def calcSlackVector(self, element, b):
""" calculates the slack vector adjustments for a particular
node.
@param element is the element from the node we want to send slack.
@param b is the balanced vector.
@return is the slack vector for the particular node.
"""
self.slack = VectorOps.subFrom(VectorOps.mult(b, element.weight),\
VectorOps.mult(element.drift, element.weight))
return self.slack
def calcSlackVector(self, element, b):
""" calculates the slack vector adjustments for a particular
node.
@param element is the element from the node we want to send slack.
@param b is the balanced vector.
@return is the slack vector for the particular node.
"""
self.slack = VectorOps.subFrom(VectorOps.mult(b, element.weight),\
VectorOps.mult(element.drift, element.weight))
return self.slack
def calcDriftVector(self):
""" calculates drift vector.
Drift vector is the following vector:
u(t) = e(t) + Δv(t), where
Δv(t) = v(t) - v'(t)
"""
# calculate Δv(t)
self.dv = VectorOps.subFrom(self.cm.localStatistics, \
self.cm.lastStatistics)
# calculate drift vector
self.cm.drift = VectorOps.addTo(self.cm.estimate,\
self.dv)
def calcDriftVector(self):
""" calculates drift vector.
Drift vector is the following vector:
u(t) = e(t) + Δv(t), where
Δv(t) = v(t) - v'(t)
"""
# calculate Δv(t)
self.dv = VectorOps.subFrom(self.cm.localStatistics, \
self.cm.lastStatistics)
# calculate drift vector
self.cm.drift = VectorOps.addTo(self.cm.estimate,\
self.dv)
def calc_drift(self):
""" calculates drift vector.
Drift vector is computed as follows:
u(t) = e(t) + delta-v(t), where
delta-v(t) = v(t) = v'(t)
"""
# calculate delta-v
self.dv = VectorOps.subFrom(self.cm.localStatistics,\
self.cm.lastStatistics)
# calculate drift vector
self.cm.drift = VectorOps.addTo(self.cm.estimate, self.dv)
# now check if ball is monochromatic
if not self.check_ball(self.cm.localStatistics):
# if it is not, then send a REP-message to coordinator
# (the algorithm here is exactly the same as in REQ_receipt())
self.REQ_receipt()
def calc_drift(self):
""" calculates drift vector.
Drift vector is computed as follows:
u(t) = e(t) + delta-v(t), where
delta-v(t) = v(t) = v'(t)
"""
# calculate delta-v
self.dv = VectorOps.subFrom(self.cm.localStatistics,\
self.cm.lastStatistics)
# calculate drift vector
self.cm.drift = VectorOps.addTo(self.cm.estimate, self.dv)
# now check if ball is monochromatic
if not self.check_ball(self.cm.localStatistics):
# if it is not, then send a REP-message to coordinator
# (the algorithm here is exactly the same as in REQ_receipt())
self.REQ_receipt()
def calc_drift(self):
""" calculates drift vector.
Drift vector is computed as follows:
u(t) = e(t) + delta-v(t), where
delta-v(t) = v(t) = v'(t)
"""
# calculate delta-v
self.dv = VectorOps.subFrom(self.cm.localStatistics,\
self.cm.lastStatistics)
# calculate drift vector
self.cm.drift = VectorOps.addTo(self.cm.estimate, self.dv)
# now check if ball is monochromatic
if not self.check_ball(self.cm.localStatistics):
# if it is not, then initiate a balancing process,
self.coord_elem = self.createBalancingElement(self.node_name,\
self.cm.localStatistics, self.cm.drift, self.weight)
# initiating the balancing group with this very element
self.bp.addToBalancing(self.coord_elem)
def testSubFrom(self):
""" tests the subFrom(self, a, b) method """
self.true_result = [0, 0, 0, 0, 0]
self.test_result = VectorOps.subFrom(self.target, self.operand)
self.assertEqual(self.true_result, self.test_result)
def testSubFrom(self):
""" tests the subFrom(self, a, b) method """
self.true_result = [0, 0, 0, 0, 0]
self.test_result = VectorOps.subFrom(self.target, self.operand)
self.assertEqual(self.true_result, self.test_result)
