def __init__(self, G=None, vis=True, anim=False, head='BC',nCranes=2,series=None, bundler=False, twigCrack=False, observer=False): SimExtend.__init__(self,G, vis, anim, animDelay=1.2,series=series) #does some common stuff, e.g. seed #if no file to read the simulationsparameters from: setDefaultThinningParams(self.G.simParam) #sets the parameters to default values if not self.G.terrain: self.G.areaPoly=[(0,0), (25,0), (25,40), (0,40)] #default for thinning files. self.G.terrain=Terrain(G=self.G) self.G.terrain.readTrees(thinning=True) craneMax=self.G.simParam['maxCraneLength'] startPos=[random.uniform(craneMax, 25-craneMax), -4] self.m=ThinningMachine(name="thinny", sim=self, G=self.G, head=head, nCranes=nCranes,startPos=startPos, bundler=bundler,twigCrack=twigCrack) self.treeStats() #do some statistics on the trees self.activate(self.m,self.m.run()) if observer: self.o=Observer(name="obsy", sim=self, G=self.G) self.activate(self.o, self.o.run()) self.simulate(until=10000) #some simulation information: if observer: self.timeStats() """ print self.o.tstep*sum([c[1] for c in self.o.lAMoni]), 'left head active time via monitor' print self.o.tstep*sum([c[1] for c in self.o.lWBMoni]), 'left head waiting for Bundler' print self.stats['oneCraneWorkTime'], 'one crane work time' print self.stats['oneCraneWaitDriverTime'], 'one crane wait for driver time' if self.m.hasBundler: print self.stats['oneCraneWaitBundlerTime'], 'one crane wait for bundler time' if len(self.m.heads)==2: print self.o.tstep*sum([c[1] for c in self.o.rAMoni]), 'right head active time via monitor' print self.o.tstep*sum([c[1] for c in self.o.rWBMoni]), 'right head waiting for Bundler' print self.stats['twoCranesWorkTime'], 'two cranes work time' print self.stats['twoCranesWaitDriverTime'], 'two cranes wait for driver time' if self.m.hasBundler: print self.stats['twoCranesWaitBundlerTime'], 'two cranes wait for bundler time' """ self.stats['productivity']=len(self.m.trees)/self.now()*3600 self.stats['outTake']=100*len(self.m.trees)/float(len(self.G.terrain.trees)) self.stats['groundAreaRatio']=sum([t.dbh**2*pi*0.25 for t in self.m.trees])/max(1,sum([t.dbh**2*pi*0.25 for t in self.G.terrain.trees])) print "Simulation ended. Productivity: %.1f trees/hour. %.1f %% of the trees were harvested"%(len(self.m.trees)/self.now()*3600, self.stats['outTake']) print "average trees per corridor: %f average log weight in corridor: %f trees in main road: %f"%(self.avTreesPerCorr, self.avCorrTreeWeight, self.treesPerRoad) self.setQueuePerc() print self.getGeneralStatsString() if self.p: #plot self.p.terminate() if vis: plt.show()
class ThinningSim(SimExtend):
"""
class for a single simulation with a 1a or 2a thinning machine
"""
def __init__(self, G=None, vis=True, anim=False, head='BC',nCranes=2,series=None, bundler=False, twigCrack=False, observer=False):
SimExtend.__init__(self,G, vis, anim, animDelay=1.2,series=series) #does some common stuff, e.g. seed
#if no file to read the simulationsparameters from:
setDefaultThinningParams(self.G.simParam) #sets the parameters to default values
if not self.G.terrain:
self.G.areaPoly=[(0,0), (25,0), (25,40), (0,40)] #default for thinning files.
