def make(self):
curr_path = os.getcwd()
all_path = curr_path + "/all"
if os.path.exists(all_path):
os.system('rm -r ./all')
os.makedirs(all_path)
if self.n_s0 > 0:
self.copy_s0()
self.select_coord_many()
self.copy()
if self.n_ci > 0:
self.copy_ci()
# """Save the list to a file named list_file.dat"""
list_file = self.list_file
num = self.num
sl = self.savelist
curr_path = os.getcwd()
all_path = curr_path + "/all"
workfile = all_path + "/" + list_file
fp = open(workfile, "w")
for i in range(num):
print("%10d%10d%10d" % (sl[i][0], sl[i][1], sl[i][2]), file=fp)
fp.close()
print("The total geom selected is %10d" % self.num)
self.inp['n_geom'] = self.num
json.dump_json('inp.json', self.inp)
print("The select work is done")
def make(self):
curr_path = os.getcwd()
work_path = curr_path + '/all'
os.chdir(work_path)
self.rmsd_matrix = np.loadtxt('rmsd_all.dat')
self.savelist = np.loadtxt('list_file_save.dat')
command1 = 'cp rmsd_all.dat rmsd_all.dat_old'
command2 = 'cp list_file_save.dat list_file_save.dat_old'
os.system(command1)
os.system(command2)
if self.inp['job_select'] == 'isomap':
self.isomap_epsilon()
else:
self.classical_analy()
os.chdir(curr_path)
json.dump_json('inp.json', self.inp)
#! /usr/bin/env python
import rmsd_analys
import mds_cla
import mds_analys
import sub_inp_json as json
import os
import shutil
inp = json.load_json('inp.json')
inp['job_select'] = raw_input(
"which job do u choose,classical or isomap(classical/isomap):")
inp['rmsd_cutoff'] = raw_input("Input the rmsd_cutoff value:")
if inp['job_select'] == 'isomap':
inp['mds_cutoff'] = raw_input("Input the mds_cutoff value:")
inp['mds_dimension'] = raw_input("Choose mds dimension:")
json.dump_json('inp.json', inp)
if inp['job_select'] == 'isomap':
file_name = inp['job_select'] + '_rmsdcut_' + inp[
'rmsd_cutoff'] + '_mdscut_' + inp['mds_cutoff']
if inp['job_select'] == 'classical':
file_name = inp['job_select'] + '_rmsdcut_' + inp['rmsd_cutoff']
curr_dir = os.getcwd()
workdir = curr_dir + '/' + file_name
if os.path.exists(workdir):
shutil.rmtree(workdir)
os.mkdir(workdir)
command1 = 'cp -r all ' + workdir
command2 = 'cp inp.json ' + workdir
os.system(command1)
os.system(command2)
#!/usr/bin/env python
import os
import sub_inp_json
import numpy as np
from sub_kkr_prediction_tool import kkr_single_all_step
filename = 'kkr.input'
xxx = sub_inp_json.read_dat_with_label(filename)
sub_inp_json.dump_json('kkr.json', xxx)
def kkr_single_geom_all():
kkrname = "kkr.json"
xxx_input = sub_inp_json.load_json(kkrname)
n_x_dim = int(xxx_input['n_x_dim'])
n_y_dim = int(xxx_input['n_y_dim'])
label_x_descriptor = int(xxx_input['label_x_descriptor'])
para_kernel = xxx_input['para_kernel']
rescale = xxx_input['rescale']
label_grad = xxx_input['label_grad']
para_alpha = float(xxx_input['para_alpha'])
para_gamma = float(xxx_input['para_gamma'])
energy_zero = float(xxx_input['energy_zero'])
curr_dir = os.getcwd()
kkr_path = './kkr'
x_train = np.loadtxt('./kkr/x_train.dat')
#!/usr/bin/env python
import os
import sub_inp_json
filename = 'fitting.input'
xxx = sub_inp_json.read_dat_with_label(filename)
sub_inp_json.dump_json('input_initial.json', xxx)
os.system('cp input_initial.json ../input_initial.json')