We construct an `NDSolve`

method which can pass an `NIntegrate`

method to `NIntegrate`

to set up an integration rule. We define a method `nintegrate`

implements such a method. The requirements are

- the ODE is of the form
`y'(x) == f(x)`

, and - the
`NIntegrate`

method returns an interpolatory rule.

Example:

```
foo = NDSolveValue({y'(x) == Sin(x^2), y(0) == 0}, y, {x, 0, 15},
Method -> nintegrate, InterpolationOrder -> All)
```

Error plot:

```
Plot(
Evaluate@RealExponent(Integrate(Sin(x^2), x) - foo(x)),
{x, 0, 15},
GridLines -> {Flatten@foo@"Grid", None}, (* show steps *)
PlotRange -> {-18.5, 0.5})
```

Another example:

```
foo = NDSolveValue({y'(x) == Sin(x^2), y(0) == 0}, y, {x, 0, 15},
Method -> {nintegrate,
Method -> {"ClenshawCurtisRule", "Points" -> 33}},
InterpolationOrder -> All, WorkingPrecision -> 32,
PrecisionGoal -> 24, MaxStepFraction -> 1, StartingStepSize -> 15)
```

Error plot:

```
Block({$MaxExtraPrecision = 500},
ListLinePlot(
Integrate(Sin(x^2), x) - foo(x) /. x -> Subdivide(0, 15, 1000) //
RealExponent, DataRange -> {0, 15}, PlotRange -> {-35.5, 0.5},
GridLines -> {Flatten@foo@"Grid", None})
)
```

**Code for method**

```
nintegrate::nintode =
"Method nintegrate requires an ode of the form ``'(``) == f(``)";
nintegrate::nintinit =
"NIntegrate method `` did not return an interpolatory integration rule.";
nintegrate(___)("StepInput") = {"F"("T"), "H", "T", "X", "XP"};
nintegrate(___)("StepOutput") = {"H", "XI"};
nintegrate(rule_, order_, ___)("DifferenceOrder") := order;
nintegrate(___)("StepMode") := Automatic
Options@nintegrate = {Method -> "GaussKronrodRule"};
getorder(points_, method_) :=
Switch(method
, "GaussKronrodRule" | "GaussKronrod",
(* check points should be odd ??? *)
With({gp = (points - 1)/2},
If(OddQ(gp), 3 gp + 2, 3 gp + 1)
)
, "GauseBerntsenEspelidRule", 2 points - 1
, "LobattoKronrodRule",
(* check points should be odd ??? *)
With({glp = (points + 1)/2},
If(OddQ(glp), 3 glp - 2, 3 glp - 3)
)
, "GauseBerntsenEspelidRule",
2 points - 1
, "NewtonCotesRule",
If(OddQ(points), points, points - 1)
, _, points - 1
);
nintegrate /:
NDSolve`InitializeMethod(nintegrate, stepmode_, sd_, rhs_, state_,
mopts : OptionsPattern(nintegrate)) :=
Module({prec, order, norm, rule, xvars, tvar, imeth},
xvars = NDSolve`SolutionDataComponent(state@"Variables", "X");
tvar = NDSolve`SolutionDataComponent(state@"Variables", "T");
If(Length@xvars != 1,
Message(nintegrate::nintode, First@xvars, tvar, tvar);
Return($Failed));
If(! VectorQ(rhs("FunctionExpression")(
N@NDSolve`SolutionDataComponent(sd, "T"),
Sequence @@ xvars),
NumericQ
),
Message(nintegrate::nintode, First@xvars, tvar, tvar);
Return($Failed));
prec = state@"WorkingPrecision";
norm = state@"Norm";
imeth = Replace(Method /. mopts, Automatic -> "GaussKronrodRule");
rule =
NIntegrate(1, {x, 0, 1},
Method -> {"GlobalAdaptive", "SymbolicProcessing" -> 0,
Method -> imeth},
WorkingPrecision -> prec,
IntegrationMonitor :>
(Return(Through(#@"GetRule"), NIntegrate) &));
rule = Replace(rule, {
{(NIntegrate`GeneralRule | NIntegrate`ClenshawCurtisRule)(idata_)} :>
idata,
_NIntegrate :>
Return($Failed),
_ :> (* What happened here? *)
(Message(nintegrate::nintinit, Method -> imeth);
Return($Failed))
});
order =
getorder(Length@First@rule, imeth /. {m_String, ___} :> m);
nintegrate(rule, order, norm)
);
(rule : nintegrate(int_, order_, norm_, ___))(
"Step"(rhs_, h_, t_, x_, xp_)) :=
Module({prec, tt, xx, dx, normh, err, hnew, temp},
(* Norm scaling will be based on current solution y. *)
normh = (Abs(h) temp(#1, x) &) /. {temp -> norm};
tt = Rescale(int((1)), {0, 1}, {t, t + h});
xx = rhs /@ tt;
dx = h*int((2)).xx;
(* Compute scaled error estimate *)
err = h*int((3)).xx // normh;
hnew = Which(
err > 1 (* Rejected step: reduce h by half *)
, dx = $Failed; h/2
, err < 2^-(order + 2), 2 h
, err < 1/2, h
, True, h Max(1/2, Min(9/10, (1/(2 err))^(1/(order + 1))))
);
(* Return step data along with updated method data *)
{hnew, dx});
```