API文档

pyts Python软件包的完整API文档。

: 近似算法

pyts.approximation 模块包含近似算法。

approximation.DiscreteFourierTransform([…])	Discrete Fourier Transform.
approximation.MultipleCoefficientBinning([…])	Bin continuous data into intervals column-wise.
approximation.PiecewiseAggregateApproximation([…])	Piecewise Aggregate Approximation.
approximation.SymbolicAggregateApproximation([…])	Symbolic Aggregate approXimation.
approximation.SymbolicFourierApproximation([…])	Symbolic Fourier Approximation.

: 词袋算法

pyts.bag_of_words 模块包含词袋算法。

bag_of_words.BagOfWords([window_size, …])	Bag-of-words representation for time series.
bag_of_words.WordExtractor([window_size, …])	Transform discretized time series into sequences of words.

: 分类算法

pyts.classification 模块包含分类算法。

classification.BOSSVS([word_size, n_bins, …])	Bag-of-SFA Symbols in Vector Space.
classification.KNeighborsClassifier([…])	k-nearest neighbors classifier.
classification.LearningShapelets([…])	Learning Shapelets algorithm.
classification.SAXVSM([window_size, …])	Classifier based on SAX-VSM representation and tf-idf statistics.
classification.TimeSeriesForest([…])	A random forest classifier for time series.
classification.TSBF([n_estimators, …])	Time Series Bag-of-Features algorithm.

: 数据集加载工具

pyts.datasets 模块提供了创建、加载和获取时间序列数据集的工具。

datasets.fetch_ucr_dataset(dataset[, …])	Fetch dataset from UCR TSC Archive by name.
datasets.fetch_uea_dataset(dataset[, …])	Fetch dataset from UEA TSC Archive by name.
datasets.load_basic_motions([return_X_y])	Load and return the Basic Motions dataset.
datasets.load_coffee([return_X_y])	Load and return the Coffee dataset.
datasets.load_gunpoint([return_X_y])	Load and return the GunPoint dataset.
datasets.load_pig_central_venous_pressure([…])	Load and return the PigCVP dataset.
datasets.make_cylinder_bell_funnel([…])	Make a Cylinder-Bell-Funnel dataset.
datasets.ucr_dataset_info([dataset])	Information about the UCR datasets.
datasets.ucr_dataset_list()	List of available UCR datasets.
datasets.uea_dataset_info([dataset])	Information about the UEA datasets.
datasets.uea_dataset_list()	List of available UEA datasets.

: 分解算法

pyts.decomposition 模块包含分解算法。

decomposition.SingularSpectrumAnalysis([…])

Singular Spectrum Analysis.

: 图像处理算法

pyts.image 模块包含将时间序列转换为图像的算法。

image.GramianAngularField([image_size, …])	Gramian Angular Field.
image.MarkovTransitionField([image_size, …])	Markov Transition Field.
image.RecurrencePlot([dimension, …])	Recurrence Plot.

: 指标

pyts.metrics 模块包含各种度量指标。

metrics.boss(x, y)	Return the BOSS distance between two arrays.
metrics.dtw([x, y, dist, method, options, …])	Dynamic Time Warping (DTW) distance between two samples.
metrics.itakura_parallelogram(n_timestamps_1)	Compute the Itakura parallelogram.
metrics.sakoe_chiba_band(n_timestamps_1[, …])	Compute the Sakoe-Chiba band.
metrics.show_options([method, disp])	Show documentation for additional options of Dynamic Time Warping methods.

: 多元时间序列工具

pyts.multivariate 模块包含处理多元时间序列的工具。

分类

multivariate.classification.MultivariateClassifier(…)

Classifier for multivariate time series.

图像

multivariate.image.JointRecurrencePlot([…])

Joint Recurrence Plot.

转换

multivariate.transformation.MultivariateTransformer(…)	Transformer for multivariate time series.
multivariate.transformation.WEASELMUSE([…])	WEASEL+MUSE algorithm.

实用工具

multivariate.utils.check_3d_array(X)

Check that the input is a three-dimensional array.

: 预处理工具

pyts.preprocessing 模块包含预处理算法。

扩展性

preprocessing.MaxAbsScaler()	Scale each sample by its maximum absolute value.
preprocessing.MinMaxScaler([sample_range])	Transforms samples by scaling each sample to a given range.
preprocessing.RobustScaler([with_centering, …])	Scale samples using statistics that are robust to outliers.
preprocessing.StandardScaler([with_mean, …])	Standardize time series by removing mean and scaling to unit variance.

转换

preprocessing.PowerTransformer([method, …])	Apply a power transform sample-wise to make data more Gaussian-like.
preprocessing.QuantileTransformer([…])	Transform samples using quantiles information.

离散化

preprocessing.KBinsDiscretizer([n_bins, …])

Bin continuous data into intervals sample-wise.

缺失值填补

preprocessing.InterpolationImputer([…])

Impute missing values using interpolation.

: 转换算法

pyts.transformation 模块包含转换算法。

transformation.BagOfPatterns([window_size, …])	Bag-of-patterns representation for time series.
transformation.BOSS([word_size, n_bins, …])	Bag of Symbolic Fourier Approximation Symbols.
transformation.ROCKET([n_kernels, …])	RandOm Convolutional KErnel Transformation.
transformation.ShapeletTransform([…])	Shapelet Transform Algorithm.
transformation.WEASEL([word_size, n_bins, …])	Word ExtrAction for time SEries cLassification.

: 实用工具

pyts.utils 模块包含实用工具。

utils.segmentation(ts_size, window_size[, …])	Compute the indices for Piecewise Agrgegate Approximation.
utils.windowed_view(X, window_size[, …])	Return a windowed view of a 2D array.