grid_from_bounding_box

gwcs.wcstools.grid_from_bounding_box(bounding_box, step=1, center=True, selector=None)

Create a grid of input points from the WCS bounding_box.

Note: If bbox is a tuple describing the range of an axis in bounding_box,

x.5 is considered part of the next pixel in bbox[0] and part of the previous pixel in bbox[1]. In this way if bbox describes the edges of an image the indexing includes only pixels within the image.

Parameters:

bounding_boxtuple | ~astropy.modeling.bounding_box.ModelBoundingBox | ~astropy.modeling.bounding_box.CompoundBoundingBox

The bounding_box of a WCS object, bounding_box.

stepscalar or tuple

Step size for grid in each dimension. Scalar applies to all dimensions.

centerbool

selectortuple | None

If selector is set then it must be a selector tuple and bounding_box must be a CompoundBoundingBox.

The bounding_box is in order of X, Y [, Z] and the output will be in the

same order.

Returns:

x, y [, z]: ndarray

Grid of points.

Examples

>>> bb = ((-1, 2.9), (6, 7.5))
>>> grid_from_bounding_box(bb, step=(1, .5), center=False)
array([[[-1. ,  0. ,  1. ,  2. ,  3. ],
        [-1. ,  0. ,  1. ,  2. ,  3. ],
        [-1. ,  0. ,  1. ,  2. ,  3. ],
        [-1. ,  0. ,  1. ,  2. ,  3. ]],
       [[ 6. ,  6. ,  6. ,  6. ,  6. ],
        [ 6.5,  6.5,  6.5,  6.5,  6.5],
        [ 7. ,  7. ,  7. ,  7. ,  7. ],
        [ 7.5,  7.5,  7.5,  7.5,  7.5]]])

>>> bb = ((-1, 2.9), (6, 7.5))
>>> grid_from_bounding_box(bb)
array([[[-1.,  0.,  1.,  2.,  3.],
        [-1.,  0.,  1.,  2.,  3.]],
       [[ 6.,  6.,  6.,  6.,  6.],
        [ 7.,  7.,  7.,  7.,  7.]]])