def autoScafMidSeam(self, strands):
"""docstring for autoScafMidSeam"""
part = self.part()
strandType = StrandType.Scaffold
idx = part.activeBaseIndex()
for i in range(1, len(strands)):
row1, col1, sSidx1 = strands[i-1] # previous strand
row2, col2, sSidx2 = strands[i] # current strand
vh1 = part.virtualHelixAtCoord((row1, col1))
vh2 = part.virtualHelixAtCoord((row2, col2))
strand1 = vh1.scaffoldStrandSet()._strandList[sSidx1]
strand2 = vh2.scaffoldStrandSet()._strandList[sSidx2]
# determine if the pair of strands are neighbors
neighbors = part.getVirtualHelixNeighbors(vh1)
if vh2 in neighbors:
p2 = neighbors.index(vh2)
if vh2.number() % 2 == 1:
# resize and install external xovers
try:
# resize to the nearest prexover on either side of idx
newLo = util.nearest(idx, part.getPreXoversHigh(strandType, p2, maxIdx=idx-10))
newHi = util.nearest(idx, part.getPreXoversLow(strandType, p2, minIdx=idx+10))
if strand1.canResizeTo(newLo, newHi) and \
strand2.canResizeTo(newLo, newHi):
# do the resize
strand1.resize((newLo, newHi))
strand2.resize((newLo, newHi))
# install xovers
part.createXover(strand1, newHi, strand2, newHi)
part.createXover(strand2, newLo, strand1, newLo)
except ValueError:
pass # nearest not found in the expanded list
# go back an install the internal xovers
if i > 2:
row0, col0, sSidx0 = strands[i-2] # two strands back
vh0 = part.virtualHelixAtCoord((row0, col0))
strand0 = vh0.scaffoldStrandSet()._strandList[sSidx0]
if vh0 in neighbors:
p0 = neighbors.index(vh0)
l0, h0 = strand0.idxs()
l1, h1 = strand1.idxs()
oLow, oHigh = util.overlap(l0, h0, l1, h1)
try:
lList = filter(lambda x:x>oLow and x<oHigh, part.getPreXoversLow(strandType, p0))
lX = lList[len(lList)/2]
hList = filter(lambda x:x>oLow and x<oHigh, part.getPreXoversHigh(strandType, p0))
hX = hList[len(hList)/2]
# install high xover first
part.createXover(strand0, hX, strand1, hX)
# install low xover after getting new strands
# following the breaks caused by the high xover
strand3 = vh0.scaffoldStrandSet()._strandList[sSidx0]
strand4 = vh1.scaffoldStrandSet()._strandList[sSidx1]
part.createXover(strand4, lX, strand3, lX)
except IndexError:
pass # filter was unhappy
def autoScafRaster(self, strands):
"""docstring for autoScafRaster"""
part = self.part()
idx = part.activeBaseIndex()
for i in range(1, len(strands)):
row1, col1, sSidx1 = strands[i-1] # previous strand
row2, col2, sSidx2 = strands[i] # current strand
vh1 = part.virtualHelixAtCoord((row1, col1))
vh2 = part.virtualHelixAtCoord((row2, col2))
strand1 = vh1.scaffoldStrandSet()._strandList[sSidx1]
strand2 = vh2.scaffoldStrandSet()._strandList[sSidx2]
# determine if the pair of strands are neighbors
neighbors = part.getVirtualHelixNeighbors(vh1)
if vh2 in neighbors:
p2 = neighbors.index(vh2)
if vh2.number() % 2 == 1:
# resize and install external xovers
try:
# resize to the nearest prexover on either side of idx
newLo1 = newLo2 = util.nearest(idx, part.getPreXoversHigh(StrandType.Scaffold, p2, maxIdx=idx-8))
newHi = util.nearest(idx, part.getPreXoversLow(StrandType.Scaffold, p2, minIdx=idx+8))
if vh1.number() != 0: # after the first helix
newLo1 = strand1.lowIdx() # leave alone the lowIdx
if vh2.number() != len(strands)-1: # before the last
newLo2 = strand2.lowIdx() # leave alone the lowIdx
if strand1.canResizeTo(newLo1, newHi) and \
