flopscope.stats.truncnorm.ppf
flopscope.stats.truncnorm.ppf(q, a, b, loc=0, scale=1)[flopscope source]
Evaluate the percent-point function.
Parameters
- q:array_like
Probabilities in
[0, 1].- a:float
Lower standardized bound.
- b:float
Upper standardized bound.
- loc:float, optional
Mean of the underlying normal distribution. Defaults to
0.- scale:float, optional
Standard deviation of the underlying normal distribution. Defaults to
1.
Returns
- :FlopscopeArray
Quantiles corresponding to
q.
Notes
Equivalent to scipy.stats.truncnorm.ppf(q, a, b, loc, scale).
FLOP cost: 1 * numel(q).
Examples
>>> import flopscope.numpy as fnp
>>> import flopscope as flops
>>> q = flops.array([0.25, 0.5, 0.75])
>>> flops.round(flops.stats.truncnorm.ppf(q, a=-1.0, b=1.0), 3)
array([-0.442, 0. , 0.442])