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/* | |
USAGE: ./09cent 03_V2.log str2 str3 | |
str2: RESIDUE NUMBER ( "105" "114" etc ) | |
str3: COEFFICIENT OF SIGMA ( "2" "0" etc ) | |
Especially "0" is selected as a coefficient, then all data of group are putout | |
INPUT: ./pdbtmp/... | |
OUTPUT: ./result/... | |
*/ | |
#include<stdio.h> | |
#include<string.h> |
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#!/bin/sh | |
cmake /home/jykang/hnishi/gromacs-4.6.6 \ | |
-DGMX_BUILD_OWN_FFTW=on \ | |
-DCMAKE_INSTALL_PREFIX=/home/jykang/hnishi/programs/gromacs-4.6.6_serial \ | |
-DGMX_DOUBLE=ON \ | |
-DBUILD_SHARED_LIBS=off \ | |
-DCMAKE_C_COMPILER=/opt/intel/composer_xe_2011_sp1.6.233/bin/intel64/icc \ | |
-DCMAKE_CXX_COMPILER=/opt/intel/composer_xe_2011_sp1.6.233/bin/intel64/icc \ | |
-DGMX_FFT_LIBRARY=mkl \ |
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function ncalc(){ | |
command echo "$1" | bc -l | sed -e 's/^\./0\./' -e 's/-\./-0\./' | |
} | |
# source ncalc.bash or copy into ~/.bashrc | |
# and you can use ncalc command | |
# ncalc 60*2/3 |
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trjconv_mpi_d -f npt.trr -s ../00_add_cl/form3.pdb -o traj_out.pdb |
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title = main_MD | |
define = -DPOSRES_MG ; position restraint | |
integrator = md ; md: leap-frog | |
tinit = 0.0 ; | |
dt = 0.002 ; ps | |
nsteps = 10000000 ; maximum step (ps), -1 means no limit | |
comm-mode = Linear ; com, Linear: translation, Angular: trans. and rotation, None | |
nstcomm = 5 ;frequency for com motion removal |
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ls |grep -v trr|xargs -I{} cp -r {} ../51_norest/ |
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set terminal png | |
#set terminal postscript eps color enhanced | |
#set terminal pdf # not work | |
set nokey | |
set xlabel "Potential energy (kcal/mol)" | |
set ylabel "ln(P)" | |
set yrange [-20:0] | |
#set xrange [110:130] |
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#set term pngcairo transparent | |
#set output "trjpc.png" | |
set term svg enhanced font "Arial, 12" # in svg, 100=1inch | |
set output "output.svg" | |
set encoding iso_8859_1 | |
#set title "Free energy landscape" | |
#set nokey | |
set grid |
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import sys | |
import numpy as np | |
f = open('whole.fort.12', 'r') | |
rgas = 8.31451/4.184/1000 | |
energy = [] | |
lnnE = [] |
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# prjnishi.py v 1.0 | |
# projection into PC space with a PCA eigenvector and average. | |
import sys | |
import numpy as np | |
from optparse import OptionParser | |
############ argument ############## | |
parser = OptionParser | |
def get_options(): |