```python

```


```python
import numpy as np
from sympy import *
init_printing(use_unicode=False)
L00, L11, L22, L33, L44 = symbols('L00 L11 L22 L33 L44')
L10, L20, L30, L40 = symbols('L10 L20 L30 L40')
L21, L31, L41 = symbols('L21 L31 L41')
L32, L42 = symbols('L32 L42')
L43 = symbols('L43')
D0, D1, D2, D3, D4 = symbols('D0 D1 D2 D3 D4')
```


```python
L = Matrix([[1, 0, 0, 0, 0],
            [L10, 1, 0, 0, 0],
            [L20, L21, 1, 0, 0],
            [L30, L31, L32, 1, 0],
            [L40, L41, L42, L43, 1]
])


Lt = L.transpose()

D = Matrix([
    [D0, 0, 0, 0, 0],
    [0, D1, 0, 0, 0],
    [0, 0, D2, 0, 0],
    [0, 0, 0, D3, 0],
    [0, 0, 0, 0, D4]
])
```


```python
A = L*D*Lt
```


```python
mod = A.shape[0]
mods = []
Diags = []
for b in range(mod):
    Diags.append([])
    mods.append(b)

for desloc in range(A.shape[0]):
    for i in range(A.shape[0]):
        for j in range(A.shape[0]):
            if i == j + desloc:
                Diags[desloc].append(A[i,j])
                print(A[i,j])
    print('-----------------------------')
```

    D0
    D0*L10**2 + D1
    D0*L20**2 + D1*L21**2 + D2
    D0*L30**2 + D1*L31**2 + D2*L32**2 + D3
    D0*L40**2 + D1*L41**2 + D2*L42**2 + D3*L43**2 + D4
    -----------------------------
    D0*L10
    D0*L10*L20 + D1*L21
    D0*L20*L30 + D1*L21*L31 + D2*L32
    D0*L30*L40 + D1*L31*L41 + D2*L32*L42 + D3*L43
    -----------------------------
    D0*L20
    D0*L10*L30 + D1*L31
    D0*L20*L40 + D1*L21*L41 + D2*L42
    -----------------------------
    D0*L30
    D0*L10*L40 + D1*L41
    -----------------------------
    D0*L40
    -----------------------------



```python
for elemente in A.col(1):
    print(elemente)


```

    D0*L10
    D0*L10**2 + D1
    D0*L10*L20 + D1*L21
    D0*L10*L30 + D1*L31
    D0*L10*L40 + D1*L41



```python
A00, A11, A22, A33, A44 = symbols('A00 A11 A22 A33 A44')
A10, A20, A30, A40 = symbols('A10 A20 A30 A40')
A21, A31, A41 = symbols('A21 A31 A41')
A32, A42 = symbols('A32 A42')
A43 = symbols('A43')


T = Matrix([[0, 0, 0, 0, 0],
            [A10, 0, 0, 0, 0],
            [A20, A21, 0, 0, 0],
            [A30, A31, A32, 0, 0],
            [A40, A41, A42, A43, 0]
])

T = T + T.transpose()
DT = Matrix([
    [A00, 0, 0, 0, 0],
    [0, A11, 0, 0, 0],
    [0, 0, A22, 0, 0],
    [0, 0, 0, A33, 0],
    [0, 0, 0, 0, A44]
])

T += DT
x = T - A

b0, b1, b2, b3, b4 = symbols('bo b1 b2 b3 b4')


b = Matrix([b0, b1, b2, b3, b4])



print(latex(b))
b
```

    \left[\begin{matrix}bo\\b_{1}\\b_{2}\\b_{3}\\b_{4}\end{matrix}\right]





$\displaystyle \left[\begin{matrix}bo\\b_{1}\\b_{2}\\b_{3}\\b_{4}\end{matrix}\right]$



30155a6ba70007c846b16378e1a2385dfb652b32
ipynb
Jupyter Notebook
Numerico/EP2/Extra/Matrix_finder.ipynb
victorathanasio/Personal-projects
94c870179cec32aa733a612a6faeb047df16d977
MIT
Numerico/EP2/Extra/Matrix_finder.ipynb
victorathanasio/Personal-projects
94c870179cec32aa733a612a6faeb047df16d977
MIT
Numerico/EP2/Extra/Matrix_finder.ipynb
victorathanasio/Personal-projects
94c870179cec32aa733a612a6faeb047df16d977
MIT
Qwen/Qwen-72B
1. YES
2. YES