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simple integrals give give difficult results - Сообщения
#1 Опубликовано: 12.08.2019 16:52:05
Integrating the simple functions 1/x, 1/x², 1/x³ upwards from 1 give correct results for low values of the upper limit but with the upper limit in the order of 200 or higher the results are not what I would expect. Please see the attached worksheet.
Is there a problem with the integral function or is there something I haven't grasped?
H
integral.sm (5 КиБ) скачан 33 раз(а).
Is there a problem with the integral function or is there something I haven't grasped?
H
integral.sm (5 КиБ) скачан 33 раз(а).
#2 Опубликовано: 13.08.2019 01:33:32
Hi. It's because the integral it's a numerical procedure, and maybe not a very robust one. So, like any numerical method, if it don't work, just use another.
integral.sm (13 КиБ) скачан 35 раз(а).
Best regards.
Alvaro.
integral.sm (13 КиБ) скачан 35 раз(а).
Best regards.
Alvaro.
#3 Опубликовано: 13.08.2019 05:04:21
Hakelm,
I opened your file and the results were correct. Therefore I believe that the parameter for the accuracy of the integrals in your SMath installation is not correctly set.
Try to change Tools->Options->Calculation->Integral Accuracy
For example, write 1000
However, Alvaro's considerations must be kept in mind
sergio
I opened your file and the results were correct. Therefore I believe that the parameter for the accuracy of the integrals in your SMath installation is not correctly set.
Try to change Tools->Options->Calculation->Integral Accuracy
For example, write 1000
However, Alvaro's considerations must be kept in mind
sergio
#4 Опубликовано: 13.08.2019 06:50:17
Many thanks for two very good answers!
Now I know that Smath doesn't know even the simplest of integrals but that approximation accuracy can be improved upon.
Even if I understand my system doesn't (SMathStudioDesktop.0_99_7109.Mono on Ubuntu 16.04).
It can't find the function Rkadapt.
I guess that the Runge-Kutta functions are to be found i some plugin. Where can I find that?
H
Now I know that Smath doesn't know even the simplest of integrals but that approximation accuracy can be improved upon.
Even if I understand my system doesn't (SMathStudioDesktop.0_99_7109.Mono on Ubuntu 16.04).
It can't find the function Rkadapt.
I guess that the Runge-Kutta functions are to be found i some plugin. Where can I find that?
H
#5 Опубликовано: 13.08.2019 08:44:46
WroteI guess that the Runge-Kutta functions are to be found i some plugin. Where can I find that?
ODE Solvers.
Russia ☭ forever, Viacheslav N. Mezentsev
#6 Опубликовано: 13.08.2019 10:35:06
WroteIs there a problem with the integral function or is there something I haven't grasped?
The Simpson integrator ranges from exact to freak.
In your examples, increase the integral accuracy from
menu, options, calculations, integral accuracy [max 10000]
Wise to sanity Wolfram Alpha cost is 0.00 $
integral.sm (46 КиБ) скачан 30 раз(а).
#7 Опубликовано: 14.08.2019 10:19:49
May I assume that the SMath-integral is made using Simpson's rule and that the integral accuracy [max 10000] is the number of steps taken by Simpson?
H
H
#8 Опубликовано: 14.08.2019 11:14:29
WroteMay I assume that the SMath-integral is made using Simpson's rule and that the integral accuracy [max 10000] is the number of steps taken by Simpson?
Quite right: The Smath integrator is Simpson.
Ranged accuracy [50 ... 10000]. Trivial cases are exact.
Two more exact cases are know 1/x [ln(x), b_spline].
On long range of the variate 'x' the Simpson/Romberg kernel
gives a much better result than simple Simpson.
Carlos adaptive algorithm is fool proof all cases.
You want these two proposed ... reply YES/NO.
Jean
#9 Опубликовано: 14.08.2019 13:53:22
Yes please
H
H
#10 Опубликовано: 14.08.2019 19:07:51
As you can see, Romberg has the virtue of reducing the range of integration
in the [0 ... 1 ] domain. In two versions directly associated with the
Smath native Simpson integrator or Simpson algo style, thus integration
accuracy 'n' @ the user command line.
These two documents are like minimalist tool box.
Jean

Integrate Compendium_1 Romberg_FD_Adaptive [Carlos].sm (142 КиБ) скачан 31 раз(а).
Integrate Compendium_21 Simpson-Romberg Merit.sm (138 КиБ) скачан 26 раз(а).
in the [0 ... 1 ] domain. In two versions directly associated with the
Smath native Simpson integrator or Simpson algo style, thus integration
accuracy 'n' @ the user command line.
These two documents are like minimalist tool box.
Jean
Integrate Compendium_1 Romberg_FD_Adaptive [Carlos].sm (142 КиБ) скачан 31 раз(а).
Integrate Compendium_21 Simpson-Romberg Merit.sm (138 КиБ) скачан 26 раз(а).
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