scipy.special.exp10#

scipy.special.exp10(x, out=None) = <ufunc 'exp10'>#

Compute 10**x element-wise.

Parameters:

xarray_like: x must contain real numbers.
outndarray, optional: Optional output array for the function values

Returns:

scalar or ndarray: 10**x, computed element-wise.

Notes

exp10 has experimental support for Python Array API Standard compatible backends in addition to NumPy. Please consider testing these features by setting an environment variable SCIPY_ARRAY_API=1 and providing CuPy, PyTorch, JAX, or Dask arrays as array arguments. The following combinations of backend and device (or other capability) are supported.

Library	CPU	GPU
NumPy	✅	n/a
CuPy	n/a	✅
PyTorch	✅	⛔
JAX	⚠️ no JIT	⛔
Dask	✅	n/a

See Support for the array API standard for more information.

Examples

>>> import numpy as np
>>> from scipy.special import exp10

>>> exp10(3)
1000.0
>>> x = np.array([[-1, -0.5, 0], [0.5, 1, 1.5]])
>>> exp10(x)
array([[  0.1       ,   0.31622777,   1.        ],
       [  3.16227766,  10.        ,  31.6227766 ]])