class_docstr: Proximal operator of the L1 norm (soft-thresholding)
  
  Parameters
  ----------
  strength : `float`
      Level of L1 penalization
  
  range : `tuple` of two `int`, default=`None`
      Range on which the prox is applied. If `None` then the prox is
      applied on the whole vector
  
  positive : `bool`, default=`False`
      If True, apply L1 penalization together with a projection
      onto the set of vectors with non-negative entries
  
  Attributes
  ----------
  dtype : `{'float64', 'float32'}`
      Type of the arrays used.
code: def _call(self, coeffs: np.ndarray, step: object, out: np.ndarray):
      self._prox.call(coeffs, step, out)
  
file_path: tick/tick/prox/prox_l1.py
imports: import numpy
  from .base import Prox
  from .build.prox import ProxL1Double
  from .build.prox import ProxL1Float
label_desc: Use image node_id 2 for calling the ProxL1 obj's underlying member method code with example usage: obj._call(coeffs, step, out) without return types