def derivative(params, p, output, best_parameters=None, partial=False):
F = threebody.Fitter(**params)
if p not in F.parameters:
raise ValueError("Parameter %s not among options: %s" %
(p, F.parameters))
if best_parameters is not None:
F.best_parameters = pickle.load(open(best_parameters, "rb"))
print(F.goodness_of_fit(F.best_parameters))
if partial:
vals, names = F.compute_linear_parts()
for (n, v) in zip(names, vals):
F.best_parameters[n] = v
bs = base_steps.get(p, 1e-3)
sg = numdifftools.MaxStepGenerator(bs, use_exact_steps=True)
def fres(v):
bp = F.best_parameters.copy()
print(p, bp[p], v, end="\t")
bp[p] += v
try:
r = F.residuals(bp, linear_fit=False)
print(F.goodness_of_fit(bp))
return r
except ValueError:
print(np.inf)
return np.inf * np.ones_like(F.mjds)
nl_der = numdifftools.Derivative(fres, step=sg)(0)
np.save(output, nl_der)
def optimize(params,
best_filename,
best_parameters=None,
method="BOBYQA",
output=None):
F = threebody.Fitter(**params)
if (best_parameters is not None and best_parameters != "default"):
F.best_parameters = pickle.load(open(best_parameters, "rb"))
M = minuit_wrap.Fitter(F.make_mfun(), output=output)
for p in F.parameters:
M.values[p] = F.best_parameters[p]
M.errors[p] = F.best_errors[p]
M.set_normalization()
M.tol = 100
M.strategy = 1
M.printMode = 3
M.best_filename = best_filename
if method == "MINUIT":
M.migrad()
elif method == "Powell":
M.scipy_minimize("Powell", options=dict(ftol=1e-8))
elif method == "basinhopping":
M.scipy_minimize("basinhopping",
minimizer_kwargs=dict(method="Powell",
options=dict(ftol=1e-6)))
elif method == "BOBYQA":
M.nlopt_minimize()
elif method == "simplex":
import nlopt
M.nlopt_minimize(optimizer=nlopt.LN_SBPLX)
elif method == "gp":
M.gp_minimize(n_random_starts=len(F.parameters),
n_calls=1000,
verbose=True)
else:
raise ValueError("Unknown method")
# Aargh! but taskset fixes it
# Not needed if using MPI
# os.system("taskset -p 0xffffffff %d" % os.getpid())
trust_nfs = True
n_steps = 100000
logger.debug("Process of rank %s running on host %s",
os.environ['OMPI_COMM_WORLD_RANK'], os.environ["HOST"])
logger.debug("Environment: %s", os.environ)
logger.debug("creating Fitter")
fn = 'emcee_params.pickle'
fitter_params = pickle.load(open(fn, "rb"))
F = threebody.Fitter(**fitter_params)
logger.debug("Fitter created")
j = 0
def lnprob(offset):
global j
logger.debug("call %d" % j)
j = j + 1
params = F.best_parameters.copy()
if len(offset) != len(F.parameters):
raise ValueError("Parameter mismatch between walker and Fitter")
for p, o in zip(F.parameters, offset):
params[p] += o
if False:
with open(
#!/usr/bin/env python
import os
import cPickle as pickle
import numpy as np
import scipy.linalg
import kepler
import quad_integrate
import threebody
fp = "fake_toas_fitter.pickle"
if os.path.exists(fp):
d = pickle.load(open(fp, "rb"))
F = threebody.Fitter(**d)
else:
F = threebody.Fitter()
rms = 3e-6
days = 1000
n_per_day = 100
times = np.linspace(1, days + 1, n_per_day * days + 1)
o = F.compute_orbit(F.best_parameters)
F_linear = F.compute_linear_parts(F.best_parameters)
def freq(t):
t0 = F_linear['tzrmjd'] + (F_linear['tzrmjd_base'] - F.base_mjd)
t_s = (t - t0) * 86400
return (F_linear['f0'] + F_linear['f1'] * t_s)
import numpy as np
import scipy.linalg
import pymc
import minuit
import threebody
import kepler
import quad_integrate
import minuit_wrap
jobid = os.environ['PBS_JOBID']
dbdir = os.path.join('/home/aarchiba/projects/threebody/chains', jobid)
local_dbdir = tempfile.mkdtemp()
F = threebody.Fitter()
# Any distribution I put here is a prior, so let's be broad
#spread = 10000.
#offset = pymc.Normal('offset',
# mu=np.zeros(len(F.parameters)),
# tau=spread**(-2)*np.array([F.best_errors[p] for p in F.parameters])**(-2))
# Flat priors! This is not kosher but should be fine
@pymc.stochastic()
def offset(value=np.zeros(len(F.parameters))):
return 0
@pymc.deterministic(trace=False)
def make_fitter(d):
return threebody.Fitter(**d)
import numpy as np
import scipy.linalg
import emcee
import threebody
import optimizer
# For some reason numpy sets the CPU affinity so we only use one processor
# Aargh! but taskset fixes it
#os.system("taskset -p 0xffffffff %d" % os.getpid())
debug = False
F = threebody.Fitter("0337+17-scott-2013-06-06", tzrmjd_middle=True)
def chi2(offset):
if np.shape(offset) != (len(F.parameters), ):
raise ValueError("Received an offset of shape %s" %
(np.shape(offset), ))
params = F.best_parameters.copy()
for p, o in zip(F.parameters, offset):
params[p] += o
r = F.residuals(params) / F.phase_uncerts
return np.sum(r**2)
pool = emcee.utils.MPIPool()
if not pool.is_master():
