def __init__(self,
configfile,
capacity=100,
address='127.0.0.1',
port=5556,
save_plots=None):
# set up socket
sock_addr = 'tcp://%s:%d' % (address, port)
logger.info('Connecting to %s' % sock_addr)
context = SerializingContext()
self.socket = context.socket(zmq.SUB)
self.socket.connect(sock_addr)
self.socket.setsockopt_string(zmq.SUBSCRIBE, u'')
if save_plots and not op.exists(op.dirname(save_plots)):
raise OSError('%s does not exist' % op.dirname(save_plots))
self.save_plots = save_plots
data_pars = utils.read_config(configfile)
defaults = utils.get_path('defaults.ini')
self.priors, self.initparams = utils.load_params(defaults)
self.priors.update(data_pars['priors'])
self.initparams.update(data_pars['initparams'])
self.nchains = self.initparams['nchains']
self.refmodel = data_pars.get('refmodel', dict())
self.capacity = capacity
self.modellength = int(self.priors['layers'][1] + 1) * 2
self.vs_step = np.ones((capacity, self.modellength)) * np.nan
self.dep_step = np.ones((capacity, self.modellength)) * np.nan
self.likes = np.ones((capacity)) * np.nan
self.vpvss = np.ones((capacity)) * np.nan
self.modelmatrix = np.ones((capacity, self.modellength)) * np.nan
self.mantle = self.priors['mantle']
# colors only for inversion targets - modeled data
# self.colors = ['purple', 'green', 'orange' 'red', 'brown', 'blue']
self.colors = [
'teal', 'lightcoral', 'saddlebrown', 'magenta', 'royalblue'
]
self.targets = data_pars['targets']
self.targetrefs = [target.ref for target in self.targets]
self.ntargets = len(self.targets)
self.noises = np.ones((self.capacity, self.ntargets * 2)) * np.nan
self.init_style_dicts()
self.init_plot()
self.init_arrays()
self.breakloop = np.zeros(self.nchains)
def __init__(self,
targets,
chainidx=0,
initparams={},
modelpriors={},
sharedmodels=None,
sharedmisfits=None,
sharedlikes=None,
sharednoise=None,
sharedvpvs=None,
random_seed=None):
self.chainidx = chainidx
self.rstate = np.random.RandomState(random_seed)
defaults = utils.get_path('defaults.ini')
self.priors, self.initparams = utils.load_params(defaults)
self.initparams.update(initparams)
self.priors.update(modelpriors)
self.dv = (self.priors['vs'][1] - self.priors['vs'][0])
self.nchains = self.initparams['nchains']
self.station = self.initparams['station']
# set targets and inversion specific parameters
self.targets = targets
# set parameters
self.iter_phase1 = int(self.initparams['iter_burnin'])
self.iter_phase2 = int(self.initparams['iter_main'])
self.iterations = self.iter_phase1 + self.iter_phase2
self.iiter = -self.iter_phase1
self.lastmoditer = self.iiter
self.propdist = np.array(self.initparams['propdist'])
self.acceptance = self.initparams['acceptance']
self.thickmin = self.initparams['thickmin']
self.maxlayers = int(self.priors['layers'][1]) + 1
self.lowvelperc = self.initparams['lvz']
self.highvelperc = self.initparams['hvz']
self.mantle = self.priors['mantle']
# chain models
self._init_chainarrays(sharedmodels, sharedmisfits, sharedlikes,
sharednoise, sharedvpvs)
# init model and values
self._init_model_and_currentvalues()
def __init__(self,
targets,
initparams=dict(),
priors=dict(),
random_seed=None):
self.sock_addr = 'tcp://*:5556'
self.rstate = np.random.RandomState(random_seed)
defaults = utils.get_path('defaults.ini')
self.priors, self.initparams = utils.load_params(defaults)
self.priors.update(priors)
self.initparams.update(initparams)
