code: def circ_corrcl(x, y):
      """Correlation coefficient between one circular and one linear variable
      random variables.
  
      Parameters
      ----------
      x : 1-D array_like
          First circular variable (expressed in radians).
          The range of ``x`` must be either :math:`[0, 2\\pi]` or
          :math:`[-\\pi, \\pi]`. If ``angles`` is not
          expressed in radians (e.g. degrees or 24-hours), please use the
          :py:func:`pingouin.convert_angles` function prior to using the present
          function.
      y : 1-D array_like
          Second circular variable (linear)
  
      Returns
      -------
      r : float
          Correlation coefficient
      pval : float
          Uncorrected p-value
  
      Notes
      -----
      Please note that NaN are automatically removed from datasets.
  
      Examples
      --------
      Compute the r and p-value between one circular and one linear variables.
  
      >>> from pingouin import circ_corrcl
      >>> x = [0.785, 1.570, 3.141, 0.839, 5.934]
      >>> y = [1.593, 1.291, -0.248, -2.892, 0.102]
      >>> r, pval = circ_corrcl(x, y)
      >>> print(round(r, 3), round(pval, 3))
      0.109 0.971
      """
      from scipy.stats import pearsonr, chi2
  
      x = np.asarray(x)
      y = np.asarray(y)
      assert x.size == y.size, "x and y must have the same length."
  
      # Remove NA
      x, y = remove_na(x, y, paired=True)
      n = x.size
  
      # Compute correlation coefficent for sin and cos independently
      rxs = pearsonr(y, np.sin(x))[0]
      rxc = pearsonr(y, np.cos(x))[0]
      rcs = pearsonr(np.sin(x), np.cos(x))[0]
  
      # Compute angular-linear correlation (equ. 27.47)
      r = np.sqrt(
          (rxc**2 + rxs**2 - 2 * rxc * rxs * rcs) / (1 - rcs**2)
      )
  
      # Compute p-value
      pval = chi2.sf(n * r**2, 2)
      return r, pval
  
file_path: pingouin/pingouin/circular.py
imports: import numpy
  from scipy.stats import norm
  from .utils import remove_na
label_desc: Use image node_id 7 for calling a global function with example usage: circ_corrcl(x, y) and returns: r,  pval