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| author | Matti Picus <matti.picus@gmail.com> | 2019-08-27 11:19:34 +0300 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2019-08-27 11:19:34 +0300 |
| commit | 17ff82a7f3ca49717128b89d1a5560f4545fda0f (patch) | |
| tree | 1605404fee965445a644ae1ceeebbe0fa055ac0a /numpy | |
| parent | 123db90bfc977165577347beaaa2849a6747593b (diff) | |
| parent | ad49532a21cc007d4a1f0ba42f2a25db013c6505 (diff) | |
| download | numpy-17ff82a7f3ca49717128b89d1a5560f4545fda0f.tar.gz | |
Merge pull request #14365 from WarrenWeckesser/doc-average
DOC: lib: Add more explanation of the weighted average calculation.
Diffstat (limited to 'numpy')
| -rw-r--r-- | numpy/lib/function_base.py | 7 | ||||
| -rw-r--r-- | numpy/ma/extras.py | 7 |
2 files changed, 10 insertions, 4 deletions
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py index 9d380e67d..21532838b 100644 --- a/numpy/lib/function_base.py +++ b/numpy/lib/function_base.py @@ -316,14 +316,17 @@ def average(a, axis=None, weights=None, returned=False): The weights array can either be 1-D (in which case its length must be the size of `a` along the given axis) or of the same shape as `a`. If `weights=None`, then all data in `a` are assumed to have a - weight equal to one. + weight equal to one. The 1-D calculation is:: + + avg = sum(a * weights) / sum(weights) + + The only constraint on `weights` is that `sum(weights)` must not be 0. returned : bool, optional Default is `False`. If `True`, the tuple (`average`, `sum_of_weights`) is returned, otherwise only the average is returned. If `weights=None`, `sum_of_weights` is equivalent to the number of elements over which the average is taken. - Returns ------- retval, [sum_of_weights] : array_type or double diff --git a/numpy/ma/extras.py b/numpy/ma/extras.py index 639b3dd1f..de1aa3af8 100644 --- a/numpy/ma/extras.py +++ b/numpy/ma/extras.py @@ -549,8 +549,11 @@ def average(a, axis=None, weights=None, returned=False): The weights array can either be 1-D (in which case its length must be the size of `a` along the given axis) or of the same shape as `a`. If ``weights=None``, then all data in `a` are assumed to have a - weight equal to one. If `weights` is complex, the imaginary parts - are ignored. + weight equal to one. The 1-D calculation is:: + + avg = sum(a * weights) / sum(weights) + + The only constraint on `weights` is that `sum(weights)` must not be 0. returned : bool, optional Flag indicating whether a tuple ``(result, sum of weights)`` should be returned as output (True), or just the result (False). |