This is short-hand for np.r_['-1,2,0', index expression] , which is useful because of its common occurrence. In particular, arrays will be stacked along their last axis after being upgraded to at least 2-D with 1's post-pended to the shape (column vectors made out of 1-D arrays).

Translates slice objects to concatenation along the second axis.

See Also

column_stack

Stack 1-D arrays as columns into a 2-D array.

r_

For more detailed documentation.

Examples

>>> np.c_[np.array([1,2,3]), np.array([4,5,6])]
array([[1, 4],
       [2, 5],
       [3, 6]])

>>> np.c_[np.array([[1,2,3]]), 0, 0, np.array([[4,5,6]])]
array([[1, 2, 3, ..., 4, 5, 6]])

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

scipy.spatial._kdtree.KDTree.query_ball_point scipy.interpolate._cubic.CubicSpline scipy.spatial._kdtree.KDTree.query scipy.spatial._qhull.Delaunay scipy.interpolate._bsplines.make_interp_spline

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them

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GitHub : /numpy/lib/index_tricks.py#531
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