def get_response_content(fs):
headers = [
# define the point
'exch21', 'exch31', 'exch32', 'exch41', 'exch42', 'exch43',
'mutprob1', 'mutprob2', 'mutprob3', 'mutprob4',
'balprob1', 'balprob2', 'balprob3', 'balprob4',
'infotype',
't',
# annotate with some summary statistics
'shannon.ent.diff',
'logical.ent.diff',
'log.shannon.ent.ratio',
'log.logical.ent.ratio',
'expected.rate.diff',
'spectral.rate.diff',
'log.expected.rate.ratio',
'log.spectral.rate.ratio',
'mi.diff',
'fi.diff',
'log.mi.ratio',
'log.fi.ratio',
# define the label
'label',
]
accum = Accumulator()
combobreaker.run_callable(accum, nseconds=5, niterations=fs.nsamples)
# return csv contents
out = StringIO()
print >> out, ', '.join(headers)
for row in accum.rows:
print >> out, ', '.join(str(x) for x in row)
return out.getvalue()
def main(args):
"""
@param args: from argparse
"""
# get some state that will not change between k-means restarts
with open(args.table_filename) as fin:
rtable = RUtil.RTable(fin)
points = get_rtable_info(rtable, args.annotation, args.axes)
init_strategy = kmeans.InitStrategy().string_to_function(args.kmeans_init)
gs = GlobalState(rtable, points, args.annotation, args.k, init_strategy)
# go until iteration is stopped for some reason
print combobreaker.run_callable(
ClusterState(gs), args.nseconds, args.nrestarts)
def get_response_content(fs):
#nseconds_max = 20
out = StringIO()
print >> out, 'theta:', fs.theta
print >> out, 'Nr:', fs.Nr
print >> out, 'Ns:', fs.Ns
print >> out
for N_diploid in (50, 100, 200):
N_hap = N_diploid * 2
# TODO check s vs N_diploid so that selection is not too big
# as to make fitnesses negative or zero
#
#
f = Accum(N_hap, fs.theta / 2, fs.Nr, fs.Ns / N_diploid)
info = combobreaker.run_callable(f, niterations=fs.nsamples_max)
#
nt1 = len(f.type_1_times)
nt2 = len(f.type_2_times)
print >> out, '2N:', N_hap
print >> out, 'number of type 1 substitutions:', nt1
print >> out, 'number of type 2 substitutions:', nt2
pt1 = nt1 / float(nt1 + nt2)
pt2 = nt2 / float(nt1 + nt2)
print >> out, 'proportion of type 1 substitutions:', pt1
print >> out, 'proportion of type 2 substitutions:', pt2
e1 = np.mean(f.type_1_times) / N_hap
e2 = np.mean(f.type_2_times) / N_hap
print >> out, 'mean type 1 pathway generations per 2N:', e1
print >> out, 'mean type 2 pathway generations per 2N:', e2
print >> out
return out.getvalue()
def get_response_content(fs):
out = StringIO()
np.set_printoptions(linewidth=200)
# look at a bunch of random induced nontrivial connected subgraphs
f = MyCallback(fs.ndim, fs.pkeep)
info = combobreaker.run_callable(f, nseconds=5)
print >> out, info
return out.getvalue()
def get_response_content(fs):
out = StringIO()
np.set_printoptions(linewidth=200)
# look at a bunch of random induced nontrivial connected subgraphs
f = MyCallback(fs.ndim, fs.pkeep)
info = combobreaker.run_callable(f, nseconds=5)
print >> out, info
return out.getvalue()
def get_response_content(fs):
# get the user data
nstates = fs.nstates
# request a limited amount of time
nseconds = 4.0
# get the results
accum = Accumulate(nstates)
info = combobreaker.run_callable(accum, nseconds=nseconds)
return str(info)
def get_response_content(fs):
# get the user data
nstates = fs.nstates
# request a limited amount of time
nseconds = 4.0
# get the results
accum = Accumulate(nstates)
info = combobreaker.run_callable(accum, nseconds=nseconds)
return str(info)
