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Ankit Agrawal
39 lines
1.2 KiB
Python
39 lines
1.2 KiB
Python
def sum_blocks(array, factors):
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"""Sums the elements in blocks of integer factors and pads the original
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array with zeroes if the dimensions are not perfectly divisible by factors.
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This function is different from resize and rescale in transform._warps in
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the sense that they use interpolation to upsample or downsample on a 2D
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array, while this function performs only dawnsampling but on any
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n-dimensional array and returns the sum of elements in a block of size
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factors in the original array.
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Parameters
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----------
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array : ndarray
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Input n-dimensional array.
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factors: tuple
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Tuple containing integer values representing block length along each
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axis.
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Returns
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-------
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array : ndarray
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Downsampled array with same number of dimensions as that of input
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array.
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Example
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-------
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>>> a = np.arange(15).reshape(3, 5)
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>>> a
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array([[ 0, 1, 2, 3, 4],
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[ 5, 6, 7, 8, 9],
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[10, 11, 12, 13, 14]])
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>>> sum_blocks(a, (2,3))
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array([[21, 24],
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[33, 27]])
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"""
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from ..transform._warps import _downsample
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return _downsample(array, factors)
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