Returns the percentage of values that are present in the time series more than once. Percentage_of_reoccurring_values_to_all_values(x) Returns the percentage of non-unique data points. Percentage_of_reoccurring_datapoints_to_all_datapoints(x) Returns the mean value of a central approximation of the second derivativeĬalculates the lowest value of the time series x.Ĭalculates the number of crossings of x on m.Ĭalculates the number of peaks of at least support n in the time series x.Ĭalculates the value of the partial autocorrelation function at the given lag. Largest fixed point of dynamics :math:argmax_x ` estimated from polynomial ,Ĭalculates the highest value of the time series x.Ĭalculates the arithmetic mean of the n absolute maximum values of the time series.
#Absolute max and min calculator plus#
Returns the length of the longest consecutive subsequence in x that is smaller than the mean of xĬalculates the 1-D Matrix Profile and returns Tukey’s Five Number Set plus the mean of that Matrix Profile. Returns the length of the longest consecutive subsequence in x that is bigger than the mean of x Returns the last location of the minimal value of x.Ĭalculate a complexity estimate based on the Lempel-Ziv compression algorithm.Ĭalculate a linear least-squares regression for the values of the time series versus the sequence from 0 to length of the time series minus one. Returns the relative last location of the maximum value of x. Returns the kurtosis of x (calculated with the adjusted Fisher-Pearson standardized moment coefficient G2).ĭoes time series have large standard deviation? Returns the first location of the minimal value of x.Ĭalculate the binned entropy of the power spectral density of the time series (using the welch method).Ĭoefficients of polynomial, which has been fitted toĬhecks if any value in x occurs more than onceĬhecks if the maximum value of x is observed more than onceĬhecks if the minimal value of x is observed more than onceĬalculates the relative index i of time series x where q% of the mass of x lies left of i. Returns the first location of the maximum value of x. Returns the spectral centroid (mean), variance, skew, and kurtosis of the absolute fourier transform spectrum.Ĭalculates the fourier coefficients of the one-dimensional discrete Fourier Transform for real input by fast Returns the number of values in x that are lower than the mean of xĬalculates a Continuous wavelet transform for the Ricker wavelet, also known as the “Mexican hat wavelet” which isĬalculates the sum of squares of chunk i out of N chunks expressed as a ratio with the sum of squares over the whole series.
Returns the percentage of values in x that are lower than t Returns the number of values in x that are higher than the mean of x Returns the percentage of values in x that are higher than t This function calculator is an estimate for a time series complexity (A more complex time series has more peaks, valleys etc.). Uses c3 statistics to measure non linearity in the time seriesĬhange_quantiles(x, ql, qh, isabs, f_agg)įirst fixes a corridor given by the quantiles ql and qh of the distribution of x. įirst bins the values of x into max_bins equidistant bins. Useful for anomaly detection applications. This feature calculator fits the unconditional maximum likelihood of an autoregressive AR(k) process.Ĭalculates the autocorrelation of the specified lag, according to the formula Implements a vectorized Approximate entropy algorithm.
Returns the sum over the absolute value of consecutive changes in the series xĭescriptive statistics on the autocorrelation of the time series.Ĭalculates a linear least-squares regression for values of the time series that were aggregated over chunks versus the sequence from 0 up to the number of chunks minus one. Returns the absolute energy of the time series which is the sum over the squared valuesĬalculates the highest absolute value of the time series x. The following list contains all the feature calculations supported in the current version of tsfresh: abs_energy(x) This module contains the feature calculators that take time series as input and calculate the values of the feature. All feature calculators are contained in the submodule: tsfresh.feature_extraction.feature_calculators Tsfresh calculates a comprehensive number of features.
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