Add PyMC3 sampler

I have started an attempt to add PyMC3 as a sampler option.

At the moment this can be used with the Uniform prior, for which I have added a new pymc3 method, and the GaussianLikelihood for which I have added a pymc3_likelihood method. I can convert the other prior classes to also have pymc3 methods too.

At the moment I've just got PyMC3 to run with the default NUTS sampler, but can change the _run_external_sampler method to take in other allowed sampler keyword args.

I've tested this with a linear regression example and it works!

tupak/core/likelihood.py

@@ -126,10 +126,10 @@ 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))