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# Copyright 2017, Google Inc. |
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# All rights reserved. |
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# |
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# Redistribution and use in source and binary forms, with or without |
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# modification, are permitted provided that the following conditions are |
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# met: |
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# |
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# * Redistributions of source code must retain the above copyright |
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# notice, this list of conditions and the following disclaimer. |
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# * Redistributions in binary form must reproduce the above |
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# copyright notice, this list of conditions and the following disclaimer |
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# in the documentation and/or other materials provided with the |
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# distribution. |
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# * Neither the name of Google Inc. nor the names of its |
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# contributors may be used to endorse or promote products derived from |
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# this software without specific prior written permission. |
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# |
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS |
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# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT |
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# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR |
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# A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT |
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# OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, |
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# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT |
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# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, |
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# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY |
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# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT |
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# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE |
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# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
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|
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from scipy import stats |
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new=[66034560.0, 126765693.0, 99074674.0, 98588433.0, 96731372.0, 110179725.0, 103802110.0, 101139800.0, 102357205.0, 99016353.0, 98840824.0, 99585632.0, 98791720.0, 96171521.0, 95327098.0, 95629704.0, 98209772.0, 99779411.0, 100182488.0, 98354192.0, 99644781.0, 98546709.0, 99019176.0, 99543014.0, 99077269.0, 98046601.0, 99319039.0, 98542572.0, 98886614.0, 72560968.0] |
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old=[60423464.0, 71249570.0, 73213089.0, 73200055.0, 72911768.0, 72347798.0, 72494672.0, 72756976.0, 72116565.0, 71541342.0, 73442538.0, 74817383.0, 73007780.0, 72499062.0, 72404945.0, 71843504.0, 73245405.0, 72778304.0, 74004519.0, 73694464.0, 72919931.0, 72955481.0, 71583857.0, 71350467.0, 71836817.0, 70064115.0, 70355345.0, 72516202.0, 71716777.0, 71532266.0] |
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_THRESHOLD = 0.01 |
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def scale(a, mul): |
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return [x*mul for x in a] |
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def cmp(a, b): |
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return stats.mannwhitneyu(a, b, True, 'two-sided') |
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def speedup(new, old): |
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s0, p0 = cmp(new, old) |
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print s0, p0 |
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if s0 == 0: return 0 |
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if p0 >= _THRESHOLD: return 0 |
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if s0 < 0: |
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pass |
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else: |
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pct = 1 |
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while True: |
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sp, pp = cmp(new, scale(old, 1 + pct / 100.0)) |
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if sp <= 0: break |
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if pp >= _THRESHOLD: break |
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pct += 1 |
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return pct - 1 |
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|
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print speedup(new, old) |
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