This is the third of four short posts about matten. The previous post covered the numeric core. This one covers a separate feature: ingesting messy, real-world data.
The problem
The numeric Tensor in the previous post is clean by construction: every cell is an f64. That is fine when your data is already clean. It is less fine when it arrives from a JSON API or a CSV file that has missing cells, integer values alongside floats, or the occasional boolean flag.
The dynamic feature adds an ingestion-and-cleanup layer for that case. It is not a second compute engine — you cannot do arithmetic on a dynamic tensor directly. The idea is simpler: ingest heterogeneous data, inspect and clean it, then convert explicitly to a numeric tensor when you are confident the data is ready.
Enable it:
