the answer is in the links -- just to demonstrate or validate what it says:
First@Last@
Reap@NIntegrate[Sin[x], {x, 0, 1}, EvaluationMonitor :> Sow[x],
MaxRecursion -> 0, Method -> "GaussKronrodRule"]
xi=First@Last@
Reap@NIntegrate[Sin[x], {x, 0, 1}, EvaluationMonitor :> Sow[x],
MaxRecursion -> 0]
{0.00795732, 0.0469101, 0.122917, 0.230765, 0.360185, 0.5, 0.639815,
0.769235, 0.877083, 0.95309, 0.992043}
{0.00795732, 0.0469101, 0.122917, 0.230765, 0.360185, 0.5, 0.639815,
0.769235, 0.877083, 0.95309, 0.992043}
the default uses the same evaluation points as the "GaussKronrodRule"
method.
You can then pull out the weights like this:
w=(f[x_?NumericQ] := Boole[x == #];
Quiet@NIntegrate[f[x], {x, 0, 1}, MaxRecursion -> 0]) & /@ xi
{0.021291, 0.0576167, 0.0934004, 0.12052, 0.136425, 0.141494,
0.136425, 0.12052, 0.0934004, 0.0576167, 0.021291}
and show they are of course the same whether you specify "GaussKronrodRule"
or nothing.
for completeness, just to show the weight extraction is correct:
{w.Sin[xi] , NIntegrate[Sin[x], {x, 0, 1}]}
SameQ @@ %
{0.459698, 0.459698}
True
Finally note, even with MaxRecursions->0
the automatic method can change, for example if it detects an oscilatory function:
First@Last@Reap@NIntegrate[Sin[4 x], {x, 0, 1}, EvaluationMonitor :> Sow[x],
MaxRecursion -> 0]
{1., 0.996057, 0.984292, 0.964888, 0.938153, 0.904508, 0.864484,
0.818712, 0.767913, 0.71289, 0.654508, 0.593691, 0.531395, 0.468605,
0.406309, 0.345492, 0.28711, 0.232087, 0.181288, 0.135516, 0.0954915,
0.0618467, 0.0351118, 0.0157084, 0.00394265, 0.}
NIntegrate[]
uses"GlobalAdaptive"
as the integration strategy, with the Gauss-Kronrod rule as the integration rule. Here is a related question. $\endgroup$