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########################################################################
##
## Copyright (C) 2008-2024 The Octave Project Developers
##
## See the file COPYRIGHT.md in the top-level directory of this
## distribution or <https://octave.org/copyright/>.
##
## This file is part of Octave.
##
## Octave is free software: you can redistribute it and/or modify it
## under the terms of the GNU General Public License as published by
## the Free Software Foundation, either version 3 of the License, or
## (at your option) any later version.
##
## Octave is distributed in the hope that it will be useful, but
## WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with Octave; see the file COPYING. If not, see
## <https://www.gnu.org/licenses/>.
##
########################################################################
## -*- texinfo -*-
## @deftypefn {} {@var{q} =} quadgk (@var{f}, @var{a}, @var{b})
## @deftypefnx {} {@var{q} =} quadgk (@var{f}, @var{a}, @var{b}, @var{abstol})
## @deftypefnx {} {@var{q} =} quadgk (@var{f}, @var{a}, @var{b}, @var{abstol}, @var{trace})
## @deftypefnx {} {@var{q} =} quadgk (@var{f}, @var{a}, @var{b}, "@var{prop}", @var{val}, @dots{})
## @deftypefnx {} {[@var{q}, @var{err}] =} quadgk (@dots{})
##
## Numerically evaluate the integral of @var{f} from @var{a} to @var{b}
## using adaptive @nospell{Gauss-Kronrod} quadrature.
##
## @var{f} is a function handle, inline function, or string containing the name
## of the function to evaluate. The function @var{f} must be vectorized and
## return a vector of output values when given a vector of input values (See
## property @qcode{"ArrayValued"} for an exception to this rule).
##
## @var{a} and @var{b} are the lower and upper limits of integration. Either
## or both limits may be infinite or contain weak end singularities. Variable
## transformation will be used to treat any infinite intervals and weaken the
## singularities. For example:
##
## @example
## quadgk (@@(x) 1 ./ (sqrt (x) .* (x + 1)), 0, Inf)
## @end example
##
## @noindent
## Note that the formulation of the integrand uses the element-by-element
## operator @code{./} and all user functions to @code{quadgk} should do the
## same.
##
## The optional argument @var{abstol} defines the absolute tolerance used to
## stop the integration procedure. The default value is 1e-10 (1e-5 for
## single).
##
## The algorithm used by @code{quadgk} involves subdividing the integration
## interval and evaluating each subinterval. If @var{trace} is true then after
## computing each of these partial integrals display: (1) the number of
## subintervals at this step, (2) the current estimate of the error @var{err},
## (3) the current estimate for the integral @var{q}.
##
## The behavior of the algorithm can be configured by passing arguments to
## @code{quadgk} as pairs @qcode{"@var{prop}", @var{val}}. Valid properties
## are
##
## @table @code
## @item AbsTol
## Define the absolute error tolerance for the quadrature. The default
## absolute tolerance is 1e-10 (1e-5 for single).
##
## @item RelTol
## Define the relative error tolerance for the quadrature. The default
## relative tolerance is 1e-6 (1e-4 for single).
##
## @item ArrayValued
## When set to true, the function @var{f} produces an array output for a scalar
## input. The default is false which requires that @var{f} produce an output
## that is the same size as the input. For example,
##
## @example
## quadgk (@@(x) x .^ (1:5), 0, 2, "ArrayValued", 1)
## @end example
##
## @noindent
## will integrate @code{[x.^1, x.^2, x.^3, x.^4, x.