def init_agents():
global agents, nAgents, square, circle, avgInput, \
nAgentsWht, nAgentsBlk, nAgentsOth, avgInput
totInput = 0.
## for each agent
for agtId in range(nAgents):
#
writelog.write("agtId = %d\n"%agtId)
newAgent = init_agent(agtId)
# Append to agents list
agents.append(newAgent)
totInput += newAgent['iVal']
avgInput = totInput/float(nAgents)
# Service provider square and 2 sigma range
square = plt.Rectangle((axes.provXOrg, axes.provYOrg),
axes.provSize, axes.provSize, fc=(0,1,0), ec='k')
axes.ax.add_patch(square)
# Dist feature sigma radius dashed circle
circle = plt.Circle((axes.provXOrg, axes.provYOrg), radius=rSigma, ec='r',
fc='none', linestyle='dashed', visible=axes.checkDist)
axes.ax.add_patch(circle)
def printSched():
for indx, entry in enumerate(schedList):
outStr=StringIO.StringIO()
outStr.write(' %3d: ['%entry[0])
# outStr.write(' %3d: %s ['%(entry[0], ststr)) # Duplicate line?
for tr in range(1,standardSched+1):
if entry[tr] == None:
outStr.write(' ~ ')
else:
outStr.write('%4.2f '%entry[tr])
outStr.write(']\n')
writelog.write(outStr.getvalue())
outStr.close()
def printSched(schedList):
for indx, entry in enumerate(schedList):
outStr=StringIO.StringIO()
outStr.write(' %3d: ['%entry[0])
outStr.write(' %3d: ['%entry[0])
for tr in range(1,agents.standardSched+1):
if entry[tr] == None:
outStr.write(' ~ ')
else:
outStr.write('%4.2f '%entry[tr])
outStr.write(']\n')
writelog.write(outStr.getvalue())
outStr.close()
def init_agents():
global agents, nAgents, square, circle, \
agencyList, nAgencies, \
nAgentsWht, nAgentsBlk, nAgentsOth, avgInput
global dataFileName
print '*****[ In init_agents() ]*****'
totInput = 0.
## for each agent
for agtId in range(nAgents):
#
if doingLogging:
writelog.write("agtId = %d\n"%agtId)
# start = time.time()
#print ' init_agent(%d) '%agtId
newAgent = init_agent(agtId)
# end = time.time()
# elapsed = end - start
# (min_, sec) = divmod(elapsed, 60)
# (hr, min_) = divmod(min_, 60)
# print ' elapsed time = %02d:%02d:%02d'%(hr, min_, sec)
# Append to agents list
agents.append(newAgent)
totInput += newAgent['iVal']
avgInput = totInput/float(nAgents)
if axes.checkStepped:
dataFileName = 'Sp19Stepped.dat'
else:
dataFileName = 'Sp19.dat'
if os.path.exists(dataFileName):
os.remove(dataFileName)
def printSched(agcy):
schedList = agcy['schedList']
name = agcy['name']
abbrev = agcy['abbrev']
boro = agcy['boro']
writelog.write('========[ '+name+' ('+abbrev+') in '+boro+' ]========\n')
for indx, entry in enumerate(schedList):
outStr=StringIO.StringIO()
if entry[1]:
stateStr = 'X'
else:
stateStr = ' '
outStr.write(' %3d: %s ['%(entry[0], stateStr))
for tr in range(2,standardSched+2):
if entry[tr] == None:
outStr.write(' ~ ')
else:
outStr.write('%4.2f '%entry[tr])
outStr.write(']\n')
writelog.write(outStr.getvalue())
outStr.close()
def on_pick(event):
for boro in agencies.agenciesList:
found = False
for agcy in agencies.agenciesList[boro]:
if agcy['square'] is event.artist:
found = True
agencies.selected['square'].set_lw(1)
agencies.selected['square'].set_ec('k')
agencies.selected = agcy
agcy['square'].set_lw(4)
agcy['square'].set_ec('r')
if agencies.selected['tileArray'] == []:
agents.initTileArray(agencies.selected)
agents.updateTileArray(agencies.selected)
axes.schedTitle.set_text(boro+': '+agcy['abbrev']+' '+agcy['name'])
axes.fig.canvas.draw()
break
if found == True:
break
if agents.doingLogging:
writelog.write('In on_pick(): selected is now %s %s %s\n'%(
agencies.selected['boro'], agencies.selected['abbrev'], agencies.selected['name']))
lastT = 0.
dt = 1
dArray = deque([0.])
tArray = deque([0.])
