Adaptive Synchronization with Hebbian Learning and Elasticity

Setup python enviroment

(1) Create an ASHLE python virtual enviroment

python -m venv ashlenv

(2) Start the ASHLE virtual enviroment

source /path/to/ahslenv/bin/activate

(3) Setup the ASHLE virtual enviroment

python3 setup.py install

Execute experiments from the paper:

python1 exp<experiment_number>.py

where <experiment_number> = [1, 2, 3]

Experiment 1 (exp1.py)

Simulation of the MA between a musician’s beat and a metronome beat with a period shorter or longer than the musician’s SMP during solo musical performance.

Note: generates Figure 2 A,B,C from the article.

Experiment 2 (exp2.py)

Simulation of the slope between consecutive IBIs when an unpaced musician performs a melody starting at a tempo that is different than the SMT.

Note: generates Figure 3 A,B,C from the article.

Experiment 3 (exp3.py)

Simulation of the mean absolute asynchrony between two musicians with matching or mismatching SMTs during duet musical performance.

Note: generates Figure 4 A,B,C from the article.

Table to generate all figures from the article

Figure No.	Script to execute	File name
Figure 1	N/A	/figures_raw/fig1(.eps/.png)
Figure 2	/exp1/exp1.py	/figures_raw/fig2(.eps/.png)
Figure 3	/exp2/exp2.py	/figures_raw/fig3(.eps/.png)
Figure 4	/exp3/exp3.py	/figures_raw/fig4(.eps/.png)
Figure 5	/exp3/exp3.py	/figures_raw/fig5(.eps/.png)
Figure 6	/param_analysis/asynch_lims.py	/figures_raw/fig6(.eps/.png)
Figure 7	/param_analysis/asynch_detail.py	/figures_raw/fig7(.eps/.png)
Figure 8	/param_analysis/slope.py	/figures_raw/fig8(.eps/.png)