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plotDist.py
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plotDist.py
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from matplotlib import pyplot
from matplotlib import colors
import numpy
import math
def skip_lines(f,lines):
for i in range(lines):
f.readline()
def get_data(fileName):
#hold the positions - FIX THIS LATER
statesInRbt = [[[],[]],[[],[]],[[],[]],[[],[]],[[],[]],[[],[]]]
#hold the log probs - FIX THIS LATER
logProbs = [[]]
f = open(fileName,'r')
#read the initial stuff you need
f.readline()
actionType = int(f.readline())
f.readline()
model = int(f.readline())
skip_lines(f,5)
numStates = int(f.readline())
skip_lines(f,numStates*6+2)
# here's where we need to get the cartesian version of the states
for i in range(numStates):
holdLine = f.readline()
valList = holdLine.split(',')
numList = []
numList.append(int(valList[0]))
numList.append(float(valList[1]))
numList.append(float(valList[2]))
statesInRbt[numList[0]][0].append(numList[1])
statesInRbt[numList[0]][1].append(numList[2])
skip_lines(f,1)
numActions = int(f.readline())
skip_lines(f,numActions+2)
numMPPairs = int(f.readline())
# this is gonna be a problem
numVarTypes = []
skip_lines(f,1)
for i in range(numMPPairs):
skip_lines(f,5)
numVarTypes.append(int(f.readline()))
skip_lines(f,1)
for i in range(numStates):
logProbs[0].append(float(f.readline()))
skip_lines(f,1+numMPPairs+1)
# broken into two lines: skip_lines(f,numMPPairs*(6+1)+(1+1+1+1)+numStates)
data = []
for i in range(numMPPairs):
data.append([float(f.readline())])
skip_lines(f,1)
# get the initial pose in rbt:
poses = [[],[]]
holdPose = f.readline()
stringList = holdPose.split(',')
stringList.pop() # get rid of the empty string at the end because of the last ,
poseList = []
poseList.append(float(stringList[0]))
poseList.append(float(stringList[1]))
poses[0].append(poseList[0])
poses[1].append(poseList[1])
skip_lines(f,1)
numSteps = int(f.readline())
#this has to happen until you get to the end of the file
actions = [[],[]]
obs = [[],[]]
for i in range(numSteps):
skip_lines(f,5)
# get action. hellz yeah.
holdAction = f.readline()
actionString = holdAction.split(',')
actionString.pop() # get rid of the empty string at the end because of the last ,
actionList = []
actionList.append(float(actionString[0]))
actionList.append(float(actionString[1]))
actions[0].append(actionList[0])
actions[1].append(actionList[1])
skip_lines(f,1)
# get current pose
holdP = f.readline()
stringL = holdP.split(',')
stringL.pop() # get rid of the empty string at the end because of the last ,
poseL = []
poseL.append(float(stringL[0]))
poseL.append(float(stringL[1]))
poses[0].append(poseL[0])
poses[1].append(poseL[1])
skip_lines(f,1)
# get obs
holdO = f.readline()
stringLO = holdO.split(',')
stringLO.pop() # get rid of the empty string at the end because of the last ,
obsL = []
obsL.append(float(stringLO[0]))
obsL.append(float(stringLO[1]))
obs[0].append(obsL[0])
obs[1].append(obsL[1])
skip_lines(f,1)
logProbs.append([])
for i in range(numStates):
logProbs[-1].append(float(f.readline()))
skip_lines(f,1+numMPPairs+1)
#skip_lines(f,11+numStates+1+numMPPairs+1)
for j in range(numMPPairs):
data[j].append(float(f.readline()))
f.close()
return data, numSteps, numMPPairs, model, statesInRbt, logProbs, poses, actions, obs, actionType, numVarTypes
#main
#fileName = 'data/data0Thu_Dec_12_09_30_05_2013.txt' #relative but wrong
#fileName = 'data/data0Thu_Dec_12_14_10_47_2013.txt' #absolute but wrong
#fileName = 'data/data0Thu_Dec_12_09_30_05_2013.txt' #relative but wrong
#fileName = 'data/data0Sun_Dec_15_23_19_13_2013.txt' #absolute
#fileName = 'data/data0Sun_Dec_15_23_26_33_2013.txt' #absolute 10 steps
#fileName = 'data/data0Sun_Dec_15_23_42_44_2013.txt' #absolute with addition
#fileName = 'data/data0Sun_Dec_15_23_53_49_2013.txt' #absolute
#fileName = 'data/data0Mon_Dec_16_00_01_26_2013.txt' #relative
#consistent actions
#consistent transition model and real world
#trans var - 0.0001, obs var - 0.01
#fileName = 'data/data0Mon_Dec_16_00_03_35_2013.txt' #TM-relative, W-relative
#fileName = 'data/data0Mon_Dec_16_00_05_45_2013.txt' #TM-absolute, W-absolute