^5]} in one function call
## rather than having to repeatedly define a single anonymous function and
## use a normal invocation of @code{quadgk}.
##
## @item WayPoints
## Specify points which will become endpoints for subintervals in the
## algorithm which can result in significantly improved estimation of the error
## in the integral, faster computation, or both. It can be useful to specify
## more subintervals around a region where the integrand is rapidly changing or
## to flag locations where there is a discontinuity in the first derivative
## of the function. For example, the signum function has a discontinuity at
## @code{x == 0} and by specifying a waypoint
##
## @example
## quadgk (@@(x) sign (x), -0.5, 1, "Waypoints", [0])
## @end example
##
## @noindent
## the error bound is reduced from 4e-7 to 1e-13.
##
## If the function has @strong{singularities} within the region of integration
## those should not be addressed with waypoints. Instead, the overall integral
## should be decomposed into a sum of several smaller integrals such that the
## singularity occurs as one of the bounds of integration in the call to
## @code{quadgk}.
##
## If any of the waypoints are complex then contour integration is performed as
## documented below.
##
## @item MaxIntervalCount
## @code{quadgk} initially subdivides the interval on which to perform the
## quadrature into 10 intervals or, if WayPoints are given, at each waypoint.
## Subintervals that have an unacceptable error are subdivided and
## re-evaluated. If the number of subintervals exceeds 650 subintervals at any
## point then a poor convergence is signaled and the current estimate of the
## integral is returned. The property @qcode{"MaxIntervalCount"} can be used
## to alter the number of subintervals that can exist before exiting.
##
## @item Trace
## If logically true @code{quadgk} prints information on the convergence of the
## quadrature at each iteration.
## @end table
##
## If any of @var{a}, @var{b}, or @var{waypoints} is complex then the
## quadrature is treated as a contour integral along a piecewise linear
## path defined by
## @code{[@var{a}, @var{waypoints}(1), @var{waypoints}(2), @dots{}, @var{b}]}.
## In this case the integral is assumed to have no edge singularities. For
## example,
##
## @example
## @group
## quadgk (@@(z) log (z), 1+1i, 1+1i, "WayPoints",
## [-1+1i, -1-1i, +1-1i])
## @end group
## @end example
##
## @noindent
## integrates @code{log (z)} along the square defined by
## @code{[1+1i, -1+1i, -1-1i, +1-1i]}.
##
## The result of the integration is returned in @var{q}.
##
## @var{err} is an approximate bound on the error in the integral
## @w{@code{abs (@var{q} - @var{I})}}, where @var{I} is the exact value of the
## integral. If the adaptive integration did not converge, the value of
## @var{err} will be larger than the requested tolerance. If only a single
## output is requested then a warning will be emitted when the requested
## tolerance is not met. If the second output @var{err} is requested then no
## warning is issued and it is the responsibility of the programmer to inspect
## and determine whether the results are satisfactory.
##
## Reference: @nospell{L.F. Shampine},
## @cite{"Vectorized adaptive quadrature in @sc{matlab}"}, Journal of
## Computational and Applied Mathematics, pp.@: 131--140, Vol 211, Issue 2,
## Feb 2008.
##
## @seealso{quad, quadv, quadl, quadcc, trapz, dblquad, triplequad, integral,
## integral2, integral3}
## @end deftypefn
function [q, err] = quadgk (f, a, b, varargin)
if (nargin < 3)
print_usage ();
endif
abstol = [];
reltol = [];
waypoints = [];
maxint = 650;
arrayvalued = false;
trace = false;
