A number of control statements are available in GP. They are simpler and have a syntax slightly different from their C counterparts, but are quite powerful enough to write any kind of program. Some of them are specific to GP, since they are made for number theorists. As usual, X will denote any simple variable name, and seq will always denote a sequence of expressions, including the empty sequence.
Caveat. In constructs like
for (X = a,b, seq)
the variable X
is lexically scoped to the loop, leading to possibly
unexpected behavior:
n = 5;
for (n = 1, 10,
if (something_nice(), break);
);
\\ at this point n
is 5 !
If the sequence seq
modifies the loop index, then the loop
is modified accordingly:
? for (n = 1, 10, n += 2; print(n)) 3 6 9 12
Interrupts execution of current seq, and immediately exits from the n innermost enclosing loops, within the current function call (or the top level loop); the integer n must be positive. If n is greater than the number of enclosing loops, all enclosing loops are exited.
Interrupt the program and enter the breakloop. The program continues when the breakloop is exited.
? f(N,x)=my(z=x^2+1);breakpoint();gcd(N,z^2+1-z); ? f(221,3) *** at top-level: f(221,3) *** ^ — — -- *** in function f: my(z=x^2+1);breakpoint();gcd(N,z *** ^ — — — — — — -- *** Break loop: type <Return> to continue; 'break' to go back to GP break> z 10 break> %2 = 13
(In the break loop) go down n frames. This allows to cancel a previous
call to dbg_up
.
? x = 0; ? g(x) = x-3; ? f(x) = 1 / g(x+1); ? for (x = 1, 5, f(x+1)) *** at top-level: for(x=1,5,f(x+1)) *** ^ — — - *** in function f: 1/g(x+1) *** ^ — — - *** _/_: impossible inverse in gdiv: 0. *** Break loop: type 'break' to go back to GP prompt break> dbg_up(3) \\ go up 3 frames *** at top-level: for(x=1,5,f(x+1)) *** ^ — — — — — -- break> x 0 break> dbg_down() *** at top-level: for(x=1,5,f(x+1)) *** ^ — — - break> x 1 break> dbg_down() *** at top-level: for(x=1,5,f(x+1)) *** ^ — — - break> x 1 break> dbg_down() *** at top-level: for(x=1,5,f(x+1)) *** ^ — — - *** in function f: 1/g(x+1) *** ^ — — - break> x 2
The above example shows that the notion of GP frame is
finer than the usual stack of function calls (as given for instance by the
GDB backtrace
command): GP frames are attached to variable scopes
and there are frames attached to control flow instructions such as a
for
loop above.
In the break loop, return the error data of the current error, if any.
See iferr
for details about error data. Compare:
? iferr(1/(Mod(2,12019)^(6!)-1),E,Vec(E)) %1 = ["e_INV", "Fp_inv", Mod(119, 12019)] ? 1/(Mod(2,12019)^(6!)-1) *** at top-level: 1/(Mod(2,12019)^(6!)- *** ^ — — — — — — -- *** _/_: impossible inverse in Fp_inv: Mod(119, 12019). *** Break loop: type 'break' to go back to GP prompt break> Vec(dbg_err()) ["e_INV", "Fp_inv", Mod(119, 12019)]
(In the break loop) go up n frames, which allows to inspect data of the
parent function. To cancel a dbg_up
call, use dbg_down
.
? x = 0; ? g(x) = x-3; ? f(x) = 1 / g(x+1); ? for (x = 1, 5, f(x+1)) *** at top-level: for(x=1,5,f(x+1)) *** ^ — — - *** in function f: 1/g(x+1) *** ^ — — - *** _/_: impossible inverse in gdiv: 0. *** Break loop: type 'break' to go back to GP prompt break> x 2 break> dbg_up() *** at top-level: for(x=1,5,f(x+1)) *** ^ — — - break> x 1 break> dbg_up() *** at top-level: for(x=1,5,f(x+1)) *** ^ — — - break> x 1 break> dbg_up() *** at top-level: for(x=1,5,f(x+1)) *** ^ — — — — — -- break> x 0 break> dbg_down() \\ back up once *** at top-level: for(x=1,5,f(x+1)) *** ^ — — - break> x 1
The above example shows that the notion of GP frame is
finer than the usual stack of function calls (as given for instance by the
GDB backtrace
command): GP frames are attached to variable scopes
and there are frames attached to control flow instructions such as a
for
loop above.
