**sympy**для получения якобиановой символьной матрицы функции, возвращающей скаляр Я пытаюсь взять. For performance reason, I want to provide the

**jacobian**of the system using a LinearOperator. . However, I cannot get it to. The

**Jacobian**Matrix. The

**Jacobian**matrix collects all first-order partial derivatives of a multivariate function. Specifically, consider first a function that maps u real inputs, to a single real output: Then, for an input vector, x, of length, u, the

**Jacobian**vector of size, 1 × u, can be defined as follows:. Parameters. funccallable f (x, *args) A function that takes at least one (possibly vector) argument, and returns a value of the same length. x0ndarray. The starting estimate for the roots of func (x) = 0. argstuple, optional. Any extra arguments to func. fprimecallable f (x, *args), optional. A function to compute the

**Jacobian**of func with. Otherwise, you could use the

**jacobian**method available for matrices in

**sympy**: from

**sympy**import sin, cos, Matrix from

**sympy**.abc import rho, phi X = Matrix ( [rho*cos (phi), rho*sin (phi), rho**2]) Y = Matrix ( [rho, phi]) X.jacobian (Y) Also, you may also be interested to see this low-level variant (link). pythonで数式にはまってしまった 今学んでいることがpythonでいろいろやってみたらとても面白くて、記事にするのを忘れてしまいました。 pythonって代入や、因数分解、微分などいちいちコードで書く必要ないんですね。ライブ. Vector of variables or functions with respect to which you compute

**Jacobian**, specified as a symbolic variable, symbolic function, or vector of symbolic variables. If v is a scalar, then the result is equal to the transpose of diff(f,v).