User guide

CHAPTER

FOUR

MISCELLANEOUS

4.1 IEEE 754 Floating Point Special Values

Special values deﬁned in numpy: nan, inf,

NaNs can be used as a poor-man’s mask (if you don’t care what the original value was)

Note: cannot use equality to test NaNs. E.g.:

>>> myarr = np.array([1., 0., np.nan, 3.])

>>> np.where(myarr == np.nan)

>>> np.nan == np.nan # is always False! Use special numpy functions instead.

False

>>> myarr[myarr == np.nan] = 0. # doesn’t work

>>> myarr

array([ 1., 0., NaN, 3.])

>>> myarr[np.isnan(myarr)] = 0. # use this instead find

>>> myarr

array([ 1., 0., 0., 3.])

Other related special value functions:

isinf(): True if value is inf

isfinite(): True if not nan or inf

nan_to_num(): Map nan to 0, inf to max float, -inf to min float

The following corresponds to the usual functions except that nans are excluded from the results:

nansum()

nanmax()

nanmin()

nanargmax()

nanargmin()

>>> x = np.arange(10.)

>>> x[3] = np.nan

>>> x.sum()

nan

>>> np.nansum(x)

42.0