timeobs) + quantiles (optional): A list of values between 0 and 1 to indicate the quantiles + at which to set the thresholds. + """ + # get quantiles + if quantiles is None: + quantiles = self._select_quantiles( + num_thresholds=self.num_thresholds, uniform=False + ) + else: + if type(quantiles) != list or not all(0 <= q <= 1 for q in quantiles): + raise ValueError( + "quantiles needs to be a list of values between 0 and 1" + ) + + # flatten if input is a batch + if len(x.shape) == 4: + x = x.movedim(0, -1).flatten(start_dim=-2) + + # extract threshold values from activation quantiles + thresholds = x.quantile(q=quantiles.to(x.device), dim=-1).movedim( + source=0, destination=-1 + ) + + # set attributes + self.bias = nn.Parameter(data=thresholds, requires_grad=False) + self.is_fitted = True + + def forward(self, x: torch.Tensor) -> torch.Tensor: + """Perform a forward pass to calculate pooled features. + + Module weights will be fit to the first example if not yet fitted. + + Args: + x: Tensor of shape (Batch * Kernels * Combinations * Timeobs) + + Returns: + out: Tensor of shape (Batch * Kernels * Combinations * Thresholds) + """ + # fit if module is not yet fitted + if not self.is_fitted: + self.fit(x) + warnings.warn("automatically fit biases to first training example") + + # add missing dims + thresholds = self.bias.unsqueeze(-1) + x = x.unsqueeze(-2) + + # apply percentage of values pooling with thresholds + x = x.gt(thresholds).sum(dim=-1).div(x.size(-1)) + return x + + @property + def thresholds(self) -> list: + """A list of the threshold values considered.""" + return self.bias.flatten().tolist()