docstr: ivy.Container static method variant of ivy.modf. This method simply
  wraps the function, and so the docstring for ivy.modf also applies to
  this method with minimal changes.
  
  Parameters
  ----------
  x
      The container whose arrays should be split into
      the fractional and integral parts.
  key_chains
      The key-chains to apply or not apply the method to. Default is ``None``.
  to_apply
      If True, the method will be applied to key_chains, otherwise key_chains
      will be skipped. Default is ``True``.
  prune_unapplied
      Whether to prune key_chains for which the function was not applied.
      Default is ``False``.
  map_sequences
      Whether to also map method to sequences (lists, tuples).
      Default is ``False``.
  out
      optional output container, for writing the result to.
  
  Returns
  -------
  ret
      container including the fractional and integral parts of x.
  
  Examples
  --------
  With one :class:`ivy.Container` input:
  >>> x = ivy.Container(a=ivy.array([1.2, 2.7, 3.9]),
  >>> b = ivy.array([-1.5, 5.3, -10.7]))
  >>> ivy.Container.static_modf(x)
  {
      a: (ivy.array([0.2, 0.7, 0.9]), ivy.array([1.0, 2.0, 3.0])),
      b: (ivy.array([-0.5, 0.3, -0.7]), ivy.array([-1.0, 5.0, -10.0]))
  }
code: def static_modf(
      x: Union[ivy.Array, ivy.NativeArray, ivy.Container],
      /,
      *,
      key_chains: Optional[
          Union[List[str], Dict[str, str], ivy.Container]
      ] = None,
      to_apply: Union[bool, ivy.Container] = True,
      prune_unapplied: Union[bool, ivy.Container] = False,
      map_sequences: Union[bool, ivy.Container] = False,
      out: Optional[ivy.Container] = None,
  ) -> ivy.Container:
      """ivy.Container static method variant of ivy.modf. This method simply
      wraps the function, and so the docstring for ivy.modf also applies to
      this method with minimal changes.
  
      Parameters
      ----------
      x
          The container whose arrays should be split into
          the fractional and integral parts.
      key_chains
          The key-chains to apply or not apply the method to. Default is ``None``.
      to_apply
          If True, the method will be applied to key_chains, otherwise key_chains
          will be skipped. Default is ``True``.
      prune_unapplied
          Whether to prune key_chains for which the function was not applied.
          Default is ``False``.
      map_sequences
          Whether to also map method to sequences (lists, tuples).
          Default is ``False``.
      out
          optional output container, for writing the result to.
  
      Returns
      -------
      ret
          container including the fractional and integral parts of x.
  
      Examples
      --------
      With one :class:`ivy.Container` input:
      >>> x = ivy.Container(a=ivy.array([1.2, 2.7, 3.9]),
      >>> b = ivy.array([-1.5, 5.3, -10.7]))
      >>> ivy.Container.static_modf(x)
      {
          a: (ivy.array([0.2, 0.7, 0.9]), ivy.array([1.0, 2.0, 3.0])),
          b: (ivy.array([-0.5, 0.3, -0.7]), ivy.array([-1.0, 5.0, -10.0]))
      }
      """
      return ContainerBase.cont_multi_map_in_function(
          "modf",
          x,
          key_chains=key_chains,
          to_apply=to_apply,
          prune_unapplied=prune_unapplied,
          map_sequences=map_sequences,
          out=out,
      )
  
imports: from typing import Optional, Union, List, Dict, Tuple, Sequence
  from numbers import Number
  import ivy
  from ivy.data_classes.container.base import ContainerBase
label_desc: Use image node_id 49 for calling the _ContainerWithElementWiseExperimental obj's underlying member method code with example usage: obj.static_modf() and returns: ContainerBase