a-nikolaev
Joined 14 years ago
Joined 14 years ago
And I usually keep computation and plotting separate. Computation produces data files, and a gnuplot script generates plots. This separation of computation and plotting allows updating charts later if needed, collected data can be reused in other plots, and additional data analysis can be performed and charts can be augmented.
So I personally don't see many advantages from integrating chart generation into computational pipeline itself (except for computation monitoring or maybe when user response is needed to direct computation). Because of that, libraries that encourage charts generation from a computed array instead of dumping that data into persisted files feels like an anti-pattern to me.
- yq changed its syntax between version 3 and 4 to be more like jq (but not quite the same for some reason)
- yq has no if-then-else https://github.com/mikefarah/yq/issues/95 which is a poor design (or omission) in my opinion
So yq works when you need to process YAML, it can even handle comments quite well. Buy for pure JSON processing jq is a better tool.
Keeping indexes/keys for references, and loops over these collections can do a lot without any upfront complexity of an entity system.
http://a-nikolaev.github.io/fp/ - if anyone is interested in more learning resources.
match a, b with
| 1, 2 -> x
| _ -> y