Floating point instabilities in numpy1
np.finfo(np.float64).max
# 1.7976931348623157e+308, largest positive number
np.finfo(np.float64).tiny
# 2.2250738585072014e-308, smallest positive number at full precision
np.finfo(np.float64).smallest_subnormal
# 5e-324, smallest positive number
When we use these extremes, we get instabilities:
np.finfo(np.float64).max * 2
# inf, overflow error
np.inf - np.inf
# nan, not a number error
np.finfo(np.float64).smallest_subnormal / 2
# 0.0, underflow error