scipy.special.expm1#
- scipy.special.expm1(x, out=None) = <ufunc 'expm1'>#
- Compute - exp(x) - 1.- When x is near zero, - exp(x)is near 1, so the numerical calculation of- exp(x) - 1can suffer from catastrophic loss of precision.- expm1(x)is implemented to avoid the loss of precision that occurs when x is near zero.- Parameters:
- xarray_like
- x must contain real numbers. 
- outndarray, optional
- Optional output array for the function values 
 
- Returns:
- scalar or ndarray
- exp(x) - 1computed element-wise.
 
 - Examples - >>> import numpy as np >>> from scipy.special import expm1 - >>> expm1(1.0) 1.7182818284590451 >>> expm1([-0.2, -0.1, 0, 0.1, 0.2]) array([-0.18126925, -0.09516258, 0. , 0.10517092, 0.22140276]) - The exact value of - exp(7.5e-13) - 1is:- 7.5000000000028125000000007031250000001318...*10**-13. - Here is what - expm1(7.5e-13)gives:- >>> expm1(7.5e-13) 7.5000000000028135e-13 - Compare that to - exp(7.5e-13) - 1, where the subtraction results in a “catastrophic” loss of precision:- >>> np.exp(7.5e-13) - 1 7.5006667543675576e-13