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| author | Travis Oliphant <oliphant@enthought.com> | 2006-08-29 17:56:21 +0000 |
|---|---|---|
| committer | Travis Oliphant <oliphant@enthought.com> | 2006-08-29 17:56:21 +0000 |
| commit | 63326185c04be2795a7a33028d427e9c8c31c900 (patch) | |
| tree | 62fb5b9f5f7b6e518346fa0893e408fa24755021 /numpy/oldnumeric/random_array.py | |
| parent | 064c8eb43637e920f6019215b00ef1593d74b0c1 (diff) | |
| download | numpy-63326185c04be2795a7a33028d427e9c8c31c900.tar.gz | |
Clean-up some un-needed default axes. Fix default axes of ma.sum and ma.product
Diffstat (limited to 'numpy/oldnumeric/random_array.py')
| -rw-r--r-- | numpy/oldnumeric/random_array.py | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/numpy/oldnumeric/random_array.py b/numpy/oldnumeric/random_array.py index 550af720c..e8d386ce4 100644 --- a/numpy/oldnumeric/random_array.py +++ b/numpy/oldnumeric/random_array.py @@ -166,7 +166,7 @@ def multinomial(trials, probs, shape=[]): trials is the number of trials in each multinomial distribution. probs is a one dimensional array. There are len(prob)+1 events. prob[i] is the probability of the i-th event, 0<=i<len(prob). - The probability of event len(prob) is 1.-Numeric.sum(prob,axis=0). + The probability of event len(prob) is 1.-Numeric.sum(prob). The first form returns a single 1-D array containing one multinomially distributed vector. |