## Parse options if present.
if (nargin > 3)
if (! ischar (varargin{1}))
if (! isempty (varargin{1}))
abstol = varargin{1};
reltol = 0;
endif
if (nargin > 4)
trace = varargin{2};
endif
if (nargin > 5)
error ("quadgk: can not pass additional arguments to user function");
endif
else
if (mod (nargin - 3, 2) != 0)
error ("quadgk: property/value options must occur in pairs");
endif
idx = 1;
while (idx < nargin - 3)
if (! ischar (varargin{idx}))
error ("quadgk: property PROP must be a string");
endif
prop = varargin{idx++};
switch (lower (prop))
case "reltol"
reltol = varargin{idx++};
case "abstol"
abstol = varargin{idx++};
case "waypoints"
waypoints = varargin{idx++}(:);
case "maxintervalcount"
maxint = varargin{idx++};
case "arrayvalued"
arrayvalued = varargin{idx++};
case "trace"
trace = varargin{idx++};
otherwise
error ("quadgk: unknown property '%s'", prop);
endswitch
endwhile
endif
endif
reverse = 1;
contour = iscomplex (a) || iscomplex (b) || iscomplex (waypoints);
if ((b < a) && ! contour)
## Reverse integration
[b, a] = deal (a, b);
waypoints = sort (waypoints(waypoints > a & waypoints < b));
reverse = -1;
endif
issingle = (isa (a, "single") || isa (b, "single")
|| isa (waypoints, "single"));
if (isempty (abstol))
abstol = ifelse (issingle, 1e-5, 1e-10);
elseif (! isscalar (abstol) || abstol < 0)
error ("quadgk: ABSTOL must be a scalar >=0");
endif
if (isempty (reltol))
reltol = ifelse (issingle, 1e-4, 1e-6);
elseif (! isscalar (reltol) || reltol < 0)
error ("quadgk: RELTOL must be a scalar >=0");
endif
## FIXME: No validation of inputs MaxIntervalCount, Waypoints, ArrayValued,
## Trace.
## Convert function given as a string to a function handle
if (ischar (f))
f = @(x) feval (f, x);
endif
## Use variable substitution to weaken endpoint singularities and
## to perform integration with endpoints at infinity.
## No transform for contour integrals.
if (contour)
## contour integral, no transform
subs = [a; waypoints; b];
h = sum (abs (diff (subs)));
trans = @(t) t;
## Ensure f is always vectorized even if specified as, e.g., f = @(x) 1;
f = @(t) f (t) + 0*t;
elseif (isinf (a) && isinf (b))
## Standard infinite to finite integral transformation.
## \int_{-\infinity_^\infinity f(x) dx = \int_-1^1 f (g(t)) g'(t) dt
## where
## g(t) = t / (1 - t^2)
## g'(t) = (1 + t^2) / (1 - t^2) ^ 2
## waypoint transform is then
## t = (2 * g(t)) ./ (1 + sqrt(1 + 4 * g(t) .^ 2))
if (! isempty (waypoints))
trans = @(x) (2 * x) ./ (1 + sqrt (1 + 4 * x .^ 2));
subs = [-1; trans(waypoints); 1];
else
subs = linspace (-1, 1, 11)';
endif
h = 2;
trans = @(t) t ./ (1 - t.^2);
f = @(t) f (t ./ (1 - t .^ 2)) .* (1 + t .^ 2) ./ ((1 - t .^ 2) .^ 2);
elseif (isinf (a))
## Formula defined in Shampine paper as two separate steps.
## One to weaken singularity at finite end, then a second to transform to
## a finite interval. The singularity weakening transform is
## \int_{-\infinity}^b f(x) dx =
## - \int_{-\infinity}^0 f (b - t^2) 2 t dt
## (note minus sign) and the finite interval transform is
## \int_{-\infinity}^0 f(b - t^2) 2 t dt =
## \int_{-1}^0 f (b - g(s) ^ 2) 2 g(s) g'(s) ds
## where
## g(s) = s / (1 + s)
## g'(s) = 1 / (1 + s) ^ 2
## waypoint transform is then
## t = sqrt (b - x)
## s = - t / (t + 1)
if (! isempty (waypoints))
tmp = sqrt (b - waypoints);
trans = @(x) - x ./ (x + 1);
subs = [-1; trans(tmp); 0];
else
subs = linspace (-1, 0, 11)';
endif
h = 1;
trans = @(t) b - (t ./ (1 + t)).^2;
f = @(s) - 2 * s .* f (b - (s ./ (1 + s)) .^ 2) ./ ((1 + s) .^ 3);
elseif (isinf (b))
