Esempio n. 1
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    def runStructures(self, structures, path, calcStates=True):
        '''Run simulations for all structures in the given structure list with
        the base path "path". This method dispatches all processes and returns
        the user has to wait for processes to finish before accessing results.

        Stores started processes in self.processes
        '''

        local = Local()
        for ss in structures:
            spath = Path.joinpath(path, str(ss.dirname))
            su.mkdir(spath)
            if calcStates:
                self.initdir(ss, spath)
                #proc = su.dispatch(self.progWS, "",spath)
                proc = self.pltfm.submitjob(self.progWS, [], spath, 1, "00:10")
                self.processes.append(proc)
        if calcStates:
            dbg.debug("Starting calcWS program.....\n",
                      dbg.verb_modes["verbose"], self)
            dbg.flush()
        # TODO do not wait for all processes-start each strucrure when ready!
        self.waitforproc(1)
        dbg.debug("Starting lqcl.....\n", dbg.verb_modes["verbose"], self)
        dbg.flush()
        #del processes
        #processes = []
        for ss in structures:
            spath = Path.joinpath(path, str(ss.dirname))

            proc = self.pltfm.submitjob(self.proglqcl, [],
                                        Path.joinpath(spath, self.datpath))

            self.processes.append(proc)
        return self.processes
Esempio n. 2
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def dispatch(prog,
             args,
             dirpath=None,
             infile=None,
             outfile=None,
             errfile=None):
    '''Dispatch program prog with arguments args.

    Optional parameters:
    dirpath: Path to working directory.
    infile:  File with inputs to the program. Use subprocess.PIPE for input stream.
    outfile: File for program output. Use subprocess.PIPE for output stream.
    errfile: File for program output. Use subprocess.PIPE for output stream.

    Returns the Popen() process.

    Note that if all outputs are piped, the system can cause the program to crash
    since the pipes might not be properly closed between calls.
    '''

    if infile is None:
        infile = tmp()
    if outfile is None:
        outfile = tmp()
    if errfile is None:
        errfile = tmp()

    if args == []:
        progargs = prog
    else:
        progargs = [prog]

        for a in args:
            progargs.append(a)

    if dirpath is None:
        dirpath = "./"

    dbg.debug(
        "<<<< Dispatching program: " + str(progargs) + " from " + dirpath,
        dbg.verb_modes["chatty"])

    process = Popen(progargs,
                    cwd=dirpath,
                    close_fds=True,
                    stdout=outfile,
                    stderr=errfile,
                    stdin=infile,
                    universal_newlines=True)

    dbg.debug(" with pid=" + str(process.pid) + " >>>>\n",
              dbg.verb_modes["chatty"])
    dbg.flush()
    return process
Esempio n. 3
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    def jobstatus(self, proc):
        for info in self.procinfo:
            if info[0] == proc.pid:
                jobname = info[1]
        p = su.dispatch("bjobs", ["-J", jobname], errfile=subprocess.PIPE)
        out = p.communicate()

        if ("not found" in out[1]) and (proc.poll() != None):
            dbg.debug("process ended!")
            return False
        else:
            return True
Esempio n. 4
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    def run_sewself(self, structure, spath, inputs=None):
        '''Run sewself for given structure and structure path (spath)
        inputs (Optional): List of sting of commands to be executed (a-w)
        '''
        commands = ""
        if inputs is None:
            inputs = self.commands

        for c in inputs:
            if c[0] == 'a':
                commands += "a\n" + c[1] + "\n" + c[2] + \
                 "\n" + c[3] + "\n"
            elif c[0] == 'b':
                commands += "b\n"
                commands += str(self.numpar.get('Tlattice')) + "\n"
                commands += str(self.numpar.get('Te')) + "\n"
            elif c[0] == 'c':
                commands += "c\n"
            elif c[0] == 'd':
                commands += "d\n"
            elif c[0] == 'e':
                commands += "e\n"  # compute self-consitent potential
                commands += str(self.numpar.get('Tlattice')) + "\n"
                commands += str(self.numpar.get('Te')) + "\n"
            elif c[0] == 'f':
                commands += "f\n"
            elif c[0] == 'g':
                commands += "g\n"
                commands += str(self.numpar.get('Te')) + "\n"
            else:
                print("WARNING: Option " + c[0] + \
                " not implemented in Isewself!")
        commands += "q\n^C\n"

