diff --git a/examples/injection_examples/basic_tutorial.py b/examples/injection_examples/basic_tutorial.py
index dd990be32f856d842a49386009d90852fd5bec04..83e1556f4c8b0315d83a4459139040c99516ef03 100644
--- a/examples/injection_examples/basic_tutorial.py
+++ b/examples/injection_examples/basic_tutorial.py
@@ -14,7 +14,7 @@ time_duration = 4.
sampling_frequency = 2048.
outdir = 'outdir'
label = 'basic_tutorial'
-tupak.utils.setup_logger(outdir=outdir, label=label, log_level="info")
+tupak.utils.setup_logger(outdir=outdir, label=label)
np.random.seed(170809)
diff --git a/examples/injection_examples/how_to_specify_the_prior.py b/examples/injection_examples/how_to_specify_the_prior.py
index 500cf91a9635a9c0034beb7e2e96db97570622bf..8829a71f7846b7cf1130d0d606b13f0b37ce2f8c 100644
--- a/examples/injection_examples/how_to_specify_the_prior.py
+++ b/examples/injection_examples/how_to_specify_the_prior.py
@@ -6,7 +6,7 @@ from __future__ import division, print_function
import tupak
import numpy as np
-tupak.utils.setup_logger(log_level="info")
+tupak.utils.setup_logger()
time_duration = 4.
sampling_frequency = 2048.
diff --git a/examples/injection_examples/marginalized_likelihood.py b/examples/injection_examples/marginalized_likelihood.py
index 7fcd0acee31f1c19b266007f6cc98d3e4e77d024..67ad222560cad941c2d23a3a6de6987a95a51ca5 100644
--- a/examples/injection_examples/marginalized_likelihood.py
+++ b/examples/injection_examples/marginalized_likelihood.py
@@ -7,7 +7,7 @@ from __future__ import division, print_function
import tupak
import numpy as np
-tupak.utils.setup_logger(log_level="info")
+tupak.utils.setup_logger()
time_duration = 4.
sampling_frequency = 2048.
diff --git a/examples/other_examples/alternative_likelihoods.py b/examples/other_examples/alternative_likelihoods.py
index dd735af89c49280262d861dd6e8d26550f9f3b7e..0d31bd09ddf4ee9c582917568bf52182f16d6284 100644
--- a/examples/other_examples/alternative_likelihoods.py
+++ b/examples/other_examples/alternative_likelihoods.py
@@ -9,7 +9,7 @@ import numpy as np
import matplotlib.pyplot as plt
# A few simple setup steps
-tupak.utils.setup_logger(log_level="info")
+tupak.utils.setup_logger()
label = 'test'
outdir = 'outdir'
diff --git a/tupak/result.py b/tupak/result.py
index 60f6165079755848eedb8d13b209931b2cfe0a13..d14d37561477bb9d6ce8784f43512d85ab94316f 100644
--- a/tupak/result.py
+++ b/tupak/result.py
@@ -12,7 +12,25 @@ except ImportError:
"You do not have the optional module chainconsumer installed")
+def result_file_name(outdir, label):
+ """ Returns the standard filename used for a result file """
+ return '{}/{}_result.h5'.format(outdir, label)
+
+
+def read_in_result(outdir, label):
+ """ Read in a saved .h5 data file """
+ filename = result_file_name(outdir, label)
+ if os.path.isfile(filename):
+ return Result(deepdish.io.load(filename))
+ else:
+ return None
+
+
class Result(dict):
+ def __init__(self, dictionary=None):
+ if type(dictionary) is dict:
+ for key in dictionary:
+ setattr(self, key, dictionary[key])
def __getattr__(self, name):
try:
@@ -25,15 +43,19 @@ class Result(dict):
def __repr__(self):
"""Print a summary """
- return ("nsamples: {:d}\n"
- "noise_logz: {:6.3f}\n"
- "logz: {:6.3f} +/- {:6.3f}\n"
- "log_bayes_factor: {:6.3f} +/- {:6.3f}\n"
- .format(len(self.samples), self.noise_logz, self.logz, self.logzerr, self.log_bayes_factor,
- self.logzerr))
+ if hasattr(self, 'samples'):
+ return ("nsamples: {:d}\n"
+ "noise_logz: {:6.3f}\n"
+ "logz: {:6.3f} +/- {:6.3f}\n"
+ "log_bayes_factor: {:6.3f} +/- {:6.3f}\n"
+ .format(len(self.samples), self.noise_logz, self.logz,
+ self.logzerr, self.log_bayes_factor, self.logzerr))
+ else:
+ return ''
def save_to_file(self, outdir, label):
- file_name = '{}/{}_result.h5'.format(outdir, label)
+ """ Writes the Result to a deepdish h5 file """
+ file_name = result_file_name(outdir, label)
