Did I find the right examples for you? yes no      Crawl my project      Python Jobs

# sympy.matrices.Matrix.jacobian

All Samples(10)  |  Call(10)  |  Derive(0)  |  Import(0)

```def test_jacobian_hessian():
L = Matrix(1, 2, [x**2*y, 2*y**2 + x*y])
syms = [x, y]
assert L.jacobian(syms) == Matrix([[2*x*y, x**2], [y, 4*y + x]])

L = Matrix(1, 2, [x, x**2*y**3])
assert L.jacobian(syms) == Matrix([[1, 0], [2*x*y**3, x**2*3*y**2]])
```
```def test_jacobian_metrics():
rho, phi = symbols("rho,phi")
X = Matrix([rho*cos(phi), rho*sin(phi)])
Y = Matrix([rho, phi])
J = X.jacobian(Y)
assert J == X.jacobian(Y.T)
```
```        [   2*rho,             0],
])
assert X.jacobian(Y) == J

```

```def test_jacobian_hessian():
L = Matrix(1, 2, [x**2*y, 2*y**2 + x*y])
syms = [x, y]
assert L.jacobian(syms) == Matrix([[2*x*y, x**2], [y, 4*y + x]])

L = Matrix(1, 2, [x, x**2*y**3])
assert L.jacobian(syms) == Matrix([[1, 0], [2*x*y**3, x**2*3*y**2]])
```
```def test_jacobian_metrics():
rho, phi = symbols("rho,phi")
X = Matrix([rho*cos(phi), rho*sin(phi)])
Y = Matrix([rho, phi])
J = X.jacobian(Y)
assert J == X.jacobian(Y.T)
```
```        [   2*rho,             0],
])
assert X.jacobian(Y) == J

```