def sim2(nsim):
# Environment parameters
sidelen = 100.0
# Measurement parameters
sig = 5.0
g = 5
t = 45.0
obstimes1_w = [10.0, 16.0, 30.0, 40.0] # [10,15,20] # way points only at this point
obstimes2_w = [6.0, 13.0, 27.0, 36.0]
# Generate graph
G = roadnet.makegridgraph(g, sidelen)
# Vehicle parameters
p1 = [0, 1, 6, 7, 12, 11, 16]
nseg1 = len(p1) - 1
p2 = [13, 12, 7, 6, 1, 2, 3]
nseg2 = len(p2) - 1
vmax = 60 / 3.6
alph = 5.0
bet = 1.25
# Meeting parameters
segn = [3, 3] # Meeting segment for objects
dres = 50.0 # Distance along meeting segment for object 1
xM = roadnet.getpos(G, p1, (segn[0] - 1) * sidelen + dres, sidelen)
tM = 21.0
T = 0.0
t = t + T
p1bm = p1[0 : segn[0] + 1]
p1am = p1[(segn[0] - 1) : (nseg1 + 1)]
p2bm = p2[0 : segn[1] + 1]
p2am = p2[(segn[1] - 1) : (nseg2 + 1)]
print p2bm
print p1bm
print p2am
print p1am
print xM
# Algorithm parameters
n = 400
K = 10
m1 = 2
m2 = 2
# Generate candidate paths
numcandp1 = 0
d1 = 0
while numcandp1 < K:
candp1 = list(nx.all_simple_paths(G, p1[0], p1[-1], d1))
numcandp1 = len(candp1)
d1 = d1 + 1
numcandp2 = 0
d2 = 0
while numcandp2 < K:
candp2 = list(nx.all_simple_paths(G, p2[0], p2[-1], d2))
numcandp2 = len(candp2)
d2 = d2 + 1
# print numcandp
# Put in a suitable format for processing
segls1 = numpy.zeros((numcandp1, d1 - 1))
for i in range(numcandp1):
print candp1[i]
for j in range(len(candp1[i]) - 1):
segls1[i, j] = sidelen
segls2 = numpy.zeros((numcandp2, d2 - 1))
for i in range(numcandp2):
print candp2[i]
for j in range(len(candp2[i]) - 1):
segls2[i, j] = sidelen
# Generate data
random.seed(2.0)
z1 = roadnet.makedata2(G, p1bm, p1am, xM, tM, T, t, obstimes1_w, sig, vmax, alph, bet)
z2 = roadnet.makedata2(G, p2bm, p2am, xM, tM, T, t, obstimes2_w, sig, vmax, alph, bet)
random.seed()
roadnet.plotpath(G, p2)
xpos = z2[0, :]
ypos = z2[1, :]
plt.plot(xpos, ypos, "rx")
print z1
print z2
ntpts = 7
tax = numpy.linspace(16, 22, ntpts)
bcoeff = numpy.zeros((nsim, ntpts))
tmax = numpy.zeros((nsim))
for cnt in range((nsim)):
print cnt
# Generate data
# z1 = roadnet.makedata2(G,p1bm,p1am,xM,tM,T,t,obstimes1_w,sig,vmax,alph,bet)
# z2 = roadnet.makedata2(G,p2bm,p2am,xM,tM,T,t,obstimes2_w,sig,vmax,alph,bet)
# First stage of processing (case 1 for each object)
obstimes1 = numpy.zeros((len(obstimes1_w) + 2))
obstimes1[0] = 0.0
for i in range(len(obstimes1_w)):
obstimes1[i + 1] = obstimes1_w[i]
obstimes1[-1] = t
obstimes2 = numpy.zeros((len(obstimes2_w) + 2))
obstimes2[0] = 0.0
for i in range(len(obstimes2_w)):
obstimes2[i + 1] = obstimes2_w[i]
obstimes2[-1] = t
[datamat1, isvalid1, pP01, v1, tcum1] = case2.arclgen(obstimes1, segls1, n, vmax, alph, bet)
[datamat2, isvalid2, pP02, v2, tcum2] = case2.arclgen(obstimes2, segls2, n, vmax, alph, bet)
# Convert to positions in 2D space
xpts1 = numpy.zeros((n * numcandp1, 2 * len(obstimes1)))
for i in range((numcandp1)):
for k in range((n)):
idx = k + i * n
if isvalid1[idx]:
# print candp[i]
for j in range(len(obstimes1)):
pos = roadnet.getpos(G, candp1[i], datamat1[idx, j], sidelen)
xpts1[idx, 2 * j] = pos[0]
xpts1[idx, 2 * j + 1] = pos[1]
print isvalid2.sum()
xpts2 = numpy.zeros((n * numcandp2, 2 * len(obstimes2)))
for i in range((numcandp2)):
for k in range((n)):
idx = k + i * n
if isvalid2[idx]:
# print candp[i]
for j in range(len(obstimes2)):
pos = roadnet.getpos(G, candp2[i], datamat2[idx, j], sidelen)
if i == 14:
plt.plot(pos[0], pos[1], "g.")
