Next: Answers to Exercises, Previous: Algebra Tutorial, Up: Tutorial [Contents][Index]

The Calculator is written entirely in Emacs Lisp, a highly extensible language. If you know Lisp, you can program the Calculator to do anything you like. Rewrite rules also work as a powerful programming system. But Lisp and rewrite rules take a while to master, and often all you want to do is define a new function or repeat a command a few times. Calc has features that allow you to do these things easily.

One very limited form of programming is defining your own functions.
Calc’s `Z F` command allows you to define a function name and
key sequence to correspond to any formula. Programming commands use
the shift-`Z` prefix; the user commands they create use the lower
case `z` prefix.

1: x + x^2 / 2 + x^3 / 6 + 1 1: x + x^2 / 2 + x^3 / 6 + 1 . . ' 1 + x + x^2/2! + x^3/3! RET Z F e myexp RET RET RET y

This polynomial is a Taylor series approximation to ‘`exp(x)`’.
The `Z F` command asks a number of questions. The above answers
say that the key sequence for our function should be `z e`; the
`M-x` equivalent should be `calc-myexp`

; the name of the
function in algebraic formulas should also be `myexp`

; the
default argument list ‘`(x)`’ is acceptable; and finally `y`
answers the question “leave it in symbolic form for non-constant
arguments?”

```
1: 1.3495 2: 1.3495 3: 1.3495
. 1: 1.34986 2: 1.34986
. 1: myexp(a + 1)
.
.3 z e .3 E ' a+1 RET z e
```

First we call our new `exp`

approximation with 0.3 as an
argument, and compare it with the true `exp`

function. Then
we note that, as requested, if we try to give `z e` an
argument that isn’t a plain number, it leaves the `myexp`

function call in symbolic form. If we had answered `n` to the
final question, ‘`myexp(a + 1)`’ would have evaluated by plugging
in ‘`a + 1`’ for ‘`x`’ in the defining formula.

(•) **Exercise 1.** The “sine integral” function
‘`Si(x)`’
is defined as the integral of ‘`sin(t)/t`’ for
‘`t = 0`’ to ‘`x`’ in radians. (It was invented because this
integral has no solution in terms of basic functions; if you give it
to Calc’s `a i` command, it will ponder it for a long time and then
give up.) We can use the numerical integration command, however,
which in algebraic notation is written like ‘`ninteg(f(t), t, 0, x)`’
with any integrand ‘`f(t)`’. Define a `z s` command and
`Si`

function that implement this. You will need to edit the
default argument list a bit. As a test, ‘`Si(1)`’ should return
0.946083. (If you don’t get this answer, you might want to check that
Calc is in Radians mode. Also, `ninteg`

will run a lot faster if
you reduce the precision to, say, six digits beforehand.)
See 1. (•)

The simplest way to do real “programming” of Emacs is to define a
*keyboard macro*. A keyboard macro is simply a sequence of
keystrokes which Emacs has stored away and can play back on demand.
For example, if you find yourself typing `H a S x RET` often,
you may wish to program a keyboard macro to type this for you.

1: y = sqrt(x) 1: x = y^2 . . ' y=sqrt(x) RET C-x ( H a S x RET C-x ) 1: y = cos(x) 1: x = s1 arccos(y) + 2 n1 pi . . ' y=cos(x) RET X

When you type `C-x (`, Emacs begins recording. But it is also
still ready to execute your keystrokes, so you’re really “training”
Emacs by walking it through the procedure once. When you type
`C-x )`, the macro is recorded. You can now type `X` to
re-execute the same keystrokes.

You can give a name to your macro by typing `Z K`.

1: . 1: y = x^4 1: x = s2 sqrt(s1 sqrt(y)) . . Z K x RET ' y=x^4 RET z x

Notice that we use shift-`Z` to define the command, and lower-case
`z` to call it up.

Keyboard macros can call other macros.

