By default, return float64, but provide options for reading different formats.

I think it’s a good idea to return np.float32 by default (although I’m not 100% sure because the default type in NumPy is np.float64).

If the file has 64bit values, however, they shouldn’t be truncated by default.

So probably the default argument to read() should be format=None which should be changed appropriately within the function.

BTW, format may not be the best name choice for this parameter, maybe dtype would be rather what people would expect?

[bastibe]

subtype is a property of soundfile.SoundFile and can have any value of soundfile._subtypes.

[bastibe]

Interesting point. Come to think of it, I don’t see many reasons why we shouldn’t just switch everything over to np.float64 by default. In Numpy, pretty much everything is np.float64 by default.

The only argument against that would be that there is no microphone able to record more than 24 bits, let alone ears cabable of hearing more, which makes anything more than 32 bits kind of a waste. I can see 64 bit being useful for non-audio data though.

One could also make an argument that if the source data is, say, np.int16, read() should return exactly that. I don’t think there is much merit to this, though, since numpy integers violate too many pythonic assumptions about numbers (no infinite precision and overflow). How about providing something like read_native(), which would return the native data format of the file?