plotWidth = 500
isFemale = 0
isYoung = 1
race = 'white'
ethn = 'hispanic'
income = 'lowrange'
hadStressors = 0
nSandyTraumas = 0
PTSD_sx = 0
writelog.init('PTSD_Combo1.log')
writelog.write('sex \t age \t race \t ethn \t\t income \t hadStr nSandTr exp(P)\n')
writelog.write('=== \t === \t ==== \t ==== \t\t ====== \t ====== ======= ======\n\n')
plt.close('all')
fig = plt.figure(figsize=(12,6))
fig.canvas.set_window_title('PTSD_Distribution.py')
# Create axes boxes in a linspace xorg line
xorg = np.linspace(.05,.9,7)
axSex = plt.axes([xorg[0],.6,.08,.2]); axSex.set_title('Sex')
axAge = plt.axes([xorg[1],.6,.08,.2]); axAge.set_title('Age')
axRace = plt.axes([xorg[2],.6,.08,.2]); axRace.set_title('Race')
axEthn = plt.axes([xorg[3],.6,.08,.2]); axEthn.set_title('Ethn')
axIncome = plt.axes([xorg[4],.6,.08,.2]); axIncome.set_title('Income')
axStress = plt.axes([xorg[5],.6,.08,.2]); axStress.set_title('Stress')
axTrauma = plt.axes([xorg[6],.6,.08,.2]); axTrauma.set_title('Trauma')
def update_agent(agent):
global nEnrolled, schedList, schedPtr
# print ' In update_agent agent = %r'%agent
if doingLogging:
writelog.write('In update_agent %3d\n'%agent['id'])
writelog.write(re.sub(r',', '\n', '%r\n'%agent))
xVal = agent['xVal']
inputVal = agent['iVal']
# If service is on, service the agents
if axes.checkService:
#square.set_fc('#00ff00')
########[ Enrollment Test ]#########
# If not scheduled for treatment consider enrolling
if not agent['enrolled']:
# Shuffle agency list every time
boroName = agent['boroName']
if doingLogging:
writelog.write(' Searching through agencies in '+boroName+'\n')
#shuffledList = sample(agencies.agenciesList[boroName], listLen)
############# Loop through agencies in borough here ######################
#### For each agency in this borough
for agcy in agencies.agenciesList[boroName]:
abbrev = agcy['abbrev']
(agcyXLoc, agcyYLoc) = agcy['loc']
(xLoc, yLoc) = (agent['xLoc'], agent['yLoc'])
# Calculate probability of enrollment based on need
need = max(( avgInput - xVal),0.) * needFactor
probEnroll = need * (agcy['maxEnrolled'] - agcy['numEnrolled'])
if useProbCBTprobEnroll:
print 'WARNING: useProbCBTprobEnroll TRUE but not implemented.'
if doingLogging:
writelog.write(' agt %3d need = %4.2f numEnrolled = %4.2f probEnroll["%s"] = %5.2f xVal = %5.2f\n'%(
agent['id'], need, agcy['numEnrolled'], abbrev.ljust(8), probEnroll, xVal))
########[ Need Test ]########
# If enroll probability exceeds random threshold then enroll
if probEnroll > random():
if doingLogging:
writelog.write(' probEnroll > random: Enroll!\n')
agent['enrolled'] = True
agent['agency'] = agcy
agcy['numEnrolled'] += 1
# Define agent's bezier links to that agency
if axes.checkGraphics:
verts = ((agcyXLoc, agcyYLoc), # Bezier lnk from prov. to here
((agcyXLoc + xLoc)/2., agcyYLoc),
(xLoc, (agcyYLoc + yLoc)/2.),
(xLoc, yLoc))
bezPath = Path(verts, codes)
bezPatch = mpatches.PathPatch(bezPath, facecolor='none',
lw=1, ec='#afafaf', visible=True)
axes.ax.add_patch(bezPatch)
agent['bezPatch'] = bezPatch
agent['idText'].set_visible(True)
inputVal = agent['iVal']
# Register in schedList[]
if doingLogging:
writelog.write('About to register in schedList\n')
writelog.write(' Enrolling agent %d in agency %s\n'%(agent['id'], agcy['abbrev']))
treatList = [None for i in range(standardSched)]
treatList[agent['treatNo']] = agent['xVal']
treatList.insert(0, agent['isComplex'])
treatList.insert(0,agent['id'])
agcy['schedList'].append(treatList)
#agcy['schedList'] = treatList
#schedNo = len(agcy['schedList']) -1
# update schedule
if axes.checkGraphics and agcy is agencies.selected:
updateTileArray(agcy)
if doingLogging:
printSched(agcy)
break
############# End Loop through agencies in borough ######################
# Otherwise if already enrolled compute input treatment
else:
# If agent not accepting of CBT then un-enroll
if agent['acceptCBT'] < random():
agent['treating'] = False;
if axes.checkGraphics:
agent['bezPatch'].set_lw(1)
agent['bezPatch'].set_ec('#afafaf')
inputVal = agent['iVal']
if doingLogging: writelog.write(' agent %d acceptCBT < random() treatment %d OFF\n'%
(agent['id'], agent['treatNo']))
# Otherwise if accepting
elif random() > .25: # Randomize every other time to break sync
# If agent not being treated do next treatment
if agent['treating'] == False:
if doingLogging:
writelog.write(' agent %d treatment %d ON\n'%(agent['id'],
agent['treatNo']))
agent['treating'] = True
(provXCtr, provYCtr) = agent['agency']['loc']
if axes.checkGraphics:
agent['bezPatch'].set_lw(2)
agent['bezPatch'].set_ec('#00ff00')
# Turn on input
if axes.checkEndBen:
agent['iVal'] += doseValue*agent['iFact']/10. # endBen increase iVal
else:
inputVal = agent['iVal'] + doseValue * agent['iFact']
# Increment treatment number
agent['treatNo'] += 1
