Pysr
a pure-python symbolic regression library built on deap
Install / Use
/learn @usnistgov/PysrREADME
pysr
a pure-python symbolic regression library built on deap
Installation
We use conda, and so should you.
- Create new environment with:
conda env create -n ENVIRONMENT_NAME -f environment.ymlwhereENVIRONMENT_NAMEis the name you want for your new environment - Activate with
source activate ENVIRONMENT_NAMEon linux/OSX oractivate ENVIRONENT_NAMEon windows - Deactivate with
source deactivate
Usage
python -m scoop pysr.py csvfile numgens popsize
The first n+1 columns of the CSV are x_0 through x_n. The last column is y.
Recommended parameters
I use popsize=500 and numgens very large so I can just kill it with C-c.
Pickling
After every generation, the current population is pickled to a file called pickle. To restart from a picklefile, just run pysr.py in the same directory as pickle. To restart from the beginning, delete or move pickle.
Plotting
Just run with numgens and popsize equal to 0 to plot out the current best fit.