1: abs(x) 1: x = s1 y 1: 2 / x 1: x = 2 / y . . . . ' abs(x) RET C-x ( ' y RET a = z x C-x ) ' 2/x RET X

(•) **Exercise 2.** Define a keyboard macro to negate
the item in level 3 of the stack, without disturbing the rest of
the stack. See 2. (•)

(•) **Exercise 3.** Define keyboard macros to compute
the following functions:

- Compute
‘
`sin(x) / x`’, where ‘`x`’ is the number on the top of the stack. - Compute the base-‘
`b`’ logarithm, just like the`B`key except the arguments are taken in the opposite order. - Produce a vector of integers from 1 to the integer on the top of the stack.

See 3. (•)

(•) **Exercise 4.** Define a keyboard macro to compute
the average (mean) value of a list of numbers.
See 4. (•)

In many programs, some of the steps must execute several times.
Calc has *looping* commands that allow this. Loops are useful
inside keyboard macros, but actually work at any time.

1: x^6 2: x^6 1: 360 x^2 . 1: 4 . . ' x^6 RET 4 Z < a d x RET Z >

Here we have computed the fourth derivative of ‘`x^6`’ by
enclosing a derivative command in a “repeat loop” structure.
This structure pops a repeat count from the stack, then
executes the body of the loop that many times.

If you make a mistake while entering the body of the loop,
type `Z C-g` to cancel the loop command.

Here’s another example:

3: 1 2: 10946 2: 1 1: 17711 1: 20 . . 1 RET RET 20 Z < TAB C-j + Z >

The numbers in levels 2 and 1 should be the 21st and 22nd Fibonacci
numbers, respectively. (To see what’s going on, try a few repetitions
of the loop body by hand; `C-j`, also on the Line-Feed or `LFD`
key if you have one, makes a copy of the number in level 2.)

A fascinating property of the Fibonacci numbers is that the ‘`n`’th
Fibonacci number can be found directly by computing
‘`phi^n / sqrt(5)`’
and then rounding to the nearest integer, where
‘`phi`’,
the “golden ratio,” is
‘`(1 + sqrt(5)) / 2`’.
(For convenience, this constant is available from the `phi`

variable, or the `I H P` command.)

1: 1.61803 1: 24476.0000409 1: 10945.9999817 1: 10946 . . . . I H P 21 ^ 5 Q / R

(•) **Exercise 5.** The *continued fraction*
representation of
‘`phi`’
is
‘`1 + 1/(1 + 1/(1 + 1/( ... )))`’.
We can compute an approximate value by carrying this however far
and then replacing the innermost
‘`1/( ... )`’
by 1. Approximate
‘`phi`’
using a twenty-term continued fraction.
See 5. (•)

(•) **Exercise 6.** Linear recurrences like the one for
Fibonacci numbers can be expressed in terms of matrices. Given a
vector ‘`[a, b]`’ determine a matrix which, when multiplied by this
vector, produces the vector ‘`[b, c]`’, where ‘`a`’, ‘`b`’ and
‘`c`’ are three successive Fibonacci numbers. Now write a program
that, given an integer ‘`n`’, computes the ‘`n`’th Fibonacci number
using matrix arithmetic. See 6. (•)

A more sophisticated kind of loop is the *for* loop. Suppose
we wish to compute the 20th “harmonic” number, which is equal to
the sum of the reciprocals of the integers from 1 to 20.

3: 0 1: 3.597739 2: 1 . 1: 20 . 0 RET 1 RET 20 Z ( & + 1 Z )

The “for” loop pops two numbers, the lower and upper limits, then repeats the body of the loop as an internal counter increases from the lower limit to the upper one. Just before executing the loop body, it pushes the current loop counter. When the loop body finishes, it pops the “step,” i.e., the amount by which to increment the loop counter. As you can see, our loop always uses a step of one.