if axes.checkStepped and not agent['isComplex']:
nTreatLeft = steppedSched + 1
else:
nTreatLeft = standardSched + 1
########[ COMPLETION TEST ]#######
# If treatment done then un-enroll
if agent['treatNo'] >= nTreatLeft:
if doingLogging:
if axes.checkStepped and not agent['isComplex']:
writelog.write(' treatNo = %d steppedSched = %d\n'%
(agent['treatNo'], steppedSched))
else:
writelog.write(' treatNo = %d standardSched = %d\n'%
(agent['treatNo'], standardSched))
writelog.write('Un-enroll agent %d treatment done\n'%
agent['id'])
agent['enrolled'] = False
agent['treatNo'] = 0
agent['agency']['numEnrolled'] -= 1
if axes.checkGraphics:
agent['bezPatch'].remove()
agent['idText'].set_visible(False)
for entry in agent['agency']['schedList']:
if entry[0] == int(agent['id']):
agent['agency']['schedList'].remove(entry)
#break
# Else if already treating turn treatment off, pipeline gray
else:
for indx, sched in enumerate(agent['agency']['schedList']):
if sched[0] == int(agent['id']):
agent['agency']['schedList'][indx][agent['treatNo']+1] = agent['xVal']
#break
if doingLogging: writelog.write(' agent %d treatment %d ON\n'%
(agent['id'], agent['treatNo']+1))
# Otherwise if patient being treated turn it off
else:
agent['treating'] = False;
if axes.checkGraphics:
agent['bezPatch'].set_lw(1)
agent['bezPatch'].set_ec('#afafaf')
inputVal = agent['iVal']
if doingLogging: writelog.write(' agent %d treatment %d OFF\n'%
(agent['id'], agent['treatNo']))
# Update schedule
#schedNo = len(agcy['schedList']) -1
#print '#### schedNo = %d'%schedNo
if agent['agency']:
if axes.checkGraphics and agent['agency'] is agencies.selected:
updateTileArray(agent['agency'])
if doingLogging:
printSched(agent['agency'])
# schedList = [x for x in schedList if x[0] != agent['id']]
# Else if service is off, shut off treatment
else:
if agent['bezPatch']:
if axes.checkGraphics:
agent['bezPatch'].set_visible(False)
inputVal = agent['iVal'] * agent['iFact']
# Shunting equation
xVal += -A * xVal + (1 - xVal) * inputVal
if xVal < 0.:
xVal = 0.
elif xVal > 1.:
xVal = 1.
agent['xVal'] = xVal
if axes.checkGraphics:
if xVal > visThresh:
agent['circ1'].set_visible(False)
else:
agent['circ1'].set_visible(True)
r = (1. - xVal)
g = xVal
if axes.checkGraphics:
agent['circ1'].set_facecolor((r, g, 0.))
# Time delay
if delay > 0.:
time.sleep(delay)
def init_agent(agtId):
global nEnrolled, schedList, schedPtr
global agents, nAgents, square, circle, \
nAgentsWht, nAgentsBlk, nAgentsOth
global agencyList, nAgencies
if doingLogging:
writelog.write('In init_agent(%3d)'%agtId)
foundSpace = False
while not foundSpace:
xLoc = random() * image.aspect + .1*image.aspect
yLoc = random()
#writelog.write("agtId: % 3d xLoc, yLoc = (%4.2f, %4.2f)\n"%(agtId, xLoc, yLoc))
inMask = image.maskImg[image.imgYSize - yLoc * image.imgYSize,
(xLoc-image.xOff)*image.imgXSize/image.aspect + image.xOff][0]
boroIndx = int(image.burrIndx[image.imgYSize - yLoc * image.imgYSize,
(xLoc-image.xOff)*image.imgXSize/image.aspect + image.xOff])
if boroIndx > 0:
boroIndx -= 1
#print 'agent %3d loc (%4.2f, %4.2f) boroIndex %3d'%(agtId, xLoc, yLoc, boroIndx)
#print 'boro[boroindx] = %s'%agencies.boroughsList[boroIndx-1]
boroName = agencies.boroughsList[boroIndx-1]
if doingLogging:
writelog.write(" agtId: % 3d xLoc, yLoc = (%4.2f, %4.2f) boro %s boroIndx = %3d\n"%(
agtId, xLoc, yLoc, boroName, boroIndx))
# if inMask > .5 and boroIndx in range(1,6): # If in the masked area check for collision
if inMask > .9: # If in the masked area check for collision
if doingLogging:
writelog.write(' In boroIndx %3d\n'%boroIndx)
collision = False
for agt in range(len(agents)):
xLoc1 = agents[agt]['xLoc']
yLoc1 = agents[agt]['yLoc']
dx = xLoc1 - xLoc
dy = yLoc1 - yLoc
dist = np.sqrt(dx**2 + dy**2)
if dist < minSep:
collision = True
if doingLogging:
writelog.write(" COLLISION !!!\n")
break # Stop going through more agents
if not collision:
foundSpace = True
if doingLogging:
writelog.write(" foundSpace!\n")
writelog.write(" agtId: % 3d xLoc, yLoc = (%4.2f, %4.2f) boro %s boroIndx = %3d\n"%(
agtId, xLoc, yLoc, boroName, boroIndx))
# Otherwise keep searching
# Define agent's race and ethnicity
(income, age, sex, race, ethncy) = probDemographics(boroIndx)
#print 'boroIndx = %d, income = %s, age = %s, sex = %s, race = %s, ethncy = %s'%(boroIndx, income, age, sex, race, ethncy)
#(race, ethncy) = probRaceEthncy(boroIndx)
if race == 'White':
#raceColor = 'w'
isWhite = 1.
isBlack = 0.
isOther = 0.
nAgentsWht += 1
elif race == 'Black':
#raceColor = 'k'
isWhite = 0.
isBlack = 1.
isOther = 0.
nAgentsBlk += 1
elif race == 'Other':
#raceColor = 'gray'
isWhite = 0.
isBlack = 0.
isOther = 1.
nAgentsOth += 1
if ethncy == 'Hispanic':
#ethVis = True
isHisp = 1.
else:
#ethVis = False
isHisp = 0.
