def __init__(self, start_pmc, insert_pos):
"""Specifies the starting PMC, and the point of inserting the genus-1
split PMC.
- insert_pos = 0: insert at bottom
- insert_pos = start_pmc.n: insert at top
"""
self.start_pmc = start_pmc
self.insert_pos = insert_pos
# Prepare end_pmc
translate = dict()
for p in range(self.start_pmc.n):
if p < insert_pos:
translate[p] = p
else: # p >= insert_pos
translate[p] = p + 4
self.end_pmc = PMC(
[(translate[p], translate[q]) for p, q in self.start_pmc.pairs] +
[(insert_pos, insert_pos+2), (insert_pos+1, insert_pos+3)])
assert insert_pos >= 1 and insert_pos < start_pmc.n
# Possible cases
self.MIDDLE, self.NEXT_BOTTOM = 0, 1
if insert_pos >= 2:
self.case = self.MIDDLE
else:
self.case = self.NEXT_BOTTOM
self.splitting1 = PMCSplitting(
self.start_pmc, [(insert_pos-1, insert_pos-1)])
self.splitting2 = PMCSplitting(
self.end_pmc, [(insert_pos-1, insert_pos+3)])
self.local_pmc1 = self.splitting1.local_pmc
self.local_pmc2 = self.splitting2.local_pmc
# Required so the left to right transition on the outside can proceed.
assert self.splitting1.outer_pmc == self.splitting2.outer_pmc
self.local_da = self.getLocalDAStructure()
# Uncomment to use autoComplete. Note limit on len(coeffs_a) is 5.
# if self.case == self.MIDDLE:
# autoCompleteDA(self.local_da, [0, 1])
# Initiate the ExtendedDAStructure
ExtendedDAStructure.__init__(
self, self.local_da, self.splitting1, self.splitting2)
# With generators set, add grading. Choose a generator of class zero as
# base generator.
for gen in self.generators:
if gen.name[0] == "0":
base_gen = gen
break
self.registerHDiagram(
getSimpleCobordismDiagram(start_pmc, insert_pos), base_gen)
def __init__(self, genus, c_pair):
"""Specifies genus of the starting PMC and the ID of the pair of
anti-braid resolution.
"""
self.genus = genus
self.c_pair = c_pair
self.pmc = linearPMC(genus)
self.n = 4 * genus
self.c1, self.c2 = self.pmc.pairs[c_pair]
if self.c2 == self.c1 + 3:
self.is_degenerate = False
else:
assert self.c2 == self.c1 + 2
assert self.c1 == 0 or self.c2 == self.n - 1
self.is_degenerate = True
if self.is_degenerate:
# One position between c1 and c2, called p
self.p = self.c1 + 1
self.p_pair = self.pmc.pairid[self.p]
else:
# Two positions between c1 and c2, for (d)own and (u)p
self.d = self.c1 + 1
self.u = self.c1 + 2
self.d_pair = self.pmc.pairid[self.d]
self.u_pair = self.pmc.pairid[self.u]
# Necessary to get local DA structure.
self.splitting = PMCSplitting(self.pmc, [(self.c1, self.c2)])
self.local_pmc = self.splitting.local_pmc
self.mapping = self.splitting.local_mapping
# Local DA Structure
self.local_da = self.getLocalDAStructure()
### Uncomment to use autocompleteda to construct arrows from seeds.
# autoCompleteDA(self.local_da, ([]))
# Initiate the ExtendedDAStructure
ExtendedDAStructure.__init__(self, self.local_da,
self.splitting, self.splitting)
def __init__(self, cob):
"""Specifies the cobordism to use. cob should be of type Cobordism,
with cob.side == LEFT.