if os.path.isdir(outdir) is False:
os.makedirs(outdir)
if os.path.isfile(file_name):
@@ -98,6 +120,10 @@ class Result(dict):
kwargs['parameters'] = self.get_latex_labels_from_parameter_keys(
kwargs['parameters'])
+ # Check all parameter_labels are a valid string
+ for i, label in enumerate(self.parameter_labels):
+ if label is None:
+ self.parameter_labels[i] = 'Unknown'
c = ChainConsumer()
c.add_chain(self.samples, parameters=self.parameter_labels,
name=self.label)
@@ -194,3 +220,19 @@ class Result(dict):
self.posterior['chi_p'] = max(self.posterior.a_1 * np.sin(self.posterior.tilt_1),
(4 * self.posterior.q + 3) / (3 * self.posterior.q + 4) * self.posterior.q
* self.posterior.a_2 * np.sin(self.posterior.tilt_2))
+
+ def check_attribute_match_to_other_object(self, name, other_object):
+ """ Check attribute name exists in other_object and is the same """
+ A = getattr(self, name, False)
+ B = getattr(other_object, name, False)
+ logging.debug('Checking {} value: {}=={}'.format(name, A, B))
+ if (A is not False) and (B is not False):
+ typeA = type(A)
+ typeB = type(B)
+ if typeA == typeB:
+ if typeA in [str, float, int, dict, list]:
+ return A == B
+ elif typeA in [np.ndarray]:
+ return np.all(A == B)
+ return False
+
diff --git a/tupak/sampler.py b/tupak/sampler.py
index 281da7b52a1493f73a6af30a6aa7bc180434f5c6..0f965bb4eee0d8214012bf02c39f206fd2817781 100644
--- a/tupak/sampler.py
+++ b/tupak/sampler.py
@@ -7,7 +7,7 @@ import sys
import numpy as np
import matplotlib.pyplot as plt
-from .result import Result
+from .result import Result, read_in_result
from .prior import Prior, fill_priors
from . import utils
from . import prior
@@ -54,6 +54,7 @@ class Sampler(object):
self.kwargs = kwargs
self.result = result
+ self.check_cached_result()
self.log_summary_for_sampler()
@@ -79,6 +80,15 @@ class Sampler(object):
else:
raise TypeError('result must either be a Result or None')
+ @property
+ def search_parameter_keys(self):
+ return self.__search_parameter_keys
+
+ @property
+ def fixed_parameter_keys(self):
+ return self.__fixed_parameter_keys
+
+
@property
def external_sampler(self):
return self.__external_sampler
@@ -179,9 +189,35 @@ class Sampler(object):
def run_sampler(self):
pass
+ def check_cached_result(self):
+ """ Check if the cached data file exists and can be used """
+
+ if utils.command_line_args.clean:
+ logging.debug("Command line argument clean given, forcing rerun")
+ self.cached_result = None
+ return
+ self.cached_result = read_in_result(self.outdir, self.label)
+ if utils.command_line_args.use_cached:
+ logging.debug("Command line argument cached given, no cache check performed")
+ return
+
+ logging.debug("Checking cached data")
+ if self.cached_result:
+ check_keys = ['search_parameter_keys', 'fixed_parameter_keys',
+ 'kwargs']
+ use_cache = True
+ for key in check_keys:
+ if self.cached_result.check_attribute_match_to_other_object(
+ key, self) is False:
+ logging.debug("Cached value {} is unmatched".format(key))
+ use_cache = False
+ if use_cache is False:
+ self.cached_result = None
+
def log_summary_for_sampler(self):
- logging.info("Using sampler {} with kwargs {}".format(
- self.__class__.__name__, self.kwargs))
+ if self.cached_result is None:
+ logging.info("Using sampler {} with kwargs {}".format(
+ self.__class__.__name__, self.kwargs))
class Nestle(Sampler):
@@ -358,7 +394,7 @@ class Ptemcee(Sampler):
def run_sampler(likelihood, priors=None, label='label', outdir='outdir',
sampler='nestle', use_ratio=True, injection_parameters=None,
- **sampler_kwargs):
+ **kwargs):
"""
The primary interface to easy parameter estimation
@@ -383,7 +419,7 @@ def run_sampler(likelihood, priors=None, label='label', outdir='outdir',
injection_parameters: dict
A dictionary of injection parameters used in creating the data (if
using simulated data). Appended to the result object and saved.