strand2.canResizeTo(newLo2, newHi):
strand1.resize((newLo1, newHi))
strand2.resize((newLo2, newHi))
else:
raise ValueError
# install xovers
part.createXover(strand1, newHi, strand2, newHi)
except ValueError:
pass # nearest not found in the expanded list
else:
# resize and install external xovers
idx = part.activeBaseIndex()
try:
# resize to the nearest prexover on either side of idx
newLo = util.nearest(idx, part.getPreXoversHigh(StrandType.Scaffold, p2, maxIdx=idx-8))
if strand1.canResizeTo(newLo, strand1.highIdx()) and \
strand2.canResizeTo(newLo, strand2.highIdx()):
strand1.resize((newLo, strand1.highIdx()))
strand2.resize((newLo, strand2.highIdx()))
# install xovers
part.createXover(strand1, newLo, strand2, newLo)
else:
raise ValueError
except ValueError:
pass # nearest not found in the expanded list
def __init__(self, id, type, pos, radius, grid, bw = 1.4):
self._id = id
self.type = type
#BS or RRH
if type == self.BS_ID:
self.power = self.POWER_BS
self._radius = self.BS_RADIUS
else:
self.power = self.POWER_RRH
self._radius = self.RRH_RADIUS
self.antenna_in_range = []
self.user_in_range = []
self.resources = []
# position tupe
self._pos = pos
# antenna coverage radius
self._radius = radius
# Grid object
self._grid = grid
# Channel bw (none in the start)
self._cur_ch_bw =bw
self._cur_rb_cap = Antenna.BW_RB_MAP[bw]
# Channel BW required
self._ch_bw_required = None
# List of connected UEs
self._ues = []
self._rb_map = {}
# Register to the closest BBU
self._bbu = util.nearest(self, grid.bbus)
self._bbu.register(self)
def predict(element, tree):
if type(tree) is Leaf:
return tree.answer
if is_continuous(element[tree.attr]):
return predict(element, tree.sons[nearest(element[tree.attr],
list(tree.sons.keys()),
precision=PRECISION)])
return predict(element, tree.sons[element[tree.attr]])
def __init__(self, id, type, pos, radius, grid, bw = 1.4):
self._id = id
self.type = type
#BS or RRH
if type == Antenna.BS_ID:
self.power = threeGPP.POWER_BS
self._radius = threeGPP.BS_RADIUS
else:
self.power = threeGPP.POWER_RRH
self._radius = threeGPP.RRH_RADIUS
self.antenna_in_range = []
self.user_in_range = []
# List of connected UEs
self.connected_ues = []
self.prev_n_ues = 0
self.resources = []
# position tupe
self._pos = pos
# antenna coverage radius
self._radius = radius
# Grid object
self._grid = grid
# Channel bw (none in the start)
self._cur_ch_bw =bw
self._cur_rb_cap = Antenna.BW_RB_MAP[bw]
# Channel BW required
self._ch_bw_required = None
self._rb_map = {}
# Register to the closest BBU
self._bbu = util.nearest(self, grid.bbus)
self._bbu.register(self)
self.i = None
self.a = None
self.p = None
self.energy_efficient = None
self.consumition = None
self.datarate = None
self.user_datarate = None
self.fairness = None
self.meet_users = None
self.datarate_constraint = None
self.backup_i = None
self.backup_a = None
self.backup_p = None
self.backup_energy_efficient = None
self.backup_consumition = None
self.backup_datarate = None
self.backup_user_datarate = None
self.backup_fairness = None
self.backup_meet_users = None
self.history_i = None
self.history_a = None
self.history_p = None
self.history_energy_efficient = None
self.history_consumition = None
self.history_datarate = None
self.history_user_datarate = None
self.history_fairness = None
self.history_meet_users = None
