class_docstr: Multiple proximal operator. This allows to apply sequentially a list
  of proximal operators. This is convenient when one wants to apply different
  proximal operators on different parts of a vector.
  
  Parameters
  ----------
  proxs : `tuple` of `Prox`
      A tuple of prox operators to be applied successively.
  
  Attributes
  ----------
  dtype : `{'float64', 'float32'}`
      Type of the arrays used.
docstr: Returns the value of the penalization at ``coeffs``.
  This returns the sum of the values of each prox called on the same
  coeffs.
  
  Parameters
  ----------
  coeffs : `numpy.ndarray`, shape=(n_coeffs,)
      The value of the penalization is computed at this point
  
  Returns
  -------
  output : `float`
      Value of the penalization at ``coeffs``
code: def value(self, coeffs: np.ndarray):
      """
      Returns the value of the penalization at ``coeffs``.
      This returns the sum of the values of each prox called on the same
      coeffs.
  
      Parameters
      ----------
      coeffs : `numpy.ndarray`, shape=(n_coeffs,)
          The value of the penalization is computed at this point
  
      Returns
      -------
      output : `float`
          Value of the penalization at ``coeffs``
      """
      return self._prox.value(coeffs)
  
file_path: tick/tick/prox/prox_multi.py
imports: import numpy
  from .base import Prox
  from .build.prox import ProxMultiDouble
  from .build.prox import ProxMultiFloat
  from tick.prox import ProxZero
label_desc: Use image node_id 3 for calling the ProxMulti obj's underlying member method code with example usage: obj.value(coeffs) and returns: self