code: def sidak(pvals, alpha=0.05):
      """P-values correction with Sidak method.
  
      Parameters
      ----------
      pvals : array_like
          Array of p-values of the individual tests.
      alpha : float
          Error rate (= alpha level).
  
      Returns
      -------
      reject : array, bool
          True if a hypothesis is rejected, False if not
      pval_corrected : array
          P-values adjusted for multiple hypothesis testing using the Sidak
          procedure.
  
      See also
      --------
      bonf, holm, fdr, multicomp
  
      Notes
      -----
      The Sidak adjusted p-values are defined as:
  
      .. math::
          \\widetilde {p}_{{(i)}}= 1 - (1 - p_{{(i)}})^{n}
  
      The Sidak correction is slightly more liberal than the Bonferroni
      correction.
  
      Note that NaN values are not taken into account in the p-values correction.
  
      References
      ----------
      - Šidák, Z. K. (1967). "Rectangular Confidence Regions for the Means of
        Multivariate Normal Distributions". Journal of the American Statistical
        Association. 62 (318): 626–633.
  
      - https://en.wikipedia.org/wiki/%C5%A0id%C3%A1k_correction
  
      Examples
      --------
      >>> import numpy as np
      >>> import pingouin as pg
      >>> pvals = [.50, .003, .32, .054, .0003]
      >>> reject, pvals_corr = pg.multicomp(pvals, method='sidak', alpha=.05)
      >>> print(reject, np.round(pvals_corr, 4))
      [False  True False False  True] [0.9688 0.0149 0.8546 0.2424 0.0015]
      """
      pvals = np.asarray(pvals)
      num_nan = np.isnan(pvals).sum()
      ntests = float(pvals.size) - num_nan
      pvals_corrected = 1 - np.power((1.0 - pvals), ntests)
      pvals_corrected = np.clip(pvals_corrected, None, 1)
      with np.errstate(invalid="ignore"):
          reject = np.less(pvals_corrected, alpha)
      return reject, pvals_corrected
  
imports: import numpy
  from pandas import Series
label_desc: Use image node_id 4 for calling a global function with example usage: sidak(pvals, alpha) and returns: reject,  pvals_corrected