# Define agent's gender
if sex == 'Female':
gender = 'Female'
isFemale = 1.
isMale = 0.
else:
gender = 'Male'
isMale = 1.
isFemale = 0.
# Define agent's age
if age == 'Old':
isOld = 1.
isYoung = 0.
else:
isOld = 0.
isYoung = 1.
# Define agent's hadPrior (PTSD)
if random() > .9:
hadPrior = 1.
else:
hadPrior = 0.
# Define agent's hadStressors (from Hurricane Sandy)
if random() > .9:
hadStressors = 1.
else:
hadStressors = 0.
# Define agent's hadTrauma (from Hurricane Sandy)
if random() > .9:
hadTrauma = 1.
else:
hadTrauma = 0.
# Additional coefficients for calculate_nSymptoms()
isWhiteHisp = 0.
isBlackNonHisp = 0.
isBlackHisp = 0.
isOtherNonHisp = 0.
isOtherHisp = 0.
if race == 'White' and ethncy == 'Hispanic':
isWhiteHisp = 1.
elif race == 'Black':
if ethncy == 'NonHisp':
isBlackNonHisp = 1.
elif ethncy == 'Hisp':
isBlackHisp = 1.
elif race == 'Other':
if ethncy == 'NonHisp':
isOtherNonHisp = 1.
elif ethncy == 'Hisp':
isOtherHisp = 1.
if income == 'Low':
isIncomeLow = 1.
isIncomeMed = 0.
elif income == 'Medium':
isIncomeLow = 0.
isIncomeMed = 1.
elif income == 'High':
isIncomeLow = 0.
isIncomeMed = 0.
# Define agent's number of PTSD symptoms
nSymptoms = calculate_nSymptoms(isFemale, isYoung, isOld, isWhiteHisp,
isBlackNonHisp, isBlackHisp, isOtherNonHisp,
isOtherHisp, isIncomeLow, isIncomeMed,
hadStressors, hadTrauma)
# Calculate random value
randVal = random()
#print ' randVal: %5.2f nSymptoms: %5.2f'%(randVal, nSymptoms)
# Define agent's "input value" (natural wellness) and input factor
if useCalcNSymptoms:
iVal = (1. - nSymptoms) ** boost #<===KLUDGE!
if doingLogging:
writelog.write(' iVal = nSymptoms = %f\n'%iVal)
else:
iVal = randVal
if doingLogging:
writelog.write(' iVal = random() = %f\n'%iVal)
print ' agent(%3d) iVal: %5.2f nSymptoms: %5.2f'%(agtId, randVal, nSymptoms)
if iVal > iThresh:
iFact = 1.
isComplex = False
cmplxColor = 'k'
else:
if random() > .5:
iFact = 1.
isComplex = False
cmplxColor = 'k'
else:
iFact = 0.7
isComplex = True
cmplxColor = 'r'
# Define agent's probability of accepting CBT if offered CBT
acceptCBT = calculate_probAcceptCBT(isMale, isOld, isBlack, isWhite,
isOther, isHisp, hadPrior)
# Set xVal to equilibrium value
xVal = iVal/(A+iVal)
# totInput += iVal
r = (1. - xVal)
g = xVal
# Define agent's triple circle
circle1 = plt.Circle((xLoc, yLoc), circRad1, fc=(r,g,0),
ec=cmplxColor)
if xVal > visThresh:
circle1.set_visible(False)
else:
circle1.set_visible(True)
axes.ax.add_patch(circle1)
# Define agent's bezier links
bezPatch = None
'''
for agcy in agencies.agenciesList[agencies.boroughsList[boroIndx-1]]:
(provXCtr, provYCtr) = agcy['loc']
# Define agent's bezier links to that agency
verts = ((provXCtr, provYCtr), # Bezier lnk from prov. to here
((provXCtr + xLoc)/2., provYCtr),
(xLoc, (provYCtr + yLoc)/2.),
(xLoc, yLoc))
bezPath = Path(verts, codes)
bezPatch = mpatches.PathPatch(bezPath, facecolor='none',
lw=1, ec='#afafaf', visible=True)
axes.ax.add_patch(bezPatch)
bezList.append(bezPatch)
'''
# Agent ID number below circle
idText = axes.ax.text(xLoc-.004, yLoc-.021, '%d'%agtId, visible=False)
newAgent = {'id':agtId,
'circ1':circle1,
'boroName':boroName,
'boroIndx':boroIndx,
'bezPatch':bezPatch,
'xLoc':xLoc,
'yLoc':yLoc,
'xVal':xVal,
'iVal':iVal,
'iFact':iFact,
'isComplex':isComplex,
'gender':gender,
'race':race,
'ethncy':ethncy,
'acceptCBT':acceptCBT,
'nSymptoms':nSymptoms,
'treating':False,
'enrolled':False,
'agency':None,
'treatNo':0, # current treatment #
'idText':idText}
return newAgent
def update_agent(agent):
global nEnrolled, schedList, schedPtr, tileListPtr, avgInput
# print ' In update_agent agent = %d'%agent['id']
# writelog.write('In update_agent agent = %d\n'%agent['id'])
xVal = agent['xVal']
inputVal = agent['iVal']
# If service is on, service the agents
if axes.checkService:
square.set_fc('#00ff00')
# If not scheduled for treatment consider enrolling
if not agent['enrolled']:
need = max((avgInput - xVal),0.)
