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Published 20 hours ago • verified publisher icon NRCan

BUG: scale to minmax range

Open valhassan opened this issue 9 months ago • 0 comments

Describe the bug The original min and max ranges are inferred from the array in this function. The correct case is to provide the range as parameters to avoid floating point errors "Expected: (0, 1) Actual: (-4.768371586472142e-09, 1.0000000190734863)"

https://github.com/NRCan/geo-deep-learning/blob/c4d4b75a58c51283db088421d16fe969e9929b74/utils/utils.py#L202-L220

To Reproduce Steps to reproduce the behavior:

  1. Test the function with an array of high-precision floating points that exceed the expected range (0, 1)

Expected behavior The function should scale based on the provided parameters and shift from dynamic to static scaling.

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valhassan avatar May 13 '24 19:05 valhassan