def search_best(self, sample, position, step=(1, 1.0e6), searchrange=[], mpi=False):
"""给定sample，搜索position位置上的最佳值"""
base_sample = copy.copy(sample); best = sample
last_value = None; counter = 0; minvalue = None
#Search all elements in given range (External MPI Routine)
if not mpi:
minvalue = None
for searchitem in searchrange:
base_sample[position] = searchitem
source = global_settings.expand_src(base_sample)
value = self.run_model(source)
self.mpilog.info("[External MPI=%d]: sample=%s, count=%d, value=%g" % (mpi_rank, str(base_sample), counter, value))
#TODO: 根据不同的分布函数的核，这里不一定是minvalue有可能是maxvalue
if minvalue is None or minvalue > value:
minvalue = value
best = copy.copy(base_sample)
#An unlimited search (Internal MPI Routine)
else:
#TODO: 4 is not fixed, should be the length of sample
assert position != 0
f = step[1] if position else step[0]
base_sample[position] = mpi_rank * f if position else 4 + mpi_rank
self.mpilog.debug("My Rank is %d" % mpi_rank)
finished = False
while not finished:
if 1:
source1 = global_settings.expand_src(base_sample)
value = self.run_model(source1)
self.mpilog.info("[Internal MPI=%d]: sample=%s, count=%d, value=%g" % (mpi_rank, str(base_sample), counter, value))
if mpi_rank == 0: #Master Node
valuelist = [(value, base_sample)]
valuelist += map(lambda r: mpi_comm.recv(source=r, tag=9), range(1, mpi_size))
#for rank in range(1, mpi_size):
# valuelist += [mpi_comm.recv(source=rank, tag=9)]
self.mpilog.debug("[MPI Search], valuelist=%s" % str(valuelist))
for value_slave, base_sample_slave in valuelist:
if minvalue is None or minvalue > value_slave:
minvalue = value_slave
best = copy.copy(base_sample_slave)
counter = (counter+1) if minvalue < value_slave else 0
if counter > 40:
finished = True
else: #Slave Node
mpi_comm.send((value, base_sample), dest=0, tag=9)
base_sample[position] += mpi_size * f
finished = mpi_comm.bcast(finished, root=0)
mpi_comm.barrier();
#if position == 0 and base_sample[position] >= 720:
# break;
return (best, minvalue)
def runselftest(case=0):
testsrc = input_info.source_info(test=True)
testmet = input_info.met_info(testsrc, mode=global_settings.MET_FORMAT, dataset=global_settings.METFILE, test=bool(global_settings.METTEST))
print "Reading source data"
ReleaseQ = testsrc.read_rate()
ReleaseQ1 = global_settings.expand_src([90, 141718800.0, 140853300.0, 136447200.0, 130601400.0])
print "Reading met data"
met = testmet.get_met()
## 这里是设置案例编号的地方
if __debug__: print "Case Num: %d" % case
starttime = datetime.now()
logger.info("starttime=%s" % str(datetime.now()))
if case == 0:
model = model_puff_core(testsrc, met)
model.run_point(points=([1140.0,20.0,1.0]), force_no_debug=True)
result = model.point_list
elif case == 1:
model = model_puff_core(testsrc, met)
result = model.run_core_contour(1, False, None, [], False)
model.writefield(result, prefix="conc_field")
elif case == 2:
model = model_puff_core(testsrc, met)
points = [(500,20.0,1.0),(1000,50.0,1.0),(2000,150.0,1.)]
