content: """Check the log N log F slope of a local population."""
  import numpy as np
  import matplotlib.pyplot as plt
  
  from frbpoppy import CosmicPopulation, Survey, SurveyPopulation
  from frbpoppy.population import unpickle
  
  from tests.convenience import plot_aa_style, rel_path
  
  MAKE = True
  
  
  if MAKE:
      population = CosmicPopulation.simple(1e5, generate=True)
      survey = Survey('perfect')
      surv_pop = SurveyPopulation(population, survey)
      surv_pop.name = 'lognlogflocal'
      surv_pop.save()
  else:
      surv_pop = unpickle('lognlogflocal')
  
  # Get parameter
  parms = surv_pop.frbs.fluence
  min_p = min(parms)
  max_p = max(parms)
  
  # Bin up
  min_f = np.log10(min(parms))
  max_f = np.log10(max(parms))
  log_bins = np.logspace(min_f, max_f, 50)
  hist, edges = np.histogram(parms, bins=log_bins)
  n_gt_s = np.cumsum(hist[::-1])[::-1]
  
  # Calculate alpha
  alpha, alpha_err, norm = surv_pop.frbs.calc_logn_logs(parameter='fluence',
                                                        min_p=min_p,
                                                        max_p=max_p)
  
  print(alpha, alpha_err, norm)
  xs = 10**((np.log10(edges[:-1]) + np.log10(edges[1:])) / 2)
  xs = xs[xs >= min_p]
  xs = xs[xs <= max_p]
  ys = [norm*x**(alpha) for x in xs]
  
  plot_aa_style()
  fig = plt.figure()
  ax = fig.add_subplot(111)
  
  plt.step(edges[:-1], n_gt_s, where='post')
  plt.plot(xs, ys, linestyle='--',
           label=rf'$\alpha$ = {alpha:.3} $\pm$ {round(abs(alpha_err), 2)}')
  
  plt.xlabel('Fluence (Jy ms)')
  plt.ylabel(r'N(${>}Fluence$)')
  plt.xscale('log')
  plt.yscale('log')
  plt.legend()
  plt.tight_layout()
  plt.savefig(rel_path('plots/logn_logf_local.pdf'))
  