From 54105163d7b3b67323158667bd92da1c0c1d7e10 Mon Sep 17 00:00:00 2001
From: Moritz Huebner <moritz.huebner@ligo.org>
Date: Thu, 15 Oct 2020 22:57:30 -0500
Subject: [PATCH] Resolve "Follow-up from "Adding dnest4 Sampler""
---
bilby/core/sampler/__init__.py | 10 +-
bilby/core/sampler/base_sampler.py | 29 +++++-
bilby/core/sampler/dnest4.py | 145 +++++++-------------------
bilby/core/sampler/pymultinest.py | 24 +----
bilby/core/sampler/ultranest.py | 26 +----
test/core/sampler/dnest4_test.py | 61 +++++++++++
test/core/sampler/sampler_run_test.py | 9 ++
7 files changed, 144 insertions(+), 160 deletions(-)
create mode 100644 test/core/sampler/dnest4_test.py
diff --git a/bilby/core/sampler/__init__.py b/bilby/core/sampler/__init__.py
index 6d02882f..27da2433 100644
--- a/bilby/core/sampler/__init__.py
+++ b/bilby/core/sampler/__init__.py
@@ -25,11 +25,11 @@ from .dnest4 import DNest4
from . import proposal
IMPLEMENTED_SAMPLERS = {
- 'cpnest': Cpnest, 'dynamic_dynesty': DynamicDynesty, 'dynesty': Dynesty,
- 'emcee': Emcee, 'kombine': Kombine, 'nestle': Nestle, 'ptemcee': Ptemcee,
- 'ptmcmcsampler': PTMCMCSampler, 'pymc3': Pymc3, 'pymultinest': Pymultinest,
- 'pypolychord': PyPolyChord, 'ultranest': Ultranest,
- 'fake_sampler': FakeSampler, 'dnest4': DNest4}
+ 'cpnest': Cpnest, 'dnest4': DNest4, 'dynamic_dynesty': DynamicDynesty,
+ 'dynesty': Dynesty, 'emcee': Emcee, 'kombine': Kombine, 'nestle': Nestle,
+ 'ptemcee': Ptemcee, 'ptmcmcsampler': PTMCMCSampler, 'pymc3': Pymc3,
+ 'pymultinest': Pymultinest, 'pypolychord': PyPolyChord, 'ultranest': Ultranest,
+ 'fake_sampler': FakeSampler}
if command_line_args.sampler_help:
sampler = command_line_args.sampler_help
diff --git a/bilby/core/sampler/base_sampler.py b/bilby/core/sampler/base_sampler.py
index 74e880fb..fa05b4f8 100644
--- a/bilby/core/sampler/base_sampler.py
+++ b/bilby/core/sampler/base_sampler.py
@@ -1,10 +1,13 @@
from __future__ import absolute_import
import datetime
+import distutils.dir_util
import numpy as np
+import os
+import tempfile
from pandas import DataFrame
-from ..utils import logger, command_line_args, Counter
+from ..utils import logger, check_directory_exists_and_if_not_mkdir, command_line_args, Counter
from ..prior import Prior, PriorDict, DeltaFunction, Constraint
from ..result import Result, read_in_result
@@ -541,7 +544,8 @@ class Sampler(object):
class NestedSampler(Sampler):
- npoints_equiv_kwargs = ['nlive', 'nlives', 'n_live_points', 'npoints', 'npoint', 'Nlive', 'num_live_points']
+ npoints_equiv_kwargs = ['nlive', 'nlives', 'n_live_points', 'npoints',
+ 'npoint', 'Nlive', 'num_live_points', 'num_particles']
walks_equiv_kwargs = ['walks', 'steps', 'nmcmc']
def reorder_loglikelihoods(self, unsorted_loglikelihoods, unsorted_samples,
@@ -601,6 +605,27 @@ class NestedSampler(Sampler):
else:
return np.nan_to_num(-np.inf)
+ def _setup_run_directory(self):
+ """
+ If using a temporary directory, the output directory is moved to the
+ temporary directory.
+ Used for Dnest4, Pymultinest, and Ultranest.
