def iteration(A, B, lasso_param): Natom = len(A) SCF_A = chg_resp.copy_matrixA(A) Q_new = np.linalg.solve(A, B) SCF_iteration = 100000 SCF_threshold = 1e-6 zero_threshold = 1e-200 for Nscf in range(SCF_iteration): Q_old = Q_new for j in range(Natom-1): if abs(Q_old[j]) < zero_threshold: Q_old[j] = 0.0 for j in range(Natom-1): if abs(Q_old[j]) >= zero_threshold: param = lasso_param / abs(Q_old[j]) else: param = 0 SCF_A[j][j] = A[j][j] + param Q_new = np.linalg.solve(SCF_A, B) error = chg_resp.SCF_error(Q_new, Q_old) if error < SCF_threshold: print "convergence &",Nscf break # Q_new = chg_resp.SimpleMixing(Q_new, Q_old, 0.85) return Q_new
def iteration(A, B, lasso_param):
Natom = len(A)
SCF_A = chg_resp.copy_matrixA(A)
Q_new = np.linalg.solve(A, B)
SCF_iteration = 100000
SCF_threshold = 1e-6
zero_threshold = 1e-200
for Nscf in range(SCF_iteration):
Q_old = Q_new
for j in range(Natom - 1):
if abs(Q_old[j]) < zero_threshold:
Q_old[j] = 0.0
for j in range(Natom - 1):
if abs(Q_old[j]) >= zero_threshold:
param = lasso_param / abs(Q_old[j])
else:
param = 0
SCF_A[j][j] = A[j][j] + param
Q_new = np.linalg.solve(SCF_A, B)
error = chg_resp.SCF_error(Q_new, Q_old)
if error < SCF_threshold:
print "convergence &", Nscf
break
# Q_new = chg_resp.SimpleMixing(Q_new, Q_old, 0.85)
return Q_new
def main():
# parse args
parser = argparse.ArgumentParser(description="calculate the Ridge Charge")
parser.add_argument("FILE",
nargs=1,
help="input file(.mpac)")
parser.add_argument("-o", "--output",
nargs=1,
dest="charge_path",
help="charge file")
args = parser.parse_args()
# setting
db_path = args.FILE[0]
fr = open(db_path, "rb")
data = msgpack.unpackb(fr.read())
Atom_List = data["atoms"]
Grid_List = data["grids"]
ESP_List = data["ESP"]
Mulliken_List = data["mulliken"]
X = np.array(data["matrixX"])
Y = np.array(data["matrixY"])
net_charge = data["net_charge"]
Natom = len(Atom_List)
Ngrid = len(Grid_List)
# matrix
A = mkmat.matrixA(X, Y)
B = mkmat.matrixB(X, Y, net_charge)
I = np.matrix(np.identity(Natom))
# Ridge CHARGE
Q_new = np.zeros(Natom+1)
Ridge_A = chg_resp.copy_matrixA(A)
wt = 1e-1
chg_resp.Ridge_convert_matrix(Atom_List, A, Ridge_A, wt)
Ridge_CHARGE = np.linalg.solve(Ridge_A, B)
# RRMS
MSE = chg_resp.MSE(X, Y, Ridge_CHARGE)
ESP_square_sum = chg_resp.ESP_square_sum(Y)
RRMS = np.sqrt(MSE/ESP_square_sum)
# write the data
fw_path = args.charge_path[0]
fw = open(fw_path, "wb")
data["Ridge"] = Ridge_CHARGE[:-1]
packed = msgpack.packb(data)
fw.write(packed)
fw.close()
def main():
# parse args
parser = argparse.ArgumentParser(description="calculate the Ridge Charge")
parser.add_argument("FILE", nargs=1, help="input file(.mpac)")
parser.add_argument("-o",
"--output",
nargs=1,
dest="charge_path",
help="charge file")
args = parser.parse_args()
# setting
db_path = args.FILE[0]
fr = open(db_path, "rb")
data = msgpack.unpackb(fr.read())
Atom_List = data["atoms"]
Grid_List = data["grids"]
ESP_List = data["ESP"]
Mulliken_List = data["mulliken"]
X = np.array(data["matrixX"])
Y = np.array(data["matrixY"])
net_charge = data["net_charge"]
Natom = len(Atom_List)
Ngrid = len(Grid_List)
# matrix
A = mkmat.matrixA(X, Y)
B = mkmat.matrixB(X, Y, net_charge)
I = np.matrix(np.identity(Natom))
# Ridge CHARGE
Q_new = np.zeros(Natom + 1)
Ridge_A = chg_resp.copy_matrixA(A)
wt = 1e-1
chg_resp.Ridge_convert_matrix(Atom_List, A, Ridge_A, wt)
Ridge_CHARGE = np.linalg.solve(Ridge_A, B)
# RRMS
MSE = chg_resp.MSE(X, Y, Ridge_CHARGE)
ESP_square_sum = chg_resp.ESP_square_sum(Y)
RRMS = np.sqrt(MSE / ESP_square_sum)
# write the data
fw_path = args.charge_path[0]
fw = open(fw_path, "wb")
data["Ridge"] = Ridge_CHARGE[:-1]
packed = msgpack.packb(data)
fw.write(packed)
fw.close()
