def run(rs):
'''
Takes the Brent trajectories as input, shuffles them, and then runs the NN regression algorithm
'''
#state, command = getStateAndCommandData(BrentTrajectoriesFolder)
#stateAll, commandAll = dicToArray(state), dicToArray(command)
#print ("old:", stateAll[0])
#stateAll, commandAll = stateAndCommandDataFromTrajs(loadStateCommandPairsByStartCoords(pathDataFolder + "Brent/", 0.1, rs.det))
stateAll, commandAll = loadTrajs(pathDataFolder + "Brent/", 1, rs.det)
print("RunRegression L52")
#stateAll, commandAll = stateAndCommandDataFromTrajs(loadStateCommandPairsByStartCoords(BrentTrajectoriesFolder))
#print ("len:", len(commandAll[0]))
stateAll = np.vstack(np.array(stateAll))
commandAll = np.vstack(np.array(commandAll))
#print ("len global:", len(commandAll))
#print ("new:", commandAll[0])
#this works because both shuffles generate the same order, due to the seed
np.random.seed(0)
np.random.shuffle(stateAll)
np.random.seed(0)
np.random.shuffle(commandAll)
print("nombre d'echantillons: ", len(stateAll))
fa = regressionDict[rs.regression](rs)
fa.getTrainingData(stateAll, commandAll)
fa.train()
fa.saveTheta(rs.path+ rs.thetaFile+".theta")
def run(rs):
'''
Takes the Brent trajectories as input, shuffles them, and then runs the NN regression algorithm
'''
#state, command = getStateAndCommandData(BrentTrajectoriesFolder)
#stateAll, commandAll = dicToArray(state), dicToArray(command)
#print ("old:", stateAll[0])
#stateAll, commandAll = stateAndCommandDataFromTrajs(loadStateCommandPairsByStartCoords(pathDataFolder + "Brent/", 0.1, rs.det))
stateAll, commandAll = loadTrajs(pathDataFolder + "Brent/", 1, rs.det)
print("RunRegression L52")
#stateAll, commandAll = stateAndCommandDataFromTrajs(loadStateCommandPairsByStartCoords(BrentTrajectoriesFolder))
#print ("len:", len(commandAll[0]))
stateAll = np.vstack(np.array(stateAll))
commandAll = np.vstack(np.array(commandAll))
#print ("len global:", len(commandAll))
#print ("new:", commandAll[0])
#this works because both shuffles generate the same order, due to the seed
np.random.seed(0)
np.random.shuffle(stateAll)
np.random.seed(0)
np.random.shuffle(commandAll)
print("nombre d'echantillons: ", len(stateAll))
fa = regressionDict[rs.regression](rs)
fa.getTrainingData(stateAll, commandAll)
fa.train()
fa.saveTheta(rs.path + rs.thetaFile + ".theta")
def testRegression(setupFile, thetaFile):
"""
"""
rs=ReadXmlFile(setupFile)
stateAll, commandAll = loadTrajs(pathDataFolder + "Brent/", 0.01, rs.det)
stateAll=np.array(stateAll)
arm=ArmType[rs.Arm]()
trajReg = np.empty_like(stateAll)
trajMaker = TrajMaker(rs,0.02,None,rs.path+thetaFile)
for i in range(stateAll.shape[0]):
coordHand = arm.mgdEndEffector(stateAll[i][0][2:])
trajReg[i]=trajMaker.runTrajectory2(coordHand[0], coordHand[1])[0]
plotRegBrent(trajReg, stateAll)
