Clean up for core logging output

Adds a line to print the result and indicate where results are saved

tupak/core/prior.py

@@ -94,10 +94,10 @@ class PriorSet(dict):
                 continue
             elif isinstance(self[key], float) or isinstance(self[key], int):
                 self[key] = DeltaFunction(self[key])
-                logging.info(
+                logging.debug(
                     "{} converted to delta function prior.".format(key))
             else:
-                logging.info(
+                logging.debug(
                     "{} cannot be converted to delta function prior."
                     .format(key))
 
@@ -139,7 +139,7 @@ class PriorSet(dict):
             if isinstance(self[key], Prior):
                 samples[key] = self[key].sample(size=size)
             else:
-                logging.info('{} not a known prior.'.format(key))
+                logging.debug('{} not a known prior.'.format(key))
         return samples
 
     def prob(self, sample):
@@ -180,7 +180,7 @@ def create_default_prior(name, default_priors_file=None):
     """
 
     if default_priors_file is None:
-        logging.info(
+        logging.debug(
             "No prior file given.")
         prior = None
     else:
@@ -188,7 +188,7 @@ def create_default_prior(name, default_priors_file=None):
         if name in default_priors.keys():
             prior = default_priors[name]
         else:
-            logging.info(
+            logging.debug(
                 "No default prior found for variable {}.".format(name))
             prior = None
     return prior
@@ -579,7 +579,7 @@ class Interped(Prior):
 
     def __initialize_attributes(self):
         if np.trapz(self.yy, self.xx) != 1:
-            logging.info('Supplied PDF for {} is not normalised, normalising.'.format(self.name))
+            logging.debug('Supplied PDF for {} is not normalised, normalising.'.format(self.name))
         self.yy /= np.trapz(self.yy, self.xx)
         self.YY = cumtrapz(self.yy, self.xx, initial=0)
         # Need last element of cumulative distribution to be exactly one.

tupak/core/result.py

@@ -91,12 +91,12 @@ class Result(dict):
         if os.path.isdir(self.outdir) is False:
             os.makedirs(self.outdir)
         if os.path.isfile(file_name):
-            logging.info(
+            logging.debug(
                 'Renaming existing file {} to {}.old'.format(file_name,
                                                              file_name))
             os.rename(file_name, file_name + '.old')
 
-        logging.info("Saving result to {}".format(file_name))
+        logging.debug("Saving result to {}".format(file_name))
         try:
             deepdish.io.save(file_name, self.get_result_dictionary())
         except Exception as e:
@@ -183,7 +183,7 @@ class Result(dict):
 
         if save:
             filename = '{}/{}_corner.png'.format(self.outdir, self.label)
-            logging.info('Saving corner plot to {}'.format(filename))
+            logging.debug('Saving corner plot to {}'.format(filename))
             fig.savefig(filename, dpi=dpi)
 
         return fig

tupak/core/sampler.py

@@ -130,7 +130,7 @@ class Sampler(object):
 
         logging.info("Search parameters:")
         for key in self.__search_parameter_keys:
-            logging.info('  {} ~ {}'.format(key, self.priors[key]))
+            logging.info('  {} = {}'.format(key, self.priors[key]))
         for key in self.__fixed_parameter_keys:
             logging.info('  {} = {}'.format(key, self.priors[key].peak))
 
@@ -156,7 +156,8 @@ class Sampler(object):
             t1 = datetime.datetime.now()
             self.likelihood.log_likelihood()
             logging.info(
-                "Single likelihood eval. took {:.3e} s".format((datetime.datetime.now() - t1).total_seconds()))
+                "Single likelihood evaluation took {:.3e} s"
+                .format((datetime.datetime.now() - t1).total_seconds()))
         except TypeError as e:
             raise TypeError(
                 "Likelihood evaluation failed with message: \n'{}'\n"
@@ -212,9 +213,9 @@ class Sampler(object):
         """
         draw = np.array(list(self.priors.sample_subset(self.__search_parameter_keys).values()))
         if np.isinf(self.log_likelihood(draw)):
-            logging.info('Prior draw {} has inf likelihood'.format(draw))
+            logging.warning('Prior draw {} has inf likelihood'.format(draw))
         if np.isinf(self.log_prior(draw)):
-            logging.info('Prior draw {} has inf prior'.format(draw))
+            logging.warning('Prior draw {} has inf prior'.format(draw))
         return draw
 
     def _run_external_sampler(self):
@@ -396,7 +397,7 @@ class Dynesty(Sampler):
 
     def generate_trace_plots(self, dynesty_results):
         filename = '{}/{}_trace.png'.format(self.outdir, self.label)
-        logging.info("Writing trace plot to {}".format(filename))
+        logging.debug("Writing trace plot to {}".format(filename))
         from dynesty import plotting as dyplot
         fig, axes = dyplot.traceplot(dynesty_results,
                                      labels=self.result.parameter_labels)
@@ -504,7 +505,7 @@ class Ptemcee(Sampler):
 
         fig.tight_layout()
         filename = '{}/{}_walkers.png'.format(self.outdir, self.label)
-        logging.info('Saving walkers plot to {}'.format('filename'))
+        logging.debug('Saving walkers plot to {}'.format('filename'))
         fig.savefig(filename)
 
 
@@ -580,7 +581,7 @@ def run_sampler(likelihood, priors=None, label='label', outdir='outdir',
                                 **kwargs)
 
         if sampler.cached_result:
-            logging.info("Using cached result")
+            logging.warning("Using cached result")
             return sampler.cached_result
 
         start_time = datetime.datetime.now()
@@ -592,7 +593,6 @@ def run_sampler(likelihood, priors=None, label='label', outdir='outdir',
 
         end_time = datetime.datetime.now()
         result.sampling_time = (end_time - start_time).total_seconds()
-        logging.info('')
         logging.info('Sampling time: {}'.format(end_time - start_time))
 
         if sampler.use_ratio:
@@ -615,6 +615,8 @@ def run_sampler(likelihood, priors=None, label='label', outdir='outdir',
         result.save_to_file()
         if plot:
             result.plot_corner()
+        logging.info("Sampling finished, results saved to {}/".format(outdir))
+        logging.info("Summary of results:\n{}".format(result))
         return result
     else:
         raise ValueError(

tupak/core/utils.py

@@ -219,9 +219,10 @@ def setup_logger(outdir=None, label=None, log_level=None):
         file_handler.setLevel(LEVEL)
         logger.addHandler(file_handler)
 
-    version_file = os.path.join(os.path.dirname(os.path.dirname(__file__)), '.version')
+    version_file = os.path.join(
+        os.path.dirname(os.path.dirname(__file__)), '.version')
     with open(version_file, 'r') as f:
-        version = f.readline()
+        version = f.readline().rstrip()
     logging.info('Running tupak version: {}'.format(version))
 
 
@@ -300,8 +301,8 @@ command_line_args = set_up_command_line_arguments()
 if 'DISPLAY' in os.environ:
     pass
 else:
-    logging.info('No $DISPLAY environment variable found, so importing \
-                  matplotlib.pyplot with non-interactive "Agg" backend.')
+    logging.debug('No $DISPLAY environment variable found, so importing \
+                   matplotlib.pyplot with non-interactive "Agg" backend.')
     import matplotlib
     matplotlib.use('Agg')