def calculateTransientTime(self, inputs, outputs, epsilon, proximityLength = None):
# inputs: input of reserovoir
# outputs: output of reservoir
# epsilon: given constant
# proximity length: number of steps for which all states have to be epsilon close to declare convergance
# initializes two initial states as far as possible from each other in [-1,1] regime and tests when they converge-> this is transient time
length = inputs.shape[0] if inputs is not None else outputs.shape[0]
if proximityLength is None:
proximityLength = int(length * 0.1)
if proximityLength < 3:
proximityLength = 3
initial_x = B.empty((2, self.n_reservoir, 1))
initial_x[0] = - B.ones((self.n_reservoir, 1))
initial_x[1] = B.ones((self.n_reservoir, 1))
countedConsecutiveSteps = 0
length = inputs.shape[0] if inputs is not None else outputs.shape[0]
for t in range(length):
if B.max(B.ptp(initial_x, axis=0)) < epsilon:
if countedConsecutiveSteps >= proximityLength:
return t - proximityLength
else:
countedConsecutiveSteps += 1
else:
countedConsecutiveSteps = 0
u = inputs[t].reshape(-1, 1) if inputs is not None else None
o = outputs[t].reshape(-1, 1) if outputs is not None else None
for i in range(initial_x.shape[0]):
self.update(u, o, initial_x[i])
#transient time could not be determined
raise ValueError("Transient time could not be determined - maybe the proximityLength is too big.")
def getEquilibriumState(inputs, outputs, epsilon = 1e-3):
# inputs: input of reserovoir
# outputs: output of reservoir
# epsilon: given constant
# returns the equilibrium state when esn is fed with the first state of input
x = B.empty((2, self.n_reservoir, 1))
while not B.max(B.ptp(x, axis=0)) < epsilon:
x[0] = x[1]
u = inputs[0].reshape(-1, 1) if inputs is not None else None
o = outputs[0].reshape(-1, 1) if outputs is not None else None
self.update(u, o, x[1])
return x[1]
def reduceTransientTime(self, inputs, outputs, initialTransientTime, epsilon = 1e-3, proximityLength = 50):
# inputs: input of reserovoir
# outputs: output of reservoir
# epsilon: given constant
# proximity length: number of steps for which all states have to be epsilon close to declare convergance
# initialTransientTime: transient time with calculateTransientTime() method estimated
# finds initial state with lower transient time and sets internal state to this state
# returns the new transient time by calculating the convergence time of initial states found with SWD and Equilibrium method
def getEquilibriumState(inputs, outputs, epsilon = 1e-3):
# inputs: input of reserovoir
# outputs: output of reservoir
# epsilon: given constant
# returns the equilibrium state when esn is fed with the first state of input
x = B.empty((2, self.n_reservoir, 1))
while not B.max(B.ptp(x, axis=0)) < epsilon:
x[0] = x[1]
u = inputs[0].reshape(-1, 1) if inputs is not None else None
o = outputs[0].reshape(-1, 1) if outputs is not None else None
self.update(u, o, x[1])
return x[1]
def getStateAtGivenPoint(inputs, outputs, targetTime):
# inputs: input of reserovoir
# outputs: output of reservoir
# targetTime: time at which the state is wanted
# propagates the inputs/outputs till given point in time and returns the state of the reservoir at this point
x = B.zeros((self.n_reservoir, 1))
length = inputs.shape[0] if inputs is not None else outputs.shape[0]
length = min(length, targetTime)
for t in range(length):
u = inputs[t].reshape(-1, 1) if inputs is not None else None
o = outputs[t].reshape(-1, 1) if outputs is not None else None
self.update(u, o, x)
return x
length = inputs.shape[0] if inputs is not None else outputs.shape[0]
if proximityLength is None:
proximityLength = int(length * 0.1)
if proximityLength < 3:
proximityLength = 3
x = B.empty((2, self.n_reservoir, 1))
equilibriumState = getEquilibriumState(inputs, outputs)
if inputs is None:
swdPoint, _ = hp.SWD(outputs, int(initialTransientTime*0.8))
else:
swdPoint, _ = hp.SWD(inputs, int(initialTransientTime * 0.8))
swdState = getStateAtGivenPoint(inputs, outputs, swdPoint)
x[0] = equilibriumState
x[1] = swdState
transientTime = 0
countedConsecutiveSteps = 0
for t in range(length):
if B.max(B.ptp(x, axis=0)) < epsilon:
countedConsecutiveSteps += 1
if countedConsecutiveSteps > proximityLength:
transientTime = t - proximityLength
break
else:
countedConsecutiveSteps = 0
u = inputs[t].reshape(-1, 1) if inputs is not None else None
o = outputs[t].reshape(-1, 1) if outputs is not None else None
for i in range(x.shape[0]):
self.update(u, o, x[i])
self._x = x[0]
return transientTime