#fileName = 'data/data0Mon_Dec_16_00_53_28_2013.txt' #TM-absolute, W-relative
#fileName = 'data/data0Mon_Dec_16_00_57_23_2013.txt' #TM-relative, W-absolute
#trans var - 0.01, obs var - 0.01
#fileName = 'data/data0Mon_Dec_16_09_35_38_2013.txt' #TM-relative, W-relative
#fileName = 'data/data0Mon_Dec_16_09_32_21_2013.txt' #TM-absolute, W-absolute
#fileName = 'data/data0Mon_Dec_16_09_34_39_2013.txt' #TM-absolute, W-relative
#fileName = 'data/data0Mon_Dec_16_09_29_57_2013.txt' #TM-relative, W-absolute
#after fix
#trans var - 0.0001, obs var - 0.0001
#fileName = 'data/data0Mon_Dec_16_10_38_07_2013.txt' #TM-relative, W-relative
#fileName = 'data/data0Mon_Dec_16_10_35_14_2013.txt' #TM-absolute, W-absolute
#fileName = 'data/data0Mon_Dec_16_10_32_25_2013.txt' #TM-absolute, W-relative
#fileName = 'data/data0Mon_Dec_16_10_36_40_2013.txt' #TM-relative, W-absolute
#fileName = 'data/data0Thu_Feb__6_17_01_53_2014.txt' # just a test
#fileName = 'data/data0Wed_Feb_12_11_59_09_2014.txt' # testing modelParamPairs
#fileName = 'data/data0Wed_Feb_12_16_04_52_2014.txt' # back to more models
#fileName = 'data/data0Wed_Feb_12_16_12_25_2014.txt' # full models
#fileName = 'data/data0Wed_Feb_12_16_19_32_2014.txt' #full models, absolute
#fileName = 'data/data0Wed_Feb_12_16_28_02_2014.txt' # full models, absolute, regular actions
#fileName = 'data/data0Thu_Feb_13_13_54_20_2014.txt' # full models, absolute, regular actions, noise, entropy action selection
#fileName = 'data/data0Fri_Feb_14_14_55_50_2014.txt' # full models, absolute, regular actions, noise, entropy action selection, new state space for L2
#fileName = 'data/data0Fri_Feb_14_15_02_45_2014.txt' # try again
#fileName = 'data/data0Fri_Feb_14_15_40_07_2014.txt' # try again again - final
# 2/24/14 - seeing if absolute and relative are the same:
#fileName = 'data/data0Mon_Feb_24_12_37_16_2014.txt' # absolute
#fileName = 'data/data0Mon_Feb_24_12_38_29_2014.txt' # relative
# 2/26/14 - no noise
#fileName = 'data/data0Wed_Feb_26_09_40_55_2014.txt' # absolute
fileName = 'data/data0Wed_Feb_26_09_41_34_2014.txt' # relative
# parameters
plotLog = True
data, numSteps, numMPPairs, model, statesInRbt, logProbs, poses, actions, obs, actionType, numVarTypes = get_data(fileName)
# make indeces from numVarTypes
probInds=[0]
for i in range(len(numVarTypes)):
probInds.append(probInds[i]+numVarTypes[i])
# make list of symbols
symList = ["o","s","*","D","^","v"]
# model names list
modelNames = ["Free","Fixed","Rev","Pris","L1","L2"]
#print probInds
#print numVarTypes
#print len(logProbs[0][numVarTypes[0]:numVarTypes[1]])
#print len(data)
#print 'max'
#print math.exp(max(logProbs[2]))
# plot parameters
mSize = 10
sSize = 50
if actionType == 0:
actionString = 'Absolute'
elif actionType == 1:
actionString = 'Relative'
rows = int(math.floor(math.sqrt(numSteps)))
columns = int(math.ceil(float(numSteps)/float(rows)))
if rows*columns<numSteps+1:
if rows<columns:
rows += 1
else:
columns += 1
# initial distribution
pyplot.subplot(rows,columns,1)
pyplot.subplots_adjust(left=0.05,right=1.0,bottom=0.15,top=0.95,wspace=0.2,hspace=0.4)
if plotLog:
colorNorm = colors.Normalize(-100,0)
else:
colorNorm = colors.Normalize(0,1) # YOU NEED THIS SO STUFF DOESN'T EXPLODDDEEE
# without colorNorm, you can't do repeated plotting and get a useful
# color answer becasue it normalize colors by default
'''
xs = []
ys = []
for j in range(len(statesInRbt)):
xs.extend(statesInRbt[j][0])
ys.extend(statesInRbt[j][1])
pyplot.scatter(xs,ys,c=logProbs[0],s=sSize)
'''
#print 'hello'
#print len(statesInRbt[1][0])
#print len(logProbs[0][numVarTypes[1]:numVarTypes[2]])
#print len(data[0])
for j in range(len(statesInRbt)):
if plotLog:
pyplot.scatter(statesInRbt[j][0],statesInRbt[j][1],c=logProbs[0][probInds[j]:probInds[j+1]],s=sSize,marker=symList[j],norm=colorNorm)
else:
pyplot.scatter(statesInRbt[j][0],statesInRbt[j][1],c=[math.exp(x) for x in logProbs[0][probInds[j]:probInds[j+1]]],s=sSize,marker=symList[j],norm=colorNorm)
# create the list for the legend
legendList=[]
for i in range(len(data)):
legendList.append(modelNames[i]+" - "+str("%.3G" % (data[i][0])))
pyplot.legend(legendList,bbox_to_anchor=(0., -.325, 1., .5), loc=3, ncol=2, mode="expand", borderaxespad=0.)