This harmonic number function uses the stack to hold the running total as well as for the various loop housekeeping functions. If you find this disorienting, you can sum in a variable instead:

```
1: 0 2: 1 . 1: 3.597739
. 1: 20 .
.
0 t 7 1 RET 20 Z ( & s + 7 1 Z ) r 7
```

The `s +` command adds the top-of-stack into the value in a
variable (and removes that value from the stack).

It’s worth noting that many jobs that call for a “for” loop can
also be done more easily by Calc’s high-level operations. Two
other ways to compute harmonic numbers are to use vector mapping
and reduction (`v x 20`, then `V M &`, then `V R +`),
or to use the summation command `a +`. Both of these are
probably easier than using loops. However, there are some
situations where loops really are the way to go:

(•) **Exercise 7.** Use a “for” loop to find the first
harmonic number which is greater than 4.0.
See 7. (•)

Of course, if we’re going to be using variables in our programs, we have to worry about the programs clobbering values that the caller was keeping in those same variables. This is easy to fix, though:

. 1: 0.6667 1: 0.6667 3: 0.6667 . . 2: 3.597739 1: 0.6667 . Z ` p 4 RET 2 RET 3 / s 7 s s a RET Z ' r 7 s r a RET

When we type `Z `` (that’s a back-quote character), Calc saves
its mode settings and the contents of the ten “quick variables”
for later reference. When we type `Z '` (that’s an apostrophe
now), Calc restores those saved values. Thus the `p 4` and
`s 7` commands have no effect outside this sequence. Wrapping
this around the body of a keyboard macro ensures that it doesn’t
interfere with what the user of the macro was doing. Notice that
the contents of the stack, and the values of named variables,
survive past the `Z '` command.

The *Bernoulli numbers* are a sequence with the interesting
property that all of the odd Bernoulli numbers are zero, and the
even ones, while difficult to compute, can be roughly approximated
by the formula
‘`2 n! / (2 pi)^n`’.
Let’s write a keyboard macro to compute (approximate) Bernoulli numbers.
(Calc has a command, `k b`, to compute exact Bernoulli numbers, but
this command is very slow for large ‘`n`’ since the higher Bernoulli
numbers are very large fractions.)

1: 10 1: 0.0756823 . . 10 C-x ( RET 2 % Z [ DEL 0 Z : ' 2 $! / (2 pi)^$ RET = Z ] C-x )

You can read `Z [` as “then,” `Z :` as “else,” and
`Z ]` as “end-if.” There is no need for an explicit “if”
command. For the purposes of `Z [`, the condition is “true”
if the value it pops from the stack is a nonzero number, or “false”
if it pops zero or something that is not a number (like a formula).
Here we take our integer argument modulo 2; this will be nonzero
if we’re asking for an odd Bernoulli number.

The actual tenth Bernoulli number is ‘`5/66`’.

3: 0.0756823 1: 0 1: 0.25305 1: 0 1: 1.16659 2: 5:66 . . . . 1: 0.0757575 . 10 k b RET c f M-0 DEL 11 X DEL 12 X DEL 13 X DEL 14 X

Just to exercise loops a bit more, let’s compute a table of even Bernoulli numbers.

```
3: [] 1: [0.10132, 0.03079, 0.02340, 0.033197, ...]
2: 2 .
1: 30
.
[ ] 2 RET 30 Z ( X | 2 Z )
```

The vertical-bar `|` is the vector-concatenation command. When
we execute it, the list we are building will be in stack level 2
(initially this is an empty list), and the next Bernoulli number
will be in level 1. The effect is to append the Bernoulli number
onto the end of the list. (To create a table of exact fractional
Bernoulli numbers, just replace `X` with `k b` in the above
sequence of keystrokes.)

With loops and conditionals, you can program essentially anything
in Calc. One other command that makes looping easier is `Z /`,
which takes a condition from the stack and breaks out of the enclosing
loop if the condition is true (non-zero). You can use this to make
“while” and “until” style loops.

