code: def independence_match(X, Y, Z, independencies, **kwargs):
      """
      Checks if `X \u27C2 Y | Z` is in `independencies`. This method is implemented to
      have an uniform API when the independencies are provided instead of data.
  
      Parameters
      ----------
      X: str
          The first variable for testing the independence condition X \u27C2 Y | Z
  
      Y: str
          The second variable for testing the independence condition X \u27C2 Y | Z
  
      Z: list/array-like
          A list of conditional variable for testing the condition X \u27C2 Y | Z
  
      data: pandas.DataFrame The dataset in which to test the indepenedence condition.
  
      Returns
      -------
      p-value: float (Fixed to 0 since it is always confident)
      """
      return IndependenceAssertion(X, Y, Z) in independencies
  
file_path: pgmpy/pgmpy/estimators/CITests.py
imports: import numpy
  import pandas
  from scipy import stats
  from pgmpy.independencies import IndependenceAssertion
  from pgmpy.global_vars import logger
label_desc: Use image node_id 1 for calling a global function with example usage: independence_match(X, Y, Z, independencies) and returns: unknown