  This study aims to extract and characterize structures in fully developed
pipe flow at a friction Reynolds number of $\text{Re}_\tau = 12\,400$. To do
so, we employ data-driven wavelet decomposition (DDWD) [D.~Floryan and
M.~D.~Graham, PNAS 118, e2021299118 (2021)], a method that combines features of
proper orthogonal decomposition and wavelet analysis in order to extract
energetic and spatially localized structures from data. We apply DDWD to
streamwise velocity signals measured separately via a thermal anemometer at 40
wall-normal positions. The resulting localized velocity structures, which we
interpret as being reflective of underlying eddies, are self-similar across
streamwise extents of 40 wall units to one pipe radius, and across wall-normal
positions from $y^+=350$ to $y/R=1$. Notably, the structures are similar in
shape to Meyer wavelets. Projections of the data onto the DDWD wavelet
subspaces are found to be self-similar as well, but in Fourier space; the
bounds of self-similarity are the same as before, except streamwise
self-similarity starts at a larger length scale of $450$ wall units. The
evidence of self-similarity provided in this study lends further support to
Townsend's attached eddy hypothesis, although we note that the self-similar
structures are detected beyond the log layer and extend to large length scales.
