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Hi Taka,
Great lib : ) I have a design question --
Some methods take DTM data as input, while others don't.
Let's use this as an example --
dtm.gen("sine").fit(10).amp(2)
I can use a dtm data object as input to the amp()
method.
dtm.gen("sine").fit(10).amp( dtm.ri(200,0,1) )
But, there are other functions where I cannot use a dtm data object as input. fit()
is one of those methods. This will not work:
dtm.gen("sine").fit( dtm.ri(1,5,10) ).amp(2)
I understand that
- this is an odd use case, because
.fit()
needs exactly one number as input - I could use dtm.ri(1,5,10).get(0) to return the first number, which would work.
But I wonder what you think about the idea of allowing DTM arrays as inputs into more methods? This could become a more common use case if anyone wants to write DTM code that is evaluated more than once
Or, it could even open up new territories, for example, this could have a different 'fit' length for each of the 5 repetitions.
dtm.gen("line").rep(5).fit( dtm.ri(5,5,10) )
Let me know what you think!
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