In python, I have the one 1-D array coef defined as follows:
coef = np.ones(frame_num-1)
for i in range(1,frame_num):
coef[i-1] = np.corrcoef(data[:,i],data[:,i-1])[0,1]
np.savetxt('serial_corr_results/coef_rest.txt', coef)
Now I want to do autocorrelation on it, and for that I use the code posted by deltap in another post:
timeseries = (coef)
#mean = np.mean(timeseries)
timeseries -= np.mean(timeseries)
autocorr_f = np.correlate(timeseries, timeseries, mode='full')
temp = autocorr_f[autocorr_f.size/2:]/autocorr_f[autocorr_f.size/2]
The autocorrelation works fine, however, when I want to now plot or work with the original coef, the values have changed to that of timeseries -= np.mean(timeseries).
Why does the original array coef get changed here and how can I prevent it from being altered? I need it further down in my script for some other operations.
Also, what exactly is the operation -= doing? I have tried to google that, but haven't found it. Thanks!
NumPy arrays are mutable, e.g.
timeseries = coef # timeseries and coef point to same data
timeseries[:] = 0
will set both timeseries and coef to zero.
If you do
timeseries = coef.copy() # timeseries is a copy of coef with its own data
timeseries[:] = 0
instead, coef will remain untouched.