def flow2speed_2p(inSpace, currentIter, FL, LIMIT):
'''
This function takes detector flow and convert to detector level speed.
Outputs to outCSV = inSpace+'detspd'+str(currentIter)+'-P.csv'
This code contains suggestion from Gabriel on 12/15/2014,
to take the supply speed simply as a smoothed supply speed and not weighted
Demand+supply.
'''
import sys
import numpy as np
from math import exp
try:
# READ FLOW (PEAK)
cff_p = inSpace + "CSV/detflow" + str(currentIter) + "-P.csv"
fdtype = [('idstn', 'i8'), ('flow', 'f8')]
cff_p = readcsv(cff_p, fdtype, incol=2, sort=[0], header=None)
# READ FLOW (Off PEAK)
cff_op = inSpace + "CSV/detflow" + str(currentIter) + "-OP.csv"
fdtype = [('idstn', 'i8'), ('flow', 'f8')]
cff_op = readcsv(cff_op, fdtype, incol=2, sort=[0], header=None)
numBack = 9 # How many iteration back to include in the exp. +1 = total number for exp
# Simple weight for now
avgwt = 1. / (np.arange(currentIter) + 1)
# Truncate the weight to at most 10
avgwt = avgwt[0:numBack]
avgwt = avgwt[::-1]
print avgwt
prior = np.arange(currentIter)
prior = prior[-numBack:]
# Read Previous Speeds (PEAK)
print "prior:", prior
a = np.zeros([
numBack, 1813
]) # TODO: HARDCODED 1813 here. NEED FIX WHEN UPDATE TO FULL LA AREA
j = 0
for i in prior:
inPspd = inSpace + "detspdSY" + str(i) + "-P.csv"
fdtype = [('idstn', 'i8'), ('speed', 'f8')]
ps1 = readcsv(inPspd, fdtype, incol=2, sort=[0], header=True)
print "a[", j, "]", "=", inPspd
a[j] = ps1['speed']
j += 1
b = np.average(a[:j], axis=0)
ps1['speed'] = np.copy(b)
ps_p = np.copy(ps1)
del a, b, ps1
# Read Previous Speeds (offPEAK)
print "prior:", prior
a = np.zeros([
numBack, 1813
]) # TODO: HARDCODED 1813 here. NEED FIX WHEN UPDATE TO FULL LA AREA
j = 0
for i in prior:
inPspd = inSpace + "detspdSY" + str(i) + "-OP.csv"
ps1 = readcsv(inPspd, fdtype, incol=2, sort=[0], header=True)
print "a[", j, "]", "=", inPspd
a[j] = ps1['speed']
j += 1
b = np.average(a[:j], axis=0)
ps1['speed'] = np.copy(b)
ps_op = np.copy(ps1)
del a, b, ps1
#AF = Actual Daily TOTAL FLOW (average pre expo)
inAF = inSpace + "AF.csv"
fdtype = [('idstn', 'i8'), ('center', 'i8'), ('lane', 'i8'),
('flow', 'f8')]
af = readcsv(inAF, fdtype, incol=4, sort=0, header=True)
#Convert from GF to the peak time flow F (F = GF x 2 x 6%)
#cff['flow'] = cff['flow']*0.12
#CHECK TO MAKE SURE THE ARRAYS MATCHES
x1 = af['idstn']
x2 = cff_p['idstn']
xeq = x1 == x2
if xeq[xeq != True].size != 0:
raise Exception(
"AF and Current detector flow idstn DOES NOT MATCH!")
#Calculate AF/GF ratio for center detectors
np.seterr(divide='ignore')
aft = af['center'] * af['flow']
aft = aft.sum()
cft_p = af['center'] * cff_p['flow']
cft_p = cft_p.sum()
cft_op = af['center'] * cff_op['flow']
cft_op = cft_op.sum()
ratio = aft / (cft_p + cft_op)
print "AF/GF Ratio:", ratio
#SAVE DETFLOW WITH ADJUSTMENT
#PEAK
detFlow = np.copy(cff_p)
detFlow['flow'] = detFlow['flow'] * ratio
outCSVcff = inSpace + 'CSV/detflow_adj' + str(currentIter) + '-P.csv'
np.savetxt(outCSVcff, detFlow, delimiter=',', fmt='%7.0f, %7.10f')
#OffPEAK
detFlow = np.copy(cff_op)
detFlow['flow'] = detFlow['flow'] * ratio
outCSVcff = inSpace + 'CSV/detflow_adj' + str(currentIter) + '-OP.csv'
np.savetxt(outCSVcff, detFlow, delimiter=',', fmt='%7.0f, %7.10f')
