diff --git a/bilby/core/result.py b/bilby/core/result.py
index 0c234df022ac513507f3a4547c07a29a93a55bbf..c2a8a569a5c616618bd4b3c9d346ec41f7be07cd 100644
--- a/bilby/core/result.py
+++ b/bilby/core/result.py
@@ -25,6 +25,9 @@ from .utils import (
from .prior import Prior, PriorDict, DeltaFunction, ConditionalDeltaFunction
+EXTENSIONS = ["json", "hdf5", "h5", "pickle", "pkl"]
+
+
def result_file_name(outdir, label, extension='json', gzip=False):
""" Returns the standard filename used for a result file
diff --git a/bilby/core/utils/io.py b/bilby/core/utils/io.py
index 49f77b7739baf8bf3490185bad3bdf67a30b699c..55d7c6efb76e7f824650ea4318abdc9e119451cf 100644
--- a/bilby/core/utils/io.py
+++ b/bilby/core/utils/io.py
@@ -208,7 +208,7 @@ def decode_from_hdf5(item):
return output
-def encode_for_hdf5(item):
+def encode_for_hdf5(key, item):
"""
Encode an item to a HDF5 savable format.
@@ -249,6 +249,8 @@ def encode_for_hdf5(item):
output.append(b"__none__")
elif isinstance(item[0], (int, float, complex)):
output = np.array(item)
+ else:
+ raise ValueError(f'Cannot save {key}: {type(item)} type')
elif isinstance(item, PriorDict):
output = json.dumps(item._get_json_dict())
elif isinstance(item, pd.DataFrame):
@@ -262,7 +264,7 @@ def encode_for_hdf5(item):
elif isinstance(item, tuple):
output = {str(ii): elem for ii, elem in enumerate(item)}
else:
- raise ValueError(f'Cannot save {type(item)} type')
+ raise ValueError(f'Cannot save {key}: {type(item)} type')
return output
@@ -310,7 +312,7 @@ def recursively_save_dict_contents_to_group(h5file, path, dic):
The dictionary containing the data
"""
for key, item in dic.items():
- item = encode_for_hdf5(item)
+ item = encode_for_hdf5(key, item)
if isinstance(item, dict):
recursively_save_dict_contents_to_group(h5file, path + key + '/', item)
else:
diff --git a/cli_bilby/bilby_result.py b/cli_bilby/bilby_result.py
index 6cacfb62db2cafa8ff5ed6797d690c5562875464..0bde76015aaad920ad8212fa4ed7bd6c074762e5 100644
--- a/cli_bilby/bilby_result.py
+++ b/cli_bilby/bilby_result.py
@@ -4,7 +4,7 @@ Examples
--------
To convert all the JSON result files in `outdir` to hdf5 format:
- $ bilby_result -r outdir/*json -c hdf5
+ $ bilby_result -r outdir/*json -e hdf5
Note, by default this will save the new files in the outdir defined within the
results files. To give a new location, use the `--outdir` argument.
@@ -17,54 +17,106 @@ To generate a corner plot for all the files in outdir
$ bilby_result -r outdir/*json --call plot_corner
-This is effectively calling `plot_corner()` on each of the result files
+This is calling `plot_corner()` on each of the result files
individually. Note that passing extra commands in is not yet implemented.
"""
import argparse
-import pandas as pd
import bilby
+from bilby.core.result import EXTENSIONS
from bilby.core.utils import tcolors
def setup_command_line_args():
- parser = argparse.ArgumentParser(
- description="Helper tool for bilby result files")
+ parser = argparse.ArgumentParser(description="Helper tool for bilby result files")
+ parser.add_argument("positional_results", nargs="*", help="List of results files.")
parser.add_argument(
- "results", nargs='?',
- help="List of results files.")
+ "-r",
+ "--results",
+ nargs="+",
+ dest="optional_results",
+ default=list(),
+ help="List of results files (alternative to passing results as a positional argument).",
+ )
+
+ parser.add_argument(
+ "-e",
+ "--extension",
+ type=str,
+ choices=EXTENSIONS,
+ default=True,
+ help="Use given extension for the output file.",
+ )
+ parser.add_argument(
+ "-g",
+ "--gzip",
+ action="store_true",
+ help="Gzip the merged output results file if using JSON format.",
+ )
+ parser.add_argument(
+ "-o", "--outdir", type=str, default=None, help="Output directory."
+ )
parser.add_argument(
- "-r", "--results", nargs='+', dest="option_results", default=list(),
- help="List of results files (alternative to passing results as a positional argument).")
- parser.add_argument("-c", "--convert", type=str, choices=['json', 'hdf5'],
- help="Convert all results.", default=False)
- parser.add_argument("-m", "--merge", action='store_true',
- help="Merge the set of runs, output saved using the outdir and label")
- parser.add_argument("-e", "--extension", type=str, choices=["json", "hdf5"],
- default=True, help="Use given extension for the merged output file.")
- parser.add_argument("-g", "--gzip", action="store_true",
- help="Gzip the merged output results file if using JSON format.")
- parser.add_argument("-o", "--outdir", type=str, default=None,
- help="Output directory.")
- parser.add_argument("-l", "--label", type=str, default=None,
- help="New label for output result object")
- parser.add_argument("-b", "--bayes", action='store_true',
- help="Print all Bayes factors.")
- parser.add_argument("-p", "--print", nargs='+', default=None, dest="keys",
- help="Result dictionary keys to print.")
- parser.add_argument("--call", nargs='+', default=None,
- help="Result dictionary methods to call (no argument passing available).")
