def estimate_hypers(step, problem):
"""
Get initial estimates of the hyperparameters
"""
from beat.sampler.base import iter_parallel_chains, init_stage, \
init_chain_hypers
logger.info('... Estimating hyperparameters ...')
pc = problem.config.problem_config
sc = problem.config.hyper_sampler_config
pa = sc.parameters
name = problem.outfolder
ensuredir(name)
stage_handler = TextStage(problem.outfolder)
chains, step, update = init_stage(
stage_handler=stage_handler,
step=step,
stage=0,
progressbar=sc.progressbar,
model=problem.model,
rm_flag=pa.rm_flag)
# setting stage to 1 otherwise only one sample
step.stage = 1
step.n_steps = pa.n_steps
with problem.model:
mtrace = iter_parallel_chains(
draws=pa.n_steps,
chains=chains,
step=step,
stage_path=stage_handler.stage_path(1),
progressbar=sc.progressbar,
model=problem.model,
n_jobs=pa.n_jobs,
initializer=init_chain_hypers,
initargs=(problem,),
buffer_size=sc.buffer_size,
chunksize=int(pa.n_chains / pa.n_jobs))
for v, i in pc.hyperparameters.iteritems():
d = mtrace.get_values(
v, combine=True, burn=int(pa.n_steps * pa.burn),
thin=pa.thin, squeeze=True)
lower = num.floor(d.min()) - 2.
upper = num.ceil(d.max()) + 2.
logger.info('Updating hyperparameter %s from %f, %f to %f, %f' % (
v, i.lower, i.upper, lower, upper))
pc.hyperparameters[v].lower = num.atleast_1d(lower)
pc.hyperparameters[v].upper = num.atleast_1d(upper)
pc.hyperparameters[v].testvalue = num.atleast_1d((upper + lower) / 2.)
config_file_name = 'config_' + pc.mode + '.yaml'
conf_out = os.path.join(problem.config.project_dir, config_file_name)
problem.config.problem_config = pc
bconfig.dump(problem.config, filename=conf_out)
def estimate_hypers(step, problem):
"""
Get initial estimates of the hyperparameters
"""
logger.info('... Estimating hyperparameters ...')
pc = problem.config.problem_config
sc = problem.config.hyper_sampler_config
pa = sc.parameters
name = problem.outfolder
util.ensuredir(name)
mtraces = []
for stage in range(pa.n_stages):
logger.info('Metropolis stage %i' % stage)
if stage == 0:
point = {param.name: param.testvalue for param in pc.priors}
else:
point = {param.name: param.random() for param in pc.priors}
problem.outfolder = os.path.join(name, 'stage_%i' % stage)
start = {param.name: param.random() for param in \
pc.hyperparameters.itervalues()}
if pa.rm_flag:
shutil.rmtree(problem.outfolder, ignore_errors=True)
if not os.path.exists(problem.outfolder):
logger.debug('Sampling ...')
problem.update_llks(point)
logger
with problem.model as model:
mtraces.append(pm.sample(
draws=pa.n_steps,
step=step,
trace=pm.backends.Text(
name=problem.outfolder,
model=problem.model),
start=start,
model=model,
chain=stage * pa.n_jobs,
njobs=pa.n_jobs,
))
else:
logger.debug('Loading existing results!')
mtraces.append(pm.backends.text.load(
name=problem.outfolder, model=problem.model))
mtrace = pm.backends.base.merge_traces(mtraces)
outname = os.path.join(name, 'stage_final')
if not os.path.exists(outname):
util.ensuredir(outname)
pm.backends.text.dump(name=outname, trace=mtrace)
n_steps = pa.n_steps
for v, i in pc.hyperparameters.iteritems():
d = mtrace.get_values(
v, combine=True, burn=int(n_steps * pa.burn),
thin=pa.thin, squeeze=True)
lower = num.floor(d.min(axis=0)) - 0.5
upper = num.ceil(d.max(axis=0)) + 0.5
logger.info('Updating hyperparameter %s from %f, %f to %f, %f' % (
v, i.lower, i.upper, lower, upper))
pc.hyperparameters[v].lower = lower
pc.hyperparameters[v].upper = upper
pc.hyperparameters[v].testvalue = (upper + lower) / 2.
config_file_name = 'config_' + pc.mode + '.yaml'
conf_out = os.path.join(problem.config.project_dir, config_file_name)
problem.config.problem_config = pc
bconfig.dump(problem.config, filename=conf_out)