Diffusion lammps (efficient_neuronet) Browse

vizplotgui_vmd.py
9e0598d91891efficient_neuronet

vizplotgui_vmd.py
View Options

			#!/usr/local/bin/python -i
			# preceeding line should have path for Python on your machine

			# vizplotgui_vmd.py
			# Purpose: viz running LAMMPS simulation via VMD with plot and GUI
			# Syntax: vizplotgui_vmd.py in.lammps Nfreq compute-ID
			# in.lammps = LAMMPS input script
			# Nfreq = plot data point and viz shapshot every this many steps
			# compute-ID = ID of compute that calculates temperature
			# (or any other scalar quantity)

			# IMPORTANT: this script cannot yet be run in parallel via Pypar,
			# because I can't seem to do a MPI-style broadcast in Pypar

			import sys,time
			sys.path.append("./pizza")

			# methods called by GUI

			def run():
			global runflag
			runflag = 1
			def stop():
			global runflag
			runflag = 0
			def settemp(value):
			global temptarget
			temptarget = slider.get()
			def quit():
			global breakflag
			breakflag = 1

			# method called by timestep loop every Nfreq steps
			# read dump snapshot and viz it, update plot with compute value

			def update(ntimestep):
			d.next()
			d.unscale()
			p.single(ntimestep)
			v.append('tmp.pdb','pdb')
			value = lmp.extract_compute(compute,0,0)
			xaxis.append(ntimestep)
			yaxis.append(value)
			gn.plot(xaxis,yaxis)

			# parse command line

			argv = sys.argv
			if len(argv) != 4:
			print "Syntax: vizplotgui_vmd.py in.lammps Nfreq compute-ID"
			sys.exit()

			infile = sys.argv[1]
			nfreq = int(sys.argv[2])
			compute = sys.argv[3]

			me = 0
			# uncomment if running in parallel via Pypar
			#import pypar
			#me = pypar.rank()
			#nprocs = pypar.size()

			from lammps import lammps
			lmp = lammps()

			# run infile all at once
			# assumed to have no run command in it
			# dump a file in native LAMMPS dump format for Pizza.py dump tool

			lmp.file(infile)
			lmp.command("thermo %d" % nfreq)
			lmp.command("dump python all atom %d tmp.dump" % nfreq)

			# initial 0-step run to generate initial 1-point plot, dump file, and image

			lmp.command("run 0 pre yes post no")
			value = lmp.extract_compute(compute,0,0)
			ntimestep = 0
			xaxis = [ntimestep]
			yaxis = [value]

			breakflag = 0
			runflag = 0
			temptarget = 1.0

			# wrapper on VMD window via Pizza.py vmd tool
			# just proc 0 handles reading of dump file and viz

			if me == 0:
			from vmd import vmd
			v = vmd()
			v('menu main off')
			v.rep('VDW')

			from dump import dump
			from pdbfile import pdbfile

			d = dump('tmp.dump',0)
			p = pdbfile(d)
			d.next()
			d.unscale()
			p.single(ntimestep)
			v.new('tmp.pdb','pdb')

			# display GUI with run/stop buttons and slider for temperature

			if me == 0:
			from Tkinter import *
			tkroot = Tk()
			tkroot.withdraw()
			root = Toplevel(tkroot)
			root.title("LAMMPS GUI")

			frame = Frame(root)
			Button(frame,text="Run",command=run).pack(side=LEFT)
			Button(frame,text="Stop",command=stop).pack(side=LEFT)
			slider = Scale(frame,from_=0.0,to=5.0,resolution=0.1,
			orient=HORIZONTAL,label="Temperature")
			slider.bind('<ButtonRelease-1>',settemp)
			slider.set(temptarget)
			slider.pack(side=LEFT)
			Button(frame,text="Quit",command=quit).pack(side=RIGHT)
			frame.pack()
			tkroot.update()

			# wrapper on GnuPlot via Pizza.py gnu tool

			if me == 0:
			from gnu import gnu
			gn = gnu()
			gn.plot(xaxis,yaxis)
			gn.title(compute,"Timestep","Temperature")

			# endless loop, checking status of GUI settings every Nfreq steps
			# run with pre yes/no and post yes/no depending on go/stop status
			# re-invoke fix langevin with new seed when temperature slider changes
			# after re-invoke of fix langevin, run with pre yes

			running = 0
			temp = temptarget
			seed = 12345

			lmp.command("fix 2 all langevin %g %g 0.1 %d" % (temp,temp,seed))

			while 1:
			if me == 0: tkroot.update()
			if temp != temptarget:
			temp = temptarget
			seed += me+1
			lmp.command("fix 2 all langevin %g %g 0.1 12345" % (temp,temp))
			running = 0
			if runflag and running:
			lmp.command("run %d pre no post no" % nfreq)
			ntimestep += nfreq
			if me == 0: update(ntimestep)
			elif runflag and not running:
			lmp.command("run %d pre yes post no" % nfreq)
			ntimestep += nfreq
			if me == 0: update(ntimestep)
			elif not runflag and running:
			lmp.command("run %d pre no post yes" % nfreq)
			ntimestep += nfreq
			if me == 0: update(ntimestep)
			if breakflag: break
			if runflag: running = 1
			else: running = 0
			time.sleep(0.01)

			lmp.command("run 0 pre no post yes")

			# uncomment if running in parallel via Pypar
			#print "Proc %d out of %d procs has" % (me,nprocs), lmp
			#pypar.finalize()

lammps/python/examples/vizplotgui_vmd.py9e0598d91891efficient_neuronet

vizplotgui_vmd.pyView Options

lammps/python/examples/vizplotgui_vmd.py
9e0598d91891efficient_neuronet

vizplotgui_vmd.py
View Options