self.G.terrain=Terrain(G=self.G)
self.G.terrain.readTrees(thinning=True)
craneMax=self.G.simParam['maxCraneLength']
startPos=[random.uniform(craneMax, 25-craneMax), -4]
self.m=ThinningMachine(name="thinny", sim=self, G=self.G, head=head, nCranes=nCranes,startPos=startPos, bundler=bundler,twigCrack=twigCrack)
self.treeStats() #do some statistics on the trees
self.activate(self.m,self.m.run())
if observer:
self.o=Observer(name="obsy", sim=self, G=self.G)
self.activate(self.o, self.o.run())
self.simulate(until=10000)
#some simulation information:
if observer:
self.timeStats()
"""
print self.o.tstep*sum([c[1] for c in self.o.lAMoni]), 'left head active time via monitor'
print self.o.tstep*sum([c[1] for c in self.o.lWBMoni]), 'left head waiting for Bundler'
print self.stats['oneCraneWorkTime'], 'one crane work time'
print self.stats['oneCraneWaitDriverTime'], 'one crane wait for driver time'
if self.m.hasBundler:
print self.stats['oneCraneWaitBundlerTime'], 'one crane wait for bundler time'
if len(self.m.heads)==2:
print self.o.tstep*sum([c[1] for c in self.o.rAMoni]), 'right head active time via monitor'
print self.o.tstep*sum([c[1] for c in self.o.rWBMoni]), 'right head waiting for Bundler'
print self.stats['twoCranesWorkTime'], 'two cranes work time'
print self.stats['twoCranesWaitDriverTime'], 'two cranes wait for driver time'
if self.m.hasBundler:
print self.stats['twoCranesWaitBundlerTime'], 'two cranes wait for bundler time'
"""
self.stats['productivity']=len(self.m.trees)/self.now()*3600
self.stats['outTake']=100*len(self.m.trees)/float(len(self.G.terrain.trees))
self.stats['groundAreaRatio']=sum([t.dbh**2*pi*0.25 for t in self.m.trees])/max(1,sum([t.dbh**2*pi*0.25 for t in self.G.terrain.trees]))
print "Simulation ended. Productivity: %.1f trees/hour. %.1f %% of the trees were harvested"%(len(self.m.trees)/self.now()*3600, self.stats['outTake'])
print "average trees per corridor: %f average log weight in corridor: %f trees in main road: %f"%(self.avTreesPerCorr, self.avCorrTreeWeight, self.treesPerRoad)
self.setQueuePerc()
print self.getGeneralStatsString()
if self.p: #plot
self.p.terminate()
if vis: plt.show()
def timeStats(self):
""" observe that this method performs the statcalculations on the
times and sets the values to self.s.stats"""
noCWforBundler=0
noCWforBundlerTwo=0
if self.m.hasBundler:
self.stats['bundlingTime']=self.o.tstep*sum([c[1] for c in self.o.bundlerActiveMoni])# 'active bundler time via monitor'
else: self.stats['bundlingTime']=0
if len(self.m.heads)==1:
self.stats['oneCraneWorkTime']=self.o.tstep*sum([c[1] for c in self.o.lAMoni])
self.stats['oneCraneWaitDriverTime']=self.o.tstep*sum([c[1] for c in self.o.lWDMoni])
self.stats['oneCraneWaitBundlerTime']=self.o.tstep*sum([c[1] for c in self.o.lWBMoni])
self.stats['twoCranesWorkTime']=0
self.stats['twoCranesWaitDriverTime']=0
self.stats['twoCranesWaitBundlerTime']=0
for i in range(len(self.o.lWBMoni)-1):
if self.o.lWBMoni[i][1]==0 and self.o.lWBMoni[i+1][1]==1: noCWforBundler+=1
self.stats['noCraneWaitings']=noCWforBundler
self.stats['noCraneWaitingsTwo']=noCWforBundlerTwo
elif len(self.m.heads)==2:
for i in range(len(self.o.lWBMoni)-1):
if self.o.lWBMoni[i][1]==0 and self.o.lWBMoni[i+1][1]==1: noCWforBundler+=1
if self.o.rWBMoni[i][1]==0 and self.o.rWBMoni[i+1][1]==1: noCWforBundler+=1
self.stats['noCraneWaitings']=noCWforBundler
lAMoni=np.array(self.o.lAMoni)
rAMoni=np.array(self.o.rAMoni)
#t=lAMoni[:,[0]]#takes the times into one array
addedActivity=lAMoni[:,[1]]+rAMoni[:,[1]]
addedActivityTwo=copy.deepcopy(addedActivity)
for i in range(len(addedActivity)):
if addedActivity[i]==2: addedActivity[i]=0
if addedActivityTwo[i]==1: addedActivityTwo[i]=0
elif addedActivityTwo[i]==2: addedActivityTwo[i]=1
self.stats['oneCraneWorkTime']=float(self.o.tstep*sum(addedActivity))
self.stats['twoCranesWorkTime']=float(self.o.tstep*sum(addedActivityTwo))
lWDMoni=np.array(self.o.lWDMoni)
rWDMoni=np.array(self.o.rWDMoni)
addedWD=lWDMoni[:,[1]]+rWDMoni[:,[1]]
addedWDTwo=copy.deepcopy(addedWD)
for i in range(len(addedWD)):
if addedWD[i]==2: addedWD[i]=0
if addedWDTwo[i]==1: addedWDTwo[i]=0
elif addedWDTwo[i]==2: addedWDTwo[i]=1
self.stats['oneCraneWaitDriverTime']=float(self.o.tstep*sum(addedWD))
self.stats['twoCranesWaitDriverTime']=float(self.o.tstep*sum(addedWDTwo))
lWBMoni=np.array(self.o.lWBMoni)
rWBMoni=np.array(self.o.rWBMoni)
addedWB=lWBMoni[:,[1]]+rWBMoni[:,[1]]
addedWBTwo=copy.deepcopy(addedWB)
for i in range(len(addedWB)):
if addedWB[i]==2: addedWB[i]=0
if addedWBTwo[i]==1: addedWBTwo[i]=0
elif addedWBTwo[i]==2: addedWBTwo[i]=1
for i in range(len(addedWBTwo)-1):
if addedWBTwo[i]==0 and addedWBTwo[i+1]==1: noCWforBundlerTwo+=1
self.stats['noCraneWaitingsTwo']=noCWforBundlerTwo
self.stats['oneCraneWaitBundlerTime']=float(self.o.tstep*sum(addedWB))
self.stats['twoCranesWaitBundlerTime']=float(self.o.tstep*sum(addedWBTwo))
else: raise Exception('Some error in number of heads in timeStats()')
def treeStats(self):
"""
calculates some statistics.. should maybe be done in terrain class instead?