#Convert from GF to the peak time flow F = AF/GF*6%*GF
# cff['flow'] = ratio*0.06*(cff['flow'])/af['lane']
# TODO: Ratio of 6% still ok???
cff_p['flow'] = ratio * 0.6 * (cff_p['flow']) / af['lane']
cff_op['flow'] = ratio * 0.6 * (cff_op['flow']) / af['lane']
#Update supply side speed using supply side equation
#PEAK
for x in np.nditer(cff_p['flow'], op_flags=['readwrite']):
if x > FL:
x[...] = LIMIT * exp(-0.000191 * (x - FL))
else:
x[...] = LIMIT
#OffPEAK
for x in np.nditer(cff_op['flow'], op_flags=['readwrite']):
if x > FL:
x[...] = LIMIT * exp(-0.000191 * (x - FL))
else:
x[...] = LIMIT
cff_p.dtype = ([('idstn', '<i8'), ('speed', '<f8')])
cff_op.dtype = ([('idstn', '<i8'), ('speed', '<f8')])
#SAVE THE SUPPLY SIDE SPEED
outCSV = inSpace + 'detspdSY' + str(currentIter) + '-P.csv'
print "speed updated. Writing to", outCSV
with open(outCSV, 'wb') as f:
f.write(b'id_stn,speed\n')
np.savetxt(f, cff_p, delimiter=',', fmt='%7.0f, %7.10f')
outCSV = inSpace + 'detspdSY' + str(currentIter) + '-OP.csv'
print "speed updated. Writing to", outCSV
with open(outCSV, 'wb') as f:
f.write(b'id_stn,speed\n')
np.savetxt(f, cff_op, delimiter=',', fmt='%7.0f, %7.10f')
#Set new supply side speed as linear combination of prev and current
#supply side speed. Weight wt is set in the beginning.
#Construct weight vector
#HINT: PEAK
weight = cff_p['speed'] - ps_p['speed']
weight = abs(weight)
#FULL CONTROL: weight is 10% of absolute speed difference
#Top code at 7.5mph
#Old equation actually works without modification
for x in np.nditer(weight, op_flags=['readwrite']):
if x > 25:
x[...] = 0.5
elif x > 0.25:
x[...] = x**0.5 / 10
else:
x[...] = 0
cff_p['speed'] = weight * cff_p['speed'] + (1 - weight) * ps_p['speed']
outCSV = inSpace + 'detspd' + str(currentIter) + '-P.csv'
print "speed updated. Writing to", outCSV
with open(outCSV, 'wb') as f:
f.write(b'id_stn,speed\n')
np.savetxt(f, cff_p, delimiter=',', fmt='%7.0f, %7.10f')
#HINT: OffPEAK
weight = cff_op['speed'] - ps_op['speed']
weight = abs(weight)
for x in np.nditer(weight, op_flags=['readwrite']):
if x > 25:
x[...] = 0.5
elif x > 0.25:
x[...] = x**0.5 / 10
else:
x[...] = 0
cff_op['speed'] = weight * cff_op['speed'] + (1 -
weight) * ps_op['speed']
outCSV = inSpace + 'detspd' + str(currentIter) + '-OP.csv'
print "speed updated. Writing to", outCSV
with open(outCSV, 'wb') as f:
f.write(b'id_stn,speed\n')
np.savetxt(f, cff_op, delimiter=',', fmt='%7.0f, %7.10f')
except Exception as e:
tb = sys.exc_info()[2]
print "Exception in ModSpeedCalc"
print "An error occurred in ModSpeedCalc line %i" % tb.tb_lineno
print e.message
def alloc_trans(inSpace, inFlow, currentIter):
'''
Base on alloc(), but changed the hard coded items for transit matrices
'''
import numpy as np
from ModIO import readcsv
from math import sqrt
inTT = inSpace+"CSV/TT.csv"
inTD = inSpace+"CSV/TD.csv"
inDT = inSpace+"CSV/DT.csv"
outCSV = inSpace+'CSV/Transdetflow'+str(currentIter)+'.csv'
#Test: 50 TAZs, 1813 DET
#Full: 2241 TAZs, 1813 DETs
nTAZ = 50
nDET = 1813
dttype = [('oid','i8'),('did','i8'),('name','S20'),('cost','f8')]
tttype = [('oid','i8'),('did','i8'),('name','S20'),('cost','f8'),('length','f8'),('dps','f8'),('metro','f8'),('bus','f8')]
fdtype = [('oid','i8'),('did','i8'),('postflow','f8')]
print "importing various matrices"
#Read TAZ-TAZ flow
ff = readcsv(inFlow, fdtype, incol = 3, sort = [0,1], header = None)
#Read TD cost
td = readcsv(inTD, dttype, incol = 4, sort = [1,0], header = None)
#Read DT cost
dt = readcsv(inDT, dttype, incol = 4, sort = [0,1], header = None)
#Read TT cost
tt = readcsv(inTT, tttype, incol = 14, sort = [0,1], header = None)
nTAZ = int(sqrt(tt.size))
if nTAZ != sqrt(tt.size):
print "ERROR: TAZ SIZE NOT SQUARE!"
