# Leslie model : Matrix and vector operations (in python)¶

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## Analysis of the Leslie matrix model¶

Input $\bf L = \begin{bmatrix} 0 & 1 & 2 & 0 \\ 0.5 & 0 & 0 & 0 \\ 0 & 0.6 & 0 & 0 \\ 0 & 0 & 0.1 & 0\end{bmatrix}$, $\; {\bf n}(0) = \begin{bmatrix} 0 \\ 1 \\ 0 \\ 0\end{bmatrix}$

Put the followings,

Calculate ${\bf n}(1)= {\bf L\: n}(0)$

$$\begin{pmatrix} 0 & 1 & 2 & 0 \\ 0.5 & 0 & 0 & 0 \\ 0 & 0.6 & 0 & 0 \\ 0 & 0 & 0.1 & 0\end{pmatrix} \begin{pmatrix} 0 \\ 1 \\ 0 \\ 0\end{pmatrix}$$

Using ${\bf n}(1) = \begin{pmatrix} 1 \\ 0 \\ 0.6 \\ 0 \end{pmatrix}$ 、calculate ${\bf n}(2) = {\bf L}\,{\bf n}(1)$

Using ${\bf n}(0) = \begin{pmatrix} 0 \\ 1 \\ 0 \\ 0 \end{pmatrix}$ 、calculate ${\bf n}(2) = {\bf L}{\bf L} \,{\bf n}(0)$

${\bf L}{\bf L}$ is equibalint to ${\bf L}^2$

Compute ${\bf L}^t$ with arbitrary exponent $t$. For example $t=4$, ${\bf L}^4$.

Compute ${\bf n}(t)={\bf L}^{t}{\bf n}(0), \;\; t=0, \cdots$, and plot population number of each age.

Compute ${\bf L}^{100},{\bf L}^{101}$.

Refer to element of matrix L100 and L101, for example, see the element in the third row, third column.

Compute the ratio $\frac{{\mathrm L}101[2,2]}{{\mathrm L}100[2,2]}$

#### Compare ${\bf L}^{101}$and $1.03822433996517{\bf L}^{100}$.¶

We see that ${\mathrm L101} \approx 1.03822433996521\times{\mathrm L100}$.

## Eigenvalues and the corresponding eigenvectors of matrix $\bf L$¶

Refering to the eigenvalues.

Show absolute value of the eigenvalues.

The largest eigenvalue is $\lambda_{max} = 1.0382$.

Refering to the eigenvectors.

Second colum of the matrix is the eigenvector corresponding to the largest eigenvalue $\lambda_{max} = 1.0382$.

Ingnore the minus sing of $\begin{bmatrix}u_0\\u_1\\u_2\\u_3\end{bmatrix} \approx \begin{bmatrix}-0.8737\\-0.4208\\-0.2432\\-0.0234\end{bmatrix}$.

Compute $100 \times {\Large \frac {1}{\sum {u_i}}} \begin{bmatrix}u_0\\u_1\\u_2\\u_3\end{bmatrix}$.

$\begin{bmatrix} n_0 \\n_1\\n_2\\n_3\end{bmatrix} \approx \;\;\; \begin{bmatrix}56.0 \%\\27.0\%\\15.6\%\\1.5\%\end{bmatrix}$