def pdf(
self,
x: ztyping.XTypeInput,
norm: ztyping.LimitsTypeInput = None,
*,
norm_range=None,
) -> ztyping.XType:
"""Probability density function, normalized over `norm`.
Args:
norm ():
x: `float` or `double` `Tensor`.
norm: :py:class:`~zfit.Space` to normalize over
Returns:
:py:class:`tf.Tensor` of type `self.dtype`.
"""
assert norm_range is None
norm = self._check_input_norm(norm, none_is_error=True)
with self._convert_sort_x(x) as x:
value = self._single_hook_pdf(x=x, norm=norm)
if run.numeric_checks:
z.check_numerics(
value,
message="Check if pdf output contains any NaNs of Infs")
return znp.asarray(z.to_real(value))
def pdf(self,
x: ztyping.XTypeInput,
norm_range: ztyping.LimitsTypeInput = None,
name: str = "model") -> ztyping.XType:
"""Probability density function, normalized over `norm_range`.
Args:
x (numerical): `float` or `double` `Tensor`.
norm_range (tuple, :py:class:`~zfit.Space`): :py:class:`~zfit.Space` to normalize over
name (str): Prepended to names of ops created by this function.
Returns:
:py:class:`tf.Tensor` of type `self.dtype`.
"""
norm_range = self._check_input_norm_range(norm_range,
caller_name=name,
none_is_error=True)
with self._convert_sort_x(x) as x:
value = self._single_hook_pdf(x=x,
norm_range=norm_range,
name=name)
if run.numeric_checks:
assert_op = z.check_numerics(
value,
message="Check if pdf output contains any NaNs of Infs")
assert_op = [assert_op]
else:
assert_op = []
with tf.control_dependencies(assert_op):
return z.to_real(value)
def pdf(self, x: ztyping.XTypeInput, norm_range: ztyping.LimitsTypeInput = None) -> ztyping.XType:
"""Probability density function, normalized over `norm_range`.
Args:
x (numerical): `float` or `double` `Tensor`.
norm_range (tuple, :py:class:`~zfit.Space`): :py:class:`~zfit.Space` to normalize over
Returns:
:py:class:`tf.Tensor` of type `self.dtype`.
"""
norm_range = self._check_input_norm_range(norm_range, none_is_error=True)
with self._convert_sort_x(x) as x:
value = self._single_hook_pdf(x=x, norm_range=norm_range)
if run.numeric_checks:
z.check_numerics(value, message="Check if pdf output contains any NaNs of Infs")
return z.to_real(value)