scipy.stats.hmean¶

scipy.stats.hmean(a, axis=0, dtype=None)[source]¶

Calculate the harmonic mean along the specified axis.

That is: n / (1/x1 + 1/x2 + … + 1/xn)

Parameters:

Parameters:	a : array_like Input array, masked array or object that can be converted to an array. axis : int or None, optional Axis along which the harmonic mean is computed. Default is 0. If None, compute over the whole array a. dtype : dtype, optional Type of the returned array and of the accumulator in which the elements are summed. If dtype is not specified, it defaults to the dtype of a, unless a has an integer dtype with a precision less than that of the default platform integer. In that case, the default platform integer is used.
Returns:	hmean : ndarray see dtype parameter above

a : array_like

Input array, masked array or object that can be converted to an array.

axis : int or None, optional

Axis along which the harmonic mean is computed. Default is 0. If None, compute over the whole array a.

dtype : dtype, optional

Type of the returned array and of the accumulator in which the elements are summed. If dtype is not specified, it defaults to the dtype of a, unless a has an integer dtype with a precision less than that of the default platform integer. In that case, the default platform integer is used.

Returns:

hmean : ndarray

see dtype parameter above

See also

numpy.mean: Arithmetic average
numpy.average: Weighted average
gmean: Geometric mean

Notes

The harmonic mean is computed over a single dimension of the input array, axis=0 by default, or all values in the array if axis=None. float64 intermediate and return values are used for integer inputs.

Use masked arrays to ignore any non-finite values in the input or that arise in the calculations such as Not a Number and infinity.

Examples

>>> from scipy.stats import hmean
>>> hmean([1, 4])
1.6000000000000001
>>> hmean([1, 2, 3, 4, 5, 6, 7])
2.6997245179063363