# writelog.write(' not enrolled avgInput= %5.2f xVal= %5.2f need=%5.2f\n'%
# (avgInput, xVal, need))
# Calculate probability of enrollment based on need (and distance from provider)
if axes.checkDist:
distProvX, distProvY = (agent['xLoc'] - axes.provXOrg,
agent['yLoc'] - axes.provYOrg)
distProv = np.sqrt(distProvX**2 + distProvY**2)
gauss = (1./rSigma*np.sqrt(2.*np.pi)) * \
np.exp(-(distProv**2.)/(2.*rSigma**2))
probEnroll = need * (maxEnrolled - nEnrolled) * gauss
else:
probEnroll = need * (maxEnrolled - nEnrolled)
# writelog.write(' need = %f probEnroll = %5.2f\n'%(need,probEnroll))
# If enroll probability exceeds random threshold then enroll
if probEnroll > random():
# writelog.write(' probEnroll > random\n')
agent['enrolled'] = True
nEnrolled += 1
# agent['nSched'] = standardSched
agent['bezPatch'].set_visible(True)
inputVal = agent['iVal']
agent['idText'].set_visible(True)
# Register in schedList[]
# writelog.write('About to enroll\n')
if doingLogging:
writelog.write('Enrolling agent %d\n'% agent['id'])
treatList = [None for i in range(standardSched)]
treatList[agent['treatNo']] = agent['xVal']
treatList.insert(0, agent['isComplex'])
treatList.insert(0,agent['id'])
schedList.append(treatList)
# update schedule
updateSched(schedList)
if doingLogging:
printSched()
# Otherwise if already enrolled compute input treatment
else:
if random() > .25: # Randomize every other time to break sync
# If agent not being treated do next treatment
if agent['treating'] == False:
if doingLogging:
writelog.write(' agent %d treatment %d ON\n'%(agent['id'],
agent['treatNo']))
agent['treating'] = True
agent['bezPatch'].set_lw(2)
agent['bezPatch'].set_ec('#00ff00')
# Turn on input
if axes.checkEndBen:
agent['iVal'] += doseValue*agent['iFact']/10. # endBen increase iVal
else:
inputVal = agent['iVal'] + doseValue * agent['iFact']
# Increment treatment number
agent['treatNo'] += 1
if axes.checkStepped and agent['isComplex']:
nTreatLeft = standardSched + 1
else:
nTreatLeft = steppedSched+1
if agent['treatNo'] >= nTreatLeft:
if axes.checkStepped and agent['isComplex']:
writelog.write(' treatNo = %d standardSched = %d\n'%
(agent['treatNo'], standardSched))
else:
writelog.write(' treatNo = %d steppedSched = %d\n'%
(agent['treatNo'], steppedSched))
if doingLogging: writelog.write('Un-enroll agent %d treatment done\n'%
agent['id'])
agent['enrolled'] = False
agent['treatNo'] = 0
# agent['treating'] = False
nEnrolled -= 1
agent['bezPatch'].set_lw(1)
agent['bezPatch'].set_visible(False)
agent['idText'].set_visible(False)
for entry in schedList:
if entry[0] == int(agent['id']):
schedList.remove(entry)
break
else:
for indx, sched in enumerate(schedList):
if sched[0] == int(agent['id']):
schedList[indx][agent['treatNo']+1] = agent['xVal']
break
if doingLogging: writelog.write(' agent %d treatment %d ON\n'%
(agent['id'], agent['treatNo']+1))
# Update schedule
updateSched(schedList)
if doingLogging:
printSched()
# Otherwise if patient being treated turn it off
else:
agent['treating'] = False;
agent['bezPatch'].set_lw(1)
agent['bezPatch'].set_ec('#afafaf')
inputVal = agent['iVal']
if doingLogging: writelog.write(' agent %d treatment %d OFF\n'%
(agent['id'], agent['treatNo']))
# schedList = [x for x in schedList if x[0] != agent['id']]
# Else if service is off, shut off treatment
else:
agent['bezPatch'].set_visible(False)
square.set_fc('#ffffff')
inputVal = agent['iVal'] * agent['iFact']
# Shunting equation
xVal += -A * xVal + (1 - xVal) * inputVal
if xVal < 0.:
xVal = 0.
elif xVal > 1.:
xVal = 1.
agent['xVal'] = xVal
r = (1. - xVal)
g = xVal
agent['circ1'].set_facecolor((r, g, 0.))
