Commit 81ab7c6d authored by cmaffeo2's avatar cmaffeo2
Browse files

Fixed spring constant for dihedral that spans crossovers, keeping helices...

Fixed spring constant for dihedral that spans crossovers, keeping helices parallel (note this differs from prototyped web service where 90 degree angle potentials were used)

Changed dna bead type clustering to have higher resolution

Streamlined some small parts of the code
parent 00beb7c6
......@@ -1654,10 +1654,9 @@ class SegmentModel(ArbdModel):
data = np.array([b.num_nt for b in beads])[:,np.newaxis]
order = int(2-np.log10(2*max_basepairs_per_bead)//1)
try:
clusters = hcluster.fclusterdata(data, float(max_basepairs_per_bead)/80, criterion="distance")
clusters = hcluster.fclusterdata(data, float(max_basepairs_per_bead)/500, criterion="distance")
cluster_size = [np.mean(data[clusters == i]) for i in np.unique(clusters)]
except:
## TODO debug
clusters = data
cluster_size = np.arange(len(data))+1
for b,c in zip(beads,clusters):
......@@ -1667,15 +1666,30 @@ class SegmentModel(ArbdModel):
data = np.array([b.num_nt for b in beads])[:,np.newaxis]
order = int(2-np.log10(max_nucleotides_per_bead)//1)
try:
clusters = hcluster.fclusterdata(data, float(max_basepairs_per_bead)/40, criterion="distance")
clusters = hcluster.fclusterdata(data, float(max_nucleotides_per_bead)/500, criterion="distance")
cluster_size = [np.mean(data[clusters == i]) for i in np.unique(clusters)]
except:
## TODO debug
clusters = data
cluster_size = np.arange(len(data))+1
for b,c in zip(beads,clusters):
_assign_bead_type(b, cluster_size[c-1], decimals=order)
# for bead in [b for s in segments for b in s]:
# num_nt0 = bead.num_nt
# # bead.num_nt = np.around( np.float32(num_nt), decimals=decimals )
# key = (bead.type_.name[0].upper(), bead.num_nt)
# if key in beadtype_s:
# bead.type_ = beadtype_s[key]
# else:
# t = deepcopy(bead.type_)
# t.__dict__["nts"] = bead.num_nt*2 if t.name[0].upper() in ("D","O") else bead.num_nt
# # t.name = t.name + "%03d" % (t.nts*10**decimals)
# t.name = t.name + "%.16f" % (t.nts)
# print( "{} --> {} ({})".format(num_nt0, bead.num_nt, t.name) )
# beadtype_s[key] = bead.type_ = t
""" Update bead indices """
self._countParticleTypes() # probably not needed here
self._updateParticleOrder()
......@@ -1853,30 +1867,28 @@ class SegmentModel(ArbdModel):
k_fn = lambda sep: (1.0/2) * 1.5 * kT * (1.0 / (1-np.exp(-float(sep)/147))) * 0.00030461742; # kcal_mol/degree^2
a = None
if u1 is not None and u2 is not None:
t0 = 0
k = k_fn( 0.5*(dists[b1][u1]+dists[b2][u2]) )
pot = self.get_dihedral_potential(k,t0)
self.add_dihedral( u1,b1,b2,u2, pot )
a,b,c,d = (u1,b1,b2,u2)
elif d1 is not None and d2 is not None:
t0 = 0
k = k_fn( 0.5*(dists[b1][d1]+dists[b2][d2]) )
pot = self.get_dihedral_potential(k,t0)
self.add_dihedral( d1,b1,b2,d2, pot )
a,b,c,d = (d1,b1,b2,d2 )
elif d1 is not None and u2 is not None:
t0 = 180
k = k_fn( 0.5*(dists[b1][d1]+dists[b2][u2]) )
pot = self.get_dihedral_potential(k,t0)
self.add_dihedral( d1,b1,b2,u2, pot )
a,b,c,d = (d1,b1,b2,u2)
elif u1 is not None and d2 is not None:
t0 = 180
k = k_fn( 0.5*(dists[b1][u1]+dists[b2][d2]) )
a,b,c,d = (u1,b1,b2,d2)
if a is not None:
k = k_fn( dists[b][a]+dists[c][d] )
pot = self.get_dihedral_potential(k,t0)
self.add_dihedral( u1,b1,b2,d2, pot )
self.add_dihedral( a,b,c,d, pot )
if local_twist:
k = (1.0/2) * 1.5 * kT * (1.0 / (1-np.exp(-float(1)/147))) * 0.00030461742; # kcal_mol/degree^2
k = k_fn(1)
pot = self.get_angle_potential(k,120)
if 'orientation_bead' in b1.__dict__:
o = b1.orientation_bead
......@@ -1933,11 +1945,13 @@ class SegmentModel(ArbdModel):
n1,n2,n3,n4 = (B1.particle, A1.particle, A2.particle, B2.particle)
## <cos(q)> = exp(-s/Lp) = integrate( cos[x] exp(-A x^2), {x, 0, pi} ) / integrate( exp(-A x^2), {x, 0, pi} )
## Assume A is small
## int[B_] := Normal[Integrate[ Series[Cos[x] Exp[-B x^2], {B, 0, 1}], {x, 0, \[Pi]}]/
## Integrate[Series[Exp[-B x^2], {B, 0, 1}], {x, 0, \[Pi]}]]
## Actually, without assumptions I get fitFun below
"""
<cos(q)> = exp(-s/Lp) = integrate( cos[x] exp(-A x^2), {x, 0, pi} ) / integrate( exp(-A x^2), {x, 0, pi} )
Assume A is small
int[B_] := Normal[Integrate[ Series[Cos[x] Exp[-B x^2], {B, 0, 1}], {x, 0, \[Pi]}]/
Integrate[Series[Exp[-B x^2], {B, 0, 1}], {x, 0, \[Pi]}]]
Actually, without assumptions I get fitFun below
"""
## From http://www.annualreviews.org/doi/pdf/10.1146/annurev.bb.17.060188.001405
## units "3e-19 erg cm/ 295 k K" "nm" =~ 73
......
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