Print the inner structure of A, complete if n is omitted, up
to level n otherwise. This function is useful for debugging. It is similar
to \x
but does not require A to be a history entry. In particular,
it can be used in the break loop.
Evaluates seq, where
the formal variable X goes from a to b, where a and b must be in
ℝ. Nothing is done if a > b. If b is set to +oo
, the loop will not
stop; it is expected that the caller will break out of the loop itself at some
point, using break
or return
.
Evaluates seq, where the formal variable n ranges over the composite numbers between the nonnegative real numbers a to b, including a and b if they are composite. Nothing is done if a > b.
? forcomposite(n = 0, 10, print(n)) 4 6 8 9 10
Omitting b means we will run through all composites ≥ a,
starting an infinite loop; it is expected that the user will break out of
the loop himself at some point, using break
or return
.
Note that the value of n cannot be modified within seq:
? forcomposite(n = 2, 10, n = []) *** at top-level: forcomposite(n=2,10,n=[]) *** ^ — *** index read-only: was changed to [].
Evaluates seq, where
the formal variable X ranges through the divisors of n
(see divisors
, which is used as a subroutine). It is assumed that
factor
can handle n, without negative exponents. Instead of n,
it is possible to input a factorization matrix, i.e. the output of
factor(n)
.
This routine uses divisors
as a subroutine, then loops over the
divisors. In particular, if n is an integer, divisors are sorted by
increasing size.
To avoid storing all divisors, possibly using a lot of memory, the following (slower) routine loops over the divisors using essentially constant space:
FORDIV(N)= { my(F = factor(N), P = F[,1], E = F[,2]); forvec(v = vector(#E, i, [0,E[i]]), X = factorback(P, v)); } ? for(i=1, 10^6, FORDIV(i)) time = 11,180 ms. ? for(i=1, 10^6, fordiv(i, d, )) time = 2,667 ms.
Of course, the divisors are no longer sorted by inreasing size.
Evaluates seq, where
the formal variable X ranges through [d, factor
(d)],
where d is a divisors of n
(see divisors
, which is used as a subroutine). Note that such a pair
is accepted as argument to all multiplicative functions.
It is assumed that
factor
can handle n, without negative exponents. Instead of n,
it is possible to input a factorization matrix, i.e. the output of
factor(n)
. This routine uses divisors
(,1) as a subroutine,
then loops over the divisors. In particular, if n is an integer, divisors
are sorted by increasing size.
This function is particularly useful when n is hard to factor and one must evaluate multiplicative function on its divisors: we avoid refactoring each divisor in turn. It also provides a small speedup when n is easy to factor; compare
? A = 10^8; B = A + 10^5; ? for (n = A, B, fordiv(n, d, eulerphi(d))); time = 2,091 ms. ? for (n = A, B, fordivfactored(n, d, eulerphi(d))); time = 1,298 ms. \\ avoid refactoring the divisors ? forfactored (n = A, B, fordivfactored(n, d, eulerphi(d))); time = 1,270 ms. \\ also avoid factoring the consecutive n's !
Evaluates seq, where the formal variable X ranges through the
components of V (t_VEC
, t_COL
, t_LIST
or t_MAT
). A matrix
argument is interpreted as a vector containing column vectors, as in
Vec
(V).
Evaluates seq, where the formal variable E = [name, M, G] ranges through all elliptic curves of conductors from a to b. In this notation name is the curve name in Cremona's elliptic curve database, M is the minimal model, G is a ℤ-basis of the free part of the Mordell-Weil group E(ℚ). If flag is nonzero, select only the first curve in each isogeny class.
? forell(E, 1, 500, my([name,M,G] = E); \ if (#G > 1, print(name))) 389a1 433a1 446d1 ? c = 0; forell(E, 1, 500, c++); c \\ number of curves %2 = 2214 ? c = 0; forell(E, 1, 500, c++, 1); c \\ number of isogeny classes %3 = 971
The elldata
database must be installed and contain data for the
specified conductors.
The library syntax is forell(void *data, long (*f)(void*,GEN), long a, long b, long flag)
.
Evaluates seq, where
the formal variable N is [n, factor
(n)] and n goes from
a to b; a and b must be integers. Nothing is done if a > b.