xpts2[idx, 2 * j] = pos[0]
xpts2[idx, 2 * j + 1] = pos[1]
# print datamat[cnt,:]
# print xpts[cnt,:]
[pP1, w1, pP1w, ww1] = case2.calcpostprobs(z1, xpts1, isvalid1, pP01, sig)
[pP2, w2, pP2w, ww2] = case2.calcpostprobs(z2, xpts2, isvalid2, pP02, sig)
print pP1w
print pP2w
print 1 / sum(ww1 ** 2)
print 1 / sum(ww2 ** 2)
w1cdf = numpy.cumsum(ww1)
w2cdf = numpy.cumsum(ww2)
maxval = -1.0
for a in range((ntpts)):
# print a
random.seed(3.0)
uj = random.uniform(0, 1.0 / m1)
i = 0
for j in range((m1)):
while w2cdf[i] < uj:
i = i + 1
# Find s
pathidx = i / n
[snum, seg, pos] = roadnet.getseg(G, candp2[pathidx], v2[i, :], tcum2[i, :], tax[a], sidelen)
res2 = abs((pos - G.node[candp2[pathidx][snum]]["pos"]).sum())
print pos
# MC approximation of p1 and p2
random.seed(4.0)
uk = random.uniform(0, 1.0 / m2)
l1 = 0
l2 = 0
post1 = 0.0
post2 = 0.0
# print i, ww2[i]
for k in range((m2)):
while w1cdf[l1] < uk:
l1 = l1 + 1
while w2cdf[l2] < uk:
l2 = l2 + 1
pathidx1 = l1 / n
[snum1, seg1, pos1] = roadnet.getseg(G, candp1[pathidx1], v1[l1, :], tcum1[l1, :], tax[a], sidelen)
print pos1
if (seg1[0] == seg[0]) and (seg1[1] == seg[1]):
if snum1 > 0:
tleft = tax[a] - tcum1[l1, snum1 - 1]
else:
tleft = tax[a]
post1 = post1 + scipy.stats.beta.pdf(res2 / (vmax * tleft), alph, bet) / (m2 * vmax * tleft)
elif (seg1[0] == seg[1]) and (seg1[1] == seg[0]):
if snum1 > 0:
tleft = tax[a] - tcum1[l1, snum1 - 1]
else:
tleft = tax[a]
# print tcum1[l1,:]
# print tleft
# print vmax*tleft
# print res2
print (sidelen - res2)
print tleft
post1 = post1 + scipy.stats.beta.pdf((sidelen - res2) / (vmax * tleft), alph, bet) / (
m2 * vmax * tleft
)
pathidx2 = l2 / n
[snum2, seg2, pos2] = roadnet.getseg(G, candp2[pathidx2], v2[l2, :], tcum2[l2, :], tax[a], sidelen)
# print seg, seg2
if (seg2[0] == seg[0]) and (seg2[1] == seg[1]):
if snum2 > 0:
tleft = tax[a] - tcum2[l2, snum2 - 1]
else:
tleft = tax[a]
post2 = post2 + scipy.stats.beta.pdf(res2 / (vmax * tleft), alph, bet) / (m2 * vmax * tleft)
uk = uk + 1.0 / m2
# print post1, post2
if post2 > 1e-20:
bcoeff[cnt, a] = bcoeff[cnt, a] + math.sqrt(post1 / post2) / m1
uj = uj + 1.0 / m1
if bcoeff[cnt, a] > maxval:
maxval = bcoeff[cnt, a]
tmax[cnt] = tax[a]
# print bcoeff
return bcoeff, tmax
def sim1(nsim):
# Environment parameters
sidelen = 100.0
# Measurement parameters
sig = 5.0