## Formula defined in Shampine paper as two separate steps.
## One to weaken singularity at finite end, then a second to transform to
## a finite interval. The singularity weakening transform is
## \int_a^\infinity f(x) dx = \int_0^\infinity f (a + t^2) 2 t dt
## and the finite interval transform is
## \int_0^\infinity f(a + t^2) 2 t dt =
## \int_0^1 f (a + g(s) ^ 2) 2 g(s) g'(s) ds
## where
## g(s) = s / (1 - s)
## g'(s) = 1 / (1 - s) ^ 2
## waypoint transform is then
## t = sqrt (x - a)
## s = t / (t + 1)
if (! isempty (waypoints))
tmp = sqrt (waypoints - a);
trans = @(x) x ./ (x + 1);
subs = [0; trans(tmp); 1];
else
subs = linspace (0, 1, 11)';
endif
h = 1;
trans = @(t) a + (t ./ (1 - t)).^2;
f = @(s) 2 * s .* f (a + (s ./ (1 - s)) .^ 2) ./ ((1 - s) .^ 3);
else
## Davis, Rabinowitz, "Methods of Numerical Integration" p441 2ed.
## Presented in section 5 of the Shampine paper as
## g(t) = ((b - a) / 2) * (t / 2 * (3 - t^2)) + (b + a) / 2
## g'(t) = ((b-a)/4) * (3 - 3t^2);
## waypoint transform can then be found by solving for t with
## Maxima (solve (c + 3*t - 3^3, t);). This gives 3 roots, two of
## which are complex for values between a and b and so can be ignored.
## The third is
## c = (-4*x + 2*(b+a)) / (b-a);
## k = ((sqrt(c^2 - 4) + c)/2)^(1/3);
## t = (sqrt(3)* 1i * (1 - k^2) - (1 + k^2)) / 2 / k;
if (! isempty (waypoints))
trans = @__quadgk_finite_waypoint__;
subs = [-1; trans(waypoints, a, b); 1];
else
subs = linspace (-1, 1, 11)';
endif
h = 2;
trans = @(t) ((b - a) ./ 4) * t .* (3 - t.^2) + (b + a) ./ 2;
f = @(t) f((b - a) ./ 4 .* t .* (3 - t.^2) + (b + a) ./ 2) .* ...
3 .* (b - a) ./ 4 .* (1 - t.^2);
endif
## Split interval into at least 10 subinterval with a 15 point
## Gauss-Kronrod rule giving a minimum of 150 function evaluations.
while (numel (subs) < 11)
subs = [subs.' ; subs(1:end-1).' + diff(subs.') ./ 2, NaN](:)(1:end-1);
endwhile
subs = [subs(1:end-1), subs(2:end)];
warn_id = "Octave:quadgk:warning-termination";
if (! arrayvalued)
## Initial evaluation of the integrand on the subintervals.
[q_subs, q_errs] = __quadgk_eval__ (f, subs, trans);
q0 = sum (q_subs);
err0 = sum (q_errs);
first = true;
while (true)
## Quit if any evaluations are not finite (Inf or NaN).
if (any (! isfinite (q_subs)))
warning (warn_id, "quadgk: non-finite integrand encountered");
q = q0;
err = err0;
break;
endif
tol = max (abstol, reltol .* abs (q0));
## If the global error estimate is met then exit.
if (err0 <= tol)
q = q0;
err = err0;
break;
endif
## Accept the subintervals that meet the convergence criteria.
idx = find (abs (q_errs) < tol .* abs (diff (subs, 1, 2)) ./ h);
if (first)
q = sum (q_subs(idx));
err = sum (q_errs(idx));
first = false;
else
q0 = q + sum (q_subs);
err0 = err + sum (q_errs);
q += sum (q_subs(idx));
err += sum (q_errs(idx));
endif
subs(idx,:) = [];
## If no remaining subintervals then exit.
if (isempty (subs))
break;
endif
if (trace)
disp ([rows(subs), err, q0]);
endif
## Split remaining subintervals in two
mid = (subs(:,1) + subs(:,2)) ./ 2;
subs = [subs(:,1), mid; mid, subs(:,2)];
