import scipy.integrate
scipy.integrate.quad(lambda x: 4.0/(1+x*x), 0, 1)
"""
from numpy import arange
# default # of rectangles
n = 20000
integration_points = (arange(1,n+1)-0.5)/n
def f(x):
return 4.0/(1.0+x*x)
#from pyina.mpi_scatter import parallel_map
from pyina.mpi_pool import parallel_map
if __name__ == '__main__':
out = parallel_map(f, integration_points)
from pyina import mpi
if mpi.world.rank == 0:
print("approxmiate pi : ", sum(out)/n)
print("calculated on %d nodes " % mpi.world.size)
# end of file
argfilename = sys.argv[2]
outfilename = sys.argv[3]
if funcname.endswith('.pik'): # used pickled func
workdir = None
func = pickle.load(open(funcname, 'r'))
else: # used tempfile for func
workdir = sys.argv[4]
sys.path = [workdir] + sys.path
modname = os.path.splitext(os.path.basename(funcname))[0]
module = __import__(modname)
sys.path.pop(0)
func = module.FUNC
args, kwds = pickle.load(open(argfilename, 'r'))
if world.rank == 0:
log.info('funcname: %s' % funcname) # sys.argv[1]
log.info('argfilename: %s' % argfilename) # sys.argv[2]
log.info('outfilename: %s' % outfilename) # sys.argv[3]
log.info('workdir: %s' % workdir) # sys.argv[4]
log.info('func: %s' % func)
log.info('args: %s' % str(args))
log.info('kwds: %s' % str(kwds))
res = parallel_map(func, *args, **kwds) #XXX: called on ALL nodes ?
if world.rank == 0:
log.info('res: %s' % str(res))
pickle.dump(res, open(outfilename, 'w'))
# end of file
import scipy.integrate
scipy.integrate.quad(lambda x: 4.0/(1+x*x), 0, 1)
"""
from numpy import arange
# default # of rectangles
n = 20000
integration_points = (arange(1,n+1)-0.5)/n
def f(x):
return 4.0/(1.0+x*x)
#from pyina.mpi_scatter import parallel_map
from pyina.mpi_pool import parallel_map
if __name__ == '__main__':
out = parallel_map(f, integration_points)
from pyina import mpi
if mpi.world.rank == 0:
print "approxmiate pi : ", sum(out)/n
print "calculated on %d nodes: " % mpi.world.size
# end of file
outfilename = sys.argv[3]
if funcname.endswith('.pik'): # used pickled func
workdir = None
func = pickle.load(open(funcname,'r'))
else: # used tempfile for func
workdir = sys.argv[4]
sys.path = [workdir] + sys.path
modname = os.path.splitext(os.path.basename(funcname))[0]
module = __import__(modname)
sys.path.pop(0)
func = module.FUNC
args,kwds = pickle.load(open(argfilename,'r'))
if world.rank == 0:
log.info('funcname: %s' % funcname) # sys.argv[1]
log.info('argfilename: %s' % argfilename) # sys.argv[2]
log.info('outfilename: %s' % outfilename) # sys.argv[3]
log.info('workdir: %s' % workdir) # sys.argv[4]
log.info('func: %s' % func)
log.info('args: %s' % str(args))
log.info('kwds: %s' % str(kwds))
res = parallel_map(func, *args, **kwds) #XXX: called on ALL nodes ?
if world.rank == 0:
log.info('res: %s' % str(res))
pickle.dump(res, open(outfilename,'w'))
# end of file
