  The distribution of the ratios of consecutive eigenvalue spacings of random
matrices has emerged as an important tool to study spectral properties of
many-body systems. This article numerically investigates the eigenvalue ratios
distribution of various model networks, namely, small-world, Erd\H{o}s-R\'enyi
random, and (dis)assortative random having a diagonal disorder in the
corresponding adjacency matrices. Without any diagonal disorder, the
eigenvalues ratio distribution of these model networks depict Gaussian
orthogonal ensemble (GOE) statistics. Upon adding diagonal disorder, there
exists a gradual transition from the GOE to Poisson statistics depending upon
the strength of the disorder. The critical disorder (wc) required to procure
the Poisson statistics increases with the randomness in the network
architecture. We relate wc with the time taken by the maximum entropy random
walker to reach the steady-state. These analyses will be helpful to understand
the role of eigenvalues other than the principal one for various network
dynamics such as transient behaviour.