g = 5
t = 60
t = 40.0
obstimes1_w = [10] # [10,15,20] # way points only at this point
obstimes2_w = [5, 20]
# Vehicle parameters
# p = [0,1,7,13,14,15,21,22]
p1 = [0, 1, 6, 7, 12, 11, 16]
p2 = [13, 12, 7, 6, 1, 2]
# p = [0,1,2,7]
vmax = 60 / 3.6
alph = 5
bet = 1.25
# Algorithm parameters
n = 100
K = 5
m1 = 10
m2 = 10
# Generate graph
G = roadnet.makegridgraph(g, sidelen)
# Generate candidate paths
numcandp1 = 0
d1 = 0
while numcandp1 < K:
candp1 = list(nx.all_simple_paths(G, p1[0], p1[-1], d1))
numcandp1 = len(candp1)
d1 = d1 + 1
numcandp2 = 0
d2 = 0
while numcandp2 < K:
candp2 = list(nx.all_simple_paths(G, p2[0], p2[-1], d2))
numcandp2 = len(candp2)
d2 = d2 + 1
# print numcandp
# Put in a suitable format for processing
segls1 = numpy.zeros((numcandp1, d1 - 1))
for i in range(numcandp1):
print candp1[i]
for j in range(len(candp1[i]) - 1):
segls1[i, j] = sidelen
segls2 = numpy.zeros((numcandp2, d2 - 1))
for i in range(numcandp2):
print candp2[i]
for j in range(len(candp2[i]) - 1):
segls2[i, j] = sidelen
# Generate data
tact = 0
while abs(tact - t) > 0.01:
[z1, tact] = roadnet.makedata(G, p1, obstimes1_w, sig, vmax, alph, bet)
tact = 0
while abs(tact - t) > 0.01:
[z2, tact] = roadnet.makedata(G, p2, obstimes2_w, sig, vmax, alph, bet)
for cnt in range((nsim)):
print cnt
# Generate data
tact = 0
while abs(tact - t) > 0.01:
[z1, tact] = roadnet.makedata(G, p1, obstimes1_w, sig, vmax, alph, bet)
tact = 0
while abs(tact - t) > 0.01:
[z2, tact] = roadnet.makedata(G, p2, obstimes2_w, sig, vmax, alph, bet)
# First stage of processing
obstimes1 = numpy.zeros((len(obstimes1_w) + 2))
obstimes1[0] = 0.0
for i in range(len(obstimes1_w)):
obstimes1[i + 1] = obstimes1_w[i]
obstimes1[-1] = t
obstimes2 = numpy.zeros((len(obstimes2_w) + 2))
obstimes2[0] = 0.0
for i in range(len(obstimes2_w)):
obstimes2[i + 1] = obstimes2_w[i]
obstimes2[-1] = t
[datamat1, isvalid1, pP01, v1, tcum1] = case2.arclgen(obstimes1, segls1, n, vmax, alph, bet)
[datamat2, isvalid2, pP02, v2, tcum2] = case2.arclgen(obstimes2, segls2, n, vmax, alph, bet)
# Convert to positions in 2D space
xpts1 = numpy.zeros((n * numcandp1, 2 * len(obstimes1)))
for i in range((numcandp1)):
for k in range((n)):
cnt = k + i * n
if isvalid1[cnt]:
# print candp[i]
for j in range(len(obstimes1)):
pos = roadnet.getpos(G, candp1[i], datamat1[cnt, j], sidelen)
