def logpdf(self, p, lognorm=None):
if lognorm is None:<EOL><INDENT>lognorm = self.log_norm<EOL><DEDENT>if hasattr(p, '<STR_LIT>'):<EOL><INDENT>if isinstance(p, _gvar.BufferDict):<EOL><INDENT>p = p.buf<EOL><DEDENT>else:<EOL><INDENT>p = _gvar.BufferDict(p).buf<EOL><DEDENT><DEDENT>else:<EOL><INDENT>p = numpy.asarray(p).reshape(-<NUM_LIT:1>)<EOL><DEDENT>return (<EOL>-<NUM_LIT:0.5> * (numpy.sum(self.chiv(p) ** <NUM_LIT:2>) - self.chi2)<EOL>- self.log_gnorm - self.log_norm<EOL>)<EOL>
Logarithm of the probability density function evaluated at ``p``.