The array p_val given by multivariate_gaussian(X_val, mu, var) is always only zeros.

mu and var seem fine, and also the X_val values are close to mu.

Shouldnt the p_val colose to mu be higher?

Hello @David_Gschliesser,

Did you mean exactly zero or close to zero?

Can you give 2 to 3 examples such as what `X_val`

, `mu`

, `var`

you used and what `p_val`

you got?

Raymond

Thanks for replying!

Sadly exactly zero, when I write p_val[p_val==0]=2 i get a all 2 array.

my arrays are:

mu=[14.11222578 14.99771051]

var=[1.83263141 1.70974533]

and (sorry long but i want to show the last line) X_val=

[[15.79025979 14.9210243 ]

[13.63961877 15.32995521]

[14.86589943 16.47386514]

[13.58467605 13.98930611]

[13.46404167 15.63533011]

[12.94888838 16.14006828]

[15.31084155 15.17480137]

[13.89795241 15.43169469]

[11.92096525 14.30579937]

[14.85934119 14.90066474]

[13.63501268 14.5620583 ]

[15.75981741 15.13340409]

[15.221965 14.18491044]

[12.10564111 13.42653822]

[14.80848889 13.87075725]

[15.36135887 15.99014917]

[12.72914442 15.8265107 ]

[15.38533789 15.21036416]

[13.81810534 14.29933915]

[15.3788488 15.90228514]

[14.11232153 15.31616729]

i get all zeros, even for the last one

But if i give only

If i give as values:

mu=[14.11222578, 14.99771051]

var=[1.83263141, 1.70974533]

X_val=[[14.11232153, 15.31616729]]

i get p_val=[0.0872844]

the shapes are:

mu.shape is (2,)

var.shape is (2,)

X_val.shape is (307,2)

thanks for your help, somehow i am very stuckā¦ but i have the feeling its just a little thing