[gus_massa]

It's possible to have a "sparse" matrixes where most of the values are 0 and only a few are not null. So you can guess 0 and cross your fingers.

(There are libraries that implement sparse matrixes in a more memory efficient way. I needed them for a program in Python, but I'm not an expert in Python. I found a few ways, but they are only useful for big matrixes with very few coeficients and have other restrictions to get an improved speed. I finaly gave up and used a normal np matrixes.)

[bee_rider]

How sparse is your matrix?

[gus_massa]

In the last case they were like 100x100, but only two rows or columns were not zero, so only 2% full. We were using einsums to multiply them with 4D arrays, and I solved the problem writing some code with @guvectorize.

In al old case they like 1000x1000, like a block checkboard where one of the colors had only 0, so like 50% full, but the blocks had different sizes. It was an old project in Fortran, and we used a "for"(do) for the blocks and another inside each block.

[bee_rider]

Neat. That’s fairly sparse. I’m 0% surprised to hear that small sparse matrices haven’t got as existing code out there, seems like a good excuse to roll your own :)