def dec(self, n=1):
"""
The function dec takes as input a number n which is defaulted to
1. It deletes one monomer from an assembly that it chooses -
where the probability is proportional to the surface area of the
assembly.
"""
weights = [(a, a.monomers_at_surface) for a in self.assemblies
if a.number >= n]
asmb = stats.weighted_choice(
weights) # Choose assembly by surface area
# Decrement
'''diff is the number of monomers in the assembly minus the number
you want to remove from the assembly'''
diff = asmb.number - n
'''diff must be greater than or equal to 0 because you can't
remove more than the number of monomers that compose the
assembly.'''
assert (diff >= 0)
'''If the number you want to remove = the number of monomers in
the assembly...'''
if diff == 0:
self.removeAssembly(asmb) #Just remove the assembly.
elif diff == 1: #If there is only one monomer in the assembly,
#put the monomer back in solution and...
self.monomers.inc(1)
self.removeAssembly(asmb) #just remove the assembly
else:
asmb.dec(n) #Otherwise, decrease number of monomers by 1.
def dec(self, n=1):
"""
The function dec takes as input a number n which is defaulted to
1. It deletes one monomer from an assembly that it chooses -
where the probability is proportional to the surface area of the
assembly.
"""
weights = [(a, a.monomers_at_surface) for a in self.assemblies if a.number >= n]
asmb = stats.weighted_choice(weights) # Choose assembly by surface area
# Decrement
"""diff is the number of monomers in the assembly minus the number
you want to remove from the assembly"""
diff = asmb.number - n
"""diff must be greater than or equal to 0 because you can't
remove more than the number of monomers that compose the
assembly."""
assert diff >= 0
"""If the number you want to remove = the number of monomers in
the assembly..."""
if diff == 0:
self.removeAssembly(asmb) # Just remove the assembly.
elif diff == 1: # If there is only one monomer in the assembly,
# put the monomer back in solution and...
self.monomers.inc(1)
self.removeAssembly(asmb) # just remove the assembly
else:
asmb.dec(n) # Otherwise, decrease number of monomers by 1.
def inc(self, n=1):
"""
The function inc takes as input a number n which is defaulted to 1.
It adds one monomer to an assembly that it chooses - where the
probability of being chosen is proportional to the surface area of
the assembly.
"""
# Choose assembly by surface area
weights = [(a, a.monomers_at_surface) for a in self.assemblies]
asmb = stats.weighted_choice(weights)
# Increment
asmb.inc(n)
def inc(self, n=1):
"""
The function inc takes as input a number n which is defaulted to 1.
It adds one monomer to an assembly that it chooses - where the
probability of being chosen is proportional to the surface area of
the assembly.
"""
# Choose assembly by surface area
weights = [(a, a.monomers_at_surface) for a in self.assemblies]
asmb = stats.weighted_choice(weights)
# Increment
asmb.inc(n)
def dec(self,n=1): # Choose assembly by surface area weights = [(a, a.monomers_at_surface) for a in self.assemblies if a.number >= n] asmb = stats.weighted_choice(weights) # Decrement diff = asmb.number-n assert(diff>=0) if diff == 0: self.removeAssembly(asmb) elif diff == 1: # Return to monomer pool self.monomers.inc(1) self.removeAssembly(asmb) else: asmb.dec(n)
def dec(self, n=1):
# Choose assembly by surface area
weights = [(a, a.monomers_at_surface) for a in self.assemblies
if a.number >= n]
asmb = stats.weighted_choice(weights)
# Decrement
diff = asmb.number - n
assert (diff >= 0)
if diff == 0:
self.removeAssembly(asmb)
elif diff == 1:
# Return to monomer pool
self.monomers.inc(1)
self.removeAssembly(asmb)
else:
asmb.dec(n)
data_outs.write("# Parameters:\n")
optdict = vars(options)
for (k, v) in optdict.items():
data_outs.write("#\t{k}: {v}\n".format(k=k, v=v))
data_outs.write("# Window size = {}\n".format(window_size))
n_samples = 0
scores = []
min_ent = 1e6
min_seq = None
max_ent = 0
max_seq = None
quant = gelscore.EntropyQuant()
while n_samples < options.num_samples:
# Pick sequence at random
seq = stats.weighted_choice(seq_weights)
if len(seq) >= window_size:
# Pick a subsequence within sequence at random
startpos = random.randint(0, len(seq) - window_size)
subseq = seq[startpos:(startpos + window_size)]
if not '*' in subseq:
score = quant.quant(subseq, base=options.logarithm_base)
if score < min_ent:
min_ent = score
min_seq = subseq
if score > max_ent:
max_ent = score
max_seq = subseq
scores.append(score)
n_samples += 1
def inc(self,n=1): # Choose assembly by surface area weights = [(a, a.monomers_at_surface) for a in self.assemblies] asmb = stats.weighted_choice(weights) # Increment asmb.inc(n)
data_outs.write("# Parameters:\n")
optdict = vars(options)
for (k,v) in optdict.items():
data_outs.write("#\t{k}: {v}\n".format(k=k, v=v))
data_outs.write("# Window size = {}\n".format(window_size))
n_samples = 0
scores = []
min_ent = 1e6
min_seq = None
max_ent = 0
max_seq = None
quant = gelscore.EntropyQuant()
while n_samples < options.num_samples:
# Pick sequence at random
seq = stats.weighted_choice(seq_weights)
if len(seq) >= window_size:
# Pick a subsequence within sequence at random
startpos = random.randint(0, len(seq)-window_size)
subseq = seq[startpos:(startpos+window_size)]
if not '*' in subseq:
score = quant.quant(subseq, base=options.logarithm_base)
if score < min_ent:
min_ent = score
min_seq = subseq
if score > max_ent:
max_ent = score
max_seq = subseq
scores.append(score)
n_samples += 1
def inc(self, n=1):
# Choose assembly by surface area
weights = [(a, a.monomers_at_surface) for a in self.assemblies]
asmb = stats.weighted_choice(weights)
# Increment
asmb.inc(n)