New answers tagged performance-tuning
1
Without knowing much about the data, it seems likely that it consists of numbers, and the the times and efficiencies are positive real numbers. Further I have to guess that
Select[EquipParams, #[[colEquipID]] == CurrentEquipID &][[;; , colOperatingDelayTime]]
returns a list consisting of a single number; otherwise, I cannot see how one would get ...
4
I was going to leave a comment, but without seeing the full code, I think it can be improved drastically.
At fault is that you are performing the same search every time through the loop. (If has the attribute HoldRest, so the branches are not executed unless they are used which means the search is re-executed every through.) So, at a minimum move the ...
5
Since no comment or answer has given as of the time I saw this post, and I don't have enough reputations to leave a comment, let me give a quick answer I used to solve the same kind of problems. I'm sure there must be a better way to do it with Mathematica, so this is just a beginning.
To evaluate an N-dimensional integral with a highly oscillatory ...
0
I just had something that sounded like the same problem on a linux machine. In this case there was a folder in the home directory called .Mathematica, when I removed that and ran mathematica again it worked. I have to say that it is server set up mathematica, so thing might be different, but it could be worth a try.
2
The textbook algorithm, that is, row reducing {A, I} to {I, A^(-1)} works.
n = 1000;
m = Array[RandomInteger[{0, 1}]&, {n, n}];
m // MatrixPlot
MatrixRank[m, Modulus -> 2] (* see if m is full rank *)
inverse = With[{n = Length@#},
RowReduce[MapThread[Join, {#, IdentityMatrix[n]}], Modulus -> 2][[;;,n+1;;]]]&;
inverseM = inverse[m]; // ...
5
Obviously, for large negative inputs, Exp will produce very small numbers. While this isn't intrinsically problematic, it so happens that, by default, Mathematica deals with machine underflow by converting the affected values to an arbitrary precision representation in order to avoid catastrophic loss of precision. However, sometimes one would rather ...
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