self.station = self.initparams.get('station')
savepath = op.join(self.initparams['savepath'], 'data')
if not op.exists(savepath):
os.makedirs(savepath)
# save file for offline-plotting
outfile = op.join(savepath, '%s_config.pkl' % self.station)
utils.save_config(targets,
outfile,
priors=self.priors,
initparams=self.initparams)
self.nchains = self.initparams.get('nchains')
self.ntargets = len(targets.targets)
self.iter_phase1 = int(self.initparams['iter_burnin'])
self.iter_phase2 = int(self.initparams['iter_main'])
self.iterations = self.iter_phase1 + self.iter_phase2
self.maxlayers = int(self.priors['layers'][1]) + 1
self.vpvs = self.priors['vpvs']
# shared data and chains
self._init_shareddata()
logger.info('> %d chain(s) are initiated ...' % self.nchains)
self.chains = []
for i in np.arange(self.nchains):
self.chains += [self._init_chain(chainidx=i, targets=targets)]
self.manager = mp.Manager()
def __init__(self,
configfile,
capacity=100,
address='127.0.0.1',
port=5556):
# set up socket
sock_addr = 'tcp://%s:%d' % (address, port)
logger.info('Connecting to %s' % sock_addr)
context = SerializingContext()
self.socket = context.socket(zmq.SUB)
self.socket.connect(sock_addr)
self.socket.setsockopt_string(zmq.SUBSCRIBE, u'')
data_pars = utils.read_config(configfile)
defaults = utils.get_path('defaults.ini')
self.priors, self.initparams = utils.load_params(defaults)
self.priors.update(data_pars['priors'])
self.initparams.update(data_pars['initparams'])
self.nchains = self.initparams['nchains']
self.refmodel = data_pars.get('refmodel', dict())
self.capacity = capacity
self.modellength = int(self.priors['layers'][1] + 1) * 2
self.vs_step = np.ones((capacity, self.modellength)) * np.nan
self.dep_step = np.ones((capacity, self.modellength)) * np.nan
self.likes = np.ones((capacity)) * np.nan
self.modelmatrix = np.ones((capacity, self.modellength)) * np.nan
# parameters for synthetic computation
self.vpvs = self.priors['vpvs']
# colors only for inversion targets - modeled data
self.colors = ['purple', 'green', 'orange' 'red', 'brown', 'blue']
self.targets = data_pars['targets']
self.targetrefs = [target.ref for target in self.targets]
self.ntargets = len(self.targets)
self.noises = np.ones((self.capacity, self.ntargets * 2)) * np.nan
self.init_style_dicts()
self.init_plot()
self.init_arrays()
self.breakloop = np.zeros(self.nchains)
from BayHunter import SynthObs
import logging
#
# console printout formatting
#
formatter = ' %(processName)-12s: %(levelname)-8s | %(message)s'
logging.basicConfig(format=formatter, level=logging.INFO)
logger = logging.getLogger()
#
# ------------------------------------------------------------ obs SYNTH DATA
#
# Load priors and initparams from config.ini or simply create dictionaries.
initfile = 'config.ini'
priors, initparams = utils.load_params(initfile)
# Load observed data (synthetic test data)
xsw, _ysw = np.loadtxt('observed/st3_rdispph.dat', usecols=[0, 1]).T
xrf, _yrf = np.loadtxt('observed/st3_prf.dat', usecols=[0, 1]).T
# add noise to create observed data
# order of noise values (correlation, amplitude):
# noise = [corr1, sigma1, corr2, sigma2] for 2 targets
noise = [0.0, 0.012, 0.90, 0.005]
ysw_err = SynthObs.compute_expnoise(_ysw, corr=noise[0], sigma=noise[1])
ysw = _ysw + ysw_err
yrf_err = SynthObs.compute_gaussnoise(_yrf, corr=noise[2], sigma=noise[3])
yrf = _yrf + yrf_err
#
