def NFWProfile(pos, concentration, Rvir, sample_shape, **kwargs): pos = ed.as_random_variable(tfd.TransformedDistribution(distribution=tfd.VonMisesFisher(tf.one_hot(tf.zeros_like(concentration, dtype=tf.int32),3), 0), bijector=tfb.AffineScalar(shift=pos, scale=tf.expand_dims(ed.as_random_variable(NFW(concentration, Rvir, name='radius'), sample_shape=sample_shape), axis=-1)), name='position'), sample_shape=sample_shape) return pos
def model_scoped(): return ed.as_random_variable(dist)
def model_wrapped(): return ed.as_random_variable(tfd.Normal(1., 0.1, name="x"))
import inspect from tensorflow_probability import edward2 from tensorflow_probability.python.edward2.generated_random_variables import * import distributions _globals = globals() for _name in sorted(dir(distributions)): _candidate = getattr(distributions, _name) if (inspect.isclass(_candidate) and issubclass(_candidate, distributions.Distribution) and _candidate.__module__ == 'distributions'): _globals[ _name] = lambda *params, _candidate=_candidate, **kwargs: edward2.as_random_variable( _candidate(*params, **kwargs)) del _candidate
def model_scoped(): return ed.as_random_variable(dist)
def model_wrapped(): return ed.as_random_variable(tfd.Normal(1., 0.1, name="x"))