', D

Differential operator for functions

MuPAD® notebooks will be removed in a future release. Use MATLAB® live scripts instead.

MATLAB live scripts support most MuPAD functionality, though there are some differences. For more information, see Convert MuPAD Notebooks to MATLAB Live Scripts.


f '
D([n1, n2, …], f)


D(f) or, alternatively, f' computes the derivative of the univariate function f.

D([n1, n2, ...], f) computes the partial derivative of the multivariate function f(x1, x2, …).

MuPAD® has two functions for differentiation: diff and D. D represents the differential operator that may be applied to functions; diff is used to differentiate arithmetical expressions. Mathematically, D(f)(x) coincides with diff(f(x), x); D([1, 2], f)(x, y) coincides with diff(f(x, y), x, y). Symbolic calls of D and diff can be converted to one another via rewrite. Cf. Example 8.

D(f) returns the derivative of the univariate functionf. f' is shorthand for D(f).

If f is a multivariate function and denotes the partial derivative of f with respect to its n-th argument, then D([n1, n2, ...], f) computes the partial derivative . Cf. Example 5. In particular, D([ ], f) returns f itself.


It is assumed that partial derivatives commute. Internally, D([n1, n2, ...], f) is converted to D([m1, m2, ...], f), where [m1, m2, ...] = sort([n1, n2, ...]).

f may be any object which can represent a function. In particular, f may be a functional expression built from simple functions by means of arithmetic operators (+, -, *, /, ^, @, @@). Any identifier different from CATALAN, EULER, and PI is regarded as an “unknown” function; the same holds for elements of kernel domains not explicitly mentioned on this page. Cf. Example 1. Any number and each of the three constant identifiers above is regarded as a constant function. Cf. Example 2.

If f is a list, a set, a table, or an array, then D is applied to each entry of f. Cf. Example 3.

A polynomial f of type DOM_POLY is regarded as polynomial function, the indeterminates being the arguments of the function. Cf. Example 6.

If f is a function environment, a procedure, then D can compute the derivative in some cases; see the “Background” section below. If this is not possible, a symbolic D call is returned.

Higher partial derivatives D([n1], D([n2], f)) are simplified to D([n1, n2], f). Cf. Example 7.

The derivative of a univariate function f —denoted by D(f)— is syntactically distinguished from the partial derivative D([1], f) with respect to the first variable, even if f represents a univariate function.

The usual rules of differentiation are implemented:

  • D(f + g) = D(f) + D(g),

  • D(f * g) = f * D(g) + g * D(f),

  • D(1/f) = -D(f) / f^2,

  • D(f @ g) = D(f) @ g * D(g).

Note that the composition of functions is written as f@g and not as f(g).

In order to express the n-th derivative of a univariate function for symbolic n, you can use the “repeated composition operator” @@. Cf. Example 9.

Environment Interactions

D uses option remember.


Example 1

D(f) computes the derivative of the function f:

D(sin), D(x -> x^2), D(id)

D also works for more complex functional expressions:

D(sin @ exp + 2*(x -> x*ln(x)) + id^2)

If f is an identifier without a value, a symbolic D call is returned:

delete f: D(f + sin)

The same holds for objects of kernel type that cannot be regarded as functions:


f' is shorthand for D(f):

(f + sin)', (x -> x^2)', id'

Example 2

Constants are regarded as constant functions:

PI', 3', (1/2)'

Example 3

The usual rules of differentiation are implemented. Note that lists and sets may also be taken as input; in this case, D is applied to each element of the list or set:

delete f, g: D([f+g, f*g]); D({1/f, f@g})

Example 4

The derivatives of most special functions of the library can be computed. Again, id denotes the identity function:

D(tan); D(sin*cos); D(1/sin); D(sin@cos); D(2*sin + ln)

Example 5

D can also compute derivatives of procedures:

f := x -> x^2:
g := proc(x) begin tan(ln(x)) end:
D(f), D(g)

We differentiate a function of two arguments by passing a list of indices as first argument to D. In the example below, we first differentiate with respect to the second argument and then differentiate the result with respect to the first argument:

D([1, 2], (x, y) -> sin(x*y))

The order of the partial derivatives is not relevant:

