Figure 2 Panel A
The corresponding data plotted in the paper are in the file "DataFig2PanelA.txt".
The experimental data from Mruetusatorm et al. are in the file "DataFig2PanelA_expt.txt"
To reproduce each data point, we can use the included software called "DIBS_computation.py". 
To run this program, we need python, packages numpy, matplotlib, scipy, __future__ and math.
To run the code, please:
1. Open the file "DIBs_computation.py" and fill the simulation parameters at the end of the file (the description of the parameters is more detailed above in the code).
2. Type the following in the linux command line (or equivalent for windows): "python DIBs_computation.py".

Figure 2 Panel B
The corresponding data plotted in the paper are in the file "DataFig2PanelB.txt".
No experimental data are necessary. 
The procedure is the same as the one for Figure 2 Panel A.

Figure 2 Panel E
The corresponding data plotted in the paper are in the file "DataFig2PanelE.txt".
The experimental data from Mruetusatorm et al. are in the file "DataFig2PanelE_expt.txt"
The procedure is the same as the one for Figure 2 Panel A (you just need to change the parameters to their new correct values).

Figure 2 Panel F
The corresponding data plotted in the paper are in the file "DataFig2PanelF.txt".
No experimental data are necessary. 
The procedure is the same as the one for Figure 2 Panel A.

Figure 3
ALl points of the phase diagram are computed by using the code phase_diagram_computation.py in which a loop do all simulations for any value of beta_des.
To run this program, we need python, packages numpy, matplotlib, scipy, __future__ and math.
The code is launched with the command line in the terminal python phase_diagram_computation.py
Each run will produce three output files (names can be modified): beta_des_m.txt,  beta_des_b.txt,  regime.txt. The first one is the 2D array of beta_des for the monolayer for any point of the phase diagram, the second one gathers all beta_des values for the bilayer for any point of the phase diagram, the third one is an array of integers, each one is labelling a particular regime of DIB behaviour. The list of different integers/regimes is explained in the .py file.
The plot can be reproduced by running phase_diagram_trace.py.
To run this program, the requirements are the same as the ones to run phase_diagram_computation.py.

Figure 4
Each point on the stability diagram is individually generated by running stability_computation.py. 
To run this program, we need python, packages numpy, matplotlib, scipy, __future__, math, random and sys.
The code is launched with the command line in the terminal python stability_computation.py <i> <j>
(<i> is an index which sets the outside osmolarity [and thereby the equilibrium radius of droplets R*], <j> sets the ratio between the bilayer radius and the droplet radius [and thereby the equilibrium polar angle of droplets].)
The arrays which <i> and <j> index can be found are on lines 769 (reversed on 772) and 751 of the code respectively. The conversion to R* and polar angles are on line 784 and 788.
Each run will produce four output files: EU_tuples<i>_<j>.txt,  SG_tuples<i>_<j>.txt,  MB_tuples<i>_<j>.txt,  AD_tuples<i>_<j>.txt. Only EU_tuples is needed to generate the stability diagram. These files contain a lot of zeroes, but only the first three numbers are important.
In EU_tuples these number are: number of times the system was stable, number of times the system expanded, number of times the system unzipped.
In SG_tuples these numbers are: number of times the system was stable, number of times the system increased in volume, number of times the system decreased in volume.
In MB_tuples these numbers are: 0, number of times the was a net flow of surfactant from the monolayers to the bilayers, number of times there was a net flow of surfactant from the bilayer to the monolayers.
In AD_tuples these numbers are: 0, the number of time there was a net absorption of surfactant onto the monolayers from the bath, number of times there was a net desorption of surfactant from the monolayers into the bath.
The sorted output for the stability diagram is provided in DataFig4.txt. This contains the full data plotted in Fig. 4. 
The plot can be reproduced by running stability_trace.py.
To run this program, the requirements are the same as the ones to run stability_computation.py

