On 4/23/07, Keith Goodman firstname.lastname@example.org wrote:
On 4/23/07, Christopher Barker Chris.Barker@noaa.gov wrote:
reshape(...) a.reshape(d1, d2, ..., dn, order='c')
Return a new array from this one. The new array must have the same number of elements as self. Also always returns a view or raises a ValueError if that is impossible.;
Here's a better doc string that explains "This will be a new view object if possible; otherwise, it will return a copy."
Type: function Base Class: <type 'function'> String Form: <function reshape at 0xb78894c4> Namespace: Interactive File: /usr/local/lib/python2.4/site-packages/numpy/core/fromnumeric.py Definition: numpy.reshape(a, newshape, order='C') Docstring: Return an array that uses the data of the given array, but with a new shape.
:Parameters: - `a` : array - `newshape` : shape tuple or int The new shape should be compatible with the original shape. If an integer, then the result will be a 1D array of that length. - `order` : 'C' or 'FORTRAN', optional (default='C') Whether the array data should be viewed as in C (row-major) order
or FORTRAN (column-major) order.
:Returns: - `reshaped_array` : array This will be a new view object if possible; otherwise, it will
return a copy.
:See also: numpy.ndarray.reshape() is the equivalent method.
I think that it should raise an error, or warn, if it needs to make a copy, but that isn't the tradition. Reshape does raise an error if the product of the dimensions isn't the same for both the original and the reshaped array.