- parser.add_argument("--ipython", action='store_true',
- help=("For each result given, drops the user into an "
- "IPython shell with the result loaded in"))
+ "-l",
+ "--label",
+ type=str,
+ default=None,
+ help="New label for output result object",
+ )
+ parser.add_argument(
+ "--max-samples",
+ type=int,
+ default=None,
+ help="Maximum number of samples for output result object",
+ )
+ parser.add_argument(
+ "--lightweight",
+ action="store_true",
+ help="If true, strip back the result to only the posterior",
+ )
+
+ action_parser = parser.add_mutually_exclusive_group(required=True)
+ action_parser.add_argument(
+ "-s",
+ "--save",
+ action="store_true",
+ help="Save each result output saved using the outdir and label",
+ )
+ action_parser.add_argument(
+ "-m",
+ "--merge",
+ action="store_true",
+ help="Merge the set of runs, output saved using the outdir and label",
+ )
+ action_parser.add_argument(
+ "-b", "--bayes", action="store_true", help="Print all Bayes factors."
+ )
+ action_parser.add_argument(
+ "-p",
+ "--print",
+ nargs="+",
+ default=None,
+ dest="keys",
+ help="Result dictionary keys to print.",
+ )
+ action_parser.add_argument(
+ "--call",
+ nargs="+",
+ default=None,
+ help="Result dictionary methods to call (no argument passing available).",
+ )
+ action_parser.add_argument(
+ "--ipython",
+ action="store_true",
+ help=(
+ "For each result given, drops the user into an "
+ "IPython shell with the result loaded in"
+ ),
+ )
args = parser.parse_args()
- if args.results is None:
- args.results = []
- if isinstance(args.results, str):
- args.results = [args.results]
- args.results += args.option_results
+ args.results = args.positional_results + args.optional_results
if len(args.results) == 0:
raise ValueError("You have not passed any results to bilby_result")
@@ -80,24 +132,25 @@ def read_in_results(filename_list):
def print_bayes_factors(results_list):
- print("\nPrinting Bayes factors:")
- N = len(results_list)
- for i, res in enumerate(results_list):
- print("For label={}".format(res.label))
- index = ['noise'] + [results_list[j].label for j in range(i + 1, N)]
- data = [res.log_bayes_factor]
- data += [res.log_evidence - results_list[j].log_evidence for j in range(i + 1, N)]
- series = pd.Series(data=data, index=index, name=res.label)
- print(series)
+ for res in results_list:
+ print(f"For result {res.label}:")
+ print(f" log_evidence={res.log_evidence}")
+ print(f" log_noise_evidence={res.log_noise_evidence}")
+ print(f" log_bayes_factor={res.log_noise_evidence}")
+ print(f" log_10_evidence={res.log_10_evidence}")
+ print(f" log_10_noise_evidence={res.log_10_noise_evidence}")
+ print(f" log_10_bayes_factor={res.log_noise_evidence}")
def drop_to_ipython(results_list):
for result in results_list:
message = "Opened IPython terminal for result {}".format(result.label)
- message += ("\nRunning with bilby={},\nResult generated with bilby={}"
- .format(bilby.__version__, result.version))
+ message += "\nRunning with bilby={},\nResult generated with bilby={}".format(
+ bilby.__version__, result.version
+ )
message += "\nBilby result loaded as `result`"
import IPython
+
IPython.embed(header=message)
@@ -108,17 +161,61 @@ def print_matches(results_list, args):
for attr in r.__dict__:
if key in attr:
print_line = [
- " ", tcolors.KEY, attr, ":", tcolors.VALUE,
- str(getattr(r, attr)), tcolors.END]
+ " ",
+ tcolors.KEY,
+ attr,
+ ":",
+ tcolors.VALUE,
+ str(getattr(r, attr)),
+ tcolors.END,
+ ]
print(" ".join(print_line))
+def apply_max_samples(result, args):
+ if len(result.posterior) > args.max_samples:
+ result.posterior = result.posterior.sample(args.max_samples).sort_index()
+ return result
+
+
+def apply_lightweight(result, args):
+ strip_keys = [
+ "_nested_samples",
+ "log_likelihood_evaluations",
+ "log_prior_evaluations"
+ ]
+ for key in strip_keys:
+ setattr(result, key, None)
+ return result
+
+
+def save(result, args):
+ if args.max_samples is not None:
+ result = apply_max_samples(result, args)
+ if args.lightweight:
+ result = apply_lightweight(result, args)
+ result.save_to_file(gzip=args.gzip, extension=args.extension, outdir=args.outdir)
+
+
def main():
args = setup_command_line_args()
results_list = read_in_results(args.results)
- if args.convert:
- for r in results_list:
- r.save_to_file(extension=args.convert, outdir=args.outdir)
+
+ if args.save:
+ for res in results_list:
+ if args.label is not None:
+ res.label = args.label
+ save(res, args)
+
+ if args.merge:
+ result = results_list.combine()
+ if args.label is not None:
+ result.label = args.label
+ if args.outdir is not None:
+ result.outdir = args.outdir
+
+ save(res, args)
+
if args.keys is not None:
print_matches(results_list, args)
if args.call is not None:
@@ -129,12 +226,3 @@ def main():
print_bayes_factors(results_list)
if args.ipython:
drop_to_ipython(results_list)
- if args.merge:
- result = results_list.combine()
- if args.label is not None:
- result.label = args.label
- if args.outdir is not None:
- result.outdir = args.outdir
-
- extension = args.extension
- result.save_to_file(gzip=args.gzip, extension=extension)