def get_response_content(fs):
headers = [
# define the point
'exch21',
'exch31',
'exch32',
'exch41',
'exch42',
'exch43',
'mutprob1',
'mutprob2',
'mutprob3',
'mutprob4',
'balprob1',
'balprob2',
'balprob3',
'balprob4',
'infotype',
't',
# annotate with some summary statistics
'shannon.ent.diff',
'logical.ent.diff',
'log.shannon.ent.ratio',
'log.logical.ent.ratio',
'expected.rate.diff',
'spectral.rate.diff',
'log.expected.rate.ratio',
'log.spectral.rate.ratio',
'mi.diff',
'fi.diff',
'log.mi.ratio',
'log.fi.ratio',
# define the label
'label',
]
accum = Accumulator()
combobreaker.run_callable(accum, nseconds=5, niterations=fs.nsamples)
# return csv contents
out = StringIO()
print >> out, ', '.join(headers)
for row in accum.rows:
print >> out, ', '.join(str(x) for x in row)
return out.getvalue()
def get_response_content(fs):
# get the user data
nstates = fs.nstates
# request a limited amount of time
nseconds = 4.0
# get the results
if fs.bipartitioned:
simplification = msimpl.get_fast_meta_f81_autobarrier
else:
simplification = msimpl.get_fast_f81
accum = Accumulate(nstates, simplification)
info = combobreaker.run_callable(accum, nseconds=nseconds)
return str(info)
def get_response_content(fs):
# get the user data
nstates = fs.nstates
# request a limited amount of time
nseconds = 4.0
# get the results
if fs.bipartitioned:
simplification = msimpl.get_fast_meta_f81_autobarrier
else:
simplification = msimpl.get_fast_f81
accum = Accumulate(nstates, simplification)
info = combobreaker.run_callable(accum, nseconds=nseconds)
return str(info)
def get_response_content(fs):
niterations = fs.nsamples
ntaxa = fs.ntaxa
nseconds = 4
if fs.split_fiedler:
fsplit = nhj.fsplit_fiedler
elif fs.split_random:
fsplit = nhj.fsplit_random
accum = Accumulator(ntaxa, fsplit)
info = combobreaker.run_callable(
accum, nseconds=nseconds, niterations=niterations)
out = StringIO()
print >> out, str(info)
return out.getvalue()
def get_response_content(fs):
niterations = fs.nsamples
ntaxa = fs.ntaxa
nseconds = 4
if fs.split_fiedler:
fsplit = nhj.fsplit_fiedler
elif fs.split_random:
fsplit = nhj.fsplit_random
accum = Accumulator(ntaxa, fsplit)
info = combobreaker.run_callable(accum,
nseconds=nseconds,
niterations=niterations)
out = StringIO()
print >> out, str(info)
return out.getvalue()
def get_response_content(fs):
#
N_hap = fs.N_diploid * 2
# TODO check s vs N_diploid so that selection is not too big
# as to make fitnesses negative or zero
#
(t1, v1), (t2, v2) = get_backward_info(
fs.N_diploid, fs.theta, fs.Nr, fs.Ns)
#
f = Accum(N_hap, fs.theta / 2, fs.Nr, fs.Ns / fs.N_diploid)
#
nseconds_max = 5.0
info = combobreaker.run_callable(f, nseconds_max, fs.nsamples_max)
#
out = StringIO()
print >> out, 'exact results:'
print >> out
print >> out, 'Type-1 compensatory substitution time expectation:'
print >> out, t1
print >> out
print >> out, 'Type-1 compensatory substitution time stdev:'
print >> out, math.sqrt(v1)
print >> out
print >> out, 'Type-2 compensatory substitution time expectation:'
print >> out, t2
print >> out
print >> out, 'Type-2 compensatory substitution stdev:'
print >> out, math.sqrt(v2)
print >> out
print >> out
print >> out, 'forward sampling results (%s Type-1, %s Type-2):' % (
len(f.type_1_times), len(f.type_2_times))
print >> out
print >> out, 'Type-1 compensatory substitution time expectation:'
print >> out, np.mean(f.type_1_times)
print >> out