If you make a mistake when entering a keyboard macro, you can edit
it using `Z E`. First, you must attach it to a key with `Z K`.
One technique is to enter a throwaway dummy definition for the macro,
then enter the real one in the edit command.

1: 3 1: 3 Calc Macro Edit Mode. . . Original keys: 1 <return> 2 + 1 ;; calc digits RET ;; calc-enter 2 ;; calc digits + ;; calc-plus C-x ( 1 RET 2 + C-x ) Z K h RET Z E h

A keyboard macro is stored as a pure keystroke sequence. The
`edmacro` package (invoked by `Z E`) scans along the
macro and tries to decode it back into human-readable steps.
Descriptions of the keystrokes are given as comments, which begin with
‘`;;`’, and which are ignored when the edited macro is saved.
Spaces and line breaks are also ignored when the edited macro is saved.
To enter a space into the macro, type `SPC`

. All the special
characters `RET`

, `LFD`

, `TAB`

, `SPC`

, `DEL`

,
and `NUL`

must be written in all uppercase, as must the prefixes
`C-`

and `M-`

.

Let’s edit in a new definition, for computing harmonic numbers.
First, erase the four lines of the old definition. Then, type
in the new definition (or use Emacs `M-w` and `C-y` commands
to copy it from this page of the Info file; you can of course skip
typing the comments, which begin with ‘`;;`’).

Z` ;; calc-kbd-push (Save local values) 0 ;; calc digits (Push a zero onto the stack) st ;; calc-store-into (Store it in the following variable) 1 ;; calc quick variable (Quick variable q1) 1 ;; calc digits (Initial value for the loop) TAB ;; calc-roll-down (Swap initial and final) Z( ;; calc-kbd-for (Begin the "for" loop) & ;; calc-inv (Take the reciprocal) s+ ;; calc-store-plus (Add to the following variable) 1 ;; calc quick variable (Quick variable q1) 1 ;; calc digits (The loop step is 1) Z) ;; calc-kbd-end-for (End the "for" loop) sr ;; calc-recall (Recall the final accumulated value) 1 ;; calc quick variable (Quick variable q1) Z' ;; calc-kbd-pop (Restore values)

Press `C-c C-c` to finish editing and return to the Calculator.

1: 20 1: 3.597739 . . 20 z h

The `edmacro` package defines a handy `read-kbd-macro`

command
which reads the current region of the current buffer as a sequence of
keystroke names, and defines that sequence on the `X`
(and `C-x e`) key. Because this is so useful, Calc puts this
command on the `C-x * m` key. Try reading in this macro in the
following form: Press `C-@` (or `C-SPC`) at
one end of the text below, then type `C-x * m` at the other.

Z ` 0 t 1 1 TAB Z ( & s + 1 1 Z ) r 1 Z '

(•) **Exercise 8.** A general algorithm for solving
equations numerically is *Newton’s Method*. Given the equation
‘`f(x) = 0`’ for any function ‘`f`’, and an initial guess
‘`x_0`’ which is reasonably close to the desired solution, apply
this formula over and over:

new_x = x - f(x)/f'(x)

where ‘`f'(x)`’ is the derivative of ‘`f`’. The ‘`x`’
values will quickly converge to a solution, i.e., eventually
‘`new_x`’
and ‘`x`’ will be equal to within the limits
of the current precision. Write a program which takes a formula
involving the variable ‘`x`’, and an initial guess ‘`x_0`’,
on the stack, and produces a value of ‘`x`’ for which the formula
is zero. Use it to find a solution of
‘`sin(cos(x)) = 0.5`’
near ‘`x = 4.5`’. (Use angles measured in radians.) Note that
the built-in `a R` (`calc-find-root`

) command uses Newton’s
method when it is able. See 8. (•)

