From 5bf923679707fd1603a6f73ca4d0ae8ec39e7858 Mon Sep 17 00:00:00 2001
From: David Luevano Alvarado <55825613+luevano@users.noreply.github.com>
Date: Sat, 29 Feb 2020 07:40:33 -0700
Subject: Almost completely rewrite fnm to hd
---
ml_exp/__init__.py | 4 ++--
ml_exp/compound.py | 38 +++++++++++++++++++++++---------------
ml_exp/representations.py | 36 +++++++++++++++++++-----------------
3 files changed, 44 insertions(+), 34 deletions(-)
diff --git a/ml_exp/__init__.py b/ml_exp/__init__.py
index 48ece56c8..9e64d7754 100644
--- a/ml_exp/__init__.py
+++ b/ml_exp/__init__.py
@@ -22,7 +22,7 @@ SOFTWARE.
"""
from ml_exp.compound import Compound
from ml_exp.representations import coulomb_matrix, lennard_jones_matrix,\
- first_neighbor_matrix, adjacency_matrix, check_bond, bag_of_stuff
+ get_helping_data, adjacency_matrix, check_bond, bag_of_stuff
from ml_exp.math import cholesky_solve
from ml_exp.qm7db import qm7db
from ml_exp.do_ml import simple_ml, do_ml
@@ -30,7 +30,7 @@ from ml_exp.do_ml import simple_ml, do_ml
__all__ = ['Compound',
'coulomb_matrix',
'lennard_jones_matrix',
- 'first_neighbor_matrix',
+ 'get_helping_data',
'adjacency_matrix',
'check_bond',
'bag_of_stuff',
diff --git a/ml_exp/compound.py b/ml_exp/compound.py
index ceace6984..26e393510 100644
--- a/ml_exp/compound.py
+++ b/ml_exp/compound.py
@@ -23,7 +23,7 @@ SOFTWARE.
import numpy as np
from ml_exp.data import NUCLEAR_CHARGE
from ml_exp.representations import coulomb_matrix, lennard_jones_matrix,\
- first_neighbor_matrix, adjacency_matrix, bag_of_stuff
+ get_helping_data, adjacency_matrix, bag_of_stuff
class Compound:
@@ -46,7 +46,6 @@ class Compound:
# Computed data.
self.cm = None
self.ljm = None
- self.fnm = None
self.am = None
self.bob = None
self.bo_atoms = None
@@ -54,8 +53,11 @@ class Compound:
self.bof = None
# Helping data.
+ self.fnm = None
self.bonds = None
- self.forces = None
+ self.bonds_i = None
+ self.bonds_k = None
+ self.bonds_f = None
if xyz is not None:
self.read_xyz(xyz)
@@ -101,28 +103,34 @@ class Compound:
as_eig=as_eig,
bohr_ru=bohr_ru)
- def gen_am(self,
- use_forces=False,
+ def gen_hd(self,
size=23,
bohr_ru=False):
"""
+ Generate the helping data for use in Adjacency Matrix, for example.
+ size: compund size.
+ bohr_ru: if radius units should be in bohr's radius units.
+ """
+ hp = get_helping_data(self.coordinates,
+ self.nc,
+ self.atoms,
+ size=size,
+ bohr_ru=bohr_ru)
+
+ self.fnm, self.bonds, self.bonds_i, self.bonds_k, self.bonds_f = hp
+
+ def gen_am(self,
+ use_forces=False,
+ size=23):
+ """
Generate the Adjacency Matrix for the compund.
use_forces: if the use of forces instead of k_cx should be used.
size: compound size.
bohr_ru: if radius units should be in bohr's radius units.
"""
- # First, generate the first neighor matrix.
- fnm_data = first_neighbor_matrix(self.coordinates,
- self.atoms_nc,
- self.atoms,
- size=size,
- use_forces=use_forces,
- bohr_ru=bohr_ru)
- self.fnm, self.bonds, self.forces = fnm_data
- # Now, generate the adjacency matrix.
self.am = adjacency_matrix(self.fnm,
self.bonds,
- self.forces,
+ self.bonds_f,
size=size)
def gen_bob(self,
diff --git a/ml_exp/representations.py b/ml_exp/representations.py
index 515821290..5e684314b 100644
--- a/ml_exp/representations.py
+++ b/ml_exp/representations.py
@@ -166,18 +166,17 @@ size. Arrays are not of the right shape.')
return lj
-def first_neighbor_matrix(coords,
- nc,
- atoms,
- size=23,
- use_forces=False,
- bohr_ru=False):
+def get_helping_data(coords,
+ nc,
+ atoms,
+ size=23,
+ bohr_ru=False):
"""
- Creates the First Neighbor Matrix from the molecule data given.
+ Creates helping data such as the First Neighbor Matrix for the compound.
coords: compound coordinates.
nc: nuclear charge data.
atoms: list of atoms.
- use_forces: if the use of forces instead of k_cx should be used.
+ size: compund size.
bohr_ru: if radius units should be in bohr's radius units.
NOTE: Bond distance of carbon to other elements
are (for atoms present in the qm7 dataset):
@@ -209,15 +208,15 @@ size. Arrays are not of the right shape.')
co_bond = sorted(['C', 'O'])
cn_bond = sorted(['C', 'N'])
cs_bond = sorted(['C', 'S'])
-
- pos_bonds = {cc_bond: (1.19, 1.54), ch_bond: (1.06, 1.12),
- co_bond: (1.43, 2.15), cn_bond: (1.47, 2.19),
- cs_bond: (1.81, 2.55)}
+ pos_bonds = {cc_bond: (1.19, 1.54, 1.0), ch_bond: (1.06, 1.12, 1.0),
+ co_bond: (1.43, 2.15, 0.8), cn_bond: (1.47, 2.19, 1.0),
+ cs_bond: (1.81, 2.55, 0.7)}
fnm = np.zeros((size, size), dtype=bool)
-
bonds = []
- forces = []
+ bonds_i = []
+ bonds_k = []
+ bonds_f = []
for i, xyz_i in enumerate(coords):
for j, xyz_j in enumerate(coords):
# Ignore the diagonal.
@@ -230,11 +229,14 @@ size. Arrays are not of the right shape.')
r = np.linalg.norm(rv)/cr
if r >= r_min and r <= r_max:
fnm[i, j] = True
+ # Only add to the list if in the upper triangle.
if j > i:
- bonds.append((i, j))
- forces.append(rv*nc[i]*nc[j]/r**3)
+ bonds.append(bond)
+ bonds_i.append((i, j))
+ bonds_k.append(pos_bonds[bond][2])
+ bonds_f.append(rv*nc[i]*nc[j]/r**3)
- return fnm, bonds, forces
+ return fnm, bonds, bonds_i, bonds_k, bonds_f
def adjacency_matrix(fnm,
--
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