"""
assert cob.side == LEFT
self.cob = cob
self.genus, self.c_pair, self.n = cob.genus, cob.c_pair, cob.n
self.start_pmc, self.end_pmc = cob.start_pmc, cob.end_pmc
self.large_pmc, self.small_pmc = cob.large_pmc, cob.small_pmc
self.is_degenerate = cob.is_degenerate
self.c1, self.c2 = cob.c1, cob.c2
# Four possible local cases
self.MIDDLE, self.NEXT_TOP, self.TOP, self.BOTTOM = 0, 1, 2, 3
if not self.is_degenerate:
self.d, self.u = self.cob.d, self.cob.u
self.to_s, self.pair_to_s = self.cob.to_s, self.cob.pair_to_s
self.d_pair, self.u_pair = self.cob.d_pair, self.cob.u_pair
self.du_pair = self.cob.du_pair # refers to the smaller PMC.
self.sd, self.su = self.small_pmc.pairs[self.du_pair]
u1, u2 = self.large_pmc.pairs[self.u_pair]
assert u1 == self.u
if self.c_pair < 2*self.genus-2:
# First case: c-pair at least two pairs from top
self.case = self.MIDDLE
self.splitting_small = PMCSplitting(
self.small_pmc, [(self.su-1, self.su)])
self.splitting_large = PMCSplitting(
self.large_pmc, [(self.c1, u2)])
else:
# Second case: c-pair is the next-to-topmost pair
assert self.c_pair == 2*self.genus-2
assert u2 == u1 + 2
self.case = self.NEXT_TOP
self.splitting_small = PMCSplitting(
self.small_pmc, [(self.su, self.su)])
self.splitting_large = PMCSplitting(
self.large_pmc, [(self.c1, u2)])
else:
assert self.c2 == self.c1 + 2
if self.c_pair == 2*self.genus-1:
# Third case: degenerate at top
self.case = self.TOP
self.splitting_small = PMCSplitting(
self.small_pmc, [(self.n-5, self.n-5)]) # topmost point
self.splitting_large = PMCSplitting(
self.large_pmc, [(self.c1-2, self.c2)])
else:
# Fourth case: degenerate at bottom
assert self.c_pair == 0
self.case = self.BOTTOM
self.splitting_small = PMCSplitting(self.small_pmc, [(0, 0)])
self.splitting_large = PMCSplitting(self.large_pmc, [(0, 4)])
# Assumes the LEFT case
self.splitting1 = self.splitting_large
self.splitting2 = self.splitting_small
self.local_pmc1 = self.splitting1.local_pmc
self.local_pmc2 = self.splitting2.local_pmc
# Required so the left to right transition on the outside can proceed.
assert self.splitting1.outer_pmc == self.splitting2.outer_pmc
self.local_da = self.getLocalDAStructure()
if self.case == self.MIDDLE:
autoCompleteDA(self.local_da, [2, 1, 0, 5, 6])
elif self.case == self.NEXT_TOP:
autoCompleteDA(self.local_da, [2, 1, 0])
elif self.case == self.TOP:
autoCompleteDA(self.local_da, [3, 1])
else:
autoCompleteDA(self.local_da, [0, 3])
# Initiate the ExtendedDAStructure
ExtendedDAStructure.__init__(
self, self.local_da, self.splitting1, self.splitting2)
# With generators set, add grading. Any generator can serve as base_gen
for gen in self.generators:
base_gen = gen
break
self.registerHDiagram(getCobordismDiagramLeft(self.cob), base_gen)
def __init__(self, slide):
"""Specifies the arcslide to use. slide should be of type Arcslide.
In addition to recording slide, construct the following:
local_pmc1, mapping1 - restriction of starting pmc to location of slide.
outer_pmc1, outer_mapping1 - complement of slide in starting pmc.
local_pmc2, mapping2, outer_pmc2, outer_mapping2
- same, but for ending pmc.
Moreover, find pattern_fun and translator as appropriate for the case at
hand.
"""
self.slide = slide
self.pmc1, self.pmc2 = slide.start_pmc, slide.end_pmc
n = self.pmc1.n
b1, c1, c2 = slide.b1, slide.c1, slide.c2
b1p, c1p, c2p = [slide.to_r[p] for p in b1, c1, c2]
