diff options
| author | David Luevano Alvarado <55825613+luevano@users.noreply.github.com> | 2020-02-22 18:37:50 -0700 |
|---|---|---|
| committer | David Luevano Alvarado <55825613+luevano@users.noreply.github.com> | 2020-02-22 18:37:50 -0700 |
| commit | 85198178482767d2831ddf3762e5e6eeafa990bd (patch) | |
| tree | 60524aef277834d8d1ccc2bb231a222678ff85a5 /ml_exp | |
| parent | 8d0a22b9fdef41ece399468423cb533768d0e631 (diff) | |
Fix bug, current errors present on adj matrix
Diffstat (limited to 'ml_exp')
| -rw-r--r-- | ml_exp/__main__.py | 3 | ||||
| -rw-r--r-- | ml_exp/representations.py | 16 |
2 files changed, 8 insertions, 11 deletions
diff --git a/ml_exp/__main__.py b/ml_exp/__main__.py index cb8a9a3f1..17119623e 100644 --- a/ml_exp/__main__.py +++ b/ml_exp/__main__.py @@ -28,6 +28,3 @@ if __name__ == '__main__': test = [] for i in range(1, 10): test.append(Compound(f'/home/luevano/py/ml_exp/data/qm7/000{i}.xyz')) - test[i-1].gen_cm(size=1, as_eig=False) - test[i-1].gen_ljm(size=1, as_eig=False) - test[i-1].gen_am(size=1) diff --git a/ml_exp/representations.py b/ml_exp/representations.py index ae870f3b0..796d15f98 100644 --- a/ml_exp/representations.py +++ b/ml_exp/representations.py @@ -48,8 +48,8 @@ def coulomb_matrix(coords, size. Arrays are not of the right shape.') if size < n: - print('Error. Compound size (n) is greater han (size). Using (n)\ - instead of (size).') + print('Error. Compound size (n) is greater han (size). Using (n)', + 'instead of (size).') size = n cm = np.zeros((size, size), dtype=float) @@ -115,8 +115,8 @@ def lennard_jones_matrix(coords, size. Arrays are not of the right shape.') if size < n: - print('Error. Compound size (n) is greater han (size). Using (n)\ - instead of (size).') + print('Error. Compound size (n) is greater han (size). Using (n)', + 'instead of (size).') size = n lj = np.zeros((size, size), dtype=float) @@ -137,10 +137,10 @@ def lennard_jones_matrix(coords, # so no square root is calculated. # Conversion factor is included in r^2. rv = xyz_i - xyz_j - r = sigma*np.linalg.norm(rv)/cr + r = np.linalg.norm(rv)/cr # 1/r^n - r_2 = 1/r**2 + r_2 = sigma**2/r**2 r_6 = r_2**3 r_12 = r_6**2 lj[i, j] = (4*epsilon*(r_12 - r_6)) @@ -204,9 +204,9 @@ def first_neighbor_matrix(coords, cs_bond = sorted(['C', 'S']) if use_forces: - fnm = np.empty((n, n), dtype=float) + fnm = np.zeros((n, n), dtype=float) else: - fnm = np.empty((n, n), dtype=int) + fnm = np.zeros((n, n), dtype=int) bonds = [] forces = [] |