Folder fig3 contains:
- the python script fig3.ipynb which produces figure 3a. 
- the text file traj_figure3.dat with the trajectories for gamma = 0.99, i=320, i'=100, seed = 1, lambda =30. The 7 columns correspond to: time, entropy, crosswind coordinate, downwind coordinate, action id (0 to 6 as described in the text) and observation id (0 to 1, i.e. detection or non detection).
OK

Folder fig4 contains:
- the python script fig4.ipynb, which produces figure 4a,4c (it requires prior installation of the standard package seaborn)
- four text files: close.txt, far.txt, cast.txt, surge.txt which contain the individual entries for the rate of sniffing along individual trajectories. The script bins these data to produce the 4 histograms in figure 4a, 4c.

Folder fig5 contains: 
- a python script fig5.ipynb which produces figure 5. 
- 2 subfolders named nose and ground, with the matlab file statistics.mat containing variables stat_thr_t_3e6 containing the likelihood of detection in the two dimensional plane at ground level and nose level at the threshold described in the text. These rate maps are plotted in Supplementary figure 3. 

Folder fig6 contains:
- a matlab script fig6.m which produces figure 6g
- a matlab file f6.mat with the average time spent in the patch for different seeds (15 for the full POMDP and 6 for the simplified POMDP). these data are read by the script and produce the aggregate statistics in figure 6g 