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()
def main():
# parse args
parser = argparse.ArgumentParser(description="output the Lasso charge")
parser.add_argument("FILE",
nargs=1,
help="input file(.mpac)")
parser.add_argument("-o", "--output",
nargs=1,
dest="charge_path",
default="LASSOcharge.mpac",
help="output file")
args = parser.parse_args()
# setting
db_path = args.FILE[0]
fr = open(db_path, "rb")
data = msgpack.unpackb(fr.read())
Atom_List = np.array(data["atoms"])
atoms = np.array(Atom_List[:, 5:])
atoms = atoms.astype(np.float)
X = np.array(data["matrixX"])
Y = np.array(data["matrixY"])
net_charge = data["net_charge"]
Natom = len(Atom_List)
Ngrid = len(X)
# matrixA, B
A = mkmat.matrixA(X, Y)
B = mkmat.matrixB(X, Y, net_charge)
# scf calculation
Lasso_parameter = 1e-4
Lasso_Charge = chg_lasso.iteration(A, B, Lasso_parameter)
# RRMS
RRMS = chg_resp.RRMS(X, Y, Lasso_Charge)
# write the data
fw_path = args.charge_path[0]
fw = open(fw_path, "wb")
data["Lasso"] = Lasso_Charge[:-1]
packed = msgpack.packb(data)
fw.write(packed)
fw.close()
def main():
# parse args
parser = argparse.ArgumentParser(
description="calculate the ESP/RESP 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)
# Unit Matrix
I = np.matrix(np.identity(Natom))
# matrix
A = mkmat.matrixA(X, Y)
B = mkmat.matrixB(X, Y, net_charge)
# ESP CHARGE
ESP_CHARGE = np.linalg.solve(A, B)
# RESP CHARGE
# === #
#Q_target = Mulliken_List
Q_target = np.zeros(Natom)
Q_new = np.zeros(Natom + 1)
SCF_A = resp.copy_matrixA(A)
SCF_B = resp.copy_matrixB(B)
SCF_iteration = 200
SCF_threshold = 1e-6
#rstr_type = "harmonic"
rstr_type = "hyperbolic"
# === #
for NSCF in range(SCF_iteration):
Q_old = Q_new
resp.SCF_convert_matrix(Atom_List, Q_old, Q_target, A, B, SCF_A, SCF_B,
rstr_type)
Q_new = np.linalg.solve(SCF_A, SCF_B)
error = resp.SCF_error(Q_new, Q_old)
if error < SCF_threshold:
print "convergence"
break
Q_new = resp.SimpleMixing(Q_new, Q_old, 0.85)
RESP_CHARGE = Q_new
# RRMS
MSE = resp.MSE(X, Y, RESP_CHARGE)
ESP_square_sum = 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["RESP"] = RESP_CHARGE[:-1]
packed = msgpack.packb(data)
fw.write(packed)
fw.close()
def main():
# parse args
parser = argparse.ArgumentParser(description="calculate the ESP/RESP 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)
# Unit Matrix
I = np.matrix(np.identity(Natom))
# matrix
A = mkmat.matrixA(X, Y)
B = mkmat.matrixB(X, Y, net_charge)
# ESP CHARGE
ESP_CHARGE = np.linalg.solve(A, B)
# RESP CHARGE
# === #
#Q_target = Mulliken_List
Q_target = np.zeros(Natom)
Q_new = np.zeros(Natom+1)
SCF_A = resp.copy_matrixA(A)
SCF_B = resp.copy_matrixB(B)
SCF_iteration = 200
SCF_threshold = 1e-6
#rstr_type = "harmonic"
rstr_type = "hyperbolic"
# === #
for NSCF in range(SCF_iteration):
Q_old = Q_new
resp.SCF_convert_matrix(Atom_List, Q_old, Q_target, A, B, SCF_A, SCF_B, rstr_type)
Q_new = np.linalg.solve(SCF_A, SCF_B)
error = resp.SCF_error(Q_new, Q_old)
if error < SCF_threshold:
print "convergence"
break
Q_new = resp.SimpleMixing(Q_new, Q_old, 0.85)
RESP_CHARGE = Q_new
# RRMS
MSE = resp.MSE(X, Y, RESP_CHARGE)
ESP_square_sum = 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["RESP"] = RESP_CHARGE[:-1]
packed = msgpack.packb(data)
fw.write(packed)
fw.close()
