In mpmath, what exactly does the maxdegree argument do?
A newbie here so please be gentle!
I'm using mpmath.quad to calculate a large number of integrals that are then being placed into a matrix for further calculation. My problem is that the integrands are oscillatory so the default degree of accuracy (maxdegree = 6) set by mpmath isn't enough to converge to an answer with a sensible level of error. I've upped the value of maxdegree to 25 and unless I use very oscillatory integrands then this solves the problem.
My question is: what exactly is this parameter doing? Obviously it's utilising more iterations of whatever algorithm it uses to solve the integral, but if for example I were to set it to maxdegree=1000, should I expect it to reach some kind of limit to the accuracy, or to carry out 1000 iterations for each integral?
This is probably better explained by asking, if I have an integral and the answer at iteration 10 is 1.09758354e-10 with an error of 2e-13, will the algorithm keep going until it hits floating point accuracy and then give up, or just keep calculating another 990 iterations that essentially change nothing?
Thanks! :)
python python-3.x spyder mpmath
edited Nov 26 '18 at 11:32
TrebuchetMS
2,62811023
asked Nov 26 '18 at 10:48
Chris WhiteChris White
11
add a comment |
A newbie here so please be gentle!
I'm using mpmath.quad to calculate a large number of integrals that are then being placed into a matrix for further calculation. My problem is that the integrands are oscillatory so the default degree of accuracy (maxdegree = 6) set by mpmath isn't enough to converge to an answer with a sensible level of error. I've upped the value of maxdegree to 25 and unless I use very oscillatory integrands then this solves the problem.
My question is: what exactly is this parameter doing? Obviously it's utilising more iterations of whatever algorithm it uses to solve the integral, but if for example I were to set it to maxdegree=1000, should I expect it to reach some kind of limit to the accuracy, or to carry out 1000 iterations for each integral?
This is probably better explained by asking, if I have an integral and the answer at iteration 10 is 1.09758354e-10 with an error of 2e-13, will the algorithm keep going until it hits floating point accuracy and then give up, or just keep calculating another 990 iterations that essentially change nothing?
Thanks! :)
python python-3.x spyder mpmath
edited Nov 26 '18 at 11:32
TrebuchetMS
2,62811023
asked Nov 26 '18 at 10:48
Chris WhiteChris White
11
add a comment |
A newbie here so please be gentle!
I'm using mpmath.quad to calculate a large number of integrals that are then being placed into a matrix for further calculation. My problem is that the integrands are oscillatory so the default degree of accuracy (maxdegree = 6) set by mpmath isn't enough to converge to an answer with a sensible level of error. I've upped the value of maxdegree to 25 and unless I use very oscillatory integrands then this solves the problem.
My question is: what exactly is this parameter doing? Obviously it's utilising more iterations of whatever algorithm it uses to solve the integral, but if for example I were to set it to maxdegree=1000, should I expect it to reach some kind of limit to the accuracy, or to carry out 1000 iterations for each integral?
This is probably better explained by asking, if I have an integral and the answer at iteration 10 is 1.09758354e-10 with an error of 2e-13, will the algorithm keep going until it hits floating point accuracy and then give up, or just keep calculating another 990 iterations that essentially change nothing?
Thanks! :)
python python-3.x spyder mpmath
edited Nov 26 '18 at 11:32
TrebuchetMS
2,62811023
asked Nov 26 '18 at 10:48
Chris WhiteChris White
11
A newbie here so please be gentle!
I'm using mpmath.quad to calculate a large number of integrals that are then being placed into a matrix for further calculation. My problem is that the integrands are oscillatory so the default degree of accuracy (maxdegree = 6) set by mpmath isn't enough to converge to an answer with a sensible level of error. I've upped the value of maxdegree to 25 and unless I use very oscillatory integrands then this solves the problem.
My question is: what exactly is this parameter doing? Obviously it's utilising more iterations of whatever algorithm it uses to solve the integral, but if for example I were to set it to maxdegree=1000, should I expect it to reach some kind of limit to the accuracy, or to carry out 1000 iterations for each integral?
This is probably better explained by asking, if I have an integral and the answer at iteration 10 is 1.09758354e-10 with an error of 2e-13, will the algorithm keep going until it hits floating point accuracy and then give up, or just keep calculating another 990 iterations that essentially change nothing?
Thanks! :)
python python-3.x spyder mpmath
python python-3.x spyder mpmath
edited Nov 26 '18 at 11:32
TrebuchetMS
2,62811023
asked Nov 26 '18 at 10:48
Chris WhiteChris White
11
edited Nov 26 '18 at 11:32
TrebuchetMS
2,62811023
asked Nov 26 '18 at 10:48
Chris WhiteChris White
11
edited Nov 26 '18 at 11:32
TrebuchetMS
2,62811023
edited Nov 26 '18 at 11:32
TrebuchetMS
2,62811023
edited Nov 26 '18 at 11:32
TrebuchetMS
2,62811023
2,62811023
asked Nov 26 '18 at 10:48
Chris WhiteChris White
11
asked Nov 26 '18 at 10:48
Chris WhiteChris White
11
asked Nov 26 '18 at 10:48
Chris WhiteChris White
11
11
add a comment |
add a comment |
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