regular_grid(ar_shape, n_points)

The returned points (as slices) should be as close to cubically-spaced as possible. Essentially, the points are spaced by the Nth root of the input array size, where N is the number of dimensions. However, if an array dimension cannot fit a full step size, it is "discarded", and the computation is done for only the remaining dimensions.

Parameters

ar_shape : array-like of ints

The shape of the space embedding the grid. len(ar_shape) is the number of dimensions.

n_points : int

The (approximate) number of points to embed in the space.

Returns

slices : tuple of slice objects

A slice along each dimension of :None:None:`ar_shape`, such that the intersection of all the slices give the coordinates of regularly spaced points.

versionchanged

In scikit-image 0.14.1 and 0.15, the return type was changed from a list to a tuple to ensure :None:None:`compatibility with Numpy 1.15` and higher. If your code requires the returned result to be a list, you may convert the output of this function to a list with:

>>> result = list(regular_grid(ar_shape=(3, 20, 40), n_points=8))

            <Unimplemented 'target' '.. _compatibility with NumPy 1.15: https://github.com/numpy/numpy/blob/master/doc/release/1.15.0-notes.rst#deprecations'>
           

Find :None:None:`n_points` regularly spaced along :None:None:`ar_shape`.

Examples

This example is valid syntax, but we were not able to check execution

>>> ar = np.zeros((20, 40))
... g = regular_grid(ar.shape, 8)
... g
(slice(5, None, 10), slice(5, None, 10))

This example is valid syntax, but we were not able to check execution

>>> ar[g] = 1
... ar.sum()
8.0

This example is valid syntax, but we were not able to check execution

>>> ar = np.zeros((20, 40))
... g = regular_grid(ar.shape, 32)
... g
(slice(2, None, 5), slice(2, None, 5))

This example is valid syntax, but we were not able to check execution

>>> ar[g] = 1
... ar.sum()
32.0

This example is valid syntax, but we were not able to check execution

>>> ar = np.zeros((3, 20, 40))
... g = regular_grid(ar.shape, 8)
... g
(slice(1, None, 3), slice(5, None, 10), slice(5, None, 10))

This example is valid syntax, but we were not able to check execution

>>> ar[g] = 1
... ar.sum()
8.0

See :

Back References

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

skimage.util._regular_grid.regular_grid

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