if dt.size != td.size:
print "ERROR: TD and DT SIZE NOT MATCH!"
nDET = dt.size/nTAZ
print "import completed, TAZ:", nTAZ, "DET:", nDET
print "reshaping..."
ctd = np.reshape(td['cost'],(nDET, nTAZ))
cdt = np.reshape(dt['cost'],(nDET, nTAZ))
ndt = np.reshape(dt['name'],(nDET, nTAZ))
ctt = np.reshape(tt['cost'],(nTAZ, nTAZ))
ftt = np.reshape(ff['postflow'],(nTAZ, nTAZ))
# FLOW MATRIX
print "begin flow allocation"
x3 = np.matrix(ctt)
i = 0
count = 0
detFlow = {999999: 0}
while i < nDET:
#Extract current detector id_stn
det = ndt[i,1][0:6]
# Extract cost vectors
x1 = np.matrix(ctd[i])
x1 = x1.T
x2 = np.matrix(cdt[i])
tddt=x1+x2
#Precise matching
isflow = x3 == tddt
#Element multiply by flow
flow = np.multiply(isflow, ftt)
totalflow = np.nansum(flow)
#print "Current iteration:", i
if totalflow > 0:
#print "stn", i, "flow:", totalflow
count +=1
#Record flow in dictionary
detFlow[det] = totalflow
i+=1
del detFlow[999999]
print "Number of detectors with match:", count
dtype = [('idstn','i8'),('flow','f8')]
detFlow= np.array(detFlow.items(), dtype=dtype)
np.savetxt(outCSV, detFlow, delimiter=',', fmt='%7.0f, %7.10f')
return detFlow
def update_step1(inSpace, currentIter, inTTp):
'''
Output both TT flow for driving and transit
'''
from math import exp, sqrt, pi
import numpy as np
from ModIO import readcsv
#print "Code starts on ", time.strftime("%d/%m/%Y - %H:%M:%S")
#Parameters
c1 = 5.45
c2 = -5.05
G = exp(-3.289)
beta1 = 0.535
beta2 = 0.589
tau = -2.077
#import various matrices
fdtype = [('oid','i8'),('did','i8'),('flow','f8')]
tttype = [('oid','i8'),('did','i8'),('name','S20'),('cost','f8')]
petype = [('oid','i8'),('emp','f8'),('pop','f8')]
areatype = [('oid','i8'),('area','f8')]
#import from inFlow
#This is used as OUTPUT TEMPLATE
outFTT = inSpace + "inFlow.csv"
outFTT = readcsv(outFTT, fdtype, incol = 3, sort = [0,1], header = None)
#TT Cost (pub)
#Post/PRE as SEPARATE CSV FILE
print "importing TTcost for Transit"
ttp = readcsv(inTTp, tttype, incol = 4, sort = [0,1], header = True)
print "importing TTcost for driving (current)"
#TT Cost (driving, CURRENT)
inTTd = inSpace+"CSV/TT.csv"
#inTTd = inSpace+"TTdrv.csv"
ttd = readcsv(inTTd, tttype, incol = 4, sort = [0,1], header = None)
#print "check sorting"
#make sure both TT costs are sorted correctly:
#if any(ttp['oid'] != ttd['oid']) or any(ttp['did'] != ttd['did']):
#if any(ttp['oid'] != ttd['oid']) or any(ttp['did'] != ttd['did']):
# raise Exception('Driving and Transit TT not match!')
#print "sorting is fine"
print "importing census"
#Population & employment
inPE = inSpace+"census.csv"
pe = readcsv(inPE, petype, incol = 3, sort = [0], header = True)
print "importing TAZ area"
inArea = inSpace+"TAZarea.csv"
area = readcsv(inArea, areatype, incol=2, sort=[0], header = True)
area = area['area']
print "testing squareness"
#Test square of TTcost and TTcostpub, test same size of pop/emp
ttsize = sqrt(np.size(ttd))
if ttsize != int(ttsize):
raise Exception('Driving TT cost not square!!!')