This function is only implemented for |a|, |b| < 264 (232 on a 32-bit
machine). It uses a sieve and runs in time O(sqrt{b} + b-a). It should
be at least 3 times faster than regular factorization as long as the interval
length b-a is much larger than sqrt{b} and get relatively faster as
the bounds increase. The function slows down dramatically
if primelimit
< sqrt{b}.
? B = 10^9; ? for (N = B, B+10^6, factor(N)) time = 4,538 ms. ? forfactored (N = B, B+10^6, [n,fan] = N) time = 1,031 ms. ? B = 10^11; ? for (N = B, B+10^6, factor(N)) time = 15,575 ms. ? forfactored (N = B, B+10^6, [n,fan] = N) time = 2,375 ms. ? B = 10^14; ? for (N = B, B+10^6, factor(N)) time = 1min, 4,948 ms. ? forfactored (N = B, B+10^6, [n,fan] = N) time = 58,601 ms.
The last timing is with the default primelimit
(500000) which is much less than sqrt{B+106}; it goes down
to 26,750ms
if primelimit
gets bigger than that bound.
In any case sqrt{B+106} is much larger than the interval length 106
so forfactored
gets relatively slower for that reason as well.
Note that all PARI multiplicative functions accept the [n,fan]
argument natively:
? s = 0; forfactored(N = 1, 10^7, s += moebius(N)*eulerphi(N)); s time = 6,001 ms. %1 = 6393738650 ? s = 0; for(N = 1, 10^7, s += moebius(N)*eulerphi(N)); s time = 28,398 ms. \\ slower, we must factor N. Twice. %2 = 6393738650
The following loops over the fundamental dicriminants less than X:
? X = 10^8; ? forfactored(d=1,X, if (isfundamental(d),)); time = 34,030 ms. ? for(d=1,X, if (isfundamental(d),)) time = 1min, 24,225 ms.
Evaluate seq over the partitions X = [x1,...xn] of the
integer k, i.e. increasing sequences x1 ≤ x2... ≤ xn of sum
x1+...+ xn = k. By convention, 0 admits only the empty partition and
negative numbers have no partitions. A partition is given by a
t_VECSMALL
, where parts are sorted in nondecreasing order. The
partitions are listed by increasing size and in lexicographic order when
sizes are equal:
? forpart(X=4, print(X)) Vecsmall([4]) Vecsmall([1, 3]) Vecsmall([2, 2]) Vecsmall([1, 1, 2]) Vecsmall([1, 1, 1, 1])
Optional parameters n and a are as follows:
* n = nmax (resp. n = [nmin,nmax]) restricts partitions to length less than nmax (resp. length between nmin and nmax), where the length is the number of nonzero entries.
* a = amax (resp. a = [amin,amax]) restricts the parts to integers less than amax (resp. between amin and amax).
By default, parts are positive and we remove zero entries unless amin ≤ 0, in which case we fix the size #X = nmax:
\\ at most 3 nonzero parts, all <= 4 ? forpart(v=5,print(Vec(v)), 4, 3) [1, 4] [2, 3] [1, 1, 3] [1, 2, 2] \\ between 2 and 4 parts less than 5, fill with zeros ? forpart(v=5,print(Vec(v)),[0,5],[2,4]) [0, 0, 1, 4] [0, 0, 2, 3] [0, 1, 1, 3] [0, 1, 2, 2] [1, 1, 1, 2] \\ no partitions of 1 with 2 to 4 nonzero parts ? forpart(v=1,print(v),[0,5],[2,4]) ?
The behavior is unspecified if X is modified inside the loop.
The library syntax is forpart(void *data, long (*call)(void*,GEN), long k, GEN a, GEN n)
.
Evaluates seq, where the formal variable p goes through some
permutations given by a t_VECSMALL
. If a is a positive integer then
P goes through the permutations of {1, 2, ..., a} in lexicographic
order and if a is a small vector then p goes through the
(multi)permutations lexicographically larger than or equal to a.
? forperm(3, p, print(p)) Vecsmall([1, 2, 3]) Vecsmall([1, 3, 2]) Vecsmall([2, 1, 3]) Vecsmall([2, 3, 1]) Vecsmall([3, 1, 2]) Vecsmall([3, 2, 1])
When a is itself a t_VECSMALL
or a t_VEC
then p iterates through
multipermutations
? forperm([2,1,1,3], p, print(p)) Vecsmall([2, 1, 1, 3]) Vecsmall([2, 1, 3, 1]) Vecsmall([2, 3, 1, 1]) Vecsmall([3, 1, 1, 2]) Vecsmall([3, 1, 2, 1]) Vecsmall([3, 2, 1, 1])
Evaluates seq,
where the formal variable p ranges over the prime numbers between the real
numbers a to b, including a and b if they are prime. More precisely,
the value of
p is incremented to nextprime(p + 1)
, the smallest prime strictly
larger than p, at the end of each iteration. Nothing is done if a > b.
