def getXYEstimError(foldername):
'''
Returns the error estimations in the trajectories from the given foldername
Outputs: -errors: dictionary keys = filenames, values = array of data
'''
arm = Arm()
errors = {}
for el in os.listdir(foldername):
errors[el] = []
data = np.loadtxt(foldername + el)
for i in range(data.shape[0]):
statePos = (data[i][10], data[i][11])
estimStatePos = (data[i][6], data[i][7])
errors[el].append(arm.estimErrorReduced(statePos, estimStatePos))
return errors
def getXYEstimError(foldername):
"""
Returns the error estimations in the trajectories from the given foldername
Outputs: -errors: dictionary keys = filenames, values = array of data
"""
arm = Arm()
errors = {}
for el in os.listdir(foldername):
errors[el] = []
data = np.loadtxt(foldername + el)
for i in range(data.shape[0]):
statePos = (data[i][10], data[i][11])
estimStatePos = (data[i][6], data[i][7])
errors[el].append(arm.estimErrorReduced(statePos, estimStatePos))
return errors
def getXYEstimErrorOfSpeed(foldername):
"""
Returns the error estimations in the trajectories as a function of speed from the given foldername
Outputs: -state: dictionary keys = filenames, values = array of data
"""
arm = Arm()
errors = {}
for el in os.listdir(foldername):
errors[el] = []
data = np.loadtxt(foldername + el)
for i in range(data.shape[0]):
speed = arm.cartesianSpeed((data[i][8], data[i][9], data[i][10], data[i][11]))
statePos = (data[i][10], data[i][11])
estimStatePos = (data[i][6], data[i][7])
error = arm.estimErrorReduced(statePos, estimStatePos)
errors[el].append((speed, error))
return errors
def getXYEstimError(foldername):
'''
Returns the error estimations in the trajectories from the given foldername
Outputs: -errors: dictionary keys = filenames, values = array of data
'''
arm = Arm()
errors = {}
for el in os.listdir(foldername):
errors[el] = []
data = np.loadtxt(foldername + el)
for i in range(data.shape[0]):
currentState = (data[i][12], data[i][13], data[i][14], data[i][15], data[i][16], data[i][17])
estimState = (data[i][6], data[i][7], data[i][8], data[i][9], data[i][10], data[i][11])
statePos = (currentState[3], currentState[4], currentState[5])
estimStatePos = (estimState[3], estimState[4], estimState[5])
errors[el].append(arm.estimErrorReduced(statePos,estimStatePos))
return errors
def getXYEstimErrorOfSpeed(foldername):
'''
Returns the error estimations in the trajectories as a function of speed from the given foldername
Outputs: -state: dictionary keys = filenames, values = array of data
'''
arm = Arm()
errors = {}
for el in os.listdir(foldername):
errors[el] = []
data = np.loadtxt(foldername + el)
for i in range(data.shape[0]):
speed = arm.cartesianSpeed(
(data[i][8], data[i][9], data[i][10], data[i][11]))
statePos = (data[i][10], data[i][11])
estimStatePos = (data[i][6], data[i][7])
error = arm.estimErrorReduced(statePos, estimStatePos)
errors[el].append((speed, error))
return errors