D([2, 1], (x, y) -> sin(x*y))

delete f, g:

Example 6

A polynomial is regarded as a polynomial function:

D(poly(x^2 + 3*x + 2, [x]))

We differentiate the following bivariate polynomial f twice with respect to its second variable y and once with respect to its first variable x:

f := poly(x^3*y^3, [x, y]):
D([1, 2, 2], f) = diff(f, y, y, x)

delete f:

Example 7

Nested calls to D are flattened:

D([1], D([2], f))

However, this does not hold for calls with only one argument, since D(f) and D([1], f) are not considered to be the same:


Example 8

D may only be applied to functions whereas diff makes only sense for expressions:

D(sin), diff(sin(x), x)

Applying D to expressions and diff to functions makes no sense:

D(sin(x)), diff(sin, x)

rewrite allows to rewrite expressions with D into diff-expression:

rewrite(D(f)(y), diff), rewrite(D(D(f))(y), diff)

The reverse conversion is possible as well:

map(%, rewrite, D)

Example 9

Sometimes you may need the n-th derivative of a function, where n is unknown. This can be achieved using the repeated composition operator. For example, let us write a function that computes the k-th Taylor polynomial of a function f at a point x0 and uses x as variable for that polynomial:

(f, k, x, x0) -> _plus(((D@@n)(f)(x0) * (x - x0)^n / n!) $ n = 0..k):
kthtaylorpoly(sin, 7, x, 0)

delete kthtaylorpoly:

Example 10

Advanced users can extend D to their own special mathematical functions (see “Background” section below). To this end, embed your mathematical function f, say, into a function environmentf and implement the behavior of D for this function as the "D" slot of the function environment. The slot must handle two cases: it may be either called with only one argument which equals f, or with two arguments where the second one equals f. In the latter case, the first argument is a list of arbitrary many indices; that is, the slot must be able to handle higher partial derivatives also.

Suppose, for example, that we are given a function f(t, x, y), and that we do not know anything about f except that it is differentiable infinitely often and satisfies the partial differential equation . To make MuPAD eliminate derivatives with respect to t, we can do the following:

f := funcenv(f):
f::D :=
proc(indexlist, ff)
    n        : DOM_INT,   // Number of t-derivatives.
    list_2_3 : DOM_LIST;  // List of indices of 2's and 3's.
                          // These remain unchanged.
  if args(0) <> 2 then
    error("Wrong number of arguments")
  n        :=  nops(select(indexlist, _equal, 1));
  list_2_3 :=  select(indexlist, _unequal, 1);
  // rewrite (d/dt)^n = (d^2/dx^2 + d^2/dy^2)^n
  _plus(binomial(n, k) *
        hold(D)(sort([2 $ 2*(n-k), 3 $ 2*k].list_2_3), ff)
        $ k = 0..n)

Now, partial derivatives with respect to the first argument t are rewritten by derivatives with respect to the second and third argument:

D([1], f^2)(t, x, y)

D([1, 2, 1], f)

delete f:



A function or a functional expression, an array, a list, a polynomial, a set, or a table

n1, n2, …

Indices: positive integers

Return Values

function or a functional expression. If f is an array or a list etc., a corresponding object containing the derivatives of the entries is returned.

Overloaded By



If f is a domain or a function environment with a slot"D", this slot is called to compute the derivative. The slot procedure has the same calling syntax as D. In particular —and in contrast to the slot"diff"— the slot must be able to compute higher partial derivatives because the list of indices may have length greater than one. Cf. Example 10.

If f is a procedure, a function environment without a "D" slot, then f is called with auxiliary identifiers as arguments. The result of the call is then differentiated using the function diff. If the result of diff yields an expression which can be regarded as function in the auxiliary identifers, then this function is returned, otherwise an unevaluated call of D is returned.

Let us take the function environmentsin as an example. It has no "D" slot, thus the procedure op(sin, 1), which is responsible for evaluating the sine function, is used to compute D(sin), as follows. This procedure is applied to an auxiliary identifier, say x, and differentiated with respect to this identifier via diff. The result is diff(sin(x), x) = cos(x). Via fp::expr_unapply and fp::unapply, the function cos is computed as the derivative of sin.