def run_point(self, points, ticks=None, force_no_debug=False, envelop=False):
"""This function calculate concenrations at ONE given point. Note that point is real position, NOT grid index."""
bOutput = lambda : ((not envelop) and (not ticks is None) and (tick in ticks)) or ((ticks is None or envelop) and (tick % OUTSTEP == 0))
tick = 0
output_tick = []
dest = dict(zip(points, tuple([dict() for i in range(len(points))])))
while tick * TIMESTEP < DURATION:
#判断烟团释放过程是否结束
if tick < len(self.release):
#表示此刻有无烟团释放
if self.release[tick] > 0:
#加入烟团list
self.smoke_list.append(smoke_def(self.release[tick], self.met, tick, pos=(0.0, 0.0, self.src_height)))
if bOutput():
if __debug__ and (not force_no_debug):
print "current time-tick is %d" % tick
map(smoke_def.walk, self.smoke_list)
if bOutput():
diffc = []; mass = []; stab = []; pos = [];
#In point mode, we just record all smokes down here and calculated
for smoke in filter(lambda x:not x.invalid, self.smoke_list):
pos += list(smoke.pos)
#计算扩散系数
diffc += list(smoke.diffusion_coefficents(int(smoke.curr_met[3]), smoke.walkinglength, smoke.windspeed))
mass.append(smoke.mass)
for point in points:
if mass:
X,Y,Z = point
PI = math.pi
POSX, POSY, POSZ = numpy.array(pos[0::3]).astype(numpy.float32), numpy.array(pos[1::3]).astype(numpy.float32), numpy.array(pos[2::3]).astype(numpy.float32)
DIFFX, DIFFZ = numpy.array(diffc[0::2]).astype(numpy.float32), numpy.array(diffc[1::2]).astype(numpy.float32)
MASS = numpy.array(mass).astype(numpy.float32)
temp_conc = numexpr.evaluate("sum(MASS / ((2*PI)**1.5*DIFFX*DIFFX*DIFFZ) * exp(-0.5*((X-POSX)/DIFFX)**2) * exp(-0.5*((Y-POSY)/DIFFX)**2) * (exp(-0.5*((Z-POSZ)/DIFFZ)**2) + exp(-0.5*((Z+POSZ)/DIFFZ)**2)))")
dest[point][tick] = temp_conc
else:
dest[point][tick] = 0
tick += 1
return dest
def run_core_contour(self, receipter_height=1, envelop=False, ticks=None, loc=[], force_no_debug=False):
"""
Three modes are defined in core_contour funtion:
1 contour mode [default] -> compute contours every tick
2 given time mode [set ticks parameter] -> only compute contours at given ticks
3 envelop mode [set envelop=True and give LOCs] -> override Mode 1 and 2, compute contours in Mode 1 and generate envelops based on given LOCs
"""
#计算包络线覆盖区域
make_envelop = lambda r, loc: numexpr("sum(where(r>loc,1,0),0)")
#判断当前时刻是否需要计算浓度
bOutput = lambda : ((not envelop) and (not ticks is None) and (tick in ticks)) or ((ticks is None or envelop) and (tick % OUTSTEP == 0))
#是否使用GPU计算
bUseGPU = not cuda_disabled
self.isRunning = True
result_list = []
output_tick = []
tick = 0
#Total Estimation Time is DURATION seconds
while tick * TIMESTEP < DURATION:
#烟团释放过程未结束并且此刻烟团质量大于0则加入烟团列表
if tick < len(self.release) and self.release[tick] > 0:
self.smoke_list.append(smoke_def(self.release[tick], self.met, tick, pos=(0.0, 0.0, self.src_height)))
#追踪当前每个烟团的位置，并且计算浓度场
if filter(lambda x:not x.invalid, self.smoke_list):
map(smoke_def.walk, self.smoke_list)
if bOutput():
empty_conc_matrix = numpy.zeros_like(CentralPositionMatrixX)
gdiffc = []; gmass = []; gpos = [];
for smoke in filter(lambda x:not x.invalid, self.smoke_list):
#if we use cpu, we compute each concentration field inside the loop
if not bUseGPU:
X, Y, Z = smoke.pos
mass = smoke.mass
#计算扩散系数
diffc = smoke.diffusion_coefficents(int(smoke.curr_met[3]), smoke.walkinglength, smoke.windspeed)
x, z = diffc; y = x
PI = math.pi
height = receipter_height
empty_conc_matrix = numexpr.evaluate("empty_conc_matrix + (mass/((2*PI)**1.5*x*y*z)*exp(-0.5*((CentralPositionMatrixX-X)/x)**2)*exp(-0.5*((CentralPositionMatrixY-Y)/y)**2)*(exp(-0.5*((Z-height)/z)**2) + exp(-0.5*((Z+height)/z)**2)))")
#otherwise, we just record each smoke and submit them to gpu once for all.
else:
gpos += list(smoke.pos)
#计算扩散系数
gdiffc += list(smoke.diffusion_coefficents(int(smoke.curr_met[3]), smoke.walkinglength, smoke.windspeed))
gmass.append(smoke.mass)
#Submit job to kernel.
if bUseGPU and len(gmass) > 0:
dest = run_gpu_conc(pos=numpy.array(gpos).astype(numpy.float32), diffc=numpy.array(gdiffc).astype(numpy.float32), mass=numpy.array(gmass).astype(numpy.float32),
height=receipter_height, GRID_WIDTH=GRID_SIZE, gridw=GRID_INTERVAL, smoke_count=len(gmass))
empty_conc_matrix = dest.reshape((GRID_SIZE,GRID_SIZE), order='C')
result_list.append(empty_conc_matrix)
output_tick.append(tick)
self.cpulog.debug("current time-tick is %d" % tick)
tick += 1
#Post process: return envelops or fields
if envelop:
envelop_list = []
for l in loc:
envelop_list.append(make_envelop(result_list, l))
final_result = dict(zip(loc, envelop_list))
else:
final_result = dict(zip(output_tick, result_list))
self.isRunning = False
return final_result