+ """
+ if self.use_temporary_directory:
+ temporary_outputfiles_basename = tempfile.TemporaryDirectory().name
+ self.temporary_outputfiles_basename = temporary_outputfiles_basename
+
+ if os.path.exists(self.outputfiles_basename):
+ distutils.dir_util.copy_tree(self.outputfiles_basename, self.temporary_outputfiles_basename)
+ check_directory_exists_and_if_not_mkdir(temporary_outputfiles_basename)
+
+ self.kwargs["outputfiles_basename"] = self.temporary_outputfiles_basename
+ logger.info("Using temporary file {}".format(temporary_outputfiles_basename))
+ else:
+ check_directory_exists_and_if_not_mkdir(self.outputfiles_basename)
+ self.kwargs["outputfiles_basename"] = self.outputfiles_basename
+ logger.info("Using output file {}".format(self.outputfiles_basename))
+
class MCMCSampler(Sampler):
nwalkers_equiv_kwargs = ['nwalker', 'nwalkers', 'draws', 'Niter']
diff --git a/bilby/core/sampler/dnest4.py b/bilby/core/sampler/dnest4.py
index a623635f..a35f54f6 100644
--- a/bilby/core/sampler/dnest4.py
+++ b/bilby/core/sampler/dnest4.py
@@ -1,12 +1,10 @@
-from __future__ import absolute_import
-
import os
-import tempfile
import shutil
import distutils.dir_util
import signal
import time
import datetime
+import sys
import numpy as np
import pandas as pd
@@ -20,14 +18,14 @@ class _DNest4Model(object):
def __init__(self, log_likelihood_func, from_prior_func, widths, centers, highs, lows):
"""Initialize the DNest4 model.
Args:
- log_likelihood_func (function): The loglikelihood function to use
- during the Nested Sampling run.
- from_prior_func (function): The function to use when randomly
- selecting parameter vectors from the prior space.
- widths (numpy.array): The approximate widths of the prior
- distrbutions.
- centers (numpy.array): The approximate center points of the prior
- distributions.
+ log_likelihood_func: function
+ The loglikelihood function to use during the Nested Sampling run.
+ from_prior_func: function
+ The function to use when randomly selecting parameter vectors from the prior space.
+ widths: array_like
+ The approximate widths of the prior distrbutions.
+ centers: array_like
+ The approximate center points of the prior distributions.
"""
self._log_likelihood = log_likelihood_func
self._from_prior = from_prior_func
@@ -58,9 +56,11 @@ class _DNest4Model(object):
return 0.0
- def wrap(self, x, a, b):
- assert b > a
- return (x - a) % (b - a) + a
+ @staticmethod
+ def wrap(x, minimum, maximum):
+ if maximum <= minimum:
+ raise ValueError("maximum {} <= minimum {}, when trying to wrap coordinates".format(maximum, minimum))
+ return (x - minimum) % (maximum - minimum) + minimum
class DNest4(NestedSampler):
@@ -83,8 +83,9 @@ class DNest4(NestedSampler):
The python DNest4 backend for storing the output.
Options are: 'memory' and 'csv'. If 'memory' the
DNest4 outputs are stored in memory during the run. If 'csv' the
- DNest4 outputs are written out to filse with a CSV format during
+ DNest4 outputs are written out to files with a CSV format during
the run.
+ CSV backend may not be functional right now (October 2020)
num_steps: int
The number of MCMC iterations to run
new_level_interval: int
@@ -97,53 +98,20 @@ class DNest4(NestedSampler):
Set the seed for the C++ random number generator
verbose: Bool
If True, prints information during run
- TO DO: add equivalent args for num_particles (nlive, etc.)
