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)')