# Time delay
if delay > 0.:
time.sleep(delay)
def init_agents():
global agents, nAgents, square, circle, avgInput, \
nAgentsWht, nAgentsBlk, nAgentsOth
totInput = 0.
agentId = 0
## for each agent
for agtId in range(nAgents):
writelog.write("agtId = %d\n"%agtId)
foundSpace = False
while not foundSpace:
xLoc = random() * image.aspect + .1*image.aspect
yLoc = random()
writelog.write("agtId: % 3d xLoc, yLoc = (%4.2f, %4.2f)\n"%(agtId, xLoc, yLoc))
inMask = image.maskImg[image.imgYSize - yLoc * image.imgYSize,
(xLoc-image.xOff)*image.imgXSize/image.aspect + image.xOff][0]
borough = image.burrIndx[image.imgYSize - yLoc * image.imgYSize,
(xLoc-image.xOff)*image.imgXSize/image.aspect + image.xOff]
borough -= 1 #<=== KLUDGE! (Don't know why this is necessary)
writelog.write("agtId: % 3d xLoc, yLoc = (%4.2f, %4.2f) borough = %3d\n"%(
agtId, xLoc, yLoc, borough))
# if inMask > .5 and borough in range(1,6): # If in the masked area check for collision
if inMask > .9: # If in the masked area check for collision
writelog.write(' In borough %3d\n'%borough)
collision = False
for agt in range(len(agents)):
xLoc1 = agents[agt]['xLoc']
yLoc1 = agents[agt]['yLoc']
dx = xLoc1 - xLoc
dy = yLoc1 - yLoc
dist = np.sqrt(dx**2 + dy**2)
if dist < minSep:
collision = True
writelog.write(" COLLISION !!!\n")
break # Stop going through more agents
if not collision:
foundSpace = True
writelog.write("agtId: % 3d xLoc, yLoc = (%4.2f, %4.2f) borough = %3d\n"%(
agtId, xLoc, yLoc, borough))
writelog.write(" foundSpace!\n")
# Otherwise keep searching
# Define agent's "input value" (natural wellness) and input factor
iVal = random()
if iVal > iThresh:
iFact = 1.
isComplex = False
cmplxColor = 'k'
else:
if random() > .5:
iFact = 1.
isComplex = False
cmplxColor = 'k'
else:
iFact = 0.7
isComplex = True
cmplxColor = 'r'
# Set xVal to equilibrium value
xVal = iVal/(A+iVal)
totInput += iVal
r = (1. - xVal)
g = xVal
# Define agent's race and ethnicity
(race, ethncy) = probRaceEthncy(borough)
if race == 'White':
raceColor = 'w'
nAgentsWht += 1
elif race == 'Black':
raceColor = 'k'
nAgentsBlk += 1
elif race == 'Other':
raceColor = 'gray'
nAgentsOth += 1
ethVis = ethncy == 'Hispanic'
# Define agent's triple circle & wedge
circle1 = plt.Circle((xLoc, yLoc), circRad1, fc=(r,g,0),
ec=(r,g,0))
circle2 = plt.Circle((xLoc, yLoc), circRad2, fc=cmplxColor,
ec=cmplxColor)
circle3 = plt.Circle((xLoc, yLoc), circRad3, fc=raceColor,
ec=raceColor)
wedge = mpatches.Wedge((xLoc, yLoc), circRad3, 180, 0,
fc='brown', ec='brown', visible=ethVis)
axes.ax.add_patch(circle3)
axes.ax.add_patch(wedge)
axes.ax.add_patch(circle2)
axes.ax.add_patch(circle1)
# Define agent's bezier links
verts = ((axes.provXCtr, axes.provYCtr), # Bezier lnk from prov. to here
((axes.provXCtr + xLoc)/2., axes.provYCtr),
(xLoc, (axes.provYCtr + yLoc)/2.),
(xLoc, yLoc))
bezPath = Path(verts, codes)
bezPatch = mpatches.PathPatch(bezPath, facecolor='none',
lw=1, ec='#afafaf', visible=False)
# Agent ID number below circle
idText = axes.ax.text(xLoc-.004, yLoc-.021, '%d'%agtId, visible=False)
# idText = axes.ax.text(xLoc-.004, yLoc-.021, '%d'%borough, visible=True)
# idText = axes.ax.text(xLoc-.004, yLoc-.021, '%5.2f'%inMask, visible=True)
# Append to agents list
agents.append({'id':agtId,
'circ1':circle1,
'circ2':circle2,
'circ3':circle3,
'wedge':wedge,
'bezPatch':bezPatch,
'xLoc':xLoc,
'yLoc':yLoc,
'xVal':xVal,
'iVal':iVal,
'iFact':iFact,
'isComplex':isComplex,
'race':race,
'ethncy':ethncy,
'treating':False,
'enrolled':False,
'treatNo':0, # current treatment #
'idText':idText})
axes.ax.add_patch(bezPatch)
bezLines.append(bezPatch)
agentId += 1
avgInput = totInput/float(nAgents)
# Service provider square and 2 sigma range
square = plt.Rectangle((axes.provXOrg, axes.provYOrg),
axes.provSize, axes.provSize, fc=(0,1,0), ec='k')
axes.ax.add_patch(square)
# Dist feature sigma radius dashed circle
circle = plt.Circle((axes.provXOrg, axes.provYOrg), radius=rSigma, ec='r',
fc='none', linestyle='dashed', visible=axes.checkDist)
axes.ax.add_patch(circle)
dt = 10
dArray = deque([0.])
tArray = deque([0.])
plotWidth = 500
isMale = 0
isOld = 1
isBlack = 0.
