From 3e0d13a2f3617db54b61a6875811bc969ce05261 Mon Sep 17 00:00:00 2001
From: Gregory Ashton <gregory.ashton@ligo.org>
Date: Wed, 12 Apr 2017 17:00:35 +0200
Subject: [PATCH] Removes sampler from the saved data pickle
No longer saves the emcee sampler itself to the pickle. This was done in
response to a bug encountered by David Keitel in which while dumping the
pickle an error was raised. Fixes #1
---
pyfstat/mcmc_based_searches.py | 43 +++++++++++++---------------------
1 file changed, 16 insertions(+), 27 deletions(-)
diff --git a/pyfstat/mcmc_based_searches.py b/pyfstat/mcmc_based_searches.py
index 7ee3a98..74f0d73 100644
--- a/pyfstat/mcmc_based_searches.py
+++ b/pyfstat/mcmc_based_searches.py
@@ -350,7 +350,6 @@ class MCMCSearch(core.BaseSearchClass):
logging.warning('Using saved data from {}'.format(
self.pickle_path))
d = self.get_saved_data_dictionary()
- self.sampler = d['sampler']
self.samples = d['samples']
self.lnprobs = d['lnprobs']
self.lnlikes = d['lnlikes']
@@ -414,11 +413,12 @@ class MCMCSearch(core.BaseSearchClass):
samples = sampler.chain[0, :, nburn:, :].reshape((-1, self.ndim))
lnprobs = sampler.lnprobability[0, :, nburn:].reshape((-1))
lnlikes = sampler.lnlikelihood[0, :, nburn:].reshape((-1))
- self.sampler = sampler
+ all_lnlikelihood = sampler.lnlikelihood
self.samples = samples
self.lnprobs = lnprobs
self.lnlikes = lnlikes
- self._save_data(sampler, samples, lnprobs, lnlikes)
+ self.all_lnlikelihood = all_lnlikelihood
+ self._save_data(sampler, samples, lnprobs, lnlikes, all_lnlikelihood)
def _get_rescale_multiplier_for_key(self, key):
""" Get the rescale multiplier from the rescale_dictionary
@@ -996,12 +996,12 @@ class MCMCSearch(core.BaseSearchClass):
BSGL=self.BSGL)
return d
- def _save_data(self, sampler, samples, lnprobs, lnlikes):
+ def _save_data(self, sampler, samples, lnprobs, lnlikes, all_lnlikelihood):
d = self._get_data_dictionary_to_save()
- d['sampler'] = sampler
d['samples'] = samples
d['lnprobs'] = lnprobs
d['lnlikes'] = lnlikes
+ d['all_lnlikelihood'] = all_lnlikelihood
if os.path.isfile(self.pickle_path):
logging.info('Saving backup of {} as {}.old'.format(
@@ -1036,7 +1036,6 @@ class MCMCSearch(core.BaseSearchClass):
new_d = self._get_data_dictionary_to_save().copy()
old_d.pop('samples')
- old_d.pop('sampler')
old_d.pop('lnprobs')
old_d.pop('lnlikes')
@@ -1273,21 +1272,10 @@ class MCMCSearch(core.BaseSearchClass):
print('p-value = {}'.format(p_val))
return p_val
- def get_evidence(self):
- """ Get the log10 evidence and error estimate """
- fburnin = float(self.nsteps[-2])/np.sum(self.nsteps[-2:])
- lnev, lnev_err = self.sampler.thermodynamic_integration_log_evidence(
- fburnin=fburnin)
-
- log10evidence = lnev/np.log(10)
- log10evidence_err = lnev_err/np.log(10)
- return log10evidence, log10evidence_err
-
- def _compute_evidence_long(self):
+ def compute_evidence(self):
""" Computes the evidence/marginal likelihood for the model """
betas = self.betas
- alllnlikes = self.sampler.lnlikelihood[:, :, self.nsteps[-2]:]
- mean_lnlikes = np.mean(np.mean(alllnlikes, axis=1), axis=1)
+ mean_lnlikes = np.mean(np.mean(self.all_lnlikelihood, axis=1), axis=1)
mean_lnlikes = mean_lnlikes[::-1]
betas = betas[::-1]
@@ -1300,11 +1288,12 @@ class MCMCSearch(core.BaseSearchClass):
idxs = np.isinf(mean_lnlikes)
mean_lnlikes = mean_lnlikes[~idxs]
betas = betas[~idxs]
- log10evidence = np.trapz(mean_lnlikes, betas)/np.log(10)
- z1 = np.trapz(mean_lnlikes, betas)
- z2 = np.trapz(mean_lnlikes[::-1][::2][::-1],
- betas[::-1][::2][::-1])
- log10evidence_err = np.abs(z1 - z2) / np.log(10)
+
+ log10evidence = np.trapz(mean_lnlikes, betas)/np.log(10)
+ z1 = np.trapz(mean_lnlikes, betas)
+ z2 = np.trapz(mean_lnlikes[::-1][::2][::-1],
+ betas[::-1][::2][::-1])
+ log10evidence_err = np.abs(z1 - z2) / np.log(10)
ax1.semilogx(betas, mean_lnlikes, "-o")
ax1.set_xlabel(r"$\beta$")
@@ -1901,7 +1890,6 @@ class MCMCFollowUpSearch(MCMCSemiCoherentSearch):
logging.warning('Using saved data from {}'.format(
self.pickle_path))
d = self.get_saved_data_dictionary()
- self.sampler = d['sampler']
self.samples = d['samples']
self.lnprobs = d['lnprobs']
self.lnlikes = d['lnlikes']
@@ -1955,11 +1943,12 @@ class MCMCFollowUpSearch(MCMCSemiCoherentSearch):
samples = sampler.chain[0, :, nburn:, :].reshape((-1, self.ndim))
lnprobs = sampler.lnprobability[0, :, nburn:].reshape((-1))
lnlikes = sampler.lnlikelihood[0, :, nburn:].reshape((-1))
- self.sampler = sampler
+ all_lnlikelihood = sampler.lnlikelihood
self.samples = samples
self.lnprobs = lnprobs
self.lnlikes = lnlikes
- self._save_data(sampler, samples, lnprobs, lnlikes)
+ self.all_lnlikelihood = all_lnlikelihood
+ self._save_data(sampler, samples, lnprobs, lnlikes, all_lnlikelihood)
if create_plots:
try:
--
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