? forprime(p = 4, 10, print(p)) 5 7
Setting b to +oo
means we will run through all primes
≥ a, starting an infinite loop; it is expected that the caller will break
out of the loop itself at some point, using break
or return
.
Note that the value of p cannot be modified within seq:
? forprime(p = 2, 10, p = []) *** at top-level: forprime(p=2,10,p=[]) *** ^ — *** prime index read-only: was changed to [].
Evaluates seq, where the formal variable p ranges over the prime
numbers in an arithmetic progression in [a,b]: q is either an integer
(p = a (mod q)) or an intmod Mod(c,N)
and we restrict
to that congruence class. Nothing is done if a > b.
? forprimestep(p = 4, 30, 5, print(p)) 19 29 ? forprimestep(p = 4, 30, Mod(1,5), print(p)) 11
Setting b to +oo
means we will run through all primes
≥ a, starting an infinite loop; it is expected that the caller will break
out of the loop itself at some point, using break
or return
.
Note that the value of p cannot be modified within seq:
? forprimestep(p = 2, 10, 3, p = []) *** at top-level: forprimestep(p=2,10,3,p=[]) *** ^ — *** prime index read-only: was changed to [].
Evaluates seq, where the formal variable N is [n,
factor
(n)] and n goes through squarefree integers from a to b;
a and b must be integers. Nothing is done if a > b.
? forsquarefree(N=-3,9,print(N)) [-3, [-1, 1; 3, 1]] [-2, [-1, 1; 2, 1]] [-1, Mat([-1, 1])] [1, matrix(0,2)] [2, Mat([2, 1])] [3, Mat([3, 1])] [5, Mat([5, 1])] [6, [2, 1; 3, 1]] [7, Mat([7, 1])]
This function is only implemented for |a|, |b| < 264 (232 on a 32-bit
machine). It uses a sieve and runs in time O(sqrt{b} + b-a). It should
be at least 5 times faster than regular factorization as long as the interval
length b-a is much larger than sqrt{b} and get relatively faster as
the bounds increase. The function slows down dramatically
if primelimit
< sqrt{b}. It is comparable to forfactored
, but
about ζ(2) = π2/6 times faster due to the relative density
of squarefree integers.
? B = 10^9; ? for (N = B, B+10^6, factor(N)) time = 2,463 ms. ? forfactored (N = B, B+10^6, [n,fan] = N) time = 567 ms. ? forsquarefree (N = B, B+10^6, [n,fan] = N) time = 343 ms. ? B = 10^11; ? for (N = B, B+10^6, factor(N)) time = 8,012 ms. ? forfactored (N = B, B+10^6, [n,fan] = N) time = 1,293 ms. ? forsquarefree (N = B, B+10^6, [n,fan] = N) time = 713 ms. ? B = 10^14; ? for (N = B, B+10^6, factor(N)) time = 41,283 ms. ? forsquarefree (N = B, B+10^6, [n,fan] = N) time = 33,399 ms.
The last timing is with the default primelimit
(500000) which is much less than sqrt{B+106}; it goes down
to 29,253ms
if primelimit
gets bigger than that bound.
In any case sqrt{B+106} is much larger than the interval length 106
so forsquarefree
gets relatively slower for that reason as well.
Note that all PARI multiplicative functions accept the [n,fan]
argument natively:
? s = 0; forsquarefree(N = 1, 10^7, s += moebius(N)*eulerphi(N)); s time = 2,003 ms. %1 = 6393738650 ? s = 0; for(N = 1, 10^7, s += moebius(N)*eulerphi(N)); s time = 18,024 ms. \\ slower, we must factor N. Twice. %2 = 6393738650
The following loops over the fundamental dicriminants less than X:
? X = 10^8; ? for(d=1,X, if (isfundamental(d),)) time = 53,387 ms. ? forfactored(d=1,X, if (isfundamental(d),)); time = 13,861 ms. ? forsquarefree(d=1,X, D = quaddisc(d); if (D <= X, )); time = 14,341 ms.
