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View Code? Open in Web Editor NEWA genetic algorithm to optimise the SOAP descriptor
A genetic algorithm to optimise the SOAP descriptor
Hi all
I am just trying out the code using the input.py, database and xyz in the "EXAMPLES" directory. When running it I get these printed out:
[{'lower': 2, 'upper': 6, 'centres': '{8, 7, 6, 1, 16, 17, 9}', 'neighbours': '{8, 7, 6, 1, 16, 17, 9}', 'mu': 0, 'mu_hat': 0, 'nu': 2, 'nu_hat': 0, 'average': True, 'mutationChance': 0.15, 'min_cutoff': 5, 'max_cutoff': 10, 'min_sigma': 0.1, 'max_sigma': 0.5}]
Getting SOAPS for ['soap average cutoff=8 l_max=4 n_max=3 atom_sigma=0.34 n_Z=7 Z={8, 7, 6, 1, 16, 17, 9} n_species=7 species_Z={8, 7, 6, 1, 16, 17, 9} mu=0 mu_hat=0 nu=2 nu_hat=0']
zsh: segmentation fault python genAlg.py input
And in the output_input.txt file i get the outputs:
Starting genetic algorithm with the following parameters:
Population size: 12
Sample size of best individuals: 6
Sample size of lucky individuals: 2
Number of children: 3
The descriptor parameters being used are: [{'lower': 2, 'upper': 6, 'centres': '{8, 7, 6, 1, 16, 17, 9}', 'neighbours': '{8, 7, 6, 1, 16, 17, 9}', 'mu': 0, 'mu_hat': 0, 'nu': 2, 'nu_hat': 0, 'average': True, 'mutationChance': 0.15, 'min_cutoff': 5, 'max_cutoff': 10, 'min_sigma': 0.1, 'max_sigma': 0.5}]
Generating random values for initial population
I am wondering if anyone has an idea for why i get zsh: segmentation fault python genAlg.py input.
Below are my packages and versions relevant to running SOAP_GAS:
Name Version Build Channel
ase 3.22.1 pypi_0 pypi
quippy 0.3.3 pypi_0 pypi
quippy-ase 0.9.12 pypi_0 pypi
scikit-learn 1.2.1 pypi_0 pypi
scipy 1.10.1 pypi_0 pypi
Any help would be appreciated, thanks!
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