Fast dtw implementation with matrix operations Dynamic Time Warping of two sequences, accelerated with matrix operations instead of sequential vector operations Faster than: dtw, fastdtw package (loops through iterations without matrix operations)
Parameters
----------
x: numpy.ndarray
x.ndim == 1 or 2
y: numpy.ndarray
y.ndim == 1 or 2 (consistent with x)
dist: function
function which measures distance between frames from x and y
if (ndim == 1)
function should compare entry to entry(x[i], y[j]), and return single entry
if (ndim == 2)
function should compare vector to whole matrix(x[i], y), and return single vector
it compares single vector frame from x to all vector frames in y.
ex) x.shape == (T1, 10)
y.shape == (T2, 10)
dist(x[i], y) ===> How dist is used
dist(x[i], y).shape == (T2,)
warp: maximum warp amount when finding path
(Not Supported Yet)
w: window size when computing cost matrix
(Not Supported Yet)
Returns
-------
distance: minimum sum of distance across all frames
path: DTW path of x, y in list form