Library "FunctionDynamicTimeWarping" "In time series analysis, dynamic time warping (DTW) is an algorithm for measuring similarity between two temporal sequences, which may vary in speed. For instance, similarities in walking could be detected using DTW, even if one person was walking faster than the other, or if there were accelerations and decelerations during the course of an observation. DTW has been applied to temporal sequences of video, audio, and graphics data — indeed, any data that can be turned into a linear sequence can be analyzed with DTW. A well-known application has been automatic speech recognition, to cope with different speaking speeds. Other applications include speaker recognition and online signature recognition. It can also be used in partial shape matching applications." "Dynamic time warping is used in finance and econometrics to assess the quality of the prediction versus real-world data." ~~ wikipedia reference: en.wikipedia.org/wiki/Dynamic_time_warping towardsdatascience.com/dynamic-time-warping-3933f25fcdd github.com/shunsukeaihara/pydtw/blob/master/pydtw/dtw.pyx
cost_matrix(a, b, w) Dynamic Time Warping procedure. Parameters: a: array<float>, data series. b: array<float>, data series. w: int , minimum window size. Returns: matrix<float> optimum match matrix.
traceback(M) perform a backtrace on the cost matrix and retrieve optimal paths and cost between arrays. Parameters: M: matrix<float>, cost matrix. Returns: tuple: array<int> aligned 1st array of indices. array<int> aligned 2nd array of indices. float final cost. reference: github.com/shunsukeaihara/pydtw/blob/master/pydtw/dtw.pyx
report(a, b, w) report ordered arrays, cost and cost matrix. Parameters: a: array<float>, data series. b: array<float>, data series. w: int , minimum window size. Returns: string report.
Just tested out the DTW, was already working with auto-correlation (also interested in cross correlation) so this is a helpful addition to that sort of analysis... thanks... curious if yk anyplace that describes how best to read/interpret the 'report' or 'scoring' ... closer to infinity == bad? anyway ill google and check.. appreciate this one