## If the maximum subinterval count is met, then
## accept remaining subinterval and exit.
if (rows (subs) > maxint)
warning (warn_id, "quadgk: maximum interval count (%d) exceeded", maxint);
q += sum (q_subs);
err += sum (q_errs);
break;
endif
## Evaluation of the integrand on the remaining subintervals
[q_subs, q_errs] = __quadgk_eval__ (f, subs, trans);
endwhile
if (nargout < 2 && err > max (abstol, reltol * abs (q)))
warning (warn_id,
"quadgk: Error tolerance not met. Estimated error %g", err);
endif
## Reverse integral if necessary.
q = reverse * q;
else
## f is array-valued
sz = size (f (subs(1)));
## Initial evaluation of the integrand on the subintervals
[q_subs, q_errs] = __quadgk_eval_array__ (f, subs, trans, prod (sz));
q0 = sum (q_subs, 1);
err0 = sum (q_errs, 1);
first = true;
while (true)
## Quit if any evaluations are not finite (Inf or NaN).
if (any (! isfinite (q_subs)(:)))
warning (warn_id, "quadgk: non-finite integrand encountered");
q = q0;
err = err0;
break;
endif
tol = max (abstol, reltol .* abs (q0));
## If the global error estimate is met then exit
if (err0 <= tol)
q = q0;
err = err0;
break;
endif
## Accept subintervals that meet the convergence criteria in all entries.
idx = find (all (abs (q_errs) < tol .* abs (diff (subs, 1, 2)) ./ h, 2));
if (first)
q = sum (q_subs(idx,:), 1);
err = sum (q_errs(idx,:), 1);
first = false;
else
q0 = q + sum (q_subs, 1);
err0 = err + sum (q_errs, 1);
q += sum (q_subs(idx,:), 1);
err += sum (q_errs(idx,:), 1);
endif
subs(idx,:) = [];
## If no remaining subintervals exit
if (isempty (subs))
break;
endif
if (trace)
disp ([rows(subs), err(1, 1), q0(1, 1)]); # print only first entry
endif
## Split remaining subintervals in two
mid = (subs(:,1) + subs(:,2)) ./ 2;
subs = [subs(:,1), mid; mid, subs(:,2)];
## If the maximum subinterval count is met accept remaining subinterval
## and exit
if (rows (subs) > maxint)
warning (warn_id, "quadgk: maximum interval count (%d) exceeded", maxint);
q += sum (q_subs, 1);
err += sum (q_errs, 1);
break;
endif
## Evaluation of the integrand on the remaining subintervals
[q_subs, q_errs] = __quadgk_eval_array__ (f, subs, trans, prod (sz));
endwhile
i = find (err > max (abstol, reltol * abs (q)), 1);
if (nargout < 2 && length (i) > 0)
## like ind2sub, only as vector.
j = mod (floor ((i-1)./cumprod ([1 sz(1:end-1)])),sz)+1;
s = ["(" sprintf("%d,",j)(1:end-1) ")"];
warning (warn_id,
"quadgk: Error tolerance not met. First entry at index %s with estimated error %g", s, err(i));
endif
q = reverse * reshape (q, sz);
err = reshape (err, sz);
endif
endfunction
function [q, err] = __quadgk_eval__ (f, subs, trans)
## A (15,7) point pair of Gauss-Kronrod quadrature rules.
## The abscissa and weights are copied directly from dqk15w.f from quadpack.
persistent abscissa = [-0.9914553711208126e+00, -0.9491079123427585e+00, ...
-0.8648644233597691e+00, -0.7415311855993944e+00, ...
-0.5860872354676911e+00, -0.4058451513773972e+00, ...
-0.2077849550078985e+00, 0.0000000000000000e+00, ...
0.2077849550078985e+00, 0.4058451513773972e+00, ...
0.5860872354676911e+00, 0.7415311855993944e+00, ...
0.8648644233597691e+00, 0.9491079123427585e+00, ...
