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Division by zero error in indicators. #637

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muazhari opened this issue Aug 16, 2024 · 0 comments · May be fixed by #668
Open

Division by zero error in indicators. #637

muazhari opened this issue Aug 16, 2024 · 0 comments · May be fixed by #668

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@muazhari
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muazhari commented Aug 16, 2024

Reproducible:
image
image

Suggestion:

  • Try to fix it by adding an exception in
    # if both are equal then set the upper bound to none (always the 0 or lower bound will be returned then)
    xu[xl == xu] = np.nan
    # store the lower and upper bounds
    self.xl, self.xu = xl, xu
    # check out when the input values are nan
    xl_nan, xu_nan = np.isnan(xl), np.isnan(xu)
    # now create all the masks that are necessary
    self.xl_only, self.xu_only = np.logical_and(~xl_nan, xu_nan), np.logical_and(xl_nan, ~xu_nan)
    self.both_nan = np.logical_and(np.isnan(xl), np.isnan(xu))
    self.neither_nan = ~self.both_nan
  • Try to fix it using epsilon, i.e. norm[norm==0] = np.finfo(norm.dtype).eps
@oliverweissl oliverweissl linked a pull request Dec 1, 2024 that will close this issue
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