🧰 Task
Our vispy/gpu pipeline only supports int8, uint8, int16, uint16, float32, other dtypes get coerced during slicing.
This has a pretty significant performance implication for large slices of e.g. float64 or in64 data.
See also: napari/napari#1300 (comment)
Importantly, many numpy functions can produce float64 or int64 by default, triggering this issue.
We should raise more awareness of this in the documentation and possibly add an in-depth look at the data handling pipeline from Layer.data to the displayed gpu texture.
🧰 Task
Our vispy/gpu pipeline only supports int8, uint8, int16, uint16, float32, other dtypes get coerced during slicing.
This has a pretty significant performance implication for large slices of e.g. float64 or in64 data.
See also: napari/napari#1300 (comment)
Importantly, many numpy functions can produce float64 or int64 by default, triggering this issue.
We should raise more awareness of this in the documentation and possibly add an in-depth look at the data handling pipeline from Layer.data to the displayed gpu texture.