print >> out, 'Type-1 compensatory substitution time stdev:'
print >> out, np.std(f.type_1_times)
print >> out
print >> out, 'Type-2 compensatory substitution time expectation:'
print >> out, np.mean(f.type_2_times)
print >> out
print >> out, 'Type-2 compensatory substitution time stdev:'
print >> out, np.std(f.type_2_times)
print >> out
return out.getvalue()
def get_response_content(fs):
#
N_hap = fs.N_diploid * 2
# TODO check s vs N_diploid so that selection is not too big
# as to make fitnesses negative or zero
#
(t1, v1), (t2, v2) = get_backward_info(fs.N_diploid, fs.theta, fs.Nr,
fs.Ns)
#
f = Accum(N_hap, fs.theta / 2, fs.Nr, fs.Ns / fs.N_diploid)
#
nseconds_max = 5.0
info = combobreaker.run_callable(f, nseconds_max, fs.nsamples_max)
#
out = StringIO()
print >> out, 'exact results:'
print >> out
print >> out, 'Type-1 compensatory substitution time expectation:'
print >> out, t1
print >> out
print >> out, 'Type-1 compensatory substitution time stdev:'
print >> out, math.sqrt(v1)
print >> out
print >> out, 'Type-2 compensatory substitution time expectation:'
print >> out, t2
print >> out
print >> out, 'Type-2 compensatory substitution stdev:'
print >> out, math.sqrt(v2)
print >> out
print >> out
print >> out, 'forward sampling results (%s Type-1, %s Type-2):' % (len(
f.type_1_times), len(f.type_2_times))
print >> out
print >> out, 'Type-1 compensatory substitution time expectation:'
print >> out, np.mean(f.type_1_times)
print >> out
print >> out, 'Type-1 compensatory substitution time stdev:'
print >> out, np.std(f.type_1_times)
print >> out
print >> out, 'Type-2 compensatory substitution time expectation:'
print >> out, np.mean(f.type_2_times)
print >> out
print >> out, 'Type-2 compensatory substitution time stdev:'
print >> out, np.std(f.type_2_times)
print >> out
return out.getvalue()
def get_response_content(fs):
#
N_hap = fs.N_diploid * 2
# TODO check s vs N_diploid so that selection is not too big
# as to make fitnesses negative or zero
#
t, v = get_backward_info(
fs.N_diploid, fs.theta, fs.Nr, fs.Ns)
#
f = Accum(N_hap, fs.theta / 2, fs.Nr, fs.Ns / fs.N_diploid)
nseconds_max = 5.0
info = combobreaker.run_callable(f, nseconds_max, fs.nsamples_max)
#
out = StringIO()
print >> out, 'sampling info:'
print >> out
print >> out, info
print >> out
print >> out
print >> out, 'exact results:'
print >> out
print >> out, 'compensatory substitution time expectation:'
print >> out, t
print >> out
print >> out, 'compensatory substitution time variance:'
print >> out, v
print >> out
print >> out
print >> out, 'forward sampling results:'
print >> out
print >> out, 'compensatory substitution time expectation:'
print >> out, np.mean(f.times)
print >> out
print >> out, 'compensatory substitution time variance:'
print >> out, np.var(f.times)
print >> out
return out.getvalue()
def process(nstates, nseconds):
f = Checker(nstates)
info = combobreaker.run_callable(f, nseconds=nseconds, niterations=None)
return str(info)
def get_response_content(fs):
nseconds = 4.0
accum = Accumulate(fs.nstates)
info = combobreaker.run_callable(accum, nseconds=nseconds)
return str(info)
def process(nstates, nseconds):
f = Checker(nstates)
info = combobreaker.run_callable(f, nseconds=nseconds, niterations=None)
return str(info)
def get_response_content(fs):
nseconds = 4.0
accum = Accumulate(fs.nstates)
info = combobreaker.run_callable(accum, nseconds=nseconds)
return str(info)
