class_docstr: Marginal transformation that transforms the target via an empirical CDF to
  a standard gaussian as described here: https://arxiv.org/abs/1910.03002.
  
  To be used in conjunction with a multivariate gaussian to from a copula.
  Note that this transformation is currently intended for multivariate
  targets only.
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docstr: Applies the empirical CDF forward transformation.
  
  Parameters
  ----------
  sorted_values
      Sorted target vector.
  values
      Values (real valued) that will be transformed to empirical CDF
      values.
  slopes
      Slopes of the piece-wise linear function.
  intercepts
      Intercepts of the piece-wise linear function.
  
  Returns
  -------
  quantiles
      Empirical CDF quantiles in [0, 1] interval with winsorized cutoff.
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code: def _empirical_cdf_forward_transform(
      self,
      sorted_values: np.ndarray,
      values: np.ndarray,
      slopes: np.ndarray,
      intercepts: np.ndarray,
  ) -> np.ndarray:
      """
      Applies the empirical CDF forward transformation.
  
      Parameters
      ----------
      sorted_values
          Sorted target vector.
      values
          Values (real valued) that will be transformed to empirical CDF
          values.
      slopes
          Slopes of the piece-wise linear function.
      intercepts
          Intercepts of the piece-wise linear function.
  
      Returns
      -------
      quantiles
          Empirical CDF quantiles in [0, 1] interval with winsorized cutoff.
      """
      m = sorted_values.shape[0]
      quantiles = self._forward_transform(
          sorted_values, values, slopes, intercepts
      )
  
      quantiles = np.clip(
          quantiles,
          self.winsorized_cutoff(m),
          1 - self.winsorized_cutoff(m),
      )
      return quantiles
  
imports: from typing import Callable, Iterator, List, Optional, Tuple, Type
  import numpy
  from toolz import valmap
  from gluonts.core.component import validated, tensor_to_numpy
  from gluonts.dataset.common import DataEntry
  from gluonts.exceptions import assert_data_error
  from ._base import FlatMapTransformation, MapTransformation, SimpleTransformation
label_desc: Use image node_id 5 for calling the CDFtoGaussianTransform obj's underlying member method code with example usage: obj._empirical_cdf_forward_transform(sorted_values, values, slopes, intercepts) and returns: quantiles