Erik Erlandson

Results 47 issues of Erik Erlandson

**What is the goal / desired outcome?** Run jupyterlab with pachyderm extension in OpenShift (which does not allow running containers as root by default) **If there is a way to...

feature request

This will be my tracking issue for figuring out how to approach scala 3 ### branching coulomb for scala 3 will start as a PR, but once it merges I'm...

This will require something closer to https://github.com/apache/avro/pull/841, but will make it more portable to scala.js for example

I'd consider even making `V %% U` the primary type and `Quantity` the synonym for backward compatability. Related - use `%%%` for OffsetQuantity? Are there good synonyms for `Temperature` and...

My explorations of unit analysis for matrix and vector math are promising: http://erikerlandson.github.io/blog/2020/05/01/unit-analysis-for-linear-algebra/ Not sure what the best vehicle is, maybe Spark Dataset as the representation for "tabular matrix". See...

the integration with `Refined` turned up an interesting pattern. the implementations of operations looked like this: ```scala new UnitAdd[Refined[V1, P1], U1, Refined[V2, P2], U2] { def vadd(v1: Refined[V1, P1], v2:...

The main counter-argument is whether it's more meaningful to support different units for each component.

```scala trait Fruit trait Apple extends Fruit trait Pear extends Fruit val q1 = 1.withUnit[Apple] + 1.withUnit[Pear] // is q1 Quantity[Int, Fruit] ? def f1(f: Quantity[Int, Fruit]) = { ......

CoulombVector, CoulombList, etc. It is straightforward to declare Vector[Quantity[...]] but more efficient to abstract out the unit types

I don't know all the context or use cases for `shapeless.Nat` support in `refined` (or singleton-ops), but superficially the ability to write `TypeName[3]` makes something like `TypeName[shapeless.nat._3]` obsolete. It has...