In Julia:
In [1]: M1 = [1 3 4;
45 64 33;
456 3 454;]
Out [1]: 3x3 Array{Int64,2}:
1 3 4
45 64 33
456 3 454
In [2]: M1 * inv(M1)
Out [2]: 3x3 Array{Float64,2}:
1.0 6.93889e-18 -8.67362e-19
0.0 1.0 -2.08167e-17
-1.42109e-14 -8.88178e-16 1.0
M1 * inv(M1) is supposed to get the Identity matrix by definition. What's wrong?
I tried the same thing in Matlab:
>> M1 = [1 3 4;
45 64 33;
456 3 454;]
M1 =
1 3 4
45 64 33
456 3 454
>> inv(M1)
ans =
-0.280088987764182 0.013057987135465 0.001518595540939
0.052057842046719 0.013251438796731 -0.001421869710306
0.280978865406007 -0.013203075881414 0.000686753397495
>> M1 * inv(M1)
ans =
1.000000000000000 0.000000000000000 -0.000000000000000
0 1.000000000000000 -0.000000000000000
-0.000000000000014 -0.000000000000001 1.000000000000000
>>
Matlab returns the right result here. I guess Julia will not make a mistake here. So what's wrong with my calculation / notation?
Edit
The problem is caused by number of digits in floating point result. I should have asked, how to set result digits precision in Julia?
Julia and Matlab actually give the same result (for instance, the bottom-left element is -1.4e-14 in both cases): it is not exactly the identity matrix because floating point arithmetic is not exact.
You can explicitly round the result before displaying it.
If you want an exact result, you can also use rationals.