I think this is a floating point precision issue. https://docs.python.org/3.6/tutorial/floatingpoint.html
On Fri, Dec 15, 2017 at 1:40 PM, Jesper Larsen <jesper.webm...@gmail.com> wrote: > Hi numpy people, > > I was just wondering whether this behaviour is intended: > > >>> import numpy as np > >>> np.ma.masked_values(np.array([-32768.0]), np.int16(-32768)) > masked_array(data = [-32768.], > mask = False, > fill_value = -32768.0) > > So the resulting masked array is not masked. On the other hand it is > masked in the three cases below: > > >>> np.ma.masked_values(np.array([-32767.0]), np.int16(-32767)) > masked_array(data = [--], > mask = [ True], > fill_value = -32767.0) > > >>> np.ma.masked_values(np.array([-32768.0]), -32768.0) > masked_array(data = [--], > mask = [ True], > fill_value = -32768.0) > > >>> np.ma.masked_values(np.array([-32768.0]), -32768) > masked_array(data = [--], > mask = [ True], > fill_value = -32768.0) > > Best regards, > Jesper > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion > >
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