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| author | Jarrod Millman <millman@berkeley.edu> | 2008-02-08 10:54:01 +0000 |
|---|---|---|
| committer | Jarrod Millman <millman@berkeley.edu> | 2008-02-08 10:54:01 +0000 |
| commit | c66da19ab8bd6ad7f035b77026bbd703eab199d4 (patch) | |
| tree | 55136b4e38d5991dbd68d4e0984c645f11cefce7 /numpy/core/defmatrix.py | |
| parent | 0b7800b455b3aaf50cb83a224f283e72f1dea951 (diff) | |
| download | numpy-c66da19ab8bd6ad7f035b77026bbd703eab199d4.tar.gz | |
ran reindent
Diffstat (limited to 'numpy/core/defmatrix.py')
| -rw-r--r-- | numpy/core/defmatrix.py | 16 |
1 files changed, 8 insertions, 8 deletions
diff --git a/numpy/core/defmatrix.py b/numpy/core/defmatrix.py index 7e1cacfce..c3f57efdf 100644 --- a/numpy/core/defmatrix.py +++ b/numpy/core/defmatrix.py @@ -51,16 +51,16 @@ def asmatrix(data, dtype=None): class matrix(N.ndarray): """mat = matrix(data, dtype=None, copy=True) - Returns a matrix from an array-like object, or a string of + Returns a matrix from an array-like object, or a string of data. A matrix is a specialized 2-d array that retains it's 2-d nature through operations and where '*' means matrix - multiplication and '**' means matrix power. + multiplication and '**' means matrix power. Parameters ---------- data : array-like or string - If data is a string, then interpret the string as a matrix - with commas or spaces separating columns and semicolons + If data is a string, then interpret the string as a matrix + with commas or spaces separating columns and semicolons separating rows. If data is array-like than convert the array to a matrix. dtype : data-type @@ -273,7 +273,7 @@ class matrix(N.ndarray): the flattened array by default, otherwise over the specified axis. Parameters - ---------- + ---------- axis : integer Axis along which the means are computed. The default is to compute the standard deviation of the flattened array. @@ -289,7 +289,7 @@ class matrix(N.ndarray): cast if necessary. Returns - ------- + ------- mean : The return type varies, see above. A new array holding the result is returned unless out is specified, in which case a reference to out is returned. @@ -342,7 +342,7 @@ class matrix(N.ndarray): mean : average Notes - ----- + ----- The standard deviation is the square root of the average of the squared deviations from the mean, i.e. var = sqrt(mean((x - x.mean())**2)). The computed standard @@ -362,7 +362,7 @@ class matrix(N.ndarray): ---------- axis : integer Axis along which the variance is computed. The default is to - compute the variance of the flattened array. + compute the variance of the flattened array. dtype : data-type Type to use in computing the variance. For arrays of integer type the default is float32, for arrays of float types it is |