result = model.run_point(points=points, force_no_debug=True)
model.writepoint(result)
elif case == 3:
model = model_puff_corea(testsrc, met)
result = model.run_point(points=[(500,20.0,1.0)], force_no_debug=True)
model1 = model_puff_core(ReleaseQ1, MetField, MetSeq)
result1 = model1.run_point(points=[(500,20.0,1.0)], force_no_debug=True)
from pylab import plot, xlabel, ylabel, grid, show, Rectangle, legend
x = result.values()[0].keys()
y1 = result.values()[0].values()
y2 = result1.values()[0].values()
plot(x,y1,'go-')
plot(x,y2,'bo--')
xlabel(u"时间刻度(10s)")
ylabel(u"浓度(mg/m3)")
p1 = Rectangle((0, 0), 1, 1, fc="g")
p2 = Rectangle((0, 0), 1, 1, fc="b")
legend([p1, p2], [u"真实源", u"反算源"])
show()
logger.info("endtime=%s" % str(datetime.now()))
print "duration=%s" % str(datetime.now() - starttime)
print "Program End Normally"
def plot_debug(result):
import pylab
from pylab import contour, grid, show
contours = (70.9/22.4, 70.9/22.4*3, 70.9/22.4*20)
contour(result, contours)
grid(True)
show()
def runselftest(case=0):
testsrc = input_info.source_info(test=True)
testmet = input_info.met_info(testsrc, mode=global_settings.MET_FORMAT, dataset=global_settings.METFILE, test=bool(global_settings.METTEST))
print "Reading source data"
ReleaseQ = testsrc.read_rate()
ReleaseQ1 = global_settings.expand_src([90, 141718800.0, 140853300.0, 136447200.0, 130601400.0])
print "Reading met data"
met = testmet.get_met()
## 这里是设置案例编号的地方
if __debug__: print "Case Num: %d" % case
starttime = datetime.now()
logger.info("starttime=%s" % str(datetime.now()))
if case == 0:
model = model_puff_core(testsrc, met)
model.run_point(points=([1140.0,20.0,1.0]), force_no_debug=True)
result = model.point_list
elif case == 1:
model = model_puff_core(testsrc, met)
result = model.run_core_contour(1, False, None, [], False)
model.writefield(result, prefix="conc_field")
elif case == 2:
def search_best(self,
sample,
position,
step=(1, 1.0e6),
searchrange=[],
mpi=False):
"""给定sample，搜索position位置上的最佳值"""
base_sample = copy.copy(sample)
best = sample
last_value = None
counter = 0
minvalue = None
#Search all elements in given range (External MPI Routine)
if not mpi:
minvalue = None
for searchitem in searchrange:
base_sample[position] = searchitem
source = global_settings.expand_src(base_sample)
value = self.run_model(source)
self.mpilog.info(
"[External MPI=%d]: sample=%s, count=%d, value=%g" %
(mpi_rank, str(base_sample), counter, value))
#TODO: 根据不同的分布函数的核，这里不一定是minvalue有可能是maxvalue
if minvalue is None or minvalue > value:
minvalue = value
best = copy.copy(base_sample)
#An unlimited search (Internal MPI Routine)
else:
#TODO: 4 is not fixed, should be the length of sample
assert position != 0
f = step[1] if position else step[0]
base_sample[position] = mpi_rank * f if position else 4 + mpi_rank
self.mpilog.debug("My Rank is %d" % mpi_rank)
finished = False
while not finished:
if 1:
source1 = global_settings.expand_src(base_sample)
value = self.run_model(source1)
self.mpilog.info(
"[Internal MPI=%d]: sample=%s, count=%d, value=%g" %
(mpi_rank, str(base_sample), counter, value))
if mpi_rank == 0: #Master Node
valuelist = [(value, base_sample)]
valuelist += map(
lambda r: mpi_comm.recv(source=r, tag=9),
range(1, mpi_size))
#for rank in range(1, mpi_size):
# valuelist += [mpi_comm.recv(source=rank, tag=9)]
self.mpilog.debug("[MPI Search], valuelist=%s" %
str(valuelist))
for value_slave, base_sample_slave in valuelist:
if minvalue is None or minvalue > value_slave:
minvalue = value_slave
best = copy.copy(base_sample_slave)
counter = (counter +
1) if minvalue < value_slave else 0
if counter > 40:
finished = True
else: #Slave Node
mpi_comm.send((value, base_sample), dest=0, tag=9)
base_sample[position] += mpi_size * f
finished = mpi_comm.bcast(finished, root=0)
mpi_comm.barrier()
#if position == 0 and base_sample[position] >= 720:
# break;
return (best, minvalue)
