code: def __new__(
      cls, base_factor, target, correlation_length, mask=NotSpecified
  ):
      if target.ndim == 2 and base_factor.mask is not target.mask:
          raise IncompatibleTerms(term_1=base_factor, term_2=target)
  
      return super(_RollingCorrelation, cls).__new__(
          cls,
          inputs=[base_factor, target],
          window_length=correlation_length,
          mask=mask,
      )
  
imports: from numpy import broadcast_arrays
  from scipy.stats import linregress, pearsonr, spearmanr
  from catalyst.errors import IncompatibleTerms
  from catalyst.pipeline.factors import CustomFactor
  from catalyst.pipeline.filters import SingleAsset
  from catalyst.pipeline.mixins import SingleInputMixin
  from catalyst.pipeline.sentinels import NotSpecified
  from catalyst.pipeline.term import AssetExists
  from catalyst.utils.input_validation import expect_bounded, expect_dtypes
  from catalyst.utils.numpy_utils import float64_dtype, int64_dtype
  from .technical import Returns
label_desc: Use image node_id 1 for calling the _RollingCorrelation obj's underlying member method code with example usage: obj.__new__(cls, base_factor, target, correlation_length, mask) and returns: super