diff options
| -rw-r--r-- | main.py | 58 |
1 files changed, 7 insertions, 51 deletions
@@ -33,8 +33,9 @@ from read_db_edata import read_db_edata from c_matrix import c_matrix from lj_matrix import lj_matrix # from frob_norm import frob_norm -from gauss_kernel import gauss_kernel -from cholesky_solve import cholesky_solve +# from gauss_kernel import gauss_kernel +# from cholesky_solve import cholesky_solve +from do_ml import do_ml def printc(text, color): @@ -90,55 +91,10 @@ toc = time.perf_counter() printc('\tL-J matrices calculation took {:.4f} seconds.'.format(toc-tic), Fore.GREEN) -# -# Problem solving with Coulomb Matrix. -# -printc('CM ML started.', Fore.CYAN) -tic = time.perf_counter() - -sigma = 1000.0 - -Xcm_training = cm_data[:6000] -Ycm_training = energy_pbe0[:6000] -Kcm_training = gauss_kernel(Xcm_training, Xcm_training, sigma) -alpha_cm = cholesky_solve(Kcm_training, Ycm_training) - -Xcm_test = cm_data[-1000:] -Ycm_test = energy_pbe0[-1000:] -Kcm_test = gauss_kernel(Xcm_test, Xcm_training, sigma) -Ycm_predicted = np.dot(Kcm_test, alpha_cm) - -print('\tMean absolute error for CM: {}'.format(np.mean(np.abs(Ycm_predicted - - Ycm_test)))) - -toc = time.perf_counter() -printc('\tCM ML took {:.4f} seconds.'.format(toc-tic), Fore.GREEN) - - -# -# Problem solving with L-J Matrix. -# -printc('L-JM ML started.', Fore.CYAN) -tic = time.perf_counter() - -sigma = 1000.0 - -Xljm_training = ljm_data[:6000] -Yljm_training = energy_pbe0[:6000] -Kljm_training = gauss_kernel(Xljm_training, Xljm_training, sigma) -alpha_ljm = cholesky_solve(Kljm_training, Yljm_training) - -Xljm_test = ljm_data[-1000:] -Yljm_test = energy_pbe0[-1000:] -Kljm_test = gauss_kernel(Xljm_test, Xljm_training, sigma) -Yljm_predicted = np.dot(Kljm_test, alpha_ljm) - -print('\tMean absolute error for LJM: {}'.format(np.mean(np.abs(Yljm_predicted - - Yljm_test)))) - -toc = time.perf_counter() -printc('\tL-JM ML took {:.4f} seconds.'.format(toc-tic), Fore.GREEN) - +# Coulomb Matrix ML +do_ml(cm_data, 'CM', energy_pbe0, 1000, 100, 1000.0) +# Lennard-Jones Matrix ML +do_ml(ljm_data, 'L-JM', energy_pbe0, 1000, 100, 1000.0) # End of program end_time = time.perf_counter() |