f47485cc4a21fb18564ede7ab0cc9001dbd0f1d9,chaospy/descriptives/sensitivity/total.py,,Sens_t,#Any#Any#,9

Before Change


    dim = len(dist)
    poly = setdim(poly, dim)

    zero = [1]*dim
    out = numpy.zeros((dim,) + poly.shape, dtype=float)
    V = Var(poly, dist, **kws)
    for i in range(dim):
        zero[i] = 0
        out[i] = ((V-Var(E_cond(poly, zero, dist, **kws), dist, **kws)) /
                  (V+(V == 0))**(V!=0))
        zero[i] = 1
    return out

After Change



    valids = variance != 0
    if not numpy.all(valids):
        out[:, valids] = Sens_t(poly[valids], dist, **kws)
        return out

    out[:] = variance
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 7

Instances


Project Name: jonathf/chaospy
Commit Name: f47485cc4a21fb18564ede7ab0cc9001dbd0f1d9
Time: 2020-06-10
Author: jonathf@gmail.com
File Name: chaospy/descriptives/sensitivity/total.py
Class Name:
Method Name: Sens_t


Project Name: jonathf/chaospy
Commit Name: f47485cc4a21fb18564ede7ab0cc9001dbd0f1d9
Time: 2020-06-10
Author: jonathf@gmail.com
File Name: chaospy/descriptives/sensitivity/main.py
Class Name:
Method Name: Sens_m


Project Name: pymc-devs/pymc3
Commit Name: 3f32776f0f58c961a1ad625f3e5e34ce31a9ebbb
Time: 2013-03-15
Author: jsalvatier@gmail.com
File Name: examples/stochastic_volatility.py
Class Name:
Method Name: