numpy.fmin(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'fmin'>
Elementwise minimum of array elements.
Compare two arrays and returns a new array containing the elementwise minima. If one of the elements being compared is a NaN, then the nonnan element is returned. If both elements are NaNs then the first is returned. The latter distinction is important for complex NaNs, which are defined as at least one of the real or imaginary parts being a NaN. The net effect is that NaNs are ignored when possible.
Parameters: 


Returns: 

See also
New in version 1.3.0.
The fmin is equivalent to np.where(x1 <= x2, x1, x2)
when neither x1 nor x2 are NaNs, but it is faster and does proper broadcasting.
>>> np.fmin([2, 3, 4], [1, 5, 2]) array([1, 3, 2])
>>> np.fmin(np.eye(2), [0.5, 2]) array([[ 0.5, 0. ], [ 0. , 1. ]])
>>> np.fmin([np.nan, 0, np.nan],[0, np.nan, np.nan]) array([ 0., 0., nan])
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https://docs.scipy.org/doc/numpy1.17.0/reference/generated/numpy.fmin.html