diff options
Diffstat (limited to 'numpy/lib')
| -rw-r--r-- | numpy/lib/shape_base.py | 26 |
1 files changed, 11 insertions, 15 deletions
diff --git a/numpy/lib/shape_base.py b/numpy/lib/shape_base.py index a8977bd4c..83e39f9f5 100644 --- a/numpy/lib/shape_base.py +++ b/numpy/lib/shape_base.py @@ -354,25 +354,26 @@ def dstack(tup): """ Stack arrays in sequence depth wise (along third axis). - Takes a sequence of arrays and stack them along the third axis - to make a single array. Rebuilds arrays divided by `dsplit`. - This is a simple way to stack 2D arrays (images) into a single - 3D array for processing. + This is equivalent to concatenation along the third axis after 2-D arrays + of shape `(M,N)` have been reshaped to `(M,N,1)` and 1-D arrays of shape + `(N,)` have been reshaped to `(1,N,1)`. Rebuilds arrays divided by + `dsplit`. - This function continues to be supported for backward compatibility, but - you should prefer ``np.concatenate`` or ``np.stack``. The ``np.stack`` - function was added in NumPy 1.10. + This function makes most sense for arrays with up to 3 dimensions. For + instance, for pixel-data with a height (first axis), width (second axis), + and r/g/b channels (third axis). The functions `concatenate`, `stack` and + `block` provide more general stacking and concatenation operations. Parameters ---------- tup : sequence of arrays - Arrays to stack. All of them must have the same shape along all - but the third axis. + The arrays must have the same shape along all but the third axis. + 1-D or 2-D arrays must have the same shape. Returns ------- stacked : ndarray - The array formed by stacking the given arrays. + The array formed by stacking the given arrays, will be at least 3-D. See Also -------- @@ -382,11 +383,6 @@ def dstack(tup): concatenate : Join a sequence of arrays along an existing axis. dsplit : Split array along third axis. - Notes - ----- - Equivalent to ``np.concatenate(tup, axis=2)`` if `tup` contains arrays that - are at least 3-dimensional. - Examples -------- >>> a = np.array((1,2,3)) |