# 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) - 1` can 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) - 1` computed 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) - 1` is:

```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
```