openpiv.pyprocess.moving_window_array

static pyprocess.moving_window_array(array, window_size, overlap)

This is a nice numpy trick. The concept of numpy strides should be clear to understand this code.

Basically, we have a 2d array and we want to perform cross-correlation over the interrogation windows. An approach could be to loop over the array but loops are expensive in python. So we create from the array a new array with three dimension, of size (n_windows, window_size, window_size), in which each slice, (along the first axis) is an interrogation window.

To understand what i mean run this code in ipython:

>>> a = np.arange(100, dtype=np.int).reshape(10,10)

>>> a
     array([[ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9],
            [10, 11, 12, 13, 14, 15, 16, 17, 18, 19],
            [20, 21, 22, 23, 24, 25, 26, 27, 28, 29],
            [30, 31, 32, 33, 34, 35, 36, 37, 38, 39],
            [40, 41, 42, 43, 44, 45, 46, 47, 48, 49],
            [50, 51, 52, 53, 54, 55, 56, 57, 58, 59],
            [60, 61, 62, 63, 64, 65, 66, 67, 68, 69],
            [70, 71, 72, 73, 74, 75, 76, 77, 78, 79],
            [80, 81, 82, 83, 84, 85, 86, 87, 88, 89],
            [90, 91, 92, 93, 94, 95, 96, 97, 98, 99]])

>>> b = moving_window_array( a, 5, 1 )

>>>  moving_window_array(a,6,2)

array([[[ 0, 1, 2, 3, 4, 5],

[10, 11, 12, 13, 14, 15], [20, 21, 22, 23, 24, 25], [30, 31, 32, 33, 34, 35], [40, 41, 42, 43, 44, 45], [50, 51, 52, 53, 54, 55]],

[[ 4, 5, 6, 7, 8, 9],

[14, 15, 16, 17, 18, 19], [24, 25, 26, 27, 28, 29], [34, 35, 36, 37, 38, 39], [44, 45, 46, 47, 48, 49], [54, 55, 56, 57, 58, 59]],

[[40, 41, 42, 43, 44, 45],

[50, 51, 52, 53, 54, 55], [60, 61, 62, 63, 64, 65], [70, 71, 72, 73, 74, 75], [80, 81, 82, 83, 84, 85], [90, 91, 92, 93, 94, 95]],

[[44, 45, 46, 47, 48, 49],

[54, 55, 56, 57, 58, 59], [64, 65, 66, 67, 68, 69], [74, 75, 76, 77, 78, 79], [84, 85, 86, 87, 88, 89], [94, 95, 96, 97, 98, 99]]])