acf¶
-
libra_py.acf.acf_mat(data, dt, opt=0)[source]¶ Compute the autocorrelation function of the given data set
- Parameters
data (list of MATRIX(ndof, 1) objects) – sequence of real-valued ndof-dimensional vectors
dt (double) – time distance between the adjacent data points [units: general]
opt (int) –
selector of the convention to to compute ACF
0 : the chemist convention, (1/(N-h)) Sum_{t=1,N-h} (Y[t]*Y[t+h])
1 : the statistician convention, (1/N) Sum_{t=1,N-h} (Y[t]*Y[t+h])
- Returns
(T, nautocorr, autocorr), where:
T (list of sz doubles ): lag time scale for the ACF [units: same as for dt] nautocorr (list of sz doubles ): normalized ACF autocorr (list of sz doubles ): un-normalized ACF
- Return type
-
libra_py.acf.acf_vec(data, dt, opt=0)[source]¶ Compute the autocorrelation function of the given data set
- Parameters
data (list of VECTOR objects) – sequence of real-valued 3-dimensional vectors
dt (double) – time distance between the adjacent data points [units: general]
opt (int) –
selector of the convention to to compute ACF
0 : the chemist convention, (1/(N-h)) Sum_{t=1,N-h} (Y[t]*Y[t+h])
1 : the statistician convention, (1/N) Sum_{t=1,N-h} (Y[t]*Y[t+h])
- Returns
(T, nautocorr, autocorr), where:
T (list of sz doubles ): lag time scale for the ACF [units: same as for dt] nautocorr (list of sz doubles ): normalized ACF autocorr (list of sz doubles ): un-normalized ACF
- Return type