        dbg.debug("Running sewself:", callclass=self)
        dbg.flush()
        proc = su.dispatch(self.sewself, [],
                           spath,
                           infile=subprocess.PIPE,
                           outfile=subprocess.PIPE,
                           errfile=subprocess.PIPE)
        dbg.debug("Communicating sewself: \n" + commands, callclass=self)
        dbg.flush()
        out, err = proc.communicate(commands)
        structure.output = out
Esempio n. 5
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    def minimize(self, model, sgenerator, pathwd, pathresults=None, seq=None):

        if pathresults is None:
            pathresults = pathwd

        dbg.debug("Starting minimization\n", dbg.verb_modes["verbose"], self)
        niter = 0
        while self.converged == 0:
            niter += 1
            dbg.debug("Iteration " + str(niter) + "\n",
                      dbg.verb_modes["verbose"], self)

            newx = self.nextstep()
            sgenerator.gen_struct_from_hilbert_curve(newx)
            if seq is not None:
                t = model.runStructSeq(sgenerator.structures[-len(newx):],
                                       pathwd, seq)
                for tt in t:
                    tt.join()
            else:
                model.runStructures(sgenerator.structures[-len(newx):], pathwd)
                model.waitforproc(0.1)
            newy = []
            xi = 0
            model.gatherResults(sgenerator.structures[-len(newx):],
                                pathwd,
                                pathresults=pathresults)
            for ss in sgenerator.structures[-len(newx):]:
                try:
                    val = -float(model.getMerit(ss, pathwd))
                    newy.append(val)
                except (ValueError):
                    del newx[xi]
                    xi -= 1
                xi += 1

            self.addpoints(newx, newy)
            self.writeresults(pathresults, "hilbert.log")

        dbg.debug(
            "Minimization finished with convergence: " + str(self.converged) +
            "\n", dbg.verb_modes["verbose"], self)
        dbg.flush()
        return self.converged
Esempio n. 6
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    def minimize(self, model, sgenerator, pathwd, pathresults=None, seq=None):

        if pathresults is None:
            pathresults = pathwd

        dbg.debug("Starting minimization\n", dbg.verb_modes["verbose"], self)
        niter = 0
        while self.converged == 0:
            niter += 1
            dbg.debug("Iteration " + str(niter) + "\n",
                      dbg.verb_modes["verbose"], self)

            newx = self.nextstep()
            sgenerator.generateStructures(newx)
            if seq is not None:
                t = model.runStructSeq(sgenerator.structures[-len(newx):],
                                       pathwd, seq)
                for tt in t:
                    tt.join()
            else:
                model.runStructures(sgenerator.structures[-len(newx):], pathwd)
                model.waitforproc(60)
            newy = []
            newx_success = []
            xi = 0
            model.gatherResults(sgenerator.structures[-len(newx):],
                                pathwd,
                                pathresults=pathresults)

            self.addEvaldPoints(model, sgenerator, pathwd,
                                sgenerator.structures[-len(newx):])

            #self.writeresults(pathresults, "mdgauss.log")

        dbg.debug(
            "Minimization finished with convergence: " + str(self.converged) +
            "\n", dbg.verb_modes["verbose"], self)
        dbg.flush()
        return self.converged
Esempio n. 7
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import aftershoq.utils.debug as dbg
from aftershoq.interface import Isewself, Inegf
from aftershoq.numerics import Paraopt, Gaussopt
from matplotlib import pyplot as pl
import aftershoq.utils.const as const

if __name__ == '__main__':

    # the working directory:
    path = "/Users/martin/Projects/Optimization/ASQW/ASQWchi2/Mehrans/v3/"
    #path = os.getcwd()+"/"+path
    su.mkdir(path)

    # Setup debugger:
    dbg.open(dbg.verb_modes['verbose'], path + "/debug.log")
    dbg.debug("Debug file \n\n")
    dbg.flush()

    sep = '\n----------------------------------------------\n'

    print('--- Welcome to the "sewself" demonstration of ---\n')
    print('               "AFTERSHOQ" \n\n')
    print('       Written by Martin Franckie 2018.')
    print('       Please give credit where credit')
    print('                   is due\n')
    print(sep)
    print('Creating semiconductor materials and alloys:\n')
    print('       ( All CBO relative to GaAs )\n')

    # create materials GaAs and two AlGaAs: