code: def fit_params_to_1d_data(logX):
      
      m_max = logX.shape[0]
      p_max = logX.shape[1]
      params = np.zeros((m_max, p_max, 3)) 
      for m_ in range(m_max):
          for p_ in range(p_max):
              params[m_,p_] = skewnorm.fit(logX[m_,p_])
      
      return params
docs: Fit skewed normal distributions to 1-D capactity data, 
      and return the distribution parameters.
  
      Args
      ----
      logX:
          Logarithm of one-dimensional capacity data, 
          indexed by module and phase resolution index