From 47980fefbf466798842e9ac4943e80669928e219 Mon Sep 17 00:00:00 2001
From: Colm Talbot <colm.talbot@ligo.org>
Date: Sat, 12 May 2018 12:46:21 +1000
Subject: [PATCH] update to use new parameter conversion to make a monolithic
posterior
---
tupak/result.py | 13 +++++++++++--
1 file changed, 11 insertions(+), 2 deletions(-)
diff --git a/tupak/result.py b/tupak/result.py
index c209aab96..347593a34 100644
--- a/tupak/result.py
+++ b/tupak/result.py
@@ -4,6 +4,7 @@ import numpy as np
import deepdish
from chainconsumer import ChainConsumer
import pandas as pd
+import tupak
class Result(dict):
@@ -159,13 +160,21 @@ class Result(dict):
for key in self.prior:
prior_file.write(self.prior[key])
- def samples_to_data_frame(self):
+ def samples_to_data_frame(self, waveform_generator=None, interferometers=None, priors=None):
"""
Convert array of samples to data frame.
- :return:
+ Parameters
+ ----------
+ waveform_generator: tupak.waveform_generator.WaveformGenerator, optional
+ If the waveform generator and interferometers are provided, the SNRs will be recorded.
+ interferometers: tupak.detector.Interferometer
+ If the waveform generator and interferometers are provided, the SNRs will be recorded.
+ priors: dict
+ Dictionary of prior object, used to fill in delta function priors.
"""
data_frame = pd.DataFrame(self.samples, columns=self.search_parameter_keys)
+ tupak.conversion.generate_all_bbh_parameters(data_frame, waveform_generator, interferometers, priors)
self.posterior = data_frame
for key in self.fixed_parameter_keys:
self.posterior[key] = self.prior[key].sample(len(self.posterior))
--
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