- **sampler_kwargs:
+ **kwargs:
All kwargs are passed directly to the samplers `run` functino
Returns
@@ -404,7 +440,11 @@ def run_sampler(likelihood, priors=None, label='label', outdir='outdir',
sampler_class = globals()[sampler.title()]
sampler = sampler_class(likelihood, priors, sampler, outdir=outdir,
label=label, use_ratio=use_ratio,
- **sampler_kwargs)
+ **kwargs)
+ if sampler.cached_result:
+ logging.info("Using cached result")
+ return sampler.cached_result
+
result = sampler.run_sampler()
result.noise_logz = likelihood.noise_log_likelihood()
if use_ratio:
@@ -414,7 +454,8 @@ def run_sampler(likelihood, priors=None, label='label', outdir='outdir',
result.log_bayes_factor = result.logz - result.noise_logz
result.injection_parameters = injection_parameters
result.fixed_parameter_keys = [key for key in priors if isinstance(key, prior.DeltaFunction)]
- # result.prior = prior # Removed as this breaks the saving of the data
+ result.priors = priors
+ result.kwargs = sampler.kwargs
result.samples_to_data_frame()
result.save_to_file(outdir=outdir, label=label)
return result
diff --git a/tupak/utils.py b/tupak/utils.py
index a6405f5883a583d40967d01b102eabaad37cc3ae..71eb761fa4ad05a896e724cca3abc97df5ff8fa8 100644
--- a/tupak/utils.py
+++ b/tupak/utils.py
@@ -4,6 +4,7 @@ import os
import numpy as np
from math import fmod
from gwpy.timeseries import TimeSeries
+import argparse
# Constants
speed_of_light = 299792458.0 # speed of light in m/s
@@ -281,7 +282,7 @@ def get_vertex_position_geocentric(latitude, longitude, elevation):
return np.array([x_comp, y_comp, z_comp])
-def setup_logger(outdir=None, label=None, log_level='info'):
+def setup_logger(outdir=None, label=None, log_level=None):
""" Setup logging output: call at the start of the script to use
Parameters
@@ -298,6 +299,8 @@ def setup_logger(outdir=None, label=None, log_level='info'):
LEVEL = getattr(logging, log_level.upper())
except AttributeError:
raise ValueError('log_level {} not understood'.format(log_level))
+ elif log_level is None:
+ LEVEL = command_line_args.log_level
else:
LEVEL = int(log_level)
@@ -509,4 +512,33 @@ def get_open_strain_data(
return strain
+def set_up_command_line_arguments():
+ parser = argparse.ArgumentParser(
+ description="Command line interface for tupak scripts")
+ parser.add_argument("-v", "--verbose", action="store_true",
+ help=("Increase output verbosity [logging.DEBUG]." +
+ " Overridden by script level settings"))
+ parser.add_argument("-q", "--quite", action="store_true",
+ help=("Decrease output verbosity [logging.WARNING]." +
+ " Overridden by script level settings"))
+ parser.add_argument("-c", "--clean", action="store_true",
+ help="Force clean data, never use cached data")
+ parser.add_argument("-u", "--use-cached", action="store_true",
+ help="Force cached data and do not check its validity")
+ args, _ = parser.parse_known_args()
+
+ if args.quite:
+ args.log_level = logging.WARNING
+ elif args.verbose:
+ args.log_level = logging.DEBUG
+ else:
+ args.log_level = logging.INFO
+
+ return args
+
+
+command_line_args = set_up_command_line_arguments()
+
+
+