# Note intervals (start, end) with start > end are ignored.
# patterns_base specifies one of the four base patterns of arcslides.
# translator gives the mapping between points in the base pattern and
# points in the pattern at hand.
if b1 == c1 + 1: # downward
if c2 == c1 + 2: # short underslide downward
local_cut1, local_cut2 = ([(c1, c2)], [(c1p, c2p)])
patterns_fun = ArcslideDA._short_underslide_down
if c1 == 0:
translator = ([-1, 0, 1, 2, 3], [-1, 0, 1, 2, 3])
elif c2 == n - 1:
translator = ([0, 1, 2, 3, -1], [0, 1, 2, 3, -1])
else:
translator = None
elif c2 > c1: # general underslide downward
local_cut1, local_cut2 = (
[(c1, b1), (c2, c2)], [(c1p, c1p), (b1p, c2p)])
patterns_fun = ArcslideDA._general_underslide_down
if c1 == 0:
translator = ([-1, 0, 1, 2, 3, 4, 5],
[-1, 0, 1, 2, 3, 4, 5])
elif c2 == n - 1:
translator = ([0, 1, 2, 3, 4, 5, -1],
[0, 1, 2, 3, 4, 5, -1])
else:
translator = None
else: # c2 < c1, general overslide downward
local_cut1, local_cut2 = (
[(c2, c2), (c1, b1)], [(b1p, c2p), (c1p, c1p)])
patterns_fun = ArcslideDA._general_underslide_down
if c2 == 0 and b1 == n - 1:
translator = ([2, 3, 4, -1, -1, 0, 1],
[3, 4, -1, -1, 0, 1, 2])
elif c2 == 0:
translator = ([2, 3, 4, 5, -1, 0, 1],
[3, 4, 5, -1, 0, 1, 2])
elif b1 == n - 1:
translator = ([3, 4, 5, -1, 0, 1, 2],
[4, 5, -1, 0, 1, 2, 3])
else:
translator = ([3, 4, 5, 6, 0, 1, 2], [4, 5, 6, 0, 1, 2, 3])
elif b1 == c1 - 1: # upward
if c2 == c1 - 2: # short underslide upward
local_cut1, local_cut2 = ([(c2, c1)], [(c2p, c1p)])
patterns_fun = ArcslideDA._short_underslide_up
if c2 == 0:
translator = ([-1, 0, 1, 2, 3], [-1, 0, 1, 2, 3])
elif c1 == n - 1:
translator = ([0, 1, 2, 3, -1], [0, 1, 2, 3, -1])
else:
translator = None
elif c2 < c1: # general underslide upward
local_cut1, local_cut2 = (
[(c2, c2), (b1, c1)], [(c2p, b1p), (c1p, c1p)])
patterns_fun = ArcslideDA._general_underslide_up
if c2 == 0:
translator = ([-1, 0, 1, 2, 3, 4, 5],
[-1, 0, 1, 2, 3, 4, 5])
elif c1 == n - 1:
translator = ([0, 1, 2, 3, 4, 5, -1],
[0, 1, 2, 3, 4, 5, -1])
else:
translator = None
else: # c2 > c1, general overslide upward
local_cut1, local_cut2 = (
[(b1, c1), (c2, c2)], [(c1p, c1p), (c2p, b1p)])
patterns_fun = ArcslideDA._general_underslide_up
if b1 == 0 and c2 == n - 1:
translator = ([3, 4, -1, -1, 0, 1, 2],
[2, 3, 4, -1, -1, 0, 1])
elif b1 == 0:
translator = ([3, 4, 5, -1, 0, 1, 2],
[2, 3, 4, 5, -1, 0, 1])
elif c2 == n - 1:
translator = ([4, 5, -1, 0, 1, 2, 3],
[3, 4, 5, -1, 0, 1, 2])
else:
translator = ([4, 5, 6, 0, 1, 2, 3], [3, 4, 5, 6, 0, 1, 2])
else:
# All cases are covered. Should not happen.
raise NotImplementedError(
"This slide pattern is not yet implemented.")
self.patterns_fun = patterns_fun
self.translator = translator
# Necesssary to get local DA structure.
self.splitting1 = PMCSplitting(self.pmc1, local_cut1)
self.splitting2 = PMCSplitting(self.pmc2, local_cut2)
self.local_pmc1 = self.splitting1.local_pmc
self.local_pmc2 = self.splitting2.local_pmc
self.mapping1 = self.splitting1.local_mapping
self.mapping2 = self.splitting2.local_mapping
# Required so the left to right transition on the outside can proceed.
assert self.splitting1.outer_pmc == self.splitting2.outer_pmc
# Initiate the ExtendedDAStructure
ExtendedDAStructure.__init__(
self, self.getLocalDAStructure(), self.splitting1, self.splitting2)
# With generators set, add grading. Any generator can serve as base_gen
for gen in self.generators:
base_gen = gen
break
self.registerHDiagram(getArcslideDiagram(self.slide), base_gen)
