Closed rbardenet closed 5 years ago
It's a good idea. I suggests to pick the most explicit names, and remove one-letter parameters, so chose size
or ndim
instead of N
or n
.
You're right @rbardenet, that is a bit confusing, since we a dealing with the size N
of a matrix, I am tempted to use N
but as @Naereen pointed out one-letter parameters are not recommended...
Btw, there are also the M
and M_1
, M_2
sizes for matrix sizes in other models.
What about:
dim_N
, dim_M
, dim_M1
, dim_M2
, orsize_N
, size_M
, size_M1
, size_M2
?Do as numpy and scipy do:
shape : int or sequence of ints
Shape of the new array, e.g., (2, 3) or 2.
? (cf source)
I'd go for 'size', which is the most explicit. I remember reading somewhere that being explicit in the names of your variables never hurts. Re:'shape', it's a good idea, but unless we are extremely careful to always conform to the numpy notation, I think it may bring confusion.
Hi @rbardenet and @Naereen,
Finally, I've opted for size_*
and completely reshape the BetaEnsemble
class #34
Check out the Tuto_DPPy or the HTML version for figures 😄
Right now, full matrix models have parameter 'N', while banded models have an equivalent parameter called 'size'. Do we want to have two denominations for the size of the matrix?