newanalysis.correl.correlateParallel

newanalysis.correl.correlateParallel(data1, data2, out, ltc=0)

Takes two data sets and calculates column-wise correlation functions in parallel and sums them up afterwards. The result is written into the out array.

Parameters:

• data1 – numpy array, float64, ndim=2

• data2 – numpy array, float64, ndim=2

• out – numpy array, float64, ndim=1

• ltc – type of long tail correction used 0 = none (default) 1 = the average of the time series is subtracted from it before the correlation 2 = the result is modified

Example:

dipole autocorrelation function correlateParallel(dipoles, dipoles, mu0mut)

Note

for this to work, the data arrays have to be organised as follows:

	x1	y1	z1	x2	y2	z2	…	xn	yn	zn
t1
t2
.
.
.
tm

Each column is the x/y/z component of each particle, each row is a time step.