Note that in the last loop, the fundamental discriminants
D are not evaluated in order (since quaddisc(d)
for squarefree d
is either d or 4d) but the set of numbers we run through is the same.
Not worth the complication since it's slower than testing isfundamental
.
A faster, more complicated approach uses two loops. For simplicity, assume
X is divisible by 4:
? forsquarefree(d=1,X/4, D = quaddisc(d)); time = 3,642 ms. ? forsquarefree(d=X/4+1,X, if (d[1] % 4 == 1,)); time = 7,772 ms.
This is the price we pay for a faster evaluation,
We can run through negative fundamental discriminants in the same way:
? forfactored(d=-X,-1, if (isfundamental(d),));
Evaluates seq, where the formal variable X goes from a to b in increments of s. Nothing is done if s > 0 and a > b or if s < 0 and a < b. The s can be
* a positive real number, preferably an integer: X = a, a+s, a+2s...
* an intmod Mod(c,N)
(restrict to the corresponding arithmetic
progression starting at the smallest integer A ≥ a and congruent to c
modulo N): X = A, A + N,...
* a vector of steps [s1,...,sn] (the successive steps in ℝ* are used in the order they appear in s): X = a, a+s1, a+s1+s2, ...
? forstep(x=5, 10, 2, print(x)) 5 7 9 ? forstep(x=5, 10, Mod(1,3), print(x)) 7 10 ? forstep(x=5, 10, [1,2], print(x)) 5 6 8 9
Setting b to +oo
will start an infinite loop; it is
expected that the caller will break out of the loop itself at some point,
using break
or return
.
Evaluates seq for each subgroup H of the abelian group G (given in SNF form or as a vector of elementary divisors).
If bound is present, and is a positive integer, restrict the output to subgroups of index less than bound. If bound is a vector containing a single positive integer B, then only subgroups of index exactly equal to B are computed
The subgroups are not ordered in any obvious way, unless G is a p-group in which case Birkhoff's algorithm produces them by decreasing index. A subgroup is given as a matrix whose columns give its generators on the implicit generators of G. For example, the following prints all subgroups of index less than 2 in G = ℤ/2ℤ g1 x ℤ/2ℤ g2:
? G = [2,2]; forsubgroup(H=G, 2, print(H)) [1; 1] [1; 2] [2; 1] [1, 0; 1, 1]
The last one, for instance is generated by (g1, g1 + g2). This
routine is intended to treat huge groups, when subgrouplist
is not an
option due to the sheer size of the output.
For maximal speed the subgroups have been left as produced by the algorithm. To print them in canonical form (as left divisors of G in HNF form), one can for instance use
? G = matdiagonal([2,2]); forsubgroup(H=G, 2, print(mathnf(concat(G,H)))) [2, 1; 0, 1] [1, 0; 0, 2] [2, 0; 0, 1] [1, 0; 0, 1]
Note that in this last representation, the index [G:H] is given by the
determinant. See galoissubcyclo
and galoisfixedfield
for
applications to Galois theory.
The library syntax is forsubgroup(void *data, long (*call)(void*,GEN), GEN G, GEN bound)
.
If nk is a nonnegative integer n, evaluates seq
, where
the formal variable s goes through all subsets of {1, 2,..., n};
if nk is a pair [n,k] of integers, s goes through subsets
of size k of {1, 2,..., n}. In both cases s goes through subsets
in lexicographic order among subsets of the same size and smaller subsets
come first.
? forsubset([5,3], s, print(s)) Vecsmall([1, 2, 3]) Vecsmall([1, 2, 4]) Vecsmall([1, 2, 5]) Vecsmall([1, 3, 4]) Vecsmall([1, 3, 5]) Vecsmall([1, 4, 5]) Vecsmall([2, 3, 4]) Vecsmall([2, 3, 5]) Vecsmall([2, 4, 5]) Vecsmall([3, 4, 5])
? forsubset(3, s, print(s)) Vecsmall([]) Vecsmall([1]) Vecsmall([2]) Vecsmall([3]) Vecsmall([1, 2]) Vecsmall([1, 3]) Vecsmall([2, 3]) Vecsmall([1, 2, 3])
The running time is proportional to the number
of subsets enumerated, respectively 2n and binomial
(n,k):
? c = 0; forsubset([40,35],s,c++); c time = 128 ms. %4 = 658008 ? binomial(40,35) %5 = 658008
Let v be an n-component vector (where n is arbitrary) of
two-component vectors [ai,bi] for 1 ≤ i ≤ n, where all entries
ai, bi are real numbers.
