def _make_figures(self): """Generates CDFs and normal prob plots for weights and log weights.""" weights = [record.wtkg2 for record in self.records if record.wtkg2 != 'NA'] self._make_normal_model(weights, root='brfss_weight_model') _17_rankit._make_normal_plot(weights, root='brfss_weight_normal', title='Adult weight', ylabel='Weight (kg)') log_weights = [math.log(weight) for weight in weights] xmax = math.log(175.0) axis = [3.5, 5.2, 0, 1] self._make_normal_model(log_weights, root='brfss_weight_log', xmax=xmax, xlabel='adult weight (log kg)', axis=axis) _17_rankit._make_normal_plot(log_weights, root='brfss_weight_lognormal', title='Adult weight', ylabel='Weight (log kg)')
def _make_figures(): pops = _21_populations._read_data() print(len(pops)) cdf = _13_Cdf._make_cdf_from_list(pops, 'populations') _05_myplot._clf() _05_myplot._cdf(cdf) _05_myplot._save(root='populations', title='City/Town Populations', xlabel='population', ylabel='CDF', legend=False) _05_myplot._clf() _05_myplot._cdf(cdf) _05_myplot._save(root='populations_logx', title='City/Town Populations', xlabel='population', ylabel='CDF', xscale='log', legend=False) _05_myplot._clf() _05_myplot._cdf(cdf, complement=True) _05_myplot._save(root='populations_loglog', title='City/Town Populations', xlabel='population', ylabel='Complementary CDF', yscale='log', xscale='log', legend=False) t = [math.log(x) for x in pops] t.sort() _17_rankit._make_normal_plot(t, 'populations_rankit')
def _make_normal_plot(weights): """Generates a normal probability plot of birth weights.""" _17_rankit._make_normal_plot(weights, root='nsfg_birthwgt_normal', ylabel='Birth weights (oz)', )
def main(): results = _10_relay._read_results() speeds = _10_relay._get_speeds(results) _17_rankit._make_normal_plot(speeds, root='relay_normal', ylabel='Speed (MPH)')