- Add sampling time functions
"""
- default_kwargs = dict(
- max_num_levels=20,
- num_steps=500, # Number of iterations
- new_level_interval=10000,
- num_per_step=10000,
- thread_steps=1,
- num_particles=1000,
- lam=10.0,
- beta=100,
- seed=None,
- verbose=True,
- outputfiles_basename=None,
- # backend_callback=None, # for checkpointing in dnest5
- backend='memory', # csv is currently bugged right now
-
- # could change max_num_levels based on snr
- )
-
- def __init__(
- self,
- likelihood,
- priors,
- outdir="outdir",
- label="label",
- use_ratio=False,
- plot=False,
- exit_code=77,
- skip_import_verification=False,
- temporary_directory=True,
- resume=True,
- **kwargs
- ):
+ default_kwargs = dict(max_num_levels=20, num_steps=500,
+ new_level_interval=10000, num_per_step=10000,
+ thread_steps=1, num_particles=1000, lam=10.0,
+ beta=100, seed=None, verbose=True, outputfiles_basename=None,
+ backend='memory')
+
+ def __init__(self, likelihood, priors, outdir="outdir", label="label", use_ratio=False, plot=False,
+ exit_code=77, skip_import_verification=False, temporary_directory=True, **kwargs):
super(DNest4, self).__init__(
- likelihood=likelihood,
- priors=priors,
- outdir=outdir,
- label=label,
- use_ratio=use_ratio,
- plot=plot,
- skip_import_verification=skip_import_verification,
- exit_code=exit_code,
- **kwargs
- )
+ likelihood=likelihood, priors=priors, outdir=outdir, label=label,
+ use_ratio=use_ratio, plot=plot, skip_import_verification=skip_import_verification,
+ exit_code=exit_code, **kwargs)
self.num_particles = self.kwargs["num_particles"]
self.max_num_levels = self.kwargs["max_num_levels"]
@@ -151,6 +119,13 @@ class DNest4(NestedSampler):
self._backend = self.kwargs["backend"]
self.use_temporary_directory = temporary_directory
+ self.start_time = np.nan
+ self.sampler = None
+ self._information = np.nan
+ self._last_live_sample_info = np.nan
+ self._outputfiles_basename = None
+ self._temporary_outputfiles_basename = None
+
signal.signal(signal.SIGTERM, self.write_current_state_and_exit)
signal.signal(signal.SIGINT, self.write_current_state_and_exit)
signal.signal(signal.SIGALRM, self.write_current_state_and_exit)
@@ -180,26 +155,19 @@ class DNest4(NestedSampler):
self._highs = np.array(highs)
self._lows = np.array(lows)
- self._from_prior = self.get_random_draw_from_prior
-
- self._dnest4_model = _DNest4Model(self.log_likelihood, self._from_prior, self._widths,
+ self._dnest4_model = _DNest4Model(self.log_likelihood, self.get_random_draw_from_prior, self._widths,
self._centers, self._highs, self._lows)
def _set_backend(self):
import dnest4
if self._backend == 'csv':
- # for CSVBackend, which is output data to disk
- backend = dnest4.backends.CSVBackend("{}/dnest4{}/".format(self.outdir, self.label), sep=" ")
- # change to original
+ return dnest4.backends.CSVBackend("{}/dnest4{}/".format(self.outdir, self.label), sep=" ")
else:
- # for the MemoryBackend, which is output data to memory
- backend = dnest4.backends.MemoryBackend()
- return backend
+ return dnest4.backends.MemoryBackend()
def _set_dnest4_kwargs(self):
dnest4_keys = ["num_steps", "new_level_interval", "lam", "beta", "seed"]
self.dnest4_kwargs = {key: self.kwargs[key] for key in dnest4_keys}
- return self.dnest4_kwargs
def run_sampler(self):
import dnest4
@@ -233,17 +201,11 @@ class DNest4(NestedSampler):
if self._backend == 'memory':
self._last_live_sample_info = pd.DataFrame(self.sampler.backend.sample_info[-1])
self.result.log_likelihood_evaluations = self._last_live_sample_info['log_likelihood']
-
self.result.samples = np.array(self.sampler.backend.posterior_samples)
- print("here")
- print(self.sampler.backend.posterior_samples)
- print(self.result.samples)
else:
sample_info_path = './' + self.kwargs["outputfiles_basename"] + '/sample_info.txt'
-
sample_info = np.genfromtxt(sample_info_path, comments='#', names=True)
self.result.log_likelihood_evaluations = sample_info['log_likelihood']
-
self.result.samples = np.array(self.sampler.backend.posterior_samples)
self.result.sampler_output = out
@@ -262,36 +224,7 @@ class DNest4(NestedSampler):
def _verify_kwargs_against_default_kwargs(self):
self.outputfiles_basename = self.kwargs.pop("outputfiles_basename", None)
-
- # if self.kwargs['backend_callback'] is None:
- # self.kwargs['backend_callback'] = self._backend_callback
-
- NestedSampler._verify_kwargs_against_default_kwargs(self)
-
- # def _backend_callback(self, *args, **kwargs):
- # if self.use_temporary_directory:
- # self._copy_temporary_directory_contents_to_proper_path()
- # self._calculate_and_save_sampling_time()
-
- def _setup_run_directory(self):
- """
- If using a temporary directory, the output directory is moved to the
- temporary directory.
