@@ -18,7 +18,8 @@ powdist.m defines a function which briefly analyses a light curve to search for
It plots the light curve together with a simple Leahy-normalized power spectrum (PS) of the data and the same PS rebinned onto a quasi-logarithmic grid. Then, assuming that the observation is mostly composed of Poissonian noise modified by crosstalk, it generates the expected distribution in three different crosstalk models, and plots the counts-per-bin distribution both in the data and the models.
By checking that the high-frequency PSs are flat (i.e., the noise tends to white noise), and that the alignment between at least one of the models and the data count distribution is good, users can safely just renormalize the powers in their PSs then by dividing them by half the average power at high frequencies.
The function takes five arguments as input (NyqFreq,LC,Binned,PSname,Noisename) and returns three (extrVoverE,CrossTalkProb,HalfMeanPow). \
The function takes five arguments as input (NyqFreq,LC,Binned,PSname,Noisename) and returns three (extrVoverE,CrossTalkProb,HalfMeanPow).
#### Input arguments:
-`NyqFreq` is the Nyquist frequency in Hz
-`LC` (light curve) is the vector of either binned counts, or photon times of arrival (ToAs)