race = 'white'
ethn = 'hispanic'
# income = 'lowrange'
hadPrior = 0
logitCBT = 0
probCBT = 0
writelog.init('PTSD_Logistic.log')
writelog.write('sex \t age \t race \t ethn \t\t nPrior \t logitCBT \t\t probCBT \n')
writelog.write('=== \t === \t ==== \t ==== \t\t ====== \t ====== \t\t ======= \n\n')
plt.close('all')
fig = plt.figure(figsize=(12,6))
fig.canvas.set_window_title('PTSD_LogisticCombo.py')
# Create axes boxes in a linspace xorg line
xorg = np.linspace(.05,.9,5)
axSex = plt.axes([xorg[0],.6,.08,.2]); axSex.set_title('Sex')
axAge = plt.axes([xorg[1],.6,.08,.2]); axAge.set_title('Age')
axRace = plt.axes([xorg[2],.6,.08,.2]); axRace.set_title('Race')
axEthn = plt.axes([xorg[3],.6,.08,.2]); axEthn.set_title('Ethn')
# axIncome = plt.axes([xorg[4],.6,.08,.2]); axIncome.set_title('Income')
# axStress = plt.axes([xorg[5],.6,.08,.2]); axStress.set_title('Stress')
# axTrauma = plt.axes([xorg[6],.6,.08,.2]); axTrauma.set_title('Trauma')
plotWidth = 500
isMale = 0
isOld = 1
isBlack = 0.
isWhite = 1.
isOther = 0.
race = 'white'
ethn = 'hispanic'
isHisp = 1
# income = 'lowrange'
hadPrior = 0
logitCBT = 0
probCBT = 0
writelog.init('PTSD_Logistic.log')
writelog.write('sex \t age \t race \t ethn \t\t nPrior \t logitCBT \t probCBT \n')
writelog.write('=== \t === \t ==== \t ==== \t\t ====== \t ====== \t ======= \n\n')
plt.close('all')
fig = plt.figure(figsize=(12,6))
fig.canvas.set_window_title('PTSD_LogisticCombo.py')
# Create axes boxes in a linspace xorg line
xorg = np.linspace(.05,.9,5)
axSex = plt.axes([xorg[0],.6,.08,.2]); axSex.set_title('Sex')
axAge = plt.axes([xorg[1],.6,.08,.2]); axAge.set_title('Age')
axRace = plt.axes([xorg[2],.6,.08,.2]); axRace.set_title('Race')
axEthn = plt.axes([xorg[3],.6,.08,.2]); axEthn.set_title('Ethn')
axPrior = plt.axes([xorg[4],.6,.08,.2]); axPrior.set_title('Prior CBT')
# Create axes for text output
lastT = 0.
dt = 1
dArray = deque([0.])
tArray = deque([0.])
plotWidth = 500
isFemale = 0
isYoung = 1
race = 'white'
ethn = 'hispanic'
income = 'lowrange'
hadStressors = 0
nSandyTraumas = 0
PTSD_sx = 0
writelog.init('PTSD_Combo.log')
writelog.write('sex \t age \t race \t ethn \t\t income \t hadStr nSandTr exp(P)\n')
writelog.write('=== \t === \t ==== \t ==== \t\t ====== \t ====== ======= ======\n\n')
plt.close('all')
fig = plt.figure(figsize=(12,6))
fig.canvas.set_window_title('PTSD_Distribution.py')
# Create axes boxes in a linspace xorg line
xorg = np.linspace(.05,.9,7)
axSex = plt.axes([xorg[0],.6,.08,.2]); axSex.set_title('Sex')
axAge = plt.axes([xorg[1],.6,.08,.2]); axAge.set_title('Age')
axRace = plt.axes([xorg[2],.6,.08,.2]); axRace.set_title('Race')
axEthn = plt.axes([xorg[3],.6,.08,.2]); axEthn.set_title('Ethn')
axIncome = plt.axes([xorg[4],.6,.08,.2]); axIncome.set_title('Income')
axStress = plt.axes([xorg[5],.6,.08,.2]); axStress.set_title('Stress')
axTrauma = plt.axes([xorg[6],.6,.08,.2]); axTrauma.set_title('Trauma')
def init_agent(agtId):
global nEnrolled, schedList, schedPtr, avgInput
global agents, nAgents, square, circle, avgInput, \
nAgentsWht, nAgentsBlk, nAgentsOth
foundSpace = False
while not foundSpace:
xLoc = random() * image.aspect + .1*image.aspect
yLoc = random()
writelog.write("agtId: % 3d xLoc, yLoc = (%4.2f, %4.2f)\n"%(agtId, xLoc, yLoc))
inMask = image.maskImg[image.imgYSize - yLoc * image.imgYSize,
(xLoc-image.xOff)*image.imgXSize/image.aspect + image.xOff][0]
borough = image.burrIndx[image.imgYSize - yLoc * image.imgYSize,
(xLoc-image.xOff)*image.imgXSize/image.aspect + image.xOff]
borough -= 1 #<=== KLUDGE! (Don't know why this is necessary)
writelog.write("agtId: % 3d xLoc, yLoc = (%4.2f, %4.2f) borough = %3d\n"%(
agtId, xLoc, yLoc, borough))
# if inMask > .5 and borough in range(1,6): # If in the masked area check for collision
if inMask > .9: # If in the masked area check for collision
writelog.write(' In borough %3d\n'%borough)
collision = False
for agt in range(len(agents)):
xLoc1 = agents[agt]['xLoc']
yLoc1 = agents[agt]['yLoc']
dx = xLoc1 - xLoc
dy = yLoc1 - yLoc
dist = np.sqrt(dx**2 + dy**2)
if dist < minSep:
collision = True
writelog.write(" COLLISION !!!\n")
break # Stop going through more agents
if not collision:
foundSpace = True
writelog.write("agtId: % 3d xLoc, yLoc = (%4.2f, %4.2f) borough = %3d\n"%(
agtId, xLoc, yLoc, borough))
writelog.write(" foundSpace!\n")
# Otherwise keep searching
# Define agent's race and ethnicity
(race, ethncy) = probRaceEthncy(borough)
if race == 'White':
raceColor = 'w'
isWhite = 1.