- """
- if self.use_temporary_directory:
- temporary_outputfiles_basename = tempfile.TemporaryDirectory().name
- self.temporary_outputfiles_basename = temporary_outputfiles_basename
-
- if os.path.exists(self.outputfiles_basename):
- distutils.dir_util.copy_tree(self.outputfiles_basename, self.temporary_outputfiles_basename)
- check_directory_exists_and_if_not_mkdir(temporary_outputfiles_basename)
-
- self.kwargs["outputfiles_basename"] = self.temporary_outputfiles_basename
- logger.info("Using temporary file {}".format(temporary_outputfiles_basename))
- else:
- check_directory_exists_and_if_not_mkdir(self.outputfiles_basename)
- self.kwargs["outputfiles_basename"] = self.outpuxtfiles_basename
- logger.info("Using output file {}".format(self.outputfiles_basename))
+ super(DNest4, self)._verify_kwargs_against_default_kwargs()
def _check_and_load_sampling_time_file(self):
self.time_file_path = self.kwargs["outputfiles_basename"] + '/sampling_time.dat'
@@ -355,7 +288,7 @@ class DNest4(NestedSampler):
self._calculate_and_save_sampling_time()
if self.use_temporary_directory:
self._move_temporary_directory_to_proper_path()
- os._exit(self.exit_code)
+ sys.exit(self.exit_code)
def _move_temporary_directory_to_proper_path(self):
"""
diff --git a/bilby/core/sampler/pymultinest.py b/bilby/core/sampler/pymultinest.py
index eaa14cce..e977dc15 100644
--- a/bilby/core/sampler/pymultinest.py
+++ b/bilby/core/sampler/pymultinest.py
@@ -1,11 +1,11 @@
import importlib
import os
-import tempfile
import shutil
import distutils.dir_util
import signal
import time
import datetime
+import sys
import numpy as np
@@ -175,7 +175,7 @@ class Pymultinest(NestedSampler):
self._calculate_and_save_sampling_time()
if self.use_temporary_directory:
self._move_temporary_directory_to_proper_path()
- os._exit(self.exit_code)
+ sys.exit(self.exit_code)
def _copy_temporary_directory_contents_to_proper_path(self):
"""
@@ -239,26 +239,6 @@ class Pymultinest(NestedSampler):
self.result.sampling_time = datetime.timedelta(seconds=self.total_sampling_time)
return self.result
- def _setup_run_directory(self):
- """
- If using a temporary directory, the output directory is moved to the
- temporary directory.
- """
- if self.use_temporary_directory:
- temporary_outputfiles_basename = tempfile.TemporaryDirectory().name
- self.temporary_outputfiles_basename = temporary_outputfiles_basename
-
- if os.path.exists(self.outputfiles_basename):
- distutils.dir_util.copy_tree(self.outputfiles_basename, self.temporary_outputfiles_basename)
- check_directory_exists_and_if_not_mkdir(temporary_outputfiles_basename)
-
- self.kwargs["outputfiles_basename"] = self.temporary_outputfiles_basename
- logger.info("Using temporary file {}".format(temporary_outputfiles_basename))
- else:
- check_directory_exists_and_if_not_mkdir(self.outputfiles_basename)
- self.kwargs["outputfiles_basename"] = self.outputfiles_basename
- logger.info("Using output file {}".format(self.outputfiles_basename))
-
def _check_and_load_sampling_time_file(self):
self.time_file_path = self.kwargs["outputfiles_basename"] + '/sampling_time.dat'
if os.path.exists(self.time_file_path):
diff --git a/bilby/core/sampler/ultranest.py b/bilby/core/sampler/ultranest.py
index 82815557..fdae9a8e 100644
--- a/bilby/core/sampler/ultranest.py
+++ b/bilby/core/sampler/ultranest.py
@@ -6,7 +6,6 @@ import inspect
import os
import shutil
import signal
-import tempfile
import time
import numpy as np
@@ -287,6 +286,7 @@ class Ultranest(NestedSampler):
stepsampler = self.kwargs.pop("step_sampler", None)
self._setup_run_directory()
+ self.kwargs["log_dir"] = self.kwargs.pop("outputfiles_basename")
self._check_and_load_sampling_time_file()
# use reactive nested sampler when no live points are given
@@ -326,30 +326,6 @@ class Ultranest(NestedSampler):
return self.result
- def _setup_run_directory(self):
- """
- If using a temporary directory, the output directory is moved to the
- temporary directory and symlinked back.
