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python Programming Glossary: rolling_windowEfficient Numpy 2D array construction from 1D array http://stackoverflow.com/questions/4923617/efficient-numpy-2d-array-construction-from-1d-array Rigtorp's rolling window function import numpy as np def rolling_window a window Make an ndarray with a rolling window of the last dimension.. dimension of size w. Examples x np.arange 10 .reshape 2 5 rolling_window x 3 array 0 1 2 1 2 3 2 3 4 5 6 7 6 7 8 7 8 9 Calculate rolling.. 7 8 7 8 9 Calculate rolling mean of last dimension np.mean rolling_window x 3 1 array 1. 2. 3. 6. 7. 8. if window 1 raise ValueError `window`..
Using strides for an efficient moving average filter http://stackoverflow.com/questions/4936620/using-strides-for-an-efficient-moving-average-filter At any rate here's how you do it import numpy as np def rolling_window_lastaxis a window Directly taken from Erik Rigtorp's post to.. a shape shape strides strides def rolling_window a window if not hasattr window '__iter__' return rolling_window_lastaxis.. a window if not hasattr window '__iter__' return rolling_window_lastaxis a window for i win in enumerate window if win 1 a a.swapaxes..
Rolling window for 1D arrays in Numpy? http://stackoverflow.com/questions/6811183/rolling-window-for-1d-arrays-in-numpy code but apply your function to the result. i.e. numpy.std rolling_window observations n 1 where you have from the blog def rolling_window.. observations n 1 where you have from the blog def rolling_window a window shape a.shape 1 a.shape 1 window 1 window strides a.strides..
Rolling or sliding window iterator in Python http://stackoverflow.com/questions/6822725/rolling-or-sliding-window-iterator-in-python less verbose or more efficient method for doing this def rolling_window seq window_size it iter seq win it.next for cnt in xrange window_size.. 1 win 1 win 1 e yield win if __name__ __main__ for w in rolling_window xrange 6 3 print w Example output 0 1 2 1 2 3 2 3 4 3 4 5 ..
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