(•) **Exercise 9.** The *digamma* function
‘`psi(z)`’
is defined as the derivative of
‘`ln(gamma(z))`’.
For large values of ‘`z`’, it can be approximated by the infinite sum

psi(z) ~= ln(z) - 1/2z - sum(bern(2 n) / 2 n z^(2 n), n, 1, inf)

where
‘`sum`’
represents the sum over ‘`n`’ from 1 to infinity
(or to some limit high enough to give the desired accuracy), and
the `bern`

function produces (exact) Bernoulli numbers.
While this sum is not guaranteed to converge, in practice it is safe.
An interesting mathematical constant is Euler’s gamma, which is equal
to about 0.5772. One way to compute it is by the formula,
‘`gamma = -psi(1)`’.
Unfortunately, 1 isn’t a large enough argument
for the above formula to work (5 is a much safer value for ‘`z`’).
Fortunately, we can compute
‘`psi(1)`’
from
‘`psi(5)`’
using the recurrence
‘`psi(z+1) = psi(z) + 1/z`’.
Your task: Develop a program to compute
‘`psi(z)`’;
it should “pump up” ‘`z`’
if necessary to be greater than 5, then use the above summation
formula. Use looping commands to compute the sum. Use your function
to compute
‘`gamma`’
to twelve decimal places. (Calc has a built-in command
for Euler’s constant, `I P`, which you can use to check your answer.)
See 9. (•)

(•) **Exercise 10.** Given a polynomial in ‘`x`’ and
a number ‘`m`’ on the stack, where the polynomial is of degree
‘`m`’ or less (i.e., does not have any terms higher than ‘`x^m`’),
write a program to convert the polynomial into a list-of-coefficients
notation. For example, ‘`5 x^4 + (x + 1)^2`’ with ‘`m = 6`’
should produce the list ‘`[1, 2, 1, 0, 5, 0, 0]`’. Also develop
a way to convert from this form back to the standard algebraic form.
See 10. (•)

(•) **Exercise 11.** The *Stirling numbers of the
first kind* are defined by the recurrences,

s(n,n) = 1 for n >= 0, s(n,0) = 0 for n > 0, s(n+1,m) = s(n,m-1) - n s(n,m) for n >= m >= 1.

This can be implemented using a *recursive* program in Calc; the
program must invoke itself in order to calculate the two righthand
terms in the general formula. Since it always invokes itself with
“simpler” arguments, it’s easy to see that it must eventually finish
the computation. Recursion is a little difficult with Emacs keyboard
macros since the macro is executed before its definition is complete.
So here’s the recommended strategy: Create a “dummy macro” and assign
it to a key with, e.g., `Z K s`. Now enter the true definition,
using the `z s` command to call itself recursively, then assign it
to the same key with `Z K s`. Now the `z s` command will run
the complete recursive program. (Another way is to use `Z E`
or `C-x * m` (`read-kbd-macro`

) to read the whole macro at once,
thus avoiding the “training” phase.) The task: Write a program
that computes Stirling numbers of the first kind, given ‘`n`’ and
‘`m`’ on the stack. Test it with *small* inputs like
‘`s(4,2)`’. (There is a built-in command for Stirling numbers,
`k s`, which you can use to check your answers.)
See 11. (•)

The programming commands we’ve seen in this part of the tutorial are low-level, general-purpose operations. Often you will find that a higher-level function, such as vector mapping or rewrite rules, will do the job much more easily than a detailed, step-by-step program can:

(•) **Exercise 12.** Write another program for
computing Stirling numbers of the first kind, this time using
rewrite rules. Once again, ‘`n`’ and ‘`m`’ should be taken
from the stack. See 12. (•)

This ends the tutorial section of the Calc manual. Now you know enough about Calc to use it effectively for many kinds of calculations. But Calc has many features that were not even touched upon in this tutorial. The rest of this manual tells the whole story.

Next: Answers to Exercises, Previous: Algebra Tutorial, Up: Tutorial [Contents][Index]