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MathGroup Archive 1998

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method to eliminate NIntegrate warning.


  • To: mathgroup@smc.vnet.net
  • Subject: [mg10537] method to eliminate NIntegrate warning.
  • From: "Soo-Hwan Kim" <kss@ssel.snu.ac.kr>
  • Date: Tue, 20 Jan 1998 02:23:23 -0500
  • Organization: Seoul National University, Republic of Korea

I want to know the method to eliminate NIntegrate warning.

The two warning message follows :

NIntegrate::slwcon:
   Numerical integration converging too slowly; suspect one of the
     following: singularity, oscillatory integrand, or insufficient
     WorkingPrecision.
NIntegrate::ncvb:
   NIntegrate failed to converge to prescribed accuracy after 7
     recursive bisections in x near x = 0.126684.

How can I escape from this problem ? When above-case happened, can I
believe the accuracy of my data ?

The two file which I used follows :

/********* program.ma file *************/

Result1=0;
m=9.11*10^-31;
e=1.60*10^-19;
Energy=0.5;
h=1.05458*10^-34;
Kx=(2*m*10^3*e*Energy)^(.5)/h;
data=ReadList["a.dat", Real];
num=Length[data];
For[i=1,i<=num,i++,
 phase[i]=data[[i]];
 Print[phase[i]];
]
f1[x_]=Sum[(2*i+1)*(Cos[2*phase[i+1]]-1)*LegendreP[i,Cos[x]],{i,0,num-1}];
f2[x_]=Sum[(2*i+1)*(Sin[2*phase[i+1]])*LegendreP[i,Cos[x]],{i,0,num-1}];
f3[x_]=f1[x]^2+f2[x]^2;
Kxx=1/(4*Kx^2);
Result=NIntegrate[f3[x]*Sin[x],{x,0,Pi}]; fil=OpenAppend["b.dat"];
Write[fil,2*3.141592*Kxx*Result];
For[c=1,c<=180,c++,
 Print[c];
 Result2=NIntegrate[f3[x]*Sin[x],{x,Pi/(180)*(c-1),Pi/(180)*c}
  ,MaxRecursion->0,AccuracyGoal->5];(* -> <<<Here : Warning Message>>>
*)
 Result1+=Result2;
  Write[fil,c,th,Result1/Result];


];
Close[fil];

/*************************************************/ /************ a.dat
file *************************/ 1.979491
1.319515
0.982686
0.773772
0.629903
0.524447
0.443828
0.380382
0.329298
0.287393
0.252482
0.223068
0.198016
0.176466
0.157811
0.141543
0.127341
0.114742
0.103576
0.093683
0.084864
0.076986
0.069930
0.063593
0.057875
0.052729
0.048075
0.043868
0.040043
0.036578
0.033437
0.030579
0.027981
0.025615
0.023461
0.021493
0.019704
0.018068
0.016574
0.015209
0.013952
0.012819
0.011767
0.010813
/*********************************/




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