def xtest_smoke_bag(self):
import rosrecord
import visualize
class imgAdapted:
def __init__(self, i):
self.i = i
self.size = (i.width, i.height)
def tostring(self):
return self.i.data
cam = None
filename = "/u/prdata/videre-bags/loop1-mono.bag"
filename = "/u/prdata/videre-bags/vo1.bag"
framecounter = 0
for topic, msg in rosrecord.logplayer(filename):
print framecounter
if rospy.is_shutdown():
break
#print topic,msg
if topic == "/videre/cal_params" and not cam:
cam = camera.VidereCamera(msg.data)
vo = VisualOdometer(cam)
if cam and topic == "/videre/images":
if -1 <= framecounter and framecounter < 360:
imgR = imgAdapted(msg.images[0])
imgL = imgAdapted(msg.images[1])
af = SparseStereoFrame(imgL, imgR)
pose = vo.handle_frame(af)
visualize.viz(vo, af)
framecounter += 1
print "distance from start:", vo.pose.distance()
vo.summarize_timers()
def xtest_smoke_bag(self):
import rosrecord
import visualize
class imgAdapted:
def __init__(self, i):
self.i = i
self.size = (i.width, i.height)
def tostring(self):
return self.i.data
cam = None
filename = "/u/prdata/videre-bags/loop1-mono.bag"
filename = "/u/prdata/videre-bags/vo1.bag"
framecounter = 0
for topic, msg in rosrecord.logplayer(filename):
print framecounter
if rospy.is_shutdown():
break
#print topic,msg
if topic == "/videre/cal_params" and not cam:
cam = camera.VidereCamera(msg.data)
vo = VisualOdometer(cam)
if cam and topic == "/videre/images":
if -1 <= framecounter and framecounter < 360:
imgR = imgAdapted(msg.images[0])
imgL = imgAdapted(msg.images[1])
af = SparseStereoFrame(imgL, imgR)
pose = vo.handle_frame(af)
visualize.viz(vo, af)
framecounter += 1
print "distance from start:", vo.pose.distance()
vo.summarize_timers()
def vizTest():
result = daveAndJane()
# dave = result[0]
# print(dave.nodeGenome)
jane = result[1]
# visualize.viz(dave)
visualize.viz(jane)
def refreshData(SYM, INT, KEY):
SYMBOL = SYM
INTERVAL = INT
API_KEY = KEY
url = f'https://www.alphavantage.co/query?function=TIME_SERIES_INTRADAY&symbol={SYMBOL}&interval={INTERVAL}&apikey={API_KEY}&datatype=csv'
filepath = f'./logs/streamdata-{SYMBOL}-{INTERVAL}.csv'
a = time.time()
df = pd.read_csv(url)
print(df.head())
df.to_csv(filepath)
visualize.viz(df)
b = time.time()
r = b - a
with open('./logs/timedata.csv', 'a') as f:
f.write(f'{r}\n')
else:
print "id", af.id, "inliers:", vo.inl, "proximity:", vo.proximity(
master_frame, af)
comp = visualize.render_source_with_keypoints_stats(
vo, af)
comp.save("/tmp/im%04d.tiff" % (framecounter - start))
else:
vo = vos[0]
af = SparseStereoFrame(imgL, imgR)
vo.handle_frame(af)
if 0:
inliers = [(P0, P1) for (P1, P0) in vo.pe.inliers()]
if inliers != []:
pts3d = [cam.pix2cam(*P1) for (P0, P1) in inliers]
X = [x for (x, y, z) in pts3d]
Y = [y for (x, y, z) in pts3d]
Z = [z for (x, y, z) in pts3d]
print "xrange", min(X), max(X)
print "yrange", min(Y), max(Y)
print "zrange", min(Z), max(Z)
visualize.viz(vo, af)
framecounter += 1
print "distance from start:", vo.pose.distance()
for v in vos:
print v.feature_detector.name(), v.descriptor_scheme.__class__.__name__
v.summarize_timers()
print v.log_keyframes
print
def runGeneration(population, c1, c2, c3, compatabilityThreshold,
fitnessFunction, mateFunction, muteFunction):
# print("Running Generation")
#Seperate into Species
#NEED TO TEST
species = []
# print(population)
species.append([population[0]])
for geno in population[1:]:
for speci in species:
delta = geno.compatabilityDistance(random.choice(speci), c1, c2,
c3)
if delta < compatabilityThreshold:
speci.append(geno)
break
else:
#was not assigned to a species
species.append([geno])
print("Size of population: " + str(len(population)))
print("Number of species: " + str(len(species)))
#Evaluation
#getting max fitness for return
maxFit = 0
maxGeno = species[0][0]
longGeno = species[0][0]
#speciesWEval = [[(geno, fitness), (g, f)],[spec2],[spec3]...]
