diff --git a/examples/injection_examples/create_your_own_source_model.py b/examples/injection_examples/create_your_own_source_model.py
index ad66821e101de9e7df2f3a5c02acbdf3ea7fad83..a595695044d828ef7205ee13fc72eafdec043e29 100644
--- a/examples/injection_examples/create_your_own_source_model.py
+++ b/examples/injection_examples/create_your_own_source_model.py
@@ -7,7 +7,6 @@ import tupak
 import numpy as np
 
 # First set up logging and some output directories and labels
-tupak.core.utils.setup_logger()
 outdir = 'outdir'
 label = 'create_your_own_source_model'
 sampling_frequency = 4096
diff --git a/examples/injection_examples/create_your_own_time_domain_source_model.py b/examples/injection_examples/create_your_own_time_domain_source_model.py
index 054ba5773f8b63eb643b4acb8580fb5822f4d39a..f89bb0f77c3ccbec9a9e39bd54bb23232ad7af06 100644
--- a/examples/injection_examples/create_your_own_time_domain_source_model.py
+++ b/examples/injection_examples/create_your_own_time_domain_source_model.py
@@ -8,7 +8,6 @@ and then recovered.
 import tupak
 import numpy as np
 
-tupak.core.utils.setup_logger()
 
 
 # define the time-domain model
diff --git a/examples/injection_examples/how_to_specify_the_prior.py b/examples/injection_examples/how_to_specify_the_prior.py
index 08ffbc664d069cbdef949a5e3a23ca2c808f7243..d33fc753486bd01f8fbef8968a2cf407da54ecea 100644
--- a/examples/injection_examples/how_to_specify_the_prior.py
+++ b/examples/injection_examples/how_to_specify_the_prior.py
@@ -8,7 +8,6 @@ import numpy as np
 
 import tupak.gw.prior
 
-tupak.core.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 9e9f328d8244bf7add54fcd47dc1070dbe2cf08d..6ada100981861f8cf52050c007d2dd71f51029a5 100644
--- a/examples/injection_examples/marginalized_likelihood.py
+++ b/examples/injection_examples/marginalized_likelihood.py
@@ -7,7 +7,6 @@ from __future__ import division, print_function
 import tupak
 import numpy as np
 
-tupak.core.utils.setup_logger()
 
 time_duration = 4.
 sampling_frequency = 2048.
diff --git a/examples/other_examples/gaussian_example.py b/examples/other_examples/gaussian_example.py
index 14f049287bd86219dd3ac7112413ef5c0743eaee..7b49f6098609dcc55ad3b7e2ecd40ea8901e17b7 100644
--- a/examples/other_examples/gaussian_example.py
+++ b/examples/other_examples/gaussian_example.py
@@ -8,7 +8,6 @@ import tupak
 import numpy as np
 
 # A few simple setup steps
-tupak.core.utils.setup_logger()
 label = 'gaussian_example'
 outdir = 'outdir'
 
@@ -47,10 +46,10 @@ class SimpleGaussianLikelihood(tupak.Likelihood):
 likelihood = SimpleGaussianLikelihood(data)
 priors = dict(mu=tupak.core.prior.Uniform(0, 5, 'mu'),
               sigma=tupak.core.prior.Uniform(0, 10, 'sigma'))
-priors['mu'] = 1
 
 # And run sampler
 result = tupak.run_sampler(
     likelihood=likelihood, priors=priors, sampler='dynesty', npoints=500,
     walks=10, outdir=outdir, label=label)
 result.plot_corner()
+print result.posterior.head()
diff --git a/examples/other_examples/hyper_parameter_example.py b/examples/other_examples/hyper_parameter_example.py
index 17dc87d7150bb9e2dd2103f568012626b1774e9b..9d06b22a2f7d868553c32d0c676e2e219503e41e 100644
--- a/examples/other_examples/hyper_parameter_example.py
+++ b/examples/other_examples/hyper_parameter_example.py
@@ -8,7 +8,6 @@ import numpy as np
 import inspect
 import matplotlib.pyplot as plt
 
-tupak.core.utils.setup_logger()
 outdir = 'outdir'
 
 
diff --git a/examples/other_examples/linear_regression.py b/examples/other_examples/linear_regression.py
index 9a601fe00fb50ce6a786c26c9ea43f892cdcd93e..6f812122186043340761a285af4c49fc12edb817 100644
--- a/examples/other_examples/linear_regression.py
+++ b/examples/other_examples/linear_regression.py
@@ -12,7 +12,6 @@ import matplotlib.pyplot as plt
 import inspect
 
 # A few simple setup steps
-tupak.core.utils.setup_logger()
 label = 'linear_regression'
 outdir = 'outdir'
 
diff --git a/examples/other_examples/linear_regression_unknown_noise.py b/examples/other_examples/linear_regression_unknown_noise.py
index ad7efd49664a384edd4a0e776d706e969c8d4002..6803493553f75fd812f68e2dd0cf032cf22fbb05 100644
--- a/examples/other_examples/linear_regression_unknown_noise.py
+++ b/examples/other_examples/linear_regression_unknown_noise.py
@@ -11,7 +11,6 @@ import numpy as np
 import matplotlib.pyplot as plt
 
 # A few simple setup steps
-tupak.core.utils.setup_logger()
 label = 'linear_regression_unknown_noise'
 outdir = 'outdir'