"""
trees=float(len(self.G.terrain.trees))
self.saveGeneralStats("stand no", self.G.terrain.treeFile, "-") #see simSeries for how it works..
self.saveGeneralStats("trees", trees, "-")
if trees==0: return None
self.saveGeneralStats("pine percentage", 100*len([t for t in self.G.terrain.trees if t.specie=='pine'])/trees, "%")
self.saveGeneralStats("spruce percentage", 100*len([t for t in self.G.terrain.trees if t.specie=='spruce'])/trees, "%")
self.saveGeneralStats("leaf tree percentage", 100*len([t for t in self.G.terrain.trees if t.specie=='leaf'])/trees, "%")
treeDensity=trees/self.G.terrain.area
self.saveGeneralStats("tree density", treeDensity, "trees/m2")
mLogs=len(self.m.mainRoadTrees)
mNum=0
cLogs=len(self.m.corridorTrees)
cNum=0
for r in self.m.roadList:
if r.radius>2*self.m.craneMaxL/2.+2: #main road.
mNum+=1
else:
cNum+=1
self.cNum=cNum
self.mNum=mNum
self.mLogs=mLogs
self.cLogs=cLogs
cWeight=sum([t.logWeight for w in self.m.corridorTrees ])
mWeight=sum([t.logWeight for w in self.m.corridorTrees ])
print "number of main roads:", mNum, "number of corridors:", cNum
if cNum==0: self.avTreesPerCorr=0
else: self.avTreesPerCorr=cLogs/float(cNum)
self.treesPerRoad=mLogs
if cLogs==0: self.avCorrTreeWeight=0
else: self.avCorrTreeWeight=cWeight/float(cNum)
if mLogs==0: self.avRoadTreeWeight=0
else: self.avRoadTreeWeight=mWeight/float(mNum) #the cumulative sum
#clustering... see Clark and Evans 1954
rexp=0.5*1/(sqrt(treeDensity)) #expected r
robs=0
for t in self.G.terrain.trees:
tmp=[]
R=5
while len(tmp)==0 and R<sqrt(self.G.terrain.area): #in 99.9% of the cases, this loop only runs once.
#we are not using self.G.terrain.trees for speedup reasons.
tmp=self.G.terrain.GetTrees(t.pos, R)
R+=2
if len(tmp)==0:
self.saveGeneralStats("clustering agg. index", "no trees", "trees/m2")
break
shortest=1e10
for treeTmp in tmp:
if treeTmp==t: continue #same tree
d=fun.getDistance(t.pos, treeTmp.pos)
if d<shortest: shortest=d
if shortest==1e10: raise Exception('could not find shortest tree...')
robs+=shortest
robs/=trees
print "rexp:", rexp, "robs.", robs
aggregationIndex=robs/rexp
self.saveGeneralStats("clustering agg. index", aggregationIndex, "-")
def plotMoni(self, ax, number):
tcap=50
tmin=-0.1
if self.now()<tcap: t=tcap
else:
if self.now()-tmin>400: tmin=self.now()-400
t=self.now()
if number==1: #plot driver activity
driver=self.m.driver
moni=driver.actMon
if len(moni)>0:
ax.plot(moni.tseries(),moni.yseries(), drawstyle='steps-post')
ax.axis([tmin, t, -0.1, 1.2])
ax.grid(True)
ax.set_ylabel('Working pattern')
ax.set_yticks((0, 1))#, ('idle', 'busy'))#, color = 'k')
elif number==2: #plot driver waiting queue
moni=self.m.driver.waitMon
if len(moni)>0:
maxt=int(max(moni.yseries()))
ticks=[]
for i in range(maxt+1): ticks.append(i)
ax.set_yticks(tuple(ticks))
ax.plot(moni.tseries(),moni.yseries(), drawstyle='steps-post')
ax.axis([tmin, t, -0.1, max(moni.yseries())+0.1])
ax.grid(True)
ax.set_ylabel('Wait queue for driver.')
elif number==3: #plot trees planted
moni=self.m.treeMoni
#trees planted
if len(moni)>0:
ax.plot(moni.tseries(),moni.yseries(), drawstyle='steps-post')
ax.axis([-0.1, t, -0.1, (max(moni.yseries())+1)])
ax.grid(True)
ax.set_xlabel('time(s)')
ax.set_ylabel('trees harvested')
return ax
