diff options
Diffstat (limited to 'numpy/lib/function_base.py')
| -rw-r--r-- | numpy/lib/function_base.py | 15 |
1 files changed, 10 insertions, 5 deletions
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py index 253ce9d74..03024db3c 100644 --- a/numpy/lib/function_base.py +++ b/numpy/lib/function_base.py @@ -308,11 +308,14 @@ def average(a, axis=None, weights=None, returned=False): Return the average along the specified axis. When `returned` is `True`, return a tuple with the average as the first element and the sum of the weights as the second element. `sum_of_weights` is of the - same type as `average`. The result type is the type of lowest precision - capable of representing values of both `a` and `weights` or 'float64' - if that type would be integral. Otherwise, if `a` is non integral, - result will be a `dtype` which is capable of representing both - `a.dtype` and `wgt.dtype` + same type as `average`. The result dtype follows a genereal pattern. + If `weights` is None, the result dtype will be that of `a` , or `float64` + if `a` is integral. Otherwise, if `weights` is not None and `a` is non + integral, the result type will be the type of lowest precision capable of + representing values of both `a` and `weights` but if `a` happens to be + integral, the previous rules still applies but the result dtype would + at least be `float64`. + Raises ------ ZeroDivisionError @@ -348,9 +351,11 @@ def average(a, axis=None, weights=None, returned=False): >>> np.average(data, axis=1, weights=[1./4, 3./4]) array([ 0.75, 2.75, 4.75]) >>> np.average(data, weights=[1./4, 3./4]) + Traceback (most recent call last): ... TypeError: Axis must be specified when shapes of a and weights differ. + >>> a = np.ones(5, dtype=np.float128) >>> w = np.ones(5, dtype=np.complex64) >>> avg = np.average(a, weights=w) |