Move setting of PyMC3 prior into Prior class

tupak/core/likelihood.py

@@ -127,10 +127,10 @@ class GaussianLikelihood(Likelihood):
         model_parameters = dict()
         for key in sampler.priors:
             if key == 'sigma' and self.sigma is None:
-                self.sigma = sampler.priors[key].pymc3(sampler)
+                self.sigma = sampler.priors[key].pymc3_prior(sampler)
             else:
                 if key in self.function_keys:
-                    model_parameters[key] = sampler.priors[key].pymc3(sampler)
+                    model_parameters[key] = sampler.priors[key].pymc3_prior(sampler)
                 else:
                     raise ValueError("Prior key '{}' is not a function key!".format(key))
 

tupak/core/prior.py

@@ -472,6 +472,23 @@ class Prior(object):
             label = self.name
         return label
 
+    def set_pymc3_prior(self, sampler, priortype, **kwargs):
+        from tupak.core.sampler import Sampler
+
+        if not isinstance(sampler, Sampler):
+            raise ValueError("'sampler' is not a Sampler class")
+
+        try:
+            samplername = sampler.external_sampler.__name__
+        except ValueError:
+            raise ValueError("Sampler's 'external_sampler' has not been initialised")
+
+        if samplername != 'pymc3':
+            raise ValueError("Only use this class method for PyMC3 sampler")
+        
+        if priortype in sampler.external_sampler.__dict__:
+            return sampler.external_sampler.__dict__[priortype](self.name, **kwargs)
+
 
 class DeltaFunction(Prior):
 
@@ -524,7 +541,7 @@ class DeltaFunction(Prior):
         else:
             return 0
 
-    def pymc3(self, sampler):
+    def pymc3_prior(self, sampler):
         # just return the value
         return self.peak
 
@@ -666,22 +683,13 @@ class Uniform(Prior):
         return scipy.stats.uniform.logpdf(val, loc=self.minimum,
                                           scale=self.maximum-self.minimum)
 
-    def pymc3(self, sampler):
-        from tupak.core.sampler import Sampler
+    def pymc3_prior(self, sampler):
+        priortype = 'Uniform'
+        priorargs = {}
+        priorargs['lower'] = self.minimum
+        priorargs['upper'] = self.maximum
 
-        if not isinstance(sampler, Sampler):
-            raise ValueError("'sampler' is not a Sampler class")
-
-        try:
-            samplername = sampler.external_sampler.__name__
-        except ValueError:
-            raise ValueError("Sampler's 'external_sampler' has not been initialised")
-
-        if samplername != 'pymc3':
-            raise ValueError("Only use this class method for PyMC3 sampler")
-        
-        return sampler.external_sampler.Uniform(self.name, lower=self.minimum,
-                                                upper=self.maximum)
+        return self.set_pymc3_prior(sampler, priortype, **priorargs)
 
 
 class LogUniform(PowerLaw):