0.9914553711208126e+00];
persistent weights15 = ...
diag ([0.2293532201052922e-01, 0.6309209262997855e-01, ...
0.1047900103222502e+00, 0.1406532597155259e+00, ...
0.1690047266392679e+00, 0.1903505780647854e+00, ...
0.2044329400752989e+00, 0.2094821410847278e+00, ...
0.2044329400752989e+00, 0.1903505780647854e+00, ...
0.1690047266392679e+00, 0.1406532597155259e+00, ...
0.1047900103222502e+00, 0.6309209262997855e-01, ...
0.2293532201052922e-01]);
persistent weights7 = ...
diag ([0.1294849661688697e+00, 0.2797053914892767e+00, ...
0.3818300505051889e+00, 0.4179591836734694e+00, ...
0.3818300505051889e+00, 0.2797053914892767e+00, ...
0.1294849661688697e+00]);
halfwidth = diff (subs, 1, 2) ./ 2;
center = sum (subs, 2) ./ 2;
t = (halfwidth * abscissa) + center;
x = trans ([t(:,1), t(:,end)]);
y = reshape (f (t(:)), size (t));
## This is faster than using bsxfun as the * operator can use a
## single BLAS call, rather than rows (sub) calls to the @times function.
q = sum (y * weights15, 2) .* halfwidth;
err = abs (sum (y(:,2:2:end) * weights7, 2) .* halfwidth - q);
endfunction
function [q, err] = __quadgk_eval_array__ (f, subs, trans, nel)
## A (15,7) point pair of Gauss-Kronrod quadrature rules.
## The abscissa and weights are copied directly from dqk15w.f from quadpack.
persistent abscissa = [-0.9914553711208126e+00, -0.9491079123427585e+00, ...
-0.8648644233597691e+00, -0.7415311855993944e+00, ...
-0.5860872354676911e+00, -0.4058451513773972e+00, ...
-0.2077849550078985e+00, 0.0000000000000000e+00, ...
0.2077849550078985e+00, 0.4058451513773972e+00, ...
0.5860872354676911e+00, 0.7415311855993944e+00, ...
0.8648644233597691e+00, 0.9491079123427585e+00, ...
0.9914553711208126e+00];
persistent weights15 = ...
[0.2293532201052922e-01, 0.6309209262997855e-01, ...
0.1047900103222502e+00, 0.1406532597155259e+00, ...
0.1690047266392679e+00, 0.1903505780647854e+00, ...
0.2044329400752989e+00, 0.2094821410847278e+00, ...
0.2044329400752989e+00, 0.1903505780647854e+00, ...
0.1690047266392679e+00, 0.1406532597155259e+00, ...
0.1047900103222502e+00, 0.6309209262997855e-01, ...
0.2293532201052922e-01];
persistent weights7 = ...
[0.1294849661688697e+00, 0.2797053914892767e+00, ...
0.3818300505051889e+00, 0.4179591836734694e+00, ...
0.3818300505051889e+00, 0.2797053914892767e+00, ...