This routine lets X vary over the n-dimensional
box given by v with unit steps: X is an n-dimensional vector whose i-th
entry X[i] runs through ai, ai+1, ai+2,... stopping with the
first value greater than bi (note that neither ai nor
bi - ai are required to be integers). The values of X are ordered
lexicographically, like embedded for
loops, and the expression
seq is evaluated with the successive values of X. The type of X is
the same as the type of v: t_VEC
or t_COL
.
If flag = 1, generate only nondecreasing vectors X, and if flag = 2, generate only strictly increasing vectors X.
? forvec (X=[[0,1],[-1,1]], print(X)); [0, -1] [0, 0] [0, 1] [1, -1] [1, 0] [1, 1] ? forvec (X=[[0,1],[-1,1]], print(X), 1); [0, 0] [0, 1] [1, 1] ? forvec (X=[[0,1],[-1,1]], print(X), 2) [0, 1]
As a shortcut, a vector of the form v = [[0,c1-1],...[0,cn-1]] can be abbreviated as v = [c1,...cn] and flag is ignored in this case. More generally, if v is a vector of nonnegative integers ci the loop runs over representatives of ℤn/vℤn; and flag is again ignored. The vector v may contain zero entries, in which case the loop spans an infinite lattice. The values are ordered lexicographically, graded by increasing L1-norm on free (ci = 0) components.
This allows to iterate over elements of abelian groups using their
.cyc
vector.
? forvec (X=[2,3], print(X)); [0, 0] [0, 1] [0, 2] [1, 0] [1, 1] [1, 2] ? my(i);forvec (X=[0,0], print(X); if (i++ > 10, break)); [0, 0] [-1, 0] [0, -1] [0, 1] [1, 0] [-2, 0] [-1, -1] [-1, 1] [0, -2] [0, 2] [1, -1] ? zn = znstar(36,1); ? forvec (chi = zn.cyc, if (chareval(zn,chi,5) == 5/6, print(chi))); [1, 0] [1, 1] ? bnrchar(zn, [5], [5/6]) \\ much more efficient in general %5 = [[1, 1], [1, 0]]
Evaluates the expression sequence seq1 if a is nonzero, otherwise the expression seq2. Of course, seq1 or seq2 may be empty:
if (a,seq)
evaluates seq if a is not equal to zero
(you don't have to write the second comma), and does nothing otherwise,
if (a,,seq)
evaluates seq if a is equal to zero, and
does nothing otherwise. You could get the same result using the !
(not
) operator: if (!a,seq)
.
The value of an if
statement is the value of the branch that gets
evaluated: for instance
x = if(n % 4 == 1, y, z);
sets x to y if n is 1 modulo 4, and to z otherwise.
Successive 'else' blocks can be abbreviated in a single compound if
as follows:
if (test1, seq1, test2, seq2, ... testn, seqn, seqdefault);
is equivalent to
if (test1, seq1 , if (test2, seq2 , ... if (testn, seqn, seqdefault)...));
For instance, this allows to write traditional switch / case constructions:
if (x == 0, do0(), x == 1, do1(), x == 2, do2(), dodefault());
Remark.
The boolean operators &&
and ||
are evaluated
according to operator precedence as explained in Section se:operators, but,
contrary to other operators, the evaluation of the arguments is stopped
as soon as the final truth value has been determined. For instance
if (x != 0 && f(1/x), ...)
is a perfectly safe statement.
Remark. Functions such as break
and next
operate on
loops, such as forxxx
, while
, until
. The if
statement is not a loop. (Obviously!)
Evaluates the expression sequence seq1. If an error occurs,
set the formal parameter E set to the error data.
If pred is not present or evaluates to true, catch the error
and evaluate seq2. Both pred and seq2 can reference E.
The error type is given by errname(E)
, and other data can be
accessed using the component
function. The code seq2 should check
whether the error is the one expected. In the negative the error can be
rethrown using error(E)
(and possibly caught by an higher iferr
instance). The following uses iferr
to implement Lenstra's ECM factoring
method
? ecm(N, B = 1000!, nb = 100)= { for(a = 1, nb, iferr(ellmul(ellinit([a,1]*Mod(1,N)), [0,1]*Mod(1,N), B), E, return(gcd(lift(component(E,2)),N)), errname(E)=="e_INV" && type(component(E,2)) == "t_INTMOD")) } ? ecm(2^101-1) %2 = 7432339208719
The return value of iferr
itself is the value of seq2 if an
error occurs, and the value of seq1 otherwise. We now describe the
list of valid error types, and the attached error data E; in each
case, we list in order the components of E, accessed via
component(E,1)
, component(E,2)
, etc.
