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Support for displaying a trend line and embedding a right image #24
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Support for displaying a trend line and embedding a right image #24
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Could you write a doc string explaining what this does?
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Does it make sense to do this or to interpolate?
e.g. with numpy.interp
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The reason behind repeating these numbers it that the more samples we have, we can increase the polyfit order more liberally which smoothens the curve considerably.
I don't think that it would make much sense to first interpolate the curve and then fit it again.
Also, I found out about
np.repeat
. Removing this hacky repeat method.There was a problem hiding this comment.
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So the bottom is always zero?
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Ahm, I don't quite get the question.
If all the values in
yp
are equal, then we'd have an array of all 1's after normalization. Similarly for all zeroes, we'd have a flat line.Polyfit might return negative numbers sometime (
-1
at most). But, since we only scale up positive numbers (yp[yp > 0] *= ...
), and use an offset of-1
when defining the origin, it shouldn't be a problem.There was a problem hiding this comment.
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Could you write a doc string explaining what this does?