ttsize = sqrt(np.size(ttp))
if ttsize != int(ttsize):
raise Exception('Transit TT cost not square!!!')
pesize = np.size(pe)
if pesize != int(ttsize):
raise Exception('Population/Employment vector not same size as TAZ!!!')
nTAZ = ttsize
print "square is fine, import completed"
print "creating internal cost"
#Internal cost: cost of ppl going to work within own TAZ
# replace drvcost = 21.46*[(2/3)*(area_dest/_pi)^0.5]/15
# +3.752*[(2/3)*(area_dest/_pi)^0.5]/20 if oID_TAZ12A== dID_TAZ12A
# replace with 1 if lower than 1
dist = (2./3) * (area/pi)**0.5
intci = vot * dist / 15 + 0.469 * dist
intcp = vot * dist / 3
#make diagonal (Origin = destination)
I = np.identity(nTAZ)
intci = intci*I
intcp = intcp*I
print "reshaping..."
ttcosti = np.reshape(ttd['cost'],(nTAZ, nTAZ)) + intci
ttcostp = np.reshape(ttp['cost'],(nTAZ, nTAZ)) + intcp
print "calculate Sij"
#New transit share
deltaC = ttcostp/ttcosti
exx = np.exp(c1+c2*deltaC)
sij = exx/(1+exx)
outSij = sij.reshape(nTAZ**2,1)
outCSVsij = inSpace+'CSV/Sij'+str(currentIter)+'.csv'
print "Writing transit share to", outCSVsij
with open(outCSVsij, 'wb') as f:
np.savetxt(f, outSij, delimiter=',', fmt='%7.10f')
print "population and employment"
#Gravity prediction
pop = pe['pop'] ** beta1
pop = np.matrix(pop)
emp = pe['emp'] ** beta2
emp = np.matrix(emp)
print "final matrix calculation"
FTT = G * np.array(pop.T * emp) * (sij*ttcostp + (1-sij)*ttcosti)**tau
pFTT= FTT * (1-sij)
pFTT= pFTT.reshape(1,nTAZ**2)
tFTT= FTT * (sij)
tFTT= tFTT.reshape(1,nTAZ**2)
FTT = np.reshape(FTT,(1,nTAZ**2))
outFTT['flow'] = pFTT
outCSV = inSpace+'CSV/TTflow'+str(currentIter)+'.csv'
print "Writing output to", outCSV
with open(outCSV, 'wb') as f:
np.savetxt(f, outFTT, delimiter=',', fmt='%7.0f, %7.0f, %7.10f')
outFTT['flow'] = tFTT
outCSV = inSpace+'CSV/TransTTflow'+str(currentIter)+'.csv'
print "Writing output to", outCSV
with open(outCSV, 'wb') as f:
np.savetxt(f, outFTT, delimiter=',', fmt='%7.0f, %7.0f, %7.10f')
outFTT['flow'] = FTT
outCSV = inSpace+'CSV/TotalTTflow'+str(currentIter)+'.csv'
print "Writing output to", outCSV
with open(outCSV, 'wb') as f:
np.savetxt(f, outFTT, delimiter=',', fmt='%7.0f, %7.0f, %7.10f')
#
# cff.dtype = ([('idstn', '<i8'), ('speed', '<f8')])
# b=np.copy(cff)
if __name__ == "__main__":
import numpy as np
from math import exp
inSpace = "C:\Users\Dennis\Desktop\Results\Pre_1219\Test/"
currentIter = 12
FL = 500
LIMIT = 600
# READ FLOW (PEAK)
cff_p = inSpace + "CSV/detflow" + str(currentIter) + "-P.csv"
fdtype = [('idstn', 'i8'), ('flow', 'f8')]
cff_p = readcsv(cff_p, fdtype, incol=2, sort=[0], header=None)
# READ FLOW (Off PEAK)
cff_op = inSpace + "CSV/detflow" + str(currentIter) + "-OP.csv"
fdtype = [('idstn', 'i8'), ('flow', 'f8')]
cff_op = readcsv(cff_op, fdtype, incol=2, sort=[0], header=None)
numBack = 9 # How many iteration back to include in the exp. +1 = total number for exp
# Simple weight for now
# avgwt = 1./(np.arange(currentIter)+1)
#
# # Truncate the weight to at most 10
# avgwt = avgwt[0:numBack]
# avgwt = avgwt[::-1]
#
# print avgwt
if __name__ == '__main__':
