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# Train a network offline
# Inputs: two scaled front sensor readings
# Outputs: one translate reading (unscaled)
from pyrobot.brain.conx import *
from pyrobot.system.log import *
def setFromFile(filename, cols = None, delim = ' '):
fp = open(filename, "r")
line = fp.readline()
lineno = 1
lastLength = None
data = []
while line:
linedata = [float(x) for x in line.strip().split(delim)]
if cols == None: # get em all
newdata = linedata
else: # just get some cols
newdata = []
for i in cols:
newdata.append( linedata[i] )
if lastLength == None or len(newdata) == lastLength:
data.append( newdata )
else:
raise "DataFormatError", "line = %d" % lineno
lastLength = len(newdata)
lineno += 1
line = fp.readline()
fp.close()
print "length of data array is", len(data)
return data
def saveListToFile(ls, file):
for i in range(len(ls)):
file.write(str(ls[i]) + " ")
file.write("\n")
# Create the network
n = Network()
n.addLayers(2,1,1)
# Set learning parameters
n.setEpsilon(0.3)
n.setMomentum(0.0)
n.setTolerance(0.05)
# set inputs and targets (from collected data set)
n.setInputs(setFromFile('frontsensors.dat'))
n.setTargets(setFromFile('translatetargets.dat'))
# Logging
log = Log(name = 'E05M01.txt')
best = 0
for i in xrange(0,1000,1):
tssError, totalCorrect, totalCount, totalPCorrect = n.sweep()
correctpercent = (totalCorrect*0.1) / (totalCount*0.1)
log.writeln( "Epoch # "+ str(i)+ " TSS ERROR: "+ str(tssError)+
" Correct: "+ str(totalCorrect)+ " Total Count: "+
str(totalCount)+ " %correct = "+ str(correctpercent))
if best < correctpercent:
n.saveWeightsToFile("E05M01.wts")
best = correctpercent
print "done" |