isBlack = 0.
isOther = 0.
nAgentsWht += 1
elif race == 'Black':
raceColor = 'k'
isWhite = 0.
isBlack = 1.
isOther = 0.
nAgentsBlk += 1
elif race == 'Other':
raceColor = 'gray'
isWhite = 0.
isBlack = 0.
isOther = 1.
nAgentsOth += 1
if ethncy == 'Hispanic':
ethVis = True
isHisp = 1.
else:
ethVis = False
isHisp = 0.
# Define agent's gender
if random() > .5:
gender = 'Male'
isMale = 1.
else:
gender = 'Female'
isMale = 0.
# Define agent's age
if random() > .75:
isOld = 1.
else:
isOld = 0.
# Define agent's hadPrior (PTSD)
if random() > .9:
hadPrior = 1.
else:
hadPrior = 0.
# Define agent's "input value" (natural wellness) and input factor
# Using probCBT
if useProbCBT:
fstr = ' isMale=%1d isOld=%1d isBlack=%1d isWhite=%1d isOther=%1d '\
'isHisp=%1d hadPrior=%1d\n'
writelog.write(fstr%(isMale, isOld, isBlack, isWhite,
isOther, isHisp, hadPrior))
probCBT = calculate_distribution(isMale, isOld, isBlack, isWhite,
isOther, isHisp, hadPrior)
iVal = 1. - probCBT
if iVal > 1:
iVal = 1.
elif iVal < 0.:
iVal = 0.
writelog.write(' calculate_distribution: probCBT = %f iVal = %f\n'%(probCBT,iVal))
# Or using just random
else:
iVal = random()
writelog.write(' calculate_input: iVal = %f\n'%iVal)
if iVal > iThresh:
iFact = 1.
isComplex = False
cmplxColor = 'k'
else:
if random() > .5:
iFact = 1.
isComplex = False
cmplxColor = 'k'
else:
iFact = 0.7
isComplex = True
cmplxColor = 'r'
# Set xVal to equilibrium value
xVal = iVal/(A+iVal)
# totInput += iVal
r = (1. - xVal)
g = xVal
# Define agent's triple circle & wedge
circle1 = plt.Circle((xLoc, yLoc), circRad1, fc=(r,g,0),
ec=cmplxColor)
'''
circle2 = plt.Circle((xLoc, yLoc), circRad2, fc=cmplxColor,
ec=cmplxColor)
circle3 = plt.Circle((xLoc, yLoc), circRad3, fc=raceColor,
ec=raceColor)
wedge = mpatches.Wedge((xLoc, yLoc), circRad3, 180, 0,
fc='brown', ec='brown', visible=ethVis)
axes.ax.add_patch(circle3)
axes.ax.add_patch(wedge)
axes.ax.add_patch(circle2)
'''
if xVal > visThresh:
circle1.set_visible(False)
else:
circle1.set_visible(True)
axes.ax.add_patch(circle1)
# Define agent's bezier links
verts = ((axes.provXCtr, axes.provYCtr), # Bezier lnk from prov. to here
((axes.provXCtr + xLoc)/2., axes.provYCtr),
(xLoc, (axes.provYCtr + yLoc)/2.),
(xLoc, yLoc))
bezPath = Path(verts, codes)
bezPatch = mpatches.PathPatch(bezPath, facecolor='none',
lw=1, ec='#afafaf', visible=False)
axes.ax.add_patch(bezPatch)
'''
# Define agent's gender symbol
if gender == 'Male':
xData = [xLoc + circRad2,
xLoc + 1.5*circRad2,
xLoc + 1.5*circRad2-circRad2/2,
xLoc + 1.5*circRad2,
xLoc + 1.5*circRad2]
yData = [yLoc + circRad2,
yLoc + 1.5*circRad2,
yLoc + 1.5*circRad2,
yLoc + 1.5*circRad2,
yLoc + 1.5*circRad2-circRad2/2]
elif gender == 'Female':
xData = [xLoc,
xLoc,
xLoc,
xLoc - .5*circRad2,
xLoc + .5*circRad2]
yData = [yLoc - circRad2,
yLoc - 2*circRad2,
yLoc - 1.5*circRad2,
yLoc - 1.5*circRad2,
yLoc - 1.5*circRad2]
gendSymb = plt.Line2D(xData, yData, color='k')
axes.ax.add_line(gendSymb)
'''
# Agent ID number below circle
idText = axes.ax.text(xLoc-.004, yLoc-.021, '%d'%agtId, visible=False)
newAgent = {'id':agtId,
'circ1':circle1,
'bezPatch':bezPatch,
'xLoc':xLoc,
'yLoc':yLoc,
'xVal':xVal,
'iVal':iVal,
'iFact':iFact,
'isComplex':isComplex,
'gender':gender,
'race':race,
'ethncy':ethncy,
'treating':False,
'enrolled':False,
'treatNo':0, # current treatment #
'idText':idText}
return newAgent