0.1294849661688697e+00];
halfwidth = diff (subs, 1, 2) ./ 2;
center = sum (subs, 2) ./ 2;
t = (halfwidth * abscissa) + center;
x = trans ([t(:,1), t(:,end)]);
y = zeros (nel, columns(t), rows(t));
for i = 1:rows (t)
for j = 1:columns(t)
y(:,j,i) = f (t(i,j))(:);
endfor
endfor
y = permute (y, [2 3 1]);
q = reshape (weights15 * y(:,:), [rows(t), nel]) .* halfwidth;
err = abs (reshape (weights7 * y(2:2:end,:), rows (t), nel) .* halfwidth - q);
endfunction
function t = __quadgk_finite_waypoint__ (x, a, b)
c = (-4 .* x + 2.* (b + a)) ./ (b - a);
k = ((sqrt (c .^ 2 - 4) + c) ./ 2) .^ (1/3);
t = real ((sqrt (3) .* 1i * (1 - k .^ 2) - (1 + k .^ 2)) ./ 2 ./ k);
endfunction
%!assert (quadgk (@sin,-pi,pi), 0, 1e-10)
%!test
%! warning ("off", "Octave:legacy-function", "local");
%! assert (quadgk (inline ("sin"), -pi, pi), 0, 1e-10);
%!assert (quadgk ("sin",-pi,pi), 0, 1e-10)
%!assert (quadgk (@sin,-pi,pi, "WayPoints", 0, "MaxIntervalCount", 100,
%! "RelTol", 1e-3, "AbsTol", 1e-6, "trace", false), 0, 1e-6)
%!assert (quadgk (@sin,-pi,pi, 1e-6, false), 0, 1e-6)
%!assert <*51867> (quadgk (@(x) x, 0, 0), 0, 0)
%!assert (quadgk (@sin,-pi,0), -2, 1e-10)
%!assert (quadgk (@sin,0,pi), 2, 1e-10)
%!assert (quadgk (@(x) 1./sqrt (x),0,1), 2, 1e-10)
%!assert (quadgk (@(x) abs (1 - x.^2),0,2, "Waypoints", 1), 2, 1e-10)
%!assert (quadgk (@(x) 1./(sqrt (x) .* (x+1)),0,Inf), pi, 1e-10)
%!assert <*57614> (quadgk (@(z) exp (z)./z, 1, 1,
%! "Waypoints", [1+i, -1+i, -1-i, 1-i]),
%! complex (0, 2*pi), 1e-10)
%!assert <*57614> (quadgk (@(z) exp (z)./z, 1, 1,
%! "Waypoints", [1-i, -1-i, -1+i, 1+i]),
%! complex (0, -2*pi), 1e-10)
%!assert (quadgk (@(z) log (z),1+1i,1+1i, "WayPoints", [1-1i, -1,-1i, -1+1i]),
%! complex (0, pi), 1e-10)
%!assert (quadgk (@(x) exp (-x .^ 2),-Inf,Inf), sqrt (pi), -1e-6)
%!assert (quadgk (@(x) exp (-x .^ 2),-Inf,0), sqrt (pi)/2, -1e-6)
%!test
%! f = @(x) x .^ 5 .* exp (-x) .* sin (x);
%! assert (quadgk (f, 0, Inf, "RelTol", 1e-8, "AbsTol", 1e-12), -15, -1e-8);
## Test vector-valued functions
%!assert (quadgk (@(x) [(sin (x)), (sin (2 * x))], 0, pi, "arrayvalued", 1),
%! [2, 0], 1e-6)
## Test matrix-valued functions
%!assert (quadgk (@(x) [ x,x,x; x,1./sqrt(x),x; x,x,x ], 0, 1, "arrayvalued",1),
%! [0.5,0.5,0.5; 0.5,2,0.5; 0.5,0.5,0.5], 15*1e-6);
## Bug #62412
%!warning <Error tolerance not met>
%! f = @(t) -1 ./ t.^1.1;
%! quadgk (f, 1, Inf);
## Test input validation
%!error quadgk (@sin)
%!error quadgk (@sin, 0)
%!error <can not pass additional arguments> quadgk (@sin, 0, 1, 1e-6, true, 4)
%!error <options must occur in pairs> quadgk (@sin, 0, 1, "DummyArg")
%!error <PROP must be a string> quadgk (@sin, 0, 1, "AbsTol", 1e-6, 2, 3)
%!error <unknown property 'foo'> quadgk (@sin, 0, 1, "foo", 3)
%!error <ABSTOL must be a scalar> quadgk (@sin, 0, 1, ones (2,2))
%!error <ABSTOL must be a scalar .=0> quadgk (@sin, 0, 1, -1)
%!error <RELTOL must be a scalar> quadgk (@sin, 0, 1, "RelTol", ones (2,2))
%!error <RELTOL must be a scalar> quadgk (@sin, 0, 1, "RelTol", -1)
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