# Want Link objective, not just detectors.
# i.e. minimize the aggregate cost travelling on the highway network's links
# Need : link distance, cost = (11.5375 * dist / inSpd + 0.469 * dist)
inSpace = "/Users/SWOT/Desktop/TestBisection/"
currentIter = 10
ratio = 10
FL = 500
LIMIT = 65
import numpy as np
cff_op = inSpace + "detflow_adj" + str(currentIter) + ".csv"
fdtype = [('idstn', 'i8'), ('flow', 'f8')]
x1 = readcsv(cff_op, fdtype, incol=2, sort=[0], header=None)
cff_op = inSpace + "detflow_adj" + str(currentIter + 1) + ".csv"
fdtype = [('idstn', 'i8'), ('flow', 'f8')]
y1 = readcsv(cff_op, fdtype, incol=2, sort=[0], header=None)
inAF = inSpace + "AF.csv"
fdtype = [('idstn', 'i8'), ('center', 'i8'), ('lane', 'i8'),
('flow', 'f8')]
af = readcsv(inAF, fdtype, incol=4, sort=0, header=True)
# Make sure the idstn align
checksum = x1['idstn'] != y1['idstn']
print 'number of detectors out of order:', checksum.sum()
if checksum.sum() > 0:
print 'OH SHIT'
def dta_1p(inSpace, inTTflow, fl, limit):
'''
This script runs the DTA loop.
This script also contains the travelcost subfunction
Inputs
------
inSpace : str
Path
inTTflow : str
Full path to TT flow of current iteration
fl : int
flow per lane
limit : int
speed limit
'''
import numpy as np
# XXX Begin sub function block
def bisection(a, b, tol, x, y, vd):
'''
Bisection method to find root.
hardcoded in objective function as flowGradient,
and value function as travelcost.
Input
-----
a : value
min search value
b : value
max search value
tol : value
tolerance
x,y : vector
flow vectors (prev, predicted)
vd : vector
distance vector from AF
Return
------
Alpha of root.
'''
def f(alpha):
return flowGradient(x, y, alpha, vd)
c = (a+b)/2.0
while (b-a)/2.0 > tol:
if f(c) == 0:
print 'fc=0'
return c
elif f(a)*f(c) < 0:
b = c
else :
a = c
c = (a+b)/2.0
return c
def flowGradient(x, y, alpha, vdist):
'''
Calculate the gradient value based on value function and various inputs
(y1-x1)*t(x1+a*(y1-x1))
Contains a short, no-output version of flow2spd, and travelcost calculation
Input
-----
x : vector
Prev flow
y : vector
Expected flow
alpha : value
Alpha value for move. See Sheffi p. 119. Supplied from bisection
vdist : vector
vector of distance from AF reading
Output
------
Grad(Z) : Value
Value of the gradient, for use in bisection method
'''
def flow2spd(x, FL, LIMIT):