print("Starting Evaluation")
speciesWEval = []
for speci in species:
speciVal = []
for geno in speci:
fitness = fitnessFunction(geno)
# print("fitness: " + str(fitness))
speciVal.append((geno, fitness))
if fitness > maxFit:
maxFit = fitness
maxGeno = geno
if len(geno.nodeGenome) > len(longGeno.nodeGenome):
longGeno = geno
"""
if fitness != 0.13:
for i in range(10):
print("LOOOOOOOOK ITS NOT 13")
if len(geno.connectGenome) != 10 or len(geno.nodeGenome) != 11:
for i in range(10):
print("LOOOOOOOOK STRUCTURE MUTATION")
"""
speciesWEval.append(speciVal)
print("Finished Evaluation")
visualize.viz(maxGeno)
visualize.viz(longGeno)
print("MaxFit inside gen: " + str(maxFit))
#Grwoth/decline of species
#adjusted fitness
speciesWAdjEval = []
for speci in speciesWEval:
speciVal = []
for genoFPair in speci:
speciVal.append((genoFPair[0], genoFPair[1] / len(speci)))
speciesWAdjEval.append(speciVal)
# print(speciesWAdjEval)
#mean adjusted fitness
adjSum = 0
count = 0
for speci in speciesWAdjEval:
for genoFPair in speci:
adjSum += genoFPair[1]
count += 1
meanF = adjSum / count
#mating
unmutedPop = []
for speci in speciesWAdjEval:
adjSum = 0
for genoFPair in speci:
adjSum += genoFPair[1]
if len(population) < 50:
newNum = int(math.ceil(adjSum / meanF))
else:
newNum = int(math.floor(adjSum / meanF))
unmutedPop.append(mateFunction(speci, newNum))
#mutating
mutedPop = []
for speci in unmutedPop:
for pop in speci:
mutedPop.append(muteFunction(pop))
return (mutedPop, maxFit)
if af.id == 0:
master_frame = af
else:
print "id", af.id, "inliers:", vo.inl, "proximity:", vo.proximity(master_frame, af)
comp = visualize.render_source_with_keypoints_stats(vo, af)
comp.save("/tmp/im%04d.tiff" % (framecounter - start))
else:
vo = vos[0]
af = SparseStereoFrame(imgL, imgR)
vo.handle_frame(af)
if 0:
inliers = [ (P0,P1) for (P1,P0) in vo.pe.inliers()]
if inliers != []:
pts3d = [cam.pix2cam(*P1) for (P0,P1) in inliers]
X = [ x for (x,y,z) in pts3d ]
Y = [ y for (x,y,z) in pts3d ]
Z = [ z for (x,y,z) in pts3d ]
print "xrange", min(X), max(X)
print "yrange", min(Y), max(Y)
print "zrange", min(Z), max(Z)
visualize.viz(vo, af)
framecounter += 1
print "distance from start:", vo.pose.distance()
for v in vos:
print v.feature_detector.name(), v.descriptor_scheme.__class__.__name__
v.summarize_timers()
print v.log_keyframes
print