xpts1[cnt, 2 * j] = pos[0]
xpts1[cnt, 2 * j + 1] = pos[1]
xpts2 = numpy.zeros((n * numcandp2, 2 * len(obstimes2)))
for i in range((numcandp2)):
for k in range((n)):
cnt = k + i * n
if isvalid2[cnt]:
# print candp[i]
for j in range(len(obstimes2)):
pos = roadnet.getpos(G, candp2[i], datamat2[cnt, j], sidelen)
xpts2[cnt, 2 * j] = pos[0]
xpts2[cnt, 2 * j + 1] = pos[1]
# print datamat[cnt,:]
# print xpts[cnt,:]
[pP1, w1, pP1w, ww1] = case2.calcpostprobs(z1, xpts1, isvalid1, pP01, sig)
[pP2, w2, pP2w, ww2] = case2.calcpostprobs(z2, xpts2, isvalid2, pP02, sig)
print pP1w
print pP2w
npts = 20
tax = numpy.linspace(1, 35, npts)
bcoeff = numpy.zeros(npts)
w1cdf = numpy.cumsum(ww1)
w2cdf = numpy.cumsum(ww2)
for a in range((npts)):
# print a
uj = random.uniform(0, 1.0 / m1)
i = 0
for j in range((m1)):
while w2cdf[i] < uj:
i = i + 1
# Find s
pathidx = i / n
[snum, seg, pos] = roadnet.getseg(G, candp2[pathidx], v2[i, :], tcum2[i, :], tax[a], sidelen)
res2 = abs((pos - G.node[candp2[pathidx][snum]]["pos"]).sum())
# print seg
# MC approximation of p1 and p2
uk = random.uniform(0, 1.0 / m2)
l1 = 0
l2 = 0
post1 = 0
post2 = 0
# print i, ww2[i]
for k in range((m2)):
while w1cdf[l1] < uk:
l1 = l1 + 1
while w2cdf[l2] < uk:
l2 = l2 + 1
pathidx1 = l1 / n
[snum1, seg1, pos1] = roadnet.getseg(G, candp1[pathidx1], v1[l1, :], tcum1[l1, :], tax[a], sidelen)
if (seg1[0] == seg[0]) and (seg1[1] == seg[1]):
if snum1 > 0:
tleft = tax[a] - tcum1[l1, snum1 - 1]
else:
tleft = tax[a]
post1 = post1 + scipy.stats.beta.pdf(res2 / (vmax * tleft), alph, bet) / (m2 * vmax * tleft)
elif (seg1[0] == seg[1]) and (seg1[1] == seg[0]):
if snum1 > 0:
tleft = tax[a] - tcum1[l1, snum1 - 1]
else:
tleft = tax[a]
post1 = post1 + scipy.stats.beta.pdf((sidelen - res2) / (vmax * tleft), alph, bet) / (
m2 * vmax * tleft
)
pathidx2 = l2 / n
[snum2, seg2, pos2] = roadnet.getseg(G, candp2[pathidx2], v2[l2, :], tcum2[l2, :], tax[a], sidelen)
# print seg, seg2
if (seg2[0] == seg[0]) and (seg2[1] == seg[1]):
if snum2 > 0:
tleft = tax[a] - tcum2[l2, snum2 - 1]
else:
tleft = tax[a]
post2 = post2 + scipy.stats.beta.pdf(res2 / (vmax * tleft), alph, bet) / (m2 * vmax * tleft)
uk = uk + 1.0 / m2
# print p1, p2
if post2 > 1e-20:
bcoeff[a] = bcoeff[a] + math.sqrt(post1 / post2) / m1
uj = uj + 1.0 / m1
print bcoeff
return ww1, ww2