# given x as PER LANE flow, FL, LIMIT, returns the resulting speed.
from math import exp
if x > FL:
return LIMIT * exp(-0.000191*(x-FL))
else:
return LIMIT
def travelcost(x, dist):
# segment length to be implimented
vflow2spd = np.vectorize(flow2spd, otypes=[np.float])
travelcost = (11.5375 *dist / vflow2spd(x, fl, limit)) + 0.469 * dist
travelcost = (1/vflow2spd(x, fl, limit))**4
travelcost = 65**.2 - vflow2spd(x, fl, limit)**.2
return travelcost
grad = (y-x)*travelcost(x+alpha*(y-x), vdist)
return grad.sum()
# XXX end sub function block
try:
print "bisection starts on ", time.strftime("%H:%M:%S")
# Create temp speed
x1path = "CSV/xdetflow.csv"
outCSV = "detspd-temp.csv"
ratio_x = ModSpeedCalc.flow2speed(inSpace, x1path, fl, limit, outCSV, dta=True) #detspd-temp.csv
# Perform all or nothing allocation
print "DTA scratch version"
ModSetupWorker.clearOld(base,tempP)
print "GIS operation"
inSpeed = "detspd-temp.csv"
ModGIS.GISops_dta(inSpace, inGdb, fcTAZ, fcDet, inSpeed) # TT, DT, TD
print "allocation"
y1path = "CSV/ydetflow.csv"
# inFlow is global
ModAlloc.alloc(inSpace, inFlow, inSpace+y1path, period = "P") # Gives detflow y1
ratio_y = ModSpeedCalc.flow2speed(inSpace, y1path, fl, limit, outCSV="", dta=True)
# ratio_x = 10.0550935465
# ratio_y = 10.7308926556
# Find Alpha
fdtype = [('idstn','i8'),('flow','f8')]
x1 = readcsv(inSpace+x1path, fdtype, incol = 2, sort = [0], header = None)
y1 = readcsv(inSpace+y1path, fdtype, incol = 2, sort = [0], header = None)
inAF = inSpace+"AF.csv"
fdtype = [('idstn','i8'),('center','i8'),('lane','i8'),('flow','f8'),('dist','f8')]
af = readcsv(inAF, fdtype, incol = 5, sort=0, header = True)
checksum = x1['idstn'] != y1['idstn']
print 'number of detectors out of order:', checksum.sum()
if checksum.sum() > 0:
raise('OH NOES!!, XY not match')
checksum = x1['idstn'] != af['idstn']
print 'number of detectors out of order:', checksum.sum()
if checksum.sum() > 0:
print 'OH NOES!!, AF not match'
vx1 = ratio_x * .06 * x1['flow'] / af['lane']
vy1 = ratio_y * .06 * y1['flow'] / af['lane']
vd = af['dist']
alfa = bisection(0, 1, 0.0001, vx1, vy1, vd)
print "bisection result:", alfa
x1back = x1path[:-4]+str(alfa)+x1path[-4:]
y1back = y1path[:-4]+str(alfa)+y1path[-4:]
shutil.copy(inSpace+x1path,inSpace+x1back)
shutil.copy(inSpace+y1path,inSpace+y1back)
# Create det flow x2
x2flow = x1['flow']+alfa*(y1['flow']-x1['flow'])
x2 = np.copy(x1)
x2['flow'] = x2flow
outX2 = inSpace+'CSV/xdetflow.csv'
np.savetxt(outX2, x2, delimiter=',', fmt='%7.0f, %7.10f')
print "bisection ends on ", time.strftime("%H:%M:%S"), "found alpha =", alfa
return alfa
except Exception as e:
# If an error occurred, print line number and error message
import sys
tb = sys.exc_info()[2]
print "An error occurred in dta_1p line %i" % tb.tb_lineno
print str(e)
outCSV = inSpace + 'ODthrough' + detdesired + '.csv'
inFlow = inSpace + "CSV/TTflow" + str(currentIter) + ".csv"
#Test: 50 TAZs, 1813 DET
#Full: 2241 TAZs, 1813 DETs
nTAZ = 50
nDET = 1813
#fields = ["OriginID", "DestinationID", "Name", "Total_Cost"]
datatype = [('oid', 'i8'), ('did', 'i8'), ('name', 'S20'), ('cost', 'f8')]
#fdtype = [('oid','i8'),('did','i8'),('preflow','f8'),('postflow','f8')]
fdtype = [('oid', 'i8'), ('did', 'i8'), ('postflow', 'f8')]
print "importing various matrices"
#Read TAZ-TAZ flow
ff = readcsv(inFlow, fdtype, incol=3, sort=[0, 1], header=None)
#Read TD cost
td = readcsv(inTD, datatype, incol=4, sort=[1, 0], header=None)
#Read DT cost
dt = readcsv(inDT, datatype, incol=4, sort=[0, 1], header=None)
#Read TT cost
tt = readcsv(inTT, datatype, incol=4, sort=[0, 1], header=None)
nTAZ = int(sqrt(tt.size))
if nTAZ != sqrt(tt.size):
print "ERROR: TAZ SIZE NOT SQUARE!"
if dt.size != td.size:
print "ERROR: TD and DT SIZE NOT MATCH!"
if __name__ == '__main__':
import ModSpeedCalc
from ModIO import readcsv
import os
maxa = 1.
