source: issm/oecreview/Archive/14312-15392/ISSM-14871-14872.diff@ 15393

../trunk-jpl/src/m/solve/solve.py

@@ -1 @@
-import datetime
-import os
-import shutil
-from pairoptions import *
-from process_solve_options import *
-from EnumDefinitions import *
-from EnumToString import EnumToString
-from ismodelselfconsistent import *
-from marshall import *
-from ispetsc import *
-from waitonlock import *
-from loadresultsfromcluster import *
-
-def solve(md,solutionenum,*args):
-        """
-        SOLVE - apply solution sequence for this model
- 
-           Usage:
-              md=solve(md,solutionenum,varargin)
-              where varargin is a list of paired arguments of string OR enums
- 
-           solution types available comprise:
-              - DiagnosticSolutionEnum
-              - PrognosticSolutionEnum
-              - ThermalSolutionEnum
-              - SteadystateSolutionEnum
-              - TransientSolutionEnum...
-              - BalancethicknessSolutionEnum
-              - BedSlopeSolutionEnum
-              - SurfaceSlopeSolutionEnum
-              - HydrologySolutionEnum
-              - FlaimSolutionEnum
- 
-           extra options:
-              - loadonly : does not solve. only load results
- 
-           Examples:
-              md=solve(md,DiagnosticSolutionEnum);
-        """
-
-        #recover and process solve options
-        options=pairoptions('solution_type',solutionenum,*args)
-        options=process_solve_options(options)
-
-        #recover some fields
-        md.private.solution=options['solution_type']
-        cluster=md.cluster
-
-        #check model consistency
-        print "checking model consistency"
-        if solutionenum == FlaimSolutionEnum():
-                md.private.isconsistent=True
-                md.mesh.checkconsistency(md,solutionenum)
-                md.flaim.checkconsistency(md,solutionenum)
-                if not md.private.isconsistent:
-                        raise RuntimeError("Model not consistent, see messages above.")
-        else:
-                ismodelselfconsistent(md)
-
-        #First, build a runtime name that is unique
-        c=datetime.datetime.now()
-        md.private.runtimename="%s-%02i-%02i-%04i-%02i-%02i-%02i-%i" % (md.miscellaneous.name,c.month,c.day,c.year,c.hour,c.minute,c.second,os.getpid())
-
-        #if running qmu analysis, some preprocessing of dakota files using models
-        #fields needs to be carried out. 
-        if md.qmu.isdakota:
-                md=preqmu(md,options)
-
-        #flaim analysis
         if options['solution_type'] == FlaimSolutionEnum():
                 md=flaim_sol(md,options)
                 [md.private.solution]=EnumToString(options['solution_type'])
@@ -82 +13 @@
         md.toolkits.ToolkitsFile(md.miscellaneous.name+'.toolkits')    # toolkits file
         cluster.BuildQueueScript(md.private.runtimename,md.miscellaneous.name,md.private.solution,md.settings.io_gather,md.debug.valgrind,md.debug.gprof)    # queue file
 
-        #we need to make sure we have PETSC support, otherwise, we run with only one cpu: 
-        if not ispetsc():
-                print "PETSC support not included, running on 1 cpu only!"
-                cluster.np=1
-
         #Stop here if batch mode
         if strcmpi(options['batch'],'yes'):
                 print 'batch mode requested: not launching job interactively'