on Monday, November 6th, 2017 1:37 | by Christian Rohrsen
I have analyzed the c105+c232 > tnt data from Sathish. There are a total of 43 flies, although many of them only flew for a few minutes, and therefore should be discarded. Below all of the individual fly scores. I need to analyse now the other groups. This is btw the modified data set, whatever that means for Sathish.
This is a video of the projection from the torque data from Maye et al. 2007. The spikes are not that well sorted in this case as in the Strokelitude. I guess this is because the spikes do not look so smooth.
on Monday, October 30th, 2017 1:32 | by Axel Gorostiza
Here I used the CaLexA tool with the elav driver, and reared the flies on constant darkness or under L-D cycles.
on | by Christian Rohrsen
This is an example of a recurrence plot analysis. In the first graph is shown in single point in time in the optimal embedding dimension and the distance to the other points. For the recurrence plot analysis it is needed to put a threshold to make it binary. This is the second graph. From this second graph one can count many parameters like determinism, laminarity and so on. From what I see, the plots from the Strokelitude as well as Bjoern´s flight simulator in Maye et al 2007 show similar pattern (kind of crosses with vertical and horizontal lines).
This is a measure of the Recurrence Quantitative Analysis of different groups. Recurrence threshold is a tricky and to some extent subjective measure, so this is why I tried two different ones.
DET: recurrence points that form a diagonal line of minimal length, the more diagonal, the more deterministic.
LMAX: Max diagonal line length or divergence. Sometimes considered as an estimator of max. Lyapunov exponent
ENT: Shannon entropy reflects the complexity of the system
TND: info about stationarity (trend)
LAM: Laminarity is related to laminar phases in the system (intermittency). It is tallied as vertical lines over a threshold.
TT: Trapping time, measuring the average length of vertical lines. Related to laminarity.
on Monday, October 16th, 2017 2:26 | by Christian Rohrsen
Video of the attractor projected from a chunk of flight trace. Here one can see the difference in the trajectories of up- and down spikes. So here is another way of spike sorting by the way :).
Coloured traces depending where the locate in the attractor projection. Green means that they lie outside and when they stay with the PCs around zero its in red. The fly1r above does not look so clean as the v8 fly below (the cleanest measure I have)
Here I tested two common OA drivers in photopreference. Although the results are not conclusive, there could be something there.
on Monday, October 9th, 2017 2:34 | by Christian Rohrsen
These are the results of the SMAP for the TNTxWTB. I also have done a few for the c105;;c232xWTB but there is not much to say. I would say that the cleanest lines show a bigger slope, but prone to subjectiveness.
on Monday, October 2nd, 2017 5:35 | by Christian Rohrsen
This is what I showed about one fly from this line showing the attractor.
This graph is what I forgot to show in the lab meeting. There are the 6 best traces from this same line. All of them selected ad hoc subjectively. The three best of them to my eyes are exactly the three above in the graph (v8-this one is the one shown in the picture with the attractors-,v4,v2). What does this means? the ones with better traces (subjectively) have higher offset in the phi, this means that they are more predictable overall (maybe because more resolution?). In addition, they show higher slopes which means more nonlinearity.
This is a new try to set up the CaLexA technique.
TH-CaLexA L-D 12:12 Without Wings