Summary of results of master thesis

on Monday, December 11th, 2017 12:35 | by

Self-learning of Rover/sitter from flight simulator

Long-term memroy from self-learning

 

Self-learning training/tests from transgeneic flies

Print Friendly, PDF & Email

Chrimson/Gr28bd lines tests in yellow light (580nm)

on Monday, December 4th, 2017 2:17 | by

 

Print Friendly, PDF & Email

Better analysis of slope dependence on flight length and further insights in the SMAP code

This is another way of showing how the slope of the SMAP analysis varies with length. I have choped the time series in 4 chunks and saw what was the slope for the chunks and for the whole time series. I think this is the best statistical way of doing it, it should not depend on what line was tested. I cannot see any effect.

 

Here below is just to show what I found out in the code. What I thought that theta was controlling for nonlinearity in the model, for me it seems rather a control for under- overfitting in the model. So I might need to read the paper and see what do they say, and if it is the same as what I found out in the code.

 

Print Friendly, PDF & Email

Do not agree with Sathish?

on Monday, November 27th, 2017 2:43 | by

So this is the final graph assuming that 20Hz is the sampling rate. Sathish was not sure what it was and he said he will check.

 

 

 

To have a better overview how the length of the flight compares with the slope obtained from the SMAP. There is no big correlation whatsoever with around 100 flies. Sathish found this in his thesis with data from seventy something WTB, but to me it seems like an anecdotal result.

Here the same as above, just for showing the fit line.

Print Friendly, PDF & Email

new TrpA/chrimson self-learning tests

on | by

NorpA; Chrimson/Gr28 (N=12, ATR)

NorpA; Chrimson/Gr28 (N012, No ATR)

NorpA;Chrimson/+ (N=11, ATR)

 

Print Friendly, PDF & Email

Thornlabs spectrometer working!

on Monday, November 20th, 2017 2:59 | by

After getting a new spectrometer, we confirmed that the first one was faulty. Comparison of old (1st and 3rd measures) and new (2nd and 4th) spectrometer. Now much more sensitive and the right spectrum measured for the green LED present in the spectrometer itself and for the light comming out of the light guide coupled with the red LED (whose spectrum does not seem to change after travelling through the light guide)

 

Print Friendly, PDF & Email

All sathish data analysis

This are the results of all of the flies analyzed from Sathish. I just need to know the frequency of the acquisition to exclude the ones that are below 6 minutes.

 

 

 

Print Friendly, PDF & Email

Sathish data

on Monday, November 6th, 2017 1:37 | by

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.

Print Friendly, PDF & Email

Testing CaLexA

on Monday, October 30th, 2017 1:32 | by

Here I used the CaLexA tool with the elav driver, and reared the flies on constant darkness or under L-D cycles.

L-D Cycle

D-D

Print Friendly, PDF & Email

Recurrence quantitative analysis

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.

 

Automat

 

One stripe

Openloop

Uniform

Print Friendly, PDF & Email