Handle priors as part of the result object and several other minor fixes

CHANGELOG.md

@@ -25,6 +25,7 @@ Changes currently on master, but not under a tag.
 - Fix interpretation of kwargs for dynesty
 - PowerSpectralDensity structure modified
 - Fixed bug in get_open_data 
+- .prior files are no longer created. The prior is stored in the result object.
 
 ### Removed
 - Removes the "--detectors" command line argument (not a general CLI requirement)

tupak/core/prior.py

@@ -7,6 +7,7 @@ from scipy.special import erf, erfinv
 import scipy.stats
 import os
 from collections import OrderedDict
+from future.utils import iteritems
 
 from tupak.core.utils import logger
 from tupak.core import utils
@@ -26,17 +27,17 @@ class PriorSet(OrderedDict):
         """
         OrderedDict.__init__(self)
         if isinstance(dictionary, dict):
-            self.update(dictionary)
+            self.from_dictionary(dictionary)
         elif type(dictionary) is str:
             logger.debug('Argument "dictionary" is a string.' +
                          ' Assuming it is intended as a file name.')
-            self.read_in_file(dictionary)
+            self.from_file(dictionary)
         elif type(filename) is str:
-            self.read_in_file(filename)
+            self.from_file(filename)
         elif dictionary is not None:
-            raise ValueError("PriorSet input dictionay not understood")
+            raise ValueError("PriorSet input dictionary not understood")
 
-    def write_to_file(self, outdir, label):
+    def to_file(self, outdir, label):
         """ Write the prior distribution to file.
 
         Parameters
@@ -55,7 +56,7 @@ class PriorSet(OrderedDict):
                 outfile.write(
                     "{} = {}\n".format(key, self[key]))
 
-    def read_in_file(self, filename):
+    def from_file(self, filename):
         """ Reads in a prior from a file specification
 
         Parameters
@@ -75,6 +76,20 @@ class PriorSet(OrderedDict):
                 prior[key] = eval(val)
         self.update(prior)
 
+    def from_dictionary(self, dictionary):
+        for key, val in iteritems(dictionary):
+            if isinstance(val, str):
+                try:
+                    prior = eval(val)
+                    if isinstance(prior, Prior):
+                        val = prior
+                except (NameError, SyntaxError, TypeError):
+                    logger.debug(
+                        "Failed to load dictionary value {} correctlty"
+                        .format(key))
+                    pass
+            self[key] = val
+
     def convert_floats_to_delta_functions(self):
         """ Convert all float parameters to delta functions """
         for key in self:

tupak/core/result.py

@@ -10,7 +10,7 @@ from collections import OrderedDict
 
 from tupak.core import utils
 from tupak.core.utils import logger
-from tupak.core.prior import DeltaFunction
+from tupak.core.prior import PriorSet, DeltaFunction
 
 
 def result_file_name(outdir, label):
@@ -70,12 +70,19 @@ class Result(dict):
             A dictionary containing values to be set in this instance
         """
 
+        # Set some defaults
+        self.outdir = '.'
+        self.label = 'no_name'
+
         dict.__init__(self)
         if type(dictionary) is dict:
             for key in dictionary:
                 val = self._standardise_a_string(dictionary[key])
                 setattr(self, key, val)
 
+        if getattr(self, 'priors', None) is not None:
+            self.priors = PriorSet(self.priors)
+
     def __add__(self, other):
         matches = ['sampler', 'search_parameter_keys']
         for match in matches:
@@ -171,8 +178,14 @@ class Result(dict):
             os.rename(file_name, file_name + '.old')
 
         logger.debug("Saving result to {}".format(file_name))
+
+        # Convert the prior to a string representation for saving on disk
+        dictionary = dict(self)
+        if dictionary.get('priors', False):
+            dictionary['priors'] = {key: str(self.priors[key]) for key in self.priors}
+
         try:
-            deepdish.io.save(file_name, dict(self))
+            deepdish.io.save(file_name, dictionary)
         except Exception as e:
             logger.error("\n\n Saving the data has failed with the "
                          "following message:\n {} \n\n".format(e))
@@ -270,8 +283,8 @@ class Result(dict):
         string = r"${{{0}}}_{{-{1}}}^{{+{2}}}$"
         return string.format(fmt(median), fmt(lower), fmt(upper))
 
-    def plot_corner(self, parameters=None, priors=None, titles=True, save=True,
-                    filename=None, dpi=300, **kwargs):
+    def plot_corner(self, parameters=None, priors=False, titles=True,
+                    save=True, filename=None, dpi=300, **kwargs):
         """ Plot a corner-plot using corner
 
         See https://corner.readthedocs.io/en/latest/ for a detailed API.
@@ -280,9 +293,10 @@ class Result(dict):
         ----------
         parameters: list, optional
             If given, a list of the parameter names to include
-        priors: tupak.core.prior.PriorSet
-            If given, add the prior probability density functions to the
-            one-dimensional marginal distributions
+        priors: {bool (False), tupak.core.prior.PriorSet}
+            If true, add the stored prior probability density functions to the
+            one-dimensional marginal distributions. If instead a PriorSet
+            is provided, this will be plotted.
         titles: bool
             If true, add 1D titles of the median and (by default 1-sigma)
             error bars. To change the error bars, pass in the quantiles kwarg.
@@ -363,11 +377,17 @@ class Result(dict):
                         **kwargs['title_kwargs'])
 
         #  Add priors to the 1D plots
-        if priors is not None:
+        if priors is True:
+            priors = getattr(self, 'priors', False)
+        if isinstance(priors, dict):
             for i, par in enumerate(parameters):
                 ax = axes[i + i * len(parameters)]
                 theta = np.linspace(ax.get_xlim()[0], ax.get_xlim()[1], 300)
                 ax.plot(theta, priors[par].prob(theta), color='C2')
+        elif priors in [False, None]:
+            pass
+        else:
+            raise ValueError('Input priors={} not understood'.format(priors))
 
         if save:
             if filename is None:

tupak/core/sampler/__init__.py

@@ -108,9 +108,6 @@ def run_sampler(likelihood, priors=None, label='label', outdir='outdir',
 
     priors.fill_priors(likelihood, default_priors_file=default_priors_file)
 
-    if save:
-        priors.write_to_file(outdir, label)
-
     if isinstance(sampler, Sampler):
         pass
     elif isinstance(sampler, str):
@@ -148,6 +145,8 @@ def run_sampler(likelihood, priors=None, label='label', outdir='outdir',
     if type(meta_data) == dict:
         result.update(meta_data)
 
+    result.priors = priors
+
     end_time = datetime.datetime.now()
     result.sampling_time = (end_time - start_time).total_seconds()
     logger.info('Sampling time: {}'.format(end_time - start_time))