I'm using PyWavelets for singularity detection in a time series of measured values.
The values were taken with a sample time of 10 ms and the length of each data set is 2048 values.
Along with the data set, I have an array with the time stamps for each measured value.
I did
wavelet_name = "bior5.5"
w = pywt.Wavelet(wavelet_name)
maxlev = pywt.dwt_max_level(len(pressure_values), w.dec_len)
coeffs = pywt.wavedec(pressure_values, wavelet_name, level=maxlev)
That leads to coeffs with the following lengths per scale:
scale 1 length = 26
scale 2 length = 42
scale 3 length = 74
scale 4 length = 138
scale 5 length = 265
scale 6 length = 520
scale 7 length = 1029
I can now find the singularities in the coefficients that appear over multiple scales, but I need to properly link these to a time stamp.
How can this be done properly?
I'm also confused, because I expected that the length of e.g. scale 7 would be 1024 after the downsampling in the decomposition process. With that length it would have been clear which coefficient maps to which time stamp.
Any hint is appreciated!