def log_prior(self):
if self.priors.size == <NUM_LIT:0>:<EOL><INDENT>return <NUM_LIT:0.><EOL><DEDENT>x = self.param_array<EOL>log_p = reduce(lambda a, b: a + b, (p.lnpdf(x[ind]).sum() for p, ind in self.priors.items()), <NUM_LIT:0>)<EOL>log_j = <NUM_LIT:0.><EOL>priored_indexes = np.hstack([i for p, i in self.priors.items()])<EOL>for c,j in self.constraints.items():<EOL><INDENT>if not isinstance(c, Transformation):continue<EOL>for jj in j:<EOL><INDENT>if jj in priored_indexes:<EOL><INDENT>log_j += c.log_jacobian(x[jj])<EOL><DEDENT><DEDENT><DEDENT>return log_p + log_j<EOL>
evaluate the prior