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| author | Jarrod Millman <millman@berkeley.edu> | 2008-04-20 11:49:35 +0000 |
|---|---|---|
| committer | Jarrod Millman <millman@berkeley.edu> | 2008-04-20 11:49:35 +0000 |
| commit | 8c663313de36e860bbfea0909de181d330bfdfc7 (patch) | |
| tree | a7b5f3585d2b8a2d8307bfb03dd0e449fa732860 /numpy/add_newdocs.py | |
| parent | cb7de97f089b67eaacf37ddbebcfb91c292c0ef4 (diff) | |
| download | numpy-8c663313de36e860bbfea0909de181d330bfdfc7.tar.gz | |
ran reindent in preparation for the 1.1 release
Diffstat (limited to 'numpy/add_newdocs.py')
| -rw-r--r-- | numpy/add_newdocs.py | 16 |
1 files changed, 8 insertions, 8 deletions
diff --git a/numpy/add_newdocs.py b/numpy/add_newdocs.py index be2b86f63..c61ffcab8 100644 --- a/numpy/add_newdocs.py +++ b/numpy/add_newdocs.py @@ -1314,10 +1314,10 @@ add_newdoc('numpy.core.multiarray', 'ndarray', ('std', Notes ----- The standard deviation is the square root of the average of the squared - deviations from the mean, i.e. var = sqrt(mean(abs(x - x.mean())**2)). - The computed standard deviation is computed by dividing by the number of - elements, N-ddof. The option ddof defaults to zero, that is, a - biased estimate. Note that for complex numbers std takes the absolute + deviations from the mean, i.e. var = sqrt(mean(abs(x - x.mean())**2)). + The computed standard deviation is computed by dividing by the number of + elements, N-ddof. The option ddof defaults to zero, that is, a + biased estimate. Note that for complex numbers std takes the absolute value before squaring, so that the result is always real and nonnegative. """)) @@ -1503,10 +1503,10 @@ add_newdoc('numpy.core.multiarray', 'ndarray', ('var', Notes ----- The variance is the average of the squared deviations from the mean, - i.e. var = mean(abs(x - x.mean())**2). The mean is computed by - dividing by N-ddof, where N is the number of elements. The argument - ddof defaults to zero; for an unbiased estimate supply ddof=1. Note - that for complex numbers the absolute value is taken before squaring, + i.e. var = mean(abs(x - x.mean())**2). The mean is computed by + dividing by N-ddof, where N is the number of elements. The argument + ddof defaults to zero; for an unbiased estimate supply ddof=1. Note + that for complex numbers the absolute value is taken before squaring, so that the result is always real and nonnegative. """)) |