myimagelib.corrLib.corrS

myimagelib.corrLib.corrS(X, Y, U, V)

Compute the spatial autocorrelations of a velocity field.

Parameters:

X,Y,U,V (2d arrays) – the result of PIV analysis. Each is a 2D array. Use pivLib.read_piv() to construct thses arrays from PIV data files.

Returns:

x, y, CA, CV – The angle autocorrelation (CA) and velocity autocorrelation (CV). x, y are the associated distances.

Note

We only consider half of the length in each dimension, so x, y are different from the input X, Y.

>>> from myimagelib.corrLib import corrS
>>> X, Y, CA, CV = corrS(x, y, u, v)

Edit

  • Dec 13, 2021 – i) Replace all the mean() function to nanmean, to handle masked PIV data. ii) Add doc string.

  • Dec 15, 2021 – if norm vsqrt==0, set it to np.nan to avoid divided by zero warning!

  • Dec 16, 2021 – Shift the output X, Y origin to 0, 0, so that 0 distance will have the correlation function = 1. More intuitive.

  • Jan 05, 2023 – Adapt myimagelib import style.