I’m guessing that you’re seeing the effects of floating point rounding.
numpy.arange does the same thing as python’s range: It doesn’t include the “endpoint”. (e.g. range(0, 4, 2) will yield [0,2] instead of [0,2,4])
However, for floating point steps, the rounding errors are accumulate, and occasionally the last value will actually include the endpoint.
As noted in the documentation for arange:
When using a non-integer step, such as 0.1, the results will often not
be consistent. It is better to uselinspacefor these cases.
numpy.linspace generates a specified number of points between a starting and ending point. Incidentally, it does include the endpoints by default.