- """
- if self.use_temporary_directory:
- temporary_outputfiles_basename = tempfile.TemporaryDirectory().name
- self.temporary_outputfiles_basename = temporary_outputfiles_basename
-
- if os.path.exists(self.outputfiles_basename):
- distutils.dir_util.copy_tree(
- self.outputfiles_basename, self.temporary_outputfiles_basename
- )
- check_directory_exists_and_if_not_mkdir(temporary_outputfiles_basename)
-
- self.kwargs["log_dir"] = self.temporary_outputfiles_basename
- logger.info(
- "Using temporary file {}".format(temporary_outputfiles_basename)
- )
- else:
- check_directory_exists_and_if_not_mkdir(self.outputfiles_basename)
- self.kwargs["log_dir"] = self.outputfiles_basename
- logger.info("Using output file {}".format(self.outputfiles_basename))
-
def _clean_up_run_directory(self):
if self.use_temporary_directory:
self._move_temporary_directory_to_proper_path()
diff --git a/test/core/sampler/dnest4_test.py b/test/core/sampler/dnest4_test.py
new file mode 100644
index 00000000..fc67a0f8
--- /dev/null
+++ b/test/core/sampler/dnest4_test.py
@@ -0,0 +1,61 @@
+import unittest
+
+from mock import MagicMock
+
+import bilby
+
+
+class TestDnest4(unittest.TestCase):
+ def setUp(self):
+ self.likelihood = MagicMock()
+ self.priors = bilby.core.prior.PriorDict(
+ dict(a=bilby.core.prior.Uniform(0, 1), b=bilby.core.prior.Uniform(0, 1))
+ )
+ self.sampler = bilby.core.sampler.DNest4(
+ self.likelihood,
+ self.priors,
+ outdir="outdir",
+ label="label",
+ use_ratio=False,
+ plot=False,
+ skip_import_verification=True,
+ )
+
+ def tearDown(self):
+ del self.likelihood
+ del self.priors
+ del self.sampler
+
+ def test_default_kwargs(self):
+ expected = dict(
+ max_num_levels=20, num_steps=500,
+ new_level_interval=10000, num_per_step=10000,
+ thread_steps=1, num_particles=1000, lam=10.0,
+ beta=100, seed=None, verbose=True, backend='memory'
+ )
+ for key in self.sampler.kwargs.keys():
+ print(
+ "key={}, expected={}, actual={}".format(
+ key, expected[key], self.sampler.kwargs[key]
+ )
+ )
+ self.assertDictEqual(expected, self.sampler.kwargs)
+
+ def test_translate_kwargs(self):
+ expected = dict(
+ max_num_levels=20, num_steps=500,
+ new_level_interval=10000, num_per_step=10000,
+ thread_steps=1, num_particles=1000, lam=10.0,
+ beta=100, seed=None, verbose=True, backend='memory'
+ )
+
+ for equiv in bilby.core.sampler.base_sampler.NestedSampler.npoints_equiv_kwargs:
+ new_kwargs = self.sampler.kwargs.copy()
+ del new_kwargs["num_particles"]
+ new_kwargs[equiv] = 1000
+ self.sampler.kwargs = new_kwargs
+ self.assertDictEqual(expected, self.sampler.kwargs)
+
+
+if __name__ == "__main__":
+ unittest.main()
diff --git a/test/core/sampler/sampler_run_test.py b/test/core/sampler/sampler_run_test.py
index 2d697494..3278ddc0 100644
--- a/test/core/sampler/sampler_run_test.py
+++ b/test/core/sampler/sampler_run_test.py
@@ -40,6 +40,15 @@ class TestRunningSamplers(unittest.TestCase):
resume=False,
)
+ def test_run_dnest4(self):
+ _ = bilby.run_sampler(
+ likelihood=self.likelihood,
+ priors=self.priors,
+ sampler="dnest4",
+ nlive=100,
+ save=False,
+ )
+
def test_run_dynesty(self):
_ = bilby.run_sampler(
likelihood=self.likelihood,
--
GitLab