flopscope.stats.cauchy.ppf
flopscope.stats.cauchy.ppf(q, loc=0, scale=1)[flopscope source]
Evaluate the percent-point function.
Parameters
- q:array_like
Probabilities in
[0, 1].- loc:float, optional
Location parameter of the distribution. Defaults to
0.- scale:float, optional
Scale parameter of the distribution. Defaults to
1.
Returns
- :FlopscopeArray
Quantiles corresponding to
q.
Notes
Equivalent to scipy.stats.cauchy.ppf(q, loc, scale).
FLOP cost: 28 * numel(q) (composite: q-0.5(1) + pi*(1) +
tan(16) + loc+scale*(2) + 3 where(8), FMA=2, weight 1.0).
Examples
>>> import flopscope.numpy as fnp
>>> import flopscope as flops
>>> q = flops.array([0.25, 0.5, 0.75])
>>> flops.round(flops.stats.cauchy.ppf(q), 3)
array([-1., 0., 1.])