code: def _fmt_probplot_axis(ax, dist, nobs):
      """
      Formats a theoretical quantile axis to display the corresponding
      probabilities on the quantiles' scale.
  
      Parameters
      ----------
      ax : AxesSubplot, optional
          The axis to be formatted
      nobs : scalar
          Number of observations in the sample
      dist : scipy.stats.distribution
          A scipy.stats distribution sufficiently specified to implement its
          ppf() method.
  
      Returns
      -------
      There is no return value. This operates on `ax` in place
      """
      _check_for(dist, "ppf")
      axis_probs = np.linspace(10, 90, 9, dtype=float)
      small = np.array([1.0, 2, 5])
      axis_probs = np.r_[small, axis_probs, 100 - small[::-1]]
      if nobs >= 50:
          axis_probs = np.r_[
              small / 10, axis_probs, 100 - small[::-1] / 10
          ]
      if nobs >= 500:
          axis_probs = np.r_[
              small / 100, axis_probs, 100 - small[::-1] / 100
          ]
      axis_probs /= 100.0
      axis_qntls = dist.ppf(axis_probs)
      ax.set_xticks(axis_qntls)
      ax.set_xticklabels(
          [str(lbl) for lbl in (axis_probs * 100)],
          rotation=45,
          rotation_mode="anchor",
          horizontalalignment="right",
          verticalalignment="center",
      )
      ax.set_xlim([axis_qntls.min(), axis_qntls.max()])
  
imports: from statsmodels.compat.python import lzip
  import numpy
  from scipy import stats
  from statsmodels.distributions import ECDF
  from statsmodels.regression.linear_model import OLS
  from statsmodels.tools.decorators import cache_readonly
  from statsmodels.tools.tools import add_constant
  from .None import utils
label_desc: Use image node_id 5 for calling a global function with example usage: _fmt_probplot_axis(ax, dist, nobs) without return types