Internal errors, "system" errors.
* "e_ARCH"
. A requested feature s is not available on this
architecture or operating system.
E has one component (t_STR
): the missing feature name s.
* "e_BUG"
. A bug in the PARI library, in function s.
E has one component (t_STR
): the function name s.
* "e_FILE"
. Error while trying to open a file.
E has two components, 1 (t_STR
): the file type (input, output,
etc.), 2 (t_STR
): the file name.
* "e_IMPL"
. A requested feature s is not implemented.
E has one component, 1 (t_STR
): the feature name s.
* "e_PACKAGE"
. Missing optional package s.
E has one component, 1 (t_STR
): the package name s.
Syntax errors, type errors.
* "e_DIM"
. The dimensions of arguments x and y submitted
to function s does not match up.
E.g., multiplying matrices of inconsistent dimension, adding vectors of
different lengths,...
E has three component, 1 (t_STR
): the function name s, 2: the
argument x, 3: the argument y.
* "e_FLAG"
. A flag argument is out of bounds in function s.
E has one component, 1 (t_STR
): the function name s.
* "e_NOTFUNC"
. Generated by the PARI evaluator; tried to use a
GEN
x which is not a t_CLOSURE
in a function call syntax (as in
f = 1; f(2);
).
E has one component, 1: the offending GEN
x.
* "e_OP"
. Impossible operation between two objects than cannot
be typecast to a sensible common domain for deeper reasons than a type
mismatch, usually for arithmetic reasons. As in O(2) + O(3)
: it is
valid to add two t_PADIC
s, provided the underlying prime is the same; so
the addition is not forbidden a priori for type reasons, it only becomes so
when inspecting the objects and trying to perform the operation.
E has three components, 1 (t_STR
): the operator name op,
2: first argument, 3: second argument.
* "e_TYPE"
. An argument x of function s had an unexpected type.
(As in factor("blah")
.)
E has two components, 1 (t_STR
): the function name s,
2: the offending argument x.
* "e_TYPE2"
. Forbidden operation between two objects than cannot be
typecast to a sensible common domain, because their types do not match up.
(As in Mod(1,2) + Pi
.)
E has three components, 1 (t_STR
): the operator name op,
2: first argument, 3: second argument.
* "e_PRIORITY"
. Object o in function s contains
variables whose priority is incompatible with the expected operation.
E.g. Pol([x,1], 'y)
: this raises an error because it's not possible to
create a polynomial whose coefficients involve variables with higher priority
than the main variable. E has four components: 1 (t_STR
): the function
name s, 2: the offending argument o, 3 (t_STR
): an operator
op describing the priority error, 4 (t_POL
):
the variable v describing the priority error. The argument
satisfies variable
(x) op variable
(v).
* "e_VAR"
. The variables of arguments x and y submitted
to function s does not match up. E.g., considering the algebraic number
Mod(t,t^2+1)
in nfinit(x^2+1)
.
E has three component, 1 (t_STR
): the function name s, 2
(t_POL
): the argument x, 3 (t_POL
): the argument y.
Overflows.
* "e_COMPONENT"
. Trying to access an inexistent component in a
vector/matrix/list in a function: the index is less than 1 or greater
than the allowed length.
E has four components,
1 (t_STR
): the function name
2 (t_STR
): an operator op ( < or > ),
2 (t_GEN
): a numerical limit l bounding the allowed range,
3 (GEN
): the index x. It satisfies x op l.
* "e_DOMAIN"
. An argument is not in the function's domain.
E has five components, 1 (t_STR
): the function name,
2 (t_STR
): the mathematical name of the out-of-domain argument
3 (t_STR
): an operator op describing the domain error,
4 (t_GEN
): the numerical limit l describing the domain error,
5 (GEN
): the out-of-domain argument x. The argument satisfies x
op l, which prevents it from belonging to the function's domain.
* "e_MAXPRIME"
. A function using the precomputed list of prime
numbers ran out of primes.
