'Calculate the power of a t-test for one sample or paired samples.
Parameters
effect_size : float
standardized effect size, mean divided by the standard deviation.
effect size has to be positive.
nobs : int or float
sample size, number of observations.
alpha : float in interval (0,1)
significance level, e.g. 0.05, is the probability of a type I
error, that is wrong rejections if the Null Hypothesis is true.
df : int or float
degrees of freedom. By default this is None, and the df from the
one sample or paired ttest is used, ``df = nobs1 - 1``
alternative : string, \'two-sided\' (default), \'larger\', \'smaller\'
extra argument to choose whether the power is calculated for a
two-sided (default) or one sided test. The one-sided test can be
either \'larger\', \'smaller\'.
Returns
power : float
Power of the test, e.g. 0.8, is one minus the probability of a
type II error. Power is the probability that the test correctly
rejects the Null Hypothesis if the Alternative Hypothesis is true.'

def power(self, effect_size, nobs, alpha, df=None, alternative='two-sided'):

    return ttest_power(effect_size, nobs, alpha, df=df, alternative=alternative)
