Functions like numpy.random.uniform() return floating point values between a two bounds, including the first bound but excluding the top one. That is, numpy.random.uniform(0,1) may yield 0 but will never result in 1.
I'm taking such numbers and processing them with a function that sometimes returns results outside of the range. I can use numpy.clip() to chop values outside of the range back to 0-1, but unfortunately that limit is inclusive of the top number.
How do I specify "the number infinitesimally smaller than 1" in python?
Well, if you're using numpy, you can simply use numpy.nextafter:
>>> import numpy
>>> numpy.nextafter(1, 0)
0.99999999999999989
Note that (at least for me):
>>> import sys
>>> 1-sys.float_info.epsilon
0.9999999999999998
>>> numpy.nextafter(1, 0) - (1-sys.float_info.epsilon)
1.1102230246251565e-16
>>> numpy.nextafter(1, 0) > (1-sys.float_info.epsilon)
True
Incidentally, to second @Robert Kern's point that sometimes random.uniform will include the upper bound for some inputs other than (0, 1):
>>> import random, numpy
>>> numpy.nextafter(0,1)
4.9406564584124654e-324
>>> random.uniform(0, numpy.nextafter(0,1))
0.0
>>> random.uniform(0, numpy.nextafter(0,1))
0.0
>>> random.uniform(0, numpy.nextafter(0,1))
4.9406564584124654e-324
[I share the general sense that there is probably a better way to approach this problem.]