pyplot.colorbar()
pyplot.plot(poses[0][0],poses[1][0],'ro',markersize=mSize)
pyplot.title('initial - '+actionString)
print actionString
print 'Initialization:'
print [d[0] for d in data]
for i in range(numSteps):
pyplot.subplot(rows,columns,i+2)
#pyplot.clim(0,1)
for j in range(len(statesInRbt)):
if plotLog:
pyplot.scatter(statesInRbt[j][0],statesInRbt[j][1],c=logProbs[i+1][probInds[j]:probInds[j+1]],s=sSize,marker=symList[j],norm=colorNorm)
else:
pyplot.scatter(statesInRbt[j][0],statesInRbt[j][1],c=[math.exp(x) for x in logProbs[i+1][probInds[j]:probInds[j+1]]],s=sSize,marker=symList[j],norm=colorNorm)
pyplot.hold(True)
#print 'max'+str(i)+str(j)
#print math.exp(max(logProbs[i+1][probInds[j]:probInds[j+1]]))
'''
xs = []
ys = []
for j in range(len(statesInRbt)):
xs.extend(statesInRbt[j][0])
ys.extend(statesInRbt[j][1])
pyplot.scatter(xs,ys,c=[math.exp(x) for x in logProbs[i+1]],s=sSize)
'''
# create the list for the legend
legendList=[]
for k in range(len(data)):
legendList.append(modelNames[k]+" - "+str("%.3G" % (data[k][i+1])))
pyplot.legend(legendList,bbox_to_anchor=(0., -.325, 1., .5), loc=3, ncol=2, mode="expand", borderaxespad=0.)
pyplot.colorbar()
print 'step: '+str(i)
pyplot.plot(poses[0][i],poses[1][i],'ro',markersize=mSize)
print 'start: '+str(poses[0][i])+','+str(poses[1][i])
pyplot.plot(poses[0][i+1],poses[1][i+1],'bo',markersize=mSize)
print 'end: '+str(poses[0][i+1])+','+str(poses[1][i+1])
if actionType == 0:
pyplot.plot(actions[0][i],actions[1][i],'g^',markersize=mSize)
print 'action: '+str(actions[0][i])+','+str(actions[1][i])
elif actionType == 1:
pyplot.plot(actions[0][i]+poses[0][i],actions[1][i]+poses[1][i],'g^',markersize=mSize)
print 'action: '+str(actions[0][i])+','+str(actions[1][i])
print 'result: '+str(actions[0][i]+poses[0][i])+','+str(actions[1][i]+poses[1][i])
pyplot.plot(obs[0][i],obs[1][i],'yx',markersize=mSize)
print 'obs: '+str(obs[0][i])+','+str(obs[1][i])
pyplot.title('step'+str(i))
print 'Distribution:'
print [d[i+1] for d in data]
pyplot.show()
'''
for b in range(len(statesInRbt)):
pyplot.plot(statesInRbt[b][0],statesInRbt[b][1],'o')
pyplot.show()
'''
'''
#main
#just to get the numbers we want
model = 0
asTypes = ['simple','random','entropy']
asNum = 2
path = 'data/model'+str(model)+'/'+asTypes[asNum]+'/'
print path
startFileName = path+'data'+str(model)+'_0.txt'
#setup
startData, nSteps, nMPPairs, m = get_data(startFileName)
totalData = numpy.array(startData)
trials = 10 #how many trials
for i in range(1,trials):
fileName = path+'data'+str(model)+'_'+str(i)+'.txt'
data, numSteps, numMPPairs, model = get_data(fileName)
dataArray = numpy.array(data)
totalData += dataArray
avgData = totalData/trials
#print avgData[5,:]
inds = range(nSteps+1)
models = ['Free','Fixed','Rev','Pris','RevPrisL','PrisPrisL']
for i in range(nMPPairs):
pyplot.plot(inds,avgData[i,:],'-o')
pyplot.title(models[m]+' - '+asTypes[asNum])
pyplot.ylabel('Probability')
pyplot.xlabel('Step')
pyplot.legend(models,loc=2)
pyplot.show()
## data, numSteps, numMPPairs, model = get_data('data5Sun_Sep_15_17_10_07_2013.txt')
## inds = range(numSteps+1)
## models = ['Free','Fixed','Rev','Pris','RevPrisL','PrisPrisL']
## #colors = ['r','g',
## for i in range(numMPPairs):
## pyplot.plot(inds,data[i],'-o')
## pyplot.title(models[model])
## pyplot.ylabel('Probability')
## pyplot.xlabel('Step')
## pyplot.legend(models)
## dataArray = numpy.array(data)
## print dataArray
## print dataArray[5,:]
## pyplot.show()
'''