E has one component, 1 (t_INT
): the requested prime bound, which
overflowed primelimit
or 0 (bound is unknown).
* "e_MEM"
. A call to pari_malloc
or pari_realloc
failed. E has no component.
* "e_OVERFLOW"
. An object in function s becomes too large to be
represented within PARI's hardcoded limits. (As in 2^2^2^10
or
exp(1e100)
, which overflow in lg
and expo
.)
E has one component, 1 (t_STR
): the function name s.
* "e_PREC"
. Function s fails because input accuracy is too low.
(As in floor(1e100)
at default accuracy.)
E has one component, 1 (t_STR
): the function name s.
* "e_STACK"
. The PARI stack overflows.
E has no component.
Errors triggered intentionally.
* "e_ALARM"
. A timeout, generated by the alarm
function.
E has one component (t_STR
): the error message to print.
* "e_USER"
. A user error, as triggered by
error
(g1,...,gn).
E has one component, 1 (t_VEC
): the vector of n arguments given
to error
.
Mathematical errors.
* "e_CONSTPOL"
. An argument of function s is a constant
polynomial, which does not make sense. (As in galoisinit(Pol(1))
.)
E has one component, 1 (t_STR
): the function name s.
* "e_COPRIME"
. Function s expected coprime arguments,
and did receive x,y, which were not.
E has three component, 1 (t_STR
): the function name s,
2: the argument x, 3: the argument y.
* "e_INV"
. Tried to invert a noninvertible object x in
function s.
E has two components, 1 (t_STR
): the function name s,
2: the noninvertible x. If x = Mod
(a,b)
is a t_INTMOD
and a is not 0 mod b, this allows to factor
the modulus, as gcd
(a,b) is a nontrivial divisor of b.
* "e_IRREDPOL"
. Function s expected an irreducible polynomial,
and did receive T, which was not. (As in nfinit(x^2-1)
.)
E has two component, 1 (t_STR
): the function name s,
2 (t_POL
): the polynomial x.
* "e_MISC"
. Generic uncategorized error.
E has one component (t_STR
): the error message to print.
* "e_MODULUS"
. moduli x and y submitted to function s are
inconsistent. As in
nfalgtobasis(nfinit(t^3-2), Mod(t,t^2+1))
E has three component, 1 (t_STR
): the function s,
2: the argument x, 3: the argument y.
* "e_PRIME"
. Function s expected a prime number,
and did receive p, which was not. (As in idealprimedec(nf, 4)
.)
E has two component, 1 (t_STR
): the function name s,
2: the argument p.
* "e_ROOTS0"
. An argument of function s is a zero polynomial,
and we need to consider its roots. (As in polroots(0)
.) E has
one component, 1 (t_STR
): the function name s.
* "e_SQRTN"
. Trying to compute an n-th root of x, which does
not exist, in function s. (As in sqrt(Mod(-1,3))
.)
E has two components, 1 (t_STR
): the function name s,
2: the argument x.
Interrupts execution of current seq, resume the next iteration of the innermost enclosing loop, within the current function call (or top level loop). If n is specified, resume at the n-th enclosing loop. If n is bigger than the number of enclosing loops, all enclosing loops are exited.
Returns from current subroutine, with
result x. If x is omitted, return the (void)
value (return no
result, like print
).
Sets debug level for domain D to n (0 ≤ n ≤ 20).
The domain D is a character string describing a Pari feature or code
module, such as "bnf"
, "qflll"
or "polgalois"
. This allows
to selectively increase or decrease the diagnostics attached to a particular
feature.
If n is omitted, returns the current level for domain D.
If D is omitted, returns a two-column matrix which lists the available
domains with their levels. The debug
default allows to reset all debug
levels to a given value.
? setdebug()[,1] \\ list of all domains ["alg", "arith", "bern", "bnf", "bnr", "bnrclassfield", ..., "zetamult"] ? \g 1 \\ sets all debug levels to 1 debug = 1 ? setdebug("bnf", 0); \\ kills messages related to bnfinit and bnfisrincipal
Evaluates seq until a is not
equal to 0 (i.e. until a is true). If a is initially not equal to 0,
seq is evaluated once (more generally, the condition on a is tested
after execution of the seq, not before as in while
).
While a is nonzero, evaluates the expression sequence seq. The test is made before evaluating the seq, hence in particular if a is initially equal to zero the seq will not be evaluated at all.