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Vectorized Run-Length Encoding
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| import numpy as np | |
| def encode(v): | |
| changes = np.flatnonzero(np.diff(v)) + 1 | |
| values = np.r_[v[0], v[changes]] | |
| runlengths = np.diff(np.r_[0, changes, len(v)]) | |
| return runlengths, values | |
| def decode(runlengths, values): | |
| return np.repeat(values, runlengths) | |
| def calc_message_length(runlengths, values=None): | |
| return 8*runlengths.nbytes \ | |
| + (8*values.nbytes if values is not None else len(runlengths)) |
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| import numpy as np | |
| import rle | |
| def test_run_length(): | |
| M = np.array([[4, 0, 0, 1, 0, 0], | |
| [0, 0, 2, 2, 2, 4]]) | |
| runlengths, values = rle.encode(M.flatten()) | |
| M_decoded = rle.decode(runlengths, values).reshape(M.shape) | |
| np.testing.assert_equal(values, [4, 0, 1, 0, 2, 4]) | |
| np.testing.assert_equal(runlengths, [1, 2, 1, 4, 3, 1]) | |
| np.testing.assert_equal(M_decoded, M) | |
| assert runlengths.sum() == 12 | |
| def test_calc_message_length(): | |
| M = np.array([[4, 0, 0, 1, 0, 0], | |
| [0, 0, 2, 2, 2, 4]]) | |
| v = np.array([0, 0, 1, 0, 0, 0, 1]) | |
| runlengths, values = rle.encode(M.flatten()) | |
| assert rle.calc_message_length( | |
| runlengths.astype('uint8'), values.astype('uint16')) == (8 + 16)*6 | |
| assert rle.calc_message_length( | |
| runlengths.astype('int32'), values.astype('int64')) == (32 + 64)*6 | |
| runlengths = rle.encode_binary(v) | |
| assert rle.calc_message_length(runlengths.astype('int16')) == 16*4 + 4 |
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