Hi Julia folks, Trying to get a feel for Julia, I decided to write a basic Cox proportional hazards model. While I was implementing the routines to calculate the gradient and Hessian of the model's log-likelihood, I realized that I was making a ton of array "type errors" (dimension errors) that weren't being caught by Julia's type system because the array operations that I was using were too overloaded. Here are some examples of what I mean:
- For a 2d array X, trying to get a row with X[i] instead of X[i,:]. This returns a scalar, but if you try to add it to another row vector you'll silently get a different row vector than you expected instead of a failure. - Reversing the order of y * transpose(y) (for y an array) to get the scalar product instead of the outer product (similar silent failure as above). - Doing y .* z when one side is a row vector and the other side is a column vector, and forgetting to transpose them, causing an accidental outer product (via broadcasting) instead of elementwise product. This one is harder to get a silent failure with but I'm pretty sure I managed somehow. I caught them all in testing (I think) and am fairly satisfied my code does the right thing now, but I'd love to know if there are conventions or tools I can use to limit these errors or catch them earlier. I'm sure I'm missing a ton of stuff because I'm a Julia novice (as well as a numerics novice in general). Does anyone have any pointers? If it helps, the code I wrote is here <https://github.com/benkuhn/Survival.jl/blob/master/survival/src/coxph.jl#L60> . (It's correct now, or at least agrees with R on a small but nontrivial model; the link is to the function that computes the Hessian of the log-likelihood, which was unsurprisingly the most error-prone part.) Thanks! Ben