inSpace = "C:\Users\Dennis\Desktop\Results\DTA_Logit_test\Post/"
# Change inSpace to where the current py file is located.
# Should also have AF and xdetflow, ydetflow files.
# inSpace = str(os.path.dirname(__file__)+'/')
x1path = "xdetflow0.186218261719.csv"
y1path = "ydetflow0.186218261719.csv"
fdtype = [('idstn', 'i8'), ('flow', 'f8')]
x1 = readcsv(inSpace + x1path, fdtype, incol=2, sort=[0], header=None)
y1 = readcsv(inSpace + y1path, fdtype, incol=2, sort=[0], header=None)
inAF = inSpace + "AF.csv"
fdtype = [('idstn', 'i8'), ('center', 'i8'), ('lane', 'i8'),
('flow', 'f8'), ('dist', 'f8')]
af = readcsv(inAF, fdtype, incol=5, sort=0, header=True)
ratio_x = ModSpeedCalc.flow2speed(inSpace,
x1path,
fl,
limit,
outCSV="",
dta=True) #detspd-temp.csv
ratio_y = ModSpeedCalc.flow2speed(inSpace,
y1path,
def flow2speed(inSpace, inFlow, FL, LIMIT, outCSV, dta):
'''
Given flow vector, calculate speed vector. Returns ratio at the end.
input:
------
inSpace : str
Working path
inFlow : str
Name of DETECTOR flow vector, ending in CSV,
in program inFlow = inSpace+inFlow
FL : value
Flow / lane cutoff
LIMIT : value
Freeflow speed / speed limit (65)
outCSV : str
outCSV should be without path in inSpace
outCSV = inSpace+outCSV
outCSV = inSpace+'detspd-temp.csv'
outCSV = inSpace+'detspd'+str(currentIter)+'.csv'
, IF EMPTY, return ratio
dta : bool
if False, output detflow_adj in CSV folder
output:
-------
detspd-temp.csv if dta; if not dta detspdi.csv, detflow_adji.csv
'''
import sys
import numpy as np
try:
# read AF for ratio calculation
inAF = inSpace + "AF.csv"
fdtype = [('idstn', 'i8'), ('center', 'i8'), ('lane', 'i8'),
('flow', 'f8'), ('dist', 'f8')]
af = readcsv(inAF, fdtype, incol=5, sort=0, header=True)
# read flow
inFlow = inSpace + inFlow
fdtype = [('idstn', 'i8'), ('flow', 'f8')]
cflow = readcsv(inFlow, fdtype, incol=2, sort=0, header=None)
# CHECK TO MAKE SURE THE ARRAYS MATCHES
x1 = af['idstn']
x2 = cflow['idstn']
xeq = x1 != x2
if xeq.sum() > 0:
raise Exception(
"AF and Current detector flow idstn DOES NOT MATCH!")
# Calculate AF/GF ratio for center detectors
aft = af['center'] * af['flow']
cft = af['center'] * cflow['flow']
ratio = aft.sum() / cft.sum()
print "AF/GF Ratio:", ratio
if outCSV == "":
return ratio
if not dta:
#SAVE DETFLOW WITH ADJUSTMENT if not a DTA round
detFlow = np.copy(cflow)
detFlow['flow'] = detFlow['flow'] * ratio
outCSVcff = inSpace + 'CSV/detflow_adj' + outCSV[6] + '.csv'
np.savetxt(outCSVcff, detFlow, delimiter=',', fmt='%7.0f, %7.10f')
#Convert from GF to the peak time flow F = AF/GF*6%*GF
thisflow = ratio * .06 * cflow['flow'] / af['lane']
vfeedback = np.vectorize(congestion_feedback, otypes=[np.float])
yflow = vfeedback(thisflow, FL, LIMIT)
cflow1 = np.copy(cflow)
cflow1['flow'] = yflow
cflow1.dtype = ([('idstn', '<i8'), ('speed', '<f8')])
# Save temp speed if DTA round, save regular speed if not
outCSV = inSpace + outCSV
print "speed updated. Writing to", outCSV
with open(outCSV, 'wb') as f:
f.write(b'id_stn,speed\n')
np.savetxt(f, cflow1, delimiter=',', fmt='%7.0f, %7.10f')
return ratio
except Exception as e:
tb = sys.exc_info()[2]
print "Exception in ModSpeedCalc"
print "An error occurred in ModSpeedCalc.flow2speed line %i" % tb.tb_lineno
print e.message
