Gunnstein
Error in find_rainflow_ranges for boundary cases
find_rainflow_ranges gives error for arbitrary numpy array. For example if the array doesn't contain any cycles - fatpack.find_rainflow_ranges(np.array([1,2,3,4,5]), return_means=True, k=2**14) produces error.
Hey @abhijeet-pandey,
Since you mention "arbitrary": Are there more cases which gives error than if an array does not contain any cycles?
For the case of no cycles in the array, there should at the very least be a different error (FatpackError?) and more descriptive error message. A better solution would perhaps be if an empty array was returned since there are no cycles. I will think a bit more on this issue, but I welcome any help or comments.
Best regards, Gunnstein
I agree, that in case of no cycles - it should return empty array or None. Yes, I did observe this error on a long data set (gigabyte size) that I had which is hard to share. One characteristic of the data was that it had sections with no cycles. Hence, I tried fatpack with artificial data with no cycles and was able to reproduce the same error. I hacked myself out of this error by using a try-except block over the if statement throwing the error and do nothing (do a "pass") in case of an exception. This may not be a correct approach though.
Just thinking out loud but would a strain history of np.array([1,2,3,4,5] result in a single residual/half cycle as there is a cycle initiated but not closed.
Half cycle as per the pagoda method.
On Mon, 26 June 2023, 19:43 wweijtje, @.***> wrote:
Just thinking out loud but would a strain history of np.array([1,2,3,4,5] result in a single residual/half cycle as there is a cycle initiated but not closed.
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