Resolve "Introduce conditional prior sets"

Closes #270 (closed)

PP test show that the new capabilities do not interfere with the results we are getting so far. This test is done without any conditional priors, it just shows that everything still works as expected.

https://ldas-jobs.ligo.caltech.edu/~moritz.huebner/conditional_prior_pp/outdir_pp_test_4s/pp.png

bilby/core/prior.py

@@ -501,9 +501,10 @@ class ConditionalPriorDict(PriorDict):
         self._rescale_indexes = []
         self._least_recently_rescaled_keys = []
         super(ConditionalPriorDict, self).__init__(dictionary=dictionary, filename=filename)
+        self.resolved = False
         self._resolve_conditions()
 
-    def _resolve_conditions(self):
+    def _resolve_conditions(self, disable_log=False):
         """ Resolves how variables depend on each other and automatically sorts them into the right order """
         conditioned_keys_unsorted = [key for key in self.keys() if hasattr(self[key], 'condition_func')]
         self._unconditional_keys = [key for key in self.keys() if not hasattr(self[key], 'condition_func')]
@@ -518,9 +519,12 @@ class ConditionalPriorDict(PriorDict):
 
         self._sorted_keys = self._unconditional_keys.copy()
         self._sorted_keys.extend(self.conditional_keys)
+        self.resolved = True
 
         if len(conditioned_keys_unsorted) != 0:
-            raise IllegalConditionsException('This set contains unresolvable conditions')
+            self.resolved = False
+            if not disable_log:
+                logger.warning('This set contains unresolvable conditions')
 
     def _check_conditions_resolved(self, key, sampled_keys):
         """ Checks if all required variables have already been sampled so we can sample this key """
@@ -532,14 +536,26 @@ class ConditionalPriorDict(PriorDict):
 
     def sample_subset(self, keys=iter([]), size=None):
         self.convert_floats_to_delta_functions()
-        sorted_keys = self.get_subset_sorted_keys(keys)
+        subset_dict = ConditionalPriorDict({key: self[key] for key in keys})
+        if not subset_dict.resolved:
+            raise IllegalConditionsException("The current set of priors contains unresolveable conditions.")
         res = dict()
-        for key in sorted_keys:
-            res[key] = self[key].sample(size=size, **self._get_required_variables(key))
+        for key in subset_dict.sorted_keys:
+            res[key] = subset_dict[key].sample(size=size, **subset_dict.get_required_variables(key))
         return res
 
-    def _get_required_variables(self, key):
-        """ Returns the required variables to sample a given conditional key."""
+    def get_required_variables(self, key):
+        """ Returns the required variables to sample a given conditional key.
+
+        Parameters
+        ----------
+        key : str
+            Name of the key that we want to know the required variables for
+
+        Returns
+        ----------
+        dict: key/value pairs of the required variables
+        """
         return {k: self[k].least_recently_sampled for k in getattr(self[key], 'required_variables', [])}
 
     def prob(self, sample, **kwargs):
@@ -557,9 +573,10 @@ class ConditionalPriorDict(PriorDict):
         float: Joint probability of all individual sample probabilities
 
         """
+        self._check_resolved()
         for key, value in sample.items():
             self[key].least_recently_sampled = value
-        res = [self[key].prob(sample[key], **self._get_required_variables(key)) for key in sample]
+        res = [self[key].prob(sample[key], **self.get_required_variables(key)) for key in sample]
         return np.product(res, **kwargs)
 
     def ln_prob(self, sample, axis=None):
@@ -577,9 +594,10 @@ class ConditionalPriorDict(PriorDict):
         float: Joint log probability of all the individual sample probabilities
 
         """
+        self._check_resolved()
         for key, value in sample.items():
             self[key].least_recently_sampled = value
-        res = [self[key].ln_prob(sample[key], **self._get_required_variables(key)) for key in sample]
+        res = [self[key].ln_prob(sample[key], **self.get_required_variables(key)) for key in sample]
         return np.sum(res, axis=axis)
 
     def rescale(self, keys, theta):
@@ -596,8 +614,9 @@ class ConditionalPriorDict(PriorDict):
         -------
         list: List of floats containing the rescaled sample
         """
-        result = OrderedDict(dict())
+        self._check_resolved()
         self._update_rescale_keys(keys)
+        result = OrderedDict(dict())
         for key, index in zip(self._rescale_keys, self._rescale_indexes):
             required_variables = {k: result[k] for k in getattr(self[key], 'required_variables', [])}
             result[key] = self[key].rescale(theta[index], **required_variables)
@@ -614,10 +633,9 @@ class ConditionalPriorDict(PriorDict):
         self._rescale_keys = np.append(unconditional_keys, conditional_keys)
         self._rescale_indexes = np.append(unconditional_idxs, conditional_idxs)
 
-    def get_subset_sorted_keys(self, subset_keys):
-        subset_unconditional_keys = [key for key in self.unconditional_keys if key in subset_keys]
-        subset_conditional_keys = [key for key in self.conditional_keys if key in subset_keys]
-        return subset_unconditional_keys + subset_conditional_keys
+    def _check_resolved(self):
+        if not self.resolved:
+            raise IllegalConditionsException("The current set of priors contains unresolveable conditions.")
 
     @property
     def conditional_keys(self):
@@ -633,7 +651,7 @@ class ConditionalPriorDict(PriorDict):
 
     def __setitem__(self, key, value):
         super(ConditionalPriorDict, self).__setitem__(key, value)
-        self._resolve_conditions()
+        self._resolve_conditions(disable_log=True)
 
 
 def create_default_prior(name, default_priors_file=None):
@@ -3465,7 +3483,7 @@ def conditional_prior_factory(prior_class):
     return ConditionalPrior
 
 
-ConditionalPrior = conditional_prior_factory(Prior)  # Only for testing purposes
+ConditionalBasePrior = conditional_prior_factory(Prior)  # Only for testing purposes
 ConditionalUniform = conditional_prior_factory(Uniform)
 ConditionalDeltaFunction = conditional_prior_factory(DeltaFunction)
 ConditionalPowerLaw = conditional_prior_factory(PowerLaw)
@@ -3484,7 +3502,8 @@ ConditionalLogistic = conditional_prior_factory(Logistic)
 ConditionalCauchy = conditional_prior_factory(Cauchy)
 ConditionalGamma = conditional_prior_factory(Gamma)
 ConditionalChiSquared = conditional_prior_factory(ChiSquared)
-ConditionalConditionalInterped = conditional_prior_factory(Interped)
+ConditionalFermiDirac = conditional_prior_factory(FermiDirac)
+ConditionalInterped = conditional_prior_factory(Interped)
 
 
 class PriorException(Exception):